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Knock is a major bottleneck to achieving higher thermal efficiency in spark ignition (SI) engines. The overall tendency to knock is highly dependent on fuel anti-knock quality as well as engine operating conditions. It is, therefore, critical to gain a better understanding of fuel-engine interactions in order to develop robust knock mitigation strategies. In the present work, a numerical model based on three-dimensional (3-D) computational fluid dynamics (CFD) was developed to capture knock in a Cooperative Fuel Research (CFR) engine. For combustion modeling, a hybrid approach incorporating the G-equation model to track turbulent flame propagation, and a homogeneous reactor multi-zone model to predict end-gas auto-ignition ahead of the flame front and post-flame oxidation in the burned zone, was employed.

The Environmental Control System (ECS) of an aircraft provides thermal and pressure control of the engine bleed air for comfort of the crew members and passengers onboard. For safe and reliable operation of the ECS under complex operating environments, it is critical to detect and diagnose performance degradations in the system during early phases of fault evolution. One of the critical components of the ECS is the heat exchanger, which ensures proper cooling of the engine bleed air. This paper presents a wavelet-based fouling diagnosis approach for the heat exchanger.

This paper addresses the issues of Fault Detection and Isolation (FDI) in complex networked systems such as the Environmental Control System (ECS) of an aircraft. The ECS controls and supplies pressurized air to the aircraft and consists of multiple subsystems that in turn consist of interconnected components, heterogeneous sensing devices, and feedback controllers. These complex interconnections and feedback control loops make fault detection and isolation a very challenging task in the ECS. For example, a faulty component yields off-nominal outputs which are inputs to the other coupled components. This coupling leads to off-nominal outputs from otherwise healthy components, thus causing unwanted false-alarms. Secondly, due to off-nominal inputs, the healthy components are driven beyond their normal operating conditions, leading to cascading failures.