Journal of Engineering and Sustainable Development
Journal of Engineering and Sustainable Development, College of Engineering, Mustansiriyah University, Baghdad, Iraq ISSN (print): 2520-0917 ISSN (online): 2520-0925 The Journal of Engineering and Sustainable Development (JEASD) is an international peer-reviewed open-access scientific journal published by the College of Engineering, Mustansiriyah University, Baghdad under the regulations and standards of the Ministry of Higher Education and Scientific Research in Iraq. It aims at disseminating leading-edge knowledge and expertise in multi-disciplinary sustainable engineering topics to researchers, academic scientists, and postgraduate students. A double-blind peer-reviewing system is being used to assure the publication's quality. In the meantime, the journal commits itself to the regulations of the Committee On Publication Ethics (COPE). JEASD is an open-access journal in that contents are free of charge. 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College of Engineering, Mustansiriyah University, Baghdad, Iraq
The Journal of Engineering and Sustainable Development is an open-access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowed to search, download, share, distribute, print, or link to the full texts of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article. Creative Commons-Attribution (BY)
Demand-Response Energy Management for Renewable-Based Electric Ship Microgrids
Electrically driven ships operate as self-contained renewable microgrids that combine power from solar and wind, along with battery energy storage, to supply propulsion and auxiliary loads. Their operation depends on the real-time coordination of distributed sources under varying environmental and load conditions. This study introduces an Artificial Neural Network-based surrogate model for the Demand-Response Energy Management System (DREMS) framework that performs real-time scheduling of renewable and dispatchable sources to meet the load requirement. This lightweight model serves as a data-driven surrogate for estimating solar and wind power outputs using meteorological data as inputs. These estimates are used by the DREMS, together with load and storage conditions, to determine optimal scheduling decisions for all power units. The approach is validated through simulations in MATLAB/Simulink using practical wind and irradiance profiles from publicly available data. The simulation results demonstrate the capability of the proposed framework to maintain supply-demand balance, coordinate renewable-energy unit commitment, and support stable operation under varying renewable-generation and load conditions. Although the study focuses on an electric-driven ship, the proposed framework can be applied to isolated renewable microgrids with similar operating conditions.
Copyright (c) 2026 Naveen Kumar Thotakanama, NAGARAJA RAO SULAKE, Manickavasagam Krishnan (Author) https://creativecommons.org/licenses/by/4.0
Next-Level 5G Channel Prediction Using Residual Convolutional Neural Network (ResNet)
Accurate channel estimation is critical for achieving the high reliability and low latency required by 5G New Radio (5G NR) systems. Conventional estimators, including Least Squares (LS) and Practical Channel Estimation (PCE), rely on linear models that fail to capture nonlinear channel characteristics. Linear Minimum Mean Square Error (LMMSE) improves accuracy but requires prior channel statistics and a costly matrix inversion, limiting its real-time applicability. This paper proposes a lightweight ResNet-based channel estimator that treats the complex time-frequency channel matrix as a two-dimensional image. Convolutional layers exploit spatial correlations across subcarriers and Orthogonal Frequency Division Multiplexing (OFDM) symbol dimensions, while residual skip connections stabilize training and enable correction over a coarse LS estimate. The model is trained end-to-end using Demodulation Reference Signal (DMRS) pilot patterns in a fully 3GPP-compliant 5G NR environment based on TDL-A and TDL-C channel models (TR 38.901). Simulations over 0–30 dB SNR show consistent superiority over all benchmarks. At SNR = 10 dB, the proposed method achieves a Mean Squared Error (MSE) of 0.0177 — a 45% gain over PCE, ~90% over LS, and 29% over ChannelNet — with only ≈0.29 million parameters, single-stage training, and an inference time of 2–5 ms per OFDM frame, suitable for real-time 5G deployments.
Orthogonal Frequency Division Multiplexing
Copyright (c) 2026 Emad A. Hussien, Mohanad Abd Shehab, Abdulaziz Saleh Yeslem Bin-Habtoor, Alfian Ma’arif, Takele Ferede Agajie (Author) https://creativecommons.org/licenses/by/4.0
Experimental Study to Evaluate the Load-Bearing Capacity of Autoclaved Aerated Concrete Block Walls
It is common to use Autoclaved Aerated Concrete (AAC) blocks in the construction of partition walls and infills because of their distinctive properties, including ease of work, energy conservation, and enhanced sustainability. Experiments for the strength evaluation of AAC load-bearing walls are still limited. This paper presents an experimental study of the behavior of AAC blocks as load-bearing walls under static loads up to failure. Due to the difficulty of using the direct contact method to measure and monitor deformations in walls, the Digital Image Correlation (DIC) method was used to obtain the required data throughout the test. Eight specimens of confined walls were tested to study the effect of the thickness of the block, type of bonding material, and type of plastering on the wall strength and failure modes. ‎ The results showed that the smaller the thickness of the AAC block, the greater the strength of the wall. Also, using adhesive mortar leads to the cohesion of the wall and increases its load-bearing capacity better than using cement-sand or gypsum mortar. In addition, strengthening the plastering with steel wire meshes showed superior performance in wall behavior in improving cracking resistance and ultimate loads.
