Engineering Commons^™

Integrity Assessment Of Shipping Line Pipelines Using Risk-Based Analysis To Determine Risk And Maintenance Strategies, Ade Ratih Anggraini, Dwi Marta Nurjaya

Journal of Materials Exploration and Findings

Pipeline Shipping Lines X, Y & Z are classified as critical infrastructure, being the only transportation through the crude oil lifting from P and R location to the transfer station in NM Area. To maintain the workflow of the Shipping Line, integrity assessments and risk evaluation are required to ensure the operational and safety. Anomalies were found by analysing inspection, monitoring, and repair data, while the pipelines' future integrity was assessed by calculating the remaining life. Risk-Based Analysis (RBA), which is a modification of Kent Muhlbaeur's method, is employed to conduct the risk assessment using the Probability of Failure (POF) …

Characteristics Of Carbonaceous Materials Synthesized From Palm Oil Empty Fruit Bunch Waste Using Ferrocene Catalyst, Ahmad Nabil Shahab, Adinda Izzatul Islam, Afif Wardana, Ilham Nur Dimas Yahya, Ary Yanuar Tri Amalia, Nofrijon Sofyan, Donanta Dhaneswara

Journal of Materials Exploration and Findings

The synthesis of carbonaceous materials for reduced graphene oxide (rGO) precursors using oil palm empty fruit bunches waste as a carbon source offers a sustainable solution for waste management in the palm oil industry while delivering high-performance materials. The oil palm empty fruit bunches were carbonized, followed by acid washing, pyrolysis with ferrocene (8%, 12%, and 16% variations), and ultrasonication to produce rGO. The structural, electronic, and morphological properties of the rGO were analyzed using various characterization techniques. The band gap values decreased with increasing ferrocene concentration, from 1.14 eV (8%) to 1.06 (16%), indicating enhanced electronic conductivity. XRD analysis …

Assessment Of H2s-Induced Cracking Susceptibility In Steam Line Pipes And Weld Zones During Geothermal Well Construction, Riene Kaelamanda Pragitta, Yudha Pratesa

Journal of Materials Exploration and Findings

The susceptibility of steam line pipes, especially in the HAZ (heat-affected zone) and weldment areas, to hydrogen sulfide in the geothermal industry is crucial to understand from the early stages, particularly during construction. The combination of tensile stress from residual stresses after welding and metallurgical phase transformation makes the joint areas vulnerable to sulfide stress cracking. This condition becomes even more extreme when the equipment operates during the well stimulation phase. This research assesses the severity of H₂S-induced cracking using NACE MR0175 and ISO 15156-1 standards, focusing on the effects of pH and partial pressure of H₂S (p_{H₂S …}

A Hierarchical Soft Computational Model For Optimizing Agricultural Uavs: Recruiting Neutrosophic Theory And Tree Soft Sets, Mona Mohamed, Nurhan Alaa, Bilal Arain, Karam M. Sallam

Neutrosophic Systems with Applications

Precision agriculture is being transformed by Unmanned Aerial Vehicles (UAVs), which make it possible for yield optimization, targeted spraying, and sophisticated crop monitoring. With an emphasis on their operational capabilities, economic feasibility, and environmental implications, this research explores the revolutionary potential of UAV technology in contemporary farming systems. Practically speaking, the procedure of opting UAVs for agricultural applications is complicated by several competing aspects, inherent uncertainties, and differing stakeholder agendas. This paper suggests a new hybrid decision framework that combines Tree Soft Sets (TrSS), Neutrosophic theory, and Multi-Criteria Decision-Making (MCDM) to methodically handle these issues. Hence, the robust hybrid model …

Development Of Aczel-Alsina Aggregation Operators In Neutrosophic Cubic Sets For Multi-Expert And Multi-Criteria Weighting: Optimizing Alternative Fuel Technology Selection, Majid Khan, Muhammad Gulistan, Aitazaz A. Farooque, Mohammed M. Al-Shamiri, Witold Pedrycz

