Engineering topics
Radaideh, Majdi I. (ORCID:0000000227430567)
Publications and source records attributed to Radaideh, Majdi I. (ORCID:0000000227430567).
Multistep Criticality Search and Power Shaping in Nuclear Microreactors with Deep Reinforcement Learning
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Distance preserving machine learning for uncertainty aware accelerator capacitance predictions
Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.
Operational data for fault prognosis in particle accelerators with machine learning
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Thermal Modeling of an eVinci™-like heat pipe microreactor using OpenFOAM
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Real electronic signal data from particle accelerator power systems for machine learning anomaly detection
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Bayesian inverse uncertainty quantification of the physical model parameters for the spallation neutron source first target station
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