Figure 1: A screenshot of the Psychrometric Chart app running within a web browser.

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The terms psychrometry and psychrometrics refer to the study of moist air and its thermodynamic properties. Whilst obviously important in the design of air-conditioning systems, these same thermodynamic properties are key determinants of thermal comfort within a building, which makes psychrometrics an important part of any passive and/or climate-responsive design process.

Getting Started

When it first starts up, the app displays a standard empty psychrometric chart. You can choose to add or remove axis lines for a range of different metrics, or even highlight individual axis lines in red to assist with dynamic explanations or interactive presentations. You can do this using the checkboxes and highlight buttons in the CHART METRICS panel located on the left side of the chart.

You can select any metric line to highlight.
Figure 2a: You can visually highlight any metric line.
Or choose which metric lines to show or hide.
Figure 2b: You can also turn on/off any metric lines.

You can then import a weather data file or even the output from an EnergyPlus/OpenStudio annual hourly simulation run. To do this, either drag/drop the required .EPW or .CSV file into the browser window containing the psychro-chart application or select the Load EPW… or Load CSV… buttons in the DATA MAPPING panel.

Once loaded, you can display the data using a grid, as individual hourly data points, as monthly min/max lines or as a daily outline, as shown in Figure 3. This can done using the selector in the DATA MAPPING panel or in the SELECT DISPLAY METRIC dialog box.

Show loaded data as a distributed grid.
Figure 3a: Show loaded data as a distributed grid.
Or as individual hourly data points.
Figure 3b: Or show as individual hourly data points.
Or as monthly mean average min/max lines.
Figure 3c: Or as monthly mean average min/max lines.
r track hourly conditions over any day.
Figure 3d: Or track conditions over the course of a day.

The lines that define each mean monthly average are drawn from the average daily minimum temperature and average daily maximum relative humidity to the average daily maximum temperature and average daily minimum relative humidity. When a metric is displayed, the average minimum daily value is shown at the minimum temperature point and the maximum at the maximum temperature point.

Display Metrics

The default metric displayed when first showing grid data is the frequency distribution of temperature and humidity. This is essentially the number of unique data points within the area of the chart covered by each grid cell. This is always shown in blue and is useful for understanding the range of psychrometric conditions within the data. However, you can also choose to map any other metric in the data, which you can set using the SELECT DISPLAY METRIC dialog box. This information is shown using a different colour scale.

The data grid defaults to temperature/humidity distribution.
Figure 4a: The default data grid metric is the frequency distribution of temperature and humidity.
Temperature/humidity distribution mapped over the chart.
Figure 4b: This is shown as the number of hourly data points within each grid cell.
However you can map any weather data metric.
Figure 4c: You can choose to map any weather metric, from solar radiation or wind speed to cloud cover.
For example, the average global horizontal solar radiation.
Figure 4d: For example, the average global horizontal solar radiation in each grid cell.

You can also choose to filter the displayed data by date and/or time range using the additional tabs in the SELECT DISPLAY METRIC dialog box, as shown in Figure 5. This also allows you to filter by day of the week, which can be important for buildings with very specific weekday or weekend occupancy. It is also possible to display an interactive date range selector beneath the chart by checking the Show Date Range Selector checkbox in the DATA MAPPING panel.

Another useful option is to filter by the value of an additional metric different to the one being displayed. For example, you could display wind speeds only during daylight hour by setting the value filter to Global Horizontal Solar Radiation and being for values above 25W/m2, or only when the Wind Direction is between 45 and 135 degrees.

Filtering by date/time range and day of the week.
Figure 5a: Filtering by date/time range and day of week.
Filtering by a completely different metric.
Figure 5b: Filtering by a completely different metric

The final option is being able to select different temperature and humidity metrics for use when position mapping hourly data points. This is particularly useful when analysing EnergyPlus/OpenStudio annual hourly simulation results, allowing you to map data based on the temperature of specific zones or surfaces, or on internal humidity levels instead of outdoor.

Selecting a room-based thermal analysis metric.
Figure 6a: Selecting a room-based analysis metric.
Mapping it against room-based surface conditions.
Figure 6b: Mapping against room-based conditions.

Comfort Overlays

Once you have data displayed, you can then optionally overlay a range of comfort information on top of it. This gives more meaning to the data and, especially with detailed hourly weather values, can potentially give some insight into the most appropriate design responses for that climate. One of the best tools for this is the Givoni-Milne Bioclimatic Chart which shows potential extensions of the comfort zone resulting from building design characteristics such as solar gains, the use of internal thermal mass or heating, cooling and ventilation strategies. To show this overlay, select the Givoni Bioclimatic Chart item in the COMFORT OVERLAY panel.

