High-resolution regional climate–CFD integrated modelling to inform climate responsive design of northern buildings in a changing climate
Bibliographic record
Abstract
In permafrost regions, where climate change poses significant challenges to infrastructure stability, understanding the thermal behaviour of buildings is crucial. This study conducts a detailed investigation into the thermal performance of elevated buildings in permafrost regions within the context of a changing climate. High-resolution regional climate simulation-informed computational fluid dynamics (CFD) models were developed for northern buildings. The findings indicate that the presence of elevated buildings can disrupt the permafrost’s natural thermal equilibrium in the future. This disturbance can extend vertically and horizontally, potentially leading to altered ground temperature gradients and increased air and ground temperatures by 4.25% and 3.85%, respectively. The research findings also highlight a 12.75% reduction in wind speed beneath the study building when transitioning from the local scale ( i.e. , single-building) to the neighbourhood scale ( i.e. with surrounding buildings). These results underscore the critical significance of exploring the neighbourhood scale in building design and planning within permafrost regions, emphasizing the need for comprehensive assessment tools to inform effective strategies and decisions. The holistic approach adopted in this study, sets out a clear vision to guide northern adaptation initiatives that address some of the climate change issues in the buildings’ design by utilizing integrated climate system-built environment modelling. • Developed a computational workflow to assess building thermal impacts on permafrost. • Utilized GEM-driven CFD simulations to evaluate thermal performance under climate change. • Analysed the influence of building and neighbourhood scales on thermal performance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".