Characteristics, design, and optimization of earth-air heat exchangers: A review
Bibliographic record
Abstract
The Earth-Air Heat Exchanger (EAHE), also known as a Ground Source Heat Exchanger (GSHE) or Ground-Air Heat Exchanger (GAHE), is used to condition air in buildings and store thermal energy in a soil volume. Heat transfer within an EAHE system consists primarily of convection between air within buried pipes and conduction within adjacent soil volumes. EAHEs are most commonly employed for cooling in warm areas, with horizontal configurations being more common than vertical ones; however, they are also used for heating and in other configurations. Parameters affecting EAHE performance and cost include pipe diameter, length, and air velocity, as well as pipe material and soil type. The impact of these variables on heat transfer performance is explored. The metrics used to quantify thermal performance are reviewed. The most common are the coefficient of performance (COP) and thermal efficiency. The thermal performance of EAHE systems has been modeled at various levels of complexity. Instances of one-, two-, and three-dimensional modeling approaches, as well as transient and steady-state simulations, are reviewed. Simulation tools such as ANSYS Fluent, COMSOL, and TRNSYS are frequently used, while some studies implement model equations directly in various programming languages. A range of optimization strategies for EAHE design and operation is reviewed. Experimental and numerical studies in the literature are reviewed, highlighting key examples and those that present relevant data suitable for validating future modeling studies. Finally, current research gaps are identified, and focus areas for future EAHE research are presented. • A comprehensive review of EAHE design layouts and configurations is presented. • Key design parameters influencing thermal performance and cost are identified. • Energy modeling techniques and simulation tools used for EAHE analysis are examined. • Design and operational optimization strategies for enhancing EAHE performance are reviewed. • Energy performance metrics for technical and economic evaluation of EAHEs are summarized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".