The Hunchback of Notre Dame
by Victor Hugo
Book Fourth, Chapter 2
Additional Information
- Year Published: 1831
- Language: English
- Country of Origin: France
- Source: Hapsgood, I., trans. (1831). The Hunchback of Notre Dame. New York: Carey, Lea, and Blanchard.
-
Readability:
- Flesch–Kincaid Level: 12.0
- Word Count: 2,007
- Genre: Romance
- Keywords: culture, fate, love, loyalty
- ✎ Cite This
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In fact, Claude Frollo was no common person.
He belonged to one of those middle–class families which were called indifferently, in the impertinent language of the last century, the high ~bourgeoise~ or the petty nobility. This family had inherited from the brothers Paclet the fief of Tirechappe, which was dependent upon the Bishop of Paris, and whose twenty–one houses had been in the thirteenth century the object of so many suits before the official. As possessor of this fief, Claude Frollo was one of the twenty–seven seigneurs keeping claim to a manor in fee in Paris and its suburbs; and for a long time, his name was to be seen inscribed in this quality, between the Hôtel de Tancarville, belonging to Master Fran ois Le Rez, and the college of Tours, in the records deposited at Saint Martin des Champs.
Claude Frollo had been destined from infancy, by his parents, to the ecclesiastical profession. He had been taught to read in Latin; he had been trained to keep his eyes on the ground and to speak low. While still a child, his father had cloistered him in the college of Torchi in the University. There it was that he had grown up, on the missal and the lexicon.
Moreover, he was a sad, grave, serious child, who studied ardently, and learned quickly; he never uttered a loud cry in recreation hour, mixed but little in the bacchanals of the Rue du Fouarre, did not know what it was to ~dare alapas et capillos laniare~, and had cut no figure in that revolt of 1463, which the annalists register gravely, under the title of "The sixth trouble of the University." He seldom rallied the poor students of Montaigu on the ~cappettes~ from which they derived their name, or the bursars of the college of Dormans on their shaved tonsure, and their surtout parti–colored of bluish–green, blue, and violet cloth, ~azurini coloris et bruni~, as says the charter of the Cardinal des Quatre–Couronnes.
On the other hand, he was assiduous at the great and the small schools of the Rue Saint Jean de Beauvais. The first pupil whom the Abbé de Saint Pierre de Val, at the moment of beginning his reading on canon law, always perceived, glued to a pillar of the school Saint–Vendregesile, opposite his rostrum, was Claude Frollo, armed with his horn ink–bottle, biting his pen, scribbling on his threadbare knee, and, in winter, blowing on his fingers. The first auditor whom Messire Miles d'Isliers, doctor in decretals, saw arrive every Monday morning, all breathless, at the opening of the gates of the school of the Chef–Saint–Denis, was Claude Frollo. Thus, at sixteen years of age, the young clerk might have held his own, in mystical theology, against a father of the church; in canonical theology, against a father of the councils; in scholastic theology, against a doctor of Sorbonne.
Theology conquered, he had plunged into decretals. From the "Master of Sentences," he had passed to the "Capitularies of Charlemagne;" and he had devoured in succession, in his appetite for science, decretals upon decretals, those of Theodore, Bishop of Hispalus; those of Bouchard, Bishop of Worms; those of Yves, Bishop of Chartres; next the decretal of Gratian, which succeeded the capitularies of Charlemagne; then the collection of Gregory IX.; then the Epistle of ~Superspecula~, of Honorius III. He rendered clear and familiar to himself that vast and tumultuous period of civil law and canon law in conflict and at strife with each other, in the chaos of the Middle Ages,—a period which Bishop Theodore opens in 618, and which Pope Gregory closes in 1227.
Decretals digested, he flung himself upon medicine, on the liberal arts. He studied the science of herbs, the science of unguents; he became an expert in fevers and in contusions, in sprains and abcesses. Jacques d' Espars would have received him as a physician; Richard Hellain, as a surgeon. He also passed through all the degrees of licentiate, master, and doctor of arts. He studied the languages, Latin, Greek, Hebrew, a triple sanctuary then very little frequented. His was a veritable fever for acquiring and hoarding, in the matter of science. At the age of eighteen, he had made his way through the four faculties; it seemed to the young man that life had but one sole object: learning.
It was towards this epoch, that the excessive heat of the summer of 1466 caused that grand outburst of the plague which carried off more than forty thousand souls in the vicomty of Paris, and among others, as Jean de Troyes states, "Master Arnoul, astrologer to the king, who was a very fine man, both wise and pleasant." The rumor spread in the University that the Rue Tirechappe was especially devastated by the malady. It was there that Claude's parents resided, in the midst of their fief. The young scholar rushed in great alarm to the paternal mansion. When he entered it, he found that both father and mother had died on the preceding day. A very young brother of his, who was in swaddling clothes, was still alive and crying abandoned in his cradle. This was all that remained to Claude of his family; the young man took the child under his arm and went off in a pensive mood. Up to that moment, he had lived only in science; he now began to live in life.
This catastrophe was a crisis in Claude's existence. Orphaned, the eldest, head of the family at the age of nineteen, he felt himself rudely recalled from the reveries of school to the realities of this world. Then, moved with pity, he was seized with passion and devotion towards that child, his brother; a sweet and strange thing was a human affection to him, who had hitherto loved his books alone.
This affection developed to a singular point; in a soul so new, it was like a first love. Separated since infancy from his parents, whom he had hardly known; cloistered and immured, as it were, in his books; eager above all things to study and to learn; exclusively attentive up to that time, to his intelligence which broadened in science, to his imagination, which expanded in letters,—the poor scholar had not yet had time to feel the place of his heart.
This young brother, without mother or father, this little child which had fallen abruptly from heaven into his arms, made a new man of him. He perceived that there was something else in the world besides the speculations of the Sorbonne, and the verses of Homer; that man needed affections; that life without tenderness and without love was only a set of dry, shrieking, and rending wheels. Only, he imagined, for he was at the age when illusions are as yet replaced only by illusions, that the affections of blood and family were the sole ones necessary, and that a little brother to love sufficed to fill an entire existence.
He threw himself, therefore, into the love for his little Jehan with the passion of a character already profound, ardent, concentrated; that poor frail creature, pretty, fair– haired, rosy, and curly,—that orphan with another orphan for his only support, touched him to the bottom of his heart; and grave thinker as he was, he set to meditating upon Jehan with an infinite compassion. He kept watch and ward over him as over something very fragile, and very worthy of care. He was more than a brother to the child; he became a mother to him.
Little Jehan had lost his mother while he was still at the breast; Claude gave him to a nurse. Besides the fief of Tirechappe, he had inherited from his father the fief of Moulin, which was a dependency of the square tower of Gentilly; it was a mill on a hill, near the château of Winchestre (Bic tre). There was a miller's wife there who was nursing a fine child; it was not far from the university, and Claude carried the little Jehan to her in his own arms.
From that time forth, feeling that he had a burden to bear, he took life very seriously. The thought of his little brother became not only his recreation, but the object of his studies. He resolved to consecrate himself entirely to a future for which he was responsible in the sight of God, and never to have any other wife, any other child than the happiness and fortune of his brother. Therefore, he attached himself more closely than ever to the clerical profession. His merits, his learning, his quality of immediate vassal of the Bishop of Paris, threw the doors of the church wide open to him. At the age of twenty, by special dispensation of the Holy See, he was a priest, and served as the youngest of the chaplains of Notre–Dame the altar which is called, because of the late mass which is said there, ~altare pigrorum~.
There, plunged more deeply than ever in his dear books, which he quitted only to run for an hour to the fief of Moulin, this mixture of learning and austerity, so rare at his age, had promptly acquired for him the respect and admiration of the monastery. From the cloister, his reputation as a learned man had passed to the people, among whom it had changed a little, a frequent occurrence at that time, into reputation as a sorcerer.
It was at the moment when he was returning, on Quasimodo day, from saying his mass at the Altar of the Lazy, which was by the side of the door leading to the nave on the right, near the image of the Virgin, that his attention had been attracted by the group of old women chattering around the bed for foundlings.
Then it was that he approached the unhappy little creature, which was so hated and so menaced. That distress, that deformity, that abandonment, the thought of his young brother, the idea which suddenly occurred to him, that if he were to die, his dear little Jehan might also be flung miserably on the plank for foundlings,—all this had gone to his heart simultaneously; a great pity had moved in him, and he had carried off the child.
When he removed the child from the sack, he found it greatly deformed, in very sooth.  Claude's compassion increased at the sight of this ugliness; and he made a vow in his heart to rear the child for the love of his brother, in order that, whatever might be the future faults of the little Jehan, he should have beside him that charity done for his sake. It was a sort of investment of good works, which he was effecting in the name of his young brother; it was a stock of good works which he wished to amass in advance for him, in case the little rogue should some day find himself short of that coin, the only sort which is received at the toll–bar of paradise.
He baptized his adopted child, and gave him the name of Quasimodo, either because he desired thereby to mark the day, when he had found him, or because he wished to designate by that name to what a degree the poor little creature was incomplete, and hardly sketched out. In fact, Quasimodo, blind, hunchbacked, knock–kneed, was only an "almost."


Program Version:EnergyPlus, Version 9.1.0-08d2e308bb, YMD=2021.07.16 12:25
Tabular Output Report in Format: HTML
Building: Ref Bldg Medium Office New2004_v1.3_5.0
Environment: PHILADELPHIA 2014 ** Philadelphia International Ap PA USA TMY3 WMO#=724080
Simulation Timestamp: 2021-07-16 12:25:57
Report: Annual Building Utility Performance Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