Copyright (c) 2026 Sarra’a Dhiya’a Jaafer, Ashraf A. Alfeehan (Author) https://creativecommons.org/licenses/by/4.0
Human Verification System Based on Fuzzy Rule
The integration of humans with computers is advancing biometric systems, particularly in utilizing DNA biometrics for human verification and identification, especially in forensic contexts. DNA analysis has significantly improved forensic examinations, aiding in detecting crimes such as murders and rapes and identifying unidentified corpses. Additionally, DNA profile analysis plays a crucial role in determining paternity. The main objective of this research is to develop a human identification system that is fast, cost-effective, error-free, and equipped with user-friendly graphical interfaces. The system aims to enhance accuracy in forensic applications, utilizing fuzzy logic to improve the identification process through the use of fuzzy inference. The proposed system employs fuzzy logic to enhance accuracy in DNA motif identification. Multiple experiments validate the system's performance, demonstrating its high accuracy and scalability in handling large datasets. The experiments conducted have shown that the proposed system offers essential functions for forensic applications, significantly contributing to genetic and forensic processes. The system demonstrated high accuracy and scalability, with an improvement of 27% in accuracy compared to pre-existing systems. The proposed system stands out for its speed, cost-effectiveness, and error-free operation, with a user-friendly graphical interface.
Copyright (c) 2026 Hiba Abdulelah Dawood, Mustafa Dhiaa Al-Hassani, Majeed Arsheed Sabbah (Author) https://creativecommons.org/licenses/by/4.0
Experimental Study on Coastal Drainage Solutions for Ky Anh Urban Area, Ha Tinh Province, Vietnam
In the Central region of Vietnam, the heavy rains, low land, tidal influence, and rapid urbanization have caused coastal urban flooding to be a major and growing concern. This study focuses on assessing the drainage capacity and proposing flood drainage solutions for the Ky Anh urban area (Ha Tinh Province) through an integrated hydrological-hydraulic modeling approach. The MIKE modeling system was applied to study, including MIKE NAM, MIKE 11, MIKE 21 FM, and MIKE FLOOD. Calculation scenarios were developed based on the historical rainfall event of October 2020, combined with a 10% design tidal range and climate change projections. Simulation results indicate that the existing drainage system in Ky Anh has exceeded its capacity, resulting in severe and prolonged flooding under adverse rainfall–tidal interaction conditions. Unidirectional drainage solutions offer limited effectiveness, whereas diversion schemes and multidirectional combined solutions yield superior results. Analysis shows that peak flood levels were reduced by 0.7–0.9 m, alongside a reduction in inundated areas of over 60% and a significant shortening of flooding duration. The study confirms that a systems-based, inter-regional, and modeling-based drainage approach is a crucial scientific basis for planning and managing coastal urban areas adapted to climate change.
Copyright (c) 2026 Vu Hoang Diep, Le Van Nghi, Nguyen Minh Ngoc (Author) https://creativecommons.org/licenses/by/4.0
Deep Learning-Based Monitoring System to Enhance IoT Network Performance
The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle the dynamic and high-dimensional traffic generated by IoT environments. This study investigates the effectiveness of deep learning models, including Feedforward Neural Networks (FFNN), Convolutional Neural Networks (CNN), and Multilayer Perceptron (MLP), for enhancing IoT network monitoring. The models were trained using both synthetic and real-world IoT traffic datasets in MATLAB with Adam and Stochastic Gradient Descent with Momentum (SGDM) optimizers to improve convergence and training stability. Experimental results demonstrate that deep learning models outperform traditional machine learning techniques in detecting complex traffic patterns and anomalies. Among the evaluated models, CNN achieved the highest accuracy of 94%, compared with Decision Trees (78.5%) and Support Vector Machines (85.7%). CNNs effectively capture spatiotemporal traffic characteristics, while MLPs efficiently model nonlinear relationships in network data. The proposed framework provides a scalable, reliable approach to real-time IoT network monitoring.
Copyright (c) 2026 Radhi Sehen Issa, Gregor Alexander Aramice, Noorulden Basil, Mustafa Mahdi Ali, Takele Ferede Agajie, Alfian Ma’arif (Author) https://creativecommons.org/licenses/by/4.0
Structural Efficiency and Embodied Carbon Assessment of Pre-Engineered Versus Conventional Steel Beams
The increased focus on the reduction of greenhouse gas emissions in the building and construction sector has heightened the demand for structural systems that reduce both material and embodied carbon. Pre-engineered building (PEB) systems using tapered built-up steel beams could potentially offer a viable alternative to traditional hot-rolled prismatic sections by better matching and aligning the sectional capacity and the bending demand. However, there are still a limited number of studies that perform comparative analyses integrating structural and environmental impact. This study assessed the structural efficiency and embodied carbon of pre-engineered and conventional steel beams over spans of 6 to 20 m for fixed-end and pinned-end boundary conditions. Structural design was performed in accordance with AISC 360-16, and embodied carbon was assessed for life cycle modules A1–A5 following BS EN 15978. The results indicate that tapered built-up beams achieve higher utilisation ratios and smaller effective section sizes, particularly for short and intermediate spans. Life-cycle assessment shows that pre-engineered beams reduce embodied carbon by approximately 10–25% compared with conventional beams, primarily owing to their lower steel mass. These findings demonstrate that tapered built-up beams offer both structural and environmental advantages in the investigated design context.
