Dr. Ghanim Alwan
Simulation and chemical process control Biochemical Engineering, Chemical Engineering (General), Membranes and Separation Technology, Process Chemistry and Technology, Numerical Engineering Modeling , Simulation and Optimization Process Simulation chemical process control Biochemical Engineering Chemical Engineering Membranes and Separation Technology Process Chemistry and Technology Numerical Engineering Fluid Dynamics and Mixing Traffic and Road Safety Adsorption and biosorption for pollutant removal Advanced oxidation water treatment Advanced Multi-Objective Optimization Algorithms Modeling and simulation Simulation modeling Simulation-based optimization Biomedical Engineering Computational Theory and Mathematics Materials Chemistry Safety, Risk, Reliability and Quality Water Science and Technology

Bio

Dr. Ghanim M. Alwan is an accomplished chemical engineer and academic affiliated with the University of Technology Baghdad, Iraq. With a Ph.D. in Chemical Engineering from the University of Technology (1994) and graduate degrees from the University of Baghdad, he has built a career spanning research, teaching, and industrial consulting. His work focuses on simulation, optimization, and control of chemical processes, particularly in biochemical reactors and wastewater treatment. Dr. Alwan has held positions at Missouri University of Science and Technology, Al-Mustaqbal University College, and the Ministry of Industry. He has authored 25 publications, garnering over 200 citations and an h-index of 8, and has been recognized as a top peer reviewer by Elsevier. His memberships include prominent societies such as AIChE, SIAM, and IChemE, reflecting his contributions to the field of chemical engineering.

Educational Journey

Associate Professor Dr.PhD

University of Baghdad

Doctor of Philosophy Chemical Engineering

1994

University of Baghdad

Master of Science Chemical Engineering in College of Engineering • College of Engineering

1983
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Experience

Supervisor and Consultor

1989 - Present • Research and Develpoment

Researcher and Advisor

2010 - Present • Chemical and Biological Engineering

Al-Mustaqbal University College

Lecturer and Consultor

2019 - 2021 • Chemical and Petroleum Industries Engineering
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Affiliations

American Institute of Chemical Engineering (AIChE)

Researcher and Scientific Consulted

Member since 2011

AIChE Academy

Researcher and Scientific Consulted

Member since 2011

Society for Industrial and Applied Mathematics (SIAM)

Researcher and Scientific Consulted

Member since 2011
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Grants and Awards

GRANT

On-line control of a wastewater treatment unit

Ministry of Higher Education

2008
GRANT

Study on Catalytic Wet Air Oxidation Process for Phenol Degradation in Synthetic Wastewater Using Trickle Bed Reactor

Petroleum Research and Development Center-Ministry of Oil-Iraq

2014

Research

Hybrid Model and Optimization of Bioreactor of wastewater

Article July 10, 2015

This work deals with modeling and operation optimization of lab-scale continuous biochemical reactor. Wastewater is feeding to reactor contaminated with different concentration of glucose. The reactor is non-linear with stochastic changing in optimum operating conditions. Simulated model could develop the process and generate extra-confirmed data. The selected process variables are: dilution rate (D), feed substrate concentration (Si), pH and temperature (T). Simulated model could develop the process and generate extra-confirmed data. The effect of D was observed within Si of 20 g/L, while pH and T are affecting within Si of 60 g/L.Si has major effect on dynamic characteristics of the reactor. Reasonable agreement has been found when compared the simulated result with the previous work. Optimization technique helps the decision maker to select best operating conditions. This could reduce the risk of experimental runs and consumed cost for operating and design. Global Genetic algorithm (GA) has been found more reliable than deterministic search for the bioreactor. Optimization results are based on maximizing biomass growth. Optimal results indicate that maximum biomass concentration (X) is 80.57 g/L could be obtained at high value of Si (197.56 g/L) and low D (0.1hr-1 ).Si is sensitive variable for stochastic mutation of biomass growth.