Thermal Conductivity and Specific Heat Capacity of Insulation materials at Different Mean Temperatures
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
Abstract Thermal conductivity and heat capacity are among the most essential properties of a building insulation in calculating thermal performance which are subjected to change when exposed to temperatures variation in service. Ignoring the temperature dependency of these material properties can result in under and over estimations of buildings energy uses and the corresponding equipment sizing. To obtain more realistic conductivity values of insulation materials, in this paper, thermal conductivity tests are conducted at various mean temperatures. For the study six commonly used insulations including Cellulose fiber, Expanded Polystyrene, Extruded Polystyrene, Open Cell Spray Polyurethane, Polyisocyanurate, and Mineral Wool are considered, and their thermal conductivity are measured at seven mean temperatures ranging from 5°C to 60°C. Furthermore, their specific heat capacity are measured at nine mean temperatures ranging between 16°C and 36°C. The results showed that except Polyisocyanurate board, the thermal conductivities and specific heat capacities of all insulation materials increased linearly with rising temperature, presenting a linear regression model with correlation coefficients (R 2 ) values between 0.96 and 0.98. The curve fitting of the Polyisocyanurate thermal conductivity measurements resulted a nonlinear regression model with R 2 of 0.97. The thermal conductivity of six insulations as a function of temperature have been established.
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) | 0.000 | 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 it