Copyright (c) 2026 Riza Suwondo, Made Suangga, Militia Keintjem, Traad Alzhrani (Author) https://creativecommons.org/licenses/by/4.0
A Comparative Study for Fruit Classification Using Different CNN Machines
The automation of fruit categorization and recognition is gaining popularity, yet it is becoming increasingly challenging due to low contrast and ambiguous features. Nonetheless, autonomous fruit categorization is a complex process reliant on the locations, shapes, colors, and sizes of the objects. In this paper, five Convolutional Neural Network (CNN) models for fruit classification are evaluated to determine the best-performing model. These models are: AlexNet, VGG16, VGG19, ResNet50, and GoogleNet. The architecture layers of the deep learning methods are presented, including convolutional, pooling, and fully connected layers. To evaluate different measures of the model's performance, the confusion matrix is applied. The performance of the CNN models is evaluated on a dataset of 1000 images, with 200 images per category. The results show that VGG16 achieves the best performance among the models used in these investigations. The VGG16 model has achieved an accuracy of 0.901, an error rate of 0.099, and 0.9 for all of (precision, recall, and F-measure, respectively).
Copyright (c) 2026 Abdulqader F Abdulqader, Yahya T. Qassim (Author) https://creativecommons.org/licenses/by/4.0
Performance Characterization of Rubberized Asphalt Mixtures Incorporating Waste Tire and Solid Natural Rubber
The performance of asphalt mixtures modified with 7% and 10% waste tire and solid natural rubber is assessed in this study, along with the effects of replacing fine aggregate with these materials. According to binder testing, a 10% rubber modification improved viscosity and deformation resistance while raising the softening point to 62.25°C. According to Marshall's findings, modified binders needed a higher optimal asphalt content of 6.05% to 6.25%. While the 7% modification produced the highest stability of 23.0 kN, replacing 50% of the river sand with Solid Natural Rubber decreased stability to 6.29 kN, falling short of requirements due to reduced structural rigidity. The 10% rubber mixture showed notable increases in stiffness modulus, increasing by 88.99% at 25°C and 105.69% at 40°C, according to testing. Additionally, the 10% modification achieved the highest durability, with 3,701 cycles, a 9.4% improvement over the control, according to the Indirect Tensile Fatigue Test results. According to the study's findings, rubber modifications of 7% and 10% greatly increase load-bearing capacity and fatigue resistance; however, in order to preserve the pavement's structural stability and integrity, rubber use as a fine aggregate replacement must be strictly limited.
Copyright (c) 2026 Ramadhani Ramadhani, Hendrik Jimmyanto, Rindu Twidi Bethary, Lega Lubis Reskita (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of Groundwater Development Potential by Using System Dynamics Modeling
Groundwater in aquifers is a very important resource that can flow over long distances to meet the needs of areas that require it. However, its existence beneath the surface requires a good understanding of the water system to manage it properly. This study aimed to develop a system dynamics model to analyze the impact of water balance on the sustainability of groundwater resource development in Parepare, Indonesia. Meeting urban water needs through groundwater use is approximately 4,526,864 m³/year, significantly larger than surface water at 2,799,948 m³/year. System dynamics modeling was conducted using STELLA 10.0.4, with a 10-year simulation period. The research results show that this area experiences a rainy season for 9 months and a dry season for 3 months, but groundwater recharge occurs only for 6 months, with recharge potential ranging from 85,858 m3/month to 62,885,852 m3/month. Based on the results of the system dynamics modeling, the potential for groundwater recharge remains very high, supporting the development of new groundwater production wells to meet the water shortage, with a capacity of 239,208 m3/month.
Copyright (c) 2026 Ramli Muhammad, Aryanti Virtanti Anas, Asta Arjunoarwan Hatta, Hasbi Bakri (Author) https://creativecommons.org/licenses/by/4.0
Design and Test an Educational Model of a Robotic Arm on an Experimental Platform
A robotic arm with five degrees of freedom has been developed for use in learning laboratories. The arm's movements were designed and simulated in SOLIDWorks and LabVIEW. The LabVIEW Softmotion was used to impose motion constraints on the model. An Arduino Mega microcontroller was used to manipulate the servo motors in the joints. After the design and simulation, the system was implemented on a laboratory setup. The following steps were then specified to ‎verify the results of the LabVIEW-designed model with the real physical laboratory. These tests were the transfer of mass between two predetermined points along a certain direction. Its limitations were actuator torque and arm ‎stability limitations. Lastly, the comparison between the physical setup and the model showed high accuracy and performance in the execution of the movements. This study’s ‎findings show a qualitative enhancement in education laboratory equipment and extend to the establishment of an integrated learning system that connects the simulated model to the real laboratory systems.
Copyright (c) 2026 Ammar Fadhil Hussein AL-Maliki, Ehsan Sabah Al-Ameen, Rouzbeh Nouhi Hefzabad, Abeer K. Abd (Author) https://creativecommons.org/licenses/by/4.0
Theory and Practice for Outdoor Spaces of Urban Challenges: An Environmental Sustainable Design
This article explores the idea of living in outdoor environmental design. It works to highlight the necessity of creating outdoor spaces that will simultaneously create positive physical and mental health effects while observing sustainable environmental practices that increase quality of life. In addition, it emphasizes the role such ideas can have in spreading environmental consciousness through society. The findings of the research may constitute a theoretical guidance to promote sustainable process design, but their implementation at the local scale is still scarce. In this paper, we examine how local government and community-based organizations are beginning to adopt standards for sustainable environmental design. It highlights the importance of climate-conscious, practice-based, and site-specific outdoor living design in global and local contexts as an effective means to advance environmentally sustainable design through best practices. The described work in this paper also proves, however, that the Sustainable-Based Design approach with local context intelligence can directly contribute to the change of social, economic, and environmental conditions. Findings underscore the importance of community-based approaches for minimising social and psychological fallout from wars, terrorism, and pandemics that interrupt behaviour patterns and collective identity.
Copyright (c) 2026 Lina Kifah Kadhum, Tahrir Taki Ali Almusawi, Ashwaq Fadhel Muhkaber Alomari, Awadh Ajeel, Zainab Qahtan Abd Alrazzaq Alkhayat, Luai Nuaman Andagani (Author) https://creativecommons.org/licenses/by/4.0
Influences of Multi-Evacuation Strategies on Smart Networks
Catastrophes have increased over recent years, highlighting the need for effective disaster management systems. The largest earthquake to hit Turkey since 1939 caused damage to roughly 350,000 km² and affected 16% of Turkey's population. United Nations development experts estimate 1.5 million people were left homeless. The confirmed death toll was 53,537, with damage estimates at US$148.8 billion. Roads and communication disruptions hampered the pre-planned Disaster and Emergency Management system. Previous assessment of intelligent emergency response systems emphasizes the need for transportation networks in large-scale catastrophes. This study shows how the Intelligent Transportation System could be utilized in conjunction with emergency evacuation strategies in various situations. Meanwhile, to assess the evacuation strategies' performance, the Intelligence Disaster Management System uses different technologies, like mobiles, Social media, and vehicle devices, etc., in place of communication infrastructure and platforms. These strategies include demand, destination, and speed strategy. This research aims to model system performance and the aftermath of a disaster in a realistic urban transport city. Later, findings are compared with a control group that had a previous disaster control system. The combination of strategies compared to a singular strategy showed an increase of flow volume of 1.92 times greater.
Copyright (c) 2026 Zubaida Alazawi, Khalid Chaloob, Laith Farhan Jar, Omar Alani, Arunachalam Sundaram, Ivan Holmes (Author) https://creativecommons.org/licenses/by/4.0
EFFECT OF USING MIRRORS ON THE EFFICIENCY OF SILICON SOLAR CELL TEXTURED WITH TRIANGULAR GROOVES BY USING ZEMAX
Solar cell (photovoltaic cell) efficiency depends on the amount of sunlight falling on its surface and reflection within the cell. Different methods are used to improve solar cell efficiency. In this paper, we use triangular grooves on the upper surface of the silicon cell to reduce outside reflection on the surface of the cell and increase the internal reflection withinthe cell by putting mirrors on the four sides of the cell. We compare the performance of this cell using the Zemax program for different aspect ratio (A.R) values and incident angles of the rays against another cell with triangular grooves and no mirrors. For R=1, with a parallel incidence angle of the triangular grooves of =50, the number of rays that hit the detector is equal to2998 in the case of using mirrors. However, it was equal to 1200 without mirrors with across incidence angle of the triangular grooves of =50 = and (A.R)=1thenumber of rays for the case using mirrors was equal to 2960, and 1000 without mirrors.
Solar cell, Mirrors, Zemax, Incident angle,Grooves, Aspect ratio
Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0
Behavior of Steel Fiber Reinforced Concrete Deep Beams at Elevated Temperature
This paper presents an experimental investigation on the behavior of steel fiber reinforced concrete deep beams at elevated temperature. Twelve reinforced concrete deep beams were cast and tested. The beams were tested under a four-point loading scheme after being subjected to elevated temperatures of 25 (room temperature), 200 °C, and 400 °C. Three volumetric steel fiber ratios of 0, 0.2 and 0.4% and two ratios of shear span to effective depth of 0.4 and 0.8, were used. Results show that ultimate loads of deep beams are increased when heated at 200°C by 69.39%, 28.75% and 4.24%, and decreased when heated at 400°C by 2.04%, 25%, and 42.37% for steel fiber ratios of 0, 0.2%, and 0.4%, respectively. Steel fibers perform better in unheated beams. Incorporating 0.2 and 0.4% of steel fibers increases ultimate loads by 63.27% and 140.82% for unheated beams, 24.1% and 48.19% for beams heated at 200°C, and 25% and 41.67% for beams heated at 400°C, respectively. Also, the shear span to effective depth ratio still dominates the strength of deep beams at elevated temperature as at ambient temperature.
