Education

Research Description

Gupta is interested in modeling experimental and analytical behavior of structures, Nonclassically damped primary-secondary systems, Earthquake behavior of electrical instruments and control panels, Buried pipelines, Computer aided engineering.

Publications

Digital Engineering for Integrated Modeling and Simulation for Building-Piping Systems Through Interoperability Solutions

Crowder, N., Lee, J., Gupta, A., Han, K., Bodda, S., & Ritter, C. (2022, May 13), NUCLEAR SCIENCE AND ENGINEERING. https://doi.org/10.1080/00295639.2022.2055705

Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system

Lin, L., Athe, P., Rouxelin, P., Avramova, M., Gupta, A., Youngblood, R., … Dinh, N. (2022), ANNALS OF NUCLEAR ENERGY. https://doi.org/10.1016/j.anucene.2021.108715

A Closed-Form Solution to Characterize the Behavior of Piping T-Joints

Dubey, A. R., Gupta, A., & Cho, S. G. (2021, July 10), INTERNATIONAL JOURNAL OF STEEL STRUCTURES. https://doi.org/10.1007/s13296-021-00511-z

A Methodological Approach to Update Ground Motion Prediction Models Using Bayesian Inference

Bodda, S. S., Keller, M., Gupta, A., & Senfaute, G. (2021, November 30), PURE AND APPLIED GEOPHYSICS. https://doi.org/10.1007/s00024-021-02915-8

Application of Risk-Informed Validation Framework to a Flooding Scenario

Bodda, S. S., Gupta, A., & Sewell, R. T. (2021), ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING. https://doi.org/10.1061/AJRUA6.0001172

Modeling the behavior of reinforced concrete slabs subjected to impact

Patel, P., Bodda, S. S., & Gupta, A. (2021), NUCLEAR ENGINEERING AND DESIGN. https://doi.org/10.1016/j.nucengdes.2021.111512

Seismic Fragility of Piping Nozzles in Nuclear Power Plants: A Case for Updating the Current State-of-Practice

Gupta, A., Dubey, A. R., & Cho, S.-G. (2021), JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME. https://doi.org/10.1115/1.4051136

Seismic response of electrical equipment subjected to high?frequency ground motions

Singh, S., & Gupta, A. (2021), NUCLEAR ENGINEERING AND DESIGN, 374. https://doi.org/10.1016/j.nucengdes.2020.111046

Significance of multi-hazard risk in design of buildings under earthquake and wind loads

Kwag, S., Gupta, A., Baugh, J., & Kim, H.-S. (2021), ENGINEERING STRUCTURES. https://doi.org/10.1016/j.engstruct.2021.112623

Understanding the seismic response of electrical equipment subjected to high-frequency ground motions

Singh, S., & Gupta, A. (2021), PROGRESS IN NUCLEAR ENERGY. https://doi.org/10.1016/j.pnucene.2021.103915

View all publications via NC State Libraries

Grants

Probabilistic and AI/ML Approaches in Structural Engineering, CNEFS Core Project

NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)(1/01/22 - 12/31/22)

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Probabilistic and AI/ML Approaches in Structural Engineering, CNEFS Core Project

Sponsor: NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)

Start Date: 1/01/22

End Date: 12/31/22

Abstract

Over the past decade, the use of artificial intelligence techniques in the field of health-monitoring has gained significant interest, especially for structures such as building and bridges. This project proposes development of an Artificial Intelligence (AI) framework for the data-driven condition monitoring of nuclear structural systems and equipment, where the vibration response is governed by multiple localized modes unlike that in buildings and bridges. Hence, techniques such as signal processing and pattern recognition will be employed to extract degradation-sensitive features. Degraded locations can potentially exhibit damage such as localized yielding, cyclic fatigue, or initiation of cracking. Moreover, such locations can at times go undetected by current inspection techniques. Therefore, this research proposes a framework, which utilizes sensor response to generate an AI database for predicting degraded locations and severity in nuclear structural systems and equipment. Degradation severity will be classified as minor, moderate, and severe, along with incorporation of uncertainty.