Values gathered over 8760.00 hours| Total Energy [GJ] | Energy Per Total Building Area [MJ/m2] | Energy Per Conditioned Building Area [MJ/m2] | |
| Total Site Energy | 3948.33 | 792.49 | 792.49 |
| Net Site Energy | 3948.33 | 792.49 | 792.49 |
| Total Source Energy | 13905.32 | 2791.01 | 2791.01 |
| Net Source Energy | 13905.32 | 2791.01 | 2791.01 |
| Site=>Source Conversion Factor | |
| Electricity | 3.546 |
| Natural Gas | 1.092 |
| District Cooling | 0.848 |
| District Heating | 1.647 |
| Steam | 0.585 |
| Gasoline | 1.050 |
| Diesel | 1.050 |
| Coal | 1.050 |
| Fuel Oil #1 | 1.050 |
| Fuel Oil #2 | 1.050 |
| Propane | 1.050 |
| Other Fuel 1 | 1.000 |
| Other Fuel 2 | 1.000 |
| Area [m2] | |
| Total Building Area | 4982.19 |
| Net Conditioned Building Area | 4982.19 |
| Unconditioned Building Area | 0.00 |
| Electricity [GJ] | Natural Gas [GJ] | Additional Fuel [GJ] | District Cooling [GJ] | District Heating [GJ] | Water [m3] | |
| Heating | 203.21 | 2.84 | 0.00 | 0.00 | 0.00 | 0.00 |
| Cooling | 422.50 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Interior Lighting | 1124.33 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Exterior Lighting | 232.43 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Interior Equipment | 1838.22 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Exterior Equipment | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Fans | 88.48 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Pumps | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Heat Rejection | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Humidification | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Heat Recovery | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Water Systems | 0.00 | 36.06 | 0.00 | 0.00 | 0.00 | 174.27 |
| Refrigeration | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Generators | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Total End Uses | 3909.43 | 38.89 | 0.00 | 0.00 | 0.00 | 174.27 |
| Subcategory | Electricity [GJ] | Natural Gas [GJ] | Additional Fuel [GJ] | District Cooling [GJ] | District Heating [GJ] | Water [m3] | |
| Heating | General | 203.21 | 2.84 | 0.00 | 0.00 | 0.00 | 0.00 |
| Cooling | General | 422.50 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Interior Lighting | General | 1124.33 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Exterior Lighting | Exterior Facade Lighting | 232.43 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Interior Equipment | General | 1673.92 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Elevators | 164.30 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
| Exterior Equipment | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Fans | Fan Energy | 88.48 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Pumps | General | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Heat Rejection | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Humidification | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Heat Recovery | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Water Systems | Water Heater | 0.00 | 36.06 | 0.00 | 0.00 | 0.00 | 0.00 |
| General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 174.27 | |
| Refrigeration | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Generators | General | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Electricity Intensity [MJ/m2] | Natural Gas Intensity [MJ/m2] | Additional Fuel Intensity [MJ/m2] | District Cooling Intensity [MJ/m2] | District Heating Intensity [MJ/m2] | Water Intensity [m3/m2] | |
| Lighting | 272.32 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| HVAC | 143.40 | 7.81 | 0.00 | 0.00 | 0.00 | 0.03 |
| Other | 368.96 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Total | 784.68 | 7.81 | 0.00 | 0.00 | 0.00 | 0.03 |
| Electricity Intensity [MJ/m2] | Natural Gas Intensity [MJ/m2] | Additional Fuel Intensity [MJ/m2] | District Cooling Intensity [MJ/m2] | District Heating Intensity [MJ/m2] | Water Intensity [m3/m2] | |
| Lighting | 272.32 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| HVAC | 143.40 | 7.81 | 0.00 | 0.00 | 0.00 | 0.03 |
| Other | 368.96 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Total | 784.68 | 7.81 | 0.00 | 0.00 | 0.00 | 0.03 |
| Electricity [GJ] | Percent Electricity [%] | |
| Fuel-Fired Power Generation | 0.000 | 0.00 |
| High Temperature Geothermal* | 0.000 | 0.00 |
| Photovoltaic Power | 0.000 | 0.00 |
| Wind Power | 0.000 | 0.00 |
| Power Conversion | 0.000 | 0.00 |
| Net Decrease in On-Site Storage | 0.000 | 0.00 |
| Total On-Site Electric Sources | 0.000 | 0.00 |
| Electricity Coming From Utility | 3909.433 | 100.00 |
| Surplus Electricity Going To Utility | 0.000 | 0.00 |
| Net Electricity From Utility | 3909.433 | 100.00 |
| Total On-Site and Utility Electric Sources | 3909.433 | 100.00 |
| Total Electricity End Uses | 3909.433 | 100.00 |
| Heat [GJ] | Percent Heat [%] | |
| Water-Side Heat Recovery | 0.00 | |
| Air to Air Heat Recovery for Cooling | 0.00 | |
| Air to Air Heat Recovery for Heating | 0.00 | |
| High-Temperature Geothermal* | 0.00 | |
| Solar Water Thermal | 0.00 | |
| Solar Air Thermal | 0.00 | |
| Total On-Site Thermal Sources | 0.00 |
| Water [m3] | Percent Water [%] | |
| Rainwater Collection | 0.00 | 0.00 |
| Condensate Collection | 0.00 | 0.00 |
| Groundwater Well | 0.00 | 0.00 |
| Total On Site Water Sources | 0.00 | 0.00 |
| - | - | - |
| Initial Storage | 0.00 | 0.00 |
| Final Storage | 0.00 | 0.00 |
| Change in Storage | 0.00 | 0.00 |
| - | - | - |
| Water Supplied by Utility | 174.27 | 100.00 |
| - | - | - |
| Total On Site, Change in Storage, and Utility Water Sources | 174.27 | 100.00 |
| Total Water End Uses | 174.27 | 100.00 |
| Degrees [deltaC] | |
| Tolerance for Zone Heating Setpoint Not Met Time | 0.56 |
| Tolerance for Zone Cooling Setpoint Not Met Time | 0.56 |
| Facility [Hours] | |
| Time Setpoint Not Met During Occupied Heating | 2.33 |
| Time Setpoint Not Met During Occupied Cooling | 4.67 |
| Time Not Comfortable Based on Simple ASHRAE 55-2004 | 2338.83 |
Table of Contents
TopEMISSIONS DATA SUMMARY
| Meter |COMPONENTS OF PEAK ELECTRICAL DEMAND
| Meter |HEATING PART LOAD PERFORMANCE
| VAV_1_HEATC | VAV_2_HEATC | VAV_3_HEATC |COOLING PART LOAD PERFORMANCE
| VAV_1_COOLC DXCOIL | VAV_2_COOLC DXCOIL | VAV_3_COOLC DXCOIL |FAN PART LOAD PERFORMANCE
| VAV_1_FAN | VAV_2_FAN | VAV_3_FAN |Report: Input Verification and Results Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
General| Value | |
| Program Version and Build | EnergyPlus, Version 9.1.0-08d2e308bb, YMD=2021.07.16 12:25 |
| RunPeriod | PHILADELPHIA 2014 |
| Weather File | Philadelphia International Ap PA USA TMY3 WMO#=724080 |
| Latitude [deg] | 39.87 |
| Longitude [deg] | -75.2 |
| Elevation [m] | 2.00 |
| Time Zone | -5.0 |
| North Axis Angle [deg] | 0.00 |
| Rotation for Appendix G [deg] | 0.00 |
| Hours Simulated [hrs] | 8760.00 |
| Total | North (315 to 45 deg) | East (45 to 135 deg) | South (135 to 225 deg) | West (225 to 315 deg) | |
| Gross Wall Area [m2] | 1977.67 | 593.30 | 395.53 | 593.30 | 395.53 |
| Above Ground Wall Area [m2] | 1977.67 | 593.30 | 395.53 | 593.30 | 395.53 |
| Window Opening Area [m2] | 652.83 | 195.85 | 130.57 | 195.85 | 130.57 |
| Gross Window-Wall Ratio [%] | 33.01 | 33.01 | 33.01 | 33.01 | 33.01 |
| Above Ground Window-Wall Ratio [%] | 33.01 | 33.01 | 33.01 | 33.01 | 33.01 |
| Total | North (315 to 45 deg) | East (45 to 135 deg) | South (135 to 225 deg) | West (225 to 315 deg) | |
| Gross Wall Area [m2] | 1977.67 | 593.30 | 395.53 | 593.30 | 395.53 |
| Above Ground Wall Area [m2] | 1977.67 | 593.30 | 395.53 | 593.30 | 395.53 |
| Window Opening Area [m2] | 652.83 | 195.85 | 130.57 | 195.85 | 130.57 |
| Gross Window-Wall Ratio [%] | 33.01 | 33.01 | 33.01 | 33.01 | 33.01 |
| Above Ground Window-Wall Ratio [%] | 33.01 | 33.01 | 33.01 | 33.01 | 33.01 |
| Total | |
| Gross Roof Area [m2] | 1660.73 |
| Skylight Area [m2] | 0.00 |
| Skylight-Roof Ratio [%] | 0.00 |
| Area [m2] | Conditioned (Y/N) | Part of Total Floor Area (Y/N) | Volume [m3] | Multipliers | Above Ground Gross Wall Area [m2] | Underground Gross Wall Area [m2] | Window Glass Area [m2] | Opening Area [m2] | Lighting [W/m2] | People [m2 per person] | Plug and Process [W/m2] | |
| CORE_BOTTOM | 983.54 | Yes | Yes | 2698.04 | 1.00 | 0.00 | 0.00 | 0.00 | 0.00 | 20.0000 | 25.00 | 52.6474 |
| CORE_MID | 983.54 | Yes | Yes | 2698.04 | 1.00 | 0.00 | 0.00 | 0.00 | 0.00 | 20.0000 | 25.00 | 20.0000 |
| CORE_TOP | 983.54 | Yes | Yes | 2698.04 | 1.00 | 0.00 | 0.00 | 0.00 | 0.00 | 20.0000 | 25.00 | 20.0000 |
| FIRSTFLOOR_PLENUM | 1660.73 | Yes | No | 2024.76 | 1.00 | 202.84 | 0.00 | 0.00 | 0.00 | 0.0000 | 0.0000 | |
| MIDFLOOR_PLENUM | 1660.73 | Yes | No | 2024.76 | 1.00 | 202.84 | 0.00 | 0.00 | 0.00 | 0.0000 | 0.0000 | |
| PERIMETER_BOT_ZN_1 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_BOT_ZN_2 | 131.26 | Yes | Yes | 360.08 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_BOT_ZN_3 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_BOT_ZN_4 | 131.25 | Yes | Yes | 360.05 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_MID_ZN_1 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_MID_ZN_2 | 131.26 | Yes | Yes | 360.08 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_MID_ZN_3 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_MID_ZN_4 | 131.25 | Yes | Yes | 360.05 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_TOP_ZN_1 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_TOP_ZN_2 | 131.26 | Yes | Yes | 360.08 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_TOP_ZN_3 | 207.34 | Yes | Yes | 568.77 | 1.00 | 136.92 | 0.00 | 65.28 | 65.28 | 20.0000 | 25.00 | 20.0000 |
| PERIMETER_TOP_ZN_4 | 131.25 | Yes | Yes | 360.05 | 1.00 | 91.28 | 0.00 | 43.52 | 43.52 | 20.0000 | 25.00 | 20.0000 |
| TOPFLOOR_PLENUM | 1660.73 | Yes | No | 2024.76 | 1.00 | 202.84 | 0.00 | 0.00 | 0.00 | 0.0000 | 0.0000 | |
| Total | 4982.19 | 13667.13 | 1369.16 | 0.00 | 652.83 | 652.83 | 20.0000 | 25.00 | 26.4449 | |||
| Conditioned Total | 4982.19 | 13667.13 | 1369.16 | 0.00 | 652.83 | 652.83 | 20.0000 | 25.00 | 26.4449 | |||
| Unconditioned Total | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | ||||||
| Not Part of Total | 4982.19 | 6074.28 | 608.51 | 0.00 | 0.00 | 0.00 | 0.0000 | 0.0000 |
Report: Component Sizing Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
AirTerminal:SingleDuct:VAV:Reheat| Design Size Maximum Air Flow Rate [m3/s] | Design Size Constant Minimum Air Flow Fraction | User-Specified Constant Minimum Air Flow Fraction | Design Size Minimum Air Flow Rate [m3/s] | Design Size Maximum Flow per Zone Floor Area during Reheat [m3/s-m2] | Design Size Maximum Flow Fraction during Reheat [] | |
| CORE_BOTTOM VAV BOX COMPONENT | 3.15 | 0.238106 | 0.300000 | 0.944271 | 0.000960 | 0.300000 |
| CORE_MID VAV BOX COMPONENT | 3.08 | 0.243507 | 0.300000 | 0.923328 | 0.000939 | 0.300000 |
| CORE_TOP VAV BOX COMPONENT | 3.48 | 0.215345 | 0.300000 | 1.04 | 0.001062 | 0.300000 |
| PERIMETER_BOT_ZN_1 VAV BOX COMPONENT | 1.09 | 0.200000 | 0.300000 | 0.328023 | 0.001582 | 0.300000 |
| PERIMETER_BOT_ZN_2 VAV BOX COMPONENT | 1.14 | 0.200000 | 0.300000 | 0.341307 | 0.002600 | 0.300000 |
| PERIMETER_BOT_ZN_3 VAV BOX COMPONENT | 0.704604 | 0.224228 | 0.300000 | 0.211381 | 0.001019 | 0.300000 |
| PERIMETER_BOT_ZN_4 VAV BOX COMPONENT | 1.28 | 0.200000 | 0.300000 | 0.385016 | 0.002933 | 0.300000 |
| PERIMETER_MID_ZN_1 VAV BOX COMPONENT | 1.33 | 0.200000 | 0.300000 | 0.397517 | 0.001917 | 0.300000 |
| PERIMETER_MID_ZN_2 VAV BOX COMPONENT | 1.30 | 0.200000 | 0.300000 | 0.389348 | 0.002966 | 0.300000 |
