842 research outputs found

    Spatially varying fuzzy multi-scale uncertainty propagation in unidirectional fibre reinforced composites

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    SN and SS are grateful for the support provided through the Lloyd’s Register Foundation Centre. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.Peer reviewedPostprin

    Non-Intrusive Uncertainty Quantification for U3Si2 and UO2 Fuels with SiC/SiC Cladding using BISON for Digital Twin-Enabling Technology

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    U.S. Nuclear Regulatory Committee (NRC) and U.S. Department of Energy (DOE) initiated a future-focused research project to assess the regulatory viability of machine learning (ML) and artificial intelligence (AI)-driven Digital Twins (DTs) for nuclear applications. Advanced accident tolerant fuel (ATF) is one of the priority focus areas of the DOE/ NRC. DTs have the potential to transform the nuclear energy sector in the coming years by incorporating risk-informed decision-making into the Accelerated Fuel Qualification (AFQ) process for ATF. A DT framework can offer game-changing yet practical and informed solutions to the complex problem of qualifying advanced ATFs. However, novel ATF technology suffers from a couple of challenges, such as (i) Data unavailability; (ii) Lack of data, missing data; and (iii) Model uncertainty. These challenges must be resolved to gain the trust in DT framework development. In addition, DT-enabling technologies consist of three major areas: (i) modeling and simulation (M&S), covering uncertainty quantification (UQ), sensitivity analysis (SA), data analytics through ML/AI, physics-based models, and data-informed modeling, (ii) Advanced sensors/instrumentation, and (iii) Data management. UQ and SA are important segments of DT-enabling technologies to ensure trustworthiness, which need to be implemented to meet the DT requirement. Considering the regulatory standpoint of the modeling and simulation (M&S) aspect of DT, UQ and SA are paramount to the success of DT framework in terms of multi-criteria and risk-informed decision-making. In this study, the adaptability of polynomial chaos expansion (PCE) based UQ/SA in a non-intrusive method in BISON was investigated to ensure M&S aspects of the AFQ for ATF. This study introduces the ML-based UQ and SA methods while exhibiting actual applications to the finite element-based nuclear fuel performance code

    Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction

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    Computationally efficient and trustworthy machine learning algorithms are necessary for Digital Twin (DT) framework development. Generally speaking, DT-enabling technologies consist of five major components: (i) Machine learning (ML)-driven prediction algorithm, (ii) Temporal synchronization between physics and digital assets utilizing advanced sensors/instrumentation, (iii) uncertainty propagation, and (iv) DT operational framework. Unfortunately, there is still a significant gap in developing those components for nuclear plant operation. In order to address this gap, this study specifically focuses on the "ML-driven prediction algorithms" as a viable component for the nuclear reactor operation while assessing the reliability and efficacy of the proposed model. Therefore, as a DT prediction component, this study develops a multi-stage predictive model consisting of two feedforward Deep Learning using Neural Networks (DNNs) to determine the final steady-state power of a reactor transient for a nuclear reactor/plant. The goal of the multi-stage model architecture is to convert probabilistic classification to continuous output variables to improve reliability and ease of analysis. Four regression models are developed and tested with input from the first stage model to predict a single value representing the reactor power output. The combined model yields 96% classification accuracy for the first stage and 92% absolute prediction accuracy for the second stage. The development procedure is discussed so that the method can be applied generally to similar systems. An analysis of the role similar models would fill in DTs is performed

    Recent developments in metal wire based electro-mechanical impedance technique for structural health monitoring

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    This paper presents an overview of the recent experimental and numerical developments in the field of metal wire based electro-mechanical impedance (MWBEMI) technique for the purpose of structural health monitoring (SHM). MWBEMI approach is a new variant of the EMI technique and has specific advantages, which makes it a preferred technique for certain ceramics and inaccessible locations of the structure. This paper summarizes the experimental investigations for studying the practical aspects of the technique. It then describes a new algorithm for damage localization in 2D structures using minimum number of sensors. The overall results demonstrate strong potential of the MWBEMI approach for improved SHM

    Investigation into metal wire based variant of EMI technique for structural health monitoring

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    Electro mechanical impedance method (EMI) is a newly non-destructive evaluation method which is becoming very famous in the field of structural health monitoring. In this article a new approach is being proposed to effectively detect the initiation and progression of structural damage by the global dynamic electro-mechanical impedance (EMI) techniques. In this context the PZT patches are being used to determine the natural frequency and the strain mode shapes and the electro mechanical admittance signature to facilitate an improved damage assessment. Nowadays the safety issues for the case of composite building materials are getting more importance. The main problem of using EMI method is its brittleness so to overcome from this problem we are using this method by coupling a metal wire with a PZT element. In this method we created progressive damages and deterioration scenarios and we evaluated with the application of the proposed metal wire EMI method

    Metal-wire-based twin one-dimensional orthogonal array configuration of PZT patches for damage assessment of two-dimensional structures

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    This article presents a new field-deployable algorithm harnessing the metal-wire-based variant of the electro-mechanical impedance technique, warranting drastically lesser number of piezo sensors, for damage detection and localization on large two-dimensional structures such as plates. The metal-wire-based approach is a new variant of the electro-mechanical impedance technique. Although less sensitive than the conventional electro-mechanical impedance technique, it is a panacea in situations where direct bonding of lead zirconate titanate (PZT) patches on the host structure is not possible, such as inaccessible structural locations, parts under continuous impact from external loads, brittle materials (triggering signatures without any peaks) or high-temperature locations. This article first reports detailed experimental investigations into the practical aspects of the metal-wire-based electro-mechanical impedance technique. These cover the effect of various associated parameters, such as the wire cross-section, shape, discontinuity and other related issues. Repeatability of signature is also investigated along with the effect of possible breakage in the wire and inadvertent bending. The technique is further adapted by replacing the wire by a thin foil, which is found to improve the damage sensitivity substantially. The proposed algorithm for damage localization on two-dimensional structures uses the PZT patches in the metal-wire-based orthogonal twin-array configuration. The metal-wire-based electro-mechanical impedance technique is first simulated through finite element method, coupled with the basic impedance model, to test the algorithm on the numerical model of a mild steel plate, 1200 mm×970 mm×8 mm in size. The algorithm is then validated through full-scale test on the actual plate, covering damage at various locations. The developments of this article shall pave way for practical application of the metal-wire-based electro-mechanical impedance technique on large two-dimensional structures with minimum number of sensors, especially in situations where the direct electro-mechanical impedance technique is not feasible to be used.</p

    Effect of size-dependent properties on electromechanical behaviour of composite structures

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    Due to its electromechanical applications in the form of nanodevices such as distributors, actuators, and sensors, the electromechanical behavior of piezocomposite structures becomes a new avenue for research. This article presents the derivation of an exact analytical solution of the composite plate based on theory of Kirchhoff’s plate and extended theory of piezoelectricity. The electromechanical behavior of piezocomposite structures accounting the influence of size-dependent properties such as piezoelectric and surface effect is investigated. In addition to this, the parametric analysis is carried out using the different parameters such as aspect ratio and thickness on the electromechanical response of composite structures. The consequences of the present study explore that the influence of size-dependent properties on the electromechanical behavior of composite structures is noteworthy with respect to the size of structures and can be ignored at bulk sizes. The electromechanical behavior including dynamic response (resonant frequency) of composite plates shows significant enhancement as compared to the conventional composite plate. This current study offers pathways for developing novel composite materials with enhanced control authority and offer guideline for the application and design of nanodevices in energy harvesting. It also highlights the opportunity to evolve high-performance and lightweight micro/nano-electro-mechanical system (M-/NEMS)
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