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Digital Engineering Solutions in Construction Engineering and Integration with Structural Design and Risk Assessment - CNEFS Core -Project

NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)(1/01/22 - 12/31/22)

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Digital Engineering Solutions in Construction Engineering and Integration with Structural Design and Risk Assessment - CNEFS Core -Project

Sponsor: NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)

Start Date: 1/01/22

End Date: 12/31/22

Abstract

There have been and will continue to be rapid advances in 3D scanning and augmented/virtual reality technologies to improve construction costs and schedules, especially in the nuclear energy industry that has suffered from construction cost escalation and delays. A key challenge faced in the implementation of these modern technologies relates to changes needed in the regulatory practice and approvals. It is vital for regulatory agencies like USNRC to understand the fundamental basis of these technologies and characterize the accuracy and consistency in them. This project is aimed at conducting the research needed to support this effort which would eventually be needed in the near future. More specifically, it is proposed to: (i) characterize technical specifications and the associated parameters that govern the accuracy of virtual inspections, and (ii) identify items at a construction or manufacturing site that are conducive to virtual inspections and the items that are not.

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An Open Source, Parallel, and Distributed Web-Based Probabilistic Risk Assessment Platform to Support Real Time Nuclear Power Plant Risk-Informed Operational Decisions

US Dept. of Energy (DOE)(10/01/21 - 9/30/24)

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An Open Source, Parallel, and Distributed Web-Based Probabilistic Risk Assessment Platform to Support Real Time Nuclear Power Plant Risk-Informed Operational Decisions

Sponsor: US Dept. of Energy (DOE)

Start Date: 10/01/21

End Date: 9/30/24

Abstract

The main objective of the proposed work is to develop, demonstrate, and evaluate a probabilistic risk assessment (PRA) software platform needed to address the major challenges of the current legacy PRA tools, such as better quantification speed, integration of multi-hazard models into traditional PRAs, and model modification simplification and documentation automation. To achieve the main objective, we will first perform benchmarking and profiling of current PRA tools, such as SCRAM and SAPHIRE, to investigate the current bottlenecks in the quantification speed and memory requirements. Secondly, we will design, implement, and benchmark a PRA software platform based on a web-based stack using the latest technologies available to overcome the mentioned challenges. Finally, we will evaluate the performance gains of this framework by modeling and quantifying large PRA models that would have been too expensive to run using the legacy PRA tools.

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Development and Assessment of Digital Twin for Advanced Reactors

US Dept. of Energy (DOE)(8/16/21 - 6/30/24)

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Development and Assessment of Digital Twin for Advanced Reactors

Sponsor: US Dept. of Energy (DOE)

Start Date: 8/16/21

End Date: 6/30/24

Abstract

A DT-DAP (Digital Twin Development and Assessment Process) methodology has been formulated at NCSU in the ARPA-E sponsored project. DT-DAP can be very effective in guiding the design, training, testing, and application of DTs to improve effectiveness, accuracy and acceptance of system design and safety analysis.

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Probabilistic Risk-Informed Approaches in Structural and Earthquake Engineering, CNEFS Enhancement Project

Electricite de France (EDF/DER)(1/01/20 - 12/31/21)

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Probabilistic Risk-Informed Approaches in Structural and Earthquake Engineering, CNEFS Enhancement Project

Sponsor: Electricite de France (EDF/DER)

Start Date: 1/01/20

End Date: 12/31/21

Abstract

In recent years, flooding at nuclear power plants (NPP) has increased emphasis on using high fidelity simulations to evaluate the vulnerability of nuclear plants. One of the key limitations in the use of high fidelity simulations is related to a lack of verification and validation (V&V) of such simulations. One outcome of incomplete and insufficient V&V relates to a large degree of uncertainty in the simulation results which in turn leads to conservative assumptions by the decision makers. Past experience has shown that such conservative assumptions in the context of safety assessment for other external hazards such as seismic have resulted in highly overdesigned NPP systems and excessively high costs. Therefore, it is quite important that various uncertainties in this process are appropriately identified and included through formal uncertainty quantification (UQ). A robust framework for verification and validation is needed to not only include uncertainties but also to formalize the confidence in predictions of system level validation that are based on component level data using Bayesian Network. In addition, the framework has to identify the basic events that are critical in the perspective of overall validation. This process helps in allocating the resources efficiently thereby reducing the effort to conduct high fidelity simulations and large-scale experiments.