Neutrosophic Systems with Applications

Managing vague and uncertain data has long been a challenge in decision-making (DM), particularly in scenarios where criteria and expert assessments play a critical role. This paper introduces operational laws based on Aczel-Alsina (AA) norms within Neutrosophic Cubic Sets (NCS) to more effectively handle uncertainty. Leveraging these operational laws, we propose two aggregation operators: the Neutrosophic Cubic Aczel-Alsina Weighted Averaging (NCAAWA) and the Neutrosophic Cubic Aczel-Alsina Weighted Geometric (NCAAWG) operators. These provide a comprehensive approach to data aggregation, preserving both additive and multiplicative influences on outcomes in complex systems. In DM, the importance of weights is paramount, and we introduce …

Offering A Manufacturing Curriculum Online To Rural Schools: The Case Of The Nimm Project, Raymond A. Dixon, Farjahan Shawon

Journal of Research in Technical Careers

This case study examined the extent to which the two implemented manufacturing pathways of the NIMM project successfully facilitated access and engaged high school students from rural regions in two manufacturing curricula. The program consisted of two tracks or career pathways for manufacturing technicians: Mechanical CADD technician and Electro-Mechanical technician. The Mechanical CADD program was delivered online, and the Electro-Mechanical program was delivered online and through a summer skills academy. Findings include, students showed less preference for CTE manufacturing courses in an online asynchronous format, CTE instructors need to be trained to teach online, proper IT infrastructure is needed for …

How Do Parents Influence Female Students' Engineering Trajectory?, Niloufar Bayati, Cameron Denson

Journal of Research in Technical Careers

Using the Parental Socialization Framework, this research provides a detailed analysis of how early STEM exposure, parental confidence in abilities, and gender-neutral upbringing contribute to the development of STEM identities among women. Employing a hermeneutic phenomenological approach, six undergraduate women engineering majors were interviewed in-depth about their parents' influence on their STEM pathways. The findings reveal that parents' high academic expectations, confidence in their daughters' abilities, verbal and non-verbal encouragement, and early STEM opportunities are pivotal in steering female participants toward engineering. The study also underscores the importance of creating a gender-neutral environment that allows girls to explore and develop …

Spin Coater Design With Pid Algorithm Using Polynomial Regression Approach And Bias Tuning For Tio2 Deposition Process, Geo Surya Andika, Nofrijon Sofyan, Donanta Dhaneswara, Akhmad Herman Yuwono

Journal of Materials Exploration and Findings

The thin-film deposition technique using spin coating offers a cost-effective alternative to Chemical Vapor Deposition (CVD) and Physical Vapor Deposition (PVD). The spin-coating process requires precise control of the motor drive system to ensure that the rotational speed, measured in rotations per minute (RPM), aligns with the set point and remains stable. This study presents the design and development of a spin coater prototype to achieve uniform thin-film deposition. The control method employed utilizes a Proportional-Integral-Derivative (PID) algorithm, incorporating a polynomial approach with bias tuning. The PID control was chosen to achieve stable operation in a non-linear system. The performance …

Towards Explainable And Robust Nlp: Neutrosophic Probability Augmentation In Text Classification, Nabil M. Abdel-Aziz, Mahmoud Ibrahim, Khalid A. Eldrandaly

Neutrosophic Systems with Applications

The rapid growth of textual data necessitates advanced text classification models. However, traditional methods struggle with ambiguity and uncertainty in natural language, reducing classification reliability. To address this, we integrate neutrosophic logic, which explicitly models truth, indeterminacy, and falsity, into a DistilBERT-based text classification framework. Additionally, we employ data augmentation using synonym replacement to enhance generalization. Our approach is evaluated on the AG News dataset, classifying articles into four categories: World, Sports, Business, and Science/Technology. By incorporating neutrosophic attributes, the proposed framework assesses text quality, mitigates uncertainty, and improves robustness against ambiguous inputs. Experimental results demonstrate an accuracy of 94.10%, …