Copyright (c) 2026 Jawad K. Al-Bayati, Mohammed Hashim Mohammed, Esraa Kh. Mohsin Abuzaid, Siti A. Osman (Author) https://creativecommons.org/licenses/by/4.0
Cement Plant Power Demand Prediction Using 1D Convolutional Neural Network Model: A Case Study
The management and operation of the power system would be significantly enhanced if accurate prior knowledge of power exchanges were provided, which could provide valuable insights into the system and help predict the required energy, enabling appropriate solutions to various challenges and preventing failures. The power consumption, reactive power, and power factor are critical parameters for assessing the performance of power system operations and planning. This paper presents One-Dimensional Convolutional Neural Networks (1DCNN) models for forecasting fluctuations of these parameters within the electrical power demand of a cement factory, thereby enabling effective monitoring of the cement production line. In addition, Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (Bi-LSTM) models are modified to improve their effectiveness. Subsequently, the outcomes of the models were compared with those of conventional ARIMA models. Meanwhile, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Bias Error (MBE), and Mean Absolute Percentage Error (MAPE) are used to evaluate the predictive model's accuracy. It is a frequently used metric, especially in regression tasks. The results indicated that the suggested models can effectively predict the behavior of such a power system with an RMSE of less than 3%.
One-Dimensional Convolutional Neural Networks
Copyright (c) 2026 Tawfeeq E. Abdulabbas, Sawsan M. Mahmoud , Hanan A. Al-Jubouri , Hongbo Du, Khalid S. Aleja , Mustafa S. Agha (Author) https://creativecommons.org/licenses/by/4.0
Survey and Geospatial Analysis of Soil Salinity and Organic Carbon Dynamics in Garmian District, Iraq
Soil organic carbon (SOC) is crucial for maintaining soil health, as it supports microorganisms, improves soil structure, and regulates nutrient availability. Typically, SOC and salinity exhibit an inverse relationship, influenced by factors such as vegetation, topography, salt composition, and climate. In this study, we mapped soil salinity (ECe: 0.55–3.14 dS/m) and measured SOC (4.5–10.4 g/kg) at 50 field sites. The study employed statistical and spatial analyses, combined with remote sensing and geographic information systems, to quantify the interaction between them. The study found that SOC generally declines with increasing salinity, with a clear threshold at 1.43 dS/m. Beyond this threshold, further SOC loss slows, likely due to the mitigating effects of salinity-tolerant grasses and calcium-rich parent material on sodium stress. Vegetation cover (short grasses occupying 29.3 % of the area) helped sustain soil organic carbon even under higher salinity. These findings align with our research objectives by quantifying the relationship between SOC and salinity and identifying the primary factors that control it. The results suggest that promoting salinity-tolerant vegetation and applying calcium-based amendments are effective strategies for maintaining SOC levels in semiarid, calcareous soils. The study findings provide actionable spatial guidance for targeted soil management and ecological planning in similar regions.
Normalized Difference Vegetation Index (NDVI)
Copyright (c) 2026 Salim Neimat Azeez, Iraj Rahimi, Ayad M. Fadhil Al-Quraishi (Author) https://creativecommons.org/licenses/by/4.0
Application of Nano-Titanium Dioxide to Collapsible Gypseous Soils for Stabilization
Nano titanium dioxide is a soil chemical additive that can act as a cementing agent and water barrier. This research aims to investigate how different percentages of NTD affect the collapsibility and severity of natural sandy soils with gypsum contents of 35, 50, and 60%, taken from three other locations in the Salah Al-Deen government. Single- and double-oedometer tests were conducted to investigate the collapsibility of gypseous soils stabilized with NTD and to compare them with untreated soil samples. All test results for both single- and double-oedometer tests showed a significant effect of NTD on decreasing Cp values, with varying percentages and, hence, a transformation in the degree of severity across the three tested soils at NTD percentages of 0.1, 0.3, and 0.5%. These findings suggest that even trace amounts of NTD could be a promising agent for stabilizing collapsible gypseous soils in civil engineering projects. This could lead to more stable and reliable ground support in areas with prevalent soil types. Advances in the application of nano titanium dioxide are opening new avenues for enhancing soil stabilization techniques and ensuring the longevity of engineering structures.
Copyright (c) 2026 Najwa Wasif Jassim, Mastura Azmi, Mohammed Yousif Fattah (Author) https://creativecommons.org/licenses/by/4.0
Bibliometric Analysis of Sustainable Public Transport Indicators: Trends of Global Research from 2000-2024
This article offers a bibliographic review of studies undertaken concerning sustainable public transport and the importance of sustainability indicators to the growth of the transport field. The study used a total of 430 Scopus-indexed articles published between the years 2000 and 2024 using the phrases “sustainable,” “public transport,” and “indicators.” These articles were reviewed using the software packages VOSviewer and Biblioshiny. The article explores the contribution of the indicators towards the analysis and implementation of sustainable transport systems, and their added value and limitations. The findings of the article indicate that the leading country concerning the publication of articles is China, and the leading journal is Sustainability (Switzerland). The most used keywords are “indicators,” followed by “transport,” “sustainability,” and “sustainable transport systems.” The most used indicators are emissions, energy consumption, and accessibility, followed by user satisfaction and cost efficiency. These are used concerning the environmental, societal, and economic aspects of the sustainability of the transport systems. The leading nation studied herein is Italy, and there are various studies that highlight the progress of the intelligent and sustainable mobility systems of the Italian States.
Copyright (c) 2026 Ala Zuhier Keblawi, Mohd Rosli Mohd Hasan, Khaled Ahmad Al-Sahili, Ahmad Farhan Sadullah, Samer Saeed Abdulhussein (Author) https://creativecommons.org/licenses/by/4.0
Structural Fragility Behavior of Steel Lattice Power Transmission Tower Subjected to High-Intensity Wind Loading
Transmission towers are indeed vital components of power transmission lines, but they also belong to the category of complex structural systems. The ultimate strength of this system can be highly compromised by strong wind forces that may act on it, and thus allow a situation where there is an outage in the event of storms. This paper presents a case study assessment for a steel lattice high-voltage transmission tower located within Iraq’s territory after experiencing extreme-intensity wind loads (tornado). An inelastic dynamic analysis was carried out to establish the effects of tornado wind loads on such types of structures. Two different approaches were adopted by this research; one based on performance per scaled full-scale model applying various independent intensities’ loadings, while the other used a constant, systematically scaled set of records representing different levels of intensities. A cross-validation methodology was used to acquire the dynamic stability of the lattice tower. The results showed that this high-intensity wind speed is greater than the minimum design loads of the latest development code for structures in this area. There is an urgent need to check on those transmission towers located within highly risky areas, as emphasized by this study.
Copyright (c) 2026 HUSAIN KHALAF JARALLAH, Hayder Ali Abbas (Author) https://creativecommons.org/licenses/by/4.0
Effect of Flow Splitters on Energy Loss in C-Type Piano Key Weirs
Piano key weirs (PKWs) are a new type of labyrinth weirs. They have a longer crest length within a limited width and, unlike linear weirs, ultimately have a higher discharge coefficient. The higher energy loss in PKWs can reduce scour. Therefore, this study used flow splitters on the weir crest and two C-type PKWs with heights of 0.18 m and 0.20 m. The splitters had rectangular and circular cross-sections. They were arranged in three configurations: two-by-two, four-by-four, and six-by-six in each cycle. The results showed that the presence of a flow splitter increases energy loss. Additionally, as the number of splitters increases, energy loss increases, and the discharge coefficient decreases. Adding six rectangular flow splitters to the weir per cycle resulted in an average increase in energy loss of approximately 10.40% and a decrease in the discharge coefficient of 18.60%. On average, rectangular flow splitters had 1.24% higher energy loss than circular ones. The energy loss in weirs with rectangular and circular flow splitters increased by about 6.89% and 5.72%, respectively, compared to those without flow splitters. A 10% increase in weir height led to a decrease in both the discharge coefficient (by about 9.20%) and the energy loss (by about 1.68%).
Copyright (c) 2026 Amirhossein Fathi, Wadi Mohammed Wadi, Ali Khoshfetrat, Seyed Hamid Alavi (Author) https://creativecommons.org/licenses/by/4.0
Baffle Pier Effects on Hydraulic Performance and Scour Downstream of Sluice Gates
Sluice gates control water levels and discharge them into small irrigation canals. This study examined a modified stilling basin incorporating submerged baffle piers downstream. The study analyzed hydraulic-jump characteristics, energy-dissipation efficiency, velocity distribution patterns, water-level fluctuations, and bed configurations resulting from flow downstream of the sluice gate. The experimental program comprised ninety runs using ten stilling basin models. These models involve various stilling basins with different baffle pier heights and angles, tested under a range of flow conditions. A smooth apron without baffle piers served as the reference case for comparison. Results showed that baffle piers with a height of 12 cm and a 45° angle oriented against the flow optimized stilling basin performance, improving flow characteristics and minimizing bed configuration. This optimal design decreased dimensionless jump length by 45-47%, increased energy dissipation efficiency by 46-60%, and reduced maximum velocity by 33% compared to the smooth apron across the tested Froude number range. Based on these results, a multiple regression analysis was conducted to develop an empirical equation to predict energy dissipation in the modified stilling basins. These findings provide practical design guidelines for optimizing the performance of stilling basins in small irrigation canal systems.
Copyright (c) 2026 Ibrahim M.M , Baydaa Hamdi Salih, Ahmed M. Ibraheem, Abeer Samy (Author) https://creativecommons.org/licenses/by/4.0
Cost Modeling of the Construction Safety Management System (CSMS) in Road Construction Projects in South Papua Province, Indonesia
The implementation of the Construction Safety Management System (CSMS) in road construction projects in Indonesia, particularly in South Papua Province, continues to face significant challenges due to limited guidance and inconsistent safety cost estimation. A key element of CSMS is proper safety budgeting, yet many project estimators lack adequate understanding of how these costs should be calculated. This study aims to estimate safety budgets for asphalt road construction projects using a cost modeling approach based on road length and width. Research data were obtained from cost budget plans, price quantity lists, unit price analyses, and as-built drawings. Descriptive analysis was applied to determine the proportion of safety costs, followed by multiple linear regression to develop a predictive model relating CSMS costs to road dimensions. The findings show that the average CSMS cost accounts for 1.17% of the total project value. The regression results indicate that safety costs increase with project scale. Each additional kilometer of road adds approximately IDR 29.5 million (USD 1,845), and each additional meter of road width adds approximately IDR 8.6 million (USD 537). These results provide practical guidance for contractors and procurement authorities in allocating safety budgets more accurately and strengthening compliance with construction safety regulations.
Copyright (c) 2026 M Asad Abdurrahman, Anggun Meranti Yuwandari Baswetan, Rosmariani Arifuddin (Author) https://creativecommons.org/licenses/by/4.0
Neural Network Prediction of Mass Transfer Coefficients in Distillation Columns Using Aspen Hysys
Predicting the mass transfer coefficient (K) is one of the most important parameters in industrial separation processes, as it greatly determines the efficacy of distillation in separating components between the liquid and vapor phases. Traditional approaches find it difficult to model K dependence on operational factors such as reflux ratio, molar feed flow rate, and feed composition. This research combines the Aspen Hysys simulation and artificial neural networks (ANNs) to write K as a function of these variables in a benzene-toluene binary system. Aspen Hysys was used to simulate a continuous distillation column that produced K values under different conditions. This data was used to train an ANN (3:4:1 multilayer perceptron) to predict K. The ANN's training performance was 95.3%, and its predictive accuracy was high. This composite method can improve predictive performance in the optimization of distillation column design and operation. It can be effectively used as a tool in industrial practice.
Copyright (c) 2026 Shahad Z. Al-Najjar, Hayder A. Alhameedi, Salih A. Rushdi, Zainab T. Al-Sharify, Helen Onyeaka, Suzanne Alsamaq (Author) https://creativecommons.org/licenses/by/4.0
A Compact High-Gain Dual-Band Antenna for Ultrawideband Applications
This study deals with the extensive development of multiband antennas, compact in size and high in performance, to meet the requirements of modern wireless communication systems, namely the Ultrawideband (UWB) applications. This research presents the design of a Dual-Band Patch Antenna (DBPA) that works at 4.1 GHz and 6.7 GHz frequency ranges. This design offers a proposed solution to efficiently overcome the challenges of designing single-band microstrip patch antennas and the obstacles associated with the operation of conventional ones by achieving a noticeable increase in gain. The proposed antenna achieves a noticeable gain of approximately 10.227 dB at the frequency of 4.1 GHz and 4.982 dB at 6.7 GHz while achieving compact dimensions (65.2 mm 7 76.6 mm 1 1.6 mm) using an FR-4 substrate. In addition, the simulations show a fairly well-matched input impedance, a reflection coefficient of less than -10 dB, and a Voltage Standing Wave Ratio (VSWR) of less than 2 in both operating frequency ranges. The antenna also develops a uniform radiation pattern that suits various UWB communication applications. This performance is attributed to the good positioning and the appropriate dimensions of the rectangular slots, which leads to modifying the current path and focusing the surface wave, which enhances the gain and radiation efficiency.
Copyright (c) 2025 Ali Khalid Jassim Al shamariy (Author) https://creativecommons.org/licenses/by/4.0
Buckthorn Leaves as an Efficient Material for Simultaneously Multi Eco-Friendly Purposes
Zinc, an essential element, offers numerous benefits; however, an excessive accumulation of zinc within the human body can pose detrimental effects. This study endeavors to mitigate zinc contamination in water sources through an adsorption process utilizing buckthorn leaves as a cost-effective, natural adsorbent. The investigation examined various operational parameters that affect the adsorption process, including pH levels, initial zinc ion concentrations, buckthorn leaf dosage, contact duration, temperature, and agitation speed. The results showed that 78% was the maximum removal of zinc ions, achieved at the optimum conditions of 6, 25 ppm, 4.5 g, 120 min, 45 °C, and 350 rpm, respectively. Furthermore, the residual buckthorn leaves, laden with zinc ions, were evaluated for potential utilization as an organic fertilizer for white beans. The investigation entailed determining the zinc ion content adsorbed by the leaves. Subsequent cultivation trials demonstrated a noteworthy enhancement in bean pod yield from soil treated with zinc-loaded leaves, exhibiting a 9% increase compared to soil treated solely with raw leaves or left untreated. Notably, the resulting crop mass was equivalent across all treatment groups. Thus, this study presents an innovative approach to simultaneously manage solid waste and purify water, offering an efficient, cost-effective, and environmentally sustainable solution
Copyright (c) 2025 Suha Anwer Ibrahim, Alanood A. Alsarayreh, Teba Tariq Khaled, Mohammed Nsaif Abbas (Author) https://creativecommons.org/licenses/by/4.0
Production of Heat-Insulating Concrete Hollow Block
Hollow concrete blocks are primarily used in residential buildings, factories, and multi-storied construction. The main goal is to produce a new insulation block from lightweight concrete by mixing light expanded clay aggregate (LECA) at a specified weight percentage with gravel. A trial-and-error method was used to determine the mixture ratio (cement: sand: lightweight aggregate) of (1:1.75:3.25) by weight, with a water-to-cement ratio of 0.48. Cubic, cylinder, and block samples were prepared with various volume proportions of LECA by natural coarse aggregate in percentages of (0, 50, and 75) %. Mechanical and physical properties, such as compressive and tensile strengths, density, and thermal conductivity, were investigated at ages 7, 14, and 28 days. The test results show that incorporating LECA reduces the density and compressive and tensile strengths, and enhances the blocks' insulating characteristics. Additionally, the thermal conductivity of the prepared specimens decreased by approximately 57% in blocks containing 75% LECA. The results are promising and indicate that the present insulation block can be used in composite slabs.
Copyright (c) 2026 Ibtesam F. Nasser, Ikram Ameen Saeed, Manolia Abed Al-Wahab Ali, Sawsan Abd-Alkarem Jihad (Author) https://creativecommons.org/licenses/by/4.0
The Effect of Hydrogen on Performance of Internal Combustion Engine Fueled by Compressed Natural Gas
The natural gas can readily serve as the replacement fuel for internal combustion engines. This work tested the SI engine when running on a hydrogen-enriched compressed natural gas (CNG) mixture. The modelling has been implemented at a range of engine speeds from 1000 to 5500 rpm with a full load, direct injection, and a spark-ignited engine with a compression ratio of 10. Engine performance influences were examined, especially regarding brake power, brake thermal efficiency (BTE), and brake specific fuel consumption (BSFC), in addition to the combustion characteristics like cylinder temperature and pressure. A Lotus Engine Simulation program was used for analyzing and modeling. The results demonstrated that the best performance and combustion characteristics were with mixtures that have increased in the H2 percentage. The results show that the brake power and BTE increased, and the BSFC decreased with the increase of hydrogen in the mixture. It was found that the brake power and BTE increased by 2% and 21% for HCNG 25, and the best reduction in BSFC was 6% for HCNG 20 compared to the CNG. It was also observed that maximum cylinder pressure (Pmax) and temperature (Tmax) increase with increasing percentage of H2 in the mixture.
Copyright (c) 2025 Fouad Alwan Saleh, Abdulrahman Shakir Mahmood, Mohammed Kadhim Allawi, Ali Khalid Shaker Al-Sayyab (Author) https://creativecommons.org/licenses/by/4.0
Using Harris Hawks Optimization to Determine Optimal Placement and Sizing of Shunt Capacitors and Distributed Generators
The power supply problem represents one of the never-ending problems that constantly remain prominent. Consequently, we continuously improve power generators, networks, and system configurations. The installation of shunt capacitors and distributed generators represents the main improvement. Because electricity systems are constantly growing, maximizing benefits and minimizing disadvantages is necessary. Therefore, one of the most important aspects of growing algorithms is optimization. In this work, Harries Hawks Optimization (HHO) is the optimization technique suggested to calculate and determine the optimal size of the shunt capacitors and distribution generation on the radial distribution system. The reconfiguration method (RM) is an approach that refers to the best and optimal location of the distribution generation and the shunt capacitor. The main goal of selecting the optimal size (using HHO) and optimal placement (using RM) is to minimize the voltage deviation. This paper presents three cases: the first case includes determining the optimal voltage deviation after installing shunt capacitors on radial distribution networks; the second case involves calculating the optimal voltage deviation after installing distribution generation on this system. The last case is conducted to calculate the optimal voltage deviation after installing SC and DG simultaneously. Results of the proposed HHO algorithm show a considerable reduction in the voltage deviation rate. That is, the voltage deviation is minimized to 38.95%, 75.13%, and 90.23 % in the three cases, respectively. The proposed approaches (HHO and RM) are applied to the IEEE 69-bus power system. Three scenarios have been used to demonstrate the effectiveness and superiority of the suggested methods.
Copyright (c) 2026 Ali D. Abdulazeez, Mazin T. Muhssin, Petr P. Oschepkov , Bahaa Hussein Al IGEB (Author) https://creativecommons.org/licenses/by/4.0
Characteristics of Novel Lightweight Concrete Strengthened by Waste Copper Fiber and Steel Fiber
Fear of the increase in global warming, the construction sector seeks to find an alternative to traditional concrete. This paper aims to create high-performance aerated-polystyrene lightweight concrete reinforced by micro-steel fibers and sustainable waste copper fibers that meet sustainable criteria for sound and thermal insulation, and high compressive strength for lightweight concrete that satisfies structural criteria. The methodology was carried out by preparing reference lightweight concrete, in addition to eight aerated-polystyrene lightweight concrete mixtures reinforced by micro-steel fibers and waste copper fibers with ratios of (0.3, 0.6, 0.9, and 1.2) % by concrete volume for each kind. The mechanical characteristics, dry density, thermal conductivity, ultrasonic pulse velocity, scanning electron microscopy, and acoustic impedance were investigated, and compared with the reference concrete without fibers. The final results displayed that the maximum compressive strength of A-EPSC reinforced by micro-steel fibers and waste copper fibers were 56.9 MPa and 55.9 MPa respectively with a maximum density of 1917 Kg/m3. The originality of this research was to adopt waste copper fibers as a sustainable free-cost fiber resulting from the coils of damaged electronic and electrical devices instead of micro-steel fibers to produce aerated-expanded polystyrene lightweight concrete, as an alternative to micro-steel fibers.
Copyright (c) 2025 Samer Abdulhussein, M.Z.A. Mohd Zahid , Izwan B. Johari, Nada Mahdi Fawzi (Author) https://creativecommons.org/licenses/by/4.0