Chemical Engineering Commons^™

An Ai And Iot Framework For Dynamic Optimization And Sustainability In Smart Cities, Zeinab E. Ahmed, Rashid A. Saeed, Salah Hagahmoodi, Mamoon M. Saeed, Khalid Hamid, Sally D. Abugasim, Eyman F. A. Elsmany

Al-Esraa University College Journal for Engineering Sciences

Smart cities are emerging as a critical solution for creating more efficient, sustainable, and comfortable urban environments. This transformation is primarily driven by the synergistic integration of the Internet of Things (IoT) and Artificial Intelligence (AI). The IoT provides a pervasive network of connected sensors that collect real-time urban data, while AI serves as the analytical engine that processes this information to optimize city-wide systems. This paper presents a comprehensive framework that leverages this AI-IoT convergence for dynamic optimization to achieve long-term urban sustainability. The framework focuses on enabling intelligent, data-driven decision-making across core urban domains. The discussion and analysis …

The Design And Optimization Of A Styrene Production Plant, Kaylee Hardenstein, Amanda Anderson

Honors Theses

This thesis presents the design and economic optimization of a Styrene Production Plant targeting a capacity of 100,000 tonnes/yr at a product purity of 99.8 wt%. The process relies on the dehydrogenation of ethylbenzene in a packed-bed reactor system. Downstream separation is achieved through a series of cooling, phase separation, and distillation operations to recover styrene while recycling unreacted ethylbenzene and recovering valuable byproducts.

A base case design was developed and evaluated using a process simulation software, Aspen Plus V14, and an economic analysis. Sensitivity analysis identified the styrene market price and ethylbenzene raw material cost as the dominant factors …

Pid Control For Lower Limb Exoskeletons: A Framework Evaluation, Javlonbek Rakhmatillaev, Vytautas Bučinskas

Chemical Technology, Control and Management

This research provides a detailed guideline for implementing and evaluating Proportional Integral Derivative (PID) control frameworks in lower limb rehabilitation exoskeleton robotics. It examines the role of control systems within rehabilitation robotics, outlines the principles of PID control, describes exoskeleton architecture, explores applications of PID control, reviews optimization strategies, presents experimental validations, and considers future developments in the field. The proposed control framework incorporates aspects of mechanical design, actuator and sensor selection, and PID-based control algorithms, thereby promoting safe, accurate, and individualized rehabilitation support. Recommendations and effective guidance for future work are also presented.

Supply Chain Optimization For Fertilizer Production From Wastewater, Ethan Clement Robey

Graduate Theses, Dissertations, and Problem Reports (ETD)

In West Virginia, approximately 27,000 tons of wastewater solids are generated annually, with nearly 75% being landfilled or alternatively disposed of in a non-beneficial manner. Over the past two decades, the amount of these solids being taken for beneficial uses, such as agricultural application, has declined by 25%, while landfilling has increased by more than 30%. This highlights issues related to eutrophication and disposal costs. This study aims to develop a supply chain optimization framework that addresses the conversion of wastewater solids into fertilizers to match local farm requirements, while determining processing facility locations that minimize transportation costs. To determine …

Models And Algorithms Of Control Mechanisms In Information Exchange Processes, Madina M. Fozilova, Dilshoda N. Uchqunova

Chemical Technology, Control and Management

In modern digital systems, efficient and reliable information exchange is essential for the stability of corporate systems. Traditional data management models struggle to detect and eliminate invalid, incomplete data at early stages, resulting in reduced accuracy and system inefficiency. This article proposes an advanced framework for controlling information exchange processes through the development of a Verification and Filtering algorithm. The algorithm operates within a multi-layered conceptual model that includes data input, control, validation, optimization, and decision layers. Acting as the core component, the Verification and Filtering algorithm distinguishes valid from invalid records in real time, ensuring data integrity before storage. …

Optimization Of Bioethanol From Plantain Peel Using Saccharomyces Cerevisiae, Akinjide A. Akinola, Olawole O. Olanipekun, Paul A. David

Mansoura Engineering Journal

This research aimed to evaluate the potential of using plantain peels as a raw material for producing bioethanol with the help of Saccharomyces cerevisiae. The study utilized a four-factor Box-Behnken design (BBD) and response surface methodology (RSM) to optimize the fermentation conditions. The factors considered for optimization were substrate concentration (1-4 g), pH (5-7), temperature (30-45°C), and fermentation time (24-96 hours). Through this optimization process, the study found that the optimal conditions for bioethanol production were 4 g substrate concentration, pH 6, 45°C temperature, and 60 hours of fermentation time. Utilizing these optimal conditions resulted in a bioethanol yield of …

