Chemical Engineering Commons^™

Influence Of Fused Deposition Modeling Process Parameters On The Constitutive Model Of Hyperelastic Thermoplastic Polyurethane, Lucas Gallup, Mohamed Trabia, Brendan O'Toole, Youssef Fahmy

Mechanical Engineering Faculty Research

Thermoplastic polyurethanes (TPUs) are suited for fused deposition modeling (FDM) of parts that require high levels of flexibility and strength. Predicting the deformation of TPU parts produced using FDM may be difficult, especially under large deformations, as their constitutive models depend on the printing process parameters. The lack of understanding led to the absence of constitutive models for TPU parts produced using FDM. This work aims to identify accurate hyperelastic constitutive models. Six groups of uniaxial tensile specimens were produced using FDM. These groups were made with variations in two process parameters, which were infill geometry and extrusion nozzle temperature. …

Determination Of The Kinetic Parameters Of Cholesterol Oxidation Using Cholesterol Oxidase From Streptomyces Sp., Meka Saima Perdani, Heri Hermansyah, Muhamad Sahlan, Dwini Normayulisa Putri, Teguh Pambudi, Anggi Khairina Hanum Hasibuan

Makara Journal of Technology

Cholesterol oxidase (CO) was successfully produced from Streptomyces sp. via the submerged fermentation method, and 69 U/mL enzyme activity was obtained. This study aimed to determine cholesterol oxidation kinetics and the production of CO as a catalyst. The enzyme was diluted to 0.15, 0.075, and 0.00375 U/mL for the oxidation reaction. The substrate was also prepared in three concentrations: 3.23, 6.46, and 12.93 mM. The optimization of conditions for enzymatic cholesterol oxidation was investigated through measurement of the effect of initial cholesterol and enzyme concentrations. Cholesterol concentration was rapidly measured via high-performance liquid chromatography (HPLC). The kinetics of CO were …

Physics-Informed Heterogeneous Spatiotemporal Graph Neural Network For Reservoir Simulation, Ahmed A.M.A. Abdullah

LSU Master's Theses

Reservoir simulation is the state-of-the-art method for predicting the flow of petroleum reservoir fluids in porous media. It provides an accurate and unbiased prediction of the performance of petroleum reservoirs under different operating conditions. Despite its advantages, reservoir simulation is computationally expensive; with typical full-field simulation models running for several hours. This limitation is worsened when simulating reservoirs with several equations for each cell, such as multiphysics or compositional reservoir simulation. The goal of this research is to provide a fast and accurate spatiotemporal machine-learning model that incorporates discretized governing mass balance equations for training. To achieve this, we propose …

Capacity Of Self Compact Concrete Walls Using Attapulgite As A Partial Replacement Of Cement Under One Way And Two Way Action Restriction, Wissam Kadhim Alsaraj, Luma Abdul Ghani Zghair, Akhlas Hashem Mohammed

Al-Esraa University College Journal for Engineering Sciences

This investigation about the structural performance of sustainable self-compact concrete walls exposed to eccentric axial regularly dispersed loading, including the effect of aspect ratio (AR) and slenderness ratio (λ) by one-way and two-way action. The experimental program includes testing ten wall panels, the eccentricity of the loading system equivalent to one-sixth of depth. These wall panels are separated into four groups, each one consisting of three specimens. first and second groups clarify the aspect ratio (H/L) effect. The results indicated for decreasing AR from (0.75 to 0.625), (0.625 to 0.5), and (0.75 to 0.5), the increase of final load is …

Exploring The Benefits Of Feature Selection Based On Bat Algorithm And Deep Learning In Brain Cancer Diagnosis, Noor Fawzi Shafiq

Al-Esraa University College Journal for Engineering Sciences

Brain cancer is considered one of the most dangerous types that must be treated as soon as possible. Therefore, it is necessary to detect brain cancer in its early stages to enhance the diagnosis of the condition. This study proposes to combine the bat algorithm (BA) with deep learning methods to identify and classify brain tumors in medical images accurately.

