Building Performance Simulation - Evidence based analysis

ARCH 753 : BUILDING PERFORMANCE SIMULATION EVIDENCE BASED ANALYSIS

CLIMATE ZONE: 4A

PRIYAL PAREKH

SITE CHOSEN : St. Louis, Missouri

Climate Zone : 4A

Climate type : Humid subtropical

The hot summer season lasts for around 4 from JunetoSept , with an average daily high temperature above 26°C. The hottest month of the year in St. Louis is July, with an average high of 26°C and low of 21°C. The cold season lasts for around 3 months, from NovembertoFebruary , with an average daily high temperature below 10°C.

The coldest month of the year in St. Louis is January, with an average low of 3°C.

The relativity humidity is extremely high most times of the year with rainfall throughout the year high probability in summer months.

Strong winds blow from the north-west and south which are the two main directions need to be shielded from strong winter winds.

WIND ROSE

RELATIVITY HUMIDITY

DEW POINT TEMPERATURE

SPRING SUMMER FALL WINTER

The psychometric chart is a measure to show comfort hours in summer and winter respectively. Being a tropical climate, the summer is much harsher which is why higher discomfort hours exist during these month, the higher humidity adds to this. Passive strategies like occupant cooling with fans, dehumidification, capturing internal heat and correct placement and sizing of openings.

The sun path charts show the sun angles move lower from summer to winter as time of the day progresses. The sun angle moves southward from spring to winter, and the angles get lower as well which makes the south receive the winter sun the most. Moving from east to west throughout the day the east side receives most of the radiation throughout the year. This needs to be shielded from in summer.

SKY DOME

TOTAL RADIATION DIRECT RADIATION DIFFUSE RADIATION

PSYCHOMETRIC CHART ( SUMMER)

PSYCHOMETRIC CHART (WINTER)

SUNPATH

The massing of the building was explored with different floor ratios for the total area. The different options iterated showed good results but the floor plan would get too narrow which would be not an ideal design option.

The aim is to achieve an even distribution of the daylighting metrics, thermal comfort and even energy optimization.

The selected option fulfils these criteria and optimizes a floor ratio of 15 which is oriented towards east-west so the longer facades face north and south and can gain heat from these two mainly.

MASSING STRATEGIES

FLOOR RATIO : 10

The angles in summer are more overhead and northward more steeper angles. The highest temperature sun rays fall from the west direction which is why the west wwr ratio is chosen to be lesser.

The angles during winter moving southward are at a lower angle, more gentler toward the windows. The aim is to bring in the winter sun, desired to allow heat in and make the space warmer passively.

FLOOR RATIO : 15

FLOOR RATIO : 20

FLOOR RATIO : 25

DESIGN MASSING & STRATEGIES

To select the correct ratio for massing for the apartment, and wall window ratio a study of different scenarios by running iterations was run to understand how they would perform in means of occupant thermal comfort and optimize daylighting. These iterations were tested for Useful daylight illuminance and then one ratio was chosen for the massing of the apartment .

DESIGN MASSING & STRATEGIES

• The best option of massing and orientation chosen for this apartment would be along the East west axis.

• This climate has high humidity in winter months - December to February – shading on that side Northwest – lesser WWR

• The South façade can have the highest WWR to allow the winter sun to penetrate inside.

• The west WWR should be smallest or negligible since the strongest wind direction blows so to avoid it into spaces.

• The highest temperature sun rays fall from the west direction which is why the west WWR ratio is chosen to be lesser.

• North can have a lesser WWR than south – summer sun angle

According to these passive design strategies and massing iterations, a WWR was chosen & the program of the spaces was divided accordingly.

• The space is divided to place the office space In the west direction and the main apartment in east.

• The aim was achieve maximum gain from east in the early morning which is optimized with this placement.

• The office is a space used more throughout the day so west façade can be optimized for allowing sunlight during evening timings.

• The total area of 150 sq mts. is divided into a 50 sq meter west office and remainder 100 sq meter bedroom space.

CHOSEN WALL WINDOW RATIOS :

North Façade = 0.4

East Façade = 0.2

South Façade = 0.6

West Façade = 0.2

The daylighting in the above charts is the point in time analysis charts show the distribution of useful daylight in the apartment through different seasons of spring summer & winter. As per the sun angle and solar radiance the lux levels are highest in the spring months during afternoon specially from the south since angles are lower. Shading devices like louvers could help reduce this high amount, but in winter the lux levels are much lower.

BASELINE MODEL

ASSUMPTIONS :

A base model with certain assumptions on its construction type and material property values are taken which creates a scenario to analyze this apartment if it were constructed using a wood framed building.

INPUTS:

2019: ClimateZone4: Wood Framed

R Value – 12

U value : 0.38

SHGC – 0.5

PERCENT OF PEOPLE DISSATISFIED

Average PPD for Apartment 22.21 %

Average PPD for Office = 51.02 %

Construction types : Typical Insulated Wood Framed Exterior Wall-R16 - 25mm Stucco ; 5/8 in. Gypsum Board Typical Insulation-R15 ; 5/8 in. Gypsum Board

PREDICTED MEAN VOTE

Average PMV for Apartment : -0.501858 (in the slightly cool range)

Average PMV for Office = -0.91478 (extreme during both seasons)

BASELINE ENERGY ANALYSIS

TOTAL LOADS

Due to being a tropical climate most of the loads are heating and cooling, mostly through mechanical ventilation. These can be reduced through various passive strategies. The thermal load charts show that most of the energy consumed is due to heating loads in winter which cause more than 50% of the total energy used throughout the year.