| PERIMETER_MID_ZN_3 VAV BOX COMPONENT | 0.937062 | 0.200000 | 0.300000 | 0.281118 | 0.001356 | 0.300000 |
| PERIMETER_MID_ZN_4 VAV BOX COMPONENT | 1.44 | 0.200000 | 0.300000 | 0.431301 | 0.003286 | 0.300000 |
| PERIMETER_TOP_ZN_1 VAV BOX COMPONENT | 1.34 | 0.200000 | 0.300000 | 0.403137 | 0.001944 | 0.300000 |
| PERIMETER_TOP_ZN_2 VAV BOX COMPONENT | 1.28 | 0.200000 | 0.300000 | 0.383557 | 0.002922 | 0.300000 |
| PERIMETER_TOP_ZN_3 VAV BOX COMPONENT | 1.02 | 0.200000 | 0.300000 | 0.307337 | 0.001482 | 0.300000 |
| PERIMETER_TOP_ZN_4 VAV BOX COMPONENT | 1.48 | 0.200000 | 0.300000 | 0.444497 | 0.003387 | 0.300000 |
| Design Size Nominal Capacity [W] | |
| CORE_BOTTOM VAV BOX REHEAT COIL | 38605.85 |
| CORE_MID VAV BOX REHEAT COIL | 37749.59 |
| CORE_TOP VAV BOX REHEAT COIL | 42686.32 |
| PERIMETER_BOT_ZN_1 VAV BOX REHEAT COIL | 15741.07 |
| PERIMETER_BOT_ZN_2 VAV BOX REHEAT COIL | 13954.08 |
| PERIMETER_BOT_ZN_3 VAV BOX REHEAT COIL | 15445.37 |
| PERIMETER_BOT_ZN_4 VAV BOX REHEAT COIL | 15741.10 |
| PERIMETER_MID_ZN_1 VAV BOX REHEAT COIL | 17053.29 |
| PERIMETER_MID_ZN_2 VAV BOX REHEAT COIL | 15918.22 |
| PERIMETER_MID_ZN_3 VAV BOX REHEAT COIL | 16794.09 |
| PERIMETER_MID_ZN_4 VAV BOX REHEAT COIL | 17633.45 |
| PERIMETER_TOP_ZN_1 VAV BOX REHEAT COIL | 21359.82 |
| PERIMETER_TOP_ZN_2 VAV BOX REHEAT COIL | 15681.45 |
| PERIMETER_TOP_ZN_3 VAV BOX REHEAT COIL | 21126.31 |
| PERIMETER_TOP_ZN_4 VAV BOX REHEAT COIL | 18172.93 |
| Sum of Air Terminal Maximum Heating Flow Rates [m3/s] | Sum of Air Terminal Minimum Heating Flow Rates [m3/s] | Sum of Air Terminal Maximum Flow Rates [m3/s] | Adjusted Heating Design Air Flow Rate [m3/s] | Adjusted Cooling Design Air Flow Rate [m3/s] | Adjusted Main Design Air Flow Rate [m3/s] | User Heating Air Flow Ratio [] | Calculated Heating Air Flow Ratio [] | Design Supply Air Flow Rate [m3/s] | |
| VAV_1 | 2.21 | 2.21 | 7.37 | 2.21 | 7.37 | 7.37 | 0.300000 | 0.300000 | 7.37 |
| VAV_2 | 2.42 | 2.42 | 8.08 | 2.42 | 8.08 | 8.08 | 0.300000 | 0.300000 | 8.08 |
| VAV_3 | 2.58 | 2.58 | 8.61 | 2.58 | 8.61 | 8.61 | 0.300000 | 0.300000 | 8.61 |
| Maximum Outdoor Air Flow Rate [m3/s] | Minimum Outdoor Air Flow Rate [m3/s] | |
| VAV_1_OA_CONTROLLER | 7.37 | 0.830364 |
| VAV_2_OA_CONTROLLER | 8.08 | 0.830364 |
| VAV_3_OA_CONTROLLER | 8.61 | 0.830364 |
| Design Size High Speed Rated Air Flow Rate [m3/s] | Design Size High Speed Gross Rated Total Cooling Capacity [W] | Design Size High Speed Rated Sensible Heat Ratio | Design Size Low Speed Rated Air Flow Rate [m3/s] | Design Size Low Speed Gross Rated Total Cooling Capacity [W] | Design Size Low Speed Gross Rated Sensible Heat Ratio | |
| VAV_1_COOLC DXCOIL | 7.37 | 169316.71 | 0.722791 | 2.46 | 56433.26 | 0.722791 |
| VAV_2_COOLC DXCOIL | 8.08 | 175286.02 | 0.742380 | 2.69 | 58422.83 | 0.742380 |
| VAV_3_COOLC DXCOIL | 8.61 | 191101.10 | 0.734161 | 2.87 | 63694.00 | 0.734161 |
| Design Size Design Maximum Air Flow Rate [m3/s] | Design Electric Power Consumption [W] | |
| VAV_1_FAN | 7.37 | 13819.78 |
| Design Size Nominal Capacity [W] | |
| VAV_1_HEATC | 29460.83 |
| VAV_2_HEATC | 28226.09 |
| VAV_3_HEATC | 27296.96 |
| Design Size Maximum Flow Rate [m3/s] | |
| VAV_2_FAN | 8.08 |
| VAV_3_FAN | 8.61 |
| Maximum Loop Flow Rate [m3/s] | Plant Loop Volume [m3] | |
| SWHSYS1 | 0.000031 | 0.003744 |
| Design Flow Rate [m3/s] | Design Power Consumption [W] | |
| SWHSYS1 PUMP | 0.000031 | 8.44 |
| Use Side Design Flow Rate [m3/s] | |
| SWHSYS1 WATER HEATER | 0.000031 |
Report: Climatic Data Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
SizingPeriod:DesignDay| Maximum Dry Bulb [C] | Daily Temperature Range [deltaC] | Humidity Value | Humidity Type | Wind Speed [m/s] | Wind Direction | |
| CHICAGO ANN HTG 99.6% CONDNS DB | -20.60 | 0.00 | -20.60 | Wetbulb [C] | 4.90 | 270.00 |
| CHICAGO ANN CLG .4% CONDNS WB=>MDB | 31.20 | 10.70 | 25.50 | Wetbulb [C] | 5.30 | 230.00 |
| Value | |
| None |
Report: Envelope Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
Opaque Exterior| Construction | Reflectance | U-Factor with Film [W/m2-K] | U-Factor no Film [W/m2-K] | Gross Area [m2] | Net Area [m2] | Azimuth [deg] | Tilt [deg] | Cardinal Direction | |
| CORE_BOT_ZN_5_FLOOR | EXT-SLAB | 0.30 | 2.193 | 3.401 | 983.54 | 983.54 | 0.00 | 180.00 | |
| PERIMETER_BOT_PLENUM_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 90.00 | 90.00 | E |
| PERIMETER_BOT_PLENUM_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 0.00 | 90.00 | N |
| PERIMETER_BOT_PLENUM_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 180.00 | 90.00 | S |
| PERIMETER_BOT_PLENUM_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 270.00 | 90.00 | W |
| PERIMETER_MID_PLENUM_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 90.00 | 90.00 | E |
| PERIMETER_MID_PLENUM_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 0.00 | 90.00 | N |
| PERIMETER_MID_PLENUM_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 180.00 | 90.00 | S |
| PERIMETER_MID_PLENUM_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 270.00 | 90.00 | W |
| PERIMETER_BOT_ZN_1_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 180.00 | 90.00 | S |
| PERIMETER_BOT_ZN_1_FLOOR | EXT-SLAB | 0.30 | 2.193 | 3.401 | 207.34 | 207.34 | 180.00 | 180.00 | |
| PERIMETER_BOT_ZN_2_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 90.00 | 90.00 | E |
| PERIMETER_BOT_ZN_2_FLOOR | EXT-SLAB | 0.30 | 2.193 | 3.401 | 131.26 | 131.26 | 90.00 | 180.00 | |
| PERIMETER_BOT_ZN_3_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 0.00 | 90.00 | N |
| PERIMETER_BOT_ZN_3_FLOOR | EXT-SLAB | 0.30 | 2.193 | 3.401 | 207.34 | 207.34 | 0.00 | 180.00 | |
| PERIMETER_BOT_ZN_4_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 270.00 | 90.00 | W |
| PERIMETER_BOT_ZN_4_FLOOR | EXT-SLAB | 0.30 | 2.193 | 3.401 | 131.25 | 131.25 | 270.00 | 180.00 | |
| PERIMETER_MID_ZN_1_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 180.00 | 90.00 | S |
| PERIMETER_MID_ZN_2_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 90.00 | 90.00 | E |
| PERIMETER_MID_ZN_3_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 0.00 | 90.00 | N |
| PERIMETER_MID_ZN_4_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 270.00 | 90.00 | W |
| PERIMETER_TOP_ZN_1_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 180.00 | 90.00 | S |
| PERIMETER_TOP_ZN_2_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 90.00 | 90.00 | E |
| PERIMETER_TOP_ZN_3_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 136.92 | 71.63 | 0.00 | 90.00 | N |
| PERIMETER_TOP_ZN_4_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 91.28 | 47.75 | 270.00 | 90.00 | W |
| PERIMETER_TOP_PLENUM_WALL_EAST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 90.00 | 90.00 | E |
| PERIMETER_TOP_PLENUM_WALL_NORTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 0.00 | 90.00 | N |
| PERIMETER_TOP_PLENUM_WALL_SOUTH | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 60.85 | 60.85 | 180.00 | 90.00 | S |
| PERIMETER_TOP_PLENUM_WALL_WEST | STEEL FRAME NON-RES EXT WALL | 0.22 | 0.665 | 0.738 | 40.57 | 40.57 | 270.00 | 90.00 | W |
| BUILDING_ROOF | IEAD NON-RES ROOF | 0.30 | 0.358 | 0.376 | 1660.73 | 1660.73 | 0.00 | 0.00 |
| Construction | Glass Area [m2] | Frame Area [m2] | Divider Area [m2] | Area of One Opening [m2] | Area of Multiplied Openings [m2] | Glass U-Factor [W/m2-K] | Glass SHGC | Glass Visible Transmittance | Frame Conductance [W/m2-K] | Divider Conductance [W/m2-K] | Shade Control | Parent Surface | Azimuth [deg] | Tilt [deg] | Cardinal Direction | |
| PERIMETER_BOT_ZN_1_WALL_SOUTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_BOT_ZN_1_WALL_SOUTH | 180.00 | 90.00 | S | ||
| PERIMETER_BOT_ZN_2_WALL_EAST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_BOT_ZN_2_WALL_EAST | 90.00 | 90.00 | E | ||
| PERIMETER_BOT_ZN_3_WALL_NORTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_BOT_ZN_3_WALL_NORTH | 0.00 | 90.00 | N | ||
| PERIMETER_BOT_ZN_4_WALL_WEST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_BOT_ZN_4_WALL_WEST | 270.00 | 90.00 | W | ||
| PERIMETER_MID_ZN_1_WALL_SOUTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_MID_ZN_1_WALL_SOUTH | 180.00 | 90.00 | S | ||
| PERIMETER_MID_ZN_2_WALL_EAST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_MID_ZN_2_WALL_EAST | 90.00 | 90.00 | E | ||
| PERIMETER_MID_ZN_3_WALL_NORTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_MID_ZN_3_WALL_NORTH | 0.00 | 90.00 | N | ||
| PERIMETER_MID_ZN_4_WALL_WEST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_MID_ZN_4_WALL_WEST | 270.00 | 90.00 | W | ||
| PERIMETER_TOP_ZN_1_WALL_SOUTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_TOP_ZN_1_WALL_SOUTH | 180.00 | 90.00 | S | ||
| PERIMETER_TOP_ZN_2_WALL_EAST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_TOP_ZN_2_WALL_EAST | 90.00 | 90.00 | E | ||
| PERIMETER_TOP_ZN_3_WALL_NORTH_WINDOW | WINDOW NON-RES FIXED | 65.28 | 0.00 | 0.00 | 65.28 | 65.28 | 4.855 | 0.600 | 0.461 | No | PERIMETER_TOP_ZN_3_WALL_NORTH | 0.00 | 90.00 | N | ||
| PERIMETER_TOP_ZN_4_WALL_WEST_WINDOW | WINDOW NON-RES FIXED | 43.52 | 0.00 | 0.00 | 43.52 | 43.52 | 4.855 | 0.600 | 0.461 | No | PERIMETER_TOP_ZN_4_WALL_WEST | 270.00 | 90.00 | W | ||
| Total or Average | 652.83 | 4.855 | 0.600 | 0.461 | ||||||||||||
| North Total or Average | 195.85 | 4.855 | 0.600 | 0.461 | ||||||||||||
| Non-North Total or Average | 456.98 | 4.855 | 0.600 | 0.461 |
| Construction | Area of One Opening [m2] | Area of Openings [m2] | Glass U-Factor [W/m2-K] | Glass SHGC | Glass Visible Transmittance | Parent Surface | |
| Total or Average | 0.00 | - | - | - |
| Construction | U-Factor with Film [W/m2-K] | U-Factor no Film [W/m2-K] | Gross Area [m2] | Parent Surface | |
| None |
Report: Equipment Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
Central Plant| Type | Nominal Capacity [W] | Nominal Efficiency [W/W] | IPLV in SI Units [W/W] | IPLV in IP Units [Btu/W-h] | |
| None |
| Type | Design Coil Load [W] | Nominal Total Capacity [W] | Nominal Sensible Capacity [W] | Nominal Latent Capacity [W] | Nominal Sensible Heat Ratio | Nominal Efficiency [W/W] | Nominal Coil UA Value [W/C] | Nominal Coil Surface Area [m2] | |
| VAV_1_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | 169316.71 | 122380.55 | 46936.16 | 0.72 | 3.23 | |||
| VAV_2_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | 175286.02 | 130128.88 | 45157.15 | 0.74 | 3.23 | |||
| VAV_3_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | 191101.10 | 140298.93 | 50802.17 | 0.73 | 3.23 |
| DX Cooling Coil Type | Standard Rated Net Cooling Capacity [W] | Standard Rated Net COP [W/W] | EER [Btu/W-h] | SEER [Btu/W-h] | IEER [Btu/W-h] | |
| VAV_1_COOLC DXCOIL | 168228.1 | 2.83 | 9.65 | N/A | 12.78 | |
| VAV_2_COOLC DXCOIL | 174188.5 | 2.81 | 9.58 | N/A | 12.72 | |
| VAV_3_COOLC DXCOIL | 189980.1 | 2.82 | 9.61 | N/A | 12.75 |
| DX Cooling Coil Type | Rated Net Cooling Capacity Test A [W] | Rated Electric Power Test A [W] | Rated Net Cooling Capacity Test B [W] | Rated Electric Power Test B [W] | Rated Net Cooling Capacity Test C [W] | Rated Electric Power Test C [W] | Rated Net Cooling Capacity Test D [W] | Rated Electric Power Test D [W] | |
| VAV_1_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | ||||||||
| VAV_2_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | ||||||||
| VAV_3_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed |
| DX Heating Coil Type | High Temperature Heating (net) Rating Capacity [W] | Low Temperature Heating (net) Rating Capacity [W] | HSPF [Btu/W-h] | Region Number | |
