Spectrum of Mechanical Engineering and Operational Research
Spectrum of Mechanical Engineering and Operational Research (SMEOR) publishes high-quality scientific papers that contribute significantly to the fields of mechanical engineering and operational research. The material published is of high quality and relevance, written in a manner that makes it accessible to this wide-ranging readership. Spectrum of Mechanical Engineering and Operational Research is an international peer-reviewed journal covering the main aspects of mechanical engineering and operational research and providing a source of information for applied scientists. Spectrum of Mechanical Engineering and Operational Research (SMEOR) aims at this important task by providing a venue for high-quality scientific papers that contribute significantly to the field of mechanical engineering and operational research. The material published is of high quality and relevance, written in a manner that makes it accessible to a wide-ranging readership. Papers reporting original theoretical and/or practice-oriented research or extended versions of the already published conference papers are all welcome. The scope of the journal covers the whole spectrum of mechanical engineering and operational research. Papers for publication are selected through a double-blind peer-review process to ensure originality, relevance, and readability. In doing that, the objective is not only to keep the quality of published papers high but also to provide a timely, thorough, and balanced review process. General Journal guidelines for authors Spectrum of Mechanical Engineering and Operational Research publishes research articles, reviews, short communications, and case studies. Research articles must include: motivation for the work, an adequate overview of the representative work in the field including up-to-date references, a clear statement of the novelty in the presented research, suitable theoretical background, one or more examples to demonstrate and discuss the presented ideas and, finally, conclusions. Short communications are usually 4-7 pages long, research articles and case studies 8-14 pages, while reviews can be longer. Page number limits are not strict and, with appropriate reasoning, the submitted articles can also be longer or shorter. Authors are requested to follow the SMEOR guidelines and strictly format their manuscripts as per the article template that is available here. If extensions of previously published conference papers are submitted, Editors will check if sufficient new material has been added to fulfill the journal standards and qualify the submission for the review process. The added material must not have been previously published. New results are desired but not necessarily required; however, the submission should contain expansions of key ideas, examples, elaborations, etc. of the conference submission. Aims and Scope: The principal aim of the journal is to bring together the latest research and development in various fields of decision science. We would like to highlight that papers should refer to Aims and scope, but they are not limited to. Publication Frequency: One issue per year is published online, but processed and accepted papers, with full bibliographic data, are added to the issue continuously over the whole year. Open Access: This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. eISSN (Online): 3042-0288 Publication fee: There is no submission charge or publication fee. Publication in SMEOR is free of charge for the authors. Publisher: Scientific Oasis, Tekeriška 28a, 11000 Belgrade, Serbia, Email: office@scientificoasis.org Indexing: Google Scholar; ROAD; Crossref; The digital repository of the National Library of Serbia; doiSerbia;
Modeling Uncertainty in Engineering Problems Using Asymmetric Interval Numbers (AINs)
Engineering systems are increasingly complex and subject to multiple sources of uncertainty arising from geometric tolerances, material variability, and operating conditions, which significantly affect performance and reliability, making accurate modeling of uncertainty essential in modern engineering analysis. Classical interval analysis is a well-established approach for representing uncertainty; however, traditional interval numbers (CINs) assume a symmetric and uniform distribution around the central value, whereas in practice, uncertainties are often asymmetric due to uneven measurement errors, technological deviations, or differing consequences of overestimation and underestimation. As a result, symmetric intervals may distort risk assessment and reduce the accuracy of results. This study introduces Asymmetric Interval Numbers (AINs), a generalization of classical interval numbers that allows independent modeling of uncertainty in the positive and negative directions. AINs provide a more realistic and flexible framework for representing asymmetric data distributions while retaining the simplicity of interval analysis. To demonstrate their applicability, three case studies involving different classes of engineering problems were conducted, and the results show that AINs improve the realism, stability, and interpretability of uncertainty modeling compared with classical interval approaches, confirming their potential as an effective tool for engineering analysis.
