Mohammad Awad | Engineering | Innovative Research Award

Published on by Forensic Scientist Awards

Innovative Research Award

Mohammad Awad
Affiliation Hashemite University
Country Jordan
Google Scholar ID BlOlGg0AAAAJ
Documents 3
Citations 2
h-index 1
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0009-0004-1009-7923

Mohammad Awad
Hashemite University, Jordan

Mohammad Awad of Hashemite University, Jordan, is associated with engineering research concerning the structural behavior and numerical assessment of fiber-reinforced polymer (FRP) reinforced concrete columns. His recent publications examine axial compression, load–strain response, database-based analysis, and finite element validation, establishing a focused research direction within contemporary structural engineering.

Abstract

Mohammad Awad’s research profile reflects an engineering focus on the structural performance of concrete columns strengthened or reinforced with fiber-reinforced polymer systems. The work combines empirical database analysis with finite element modelling to investigate axial compression and load–strain behavior. Such approaches can support improved understanding of structural response and provide numerical evidence for evaluating FRP-reinforced concrete systems. [1]

Keywords

Fiber-reinforced polymer; FRP reinforced concrete; concrete columns; axial compression; finite element analysis; load–strain behavior; structural engineering.

Introduction

FRP reinforcement has become an important research topic in structural engineering because its mechanical and durability characteristics offer alternatives to conventional reinforcement systems. Numerical modelling and experimental databases are frequently used together to characterize structural response and evaluate predictive approaches. Awad’s recent research addresses this area through finite element assessment and database-oriented investigation of concrete columns subjected to axial loading. [2]

Research Profile

The research profile is centered on computational structural analysis, particularly the relationship between reinforcement configuration and the mechanical response of concrete columns. The use of finite element methods provides a framework for examining load transfer and strain development, while database analysis allows broader comparison across structural cases. This combination represents a methodologically focused contribution to engineering research.

Research Contributions

  • Investigation of axial compression behavior in FRP-reinforced concrete columns.
  • Application of finite element analysis to structural load–strain response.
  • Use of database analysis to support broader evaluation and validation of structural behavior.

Publications

“Axial compression behavior of FRP reinforced concrete columns based on database analysis and finite element validation” was published in Discover Civil Engineering on 27 August 2026. The article examines database evidence alongside finite element validation of axial compression behavior. [3]

“Finite element analysis of concrete columns reinforced with fiber-reinforced polymer (FRP): Load-strain behavior” was published in Scientific Research and Essays on 31 August 2025. The study focuses on finite element evaluation of load–strain behavior in FRP-reinforced concrete columns. [4]

Research Impact

The available scholarly profile records 3 documents, 2 citations, and an h-index of 1. These quantitative indicators represent a developing publication record and should be interpreted in relation to the researcher’s recent publication activity. The subject concentration in Engineering and the focus on FRP-based structural systems provide a clearly defined technical research direction.

Award Suitability

The Innovative Research Award recognizes research characterized by methodological development, relevant technical investigation, and potential contribution to its field. Awad’s work demonstrates innovation through the combined use of finite element modelling and database analysis to study FRP-reinforced concrete columns. The alignment between the research topic, engineering specialization, and recent peer-reviewed publications provides a substantive basis for consideration.

Conclusion

Mohammad Awad presents an emerging engineering research profile focused on computational and analytical assessment of FRP-reinforced concrete columns. His recent publications establish a coherent direction in structural behaviour, finite element analysis, and database-supported validation, making the profile relevant to research recognition in innovative engineering studies.

References

  1. Elsevier. (n.d.). Google Scholar author details: Mohammad Awad, Author ID BlOlGg0AAAAJ.
    https://scholar.google.com/citations?hl=en&user=BlOlGg0AAAAJ
  2. Awad, M. (2025). Finite element analysis of concrete columns reinforced with fiber-reinforced polymer (FRP): Load-strain behavior. Scientific Research and Essays.
    https://doi.org/10.5897/sre2025.6801
  3. Awad, M. (2026). Axial compression behavior of FRP reinforced concrete columns based on database analysis and finite element validation. Discover Civil Engineering.
    https://doi.org/10.1007/s44290-026-00602-y
  4. Awad, M. (2025). Finite element analysis of concrete columns reinforced with fiber-reinforced polymer (FRP): Load-strain behavior. Scientific Research and Essays, ISSN 1992-2248.
    https://doi.org/10.5897/sre2025.6801
  5. International Organization for Standardization. Structural engineering terminology and principles for concrete and reinforcement assessment.

Behzad Motallebi Azar | Engineering | Best Researcher Award

Published on by Forensic Scientist Awards

Best Researcher Award

Behzad Motallebi Azar
Sahand University of Technology, Iran

Behzad Motallebi Azar
Affiliation Sahand University of Technology
Country Iran
Scopus ID 57221133046
Documents 7
Citations 45
h-index 4
Subject Area Engineering
Event International Forensic Scientist Awards
ORCID 0000-0002-7964-0507

Behzad Motallebi Azar is an engineering researcher whose documented scholarly work addresses contemporary energy-system challenges, including prosumer participation, peer-to-peer energy trading, renewable-energy integration, energy storage, hydrogen power systems, and intelligent forecasting. His publication record includes journal, conference, and book-chapter contributions spanning optimization, reinforcement learning, transactive energy, and hybrid energy systems. The available bibliometric information records 7 documents, 45 citations, and an h-index of 4 in Scopus. [1]

