Depu Lu Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
Research Areas
Biography and Research Information
OverviewAI-generated summary
Depu Lu's research focuses on the application of artificial intelligence and advanced computational methods to address complex problems in thermal engineering and fluid dynamics. His work includes the development of three-dimensional temperature field inversion calculations using artificial intelligence algorithms, as well as temperature field reconstruction of 3D components through neural network-based methods. Lu has investigated experimental studies on multi-evaporator loop heat pipes with dual-layer structure condensers and developed new stacking model methods for inverse flow and heat coupling problems, such as those found in aero-engine turbine blades.
His recent publications also address the practical challenges in hydronic systems, specifically examining the impact of air on pressure loss in vertical pipe sections and modeling performance degradation in recirculated hydronic pumping systems. Lu's scholarship metrics include an h-index of 5, with 15 total publications and 84 total citations. He has collaborated with D. E. Claridge on at least two shared publications.
Metrics
- h-index: 5
- Publications: 15
- Citations: 84
Selected Publications
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Impact of air on vertical pipe sections pressure loss in a re-circulated hydronic system (2025)
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Impact of air on re-circulated hydronic pumping efficiency: Origin of air and performance degradation modeling (2025)
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A new stacking model method to solve an inverse flow and heat coupling problem for aero-engine turbine blades (2024)
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Experimental Study on a Multi-Evaporator Loop Heat Pipe with a Dual-Layer Structure Condenser (2023)
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Three-dimensional temperature field inversion calculation based on an artificial intelligence algorithm (2023)
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Temperature Field Reconstruction of 3d Components Through a Neural Network-Based Method (2022)
Collaborators
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