Li Xia | Plant biotechnology |Best Researcher Award

Prof. ā€ŒLi Xia |Plant biotechnology | Best Researcher Award

Prof at Qingdao University of Science and Technology China

Li Xia is a distinguished professor at the College of Chemical Engineering, Qingdao University of Science and Technology. With a PhD in Chemical Engineering, his research expertise spans process system engineering, chemical thermodynamics, dynamic simulation, process optimization, and energy-saving technologies. He has contributed extensively to the fields of chemical process simulation and intelligent chemical industry through numerous high-impact publications and patents. Li Xia has led and collaborated on several national research projects, focusing on innovative energy-saving strategies and the development of new chemical processes. His work has significantly advanced the application of thermodynamic models and optimization techniques in industrial processes.

Profile

 

šŸ“šEducation

PhD in Chemical Engineering Qingdao University of Science and Technology, China [2010-2016]

Ā šŸ¢ Professional Appointments

  • Professor College of Chemical Engineering, Qingdao University of Science and Technology [2006-present]

Research Projects šŸ“

Project Title: Research on energy saving strategies and methods for chemical processes based on fire accumulation Duration: January 2015 – December 2017 Funding Source: National Natural Science Foundation of China Grant Number: 21406124 Role: Project Leader Outcome: Concluded Project Title: Intelligent method and application research of low-temperature waste heat extraction and utilization Duration: January 2022 – December 2025 Funding Source: National Natural Science Foundation of China Grant Number: 22178190 Role: Second completer Status: Amidst Research Project Title: A new method and its application research for vapor-liquid equilibrium prediction based on elements and chemical bonds Duration: January 2012 – December 2015 Funding Source: National Natural Science Foundation of China Grant Number: 21176127 Role: Third completer Outcome: Concluded

Publications Top Notes šŸ“

  1. Benzoic Acid Catalyzed Production of Xylose and Xylooligosaccharides from Poplar
    • Authors: Li, L., Wan, Q., Lu, Y., Xu, J., Gou, J.
    • Journal: Industrial Crops and Products
    • Year: 2024
    • Volume: 213
    • Pages: 118460
    • Abstract: This study explores the catalytic production of xylose and xylooligosaccharides from poplar using benzoic acid, focusing on optimizing yield and process efficiency.

 

  1. A Matrix Completion Method for Imputing Missing Values of Process Data
    • Authors: Zhang, X., Sun, X., Xia, L., Tao, S., Xiang, S.
    • Journal: Processes
    • Year: 2024
    • Volume: 12
    • Issue: 4
    • Pages: 659
    • Abstract: This open-access article presents a matrix completion method aimed at imputing missing values in process data, potentially improving data integrity and analysis in various industrial applications.

 

  1. Design Method of Extractant for Liquidā€“Liquid Extraction Based on Elements and Chemical Bonds
    • Authors: Wei, Y., Zhang, C., Zhang, Y., Sun, X., Xiang, S.
    • Journal: Chinese Journal of Chemical Engineering
    • Year: 2024
    • Volume: 68
    • Pages: 193ā€“202
    • Abstract: The study proposes a novel design method for extractants used in liquid-liquid extraction, focusing on the role of elements and chemical bonds to enhance extraction efficiency.

 

  1. A Projected Newton Algorithm Based on Chemically Allowed Interval for Chemical Equilibrium Computations
    • Authors: Lu, H., Tao, S., Sun, X., Xia, L., Xiang, S.
    • Journal: Frontiers of Chemical Science and Engineering
    • Year: 2024
    • Volume: 18
    • Issue: 3
    • Pages: 27
    • Abstract: This article introduces a projected Newton algorithm designed to improve chemical equilibrium computations by using chemically allowed intervals, aiming to enhance accuracy and computational efficiency.

 

  1. Enhancing Working Fluid Selection for Novel Cogeneration Systems by Integrating Predictive Modeling: From Molecular Simulation to Process Evaluation
    • Authors: Wang, L., Zong, F., Liu, Z., Sun, X., Xiang, S.
    • Journal: Process Safety and Environmental Protection
    • Year: 2024
    • Volume: 183
    • Pages: 587ā€“601
    • Abstract: This research focuses on the selection of working fluids for cogeneration systems, integrating predictive modeling from molecular simulation to process evaluation to optimize performance and safety.

 

  1. Development of Special Process Simulation System for Sulfuric Acid Alkylation Process
    • Authors: Zhao, T., Xia, L., Sun, X., Chen, Y., Xiang, S.
    • Journal: Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities
    • Year: 2024
    • Volume: 38
    • Issue: 1
    • Pages: 121ā€“127
    • Abstract: This study details the development of a specialized process simulation system for the sulfuric acid alkylation process, aiming to improve efficiency and reliability in industrial applications.

 

 

Michael Todinov | Hydraulic Engineering

Ā Prof Michael Todinov :Leading Researcher in Hydraulic Engineering

šŸ‘Øā€šŸ«Ā  Salah-Eddine Chorfi , anĀ  Prof at Michael Todinov Oxford Brookes University United Kingdomo. stands as a distinguished academic and researcher in the Engineering. Holding The University of Birmingham, UK PhD related to modeling thermal and residual stresses in heat-treated automotive components

šŸŒ Professional Profiles:

šŸŽ“ EducationĀ 

Technical University of Sofia M.Sc. in Mechanical Engineering (First-class honors, top of the year, scored 99% average on all exams) ,Institute of Applied Mathematics and Computer Science, Sofia MSc in Applied Mathematics and Computer Science (First-class honors, top of the year, scored 99.3% average on all exams) ,The University of Birmingham, UK Visiting Research Scientist ,(Specialization in Modeling Heat Transfer, Thermal and Residual Stresses during Heat Treatment) The University of Birmingham, UK Higher Doctorate (DEng) titled ā€˜New probabilistic concepts and models in Engineeringā€™ (Equivalent to Doctor of Science (DSc), awarded for outstanding contributions in probabilistic modeling in Engineering.

šŸ¢ Work Experience

Oxford Brookes University, Oxford, Wheatley, OX33 1HX Professor in Mechanical Engineering (Leading research, teaching, and supervising PhD and MSc students in Reliability, Risk, and Probabilistic Modeling within the Department of Engineering and Mathematical Sciences, Oxford Brookes University) (Promoted to a top professorial level in 2011, based on strong references from US research institutions.)Cranfield University, Cranfield, Bedford, MK43 0AL(Led research, consultancy, and teaching in Reliability, Risk, and Probabilistic Modeling within the School of Applied Sciences, Cranfield University) Cranfield University, Cranfield, Bedford, MK43 0AL (Conducted research, consultancy, teaching, and supervised PhD and MSc students in Reliability, Risk, and Probabilistic Modeling within the School of Applied Sciences) The University of Birmingham, Birmingham, Edgbaston, B15 2TT, UK Research Scientist (Managed research in probabilistic modeling of fracture and fatigue, thermal and residual stress modeling after heat treatment, and improving mechanical component reliability through mathematical modeling.)Technical University of Sofia, Bulgaria Research Scientist (Managed research in heat and mass transfer, phase transformations modeling, funded by the Bulgarian Ministry of Science and Education)

 

šŸŒŸ Highlights of Scientific Accomplishments

Created foundational theory for repairable flow networks and networks with disturbed flows. Authored the pioneering book in this domain. Proved the dual network theorem for networks with disturbed flows, forming the basis of this theory. Developed a fast algorithm for decongesting flow networks and maximizing throughput flow after component failure. Discovered a fundamental flaw in algorithms for maximizing throughput flow in networks since 1956.

Developed Fundamental Theories:

Created foundational theories in repairable flow networks, networks with disturbed flows, and their optimization, leading to the first-ever published book in this field. Algorithms and Optimizations: Pioneered ultra-fast algorithms for decongesting flow networks and maximizing throughput flow, rectifying flaws in existing algorithms, and creating efficient algorithms for topology optimization. Revolutionary Discoveries: Revealed fundamental flaws in established theories, corrected models like the Weibull distribution, and challenged theories like the Johnson-Mehl-Avrami-Kolmogorov equation. Risk-Based Reliability: Spearheaded research in risk-based reliability analysis, setting quantitative reliability requirements, and driving progress in risk reduction principles, leading to pioneering publications. Materials Science and Engineering: Made breakthroughs in materials science, crack initiation criterion, phase transformations, and stress-related studies, unveiling new models and equations. Innovative Statistical Methods: Introduced statistical tests, empirical distributions, and simulation-based methods for diverse applications in materials science and engineering.

Top Noted Publication:

Reliability and risk models: setting reliability requirements Published on 2015/9/3 Cited by 154

Risk-based reliability analysis and generic principles for risk reduction Published on 2006/11/3 Cited by 99

Necessary and sufficient condition for additivity in the sense of the Palmgrenā€“Miner rule Published on 2001/5/1 Cited by 76

On some limitations of the Johnsonā€“Mehlā€“Avramiā€“Kolmogorov equation Published on 2000/11/8 Cited by 74

Is Weibull distribution the correct model for predicting probability of failure initiated by non-interacting flaws Published on 2009/2/1 Cited by 57

Maximum principal tensile stress and fatigue crack origin for compression springs Published on 1999/3/1 Cited by 53

A probabilistic method for predicting fatigue life controlled by defects Published on 1998/10/31 Cited by 50

Flow Networks: Analysis and optimization of repairable flow networks, networks with disturbed flows, static flow networks and reliability networks Published on 2013/1/16 Cited by 46

Reliability analysis based on the losses from failures Published on 2006/4 Cited by