Intelligent Decision-Making Systems In Smart Greenhouses, Muso Berdiyor Ugli Allanov

Chemical Technology, Control and Management

Smart greenhouses offer a solution to sustainable food production under climate uncertainty, yet their management often depends on fixed rules or human intuition. This study proposes an intelligent decision-making framework that integrates optimization, simulation, and a neural set into a self-learning system. By generating “conditionally real data” through simulation and evolutionary algorithms, the system can predict microclimatic changes and optimize control of water, energy, and nutrients. Continuous digital feedback enables adaptive, data-efficient operation even with limited real data. Experimental results demonstrate reduced resource use and improved yield stability, advancing the development of autonomous and resilient greenhouse ecosystems.

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev

Chemical Technology, Control and Management

The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar energy generation, grid disturbances, and power quality issues necessitate advanced control strategies. The integration of artificial intelligence (AI) into solar inverters presents a transformative solution, enhancing performance, adaptability, and reliability in real-world applications.

This review explores the role of AI techniques, including machine learning (ML), deep learning (DL), fuzzy logic, and reinforcement learning (RL), in optimizing key inverter functionalities such as maximum power point tracking (MPPT), fault detection, power quality enhancement, …

Hybrid Renewable Multi-Generation System Optimization: Attaining Sustainable Development Goals, Md Shahriar Mohtasim, Barun K. Das, Utpol K. Paul, Md Golam Kibria, Md Sanowar Hossain

Research outputs 2022 to 2026

The optimization of hybrid renewable multi-generation systems is crucial for enhancing energy efficiency, reducing costs, and ensuring sustainable power generation. These factors can be significantly affected by system designs, optimization methods, climate changes, and varying energy demands. The optimization of a stand-alone hybrid renewable energy system (HRES) that integrates various combinations of electricity, heating, cooling, hydrogen, and freshwater needs has not been reported in a single comprehensive study. Additionally, there has been insufficient attention given to the impact of temporal resolution, the recovery of excess energy usage, and aligning these efforts with the sustainable development goals (SDGs). This study reviews …

Scalable Mxene-Based Textile Supercapacitors, Abaigeal Aydt

Honors Program: Senior Projects (Public)

The demand for flexible and wearable energy storage devices for portable applications has led to the exploration of textile-based supercapacitors (TSCs). TSCs will allow for the creation of a new class of energy harvesting and storing technology directly into our clothing and will require using non-toxic and/or biocompatible materials. This will result in a greener and more sustainable path to address the challenges at the nexus of energy, mobility, and sustainability. To fabricate a TSC, a yarn made of fibers, such as wool or cotton, is coated with MXene flakes; MXenes are composed of transition metal carbides, nitrides, or carbonitrides …

Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova

Chemical Technology, Control and Management

This article discusses the methodology of automated management of situations in structurally complex systems with recycled flows. The need to develop a correct model for effectively controlling such systems based on scientific principles of analysis and decision-making is substantiated. Particular attention is paid to modeling, optimizing, and using digital technologies, including artificial intelligence, to improve the accuracy and efficiency of management decisions. The principles of decomposition, multi-criteria optimization, and linguistic models of fuzzy correspondence are described, which can be used in conditions of uncertainty and complexity of industrial facilities.

How Many Passes Does It Take? An Investigation To Determine The Optimal Number Of Liposome Extrusion Cycles, Kasey Piper

Honors Theses

Liposomes are lipid-based nanoparticles with significant applications in drug delivery and membrane research. One of the most common methods for fabricating liposomes of specific sizes is membrane extrusion, where liposomes are passed through porous membranes to reduce their size. The precise number of passes needed and the factors influencing this process remain unclear. This thesis investigates the relationship between the number of passes through a track-etched polycarbonate membrane and size and lamellarity of extruded liposomes with a focus on lipid type (DOPC, DMPC, Soy PC), membrane pore size (50, 100, 200, 400 nm), and the effect of freeze-thaw cycling. To …

Novel Nanocomposite Of Carbonized Chitosan-Zinc Oxide-Magnetite For Adsorption Of Toxic Elements From Aqueous Solutions, Dalia A. Ali Eng, Ganna Gaber Ismail Eng.

