Embodied Energy and Lifecycle Costs: Questioning (Mis)conceptions about Underground Construction
Bibliographic record
Abstract
In the construction community, underground construction is perceived as being significantly more costly and more energy-consuming than comparable surface construction. Although the literature is scarce, studies that have attempted to quantify this difference tend to compare built projects in heterogeneous conditions. The objective of this article is to present the results of life cycle cost and energy consumption simulations conducted as part of the Deep City project at the École Polytechnique fédérale de Lausanne in Switzerland. This article begins by examining the preconceptions the construction industry seems to have about underground construction as reported in the press from 2007 to 2017. Then, we present the method and results of two unpublished studies on the differences in costs and energy consumption of a hypothetical commercial building project in two different geological contexts. We find that energy consumption can be 15% higher but also 4% lower. We also find that underground construction in unconsolidated sediment ground is approximately 23% more expensive, while only 10% in bedrock, which is significantly lower than the 200% to 300% differentials reported in previous studies. We attribute this to the level of detail of our studies, the inclusion of ground conditions, and conclude that our results help to dispel certain misconceptions about underground construction, which can contribute positively to urban sustainable development goals.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".