You can then overlay comfort information over your data.
Figure 7a: You can then overlay comfort information over the loaded weather data.
This can be done in the relative humidity chart as well.
Figure 7b: This can also be done in the relative humidity chart and mapping the same data.

Having previously taught psychrometrics to architects, I always found it challenging to convincingly explain why the psychrometric chart used humidity ratio or absolute humidity in the vertical axis instead of the more familiar metric of relative humidity, and why it was so important to understand the various metric lines. Thus, one of the reasons for developing this tool was to see if I could morph seamlessly between the standard psychrometric chart and the much simpler relative humidity chart. The hope was that by simply animating back and forth between the two chart types, most of that explanation would become pretty obvious as you get to see clearly almost all of the psychrometric processes change from straight lines under the absolute humidity axis to complex curvilinear lines under relative humidity.

A by-product of this transition is that bioclimatic regions, when viewed against relative humidity, become a reasonably recognisable 90° rotated version of the original Olgyay bioclimatic chart, which helps in understanding the contribution of Givoni and Milne.

Absolute Humidity vs Humidity Ratio

At this point it is probably worth noting the issues associated with using the term absolute humidity to describe the vertical axis. I understand that humidity ratio is probably a more technically correct definition as some argue that absolute humidity is too general as it could potentially be used to cover a range of measures, humidity ratio and vapour pressure included as they are both absolute measures of humidity. However as one of my aims with this tool is to highlight the differences between using relative and absolute humidity, I would argue that it is a widely used term that, as long as the units being used to measure it are clearly displayed, is sufficiently well understood to warrant its use as a lexical counterpoint to relative humidity.

Other Comfort Measures

In addition to the bioclimatic chart, you can also overlay the Heat Index, Predicted Mean Vote (PMV), ASHRAE Standard 55 comfort classes and EN-15251 comfort categories, as shown in Figure 8.

Heat Index contours mapped over the chart.
Figure 8a: Heat Index contours mapped over the chart.
PMV contours mapped over the chart.
Figure 8b: PMV contours mapped over the chart.
The ASHRAE 55 comfort zone overlay.
Figure 8c: The ASHRAE 55 comfort zone overlay.
The EN-15251 comfort categories overlay.
Figure 8d: The EN-15251 comfort categories overlay.

Each of these overlays are generated as contours of an underlying grid of comfort values calculated over the whole chart. You can opt to view this comfort grid by checking the Show Underlying Grid or Show Predicted Mean Vote checkboxes in the COMFORT OVERLAY panel. Additional parameters that govern these comfort values are displayed as dynamic sliders immediately beneath the selector. Press and drag any slider to adjust its value or double-press to display a numeric value editor as a popover.

Process Lines

In addition to comfort data, you can also overlay lines that represent standard psychrometric processes such as sensible heating and cooling or humidification, etc. These lines project from the current indicator position and update automatically and dynamically whenever the indicator position is changed.

Display any standard psychrometric process lines.
Figure 9a: Show standard psychrometric process lines.
Add annotated points for custom process lines.
Figure 9b: Add annotated points for custom processes.

You can also add and edit your own points within the chart to create custom annotated process lines. These can be created manually, saved or imported back in. To create a process line, first position the current indicator where you need it and then press the Add Point button in the PROCESS LINES panel. Do this for each process point to create the line you require. You can press and drag any existing point within the chart or use the EDIT PROCESS POINTS popover to select and edit them manually.

Chart Settings

The app also allows some customisation and refinement of how it is displayed and some of the visual presentation. This includes being able to set the chart extents, titles and data scales, as well as padding and grid cell gaps.

Settings for the axial extents of the chart.
Figure 10a: Settings for the axial extents of the chart.
Overriding the title and subtitle of the chart.
Figure 10b: Overriding the title and subtitle of the chart.
TSetting the chart atmospheric pressure.
Figure 10c: Setting the chart atmospheric pressure.
Adjusting the data overlay scale.
Figure 3d: Adjusting the data overlay scale.
Setting the gap between adjacent grid cells.
Figure 10e: Setting the gap between adjacent grid cells.
Adjusting the edge padding around the chart.
Figure 10f: .Adjusting the padding around the chart.

Change Log

0.0.1 2018-10-30

  • Initial release.

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