In this paper, the bat algorithm was used to select distinctive features from the input brain images. The Bat Algorithm (BA) is a metaheuristic optimization algorithm that mimics the echolocation behavior of bats. It efficiently explores the feature space to …

Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi

Al-Esraa University College Journal for Engineering Sciences

The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …

A Study On Improving The Accuracy And Effectiveness Of Similarity Detection Processes In Text Files Using Nlp Techniques, Noor Abdulmuttaleb Jaafar

Al-Esraa University College Journal for Engineering Sciences

The rapid expansion of the Internet has revolutionized access to information, especially in the area of unstructured data, most of which consists of textual content. While instant access to information brings many advantages, it has also given rise to a prevalent problem – plagiarism. Copying and reusing materials without proper permission poses a significant threat to academic integrity and integrity. Rates of plagiarism, especially in academic and scientific publications, have risen with the advent of the Internet, reaching alarming levels, such as 60% in student projects. This study examines the proposed model that includes computation of similarity using cosine coefficients, …

Studies On The Synthesis, Reactivity, And Stability Of Au Nanoparticles In Ts-1 Zeolites For Propylene Epoxidation Within H2/O2 Mixtures, Weixin Li

Dissertations - ALL

The increasing global demand for energy and materials has highlighted the importance of efficient production of chemical intermediates like propylene oxide (PO), a key compound in manufacturing polyurethanes, propylene glycol, and other industrial products. Traditional methods, such as the chlorohydrin process and organic peroxide methods, pose environmental and economic challenges due to hazardous by-products and complex processes. The need for greener alternatives led to the exploration of gold (Au) catalysts for the direct catalytic epoxidation of propylene using hydrogen (H2) and oxygen (O2). This research focused on understanding the propylene epoxidation process over Au catalysts, specifically Au nanoparticles (AuNPs) supported …

An Intelligent System Using Deep Learning For Healthcare Monitoring In Light Of The Covid-19 And Future Pandemics Based On Iot, Sara Salman Qasim, Rajaa J. Khanjar, Jamal Nasir Hasoon, Baesher Abdullateff Abad, Ali Hussein Fadil, Shajan.M. Alsowaidi

Al-Esraa University College Journal for Engineering Sciences

Recently, the Internet of Things has become a compelling research field as a new topic of research in various disciplines, particularly in the field of healthcare, because the Internet of Things is rebuilding modern healthcare systems by integrating technology, economics, and social perspectives. The development of healthcare systems from traditional to more personalized systems in which patients can be easily diagnosed, monitored and treated and many people can be helped. People are treated and cared for remotely and this is what some people need in the crisis the world has been through like COVID-19. This epidemic is caused by the …

Speech Coding Based On A Hybrid Approach: Dct, Huffman And Run-Length Coding, Sundos Abdulameer Alazawi, Esraa Jaffar Baker, Shahbaa Mohammed Abdulmaged

Al-Esraa University College Journal for Engineering Sciences

The exponential expansion of data in the digital world necessitates the development of effective methods for data transmission and storage. Data compression (DC) strategies are suggested to reduce the quantity of data stored or conveyed due to constrained resources. As a result of DC ideas' ability to efficiently use existing storage space and transmission capacity, different methods have been developed in various areas. Speech coding is a lossy method of coding; therefore, the output signal differs slightly from the input signal. Speech coding is useful for message encryption, communication over long distances and speech quality. In the fields of digital …

The Evolution Of The University Of Al-Anbar Urban Planning Based On The Mental Picture's Diversity And The Contemporary Planning Spaces Filling, Ali Abdulsamea Hameed

Al-Esraa University College Journal for Engineering Sciences

This research concentrated on the role of environmental graphic design (EGD) and the place-making idea in the interior environment of Al-Anbar University. To develop an identity being visual for the University of Al-Anbar internal environment (IE) is this goal of project. The search sought to create and enhance the shape of the internal University of Al-Anbar vacuum by reviving the idea of place building. In order to build and filling the internal emptiness of the campus, the identity being visual must also be strengthened. The descriptive analytical approach was chosen since it was best suited to achieve the goal of …

Thermodynamics And Shear Flow Dynamics Of Block Copolymer Morphologies In Solution, Senyuan Liu

Dissertations - ALL

Block copolymers (BCPs) have been a focal point of research for several decades. They have been engineered to produce various morphologies by altering the combinations of chemically distinct polymer segments that interact selectively with their environment, such as in aqueous or organic solvents, or within a polymer matrix. The ability to tailor morphological features by manipulating polymer chain length, composition, and monomer chemistry has led to applications in advanced material manufacturing, catalysis, emulsification, environmental remediation, targeted drug delivery, gene therapy, and medical diagnostics. Consequently, understanding the relationship between copolymer architecture and the self-assembled morphologies at equilibrium, the pathways of structure …

Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …

Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …

Beyond The Surface: Understanding Temperature Polarisation In Dcmd Membranes Through Varied Operational Parameters, Hiras Ahamed Hijaz, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani

Research outputs 2022 to 2026

Conventionally, a single Temperature Polarisation Coefficient (TPC) value is calculated to quantify Temperature Polarisation (TP). In this research, the extent of polarisation is investigated by capturing temperature profiles at specific points along a MD membrane using miniature thermocouples, eliminating the need for TPC calculations. The extent of polarisation at a point is affected by two contributory factors, namely the proximity of flow inlets and the difference in vapour pressure across the membrane at that point. Under this direction, this work examined the influence of permeate temperature, feed salinity, and flow direction on the development of the temperature profiles. Our analysis …