Chemical Engineering

Herein, a novel nanocomposite (carbonized chitosan-zinc oxide-magnetite, CCZF) was developed to effectively remove toxic elements in water remediation. Combining the high adsorption capacities of chitosan with the magnetic properties of magnetite and the chemical stability of zinc oxide, the combination of these unique properties makes it an efficient and versatile material that offers a sustainable solution for water purification. The (CCZF) nanocomposite was synthesized through the coprecipitation method and characterized using various techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and zeta potential analysis. The results showed …

Efficient Phosphate Removal From Water Using Ductile Cast Iron Waste: A Response Surface Methodology Approach, Mai Hassan Dr., Nada Alkhashab Eng., Ahmed Osman Dr., Dalia A. Ali Eng

Chemical Engineering

Water scarcity is a critical issue worldwide. This study explores a novel method for addressing this issue by using ductile cast iron (DCI) solid waste as an adsorbent for phosphate ions, supporting the circular economy in water remediation. The solid waste was characterized using XRD, XRF, FTIR, and particle size distribution. Wastewater samples of different phosphate ion concentrations are prepared, and the solid waste is used as an adsorbent to adsorb phosphate ions using different adsorbent doses and process time. The removal percentage is attained through spectrophotometer analysis and experimental results are optimized to get the optimum conditions using Design …

Efficient Phosphate Removal From Water Using Ductile Cast Iron Waste: A Response Surface Methodology Approach, Mai Hassan Roushdy Dr., Nada Amr El-Khashab Eng,, Ahmed Ibrahim Osman Dr., Dalia Amer Ali Dr.

Chemical Engineering

Water scarcity is a critical issue worldwide. This study explores a novel method for addressing this issue by using ductile cast iron (DCI) solid waste as an adsorbent for phosphate ions, supporting the circular economy in water remediation. The solid waste was characterized using XRD, XRF, FTIR, and particle size distribution. Wastewater samples of different phosphate ion concentrations are prepared, and the solid waste is used as an adsorbent to adsorb phosphate ions using different adsorbent doses and process time. The removal percentage is attained through spectrophotometer analysis and experimental results are optimized to get the optimum conditions using Design …

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Optimization Of Bioethanol Production Using An Enzymatic Hydrolysis Process With Green Algae (Chaetomorpha) As The Raw Material, Teuku Maimun, Mirna Rahmah Lubis, Muhammad Aldi Zein, Wahed Febbry Andriansyah Ali

Makara Journal of Technology

Bioethanol is an alternative fuel derived from biological feedstock used to decrease the reliance on fossil fuels because of increasing energy consumption associated with population growth and increased use of oil fuels. Bioethanol production has been widely conducted using several types of algae, but the optimal conditions for the hydrolysis and fermentation processes are not explained in more detail. Therefore, this study focuses on determining the optimal conditions for hydrolysis and fermentation to maximize the bioethanol yield. This study uses optimization based on the hydrolysis time, temperature, and pH to increase the reducing sugar content using high-performance liquid chromatography in …

Frameworks For The Techno-Economic Assessment Of Membrane-Based Bioprocessing Platforms, Juan Jose Romero Conde

All Dissertations

This dissertation describes developing and implementing computational frameworks for simulating and optimizing purification processes in the biopharmaceutical industry. The framework performs techno-economic analyses to establish value propositions for new process alternatives, especially membrane technologies. Initially, the focus is developing a framework capable of simulating monoclonal antibody (mAb) capture using membrane and resin media in multi-column chromatography (MCC) platforms for continuous manufacturing. Subsequently, the impact of capture MCC is compared against other intensification strategies in established mAb manufacturing facilities. Finally, the framework application expands to simulate the purification of adeno-associated virus (AAV) vectors for gene therapy.

Chapter 2 details the framework …

The Design And Optimization Of An Ethylbenzene Production Process, Alexander Koons

Honors Theses

Ethylbenzene is a foundational organic compound used as a reactant in styrene production. The objective of this thesis is to present the optimization of the in-house production process of ethylbenzene, aiming to avoid external procurement for the downstream styrene manufacturing facility. The process underlines a strategic approach to enhance the yield and cost efficiency of the production of ethylbenzene. An economic analysis revealed a promising net present value of approximately $57.6 million. This thesis not only proposes a viable route for internal ethylbenzene generation but also discusses optimizing the chemical production processes for enhanced efficiency and sustainability.

