Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) was originally founded in 1959. The publisher of the journal is Wuhan University of Technology. JWUT first got the scopus license in the year 2001. The journal generally publishes all aspect of engineering sciences like: physics, chemistry, mathematics, and all sorts of general engineering.
Scopus Indexed(2026)
Submission Deadline
Volume
50
, Issue
03
12 Jun 2026
Day
Hour
Min
Sec
Publish On
Volume
50
, Issue
03
30 Jun 2026
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Aim and Scopes
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) (ISSN:2095-3844) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are in the following fields but not limited to: :
Electrical Engineering and Telecommunication Section:
Computer Science Section :
Civil and architectural engineering :
Mechanical and Materials Engineering :
kinematics and dynamics of rigid bodies, theory of machines and mechanisms, vibration and balancing of machine parts, stability of mechanical systems, mechanics of continuum, strength of materials, fatigue of materials, hydromechanics, aerodynamics, thermodynamics, heat transfer, thermo fluids, nanofluids, energy systems, renewable and alternative energy, engine, fuels, nanomaterial, material synthesis and characterization, principles of the micro-macro transition, elastic behavior, plastic behavior, high-temperature creep, fatigue, fracture, metals, polymers, ceramics, intermetallics.Chemical Engineering :
Food Engineering :
Physics Section:
Mathematics Section:
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Experimental and Simulation Enhancements in Buck Converter Comportment Using SHO Method
Power electronics circuits are characterized by nonlinear dynamics, originating in cyclic topological transitions in circuits. The power converters, which are an integral component of power electronics circuits, ensure power conversion between power source and load. The nonlinear dynamics in DC-DC converters result under variations in converter parameters, load, reference voltage and current. In nominal operating conditions, such converters exhibit a stable period-1 switching cycle. In nonlinear operation, bifurcation, chaotic behavior, quasi-periodicity, and period doubling may result, yielding insights on system malfunctions. This work is aimed towards analyzing and modulating the nonlinear behavior exhibited by the Buck converter. The converter is in voltage mode control (VMC) and in continuous conduction mode (CCM) and is described by a mathematical formulation and simulated in MATLAB. Systematic variations in parameters of the converter recognize that the switching converter is able to exhibit aberrant behaviors including bifurcation, quasi-periodic, and chaotic behavior, and thus may produce instable system behavior. Our contributions include applying Spotted Hyena Optimizer (SHO) technique in simulation and experimental implementation to optimize the operation of the Buck converter and to eliminate nonlinear effects including bifurcation, double periodicity, and chaos. The technique is directed towards optimizing PID controller parameters by minimizing variation between reference voltage and observed values to ensure greater stability and efficiency. A Buck converter prototype is developed and regulated in real time using a dSPACE 1104 card. The proposed technique is validated through computational and experimental data, indicating its ability to minimize nonlinear effects in the Buck converter. The obtained results improve the important of this approach to ameliorate the performance of the Buck converter and eliminate the undesirable phenomenon.
Neural Depth-GAN Diffusion: An Advanced GAN-Diffusion Framework for High-Fidelity 2D-to-3D Image Reconstruction
Leveraging GANs with Depth-Guided Diffusion, this work introduces Neural Depth-GAN Diffusion, a novel and enhanced framework for 2D-to- 3D picture reconstruction utilizing state-of- the-art artificial intelligence algorithms. Combining Generative Adversarial Networks (GANs), diffusion models, and monocular depth map estimation guarantees computational efficiency by means of which major challenges in 3D reconstruction including precise depth estimation, effective handling of occluded regions, and preservation of geometric consistency across complex structures are addressed. Extensive research on well-known datasets as ShapeNet and KITTI indicates how better our approach is than present state-of- the-art alternatives. Neural Depth-GAN Diffusion not only saves a lot of processing time but also remarkably excels across frequently utilized metrics including Peak Signal-to- Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Chamfer Distance (CD). These findings show how successfully our paradigm strikes a mix between quality and efficiency. Moreover, the flexibility of the proposed method qualifies it for a broad spectrum of pragmatic applications including augmented reality (AR), autonomous driving, and medical imaging. By enhancing accuracy and computing feasibility, Neural Depth-GAN Diffusion sets new benchmarks in artificial intelligence-driven image processing across various domains by so giving a transformative answer to 2D-to- 3D reconstruction issues.
Assessing Contractor Performance Using Key Performance Indicators in the Construction Industry
Contractor selection is a critical determinant of success in construction projects, directly influencing cost, schedule, and quality outcomes. Despite its importance, existing evaluation methods often lack objectivity, particularly in emerging markets like Egypt. This study proposes a standardized framework for contractor assessment using Key Performance Indicators (KPIs) during both prequalification and project execution phases. Through a systematic literature review (2015–2025), we identify 12 globally recognized KPIs and validate their relevance to the Egyptian context via expert surveys (N=200). A pilot case study of two social housing projects demonstrates the framework’s applicability, ranking contractors based on cost deviation, time adherence, client satisfaction, and defect rates. Results indicate that Contractor A outperformed Contractor B in 5 of 6 KPIs. The study contributes a data driven methodology to enhance decision making in contractor selection, aligning Egypt’s construction sector with international best practices.
Relation between the Fundamental Requirements for Implementing Strategic Environmental Assessment )SEA) and Accomplishing the Objectives of Goal-11 of the United Nations Sustainable Development Goals (UN-SDGs) 2030
This study deals with the topic of Strategic Environmental Assessment (SEA) due to its crucial significance in the decision-making process, which has become a vital aspect of any development projects. Proposed policies, plans, programs, and strategic initiatives that affect the environment generally are the main focus of the idea of SEA, Unlike Environmental Impact Assessments (EIA) of projects, SEA is not used as frequently, and The Summit Strategy which aims to improve the project's environmental assessment, promote environmental protection, and achieve sustainable development. The study aims to describe the fundamental prerequisites for putting the SEA process into practice, as well as the procedures required to carry out those prerequisites, It also seeks to establish the connection between SEA and the procedures for accomplishing the eleventh goal of Sustainable Development Goals (11-SDGs), which is about making cities sustainable and moving toward the UN- Sustainable Development Goals 2030.
Phenol treatment of petroleum refinery wastewater by using electrocoagulation/ electrooxidation technique
Water pollution resulting from industrial waste, toxic biological waste, and water resulting from the refining process of crude oil: all of these pollutants are dumped into the environment and have become one of the problems of the current era because they contain toxic organic and inorganic pollutants. In this study, work was done to reduce the percentage of one of the pollutants present in the oil refining process water of the Najaf refineries in Iraq, represented by the organic substance phenol (C₆H₅OH), where laboratory experiments were carried out using electrical methods represented by the processes of electrocoagulation (EC) and electrooxidation (EO), and these two processes achieved remarkable success in the process of removing dissolved phenol. The work was done using aluminum and graphite electrodes as a canopy for the electric cell and steel electrodes (S.S.) as a cathode for the cell made of resistant plastic. The initial concentration of phenol in the treated water was 50 ppm under the following conditions for both processes: electric current density (10, 15, 20) mA/cm², sodium chloride (NaCl) concentration (0, 1.5, 3) g/L, and acidity (pH) (3, 7, 10) with a constant time of one hour for the (EC) process and two and a half hours for the (EO) process. The results showed the elimination rate is directly proportional to high current density and sodium chloride concentration under moderately acidic conditions, where the optimum conditions for the removal process were (CD = 20) (PH = 7) and (NaCl = 3). A removal rate of 95.05% was achieved under the conditions mentioned.
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/Journal of Wuhan University of Technology (Transportation Science and Engineering)