| None |
| Type | Design Coil Load [W] | Nominal Total Capacity [W] | Nominal Efficiency [W/W] | |
| CORE_BOTTOM VAV BOX REHEAT COIL | Coil:Heating:Electric | 38605.85 | 1.00 | |
| CORE_MID VAV BOX REHEAT COIL | Coil:Heating:Electric | 37749.59 | 1.00 | |
| CORE_TOP VAV BOX REHEAT COIL | Coil:Heating:Electric | 42686.32 | 1.00 | |
| PERIMETER_BOT_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | 15741.07 | 1.00 | |
| PERIMETER_BOT_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | 13954.08 | 1.00 | |
| PERIMETER_BOT_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | 15445.37 | 1.00 | |
| PERIMETER_BOT_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | 15741.10 | 1.00 | |
| PERIMETER_MID_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | 17053.29 | 1.00 | |
| PERIMETER_MID_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | 15918.22 | 1.00 | |
| PERIMETER_MID_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | 16794.09 | 1.00 | |
| PERIMETER_MID_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | 17633.45 | 1.00 | |
| PERIMETER_TOP_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | 21359.82 | 1.00 | |
| PERIMETER_TOP_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | 15681.45 | 1.00 | |
| PERIMETER_TOP_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | 21126.31 | 1.00 | |
| PERIMETER_TOP_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | 18172.93 | 1.00 | |
| VAV_1_HEATC | Coil:Heating:Fuel | 29460.83 | 0.80 | |
| VAV_2_HEATC | Coil:Heating:Fuel | 28226.09 | 0.80 | |
| VAV_3_HEATC | Coil:Heating:Fuel | 27296.96 | 0.80 |
| Type | Total Efficiency [W/W] | Delta Pressure [pa] | Max Air Flow Rate [m3/s] | Rated Electric Power [W] | Rated Power Per Max Air Flow Rate [W-s/m3] | Motor Heat In Air Fraction | Fan Energy Index | End Use Subcategory | Design Day Name for Fan Sizing Peak | Date/Time for Fan Sizing Peak | |
| VAV_1_FAN | Fan:SystemModel | 0.59 | 1109.65 | 7.37 | 13819.78 | 1875.99 | 1.00 | 1.12 | Fan Energy | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:00:00 |
| VAV_2_FAN | Fan:VariableVolume | 0.59 | 1109.65 | 8.08 | 15149.32 | 1875.99 | 1.00 | 1.11 | Fan Energy | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 16:00:00 |
| VAV_3_FAN | Fan:VariableVolume | 0.59 | 1109.65 | 8.61 | 16149.80 | 1875.99 | 1.00 | 1.11 | Fan Energy | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 17:00:00 |
| Type | Control | Head [pa] | Water Flow [m3/s] | Electric Power [W] | Power Per Water Flow Rate [W-s/m3] | Motor Efficiency [W/W] | End Use Subcategory | |
| SWHSYS1 PUMP | Pump:ConstantSpeed | Intermittent | 179352.00 | 0.000031 | 8.44 | 270515.84 | 0.85 | General |
| Type | Storage Volume [m3] | Input [W] | Thermal Efficiency [W/W] | Recovery Efficiency [W/W] | Energy Factor | |
| SWHSYS1 WATER HEATER | WaterHeater:Mixed | 0.38 | 845000.00 | 0.80 | 1.83 | 0.57 |
| DX Cooling Coil Type | Assocated Fan | Net Cooling Capacity [W] | COP [W/W] | EER [Btu/W-h] | IEER [Btu/W-h] | Supply Air Flow 100% [kg/s] | COP 75% Capacity [W/W] | EER 75% Capacity [Btu/W-h] | Supply Air Flow 75% [kg/s] | COP 50% Capacity [W/W] | EER 50% Capacity [Btu/W-h] | Supply Air Flow 50% [kg/s] | COP 25% Capacity [W/W] | EER 25% Capacity [Btu/W-h] | Supply Air Flow 25% [kg/s] | |
| VAV_1_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | VAV_1_FAN | 168228.10 | 2.83 | 9.65 | 12.78 | 8.5185 | 3.49 | 11.91 | 6.8623 | 4.19 | 14.29 | 4.6033 | 4.30 | 14.68 | 1.9317 |
| VAV_2_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | VAV_2_FAN | 174188.52 | 2.81 | 9.58 | 12.72 | 9.3380 | 3.47 | 11.84 | 7.5361 | 4.17 | 14.24 | 5.0569 | 4.30 | 14.66 | 2.0845 |
| VAV_3_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | VAV_3_FAN | 189980.06 | 2.82 | 9.61 | 12.75 | 9.9547 | 3.48 | 11.88 | 8.0230 | 4.18 | 14.27 | 5.3814 | 4.30 | 14.67 | 2.2383 |
Report: HVAC Sizing Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
Zone Sensible Cooling| Calculated Design Load [W] | User Design Load [W] | User Design Load per Area [W/m2] | Calculated Design Air Flow [m3/s] | User Design Air Flow [m3/s] | Design Day Name | Date/Time Of Peak {TIMESTAMP} | Thermostat Setpoint Temperature at Peak Load [C] | Indoor Temperature at Peak Load [C] | Indoor Humidity Ratio at Peak Load [kgWater/kgAir] | Outdoor Temperature at Peak Load [C] | Outdoor Humidity Ratio at Peak Load [kgWater/kgAir] | Minimum Outdoor Air Flow Rate [m3/s] | Heat Gain Rate from DOAS [W] | |
| CORE_BOTTOM | 38381.49 | 51047.38 | 51.90 | 2.367 | 3.148 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:00:00 | 26.00 | 26.00 | 0.00883 | 28.63 | 0.01878 | 0.492 | 0.00 |
| CORE_MID | 37673.19 | 50105.35 | 50.94 | 2.314 | 3.078 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 07:00:00 | 26.00 | 26.00 | 0.00882 | 21.46 | 0.01650 | 0.492 | 0.00 |
| CORE_TOP | 42439.31 | 56444.28 | 57.39 | 2.617 | 3.480 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:50:00 | 26.00 | 26.00 | 0.00880 | 27.29 | 0.01878 | 0.492 | 0.00 |
| PERIMETER_BOT_ZN_1 | 13333.75 | 17733.88 | 85.53 | 0.822 | 1.093 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 13:20:00 | 26.00 | 26.00 | 0.00870 | 30.84 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_BOT_ZN_2 | 13873.90 | 18452.29 | 140.58 | 0.855 | 1.138 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 08:50:00 | 26.00 | 26.00 | 0.00862 | 24.98 | 0.01878 | 0.066 | 0.00 |
| PERIMETER_BOT_ZN_3 | 8592.24 | 11427.67 | 55.12 | 0.530 | 0.705 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:20:00 | 26.00 | 26.00 | 0.00881 | 28.10 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_BOT_ZN_4 | 15650.69 | 20815.41 | 158.59 | 0.965 | 1.283 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 17:00:00 | 26.00 | 26.00 | 0.00861 | 29.70 | 0.01878 | 0.066 | 0.00 |
| PERIMETER_MID_ZN_1 | 16158.69 | 21491.05 | 103.65 | 0.996 | 1.325 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 13:20:00 | 26.00 | 26.00 | 0.00866 | 30.84 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_MID_ZN_2 | 15826.82 | 21049.67 | 160.36 | 0.976 | 1.298 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 08:50:00 | 26.00 | 26.00 | 0.00861 | 24.98 | 0.01878 | 0.066 | 0.00 |
| PERIMETER_MID_ZN_3 | 11427.07 | 15198.00 | 73.30 | 0.705 | 0.937 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:20:00 | 26.00 | 26.00 | 0.00873 | 28.10 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_MID_ZN_4 | 17532.24 | 23317.87 | 177.66 | 1.081 | 1.438 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 17:00:00 | 26.00 | 26.00 | 0.00859 | 29.70 | 0.01878 | 0.066 | 0.00 |
| PERIMETER_TOP_ZN_1 | 16387.15 | 21794.91 | 105.12 | 1.010 | 1.344 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 13:30:00 | 26.00 | 26.00 | 0.00866 | 30.93 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_TOP_ZN_2 | 15591.40 | 20736.57 | 157.98 | 0.961 | 1.279 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 08:50:00 | 26.00 | 26.00 | 0.00861 | 24.98 | 0.01878 | 0.066 | 0.00 |
| PERIMETER_TOP_ZN_3 | 12492.84 | 16615.48 | 80.14 | 0.770 | 1.024 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:20:00 | 26.00 | 26.00 | 0.00871 | 28.10 | 0.01878 | 0.104 | 0.00 |
| PERIMETER_TOP_ZN_4 | 18068.65 | 24031.30 | 183.09 | 1.114 | 1.482 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 17:10:00 | 26.00 | 26.00 | 0.00859 | 29.52 | 0.01878 | 0.066 | 0.00 |
| Calculated Design Load [W] | User Design Load [W] | User Design Load per Area [W/m2] | Calculated Design Air Flow [m3/s] | User Design Air Flow [m3/s] | Design Day Name | Date/Time Of Peak {TIMESTAMP} | Thermostat Setpoint Temperature at Peak Load [C] | Indoor Temperature at Peak Load [C] | Indoor Humidity Ratio at Peak Load [kgWater/kgAir] | Outdoor Temperature at Peak Load [C] | Outdoor Humidity Ratio at Peak Load [kgWater/kgAir] | Minimum Outdoor Air Flow Rate [m3/s] | Heat Gain Rate from DOAS [W] | |
| CORE_BOTTOM | 7325.88 | 9743.43 | 9.91 | 0.209 | 0.492 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.492 | 0.00 |
| CORE_MID | 8640.94 | 11492.45 | 11.68 | 0.247 | 0.492 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:40:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.492 | 0.00 |
| CORE_TOP | 20034.61 | 26646.03 | 27.09 | 0.573 | 0.762 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.492 | 0.00 |
| PERIMETER_BOT_ZN_1 | 10129.39 | 13472.09 | 64.98 | 0.289 | 0.385 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_BOT_ZN_2 | 6729.97 | 8950.85 | 68.19 | 0.192 | 0.256 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| PERIMETER_BOT_ZN_3 | 9939.10 | 13219.01 | 63.76 | 0.284 | 0.378 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_BOT_ZN_4 | 6710.66 | 8925.18 | 68.00 | 0.192 | 0.255 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| PERIMETER_MID_ZN_1 | 10973.80 | 14595.15 | 70.39 | 0.314 | 0.417 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_MID_ZN_2 | 7208.72 | 9587.60 | 73.04 | 0.206 | 0.274 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| PERIMETER_MID_ZN_3 | 10807.01 | 14373.32 | 69.32 | 0.309 | 0.411 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_MID_ZN_4 | 7272.44 | 9672.35 | 73.69 | 0.208 | 0.276 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| PERIMETER_TOP_ZN_1 | 13745.06 | 18280.93 | 88.17 | 0.393 | 0.522 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_TOP_ZN_2 | 8919.66 | 11863.15 | 90.38 | 0.255 | 0.339 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| PERIMETER_TOP_ZN_3 | 13594.80 | 18081.08 | 87.21 | 0.389 | 0.517 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.104 | 0.00 |
| PERIMETER_TOP_ZN_4 | 9031.95 | 12012.49 | 91.52 | 0.258 | 0.343 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21.50 | 21.50 | 0.00800 | -20.60 | 0.00061 | 0.066 | 0.00 |
| Calculated cooling [m3/s] | User cooling [m3/s] | Calculated heating [m3/s] | User heating [m3/s] | Adjusted cooling [m3/s] | Adjusted heating [m3/s] | Adjusted main [m3/s] | Calculated Heating Air Flow Ratio [] | User Heating Air Flow Ratio [] | |
| VAV_1 | 7.37 | 7.37 | 1.77 | 1.77 | 7.3667 | 2.2100 | 7.3667 | 0.3000 | 0.3000 |
| VAV_2 | 8.08 | 8.08 | 1.87 | 1.87 | 8.0754 | 2.4226 | 8.0754 | 0.3000 | 0.3000 |
| VAV_3 | 8.61 | 8.61 | 2.48 | 2.48 | 8.6087 | 2.5826 | 8.6087 | 0.3000 | 0.3000 |
| Previous Design Volume Flow Rate [m3/s] | Algorithm Volume Flow Rate [m3/s] | Coincident Design Volume Flow Rate [m3/s] | Coincident Size Adjusted | Peak Sizing Period Name | Peak Day into Period {TIMESTAMP}[day] | Peak Hour Of Day {TIMESTAMP}[hr] | Peak Step Start Minute {TIMESTAMP}[min] | |
| None |
| Coil Type | HVAC Type | HVAC Name | Coil Final Gross Total Capacity [W] | Coil Final Gross Sensible Capacity [W] | Coil Final Reference Air Volume Flow Rate [m3/s] | Coil Final Reference Plant Fluid Volume Flow Rate [m3/s] | Coil U-value Times Area Value [W/K] | Design Day Name at Sensible Ideal Loads Peak | Date/Time at Sensible Ideal Loads Peak | Design Day Name at Air Flow Ideal Loads Peak | Date/Time at Air Flow Ideal Loads Peak | Coil Total Capacity at Ideal Loads Peak [W] | Coil Sensible Capacity at Ideal Loads Peak [W] | Coil Air Volume Flow Rate at Ideal Loads Peak [m3/s] | Coil Entering Air Drybulb at Ideal Loads Peak [C] | Coil Entering Air Wetbulb at Ideal Loads Peak [C] | Coil Entering Air Humidity Ratio at Ideal Loads Peak [KGWATER/KGDRYAIR] | Coil Leaving Air Drybulb at Ideal Loads Peak [C] | Coil Leaving Air Wetbulb at Ideal Loads Peak [C] | Coil Leaving Air Humidity Ratio at Ideal Loads Peak [C] | Outdoor Air Drybulb at Ideal Loads Peak [C] | Outdoor Air Humidity Ratio at Ideal Loads Peak [KGWATER/KGDRYAIR] | Outdoor Air Wetbulb at Ideal Loads Peak [C] | Outdoor Air Flow Percentage at Ideal Loads Peak [%] | Zone Air Drybulb at Ideal Loads Peak [C] | Zone Air Humidity Ratio at Ideal Loads Peak [KGWATER/KGDRYAIR] | Zone Air Relative Humidity at Ideal Loads Peak [%] | Zone Sensible Heat Gain at Ideal Loads Peak [W] | Zone Latent Heat Gain at Ideal Loads Peak [W] | Coil Total Capacity at Rating Conditions [W] | Coil Sensible Capacity at Rating Conditions [W] | |
