Ladybug Primer
Ladybug Tools for Grasshopper Documentation
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    • 0 :: Import
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    • 1 :: Analyze Data
      • Construct Data
      • Construct Data Type
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  1. Components
  2. 1 :: Analyze Data

PMV Comfort

PreviousPET ComfortNextUTCI Comfort

Last updated 2 years ago

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Calculate Predicted Mean Vote (PMV).

PMV is a thermal comfort model for use on the interior of buildings where a heating or cooling system is operational. For naturally ventilated buildings, the Adaptive thermal comfort model is recommended and, for outdoor conditions, models such as Universal Thermal Climate Index (UTCI) or Physiological Equivalent Temperature (PET) are recommended.

Inputs

  • air_temp [Required]

Data Collection or individual value for air temperature in C.

  • mrt

Data Collection or individual value of mean radiant temperature (MRT) in C. Default is the same as the air_temp.

  • rel_humid [Required]

Data Collection or individual value for relative humidity in %. Note that percent values are between 0 and 100.

  • air_speed

Data Collection or individual value for air speed in m/s. Default is a very low speed of 0.1 m/s, which is typical of the room air speeds induced by HVAC systems.

  • met_rate

Data Collection or individual value of metabolic rate in met. Default is set to 1.1 met for seated, typing. Typical values include the following.

* 1 met = Metabolic rate of a resting seated person

* 1.2 met = Metabolic rate of a standing person

* 2.4 met = Metabolic rate of a person walking at ~1 m/s (2 mph)
  • clothing

Data Collection or individual value of clothing insulation in clo. Default is set to 0.7 clo for long sleeve shirt and pants. Typical values include the following.

* 1 clo = Three-piece suit

* 0.5 clo = Shorts + T-shirt

* 0 clo = No clothing
  • pmv_par

Optional comfort parameters from the "LB PMV Comfort Parameters" component to specify the criteria under which conditions are considered acceptable/comfortable. The default will assume a PPD threshold of 10% and no absolute humidity constraints.

  • run [Required]

Set to True to run the component.

Outputs

  • report

Reports, errors, warnings, etc.

  • pmv

Predicted Mean Vote (PMV). PMV is a seven-point scale from cold (-3) to hot (+3) that was used in comfort surveys of P.O. Fanger. Each interger value of the scale indicates the following:

* -3 = Cold

* -2 = Cool

* -1 = Slightly Cool

*  0 = Neutral

* +1 = Slightly Warm

* +2 = Warm

* +3 = Hot
  • ppd

Percentage of People Dissatisfied (PPD). Specifically, this is defined by the percent of people who would have a PMV beyond acceptable thresholds (typically <-0.5 and >+0.5). Note that, with the PMV model, the best possible PPD achievable is 5% and most standards aim to have a PPD below 10%.

  • set

Standard Effective Temperature (SET) in Celcius. These temperatures describe what the given input conditions "feel like" in relation to a standard environment of 50% relative humidity, <0.1 m/s average air speed, and mean radiant temperature equal to average air temperature, in which the total heat loss from the skin of an imaginary occupant with an activity level of 1.0 met and a clothing level of 0.6 clo is the same as that from a person in the actual environment.

  • comfort

Integers noting whether the input conditions are acceptable according to the assigned comfort_parameter. Values are one of the following:

* 0 = uncomfortable

* 1 = comfortable
  • condition

Integers noting the thermal status of a subject according to the assigned comfort_parameter. Values are one of the following:

* -2 = too dry (but thermally neutral)

* -1 = cold

*  0 = netural

* +1 = hot

* +2 = too humid (but thermally neutral)
  • heat_loss

A list of 6 terms for heat loss from the human energy balance calculation that underlies PMV. Valeus are in W. The terms are ordered as follows:

- Conduction

- Sweating

- Latent Respiration

- Dry Respiration

- Radiation

- Convection
  • comf_obj

A Python object containing all inputs and results of the analysis. This can be plugged into components like the "Comfort Statistics" component to get further information.

[source code]