IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p10520-d640742.html
   My bibliography  Save this article

A Model Based System Commissioning Approach for Nuclear Facilities

Author

Listed:
  • Alan Gaignebet

    (Laboratoire des Sciences des Risques (LSR), IMT Mines Ales, 30100 Alès, France)

  • Vincent Chapurlat

    (Laboratoire des Sciences des Risques (LSR), IMT Mines Ales, 30100 Alès, France)

  • Gregory Zacharewicz

    (Laboratoire des Sciences des Risques (LSR), IMT Mines Ales, 30100 Alès, France)

  • Victor Richet

    (ASSYSTEM Energy and Operation Services, 92400 Courbevoie, France)

  • Robert Plana

    (ASSYSTEM Energy and Operation Services, 92400 Courbevoie, France)

Abstract

Commissioning is considered as a critical phase in the delivery of a Nuclear Facility (NF) as it is the first stage in the authorization of the NF to be exploited. Most of the nuclear projects start to overrun costs during commissioning mainly since this phase is not addressed properly and is affected by many issues from previous phases (Design, Procurement, and Construction). This article proposes a general methodology to prepare and realize the commissioning activities. Using models to do so improves communication and removes ambiguities between stakeholders. It also formalizes and clarifies the commissioning organization and activities prior to any implementation. It also allows for capitalizing and sharing the experience from previous projects, by drawing references models and good practices patterns. The so-called Model Based commissioning method is elaborated around concepts, languages, processes, tools, and patterns inspired from Model Based System Engineering (MBSE) principles and practices. The theoretical foundations will be supported by results from nuclear facilities demonstrating the added value.

Suggested Citation

  • Alan Gaignebet & Vincent Chapurlat & Gregory Zacharewicz & Victor Richet & Robert Plana, 2021. "A Model Based System Commissioning Approach for Nuclear Facilities," Sustainability, MDPI, vol. 13(19), pages 1-21, September.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10520-:d:640742
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/10520/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/19/10520/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. F. Pfister & V. Chapurlat & M. Huchard & C. Nebut & J.‐L. Wippler, 2012. "A proposed meta‐model for formalizing systems engineering knowledge, based on functional architectural patterns," Systems Engineering, John Wiley & Sons, vol. 15(3), pages 321-332, September.
    2. Hyunsoo Lee & Woo Chang Cha, 2019. "Virtual Reality-Based Ergonomic Modeling and Evaluation Framework for Nuclear Power Plant Operation and Control," Sustainability, MDPI, vol. 11(9), pages 1-16, May.
    3. Edwin Thomas Banobi & Wooyong Jung, 2019. "Causes and Mitigation Strategies of Delay in Power Construction Projects: Gaps between Owners and Contractors in Successful and Unsuccessful Projects," Sustainability, MDPI, vol. 11(21), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Usman Ismaila & Wooyong Jung & Chan Young Park, 2022. "Delay Causes and Types in Nigerian Power Construction Projects," Energies, MDPI, vol. 15(3), pages 1-16, January.
    2. Arturo Realyvásquez-Vargas & Karina Cecilia Arredondo-Soto & Julio Blanco-Fernandez & Joanna Denisse Sandoval-Quintanilla & Emilio Jiménez-Macías & Jorge Luis García-Alcaraz, 2020. "Work Standardization and Anthropometric Workstation Design as an Integrated Approach to Sustainable Workplaces in the Manufacturing Industry," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    3. Italo Masiello & Romain Herault & Martin Mansfeld & Maria Skogqvist, 2022. "Simulation-Based VR Training for the Nuclear Sector—A Pilot Study," Sustainability, MDPI, vol. 14(13), pages 1-14, June.
    4. Francesco Costantino & Andrea Falegnami & Lorenzo Fedele & Margherita Bernabei & Sara Stabile & Rosina Bentivenga, 2021. "New and Emerging Hazards for Health and Safety within Digitalized Manufacturing Systems," Sustainability, MDPI, vol. 13(19), pages 1-35, October.
    5. Behrouz Sefid‐Dashti & Jafar Habibi, 2014. "A Reference Architecture for Mobile SOA," Systems Engineering, John Wiley & Sons, vol. 17(4), pages 407-425, December.
    6. da Cunha, Richard Alex & Rangel, Luís Alberto Duncan & Rudolf, Christian A. & Santos, Luiza dos, 2022. "A decision support approach employing the PROMETHEE method and risk factors for critical supply assessment in large-scale projects," Operations Research Perspectives, Elsevier, vol. 9(C).
    7. Marija Z. Ivanović & Đorđe Nedeljković & Zoran Stojadinović & Dejan Marinković & Nenad Ivanišević & Nevena Simić, 2022. "Detection and In-Depth Analysis of Causes of Delay in Construction Projects: Synergy between Machine Learning and Expert Knowledge," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    8. Sławomir Biruk & Piotr Jaśkowski & Magdalena Maciaszczyk, 2022. "Conceptual Framework of a Simulation-Based Manpower Planning Method for Construction Enterprises," Sustainability, MDPI, vol. 14(9), pages 1-13, April.
    9. Angelo Corallo & Maria Elena Latino & Marta Menegoli & Biagia De Devitiis & Rosaria Viscecchia, 2019. "Human Factor in Food Label Design to Support Consumer Healthcare and Safety: A Systematic Literature Review," Sustainability, MDPI, vol. 11(15), pages 1-14, July.
    10. He Zhao & Qin Heng Zhao & Beata Ślusarczyk, 2019. "Sustainability and Digitalization of Corporate Management Based on Augmented/Virtual Reality Tools Usage: China and Other World IT Companies’ Experience," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    11. Carlos Araújo-Rey & Miguel A. Sebastián, 2021. "An Approach to the Analysis of Causes of Delays in Industrial Construction Projects through Planning and Statistical Computing," Sustainability, MDPI, vol. 13(7), pages 1-21, April.
    12. Qi Liu & Jie Zhao & Youguo Shao & Libin Wen & Jianxu Wu & Dichen Liu & Yuhui Ma, 2019. "Multi-Power Joint Peak-Shaving Optimization for Power System Considering Coordinated Dispatching of Nuclear Power and Wind Power," Sustainability, MDPI, vol. 11(17), pages 1-23, September.
    13. Umer Zaman & Laura Florez-Perez & Saba Abbasi & Shahid Nawaz & Pablo Farías & Mahir Pradana, 2022. "A Stitch in Time Saves Nine: Nexus between Critical Delay Factors, Leadership Self-Efficacy, and Transnational Mega Construction Project Success," Sustainability, MDPI, vol. 14(4), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10520-:d:640742. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.