Single Valued Neutrosophic Hypersoft Set Based On Merec-Moosra Mcdm Methods For Evolution Of Sustainable Strategies For The Circular Supply Chain Based On The Beverage Industry, Alaa Salem, Rayan Hussein, Ahmed Abdelmouty, Mohamed Abouhawwash

Neutrosophic Systems with Applications

Corporate enterprises around the world are facing increasing pressure to operate sustainably due to rising environmental concerns such as climate change, resource scarcity, and ecological degradation. In response, circular supply chain (CSC) practices have emerged as a promising solution, especially within the manufacturing and beverage sectors. CSC focuses on reusing materials, minimizing waste, and creating value from products that have reached the end of their lifecycle. This study investigates the challenges and opportunities of applying circular supply chain management (CSCM) in the beverage industry, which is known for generating significant waste due to high production volumes. The research identifies key …

Deep Learning Algorithms For Traffic Flow Predictions, Adegoke Ojeniyi, Prince Pal Singh, Ankita Vashisht, Swati Kumari, Karan Karan

AUIQ Technical Engineering Science

Given the growing complexity of urban transportation systems, precise traffic flow forecasting is essential for reducing not only issues of congestion but also, for boosting road safety and enhancing mobility management. This study integrates Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Long Short-Term Memory (LSTM), and Recurrent Neural Networks (RNN) to present a hybrid deep learning framework for traffic prediction. Of these, the CNN-LSTM model is a reliable option for real-time traffic forecasting since it successfully captures both spatial and temporal dependencies, resulting in superior predictive performance. The dataset used to assess the framework includes 48,120 records from a traffic monitoring …

Investigating The Impact Of Waterhead, Time And Temperature On Dam Displacement: Application Of Computer Aided Models, Maaz Abdullah

AUIQ Technical Engineering Science

Dam displacement is a crucial indicator for assessing the safety of a concrete dam through structural health monitoring. Since the displacement data exhibits a non-linear and complex relationship with influencing factors like waterhead, time and temperature, machine learning models are deployed to accurately predict dam displacement. Furthermore, the limited availability of monitored data in the majority of the dams renders the studies conducted with a large number of observations valueless. In order to address the aforementioned issues, this study proposes a feature selection approach to predict dam displacement by examining the ability of four ensemble machine learning models on different …

Comparative Assessment Of Land Surface Temperature In Urbanized Areas Of The Saudi Arabia, Rauf Khan, Syed Ilyas, Ziaul Haq Doost

AUIQ Technical Engineering Science

Land Surface Temperature (LST) has become a critical urban climate concern due to rapid urbanization and land cover transformation in Saudi Arabian cities. This study aimed to analyze the spatial and temporal variability of LST in three climatically distinct cities encompassing Riyadh (hot desert), Dhahran (hot humid), and Abha (cold desert) over the summer months (May to September) from 2017 to 2021. LST was retrieved through the RSLab Landsat LST web application. A total of 80 samples per year were compiled for each city using a structured sampling approach, and results were aggregated using the RS-LST Aggregation Framework (RSLAF). The …

Optimizing Hydrological Pan Evaporation Prediction Using Advanced Machine Learning Techniques With Spectral Clustering, Labib Sharrar

AUIQ Technical Engineering Science

Accurate prediction of pan evaporation remains a significant challenge due to inconsistencies across different climatic regions. This study aims to enhance pan evaporation estimation by developing a robust hybrid machine learning (ML) model that integrates spectral clustering with advanced regression techniques, specifically the Histogram-based Gradient Boosting Regressor (HGBR) and Extreme Gradient Boosting Regressor (XGBR), to improve prediction accuracy and adaptability across diverse environments. The research developed a novel methodology by employing spectral clustering for models' performance enhancement, followed by rigorous hyperparameter tuning, sensitivity analysis to assess the impact of individual features on each model. Finally, models underwent lack of fit …