| CORE_BOTTOM VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | CORE_BOTTOM VAV BOX | 38605.851 | 38605.851 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 38605.85 | 20105.60 | 0.491768 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 9743.43 | 0.00 | -999.00 | -999.00 |
| CORE_MID VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | CORE_MID VAV BOX | 37749.594 | 37749.594 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:40:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:40:00 | 37749.59 | 20105.60 | 0.491768 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 11492.45 | 0.00 | -999.00 | -999.00 |
| CORE_TOP VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | CORE_TOP VAV BOX | 42686.318 | 42686.318 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 42686.32 | 31133.79 | 0.761510 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 26646.03 | 0.00 | -999.00 | -999.00 |
| PERIMETER_BOT_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_BOT_ZN_1 VAV BOX | 15741.073 | 15741.073 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 15741.07 | 15741.07 | 0.385015 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 13472.09 | 0.00 | -999.00 | -999.00 |
| PERIMETER_BOT_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_BOT_ZN_2 VAV BOX | 13954.078 | 13954.078 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 13954.08 | 10458.37 | 0.255804 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 8950.85 | 0.00 | -999.00 | -999.00 |
| PERIMETER_BOT_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_BOT_ZN_3 VAV BOX | 15445.368 | 15445.368 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 15445.37 | 15445.37 | 0.377782 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 13219.01 | 0.00 | -999.00 | -999.00 |
| PERIMETER_BOT_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_BOT_ZN_4 VAV BOX | 15741.096 | 15741.096 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 15741.10 | 10428.37 | 0.255070 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 8925.18 | 0.00 | -999.00 | -999.00 |
| PERIMETER_MID_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_MID_ZN_1 VAV BOX | 17053.285 | 17053.285 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 17053.29 | 17053.29 | 0.417111 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 14595.15 | 0.00 | -999.00 | -999.00 |
| PERIMETER_MID_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_MID_ZN_2 VAV BOX | 15918.217 | 15918.217 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 15918.22 | 11202.35 | 0.274001 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 9587.60 | 0.00 | -999.00 | -999.00 |
| PERIMETER_MID_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_MID_ZN_3 VAV BOX | 16794.090 | 16794.090 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 16794.09 | 16794.09 | 0.410771 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 14373.32 | 0.00 | -999.00 | -999.00 |
| PERIMETER_MID_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_MID_ZN_4 VAV BOX | 17633.452 | 17633.452 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 17633.45 | 11301.38 | 0.276423 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 9672.35 | 0.00 | -999.00 | -999.00 |
| PERIMETER_TOP_ZN_1 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_TOP_ZN_1 VAV BOX | 21359.824 | 21359.824 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21359.82 | 21359.82 | 0.522446 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 18280.93 | 0.00 | -999.00 | -999.00 |
| PERIMETER_TOP_ZN_2 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_TOP_ZN_2 VAV BOX | 15681.446 | 15681.446 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 15681.45 | 13861.16 | 0.339034 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 11863.15 | 0.00 | -999.00 | -999.00 |
| PERIMETER_TOP_ZN_3 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_TOP_ZN_3 VAV BOX | 21126.312 | 21126.312 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 21126.31 | 21126.31 | 0.516734 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 18081.08 | 0.00 | -999.00 | -999.00 |
| PERIMETER_TOP_ZN_4 VAV BOX REHEAT COIL | Coil:Heating:Electric | ZONEHVAC:AIRDISTRIBUTIONUNIT | PERIMETER_TOP_ZN_4 VAV BOX | 18172.928 | 18172.928 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 18172.93 | 14035.65 | 0.343302 | 16.70 | 13.18 | 0.00800000 | 50.00 | 23.94 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 0.0000 | 21.50 | 0.00800000 | 50.1490 | 12012.49 | 0.00 | -999.00 | -999.00 |
| VAV_1_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | AirLoopHVAC | VAV_1 | 169316.712 | 122380.549 | 7.366660 | -999.0 | -999.000 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:00:00 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 18:00:00 | 163366.98 | 135185.95 | 7.366660 | 28.01 | 18.85 | 0.00986824 | 11.28 | 11.28 | 0.00850000 | 28.53 | 0.01878287 | 25.11 | 11.2719 | 26.00 | 0.00873573 | 41.7242 | 119476.64 | 0.00 | 169300.20 | 122909.34 |
| VAV_1_HEATC | Coil:Heating:Fuel | AirLoopHVAC | VAV_1 | 29460.828 | 29460.828 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 13:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 07:00:00 | 29460.83 | 29460.83 | 2.209998 | 1.70 | 1.70 | 0.00452537 | 16.70 | 13.18 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 37.5731 | 21.50 | 0.00800000 | 50.1490 | 54310.56 | 0.00 | -999.00 | -999.00 |
| VAV_2_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | AirLoopHVAC | VAV_2 | 175286.021 | 130128.876 | 8.075375 | -999.0 | -999.000 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 15:40:00 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 16:00:00 | 167410.03 | 141821.38 | 8.075375 | 27.59 | 18.55 | 0.00965407 | 11.28 | 11.28 | 0.00850000 | 25.80 | 0.01791105 | 23.87 | 10.2827 | 26.00 | 0.00870773 | 41.5916 | 131161.95 | 0.00 | 175268.92 | 130690.17 |
| VAV_2_HEATC | Coil:Heating:Fuel | AirLoopHVAC | VAV_2 | 28226.093 | 28226.093 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 18:20:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 08:50:00 | 28226.09 | 28226.09 | 2.422613 | 2.81 | 2.81 | 0.00471978 | 16.70 | 13.18 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 34.2756 | 21.50 | 0.00800000 | 50.1490 | 59720.87 | 0.00 | -999.00 | -999.00 |
| VAV_3_COOLC DXCOIL | Coil:Cooling:DX:TwoSpeed | AirLoopHVAC | VAV_3 | 191101.102 | 140298.929 | 8.608679 | -999.0 | -999.000 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 16:30:00 | CHICAGO ANN CLG .4% CONDNS WB=>MDB | 7/21 17:00:00 | 185207.27 | 156652.12 | 8.608679 | 27.70 | 18.60 | 0.00967373 | 11.28 | 11.28 | 0.00850000 | 28.00 | 0.01878287 | 24.98 | 9.6457 | 26.00 | 0.00870130 | 41.5616 | 139622.54 | 0.00 | 191082.46 | 140891.56 |
| VAV_3_HEATC | Coil:Heating:Fuel | AirLoopHVAC | VAV_3 | 27296.961 | 27296.961 | -999.0 | -999.0 | -999.000 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 01:00:00 | CHICAGO ANN HTG 99.6% CONDNS DB | 1/21 24:00:00 | 27296.96 | 27296.96 | 2.582604 | 7.42 | 6.38 | 0.00552952 | 16.70 | 13.18 | 0.00800000 | -20.60 | 0.00061258 | -20.60 | 32.1522 | 21.50 | 0.00800000 | 50.1490 | 86883.68 | 0.00 | -999.00 | -999.00 |
Report: System Summary
For: Entire Facility
Timestamp: 2021-07-16 12:25:57
Economizer| High Limit Shutoff Control | Minimum Outdoor Air [m3/s] | Maximum Outdoor Air [m3/s] | Return Air Temp Limit | Return Air Enthalpy Limit | Outdoor Air Temperature Limit [C] | Outdoor Air Enthalpy Limit [C] | |
| VAV_1_OA_CONTROLLER | DifferentialDryBulb | 0.83 | 7.37 | - | |||
| VAV_2_OA_CONTROLLER | DifferentialDryBulb | 0.83 | 8.08 | - | |||
| VAV_3_OA_CONTROLLER | DifferentialDryBulb | 0.83 | 8.61 | - |
| Controller:MechanicalVentilation Name | Outdoor Air Per Person [m3/s-person] | Outdoor Air Per Area [m3/s-m2] | Outdoor Air Per Zone [m3/s] | Outdoor Air ACH [ach] | Outdoor Air Method | Outdoor Air Schedule Name | Air Distribution Effectiveness in Cooling Mode | Air Distribution Effectiveness in Heating Mode | Air Distribution Effectiveness Schedule Name | |
| None |
| Winter Clothes [hr] | Summer Clothes [hr] | Summer or Winter Clothes [hr] | |
| CORE_BOTTOM | 3084.00 | 1376.50 | 8.50 |
| CORE_MID | 3818.83 | 861.50 | 186.83 |
| CORE_TOP | 3237.50 | 1777.33 | 457.83 |
| PERIMETER_BOT_ZN_1 | 2718.17 | 3211.17 | 1189.00 |
| PERIMETER_BOT_ZN_2 | 2080.67 | 3761.50 | 1062.50 |
| PERIMETER_BOT_ZN_3 | 2496.83 | 3123.50 | 852.50 |
| PERIMETER_BOT_ZN_4 | 1870.00 | 3905.17 | 990.17 |
| PERIMETER_MID_ZN_1 | 2910.83 | 3141.67 | 1392.17 |
| PERIMETER_MID_ZN_2 | 2140.67 | 3619.83 | 1047.67 |
| PERIMETER_MID_ZN_3 | 2670.50 | 3056.17 | 1020.17 |
| PERIMETER_MID_ZN_4 | 1844.83 | 3735.00 | 869.17 |
| PERIMETER_TOP_ZN_1 | 2948.17 | 3272.83 | 1514.67 |
| PERIMETER_TOP_ZN_2 | 2352.00 | 3680.33 | 1280.00 |
| PERIMETER_TOP_ZN_3 | 2781.00 | 3297.67 | 1339.00 |
| PERIMETER_TOP_ZN_4 | 2022.33 | 3838.17 | 1114.17 |
| FIRSTFLOOR_PLENUM | 0.00 | 0.00 | 0.00 |
| MIDFLOOR_PLENUM | 0.00 | 0.00 | 0.00 |
| TOPFLOOR_PLENUM | 0.00 | 0.00 | 0.00 |
| Facility | 4695.83 | 4889.00 | 2338.83 |
| During Heating [hr] | During Cooling [hr] | During Occupied Heating [hr] | During Occupied Cooling [hr] | |
| CORE_BOTTOM | 0.00 | 0.17 | 0.00 | 0.17 |
| CORE_MID | 0.00 | 20.67 | 0.00 | 3.50 |
| CORE_TOP | 1.00 | 7.50 | 1.00 | 1.17 |
| PERIMETER_BOT_ZN_1 | 1.67 | 34.67 | 1.67 | 0.00 |
| PERIMETER_BOT_ZN_2 | 1.17 | 18.67 | 1.17 | 0.00 |
| PERIMETER_BOT_ZN_3 | 2.17 | 4.33 | 2.17 | 0.00 |
| PERIMETER_BOT_ZN_4 | 0.67 | 24.00 | 0.67 | 0.00 |
| PERIMETER_MID_ZN_1 | 1.00 | 50.33 | 0.83 | 0.00 |
| PERIMETER_MID_ZN_2 | 1.17 | 27.33 | 0.67 | 0.00 |
| PERIMETER_MID_ZN_3 | 1.83 | 16.17 | 1.50 | 0.00 |
| PERIMETER_MID_ZN_4 | 0.83 | 30.50 | 0.33 | 0.00 |
| PERIMETER_TOP_ZN_1 | 8.17 | 47.33 | 2.00 | 0.00 |
| PERIMETER_TOP_ZN_2 | 16.50 | 29.83 | 2.00 | 0.00 |
| PERIMETER_TOP_ZN_3 | 17.50 | 20.83 | 2.33 | 0.33 |
| PERIMETER_TOP_ZN_4 | 14.33 | 31.00 | 0.83 | 0.00 |
| FIRSTFLOOR_PLENUM | 0.00 | 0.00 | 0.00 | 0.00 |
| MIDFLOOR_PLENUM | 0.00 | 0.00 | 0.00 | 0.00 |
| TOPFLOOR_PLENUM | 0.00 | 0.00 | 0.00 | 0.00 |
| Facility | 19.33 | 196.67 | 2.33 | 4.67 |
Report: EMISSIONS DATA SUMMARY
For: Meter
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| CO2:FACILITY [kg] | NOX:FACILITY [kg] | SO2:FACILITY [kg] | PM:FACILITY [kg] | HG:FACILITY [kg] | WATERENVIRONMENTALFACTORS:FACILITY [L] | CARBON EQUIVALENT:FACILITY [kg] | |
| January |<PHONE_NUMBER> | 210.6632 | 633.0771 | 0.0000 | 0.0019 |<PHONE_NUMBER> | 33391.0747 |
| February |<PHONE_NUMBER> | 183.4293 | 551.3018 | 0.0000 | 0.0017 |<PHONE_NUMBER> | 29071.1619 |
| March |<PHONE_NUMBER> | 185.5852 | 557.8724 | 0.0000 | 0.0017 |<PHONE_NUMBER> | 29408.4940 |
| April |<PHONE_NUMBER> | 186.8612 | 561.7355 | 0.0000 | 0.0017 |<PHONE_NUMBER> | 29609.3659 |
| May |<PHONE_NUMBER> | 197.7887 | 594.6489 | 0.0000 | 0.0018 |<PHONE_NUMBER> | 31337.8706 |
| June |<PHONE_NUMBER> | 216.9697 | 652.4025 | 0.0000 | 0.0020 |<PHONE_NUMBER> | 34372.8020 |
| July |<PHONE_NUMBER> | 240.5491 | 723.3555 | 0.0000 | 0.0022 |<PHONE_NUMBER> | 38105.7678 |
| August |<PHONE_NUMBER> | 231.9509 | 697.5007 | 0.0000 | 0.0021 |<PHONE_NUMBER> | 36743.6723 |
