45 molecular-modeling-or-molecular-dynamic-simulation PhD positions at Cranfield University
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will dynamically adjust turbine parameters such as yaw, pitch, and torque to maximize Annual Energy Production (AEP) while minimizing component stress. Additionally, a hybrid predictive maintenance model
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make
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targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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Computing Strategies: Develop algorithms that dynamically adjust computing resources to minimize energy usage without compromising performance. Thermal Management Techniques: Design systems that effectively