Classification Of Daily Weather Conditions Using Decision Tree-Based Machine Learning Models: A Case Study Of Kabul, Afghanistan, Ahmad Bilal Ahmadullah, Ahmad Shah Irshad, Basir Ahmad Khaled

AUIQ Technical Engineering Science

As global climate variability intensifies, the need for accurate and reliable weather forecasting becomes increasingly important. This study aimed to classify daily weather conditions in Kabul, Afghanistan, by comparing two decision-tree-based machine learning (ML) models that includes Decision Tree Classifier (DTC) and Extra Trees Classifier (ETC). A complete year dataset consisting of 366 daily meteorological observations collected from a central weather station in the region for 2024 was used. Results revealed that the DTC model consistently outperformed the ETC model, obtained an overall accuracy of 99% in both the training and testing phases, compared to the ETC model's accuracy of …

Distal Weight-Bearing Implants Design Featuring An Integrated Groove Or Thread, Muntadher Saleh Mahdi, Dunya Abdulsahib Hamdi

AUIQ Technical Engineering Science

The distal weight-bearing implant was selected from a pool of approximately 17 implant systems that utilize the osseointegration mechanism currently available globally. It stands out due to its modernity, rarity, and creative concept, offering amputees with ``above-knee amputation'' a range of options that ensure their satisfaction and fulfill their requirements. However, this implant requires additional refinement and adaptation to achieve the highest level of perfection. This research implemented various modifications to the mechanical design of the implant, which were subsequently evaluated using the finite element analysis software ``ANSYS.'' Modifications included substituting the threads along the femoral stem with a groove …

Surface Urban Heat Island Effects Analysis In The Most Populated City In Thailand: Towards Sustainable Urban Development, Abdul Maulud Khairul Nizam, Muhammad Noor, Zafar Iqbal

AUIQ Technical Engineering Science

The fast and unprecedented urban growth process may violate cities' responsibilities by causing an urban heat island (UHI) and increasing the public's risk of heat-related illnesses due to vegetative area reduction and urban area inclination. The Bangkok Metropolitan Area (BMA)'s variations in Land Use Land Cover (LULC), Land Surface Temperature (LST), UHI, and several geospatial indicators, as well as the daytime and nighttime LST, are the main subjects of the study. Between 2015 and 2021, the highest Daytime LST (DLST) rose consistently from 36.77°C to 38.14°C, then slightly decreased to 37.22°C in 2023. There is a general increase in the …

A Comprehensive Review Of Advancements In Materials And Manufacturing For 3d Knee Implants, Huda Ali Hashim, Ghaidaa A. Khalid

AUIQ Technical Engineering Science

Over the past three decades, knee implant design has significantly advanced to address the challenges of replacing damaged knee joint bone with durable and efficient prosthetics. The aim of this review explore key developments in materials and manufacturing processes, focusing on biocompatible options such as zirconium, titanium alloys, UHMWP, and smart materials, as well as coatings designed for metal-sensitive patients. The study examines the mechanical forces acting on implants during daily activities, highlighting wear and infection risks, and evaluates the role of innovative manufacturing techniques in improving implant precision, cost-efficiency, and durability. Simulation methods, including Finite Element Analysis (FEA), are …

Investigating The Differential Effects Of Smote Variants On Class Imbalance And Exploring Their Applicability To A Thalassemia Prediction Model, Hussam Mezher Merdas, Ayad Hameed Mousa

AUIQ Technical Engineering Science

Researchers work around the clock on many datasets provided by various institutions. These researchers strive to come up with highly efficient Artificial Intelligence models. Often, researchers face the problem of imbalance in the distribution of classes in a particular feature in the selected dataset, which creates an Artificial Intelligence model biased towards one class at the expense of another class that is no less important than the first. On the other hand, thalassemia is a disease that affects people of different ages. The degree of disease varies according to the thalassemia class. This study proposes an improved Machine Learning model …

Wide Band Single-Mode Optical Fiber Design For Decreasing Bending Loss, Zahraa M. Kassem Alasady, Ahmed Al-Amiery

AUIQ Technical Engineering Science

Radiation loss due to fiber curving or bending is a major challenge in advanced technical applications like fiber-optic sensing or biomedical applications. This study focuses on the basic features that characterize a single-mode fiber (SMF) and its critical parameters in view of the recent improvements made. The planned design of SMF is, however, intended to resolve these problems by proposing minimizing bend loss by adopting a five-layer fiber structure designed to keep the optical field within the fiber core. The proposed SMF design exhibit ultra-low bending sensitivity, with estimated bending loss of 2×10-3 dB/turn for bending radius of 5 mm. …

Development Of Fuzzy Ontology For Explainable Artificial Intelligence For Decision-Making In Fuzzy Environment, Pavel Kosov

Chemical Technology, Control and Management

In modern artificial intelligence systems, there is an acute need to understand the decision-making logic of "black box" algorithms. Our research proposes an innovative method for increasing the transparency of such systems through the formalization of fuzzy explanatory mechanisms. We have developed an extension of existing ontological approaches by introducing the concept of fuzziness into the structure of explanatory properties, which allows overcoming the fundamental limitations of traditional XAI methods. The proposed formalization is based on the theory of collective mental models and principles of fuzzy logic, providing a more accurate reflection of uncertainty and subjectivity in expert knowledge. Our …

Application Of Quantum Algorithms In Optimization Of Cognitive Decision-Making Systems, Noilakhon Yakubova

Chemical Technology, Control and Management

The article analyzes the potential of quantum algorithms for optimizing cognitive decision-making systems in production processes in the energy sector. Compared with traditional algorithms, quantum algorithms allow high-speed processing of large amounts of variable data in real time and solving multiparameter problems based on an integrated approach. The study considers uncertainties and issues of increasing efficiency in the processes of production and distribution of electricity using a cognitive model. The integration of quantum algorithms into this model allows developing optimal strategies for using resources in production. A heating boiler was taken as a control object, and taking into account its …

Improving Image Quality In Electrical Capacitance Tomography Using Otsu Thresholding, Josiah Nombo

Tanzania Journal of Engineering and Technology (TJET)

Electrical Capacitance Tomography (ECT) is an imaging technique used in industrial process monitoring, particularly for monitoring and measuring the composition of multiphase flows. Despite its widespread application, the commonly used Linear Back Projection (LBP) algorithm often produces low-quality images due to its limited ability to handle high permittivity contrasts and nonlinearities. This study investigates the use of Otsu thresholding as a post-processing technique to enhance ECT image quality. By maximizing inter-class variance in the image histogram, Otsu thresholding improves contrast, clarity, and structural definition, enabling more effective segmentation of oil and gas components in multiphase flows. The proposed Otsu-based reconstruction …

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, …

Influence Of Substrate Temperature On The Properties Of Reactive Dc Magnetron Co-Sputtered Ag-Doped Tio2 Thin Films, Hezekiah B. Sawa

Tanzania Journal of Engineering and Technology (TJET)

This study reports on the influence of substrate temperature on the properties of Ag-doped TiO2 thin films. The films were deposited by reactive DC co-sputtering of Ti and Ag targets at different substrate temperatures and Ag target sputtering powers. Grazing incident X-ray diffractometer confirmed that all films were polycrystalline with dominant peak oriented along (101) planes representing the anatase TiO2 phase. The average grain size of the samples improved with increase in deposition temperature. At a substrate temperature of 450 ℃, the samples had a dominant peak representing the rutile phase, suggesting partial transformation from anatase to rutile phase. The …

A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha

Tanzania Journal of Engineering and Technology (TJET)

This research uses a critical realist framework to examine the factors influencing the success of enterprise resource planning (ERP) system implementation in Zimbabwean mining industry organisations. From the perspective of critical realism, the mining industry in Zimbabwe faces a complex interplay of opportunities and obstacles while implementing ERP systems. The deployment of ERP in mining firms is critically examined in this paper, emphasising how these systems might improve operational efficiency while considering Zimbabwe's particular socioeconomic circumstances. By exploring underlying structures, mechanisms, and outcomes, the research aims to identify critical challenges and opportunities and develop practical recommendations for improving ERP adoption …

Cellulose Recovery From Waste Denim Fabrics Through Indigo Vat Dye Reduction And Spandex Dissolution, Tito N. Venance

Tanzania Journal of Engineering and Technology (TJET)

This study addresses environmental conservation by tackling end-of-life management for post-consumer denim garments through the recycling of cotton fibres from waste denim. The purification process involved dithionite reduction of vat dyes in the presence of an alkali followed by selective dissolution of spandex using N,N-dimethylformamide (DMF). Optimal conditions for dye removal were determined at 90°C for 120 minutes with sodium hydroxide at 25 g/L, sodium dithionite at 6 g/L and PVP at 4.5 g/L, while spandex extraction was achieved using a 5% DMF solution at 70°C for 4 hours. Ultraviolet (UV)-vis spectrophotometric analysis indicated a significant increase in whiteness (DL*). …

Development Of A Microcontroller-Based Intelligent Traffic Light Control System For Vehicular Movement In T-Junctions, Frederick O. Ehiagwina

Tanzania Journal of Engineering and Technology (TJET)

This research is devoted to the issue of regulating traffic congestion in major cities using light-dependent resistors coupled with the PIC16F877A microcontroller. This study proposes an intelligent traffic control system for T-Junctions, utilizing sensing and control to optimize traffic flow through dynamic phase adjustments and congestion reduction, enabled by a microcontroller-based decision-making system. The proposed system reduces traffic congestion, automates control, and enhances safety, minimizing accidents and lowering infrastructure costs. Under simulated environment, it demonstrates an average response time of 50 ms and achieves 99% accuracy in displaying the correct countdown. Finally, the number of state transitions handled per minute …

Assessment Of Factors Contributing On Early Rotting Of Chromated Copper Arsenate Treated Utility Power Distribution Wood Poles In Tanzania, Innocent J. Macha

Tanzania Journal of Engineering and Technology (TJET)

The study aimed to assess the factors contributing to the premature decay of Chromated Copper Arsenate (CCA) treated utility power distribution wooden poles in Tanzania. Deteriorated poles samples from various regions in Tanzania were analyzed using handheld X-ray spectrometry to quantify the retention of CCA preservative chemicals. The ages of these poles were estimated based on annual growth rings. The findings indicated that premature failure of CCA treated wooden poles is attributed to an imbalance in the chemical composition of the preservative solution. The study found that CuO retention in most samples ranged between 10-18 kg/m3, significant lower that the …

Effect Of The Cao Catalyst Concentration Based On Barnacle Shells (Tetraclita Squamosa) On Biodiesel Production From Coconut Oil, Rinjani Rakasiwi, Sri Rezeki, Nurul Hafiza, Wivina Diah Ivontianti

Makara Journal of Technology

Barnacle shells are a source of the calcium oxide (CaO) catalyst, which is nontoxic, highly alkaline, and biodegradable. This study aims to determine the characteristics and the effect of the CaO catalyst concentration obtained from the calcination of barnacle shell particles at a temperature of 900 ℃ for 2 and 4 h on the transesterification reaction of biodiesel from coconut oil. Transesterification was conducted at 65℃ for 2 h with a methanol/coconut oil molar ratio of 6:1. The concentration of the CaO catalyst was varied (i.e., 1wt%, 3wt%, 5wt%, 7wt%, and 9wt%) for coconut oil. The results of the characterization …