| September |<PHONE_NUMBER> | 209.6599 | 630.4334 | 0.0000 | 0.0019 |<PHONE_NUMBER> | 33214.2479 |
| October |<PHONE_NUMBER> | 193.3538 | 581.3321 | 0.0000 | 0.0018 |<PHONE_NUMBER> | 30634.3779 |
| November | 95608.7407 | 173.9578 | 522.9781 | 0.0000 | 0.0016 |<PHONE_NUMBER> | 27563.2073 |
| December |<PHONE_NUMBER> | 203.5198 | 611.8304 | 0.0000 | 0.0018 |<PHONE_NUMBER> | 32248.2657 |
| Annual Sum or Average | 0.133788E+07 | 2434.2887 | 7318.4684 | 0.0000 | 0.0220 | 0.168479E+07 |<PHONE_NUMBER> |
| Minimum of Months | 95608.7407 | 173.9578 | 522.9781 | 0.0000 | 0.0016 |<PHONE_NUMBER> | 27563.2073 |
| Maximum of Months |<PHONE_NUMBER> | 240.5491 | 723.3555 | 0.0000 | 0.0022 |<PHONE_NUMBER> | 38105.7678 |
Report: COMPONENTS OF PEAK ELECTRICAL DEMAND
For: Meter
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| ELECTRICITY:FACILITY [J] | ELECTRICITY:FACILITY {Maximum}[W] | ELECTRICITY:FACILITY {TIMESTAMP} | INTERIORLIGHTS:ELECTRICITY {AT MAX/MIN} [W] | INTERIOREQUIPMENT:ELECTRICITY {AT MAX/MIN} [W] | FANS:ELECTRICITY {AT MAX/MIN} [W] | HEATING:ELECTRICITY {AT MAX/MIN} [W] | COOLING:ELECTRICITY {AT MAX/MIN} [W] | EXTERIORLIGHTS:ELECTRICITY {AT MAX/MIN} [W] | PUMPS:ELECTRICITY {AT MAX/MIN} [W] | HEATREJECTION:ELECTRICITY [] | EXTERIOREQUIPMENT:ELECTRICITY [] | HUMIDIFICATION:ELECTRICITY [] | HEATRECOVERY:ELECTRICITY [] | WATERSYSTEMS:ELECTRICITY [] | REFRIGERATION:ELECTRICITY [] | GENERATORS:ELECTRICITY [] | ELECTRICITYPRODUCED:FACILITY [] | |
| January | 0.338181E+12 | 311181.685 | 21-JAN-08:09 | 89679.346 | 111835.170 | 3884.331 | 105774.397 | 0.000 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| February | 0.294498E+12 | 340678.855 | 10-FEB-06:10 | 9964.372 | 39857.487 | 3884.331 | 272160.224 | 0.000 | 14804.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| March | 0.298008E+12 | 269455.420 | 17-MAR-07:10 | 89679.346 | 111835.170 | 3884.331 | 64048.132 | 0.000 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| April | 0.300072E+12 | 245075.627 | 09-APR-15:09 | 89679.346 | 104449.896 | 5804.412 | 0.000 | 45133.534 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| May | 0.317654E+12 | 271421.101 | 02-MAY-15:00 | 89679.346 | 104449.896 | 7998.943 | 0.000 | 69284.477 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| June | 0.348505E+12 | 298525.447 | 16-JUN-15:09 | 89679.346 | 104449.896 | 8408.222 | 0.000 | 95979.544 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| July | 0.386407E+12 | 315840.060 | 07-JUL-15:30 | 89679.346 | 104449.896 | 10245.545 | 0.000 | 111456.833 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| August | 0.372596E+12 | 313451.842 | 04-AUG-15:09 | 89679.346 | 104449.896 | 10211.847 | 0.000 | 109102.313 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| September | 0.336770E+12 | 292514.878 | 05-SEP-10:00 | 89679.346 | 103486.599 | 7431.865 | 0.000 | 91908.628 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| October | 0.310540E+12 | 263874.259 | 01-OCT-12:00 | 89679.346 | 105092.093 | 6324.335 | 0.000 | 62770.045 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| November | 0.279368E+12 | 264279.791 | 24-NOV-06:10 | 9964.372 | 39857.487 | 3884.331 | 195761.161 | 0.000 | 14804.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| December | 0.326832E+12 | 282749.108 | 29-DEC-08:09 | 89679.346 | 111835.170 | 3884.331 | 77341.820 | 0.000 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| Annual Sum or Average | 0.390943E+13 | |||||||||||||||||
| Minimum of Months | 0.279368E+12 | 245075.627 | 9964.372 | 39857.487 | 3884.331 | 0.000 | 0.000 | 0.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| Maximum of Months | 0.386407E+12 | 340678.855 | 89679.346 | 111835.170 | 10245.545 | 272160.224 | 111456.833 | 14804.000 | 8.440 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
Report: HEATING PART LOAD PERFORMANCE
For: VAV_1_HEATC
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| HEATING COIL GAS RATE [W] | HEATING COIL GAS RATE {Maximum}[W] | HEATING COIL GAS RATE {TIMESTAMP} | |
| January | 211. | 13575. | 23-JAN-07:05 |
| February | 118. | 13912. | 10-FEB-07:05 |
| March | 0. | 0. | 01-MAR-00:10 |
| April | 0. | 0. | 01-APR-00:10 |
| May | 0. | 0. | 01-MAY-00:02 |
| June | 0. | 0. | 01-JUN-00:02 |
| July | 0. | 0. | 01-JUL-00:02 |
| August | 0. | 0. | 01-AUG-00:10 |
| September | 0. | 0. | 01-SEP-00:03 |
| October | 0. | 0. | 01-OCT-00:03 |
| November | 6. | 4882. | 24-NOV-07:05 |
| December | 11. | 7067. | 29-DEC-07:05 |
| Annual Sum or Average | 28. | ||
| Minimum of Months | 0. | 0. | |
| Maximum of Months | 211. | 13912. |
Report: HEATING PART LOAD PERFORMANCE
For: VAV_2_HEATC
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| HEATING COIL GAS RATE [W] | HEATING COIL GAS RATE {Maximum}[W] | HEATING COIL GAS RATE {TIMESTAMP} | |
| January | 95. | 11153. | 23-JAN-07:05 |
| February | 68. | 12918. | 10-FEB-07:05 |
| March | 0. | 0. | 01-MAR-00:10 |
| April | 0. | 0. | 01-APR-00:10 |
| May | 0. | 0. | 01-MAY-00:02 |
| June | 0. | 0. | 01-JUN-00:02 |
| July | 0. | 0. | 01-JUL-00:02 |
| August | 0. | 0. | 01-AUG-00:10 |
| September | 0. | 0. | 01-SEP-00:03 |
| October | 0. | 0. | 01-OCT-00:03 |
| November | 3. | 2969. | 24-NOV-07:05 |
| December | 6. | 5166. | 29-DEC-07:05 |
| Annual Sum or Average | 14. | ||
| Minimum of Months | 0. | 0. | |
| Maximum of Months | 95. | 12918. |
Report: HEATING PART LOAD PERFORMANCE
For: VAV_3_HEATC
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| HEATING COIL GAS RATE [W] | HEATING COIL GAS RATE {Maximum}[W] | HEATING COIL GAS RATE {TIMESTAMP} | |
| January | 352. | 18916. | 23-JAN-07:05 |
| February | 178. | 17987. | 10-FEB-07:05 |
| March | 0. | 0. | 01-MAR-00:10 |
| April | 0. | 0. | 01-APR-00:10 |
| May | 0. | 0. | 01-MAY-00:02 |
| June | 0. | 0. | 01-JUN-00:02 |
| July | 0. | 0. | 01-JUL-00:02 |
| August | 0. | 0. | 01-AUG-00:10 |
| September | 0. | 0. | 01-SEP-00:03 |
| October | 0. | 0. | 01-OCT-00:03 |
| November | 14. | 9077. | 24-NOV-07:05 |
| December | 32. | 11208. | 29-DEC-07:05 |
| Annual Sum or Average | 47. | ||
| Minimum of Months | 0. | 0. | |
| Maximum of Months | 352. | 18916. |
Report: COOLING PART LOAD PERFORMANCE
For: VAV_1_COOLC DXCOIL
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| COOLING COIL ELECTRIC POWER [W] | COOLING COIL ELECTRIC POWER {Maximum}[W] | COOLING COIL ELECTRIC POWER {TIMESTAMP} | |
| January | 1. | 618. | 27-JAN-07:00 |
| February | 33. | 3600. | 20-FEB-16:10 |
| March | 434. | 11535. | 26-MAR-15:10 |
| April | 1655. | 14748. | 19-APR-13:10 |
| May | 4170. | 19990. | 02-MAY-16:00 |
| June | 8222. | 29404. | 16-JUN-15:10 |
| July | 10729. | 34324. | 07-JUL-15:20 |
| August | 9856. | 33803. | 04-AUG-15:10 |
| September | 6449. | 28954. | 05-SEP-11:00 |
| October | 1892. | 19495. | 01-OCT-13:00 |
| November | 558. | 12352. | 14-NOV-13:30 |
| December | 198. | 10259. | 04-DEC-14:00 |
| Annual Sum or Average | 3707. | ||
| Minimum of Months | 1. | 618. | |
| Maximum of Months | 10729. | 34324. |
Report: COOLING PART LOAD PERFORMANCE
For: VAV_2_COOLC DXCOIL
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| COOLING COIL ELECTRIC POWER [W] | COOLING COIL ELECTRIC POWER {Maximum}[W] | COOLING COIL ELECTRIC POWER {TIMESTAMP} | |
| January | 1. | 683. | 27-JAN-07:00 |
| February | 36. | 3979. | 20-FEB-16:00 |
| March | 502. | 13372. | 26-MAR-15:00 |
| April | 1906. | 17747. | 19-APR-13:30 |
| May | 5303. | 23135. | 02-MAY-16:00 |
| June | 10736. | 31267. | 16-JUN-14:50 |
| July | 13733. | 36242. | 07-JUL-15:20 |
| August | 12366. | 35830. | 04-AUG-15:00 |
| September | 8544. | 31751. | 05-SEP-11:00 |
| October | 2246. | 21970. | 01-OCT-13:30 |
| November | 641. | 13266. | 14-NOV-15:00 |
| December | 212. | 10626. | 04-DEC-15:00 |
| Annual Sum or Average | 4715. | ||
| Minimum of Months | 1. | 683. | |
| Maximum of Months | 13733. | 36242. |
Report: COOLING PART LOAD PERFORMANCE
For: VAV_3_COOLC DXCOIL
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| COOLING COIL ELECTRIC POWER [W] | COOLING COIL ELECTRIC POWER {Maximum}[W] | COOLING COIL ELECTRIC POWER {TIMESTAMP} | |
| January | 1. | 726. | 27-JAN-07:00 |
| February | 36. | 4019. | 20-FEB-16:00 |
| March | 509. | 13574. | 26-MAR-15:00 |
| April | 2026. | 18194. | 19-APR-13:15 |
| May | 5651. | 26554. | 04-MAY-15:32 |
| June | 11402. | 35462. | 16-JUN-15:00 |
| July | 14607. | 40904. | 07-JUL-15:30 |
| August | 13036. | 40208. | 04-AUG-15:00 |
| September | 8907. | 31278. | 09-SEP-13:50 |
| October | 2278. | 22076. | 01-OCT-14:00 |
| November | 643. | 13455. | 14-NOV-15:00 |
| December | 225. | 11300. | 04-DEC-15:00 |
| Annual Sum or Average | 4975. | ||
| Minimum of Months | 1. | 726. | |
| Maximum of Months | 14607. | 40904. |
Report: FAN PART LOAD PERFORMANCE
For: VAV_1_FAN
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| FAN ELECTRIC POWER [W] | FAN ELECTRIC POWER {Maximum}[W] | FAN ELECTRIC POWER {TIMESTAMP} | |
| January | 652. | 1746. | 15-JAN-13:30 |
| February | 680. | 1753. | 07-FEB-13:30 |
| March | 697. | 1933. | 26-MAR-15:30 |
| April | 757. | 1792. | 29-APR-15:30 |
| May | 770. | 2242. | 02-MAY-15:20 |
| June | 930. | 2609. | 16-JUN-16:00 |
| July | 1054. | 3183. | 08-JUL-15:20 |
| August | 1043. | 3229. | 04-AUG-15:30 |
| September | 901. | 2789. | 04-SEP-14:30 |
| October | 769. | 2162. | 08-OCT-12:30 |
| November | 634. | 1780. | 17-NOV-13:10 |
| December | 674. | 1784. | 23-DEC-13:30 |
| Annual Sum or Average | 798. | ||
| Minimum of Months | 634. | 1746. | |
| Maximum of Months | 1054. | 3229. |
Report: FAN PART LOAD PERFORMANCE
For: VAV_2_FAN
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| FAN ELECTRIC POWER [W] | FAN ELECTRIC POWER {Maximum}[W] | FAN ELECTRIC POWER {TIMESTAMP} | |
| January | 705. | 1745. | 15-JAN-13:20 |
| February | 755. | 2020. | 20-FEB-06:02 |
| March | 820. | 2347. | 28-MAR-05:02 |
| April | 965. | 2277. | 23-APR-05:02 |
| May | 1081. | 2855. | 04-MAY-14:42 |
| June | 1254. | 2855. | 18-JUN-15:30 |
| July | 1360. | 3479. | 08-JUL-15:20 |
| August | 1327. | 3597. | 17-AUG-15:12 |
| September | 1203. | 3301. | 04-SEP-14:30 |
| October | 969. | 2551. | 01-OCT-14:30 |
| November | 717. | 2148. | 01-NOV-05:02 |
| December | 730. | 2027. | 05-DEC-06:02 |
| Annual Sum or Average | 992. | ||
| Minimum of Months | 705. | 1745. | |
| Maximum of Months | 1360. | 3597. |
Report: FAN PART LOAD PERFORMANCE
For: VAV_3_FAN
Timestamp: 2021-07-16 12:25:57
Custom Monthly Report| FAN ELECTRIC POWER [W] | FAN ELECTRIC POWER {Maximum}[W] | FAN ELECTRIC POWER {TIMESTAMP} | |
| January | 839. | 1738. | 15-JAN-13:30 |
| February | 805. | 1957. | 17-FEB-13:02 |
| March | 803. | 2288. | 26-MAR-15:40 |
| April | 942. | 2333. | 29-APR-15:30 |
| May | 1092. | 3048. | 04-MAY-14:52 |
| June | 1300. | 3254. | 16-JUN-16:00 |
| July | 1421. | 3821. | 08-JUL-15:30 |
| August | 1363. | 3854. | 17-AUG-15:02 |
| September | 1202. | 3385. | 04-SEP-14:30 |
| October | 920. | 2483. | 01-OCT-14:30 |
| November | 722. | 1919. | 11-NOV-12:22 |
| December | 769. | 1768. | 23-DEC-13:20 |
| Annual Sum or Average | 1016. | ||
| Minimum of Months | 722. | 1738. | |
| Maximum of Months | 1421. | 3854. |


Lesson 12 - Display Lists in WebGL
Lesson 12 of NeHe is about how to use display lists, which are a method for caching the construction of complex objects in OpenGL 1.x. WebGL and GL-ES implictly create caches of all the high level stuctures since the vertices are passed to the GPU cached in vertex buffer objects (VBO) from which they are rendered via shaders running on the GPU. So there is no point to lesson 12 in the world of WebGL. So let's just move on folks, nothing to see here...


