Skip to content

Artificial intelligence-assisted design and CFD re-optimization of graded hybrid metal foams for faster hydrogen desorption in LaNi5 metal-hydride reactors

Oct 2026 · Frontiers in Energy Research · 0 citations · 43 references

Abstract

Heat delivery limits the discharge rate of LaNi5 metal-hydride reactors. This study develops PG-SADE-GHF to co-design radial foam porosity, CuCr1Zr/AlSi10Mg allocation, and transient heat-transfer/pressure scheduling. The original MATLAB surrogate was used only for inexpensive screening. Its selected coordinates were then evaluated directly in OpenFOAM, and the same eight design variables were re-optimized within the original bounds, followed by an expanded-bound sensitivity study. Surrogate accuracy was assessed using 32 OpenFOAM development designs and 12 additional Sobol/maximin designs whose predictions were frozen before their CFD outcomes were computed. A CFD-corrected multifidelity model was then evaluated, and the optimized designs were verified with full-360-degree OpenFOAM calculations on a 196,608-cell mesh. The screening surrogate predicted td = 7.95 min, whereas direct OpenFOAM evaluation of the same coordinates gave 12.192 min. Re-optimization within the original bounds reduced td to 7.817 min, 21.83% faster than the 10-min CuCr1Zr-89% reference, while the expanded-bound sensitivity reached 6.442 min. On the locked held-out challenge, the original surrogate yielded RMSE = 3.354 min and MAE = 3.143 min; the CFD-corrected model achieved R2 = 0.982, RMSE = 0.159 min, MAE = 0.121 min, Spearman rho = 0.986, and 100% coverage of the nominal 95% prediction intervals. Full-360-degreeverification gave 7.8083 min for the original-bound design and 6.4417 min for the expanded design. Reliable acceleration of LaNi5 desorption requires simultaneous structure-material-operation co-design together with explicit high-fidelity discrepancy correction. Final optimum values are therefore based on direct OpenFOAM calculations rather than the screening surrogate. Experimental validation remains required.

Read PDF

Similar papers

#artificial intelligence Conference Open access Jun 2018

Gibson Env: Real-World Perception for Embodied Agents

This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.

F. Xia, Amir Zamir, Zhi-Yang He et al. · 1,069 citations · ⚡112
#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17

KTO: Model Alignment as Prospect Theoretic Optimization

This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al. · 195 citations · ⚡28
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Review Nov 2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...

Masoud Mohseni, Artur Scherer, K. Johnson et al. · 121 citations · ⚡9

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.