Chemical Engineering Commons^™

Optimization Of Bearing Design In Centrifugal Pumps Using Finite Element And Experimental Methods: Application At South Refineries Company, Basra, Mohammed Hasab Naser Al-Mtasher

Al-Esraa University College Journal for Engineering Sciences

In the study, nonlinear vibration and thermo-mechanical characteristics of centrifugal pump bearings utilized in the cooling tower system of South Refineries Company (Basra) were properly examined using a combined experimental and numerical method. The intent of the study was to learn the impact of misalignment, the nature of the lubrication film, and thermal gradients on the stability of the operation of these bearings and their service life under realistic industry environment conditions. Finite element model (FEM) was constructed and tested on the basis of real field data obtained at the working pumps that allowed realistic distribution of stress and temperature. …

Modeling And Optimization Of Li-Ion Battery Recycling Process, Wang Lingling, Zhou Panpan, Ma Yulong

Dianchi(Changsha)

No abstract provided.

Review On Capacity Degradation Mechanisms And Lifetime Prediction Of Energy Storage Li-Ion Battery, Ma Yue, Chen Yanqiao, Wang Chu, Wang Xianwen, Liu Hui, Chen Yifei, Chen Lai, Yan Kang, Su Yuefeng

Dianchi(Changsha)

No abstract provided.

Opportunities And Challenges Of Cross-Border E-Commerce In Li-Ion Batteries, Ma Jingjing, Chen Xianyi

Dianchi(Changsha)

No abstract provided.

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov

Chemical Technology, Control and Management

One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest

Williams Honors College, Honors Research Projects

This report details the project known as “The BRRBOX”, a reusable, insulated thermoelectric cooler developed to keep internal temperatures at refrigeration levels or cooler for at least 48 hours. The cooler will track its internal temperature during this period and be able to give the data at the end of its delivery cycle to keep up with food and pharmaceutical standards during delivery. The BRRBOX uses Peltier-based cooling alongside vacuum insulation panels and fans to achieve efficient thermal control. An onboard microcontroller will monitor temperature, record the data, and adjust the cooling output to minimize power consumption. The box will …

Effect Of Local Steel Slag Incorporation On The Mechanical Properties Of Concrete, Ahmed Safaa Tariq Karmah, Wissam Khadum Alsaraj, Luma A. Zghair

Al-Esraa University College Journal for Engineering Sciences

The increasing interest in the production of concrete through the utilization of inexpensive materials has caused a rise in the number of studies concerning the use of materials with cementitious properties, such as Silica Fume, Slag, Fly Ash and other pozzolanic materials. Moreover, the increasing amounts of Steel Slag being produced from local factories that are being deposited without an available method of disposal provides an opportunity to harness the Slag in the production of an inexpensive, and possibly better concrete. Slag has been used as both an addition and substitution of the cement and fine aggregate. The mixtures included …

Decoding Climate Change: A Comprehensive Statistical Insight Into Temperature Anomalies In Iraq And Its Neighboring Countries, Jameel T. Al-Naffakha, Mohammed R. Al-Qassabanda, Israa Jafar

Al-Esraa University College Journal for Engineering Sciences

This study applies advanced statistical techniques, including the Mann-Kendall Trend Test and ARIMA forecasting, to validate and predict temperature anomalies across Iraq and its neighboring countries (2014–2024). Findings confirm a statistically significant warming trend (p < 0.00000005) across all nations, with Syria (1.02°C) and Turkey (0.97°C) experiencing the highest anomalies. GIS-based spatial analysis highlights regional disparities, identifying climate-vulnerable zones. The persistent rise in temperature anomalies correlates with worsening water scarcity, desertification, and extreme weather events, including prolonged droughts and heatwaves. Iraq’s peak anomaly (1.48°C) has exacerbated heat stress, agricultural decline, and reduced river inflows, while Kuwait and Saudi Arabia struggle to maintain critical infrastructure under record-breaking temperatures exceeding 50°C. These climate shifts pose severe risks to water availability, food security, and energy demand, necessitating urgent policy interventions. Key recommendations include enhanced water resource management, climate-adaptive agriculture, and renewable energy expansion. If left unaddressed, rising temperatures could destabilize the region, increasing socio-economic vulnerabilities and escalating resource conflicts. This study underscores the need for cross-border collaboration and sustainable adaptation policies to mitigate the long-term impacts of climate change in the Middle East.