Abstract

The research profile of Behzad Motallebi Azar is characterized by work in energy-system engineering and computational approaches to decentralized electricity systems. His publications examine peer-to-peer energy trading, prosumer behavior, net-load forecasting, hydrogen-based power systems, transactive energy, and interconnected hybrid energy systems. Recent work combines deep reinforcement learning and blockchain-based settlement concepts for prosumer markets, reflecting the growing role of intelligent computational methods in energy-system coordination. [2] [3]

Keywords

  • Energy Systems
  • Peer-to-Peer Energy Trading
  • Deep Reinforcement Learning
  • Prosumer Markets
  • Renewable Energy

Introduction

Modern energy systems increasingly require methods capable of coordinating distributed generation, flexible demand, storage, and prosumer participation. Research in this area has consequently expanded toward decentralized markets, intelligent forecasting, and computational optimization. Motallebi Azar’s documented publications fit within this broader engineering context, addressing both market mechanisms and operational strategies for interconnected energy resources. [4]

Research Profile

The research portfolio demonstrates an interdisciplinary connection between energy engineering, artificial intelligence, optimization, and distributed energy management. The 2026 Journal of Cleaner Production article investigates optimal prosumer participation in dual peer-to-peer markets through multi-agent deep reinforcement learning, fuzzy satisfaction levels, and blockchain settlement. [2] A 2025 conference contribution examines household-prosumer net-load forecasting using deep reinforcement learning. [3] Earlier book chapters extend the profile into techno-economic hydrogen systems, transactive energy, and coalition operation of hybrid energy systems. [5] [6]

Research Contributions

  • Application of multi-agent deep reinforcement learning to prosumer participation and peer-to-peer energy markets.
  • Investigation of deep reinforcement learning for household net-load forecasting.
  • Analysis of techno-economic considerations in centralized green-hydrogen power systems.
  • Review and analysis of transactive energy and peer-to-peer trading applications.
  • Study of coalition-based operation in interconnected hybrid energy systems incorporating renewable resources, storage, and local conversion technologies.

Publications

  1. Optimal prosumer participation in dual peer-to-peer markets using multi-agent deep reinforcement learning, fuzzy satisfaction level, and blockchain settlement. Journal of Cleaner Production, 2026.
  2. Net Load Forecasting of Household Prosumers Considering Deep Reinforcement Learning. 2025 33rd International Conference on Electrical Engineering (ICEE), 2025.
  3. Techno-Economic Analysis for Centralized GH2 Power Systems. Book chapter, 2024.
  4. Transactive Energy and Peer-to-Peer Trading Applications in Energy Systems: An Overview. Book chapter, 2023.
  5. Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems. Book chapter, 2022.

Research Impact

The available Scopus indicators record 7 documents, 45 citations, and an h-index of 4 for the researcher identified by Scopus Author ID 57221133046. [1] These indicators provide a bibliometric snapshot of the documented research output and citation visibility. The publication portfolio also shows continuity across several related themes, progressing from hybrid-energy-system operation and transactive-energy applications toward data-driven forecasting and intelligent peer-to-peer market coordination.

Award Suitability

Based on the supplied publication record and bibliometric information, Behzad Motallebi Azar presents a research profile relevant to consideration for the Best Researcher Award at the International Forensic Scientist Awards. The suitability assessment can be grounded in documented scholarly output, multidisciplinary energy-system research, peer-reviewed and scholarly publications, and measurable citation indicators rather than unsupported claims of distinction. Final award decisions remain subject to the applicable evaluation criteria and review process.

Conclusion

Behzad Motallebi Azar’s documented research focuses on emerging methods for intelligent and decentralized energy systems. His work connects peer-to-peer electricity markets, prosumer participation, reinforcement learning, forecasting, hydrogen power systems, transactive energy, renewable resources, and energy storage. The combination of publication activity and recorded citation indicators provides a concise basis for recognizing his continuing contribution to engineering research. [1]

References

  1. Elsevier. (n.d.). Scopus author details: Behzad Motallebi Azar, Author ID 57221133046. Scopus.
    https://www.scopus.com/pages/authors/57221133046
  2. Motallebi Azar, B., et al. (2026). Optimal prosumer participation in dual peer-to-peer markets using multi-agent deep reinforcement learning, fuzzy satisfaction level, and blockchain settlement. Journal of Cleaner Production.
    https://doi.org/10.1016/j.jclepro.2026.149041
  3. Motallebi Azar, B., et al. (2025). Net Load Forecasting of Household Prosumers Considering Deep Reinforcement Learning. 2025 33rd International Conference on Electrical Engineering (ICEE).
    https://doi.org/10.1109/icee67339.2025.11213685
  4. Motallebi Azar, B., et al. (2023). Transactive Energy and Peer-to-Peer Trading Applications in Energy Systems: An Overview. Book chapter.
    https://doi.org/10.1007/978-3-031-35233-1_3
  5. Motallebi Azar, B., et al. (2024). Techno-Economic Analysis for Centralized GH2 Power Systems. Book chapter.
    https://doi.org/10.1007/978-3-031-52429-5_3
  6. Motallebi Azar, B., et al. (2022). Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems. Book chapter.
    https://doi.org/10.1007/978-3-030-87653-1_7