Many researchers believe multi-zone (MZ), chemical kinetics–based models are proven,
essential toolchains for development of low-temperature combustion (LTC) engines …

Prognostics and health management (PHM) is crucial in the lifecycle monitoring of a product,
especially for complex equipment working in a harsh environment. In order to improve the …

Uncertainty quantification (UQ) in scientific machine learning (SciML) becomes increasingly
critical as neural networks (NNs) are being widely adopted in addressing complex problems …

Many studies have been published on the performance and optimisation of the Brayton
cycle and solar thermal Brayton cycle showing the potential, merits and challenges of this …

Fault diagnosis is required to ensure the safe operation of various equipment and enables
real-time monitoring of associated components. As a result, the demand for new cognitive …

Compared with the diesel engine with variable nozzle turbocharger, the performance and
economy characteristics of diesel engine without variable nozzle turbocharger are …

A numerical optimization model is developed to simulate the performance of a large four-
stroke marine turbocharged diesel engine along the entire operating range by finding the …

In this paper, central composite design (CCD) based on Design of Experiment (DoE) is
applied to obtain an optimal design of the vane geometry for a variable geometry turbine …

Copper is one of China's strategic mineral resources, and its supply security is of great
strategic significance to China. In this study, a model of China's copper resource supply …

This paper presents a physics-informed neural network (PINN) approach for monitoring the
health of diesel engines. The aim is to evaluate the engine dynamics, identify unknown …