Design and Operational Strategies for Enhancing Thermal Output in Coaxial Closed-Loop Geothermal Systems
Bibliographic record
Abstract
Coaxial closed-loop geothermal systems, increasingly recognized as scalable and low-impact geothermal solutions, remain limited by conductive heat transfer between the reservoir and wellbore. This study investigates three strategies to enhance thermal output: (i) dynamic operation scheduling, (ii) substitution of conventional fluids with Organic Rankine Cycle (ORC) working fluids, and (iii) targeted conductive enhancements near the well. Using a CMG STARS simulation framework, system performance was evaluated over 1- to 20-year horizons, introducing a characteristic thermal recovery curve as a tool for analyzing long-term behavior. Results show that extended recovery durations raise outlet temperatures but with diminishing returns, identifying approximately 80% recovery as a practical optimization point. Fluids such as n-pentane and R245fa deliver substantially greater ORC-compatible heat than water, with thermo-siphoning observed under low-flow conditions. Conductive enhancement geometries, namely ring and fishbone configurations, exhibit distinct performance profiles, with rings outperforming fishbones due to larger injected volumes and greater advantage due to reservoir reach. One-year gains range from 4.5–9.4% for rings and 0.65–1.37% for fishbones, stabilizing at 3.7–7.8% and 0.55–1.18% after 20 years. These findings provide design and operational guidance for advancing coaxial closed-loop systems in low-carbon energy deployment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".