We have included every ribosomal protein in the crystal structures, but not accessory proteins. Generic contacts with the rRNA are colored. These contacts are defined as distances within 3.4Å. Selecting a protein will show the selected protein in Jmol. Filtering protein contacts by type or some other variable will be a future feature.


PSG’s owners want to buy Leeds United. This is how they could line up with some added billionaire funding
Leeds United could become the next, well, Leeds United if Paris Saint-Germain’s owners complete their purchase of the club.
Back at the turn of the century, the Whites splurged millions on huge signings such as Rio Ferdinand and Robbie Keane in a spree that might even be surpassed should Nasser Al-Khelaifi bring in the Qatari big bucks.
Rich kids of Manchester: Premier League champs’ revenue rises to $1billion
Stream live coverage of La Liga, Bundesliga, Serie A, Ligue 1 and the EFL Championship with beIN SPORTS on KAYO. Get your 14 day free trial & start streaming instantly >
As with any spend-happy new owner, the first signings will naturally be attackers.
Marcelo Bielsa is very happy with his defence, currently the Championship’s best, and would thus focus his efforts on bolstering his frontline.
This could lead to a very interesting line-up!
26-year-old Jese Rodriguez is on his fourth loan spell away from Paris and could well benefit from the intense management of a coach like Bielsa.
On the opposite flank, Leeds could satisfy both the demands for a statement signing and stay within Premier League homegrown squad limits by bringing English winger Jadon Sancho into their inevitable ascension to the top-flight.
MORE FOOTBALL NEWS
POCH PUNTED! Spurs sack manager after horror start to season
THE CANDIDATES: The ‘Special One’, Liverpool greats, the England boss
SOS SPECIAL ONE: Mourinho hot favourite to take over struggling Tottenham
‘NO MANAGER IS SAFE’: Tim Cahill’s shock as world reacts to brutal sacking
Borussia Dortmund have previously admitted the teenager won’t stay in Germany for ever and a rising Leeds side would need to bid at least £100million (A$189m).
But the Qataris have shown that such an amount is small change.
Similarly, Mesut Ozil would be the perfect partner for all-action midfielder Kalvin Phillips with Arsenal not likely to demand a huge transfer fee for the playmaker.
Up top, Eddie Nketiah could join star defender Ben White and make his loan move to Elland Road permanent.
ANALYSIS: The Pochettino project is dead — here’s where it all went wrong
And PSG’s owners moving in to Leeds, which could be sealed after talks this week according to latest reports, may even help them solve a big conundrum back in France.
It is apparent that Neymar and Kylian Mbappe are incompatible as the big star names at Parc des Princes, so why not send the French youngster out to Elland Road to ease the tension - at least on loan?
It’s all a bit fanciful but let’s be honest, it would be one Ell of a side!
This story originally appeared in The Sun and was reproduced with permission.


The following tutorial will show you how a low-cost OPC is represented when using the opcsim software. You will learn how to build a model OPC, how to mimic a calibration for specific aerosols, and how to evaluate the OPC against a simulated aerosol distribution. Visualization tools will also be discussed.
First, we import the python libraries we need and set the styles used for plotting throughout this tutorial.
# Make imports
import opcsim
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mticks
import seaborn as sns
%matplotlib inline
# turn off warnings temporarily
import warnings
warnings.simplefilter('ignore')
# Let's set some default seaborn settings
sns.set(context='notebook', style='ticks', palette='dark', font_scale=1.75,
rc={'figure.figsize': (12,6), **opcsim.plots.rc_log})
The opcsim.OPC
class provides a simple way to model most of the
functionality of low-cost optical particle counters. This model is based
on just a few instrument parameters which should be defined in the
manufacturer’s speficication sheet.
An OPC is defined by just the laser wavelength (wl
), the exact
bins
the OPC uses as its output, and the angles for which the
scattered light is collected between (theta
). Other work has
considered much more detail that this, including the electrical
properties and characteristics of the photodetector, etc. However, this
typically requires knowledge or information that is not commonly
available in the datasheet of a low-cost particle counter, and thus we
try to provide a method that does not rely on this information.
Within the software itself, there is flexibility in how exactly you define the bins. In the end, you will end up with a 3xn array of values, where n is the number of bins. Each bin is then defined by its left bin boundary, midpoint, and right bin boundary.
To simulate an OPC using the opcsim.OPC
class, we initiate as
follows:
opc = opcsim.OPC(wl=0.658, n_bins=5, theta=(32., 88.))
opc
<class 'opcsim.models.OPC'>
When initiated with no arguments, the default arguments are used and can
be looked up in the API documentation. This sets
\(dmin=0.5\;\mu m\), \(dmax=2.5\;\mu m\), and
\(n_{bins}=5\). We can view the number of bins using the
OPC.n_bins
attribute.
opc.n_bins
5
We can also view the bin boundaries and midpoint diameters using the
OPC.bins
attribute. Here, we receieve a 3xn array where the
first entry is the left bin boundary, the middle is the midpoint
diameter as defined by its geometric mean, and the last entry is the
right bin boundary.
opc.bins
array([[0.5 , 0.58730947, 0.68986483],
[0.68986483, 0.8103283 , 0.95182697],
[0.95182697, 1.11803399, 1.3132639 ],
[1.3132639 , 1.54258466, 1.81194916],
[1.81194916, 2.12834981, 2.5 ]])
We can build more complex - or specified - models by increasing the number of bins in a couple of ways: (1) we can change the minimum or maximum cutoffs, or the total number of bins:
opc_10bins = opcsim.OPC(wl=0.658, n_bins=10, dmin=0.38, dmax=17.5)
opc_10bins.bins
array([[ 0.38 , 0.46019969, 0.55732566],
[ 0.55732566, 0.67495025, 0.81739972],
[ 0.81739972, 0.98991341, 1.19883643],
[ 1.19883643, 1.45185303, 1.75826924],
[ 1.75826924, 2.12935514, 2.57875939],
[ 2.57875939, 3.12301123, 3.78212839],
[ 3.78212839, 4.58035343, 5.54704531],
[ 5.54704531, 6.71775925, 8.13555449],
[ 8.13555449, 9.85257798, 11.93198238],
[11.93198238, 14.45024885, 17.5 ]])
If we are trying to model a specific OPC that has pre-defined bins, we can also do that with the help of some utility methods. The bins argument in the OPC class requires a 3xn array as seen above. Often, you may only have the bin boundary information and not the midpoints. We can define the bins as an array of the bin boundaries, where there are 1 more entries than total number of bins, as follows:
opc = opcsim.OPC(wl=0.658, bins=[0.38, 0.54, 0.78, 1.05, 1.5, 2.5])
opc.bins
array([[0.38 , 0.45299007, 0.54 ],
[0.54 , 0.64899923, 0.78 ],
[0.78 , 0.90498619, 1.05 ],
[1.05 , 1.25499004, 1.5 ],
[1.5 , 1.93649167, 2.5 ]])
This more or less covers how we can build various OPC’s - if you are still unsure of what to do in a specific case, feel free to post questions on the GitHub repository under the ‘Issues’ tab.
OPC’s count and size each particle individualy - the size of a particle is determined by the signal amplitude measured by the photo-detector, which is proportional to the product of the intensity of incoming light and the particle’s scattering cross-section. This model assumes light intensity is constant, thus every particle experiences the same light intensity. Assuming this is valid, we can state the size of a particle is proportional ot the scattering cross-section of that particle.
The output we receieve from an OPC is a histogram with the total number of particles in a specified size bin. So how do we know which bin a given particle belongs to? We must calibrate our OPC and tell it, based on the \(C_{scat}\) value, which bin a particle belongs to. While the literature dives deep into complicated, and possibly more accurate ways to do this, we offer three easy methods that can often be found in today’s low-cost devices:
spline
- a simple mapping between \(C_{scat}\) and
\(D_p\)
linear
- fit a power law (linear in log-log space) to the
\(C_{scat}\) values at every bin boundary
piecewise
- the same as linear
except we split into two
different curves
all particles are spheres
light intensity is constant
all particles fall squarely within the laser
We will walk through how to calibrate using each approach, but first, let’s take a look at a typical scattering pattern for an OPC with a 658 nm laser and a collection angle of 32-88 degrees.
# build a generic OPC with 10-bins
opc = opcsim.OPC(wl=0.658, theta=(32.0, 88.0), n_bins=10)
opc
<class 'opcsim.models.OPC'>
# generate an array of particle diameters
dp = np.logspace(-1, 1.25, 250)
vals = [opcsim.mie.cscat(x, wl=0.658, refr=complex(1.59, 0), theta1=32., theta2=88.) for x in dp]
fig, ax = plt.subplots(1, figsize=(6, 6))
ax.plot(dp, vals, lw=3)
ax.semilogx()
ax.semilogy()
ax.set_title("Calibration Curve for PSLs", y=1.02)
ax.set_xlabel("$D_p\;[\mu m]$")
ax.set_ylabel("$C_{scat}$")
sns.despine(offset=5)
As we can see in the figure above, there are \(C_{scat}\) values that are not monotonically increasing as the particle diameter increases, which may make it difficult to assign that value to 1 bin specifically. This is a very well known and documented issue with OPC’s and should play a role in choosing bin boundaries. Additionally, it only gets more complicated as the particle optical properties change!
Now, we will examine the two simple approaches to modeling our ways out of this.
spline
¶One of the most common ways to associate a \(C_{scat}\) value with a corresponding particle size is to use spline interpolation. Essentially, this entails evaluating the \(C_{scat}\) curve at every bin boundary and grouping all \(C_{scat}\) values within range of those two boundaries as belonging to that bin. This work fairly well when the bins are chosen intelligently for a given aerosol type. However, this is not only the case and there are non-monotonically increasing bins from time-to-time. To remove issues associated with this “dips”, we implement a solution where we interpolate across any “dips”. This is far from perfect, but gives us reasonable results.
Note that this can make it quite difficult for particles to get assigned to certain bins, especially if the \(C_{scat}\) values plateau - this can be somewhat solved by combining these bins into one bin to reduce the uncertainty in bin assignment, though it will make the correct particle sizing in that bin less precise as well.
Note that it is also possible to write your own calibration function, so do not fret!
