A population‐level analysis is proposed to address data sparsity when building predictive
models for engineering infrastructure. Utilizing an interpretable hierarchical Bayesian …

Structural health monitoring (SHM) strategies seek to evaluate, predict, and maintain
structural integrity, to improve the safety and design service life of structures in operation …

This work showcases a multi-fidelity approach, which couples experimental techniques with
numerical models within a Bayesian data-driven framework, thus enabling a direct …

To achieve higher thermal efficiency, gas turbines operate at increasingly higher turbine
inlet temperatures, leading to the need for advanced cooling methods such as film cooling …

The flow in gas turbines exhibits a highly unsteady, complex and nonuniform manner, which
presents two main challenges. Firstly, it introduces instrumentation errors, contributing to …

This paper introduces the Bayesian mass average and details its computation. Owing to the
complexity of flow in an engine and the limited instrumentation and the precision of the …

A cost-effective solution to address the challenges posed by sensitive instrumentation in
next-gen turbomachinery components is to reduce the number of measurement samples …

This manuscript outlines an automated anomaly detection framework for jet engines. It is
tailored for identifying spatial anomalies in steady-state temperature measurements at …

This paper proposes a new physics-driven prior structure for engine spatial models. It is
designed to be used on engine measurements, with the objective of obtaining more …

Recent advancements in computing, telecommunications, and metrology have propelled
data-driven decision making across the industries. Industrial health management in …