How to read expanded performance data
How to interpolate a manufacturer's expanded performance table for the exact design condition, rather than reading the nearest published row as the answer.
What this means
Expanded performance data publishes capacity and other figures only at a fixed grid of tested conditions, entering wet bulb, outdoor temperature, and airflow among them, and a real design condition rarely lands exactly on one of those published rows. Manual S equipment selection requires interpolating between the nearest published points to the actual design condition, not rounding to whichever row sits closest, and airflow is one of the interpolated variables, not a fixed background assumption the table can be read while ignoring.
Equipment and model context
- Manual S equipment selection using manufacturer expanded performance data
- Worked figures illustrate the method and are not a rating for any product
This explains how to interpolate the table correctly and what happens when a design condition falls between published points. It does not select equipment for a specific project. That requires the manufacturer's actual expanded performance data for the model under consideration and the project's actual design conditions and design airflow.
What this covers
- Why reading the nearest published row understates or overstates real capacity.
- How to interpolate between two published rows for a condition that falls between them.
- Why airflow is a variable in the table, not a fixed assumption.
- What happens when a design condition falls outside the table's published range entirely.
What changes the result
- Reading the nearest published row as the answer rather than interpolating between the rows bracketing the actual design condition.
- Interpolating on outdoor temperature or entering wet bulb while leaving airflow at whatever value the nearest row happened to use.
- Extrapolating beyond the table's published range rather than recognising the condition falls outside what the manufacturer tested and rated.
- Applying an interpolated sensible capacity without checking that latent capacity was interpolated using the same method, since the two do not always move together.
Why the table is a grid, not a continuous function
Manufacturers test equipment at a fixed set of conditions, discrete combinations of entering wet bulb, outdoor dry bulb, and airflow, and publish the measured results at each of those combinations as a row or a cell in a table. The table is a grid of tested points, not a continuous curve, and any condition falling between two grid points has no directly published figure at all.
Manual S requires selection against the actual design condition, and where that condition falls between published points, the correct figure is found by interpolation between the bracketing points, not by substituting the value from whichever published point happens to sit nearest. The two can differ meaningfully depending on how far the design condition sits from the nearest row and how steeply capacity changes across that interval.
Why airflow is part of the interpolation, not a fixed backdrop
Expanded performance tables often publish separate blocks or columns for different airflow rates, because capacity depends on airflow as much as it depends on outdoor temperature or entering wet bulb. Reading a row at the design outdoor temperature while ignoring which airflow that row was tested at, or using a different airflow than the system will actually deliver, mismatches the figure to a condition the system will not actually operate at.
A correct reading confirms the table's airflow for the row or interpolated point in use matches the system's actual design airflow, or interpolates across airflow as a third dimension alongside outdoor temperature and entering wet bulb where the design airflow itself falls between published values.
Why sensible and latent capacity need separate interpolation
A cooling coil's sensible and latent capacity do not necessarily change by the same proportion between two published test points, because the underlying physical mechanisms, covered in the sensible heat ratio discussion, respond differently to changes in entering wet bulb and airflow. Interpolating only the total capacity figure and assuming sensible and latent capacity follow the same interpolated ratio can produce an inaccurate answer for whichever one changes more steeply across that interval.
The more reliable approach interpolates sensible capacity and latent capacity as two separate values, each between the bracketing published figures for that specific quantity, rather than interpolating a single total and splitting it afterward by an assumed ratio.
What to do when the design condition falls outside the table
A design condition outside the table's published range, colder, hotter, or at an airflow beyond what was tested, is not a case for extrapolation using the same interpolation method. Extrapolating beyond tested data assumes the equipment's behaviour continues the same trend past the range the manufacturer actually measured, an assumption the manufacturer's own data provides no support for.
The correct response to a design condition outside the published range is contacting the manufacturer for additional data at that condition, selecting different equipment whose published range actually covers the design condition, or in some cases recognising that the specified condition itself needs review, since a condition genuinely outside every available manufacturer's tested range may reflect an unusual project requirement worth revisiting rather than a gap in available data alone.
For one coil's expanded performance data at a fixed airflow, this shows the published capacity at two tested outdoor temperatures and the interpolated value at the actual 92 F design condition that falls between them.
- The table publishes rows at 85 F and 95 F only; the actual 92 F design condition falls between them and has no published row of its own.
- Linear interpolation between the two published points gives 24,630 BTU per hour at 92 F, distinct from either published figure and from a simple rounding to the nearer 95 F row.
- Reading the nearer row, 95 F, would understate capacity by using the more conservative figure by coincidence here; reading the 85 F row instead would overstate it, and neither is the calculated answer.
- The same interpolation has to be performed on latent capacity separately, since sensible and latent capacity do not necessarily move by the same proportion between the two published rows.
| Shortcut taken | What it produces | Correct approach |
|---|---|---|
| Reading the nearest published row | A figure for a condition other than the actual design condition | Interpolate between the two bracketing rows |
| Interpolating temperature while ignoring the row's airflow | A figure that does not match the system's actual design airflow | Confirm or interpolate airflow alongside temperature |
| Interpolating total capacity and splitting by an assumed ratio | Sensible and latent figures that may not reflect actual coil behaviour | Interpolate sensible and latent capacity separately |
| Extrapolating beyond the published range | A figure with no manufacturer data behind it | Obtain additional manufacturer data or select different equipment |
Questions people ask about this
Is linear interpolation always accurate enough for expanded performance data?
Linear interpolation between closely spaced published points is a reasonable approximation for most equipment selection purposes, since manufacturers space test points closely enough in most published tables that the curve between them is close to linear. Where published points are widely spaced or where a capacity is known to behave non-linearly across the interval, checking with the manufacturer for a closer intermediate data point is the more reliable path.
Does selection software handle this interpolation automatically?
Many manufacturer selection software tools perform this interpolation internally when a specific design condition is entered, which is one of the genuine advantages of using the software over reading a printed table by hand. Confirming that the software is actually interpolating, rather than simply reporting the nearest published row, is worth verifying with the specific tool in use rather than assumed.
What if entering wet bulb and outdoor temperature both fall between published rows?
The interpolation becomes two-dimensional, requiring interpolation across both variables rather than one, which is more involved by hand but follows the same underlying principle: find the bracketing published points in both dimensions and interpolate proportionally across each. This is a case where selection software's automatic handling becomes particularly valuable over a manual table read.
Does this level of precision actually matter for residential selection?
The difference between a nearest-row reading and a correctly interpolated figure can be small enough to be immaterial for some selections and large enough to change an equipment choice for others, depending on how far the design condition sits from the nearest published row and how steeply the table's values change across that interval. Checking the actual gap for the specific selection at hand, rather than assuming it is always negligible, is the only way to know which case applies.
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