# calibrate using spline
opc.calibrate("psl", method="spline")
# show the Cscat values corresponding to each bin boundary
opc.calibration_function
functools.partial(<bound method OPC._digitize_opc_bins of <class 'opcsim.models.OPC'>>, cscat_boundaries=array([2.86492750e-09, 4.48206290e-09, 5.25272279e-09, 6.02393845e-09,
6.64256044e-09, 9.09772227e-09, 1.08326613e-08, 1.25676003e-08,
1.40492264e-08, 1.99683184e-08, 4.17442631e-08]))
Let’s take a look at the calibration:
fig, ax = plt.subplots(1, figsize=(10, 8))
ax = opcsim.plots.calplot(opc, ax=ax, dp=np.logspace(-1, 1, 250), plot_kws=dict(alpha=.5))
ax.set_xlim(0.1, 10)
ax.set_ylim(1e-10, 1e-6)
sns.despine()
linear
¶The second approach to generating our map of \(C_{scat}\) to \(D_p\) values is to fit a line to the data in log-log space. While this method is simple, and is often used because you only need to calibrate to a few different sizes of particles, it can lead to drastic oversizing in some regions and undersizing in others.
opc.calibrate("psl", method="linear")
opc.calibration_function
functools.partial(<bound method OPC._digitize_opc_bins of <class 'opcsim.models.OPC'>>, cscat_boundaries=array([3.12354813e-09, 3.85694293e-09, 4.76253547e-09, 5.88075700e-09,
7.26153183e-09, 8.96650627e-09, 1.10718009e-08, 1.36714091e-08,
1.68813933e-08, 2.08450672e-08, 2.57393936e-08]))
fig, ax = plt.subplots(1, figsize=(10, 8))
ax = opcsim.plots.calplot(opc, ax=ax, dp=np.logspace(-1, 1, 250), plot_kws=dict(alpha=.5))
ax.set_xlim(0.1, 10)
ax.set_ylim(1e-10, 1e-6)
sns.despine()
piecewise
¶Similarly, we can fit a piecewise
linear fit, where there are two
linear fits, separated based on the \(C_{scat}\) value at a
pre-determined breakpoint as defined by the user.
opc.calibrate("psl", method="piecewise")
opc.calibration_function
functools.partial(<bound method OPC._digitize_opc_bins of <class 'opcsim.models.OPC'>>, cscat_boundaries=array([3.19752250e-09, 3.91392940e-09, 4.79084770e-09, 5.86424010e-09,
7.17812672e-09, 8.46293429e-09, 1.06857637e-08, 1.34924297e-08,
1.70362796e-08, 2.15109384e-08, 2.71608873e-08]))
fig, ax = plt.subplots(1, figsize=(10, 8))
ax = opcsim.plots.calplot(opc, ax=ax, dp=np.logspace(-1, 1, 250), plot_kws=dict(alpha=.5))
ax.set_xlim(0.1, 10)
ax.set_ylim(1e-10, 1e-6)
sns.despine()
Above, we covered the methods used to calibrate, but you may have noticed the first argument to those calls was the material used to calibrate. The calibration material can be defined in one of two ways - you can either choose from a material in the table below or you can specify any complex refractive index. Note that the table below uses approximate literature values which were determined at close to 658 nm. Thus, if you are looking for the best results, you may want to specificy the refractive index of your material at the wavelength of light you are using.
The material lookup table is quite limited - if you would like to add to this table, please open an issue on GitHub.
option |
Material |
Refractive Index |
|---|---|---|
|
Polystyrene Latex Spheres |
1.592 + 0i |
|
Ammonium Sulfate |
1.521 + 0i |
|
Sodium Chloride |
1.5405 + 0i |
|
Sodium Nitrate |
1.448 + 0i |
|
Black Carbon |
1.95 + 0.79i |
|
Sulfuric Acid |
1.427 + 0i |
|
Secondary Organic Aerosol |
1.4 + 0.002i |
|
High estimate for Urban Aerosol |
1.6 + 0.034i |
|
Low estimate for Urban Aerosol |
1.73 + 0.086i |
The entire point of this software is to model how various OPC’s and other particle sensors “see” aerosols in the real world. The Aerosol Distribution tutorial showed how we can model realistic aerosol distributions. This section will review how the OPC’s we just built “see” these distributions. Generally speaking, the process works as follows:
For every particle in the aerosol distribution, we calculate the scattering cross-section
For each of the scattering cross-section’s we just calculated, we assign them to a bin of the OPC based on the calibration curve we generated
We end up with a histogram in the form of the cumulative number of particles in each OPC bin, just as we would if we were using a commercially available OPC
The base method we use to obtain these numbers is OPC.evaluate
. This
method returns the number of particles the OPC “sees” in each bin for a
given aerosol distribution. One component that hasn’t yet been discussed
is how the OPC reacts as relative humidity changes. Each of these
methods takes an argument for relative humidity (rh
) which will
automatically calculate the change in particle size due to hygroscopic
growth per \(\kappa\)-kohler theory; the refractive index and
density will also change accordingly based on the amount of growth that
takes place.
To evaluate a distribution, we need to first define the AerosolDistribution and the OPC.
Show examples for a few different scenarios, including growth due to RH
show examples for different calibration approaches
# build a single mode of ammonium sulfate
d = opcsim.AerosolDistribution("Amm. Sulfate")
d.add_mode(n=1e3, gm=250e-3, gsd=1.65, kappa=0.53, rho=1.77, refr=complex(1.521, 0))
d
AerosolDistribution: Amm. Sulfate
# build an OPC
opc = opcsim.OPC(wl=0.658, n_bins=24, dmin=0.25, dmax=40.)
opc
<class 'opcsim.models.OPC'>
Let’s go ahead and calibrate the OPC using ammonium sulfate:
opc.calibrate("ammonium_sulfate", method="spline")
Now, let’s go ahead and evaluate the OPC for the previously defined distribution. This will return the number of particles in each bin:
vals = opc.evaluate(d, rh=0.0)
vals
array([1.63828722e+02, 1.38275380e+02, 9.79487110e+01, 5.82297216e+01,
2.90517641e+01, 1.21637799e+01, 4.41451983e+00, 1.20624354e+00,
2.21934242e-01, 7.11360375e-02, 7.77406249e-03, 1.70456694e-03,
1.16797839e-04, 4.77037132e-05, 1.81163887e-06, 1.08749418e-07,
6.16523721e-09, 2.34763320e-10, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00])
Another important task for evaluation OPC’s is comparing the integrated
values across some pre-defined particle size range. We can accomplish
this by using the OPC.integrate
method to calculate either the total
number of particles, total surface area, total volume, or total mass
betweeen any two diameters.
Example:
opc.integrate(d, dmin=0., dmax=2.5, weight='number', rh=0.)
505.41153723883406
opc.integrate(d, dmin=0., dmax=2.5, weight='number', rh=85.)
754.771941379744
Last, it is fairly useful and important for us to be able to easily
visualize our results. There are functions built-in to compute the
histogram to use with opcsim.plots.histplot
to easily plot the
particle size distribution.
Let’s go ahead and visualize our results from earlier:
# compute the histogram
data1 = opc.histogram(d, weight="number", base="log10", rh=0.0)
data2 = opc.histogram(d, weight="number", base="log10", rh=95.0)
fig, ax = plt.subplots(1, figsize=(8, 6))
ax = opcsim.plots.pdfplot(d, ax=ax, weight="number")
ax = opcsim.plots.pdfplot(d, ax=ax, weight="number", rh=95.0)
ax = opcsim.plots.histplot(data=data1, bins=opc.bins, ax=ax, label="RH=0%",
plot_kws=dict(linewidth=2, fill=True, alpha=.35, color='blue'))
ax = opcsim.plots.histplot(data=data2, bins=opc.bins, ax=ax, label="RH=95%",
plot_kws=dict(linewidth=2))
ax.set_ylim(0, None)
ax.set_xlim(0.01, None)
ax.legend(bbox_to_anchor=(.7, 1))
sns.despine()
On the left, we have the PDF of the particle size distribution at 0% RH in dark blue with the histogram, as seen by the OPC, in light blue. In dark red, we have the PDF of the particle size distribution at 95% RH - as you can see, it has shifted right substantially. There is also the histogram, shown as red boxes, of how the OPC “see’s” the size distribution at 95% RH. Interestingly, you see the lower part of the distribution (below around 600 nm) simply moves right; however, above that point, the bin assignments start to get screwy. This is due to the Mie Resonance taking hold and making it hard to assign the \(C_{scat}\) value to the correct bin.
One way to gain an underestanding of how reliable/accurate the OPC is is to estimate the range of bins particles of a specific size could be assigned to. For example, if we calibrated our OPC with Ammonium Sulfate at 0% RH, and then only evaluated Ammonium Sulfate at that same RH, we would be fairly confident in our ability to resolve the correct bin. However, if we suddenly were in a more humid environment, how would we do?
There are a fwe metrics
methods available by default to help
understand the expected range of bin assignments - each is detailed
below.
compute_bin_assessment
¶The objective of this method is to assess the ability of an OPC to assign particles to the correct bin. It uses a calibrated OPC to evaluate a material of some refractive index and kappa value at various relative humidities. The method returns a dataframe containing data including: the correct bin assignment, the lower estimate for bin assignment, the upper estimate for bin assignment, the effective refractive index, the relative humidity, and the lower and upper limit’s of scattered light to expected scattered light.
Our primary focus here is estimating the effects of changes in relative humidity, which (1) causes the aerosols to grow as they uptake water and (2) causes the refractive index to change.
rv = opcsim.metrics.compute_bin_assessment(opc, refr=complex(1.521, 0), kappa=0.53)
rv
| bin_hi | bin_lo | bin_true | cscat_hi_ratio | cscat_lo_ratio | refr_eff | rh | |
|---|---|---|---|---|---|---|---|
| 0 | 1 | 0 | 0 | 1.000000 | 1.000000 | 1.521000+0.000000j | 0.0 |
| 1 | 2 | 1 | 1 | 1.000000 | 1.000000 | 1.521000+0.000000j | 0.0 |
| 2 | 3 | 2 | 2 | 1.000000 | 1.000000 | 1.521000+0.000000j | 0.0 |
| 3 | 4 | 3 | 3 | 1.000000 | 1.000000 | 1.521000+0.000000j | 0.0 |
| 4 | 5 | 4 | 4 | 1.000000 | 1.000000 | 1.521000+0.000000j | 0.0 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 67 | 23 | 22 | 19 | 3.542784 | 3.587729 | 1.349983+0.000000j | 95.0 |
| 68 | -99 | 23 | 20 | 3.574876 | 3.542784 | 1.349983+0.000000j | 95.0 |
| 69 | -99 | -99 | 21 | 3.540213 | 3.574876 | 1.349983+0.000000j | 95.0 |
| 70 | -99 | -99 | 22 | 3.352330 | 3.540213 | 1.349983+0.000000j | 95.0 |
| 71 | -99 | -99 | 23 | 3.576379 | 3.352330 | 1.349983+0.000000j | 95.0 |
72 rows × 7 columns
Above, we see that when RH is low and their is little growth or change in refractive index, we mostly do a great job of assigning particles to the correct bin. However, when the RH increases substantially and significant watre uptake occurs, the combination of massive growth in the actual particle size, along with the substantial change in refractive index, leads to massive oversizing which will have large effects when converting from number distribution to volume and/or mass distribution.


CrimPapers
Articles published on 7 August 2020
On 7 August 2020, 11 new articles were published in 11 journals.
Stop and Risk: Policing, Data, and the Digital Age of Discrimination
Using Heat Maps to Identify Areas Prone to Violence Against Women in the Public Sphere by Margarita Garfias Royo, Priti Parikh and Jyoti Belur
The Use of Human Trafficking Detection Data For Modelling Static and Dynamic Determinants of Human Trafficking Flows
Female Sexual Offenders and Offending by Margaret Fitzgerald-O’reilly, Susan Leahy, Catherine O’sullivan, Siobhan Weare
The Veterans Treatment Court Movement: Striving to Serve Those Who Served by Cassandra Atkin-Plunk
Trapped and Resistant Body: Everyday Practices of Women in Taiwan in the Context of Intimate Partner Violence
An Analysis of Question Style and Type in Official Finnish Asylum Interview Transcripts by Jenny Skrifvars,
julia Korkman,
veronica Sui,
tanja Veldhuizen,
jan Antfolk
Development of Online Professional Development For School Resource Officers: Understanding Trauma, Social-Emotional Learning, Restorative Discipline, and Cultural Diversity
Innovation and Transparency in the Recruitment of Women in Australian Policing by Aiyana Ward, Tim Prenzler, Jacqueline Drew
Volunteer Police, Choosing to Serve: Exploring, Comparing, and Assessing Volunteer Policing in the United States and the United Kingdom by Melissa Pepper
Technology-Facilitated Domestic Abuse in Political Economy: A New Theoretical Framework by Elizabeth Yardley


---
layout: post
title: Work work work
date: 2005-10-24 00:00:00
categories: business mobile personal
---
Two work-related announcements:
- Flirtomatic has entered its public beta - go peek! We've been working on this service for almost a year now, there's a lot to it. I'm going to write more about this in the coming months.
- For local folks, we're running a competition for this years dScape event: "send words, pictures and video clips from your mobile phone that represent 'your Brighton' to 07811 407 760". "We're going to need a montage..."


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|---|---|---|---|---|---|---|
| {{client.name}} | {{client.ip}} | {{client.connected?"Yes":"No"}} | {{vm.timeAgo(client.lastConnected)}} | {{client.defaultDashboard}} | {{client.lastConnectedDashboard}} |
|
| Start time | End time | Dashboard | Clients | |
|---|---|---|---|---|
| {{broadcast.startTime | date:'yyyy-MM-dd HH:mm'}} | {{broadcast.endTime | date:'yyyy-MM-dd HH:mm'}} | {{broadcast.dashboard}} | {{vm.formatBroadcastClients(broadcast)}} |


I'm a Front-End Web Developer who thrives on writing clean and elegant code. When I'm not working, pursuing side-projects or getting lost in the rabbit hole of web development, I can be found hiking with my dog and searching for new adventures.
I'm a Front-End Web Developer who thrives on writing clean and elegant code. When I'm not working, pursuing side-projects or getting lost in the rabbit hole of web development, I can be found hiking with my dog and searching for new adventures.
I was born and raised in Towanda, Pennsylvania. Towanda is a small town just south of the New York border in northeastern Pennsylvania. I loved growing up there!
After graduating high school, I decided to go to a college close to home and study accounting. I loved accounting in high school but quickly figured out it wasn't for me in college.
About a year after graduating from college with an accounting degree, I found my true passion of web development. I actually look forward to coding and seeing websites come alive!


This page will probably have failed to load properly (in the JS console), because Rave assumes everything is on the root context.