Copyright (c) 2025 Szymon Śniegowski, Adrianna Świder, Andrii Shekhovtsov, Wojciech Sałabun (Author) https://creativecommons.org/licenses/by/4.0
A Simple Approximation for Indentation of Finite Elastic Layers by Parabolic, Conical, and Flat-ended Cylindrical Indenters
In this work, we develop simple approximation formulas for the indentation of compressible elastic layers of arbitrary thickness by parabolic, conical, and flat-ended cylindrical indenters. Most surprisingly, a compact “Pythagoras-like” interpolation between the half-space and thin-layer limits provides an excellent solution to the problem. The proposed empirical expressions are validated against extensive Boundary Element Method simulations, showing remarkable accuracy across a wide range of elastic moduli, Poisson’s ratios (up to 1/3), indenter geometries, penetration depths, and layer thicknesses. The approach is further extended to adhesive contacts of flat-ended punches, yielding compact estimates of adhesion forces in layered systems. Owing to their simplicity and robustness, the presented formulas provide practical correction rules for interpreting experimental indentation data, particularly in nanoindentation and atomic force microscopy of thin films and biological materials.
Copyright (c) 2025 Valentin L. Popov, Mikhail Popov, Iakov A. Lyashenko (Author) https://creativecommons.org/licenses/by/4.0
Finding Humanitarian Supply Chain Management Challenges using Uncertain MCDM Methodology
Challenges have emerged for Humanitarian Supply Chain Management (HSCM), a valid and prominent subject today. It primarily focuses on stakeholders, including governments, various non-governmental organisations (NGOs), donors, suppliers, and affected communities. Addressing these challenges enhances disaster response efficiency, resource allocation, and aid delivery. In this work, we have selected several criteria, namely funding, coordination, infrastructure, transparency, logistics, and sustainability. Triangular fuzzy numbers (TFNs) are used as a mathematical tool to handle uncertainty. Data sets are collected from two decision-makers who provide their decisions in linguistic terms, which are then converted into crisp numbers. The weight of the criteria is evaluated using a popular multi-criteria decision-making (MCDM) methodology, specifically the Criteria Importance Through Inter-criteria Correlation (CRITIC) method.
Humanitarian Supply Chain Management (HSCM)
Copyright (c) 2025 Kamal Hossain Gazi, Aditi Biswas, Tripti Basuri, Arijit Ghosh, Sankar Prasad Mondal (Author) https://creativecommons.org/licenses/by/4.0
A Comprehensive Review on Climbing Robots: Mechanisms, Adhesion Techniques, and Applications
Robots that climb have recently emerged as an important class of mobile robots; they are capable of negotiating vertical or inclined surfaces and therefore have a great advantage in hazardous or hardly accessible environments for humans. Such robots will find critical applications in the inspection of infrastructures, the maintenance of nuclear plants, search and rescue operations, and space exploration. This review undertakes an exhaustive survey of climbing robot technologies by emphasizing the locomotion mechanisms and adhesion techniques available as well as their practical applications. The climbing strategies such as wheeled, tracked, legged, and hybrid systems are considered together with adhesion methods of magnetic, vacuum suction, dry adhesion, electro adhesion, and mechanical gripping. It gives the comparative advantages and limitations of each method in different environments. The present challenges in control, energy efficiency, and surface compatibility are discussed. Further advances in the integration of soft robotics, and adaptive designs are highlighted. This review tries to point out where future research should go by indicating opportunities for improving the performance and generality of climbing robots.
Copyright (c) 2025 Sushil Kumar Sahoo, Bibhuti Bhusan Choudhury, Prasant Ranjan Dhal, Ipsita Dhar, Supriya Sahu (Author) https://creativecommons.org/licenses/by/4.0
An Introductory Review of Carbon Nanotube-Based Sensors: Mechanisms, Fabrication, and Applications
Carbon nanotubes (CNTs) have attracted significant attention in sensor technologies due to their exceptional electrical conductivity, mechanical flexibility, and high surface reactivity. This review provides an in-depth overview of CNT-based sensors, covering their working principles, fabrication techniques, and major application areas. We begin by exploring the fundamental mechanisms underlying CNT sensing behavior—such as piezoresistivity, tunneling effects, and percolation conduction—followed by a discussion of common fabrication methods, including solution processing, printing, and composite integration. Key applications are highlighted, including wearable strain sensors for human motion detection, gas sensors for environmental monitoring, and self-sensing materials for structural health diagnostics. While CNT-based sensors offer clear advantages in sensitivity and form factor versatility, challenges such as material uniformity, signal stability, and long-term durability remain. We conclude by discussing future directions and strategies to overcome these limitations, aiming to guide the development of robust, scalable CNT-enabled sensing systems. This review serves as a timely resource for researchers and engineers seeking to understand and advance CNT-based sensor technologies.
