Numerical investigation and optimization of a hexagonal thermoelectric generator with diverging fins for exhaust waste heat recovery

Energy, Год журнала: 2024, Номер 301, С. 131756 - 131756

Опубликована: Май 23, 2024

Язык: Английский

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Innovative design and numerical optimization of a cylindrical thermoelectric generator for vehicle waste heat recovery

Energy Conversion and Management, Год журнала: 2025, Номер 326, С. 119478 - 119478

Опубликована: Янв. 7, 2025

Язык: Английский

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Performance and parameter prediction of SCR–ORC system based on data–model fusion and twin data–driven

Energy, Год журнала: 2024, Номер 290, С. 130263 - 130263

Опубликована: Янв. 5, 2024

Язык: Английский

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Structure Design and Performance Enhancement of Automobile Thermoelectric Generator System Integrated with a Spoiler

SAE technical papers on CD-ROM/SAE technical paper series, Год журнала: 2025, Номер 1

Опубликована: Янв. 31, 2025

<div class="section abstract"><div class="htmlview paragraph">The thermoelectric generator system is regarded as an advanced technology for recovering waste heat from automotive exhaust. To address the issue of uneven temperature distribution within exchanger that limits output performance system, this study designs a novel generation integrated with turbulence enhancers. This configuration aims to enhance convective transfer at rear end and improve overall uniformity. A multiphysics coupled model established evaluate impact enhancers on system's electrical output, comparing its traditional systems. The findings indicate integration significantly increases rate uniformity exchanger. However, it also leads increase in exhaust back pressure, which negatively affects performance. At lower flow velocities, gains power attributable considerably outweigh pressure. Specifically, under conditions 550 K 20 m/s, power, net coefficient by 39.2%, 33.6%, 8.5%, respectively. As rises, become even more pronounced. Nevertheless, high conditions, rise pressure can potentially degrade Therefore, recommended be appropriately diverted practical applications ensure optimal research provides essential theoretical guidance design optimization systems.</div></div>

Язык: Английский

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Proposing wavy-shaped legs for performance improvement of thermoelectric generators: energy, exergy, environmental, and mechanical analysis using a CFD-trained machine learning method

Thermal Science and Engineering Progress, Год журнала: 2025, Номер 62, С. 103632 - 103632

Опубликована: Апрель 28, 2025

Язык: Английский

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A fully coupled thermal-fluid-electric-mechanics multiphysics numerical model for comprehensive performance evaluation of annular thermoelectric generators

Case Studies in Thermal Engineering, Год журнала: 2025, Номер unknown, С. 106329 - 106329

Опубликована: Май 1, 2025

Язык: Английский

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A review on machine learning driven next generation thermoelectric generators

Energy Conversion and Management X, Год журнала: 2025, Номер unknown, С. 101092 - 101092

Опубликована: Май 1, 2025

Язык: Английский

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AI optimization framework using digital layouts of array structures: A case study for fuel cells

Fuel, Год журнала: 2024, Номер 373, С. 132333 - 132333

Опубликована: Июнь 28, 2024

Язык: Английский

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Study on the Ultimate Load-Bearing Capacity of Disc Buckle Tall Formwork Support Considering Uncertain Factors

Buildings, Год журнала: 2024, Номер 14(3), С. 828 - 828

Опубликована: Март 19, 2024

Disc buckle steel pipe brackets are widely used in building construction due to the advantages of its simple structure, large-bearing capacity, rapid assembling and disassembling, strong versatility. In complex projects, uncertainties affecting stability disc support need be considered ensure safety supports. A surrogate model based on a deep neural network is built trained predict ultimate load-carrying capacity stent. The results finite element calculations form sample set model. Then, we combined computationally efficient DNN with Monte Carlo method consider distribution load bracket under node pin wedge tightness, wall thickness pipe, connection connecting member. At same time, model, SHapley Additive exPlanations (SHAP) interpretability analysis was study degree influence various uncertainty factors bearing practical engineering, tall formwork has shown that predicting buckling characteristic value support. error rate prediction less than 2%. values vary range 17–25. Among bracket, joint tightness greatest impact, followed by bottom top wall-connecting parts.

Язык: Английский

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Shape-performance coupled digital twin based on heterogeneous data from multiple sources: a scissor lift platform example

Engineering With Computers, Год журнала: 2024, Номер unknown

Опубликована: Июль 29, 2024

Язык: Английский

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