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Record W4283214396 · doi:10.1002/ese3.1222

Development and heat transfer analysis of thermoelectric self‐powered fuel‐fired residential boiler

2022· article· en· W4283214396 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Science & Engineering · 2022
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsNatural Resources Canada
FundersDepartment of Science and Technology of Sichuan ProvinceChongqing UniversityNational Natural Science Foundation of China
KeywordsThermoelectric generatorBoiler (water heating)Thermoelectric effectCombustionHeat transferFuel efficiencyElectricityProcess engineeringMechanical engineeringElectricity generationAutomotive engineeringEngineeringHeating systemNuclear engineeringElectrical engineeringPower (physics)Waste managementThermodynamics

Abstract

fetched live from OpenAlex

Abstract Solid‐state thermoelectric (TE) devices offer many interesting features compared with other methods of generation, such as no moving parts, high reliability, low maintenance, and straightforward integration with other heating equipment. In this study, a thermoelectric assembly was integrated into a residential heating boiler to convert a portion of combustion heat to electricity while meeting space and/or water heating needs. A prototype was developed, in which recently developed thermoelectric modules were incorporated into a gas‐fired boiler. The electricity generated by the thermoelectric assembly would be sufficient to power the electrical auxiliary components of the heating system. In this way, the heating system could operate entirely on fuel combustion and provide the consumer with heating system reliability and a reduction in power consumption. A model for the thermoelectric conversion system was established and the thermal resistance analysis was carried out to show the influence of heat transfer coefficients and other parameters on power output and efficiency, and thus improve the system design. In this study, the single‐module integrated assembly can produce a 22.5 W power output. However, each module of the four‐/eight‐module integrated assembly can only generate a power output of 7.85/9.175 W on average. The performance of a single module in a multimodule assembly is worse than that of a single module assembly. The number of modules placed on the furnace wall is not as many as possible but has an optimal value. In this experimental environment, the assembly of eight modules is the optimal choice. Furthermore, it is found that enhancing combustion‐side heat transfer capacity is an effective way to promote system performance. The power output of the assembly composed of four modules will increase by 70% from 7.85 to 13.5 W due to the installation of the fin on the hot end.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.194
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it