Copyright (c) 2025 Suyong Choi, Byungil Hwang (Author) https://creativecommons.org/licenses/by/4.0
Selection of Ice Crossing Point location using hybrid MCDM model Fuzzy AHP-EWAA-Fuzzy CoCoSo
This paper investigates the selection of locations for tank crossings over frozen water obstacles using a hybrid Fuzzy Analytic Hierarchy Process (AHP)–Einstein Weighted Arithmetic Average (EWAA)–Fuzzy Combined Compromise Solution (CoCoSo) model. The analysis includes key criteria relevant to the selection process. The Fuzzy AHP method enables precise determination of criterion weights based on expert opinions, aggregated using the EWAA operator, while Fuzzy CoCoSo provides a comprehensive analysis of alternatives to identify the optimal location. The results show that the combination of these methods offers a reliable framework for decision-making under complex conditions. Sensitivity analysis confirms the stability of the results, and comparative analysis supports the validity of the Fuzzy CoCoSo method. The model proves to be efficient and reliable for selecting locations for tank crossings over frozen water surfaces, providing a foundation for future research and practical application.
Copyright (c) 2025 Duško Tešić, Božanić Darko, Aleksandar Milić, Adis Puška (Author) https://creativecommons.org/licenses/by/4.0
A Fermatean Fuzzy Decision-Making Model for Manufacturing Outsourcing Vendor Selection: An Improved Combined Compromise Solution Method
Selecting the most suitable manufacturing outsource vendors (MOVs) is crucial, as these decisions significantly influence organizational performance, environmental sustainability, and resilience to disruptions. However, the evaluation process often involves subjective judgments, which can introduce uncertainty and inconsistency. To address this problem, this study adopts the improved Combined Compromise Solution (CoCoSo) method, enhanced with Fermatean fuzzy logic, as a consensus-driven decision-making framework. To further improve accuracy, Fermatean fuzzy Generalized Dombi weighted aggregation operators are employed. Criteria weights are determined using dispersion measures and cross-entropy techniques. The application of the proposed method is demonstrated through a case study involving a precision gearbox manufacturing company. Among the evaluated criteria, carbon emission reduction, waste recycling rate, and on-time delivery rate are identified as the most critical, with respective weights of 0.3160, 0.1254, and 0.1254. Of the four candidate MOVs (A1, A2, A3, and A4), vendor A4 is ranked highest with a utility score of 1.96145. A comparative analysis confirms the superior performance of the proposed approach compared to alternative decision-making models.
Copyright (c) 2025 Abhijit Saha, PRASENJIT CHATTERJEE (Author) https://creativecommons.org/licenses/by/4.0
Optimizing Robotic Manufacturing in Industry 4.0: A Hybrid Fuzzy Neural Bayesian Belief Networks
In the era of Industry 4.0, robotic manufacturing systems must adapt to dynamic and uncertain environments, where optimal decision-making is crucial for operational efficiency. This paper presents a novel hybrid decision-making framework that integrates Fuzzy Neural Reinforcement Learning (RL), the Best-Worst Method (BWM), Levenshtein Distance, and Bayesian Belief Networks (BBN) to optimize robotic manufacturing processes. By combining these methodologies, the framework effectively handles uncertainty, enhances decision-making, and accelerates learning in complex manufacturing scenarios. A comprehensive system formulation is provided, along with the development of an optimization algorithm that integrates these components. Numerical simulations demonstrate the framework’s performance, highlighting its efficacy in reducing operational costs, improving production quality, and strengthening adaptive capabilities. The results show that the proposed model outperforms traditional approaches across diverse manufacturing scenarios.
Copyright (c) 2025 Hamed Fazlollahtabar (Author) https://creativecommons.org/licenses/by/4.0
Comparative Investigation of Normalization Techniques and Their Influence on MCDM Ranking – A Case Study
Urban traffic significantly contributes to air pollution, and its effects are expected to increase in the coming years. Environmental policy measures can help achieve long-term goals, in which new modes of mobility for residents can play a significant role. However, local-level decision-making is also crucial. In the face of economic volatility, cities must carefully decide on sustainable transportation expenditures that respect budget limitations and promote local air quality standards. To create a sustainable traffic strategy and address the rise in traffic demands due to increased passenger transport, the use of buses with alternative drive technologies and fuel options is becoming increasingly important in European cities. However, buses utilizing alternative drive technologies and fuel options have varying impacts on air pollution, and the required investments and expenses vary. To determine the appropriate propulsion technology and fuel for buses specifically in Nis, the analysis based on multiple criteria will be conducted using the CRITIC (Criteria Importance Through Intercriteria Correlation) and in the following TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) methods according to the defined criteria. The CRITIC method utilizes different normalization types to compute weighting coefficients and analyze their effect on the alternative rankings. Additionally, Spearman's rank correlation coefficient will be used to examine the degree of correlation between the rankings of different alternative drive technologies and fuel options for buses, calculated through the TOPSIS method.