TOTAL EUI = 424.611kWh/m2

Heating=254.167kWh/m2

Cooling=99.278kWh/m2

Interior Lighting=12.889kWh/m2

Electric Equipment=34.167kWh/m2

Water Systems=24.111kWh/m2

HEATING ENERGY CHART

COOLING ENERGY CHART

THERMAL LOAD BALANCE CHART

MONTHLY BALANCE CHART - Office

MONTHLY BALANCE CHART - Apartment

ITERATIONS: WITH LOUVERS

A couple of iterations were tried to test the most optimum louver depths along with the north wwr sine it receives summer sun, the loads were monitored.

OPTIMIZATION

This option uses a lightweight construction technique of a steel frame and minimal north openings had a barely any difference on the results of percent dissatisfied but the Eui ends up increasing which is why this option is not desired

This option with deeper 600mm louvers uses the same construction technique of wooden framed structure which brings a good amount of useful daylight inside the space but it does not reduce the EUI infact increases it which is why this option is not preferred to.

HB Construction Types : Metal Building

North WWR : 0.2

Louvers Depth : 0.30M

EUI : 452.889

PPD_1 : 22.464798

PPD_2 : 55.456388

UDI - APARTMENT : 59.652

UDI - OFFICE : 62.2615

HEATING LOAD : 91.278

COOLING LOAD : 12.889

INTERIOR LIGHTING LOAD : 34.167

HB Construction Types : Wood Framed

North WWR : 0.2

Louvers Depth : 0.60M

EUI : 450.833

PPD_1 : 22.460799

PPD_2 : 55.454632

UDI - APARTMENT : 66.061286

UDI - OFFICE : 67.9225

HEATING LOAD : 86.278

COOLING LOAD : 12.889

INTERIOR LIGHTING LOAD : 34.167

OPTIMIZATION

This option uses a lightweight construction technique of a steel frame and minimal north openings and brings about less Eui with the least percent dissatisfied and high daylight illuminance which is a preferred scenario.

This option uses a lightweight construction technique of a steel frame and minimal north openings and brings about less Eui with the least percent dissatisfied and high daylight illuminance which is a preferred scenario.

HB Construction Types : Steel Framed

North WWR : 0.2

Louvers Depth : 0.45M

EUI : 451.722

PPD_1 : 22.450766

PPD_2 : 55.453561

UDI - APARTMENT : 62.936286

UDI - OFFICE : 65.076167

HEATING LOAD : 88.611

COOLING LOAD : 12.889

INTERIOR LIGHTING LOAD : 34.167

HB Construction Types : Steel Framed

North WWR : 0.2

Louvers Depth : 0.60M

EUI : 450.833

PPD_1 : 22.460799

PPD_2 : 55.454632

UDI - APARTMENT : 66.126857

UDI - OFFICE : 67.772833

HEATING LOAD : 86.278

COOLING LOAD : 12.889

INTERIOR LIGHTING LOAD : 34.167

OPTIMIZATION

The results from the first optimization were not as expected and did not reduce the EUI to a great extent which has been the goal of the entire process. Another round of iterations was run to create and optimize by changing the material properties. The chosen modifiers were the R value of walls and interior ceiling and floors and U value for window glass material.

The R values were modified from a range of 12 to 16 and the U value is from 1.82 Kwh/-m to 1.94 kwh-/m which along with a couple of WWR options to understand the best possible option.

The optimization aim is to produce the lease EUI, to keep PPD to the least , highest UDI and Daylight autonomy and least heating & cooling eui’s.

OPTIMIZATION – PART 2

HB Construction Types : Metal Building

North WWR : 0.2

East WWR : 0.2

South WWR : 0.4

R value : 12

U Factor : 1.81

EUI : 411.778

PPD_1 : 51.026088

PPD_2 : 22.654792

UDI - APARTMENT : 52.231

UDI - OFFICE : 55.862833

DA : 98.6815

HEATING EUI : 91.722

COOLING EUI : 12.889

INTERIOR LIGHTING EUI : 34.167

OPTIMIZATION – PART 2

This option optimises the performance of the bedroom and office both by causing a significant decrease in Eui. The UDI levels are also high with less dissatisfied percent which brings about an optimum result. The monthly load charts show a decrease In the cooling loads as well compare to the baseline model.

ANNUAL LOAD BALANCE CHART

MONTHLY LOAD BALANCE CHART

CONCLUSION

It is observed that in the optimized version the end results by modifying the R value, U value and choosing optimum values of wall window ratios the end results are improved versions from the baseline model.

CHOSEN CASE BASELINE CASE

The optimized option in which the heating and cooling loads evidently reduce

TOTAL EUI = 406.333 kWh/m2

Heating=249.222kWh/m2

Cooling=85.944kWh/m2

Interior Lighting=12.889kWh/m2

Electric Equipment=34.167kWh/m2

Water Systems=24.111kWh/m2

The heating loads are quite high adding most to the total end use intensities

TOTAL EUI = 424.61 kWh/m2

Heating = 254.16 kWh/m2

Cooling = 99.27 kWh/m2

Interior Lighting = 12.88 kWh/m2

Electric Equipment = 34.16 kWh/m2

Water Systems=24.111 kWh/m2