Kinetics Model Of Cananga (Cananga Odorata) Fresh Flower Extraction Using Microwave Hydrodistillation Method, Darnengsih Darnengsih, Hikmatun Ni’Mah, Mahfud Mahfud, Ayu Chandra Kartika Fitri

Makara Journal of Science

Recent studies have focused on improving essential oil extraction methods by incorporating advanced technologies, such as microwave-assisted hydrodistillation (MHD). Despite these advancements, further research is necessary to fully understand how different kinetic models influence extraction efficiency. This study evaluates several kinetic models for extracting essential oil from fresh Cananga flowers using MHD, examining how varying microwave power affects extraction rates and correlates with kinetic model parameters. The extraction process involved introducing 200 grams of fresh Cananga flowers in 400 mL of distilled water and subjecting the mixture to microwave power levels of 200 W, 400 W, and 600 W. The …

Synthesis Of Activated Carbon From Coconut Shell And Recycled Styrofoam Nanofiber For Water Filtration, Rahma Dani, Ismet Ismet, Leni Marlina, Rona Alisya, Muhamad Abel Kirana Aldi, Anggi Ludiansyah, Lintang Auliya Kurdiati, Meutia Kamilatun Nuha Ap Idjan, Agung Mataram, Muhammad Rama Almafie, Ida Sriyanti

Makara Journal of Science

Water pollution affects life sustainability; hence, several efforts have been exerted to overcome this problem. For ex-ample, nanofiber membrane technology is introduced to retain solutes while allowing only water molecules to pass through the system. Therefore, this study aimed to maximize the technology for water filtration using the electrospin-ning method by combining Styrofoam waste-based polymer with activated carbon from coconut shell waste (ACCS). The nanofiber diameter produced ranged from 590 nm to 610 nm with porous characteristics and without beads. The carbon content varied from 68.04% to 69.84%, according to the energy dispersive X-ray measurement, demonstrating the composite’s effectiveness. The …

Optimization Of Tps Films Using An Adaptive Design Of Experiments Approach In A Bayesian Optimization Framework, Theresa Marks, Gracie White, Scott Lohman, Mayank Malhotra

The Journal of Purdue Undergraduate Research

Plastic pollution, amounting to 12 million tons annually, necessitates sustainable alternatives to single-use plastics. Compostable thermoplastic starch (TPS) films show promise but lack strength and durability compared to traditional plastics. This study employs an adaptive design of experiments (DoE) approach to enhance TPS films by optimizing testing points. The research focuses on varying concentrations of plasticizers (acetic acid and glycerol) in a water and potato starch mixture, aiming to identify the optimal ratio maximizing tensile strength and % elongation at break. Gaussian process regression (GPR) with uncertainty estimation and Bayesian optimization (BO) utilizing an acquisition function (AF) are employed. The …

Zeolite 13x Particles With Porous Tio2 Coating And Ag2o Nanoparticles As Multi-Functional Filler Materials For Face Masks, Wei Su, Kaiying Wang, Han Yu, Fateme Fayyazbakhsh, Jeremy Watts, Yue-Wern Huang, Jee-Ching Wang, Xinhua Liang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Adsorbent components in face masks are crucial for protecting individuals exposed to dangerous situations. In this study, one porous TiO₂ layer was deposited on zeolite 13X particles by coating hybrid organic/inorganic titanium alkoxide film via molecular layer deposition (MLD), followed by heat treatment to remove organic components in the MLD film. Various concentrations of Ag₂O nanoparticles were impregnated on the TiO₂-coated 13X particles, offering a wide range of antibacterial, antifungal, and antiviral characteristics. The obtained composite particles were characterized using X-ray photoelectron spectroscopy and thermal gravimetric analysis to study the composition and mass loading of …

Application Of Digital Rock Physics And Machine Learning To Improve The Understanding Of Fluid Flow Behavior Through Porous Media, Md Irfan Khan

Mechanical Engineering Theses

Accurately estimating reservoir rock properties and understanding capillary trapping mechanisms are crucial for fluid storage and flow modeling in porous media, particularly for applications such as carbon dioxide sequestration (CCS) and underground hydrogen storage (UHS). This thesis presents a comprehensive workflow that combines machine learning techniques and pore-network modeling approach to predict petrophysical properties and assess the impact of microscopic pore structures on capillary trapping. In the first part, a convolutional neural network (CNN) framework is used to predict rock properties—such as porosity, throat area, and pore surface area—from micro-computed tomography (micro-CT) X-ray images. It has been observed that incorporating …