Close

Probabilistic Risk-Informed Approaches in Structural and Earthquake Engineering, CNEFS Core Project

NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)(3/01/20 - 12/31/22)

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Probabilistic Risk-Informed Approaches in Structural and Earthquake Engineering, CNEFS Core Project

Sponsor: NCSU Center for Nuclear Energy Facilities and Structures (CNEFS)

Start Date: 3/01/20

End Date: 12/31/22

Abstract

In recent years, flooding at nuclear power plants (NPP) has increased emphasis on using high fidelity simulations to evaluate the vulnerability of nuclear plants. One of the key limitations in the use of high fidelity simulations is related to a lack of verification and validation (V&V) of such simulations. One outcome of incomplete and insufficient V&V relates to a large degree of uncertainty in the simulation results which in turn leads to conservative assumptions by the decision makers. Past experience has shown that such conservative assumptions in the context of safety assessment for other external hazards such as seismic have resulted in highly overdesigned NPP systems and excessively high costs. Therefore, it is quite important that various uncertainties in this process are appropriately identified and included through formal uncertainty quantification (UQ). A robust framework for verification and validation is needed to not only include uncertainties but also to formalize the confidence in predictions of system level validation that are based on component level data using Bayesian Network. In addition, the framework has to identify the basic events that are critical in the perspective of overall validation. This process helps in allocating the resources efficiently thereby reducing the effort to conduct high fidelity simulations and large-scale experiments.

Close

Membership in the Center for Nuclear Energy Facilities and Structures (CNEFS), Full Member

Korea Atomic Energy Research Institute (KAERI)(1/01/20 - 12/31/21)

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Membership in the Center for Nuclear Energy Facilities and Structures (CNEFS), Full Member

Sponsor: Korea Atomic Energy Research Institute (KAERI)

Start Date: 1/01/20

End Date: 12/31/21

Abstract

The Center for Nuclear Energy Facilities & Structures, has been established and is administered by North Carolina State University to conduct research in the areas of structural engineering, mechanics, risk assessment, hazard mitigation, and construction engineering and to promote research, education, and training in the Research Area. The CENTER has developed core research, non-core research, and technology transfer activities.

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Probabilistic Risk Assessment Modeling Using MASTADON

US Dept. of Energy (DOE)(11/15/19 - 3/31/23)

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Probabilistic Risk Assessment Modeling Using MASTADON

Sponsor: US Dept. of Energy (DOE)

Start Date: 11/15/19

End Date: 3/31/23

Abstract

The proposed project builds upon the previous work of CNEFS in which CNEFS helped develop capabilities for Fault Tree Analysis in the Idaho National Lab (INL)’s MASTADON toolkit. The proposed project focuses on the following specific tasks • Extend the fault-tree analysis and quantification to include event-trees • Convert C++ code to MOOSE objects and implement in MASTODON. • Create examples for PRA in MASTODON using the new fault-tree and event-tree quantification implementations • Benchmark examples with Saphire • Document these examples on the MASTODON website

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Membership in Center for Nuclear Energy Facilities and Structures (CNEFS), Full Member

Korea Hydro & Nuclear Power Co., Ltd. (KHNP)(1/01/19 - 12/31/24)

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Membership in Center for Nuclear Energy Facilities and Structures (CNEFS), Full Member

Sponsor: Korea Hydro & Nuclear Power Co., Ltd. (KHNP)

Start Date: 1/01/19

End Date: 12/31/24

Abstract

Full Membership

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BIM for VTR: Holistic Approach to Design and Construction

US Dept. of Energy (DOE)(9/17/18 - 9/30/22)

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BIM for VTR: Holistic Approach to Design and Construction

Sponsor: US Dept. of Energy (DOE)

Start Date: 9/17/18

End Date: 9/30/22

Abstract

Huge escalations in overnight construction costs and schedule delays have rendered nuclear energy commercially unattractive. Much of the research and development has focused on developing new reactor designs with accident tolerant fuels and passive safety systems intended to reduce operating and lifecycle costs. There has been little to no investment in research on nuclear construction management. Moreover, Hopf [1] argues that the primary reasons for construction cost escalation and schedule delays are related to: (i) extremely stringent nuclear safety and quality assurance standards, (ii) inexperience in managing and staffing to nuclear QA standards, (iii) excessive paperwork, and (iv) supply chain delays due to rework. To ensure the success of implementation and deployment of a new reactor (i.e., Versatile Test Reactor (VTR)), design, construction, and testing processes should be integrated. Virtual Design and Construction (VDC) using Building Information Modeling (BIM) has been proven to be a solution that bridges gap between design and construction [cite]. Furthermore, it has been used as a project control tool [cite]. BIM as a central hub of digital data exchange can bring different experts (i.e., engineers with different disciplines and contractors who build and manage construction projects) virtually together. All stakeholders have a shared resources of knowledge to help identify and minimize risk during design, construction, and operation and maintenance phases [cite]. This proposal proposes to investigate and help INL better understand the capabilities of BIM that can support the integration of design, construction, and testing of the VTR. Furthermore, the research team will pick one of the analysis (i.e., pipe stress) and develop a software/plug-in that produces 2D/3D models that can be directed imported by the analysis tool.

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