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Record W4401180612 · doi:10.18280/mmep.110715

Biodegradable Automated Thermal Container Using Peltier Technology

2024· article· en· W4401180612 on OpenAlexvenueno aff
Abhirup Sarkar, Ayushman Khetan, Priti Shahane, R Harikrishnan, Gayatri Phade, Gouri Morankar

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsnot available
Fundersnot available
KeywordsContainer (type theory)ThermalMaterials scienceComputer scienceComposite materialPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Logistics today has been an integral part of the world, responsible for major trades of goods, medicines, products, and services.However, logistics face a big problem when it comes to goods that require a constant or a near about temperature to be maintained while being on the road.Using a temperature control system can help largely reduce the problem, thus saving time, money, and resources.The proposed container can be used to store temperature sensitive items such as medicines or general purpose/day to day items or food and beverages.In this paper, we discuss a temperature-controlled container that can be used to transport such temperature sensitive items.The main technology being used in the container would be thermoelectric Peltier (TEC).The container shall be user controlled via a keypad accompanied with several safety features such as over temperature protection, emergency shutdown button, display to view the current/set temperatures and have a docked/portable power supply system.The power supply and power converter for the board has been made completely in-house using detailed PCB's.Calculations for the power requirement and its efficiency have been discussed in depth.Such a product shall provide great help to logistics and medical industry.Material of the box (HDPE) could sustain wide temperature changes and the efficiency of the overall system was 70 percent.

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 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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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