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Manufacturing causes 20% of carbon emission globally and consumes about 54% of global energy generation – this means large scale manufacturers need to understand and address their carbon emission
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useful life of critical assets. Currently, Artificial Intelligence (AI) based big data analytics tools have been massively developed in the research community to address this challenge. These AI-based
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CFD-FEA Combined Thermal-Fluid-Mechanical Modelling for Defect Control in Additive Manufacturing PhD
information, it falls short in providing stress-related data, while the finite element analysis (FEA) is widely used for determining residual stress and distortion, but it has great uncertainty in predicting
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information, it falls short in providing stress-related data, while the finite element analysis (FEA) is widely used for determining residual stress and distortion, but it has great uncertainty in predicting
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used to predict armour performance against threats, known and emerging. Overview Initially, the successful candidate will identify the critical data capture steps for accurate prediction of material
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. These challenges have created an environment where a large return can be accrued from an investment in gas turbines and related power system research and education. It is expected the research will generate new
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offers a rapid inspection while covering a large area within a short time. Therefore, it has been successfully applied to a wide range of areas such as civil engineering, medicine and biology as
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for fast and long traversal in extreme planetary environments Fast and long traversal in extreme planetary environments is required for quality scientific data gathering, unknown region exploration, in-situ
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other words, they are ineffective in understanding that correlation does not imply causation. This design flaw is clearly exemplified by recent large language models such as ChatGPT that are able to mimic
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coefficients. This strategy carries large uncertainty and requires vast amount of expensive and time-consuming experimental data. Worse, sometimes the experimental data is simply inaccessible. The need for cost