...Chaofan Huang; Sunday Aduloju; John Fritz; V. Roshan Joseph; Mark Messner; Timothy Truster A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based...

...Bach Do; Taiwo Adebiyi; Ruda Zhang Bayesian optimization (BO) has become a powerful tool for solving simulation-based engineering optimization problems thanks to its ability to integrate physical and mathematical understandings, consider uncertainty, and address the exploitation–exploration dilemma...

... within a Bayesian optimization algorithm for the self-optimization of its network structure and hyperparameters. The proposed deep learning algorithm is trained using lathe spindle health degradation data collected from an experimental accelerated run-to-failure test rig to evolve an RUL prediction model...

... into the exhibited behavior (as opposed to exhibiting a black-box behavior) remains an open problem. To address this problem, this paper extends the underlying search approach in batch-Bayesian optimization to perform search with embodied swarm agents operating in a (simulated) physical 2D arena. Key contributions...