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

Applying Machine Learning Techniques For Early Detection Of Cyber Attacks On Iot Devices, Noor Adnan Allamy

Al-Esraa University College Journal for Engineering Sciences

This research designs, implements, and evaluates a machine learning-based framework for the early detection of cyber attacks targeting Internet of Things (IoT) devices, with a specific focus on the context and challenges present in Iraq. The study conducts a comparative analysis of three supervised learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Networks (DNN)—using a combination of benchmark datasets (NSL-KDD, CIC-IDS-2017, Bot-IoT) and a synthesized dataset adapted to simulate the Iraqi threat landscape. Key performance metrics, including accuracy, precision, recall, and F1-score, were used for evaluation. The proposed Random Forest model demonstrated superior performance, achieving an accuracy …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The surrogate …

Hybrid Experimental–Computational Study On The Energy Absorption Of Graphene Nanoplatelet-Reinforced Sandwich Structures, Hamdan Yousif Hamdan

Al-Esraa University College Journal for Engineering Sciences

Background: Sandwich composites are widely used in aerospace, automotive, and marine applications because of their lightweight, stiffness, and strength, but they remain prone to out-of-plane impacts and barely visible impact damage (BVID). Graphene Nanoplatelets (GNPs) have shown strong potential to improve fracture toughness and impact resistance. However, hybrid experimental–computational studies applying such reinforcement are still lacking in developing contexts like Iraq, where practical and accessible solutions are essential. Aims: The study investigates the effect of GNP reinforcement on the low-velocity impact behavior and energy absorption of glass fiber/epoxy sandwich panels with PVC foam and balsa wood cores. Objectives include fabricating …

Effect Of Thick Closed Walls Of West And South Elevations Of Iraqi Middle And South Territory Housing Building On Reducing Energy Use, Abeer Qasim Jbur, Shaimaa M. Hamza, Mayyadah Lutfi Abdulwahhab

Al-Esraa University College Journal for Engineering Sciences

Thermal insulation is one of the most important factors in achieving sustainability, increasing efficiency, and reducing energy consumption, but modern insulation materials are expensive, in addition to their availability. Therefore, through our research, we resorted to investigating the issue of reducing thermal load in buildings through the use of thick-walled facades in the southern and western facades, where we studied a building with two windows with windows on the southern and western facades and another without these windows and with thick walls, for two locations, the first in central Iraq, which is the city of Baghdad, and the second in …

The Impact Of Ethyl Levulinate Additive On Diesel Engine Performance And Emissions: An Experimental Study, Maha Ali Ghadbaan

Al-Esraa University College Journal for Engineering Sciences

This study explores the environmental and operational impact of adding Ethyl Levulinate—a biodegradable ester derived from biomass—to diesel fuel. A fuel blend known as B5El6 (comprising 5% biodiesel and 6% Ethyl Levulinate) was prepared and tested experimentally using a single-cylinder diesel engine operating at a constant speed of 1500 rpm under full load conditions. Performance metrics and emission data were recorded, and a Life Cycle Assessment (LCA) was conducted using the IMPACT2002+ methodology.

The results revealed that B5El6 significantly reduced greenhouse gas emissions (100 kg CO2 eq) and improved ecosystem quality. However, it presented challenges in terms of human health …

The Role Of The Scenario In Formulating The Contemporary Architectural Text, Rounaq Arif Mohsin, Abbas Ali Hamza, Bashar Shamil Alkhafaji

Al-Esraa University College Journal for Engineering Sciences

In order to create an integrated architectural text, which is a complicated art that blends beauty and practical elements, a rigorous design procedure is necessary. In this situation, the scenario’s role becomes crucial in developing the current architectural text and directing architectural approaches. In order to better understand how the scenario influences the design process and the interactions between various architectural aspects, this project intends to explore and analyze the impact of the scenario in developing and refining architectural text formulation approaches.

The study looks at the idea of a scenario and how it has been used in architecture, as …

Investigation Of Some Physical Properties Of Slurry Infiltrated Fibrous Concrete (Sifcon) Under Different Curing Times, Rand Kh. Mahmoud, Mohmmed Juad Khadhim, Fayq Hasan Jabbar

Al-Esraa University College Journal for Engineering Sciences

This research studied the effects of different types fibers (Basalt, Carbon and Basalt-Carbon hybrid mix) and curing ages (7, 14, 28 and 56 days) on some physical properties of - Slurry infiltrated fibrous concrete (SIFCON). Density, ultrasonic pulse velocity UPV, Poisson’s ratio and water absorption were measured for the experimental study with 30% cement replacement by Class F fly ash to increase sustainability. It was found that properties were significantly affected by the type and dosage of fiber admixture. The UPV was enhanced by basalt fibers and the absorption reduced up to an optimal range of 3–5% after which agglomeration …

Mechanical And Durability Properties Of Cement Panels Reinforced With Hybrid And Pva Fibers, Shukran H. Faraj, Mohammed J. Kadhim

Al-Esraa University College Journal for Engineering Sciences

This study examines the synergistic effects of hybrid fibers (HF) and polyvinyl alcohol (PVA) fibers on the structural and thermal properties of silica-fume cement panels. Scanning electron microscopy (SEM) was employed to examine mortar mixtures with varying fiber content to assess their enhancement of microstructure. We conducted several experiments on compressive, flexural, and splitting tensile strength, in addition to water absorption and thermal conductivity. The results indicate that 1% HF exhibits superior mechanical qualities, with a compressive strength of 46.89 MPa, a flexural strength of 8.56 MPa, and a reduced thermal conductivity of 0.83 W/m•K. PVA fibers at 2% enhance …

Experimental Analysis Of Droplet Deformation Dynamics In Combined Dc Electric And Shear Flow Fields Using Dpiv, Ayad Ibrahim Khlewee

Al-Esraa University College Journal for Engineering Sciences

This paper presented a systematic study of such droplet deformation at the intersection of uniform DC electric field and hydrodynamic shear flow, in which we focused on conductivity ratio (R) and permittivity ratio (S), describing their influence. The results demonstrate that droplet dynamics is extremely sensitive to the regime: under DC only, either elongation or compression depending on whether R > S or R S, similarly to classical EHD predictions. Under shear-only conditions, deformation was dictated by the balance of elongational stresses (EC) and rotational stresses (RC), with increasing capillary number (Ca) leading to progressive elongation and oscillatory orientation dynamics. When …

The Imaginary In Architecture: The Conceptual Structure Of The Imaginary And Its Manifestations In Architectural Text, Noora Ghadir Hlail, Abbas Ali Hamza Al Greiza

Al-Esraa University College Journal for Engineering Sciences

This study explores the concept of the imaginary as a collective cognitive and cultural structure that shapes symbolic reality through images, myths, and deeply rooted symbols in collective memory. The research applies this concept within the field of architecture, aiming to understand how the imaginary is embodied in architectural texts as symbolic carriers of identity and cultural meaning. Adopting a descriptive-analytical methodology, the study develops a theoretical framework comprising key components—preconditions, mechanisms, and traits of the imaginary—and applies it to two selected case studies: the General Secretariat of the Iraqi Council of Ministers and the Louvre Abu Dhabi Museum. The …

Generative Ai For Method Development In Analytical Chemistry: A New Paradigm In Experimental Design And Optimization, Yasir Fathi Mahmood

Al-Esraa University College Journal for Engineering Sciences

The fast development of artificial intelligence (AI), especially generative AI models, is changing the environment of analytical chemistry. As classical method generation in analytical methods relies on manual trial-and-error methodology as well as statistical methods, generative AI is a new paradigm with automated generation of experimental methodology and optimization. In this paper, the authors discuss the use of generative AI-based technologies, including large language models (LLMs) and neural network-based generators, to create new, efficient, and customized methods of analysis. The paper examines existing applications, technology frameworks, and issues and offers a roadmap with regards to the future incorporation of generative …

Numerical Modeling And Experimental Validation Of A High-Temperature Latent Heat Thermal Energy Storage System Using Metallic Phase Change Materials For Concentrated Solar Power Applications, Fouad Hashim Sharhan

Al-Esraa University College Journal for Engineering Sciences

To ensure reliable performance for the power-block of CSP plants, high power density and near-isothermal discharge must be achieved. A robust means of achieving this is through thermal energy storage (TES). High temperature latent heat storage (LHS) with phase change materials (PCMs) can serve these purposes, however the conventional salts used in PCMs typically suffer from low thermal conductivity that limits power density and increases energy storage charging/discharging times. This manuscript investigates ways to address these limitations using high temperature metallic phase change materials (MPCMs) while also developing a validated numerical framework to aid in their design. To this end, …

Thermal Performance Evaluation Of Solar Cooling Systems For Educational Facilities In Baghdad, Yasser Alawi Mohammed Attia Al-Jubouri

Al-Esraa University College Journal for Engineering Sciences

Schools in Baghdad also suffer from poor thermal comfort, which is a common problem in high-temperature and low-humidity arid climates such as that of the city, where using cooling devices leads to a large energy demand and overloads on the national power grid. Such study offers a thorough assessment of the thermal performance of solar-based cooling systems in an efficient manner to be suitable for educational buildings in Baghdad. The analysis is centred on a solar thermal cooling system with absorption as the heat interaction medium, and an experimental characterisation and mathematical simulation itself are performed. A pilot installation, consisting …

Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data, Yusuf Shodiyevich Avazov

Chemical Technology, Control and Management

This article examines the problem of detecting and predicting industrial equipment faults using IoT sensor data through machine learning techniques. Sensor readings such as temperature, vibration, pressure, voltage, and current, as well as FFT-based features, were statistically analyzed. Class imbalance and low signal informativeness were identified as key factors limiting model accuracy. Results obtained from Logistic Regression, Random Forest, and XGBoost models were comparatively evaluated, showing that when ROC-AUC values remain around 0.5, distinguishing fault and non-fault states becomes challenging. Correlation and feature-importance analyses confirmed the absence of strong dominant indicators. The findings highlight the need to improve sensor architecture …

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. …

Predicting Simulation Times For Multiphase Thermal-Hydraulic Models, Andrew Yule, Andrew Taylor

SMU Data Science Review

Addressing the challenge of computationally intensive OLGA

simulations in the oil and gas industry, a machine learning framework is

developed for accurate runtime prediction. A specialized feature extraction

pipeline identifies key parameters—such as simulation time, time step,

number of branches, and section count—from OLGA input files that serve as

high-impact predictors. Multiple predictive models, including regression,

tree-based ensembles, and neural networks, are implemented to validate

accuracy and robustness. Results reveal that prioritizing simulations based on

predicted runtimes optimizes licensing resources and reduces operational

costs, making real-time scheduling more efficient. This research demonstrates

the effectiveness of data-driven runtime prediction in enhancing …

Analysis Of A Cloud-Based Robot Motion Planning System, Yusif Mardanzade, Latafat Abbas Gardashova

Chemical Technology, Control and Management

As a result of the integration of cloud computing technologies into the field of robotics, the concept of "cloud robotics" has emerged. Unlike traditional robots, cloud-based robot systems remove computation, memory, and even some software from the local device and rely on remote resources obtained over the network. This approach ensures that robots are not limited only by their internal computing capabilities and allows them to take advantage of the wide range of opportunities offered by the cloud infrastructure. As a result, robots have access to large databases, highly parallel computing, and collective learning capabilities anytime and anywhere. In addition, …

Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil

Al-Esraa University College Journal for Engineering Sciences

With the considerable progress of sixth-generation (6G) networks further on the horizon, security has attracted much attention in the face of increasingly sophisticated threats, especially from quantum computing. Classical cryptographic schemes based on computational hardness are becoming more and more brittle, as they can easily be attacked with a quantum computer. Quantum Key Distribution (QKD) arises as a promising tool for information-theoretic security through quantum mechanics to obtain an unbreakable key by exchanging unknown bit sequences. In this paper, we provide an extensive survey on the integration of QKD both in the envisioned 6G architecture, including current implementations, technical feasibility, …

Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali

Al-Esraa University College Journal for Engineering Sciences

A misuse attack is the most common and dangerous type of attack that could target NFV (Network Function Virtualization). In a misuse attack, the attacker attempts to consume the NVF environment’s resources by sending a large amount of traffic. To protect the NFV environment, an early and accurate misuse attack detection system has been proposed based on NFV and Random Forest Classifier. The proposed model starts with importing the dataset and analyzing it then pre-processing and feature selection using a PSO (particle swarm optimization) Test algorithm, classification is based on the most common and efficient machine learning technique, which is …