Modeling Studies Of An Intensified Reforming/Fischer-Tropsch Synthesis Process For Gas To Liquid Conversion, Brian Gray

USF Tampa Graduate Theses and Dissertations

Despite rigorous study and advancement in fields of green energy, the world's transportation industry remains poised to continue reliance on liquid hydrocarbon fuels. To date, the primary source of diesel and jet fuels is the petroleum industry; however, continuing trends in rising greenhouse gas emissions present a need for study into processes for the production of synthetic hydrocarbon fuels. The most promising technologies to meet this goal are gas-to-liquid (GtL), biomass-to-liquid (BtL) and coal-to-liquid (CtL). The commonality of these technologies is that they utilize a feedstock to produce carbon monoxide and hydrogen gas (syngas) which becomes the building blocks of …

Synthesize A Neural Network Parameter Optimizer For An Adaptive Pid Controller, Nashvandova Gulruxsor Murot Qizi

Chemical Technology, Control and Management

Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters superstructuring. In the paper, the questions of optimization of PID-regulator parameters with application of methods of neural network technology are considered. A methodology for selecting the architecture of neural network optimizer designed to determine the tuned parameters of PID regulator is proposed. The algorithm of training of the neural network, with the set on the basis of the method of inverse gradient propagation is offered. The proposed improved PID-neural regulator allowed to provide stabilization of neural network operation and its trainability in the control loop …

Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov

Chemical Technology, Control and Management

A method is being developed to optimize the generated controls for the multicomponent distillation process with prediction, based on predictive data with a moving horizon. The difference between this method and the classical modeling approach, in which the percentage of the degree of opening of valves installed on the output streams of the column is used as control actions, is that control occurs on the feedback principle. The proposed method is based on the use of a dynamic process model to optimize control actions in real time in order to achieve certain production targets. The essence of the MPC approach …

Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee

Graduate Theses, Dissertations, and Problem Reports (ETD)

First-principles models can provide very good predictions even for cases when there are no data at all, or data are limited in certain range of operating conditions, or for cases where data collection is infeasible. However, the development of accurate first-principles models for complex nonlinear dynamic systems can be time consuming, computationally expensive, and may be infeasible for certain systems due to lack of sufficient knowledge (information). It is also challenging to adapt first-principles models for time-varying systems. Furthermore, it can be difficult, if not impossible, to develop accurate models for some complex phenomena that are poorly understood. On the …

Equation-Based And Data-Driven Modeling: Open-Source Software Current State And Future Directions, Lagrande Gunnell, Bethany Nicholson, John Hedengren

Faculty Publications

A review of current trends in scientific computing reveals a broad shift to open-source and higher-level programming languages such as Python and growing career opportunities over the next decade. Open-source modeling tools accelerate innovation in equation-based and data-driven applications. Significant resources have been deployed to develop data-driven tools (PyTorch, TensorFlow, Scikit-learn) from tech companies that rely on machine learning services to meet business needs while keeping the foundational tools open. Open-source equation-based tools such as Pyomo, CasADi, Gekko, and JuMP are also gaining momentum according to user community and development pace metrics. Integration of data-driven and principles-based tools is emerging. …

Application Of Evolutionary Algorithms For Optimization Of Operation Modes Of Regional Electric Power Systems, Isamiddin Khakimovich Siddikov, Oksana Vitalevna Porubay

Chemical Technology, Control and Management

The paper presents the possibilities of using evolutionary algorithms to solve the problem of optimizing the operation modes of electric power facilities in the presence of constraints in the form of inequalities and equalities. The limits of constraints have a variable character, depending on the generated and consumed energy. Existing methods used for the optimization of modes are based on general principles and approaches to optimization, which usually adapt to the specifics of the problem. In electric power facilities, optimization problems have some peculiarities, among which is the presence of multiple constraints applied to both independent and dependent variables. Many …

Optimization Of A Bioreactor, Ali Alshami

AI Assignment Library

The primary objective of this assignimentis to learn to work effectively as a team, and to design an experiment where optimization is essential.

An Analysis Of The Production Of Pharmaceutical-Grade Acetone Via The Dehydrogenation Of Isopropanol (Ipa), Jordan Desplas

Honors Theses

The production of 99.9 wt% acetone from isopropanol in Unit 1100 is designed to start up in 2025 and operate for 12 years after startup. The engineering team was tasked with designing the process, creating an economic model, and optimizing the net present value (NPV). The process was simulated in AVEVA PRO/II Simulation for the design process, and the economic analysis was estimated in Microsoft Excel. Parametric and topological optimization was performed linearly on the unit operations in the process. The NPV was improved by $14M from a base case of $122M to an optimized case of $136M. The project …

Hybrid Modeling For Electrochemical Systems, Luis Alejandro Briceno-Mena

LSU Doctoral Dissertations

The discovery of new materials like catalysts, polymeric films, and biomolecules, is driven by industrial needs such as improving reaction or separation selectivity, enhancing therapeutic effects on medical treatments, or reducing costs of replacement. However, deployment of these advances in industrial applications is often hindered by the lack of models needed for design and optimization. Due to the novelty of materials and devices, experimental data and first principles' knowledge are scarce, making it hard to build models either via data-driven or knowledge based approaches. In this context, a way to efficiently combine domain knowledge with data could provide a pathway …

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …