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Safety, Resilience and Reliability Challenges and Engineering Research in Renewable...
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Safety, Resilience and Reliability Challenges and Engineering Research in Renewable Energies

A special issue of Safety (ISSN 2313-576X).

Deadline for manuscript submissions: 10 November 2024 | Viewed by 6343

Special Issue Editors

Dr. Mohammad Yazdi

E-Mail Website
Guest Editor
School of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
Interests: system safety; reliability, availability, maintainability and safety (RAMS); asset integrity and project management; decision making under uncertainty
Special Issues, Collections and Topics in MDPI journals
Dr. Esmaeil Zarei

E-Mail Website
Guest Editor
1. Department of Safety Science, College of Aviation, Embry-Riddle Aeronautical University, Prescott, AZ 86301, USA 2. Robertson Safety Institute (RSI), Embry-Riddle Aeronautical University, Prescott, AZ 86301, USA
Interests: safety and risk engineering in emerging and complex sociotechnical systems; system safety and human factors/reliability analysis; dynamic risk and accident analysis; risk-based decision making; risk assessment in renewable energy with primarily focus on hydrogen infrastructures
Special Issues, Collections and Topics in MDPI journals
Dr. Sidum Adumene

E-Mail Website
Guest Editor
School of Ocean Technology, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John's, NL, Canada
Interests: maritime safety and risk analysis; accident modeling; program and project ‎management; human factor engineering; offshore renewable energy; risk ‎intelligence; marine operations and asset integrity management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There has been extensive demand and attraction for renewable energies due to their considerable advantages over fossil-based fuels. These include solar, wind, hydro, biomass, and hydrogen energy. However, renewable energy production, transmission, and application are associated with serious safety, resilience, and reliability issues, which need to be examined in life cycle of renewable energies infrastructures to establish resilient and sustainable operations. Considering the unique properties of renewable energies, which are different compared to non-renewable ones, their safety, resilience, and reliability concerns have attracted considerable interest in recent years. Accordingly, this Special Issue focuses on system safety and human factors, risk and reliability analysis, asset integrity management, and accident modeling at different stages of lifecycle renewable energies from production to application.

Potential topics include but are not limited to:

  • Systematic, critical, content, and bibliometric review in renewable energy;
  • System safety and human factors analysis in renewable energy;
  • Recent advancements in reliability and risk assessment methods in renewable energy;
  • Accident investigation and lessons learned associated with renewable energy;
  • Safety, resilience, and reliability concerns in the sustainable design of renewable energy infrastructure;
  • Uncertainty handling and decision making in safe and resilient operation of renewable energy infrastructure;
  • Emerging computational modeling and simulation software trends for consequence modelling accidents (e.g., fire, explosion, dispersion);
  • The applications of machine learning and data mining in risk management of renewable energy;
  • Digitalization, cybersecurity, and natural disaster protection in renewable energy systems.

Dr. Mohammad Yazdi
Dr. Esmaeil Zarei
Dr. Sidum Adumene
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Safety is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • system safety
  • operation research
  • decision support systems
  • risk intelligence

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

26 pages, 3043 KiB  
Article
Reducing Data Uncertainties: Fuzzy Real-Time Safety Level Methodology for Socio-Technical Systems
by Apostolos Zeleskidis, Stavroula Charalampidou and Ioannis M. Dokas
Safety 2024, 10(4), 85; https://doi.org/10.3390/safety10040085 - 30 Sep 2024
Viewed by 506
Abstract
This paper presents the fuzzy real-time safety level (Fuzzy RealTSL) methodology. It aims to address the data uncertainties resulting from a lack of sensors in complex sociotechnical systems and reduce the need for the determination of their safety level in real-time during their [...] Read more.
This paper presents the fuzzy real-time safety level (Fuzzy RealTSL) methodology. It aims to address the data uncertainties resulting from a lack of sensors in complex sociotechnical systems and reduce the need for the determination of their safety level in real-time during their operation. To achieve this, the methodology utilizes: (1) safety constraints from STPA (systems theoretic process analysis) analysis and EWaSAP (early-warning-signs analysis process), (2) fuzzy logic as the mathematical backbone to identify the degree of confidence about the occurrence of unsafe system states, (3) a modified centroid point and spread ordering to enable ordering sequences of unsafe system states that can lead to accidents according to how detrimental they are to the system safety. The RealTSL methodology is presented through its step-by-step application to the panel alignment system of a solar park utilizing rotating solar arrays. This paper aims to open a new perspective on the STAMP literature for discussions of uncertainties from a lack of information about the system’s state and to make it easier to measure its safety level. Knowing the safety level of a system in real-time is crucial for the systems in question as it enables proactive risk management and enhances decision-making by providing immediate insights into potential hazards, thus safeguarding against accidents. Full article
(This article belongs to the Special Issue Safety, Resilience and Reliability Challenges and Engineering Research in Renewable Energies)
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34 pages, 1696 KiB  
Article
Enhancing System Safety and Reliability through Integrated FMEA and Game Theory: A Multi-Factor Approach
by Mohammad Yazdi
Safety 2024, 10(1), 4; https://doi.org/10.3390/safety10010004 - 22 Dec 2023
Cited by 6 | Viewed by 2384
Abstract
This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game [...] Read more.
This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game Theory, thereby enhancing the assessment and mitigation of risks in intricate environments. The novel inclusion of the Best Worst Method (BWM) and Pythagorean fuzzy uncertain linguistic variables refines the accuracy of risk evaluation by overcoming the inherent deficiencies of conventional FMEA approaches. Through sensitivity analysis, the framework’s efficacy in identifying and prioritizing failure modes is empirically validated, guiding the development of targeted interventions. The practical application of our methodology is demonstrated in a comprehensive healthcare system analysis, showcasing its versatility and significant potential to improve operational safety and reliability across various sectors. This research is particularly beneficial for systems engineers, risk managers, and decision-makers seeking to fortify complex systems against failures and their effects. Full article
(This article belongs to the Special Issue Safety, Resilience and Reliability Challenges and Engineering Research in Renewable Energies)
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26 pages, 2676 KiB  
Article
A Knowledge-Driven Model to Assess Inherent Safety in Process Infrastructure
by Kamran Gholamizadeh, Esmaeil Zarei, Sohag Kabir, Abbas Mamudu, Yasaman Aala and Iraj Mohammadfam
Safety 2023, 9(2), 37; https://doi.org/10.3390/safety9020037 - 1 Jun 2023
Cited by 6 | Viewed by 2334
Abstract
Process safety has drawn increasing attention in recent years and has been investigated from different perspectives, such as quantitative risk analysis, consequence modeling, and regulations. However, rare attempts have been made to focus on inherent safety design assessment, despite being the most cost-effective [...] Read more.
Process safety has drawn increasing attention in recent years and has been investigated from different perspectives, such as quantitative risk analysis, consequence modeling, and regulations. However, rare attempts have been made to focus on inherent safety design assessment, despite being the most cost-effective safety tactic and its vital role in sustainable development and safe operation of process infrastructure. Accordingly, the present research proposed a knowledge-driven model to assess inherent safety in process infrastructure under uncertainty. We first developed a holistic taxonomy of contributing factors into inherent safety design considering chemical, reaction, process, equipment, human factors, and organizational concerns associated with process plants. Then, we used subject matter experts, content validity ratio (CVR), and content validity index (CVI) to validate the taxonomy and data collection tools. We then employed a fuzzy inference system and the Extent Analysis (EA) method for knowledge acquisition under uncertainty. We tested the proposed model on a steam methane-reforming plant that produces hydrogen as renewable energy. The findings revealed the most contributing factors and indicators to improve the inherent safety design in the studied plant and effectively support the decision-making process to assign proper safety countermeasures. Full article
(This article belongs to the Special Issue Safety, Resilience and Reliability Challenges and Engineering Research in Renewable Energies)
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