Experimental study and statistical analysis of system performance parameters of a household freezer
Bibliographic record
Abstract
• The cooling system parameters of a household freezer are evaluated under various input parameters covering door opening effects. • The output parameters related to cooling system performance are frost amount, recovery time and energy consumption. • The recovery time increases more than twice as the ambient temperature rises from 25 °C to 32 °C. • Energy consumption escalates about 5 % from half load to full load cabinet for 30 s door opening at 32 °C and 85 % relative humidity conditions. • There is a 66 % increase in frost amount for the increasing frequency from 20 to 30 s at 32 °C and 85 % relative humidity conditions. The present research comprehensively examines the influences of different input variables, such as cabinet load level, ambient temperature, relative humidity, door opening time and day, on the output parameters of frosting amount, recovery time, and total energy consumption of the upright domestic freezer following the door opening operation. Moreover, a holistic statistical methodology, which is known as the GLM-ANOVA, was implemented for determining the parametric experimental results. Meanwhile, the effects of binary interactions between the input factors on the output parameters were extensively evaluated using statistical methods. As a consequence, the amount of frost increases with an upward gradient as the load level within the cabinet escalates from 25 °C to 32 °C. Both the duration of door openings and the relative humidity level have a double impact on the frosting. Moreover, the duration required for the system to recover from half load to full load more than doubles with an increase in ambient temperature from 25 °C to 32 °C. On the other hand, at an outdoor temperature of 25 °C, the recovery time demonstrates a close to linear relationship with the load level of the cabinet. Furthermore, the duration of door openings and the load capacity within the cabinet are considered two important factors that simultaneously influence the daily energy consumption. The infiltration of ambient air into the freezer compartment and the presence of moisture in the air substantially increase the energy consumption, especially when the relative humidity fluctuates between 30 % and 65 % and the door opening duration stretches from 10 to 20 s, respectively.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".