Variable Air Volume Hot Water Reheat Terminal Units: Temperature Stratification, Performance at Low Hot Water Supply Temperature, and Myths from the Field
Bibliographic record
Abstract
Hot water coils are common in commercial building HVAC systems. Nevertheless, their design, installation, and control are frequently sub-optimal, with respect to maximizing heat exchange effectiveness and air temperature setpoint control. For example, conditions on-site sometimes lead to coils being installed in parallel flow instead of counter flow configuration, and temperature stratification in the leaving air can lead to control issues. Additionally, low hot water supply temperatures (HWST) of ~120⁰F (49⁰C) are becoming more common with the rise of heat pump and efficiency retrofits. As hot water systems are typically designed for high HWST (160 - 180⁰F, 71 - 82⁰C), lower waterside “delta T” temperature differences (HWST – HWRT) would occur using low HWST in retrofits of conventional hot water heating systems. If buildings retain existing coils for the low-HWST systems common to efficiency retrofits, they will be unable to maintain the same design heat capacity without replacing terminal units. This creates challenges for retrofit projects throughout the industry, and low-HWST designs also present challenges to new construction. We present the background, methods, and findings of an experiment conducted in 2022 at the Price Industries Laboratory in Winnipeg, Canada. In this experiment, we tested multiple VAV HW reheat terminal units across a range of test factors, including VAV box sizes and number of coil rows. The performance of each coil setup was compared at both high and low HWSTs, and at multiple damper positions. We also performed several additional tests to determine the best solutions to common field installation and operation issues and to gauge the impact of varying coil insulation. In addition to tests we ran with stock-manufactured coils, we also ran several tests using coils of our own custom designs, focusing on symmetry and limited circuit count. The intent of these tests was to better understand the factors in VAV HW reheat systems that may be overlooked in typical system design and coil selection processes, especially as parameters such as HWST and water side temperature differences begin to change. Understanding these factors is important to the design and operation of these systems as sub-optimal performance in the terminal unit systems has cascading effects both for retro-fitted low-HWST systems and existing boiler systems. Overall, the results from this experiment serve to inform recommended changes to VAV terminal unit design, selection, and control to improve whole-building performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".