Abstract: Fracture modeling of metallic alloys with microscopic pores relies on multiscale damage simulations which typically ignore the manufacturing-induced spatial variabilities in porosity. This simplification is made because ...

Abstract: Abstract. Bayesian optimization (BO) is increasingly employed in critical applications such as materials design to find optimal solutions with minimal costs. While BO is known for its sample efficiency, relying solely on ...

Abstract: Emulation plays an important role in engineering design. However, most emulators such as Gaussian processes (GPs) are exclusively developed for interpolation/regression and their performance significantly deteriorates in ...

Abstract: As modern electronic devices are increasingly miniaturized and integrated, their performance relies more heavily on effective thermal management. In this regard, two-phase cooling methods which capitalize on thin-film ...

Abstract: Anomalies are samples that significantly deviate from the rest of the data and their detection plays a major role in building machine learning models that can be reliably used in applications such as data-driven design and ...

Abstract: Abstract. We introduce a simultaneous and meshfree topology optimization (TO) framework based on physics-informed Gaussian processes (GPs). In our approach, we parameterize all design and state variables via GP priors which ...

Abstract: Abstract. Gaussian processes (GPs) are powerful probabilistic models that define flexible priors over functions, offering strong interpretability and uncertainty quantification. However, GP models often rely on simple, ...

Abstract: Abstract. In an increasing number of applications, designers have access to multiple computer models that typically have different levels of fidelity and cost. Traditionally, designers calibrate these models one at a time ...

Abstract: Bayesian optimization (BO) is a sequential optimization strategy that is increasingly employed in a wide range of areas such as materials design. In real-world applications, acquiring high-fidelity (HF) data through physical ...

Abstract: Abstract. Foundation models are at the forefront of an increasing number of critical applications. In regards to technologies such as additive manufacturing (AM), these models have the potential to accelerate process design ...