Multi-objective optimal design of a near net zero energy solar house
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a multi-objective redesign case study of an archetype solar house based on a near net zero energy (NZE) demonstration home located in Eastman, Quebec. Using optimization techniques, pathways are identified from the original design to both cost and energy optimal designs. An evolutionary algorithm is used to optimize trade-offs between passive solar gains and active solar generation, using two objective functions: net-energy consumption and life-cycle cost over a thirty-year life cycle. In addition, this paper explores different pathways to net zero energy based on economic incentives, such as feed-in tariffs for on-site electricity production from renewables. The main objective is to identify pathways to net zero energy that will facilitate the future systematic design of similar homes based on the concept of the archetype that combines passive solar design; energy-efficiency measures, including a geothermal heat pump; and a building-integrated photovoltaic system. Results from this paper can be utilized as follows: (1) systematic design improvements and applications of lessons learned from a proven NZE home design concept, (2) use of a methodology to understand pathways to cost and energy optimal building designs, and (3) to aid in policy development on economic incentives that can positively influence optimized home design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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 it