Copyright (c) 2025 Nikola Petrović, Vesna Jovanović, Marijana Petrović, Boban Nikolić, Jelena Mihajlović (Author) https://creativecommons.org/licenses/by/4.0
Utilizing Artificial Neural Networks to Correlate Energy Consumption and Intensity in Metal Industries for the Midwest States
Energy optimization and analysis are significant in mapping energy consumption and savings for various industries. This study sheds light on utilizing two main energy evaluation parameters: Energy Intensity Utilization (EIU) and Specific energy consumption (SEC). This research paper is founded on an extensive 10-year study, from 2013 to 2023, on more than 196 on-site energy assessments performed on various manufacturing companies in Wisconsin and Northern Illinois. This research is considered a comparative study, which aims to explore the correlation between those two parameters using linear regression analysis using SPSS (Statistical Package for Social Sciences) and validate the outcomes using Artificial Neural Networks (ANN). Besides, it is also employed to assess the most updated methods, procedures, and technological applications that are meant to increase energy efficiency. This study demonstrates the relationship between energy consumption, energy savings, and the effects of energy assessment across several industrial sectors. The results have shown a linear correlation between the EIU and SEC as two of the most significant parameters in measuring energy footprint in the energy-auditing sector. Also, the results have shown that the Annual Energy Savings Percentage (AES%) could have interdependence with both the SEC and EIU energy evaluation parameters, which could provide an energy footprint baseline for any stakeholder interested in penetrating the fabricated metal products industry. The ANN results have shown that underfitting occurs when the data model cannot accurately capture the relationship between the input and output variables. The reasons for the underfitting are that the data points are small (95 data points) for a neural network, and the complexity of the model is simplistic for a machine learning application.
Copyright (c) 2025 Mohamed I. Youssef, Kada Kada, Yazeed Abushanab, Qais Alnawafah, Ryoichi S. Amano, Asma Khasawneh (Author) https://creativecommons.org/licenses/by/4.0
Personalized Regenerative Rehabilitation of Osteoarthritis Based on Mechanical Loading and Mechanoregulation
Osteoarthritis is one of the most important “civilizational diseases" that significantly restricts quality of life and active life expectancy. The current practice of treating patients with osteoarthritis often consists in replacing damaged natural joints with artificial ones. Even if the replacement procedure is successful, various complications may occur in the post operation period causing health problems in the long term. The purpose of the current research is to develop methods of regenerative rehabilitation of joints on the basis of personalized treatment technologies of osteoarthritis. This goal can be achieved through the development of programmed mechanical loading of joints taking into account modern knowledge about mechanoregulation of cells, as well as applications of tissue-engineered structures using induced pluripotent stem cells. Local regeneration processes can be supported by targeted delivery of microcapsules of multicomponent lubricants, as well as drugs.
Copyright (c) 2025 Valentin L. Popov (Author) https://creativecommons.org/licenses/by/4.0
A Decision-Making Approach to Establish a Sustainable-Circular Waste Management System: A Case Study of Istinye University
This study presents a decision-making approach for establishing a sustainable-circular waste management system at Istinye University. The approach integrates sustainability principles and circular economy concepts to minimize waste generation, promote recycling, and enhance resource efficiency. A comprehensive analysis of waste management practices at Istinye University was conducted, identifying key areas for improvement. The proposed system utilizes the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to evaluate and prioritize waste management strategies. These methods enable a structured and quantitative assessment of environmental, economic, social, and technical sustainability criteria. The findings highlight the benefits of adopting a circular waste management system, including reduced environmental impact, cost savings, and increased stakeholder engagement. This research contributes to the growing field of sustainable logistics and supply chain management by providing a practical framework applicable to educational institutions and similar organizations.
Copyright (c) 2025 Alper Bora Koçak, Erfan Babaee Tirkolaee (Author) https://creativecommons.org/licenses/by/4.0
Numerical Study of Residual Stress Effects on Deformation and Fracture in Metal Matrix Composites
Composite materials used in various industries possess pronounced microstructural heterogeneity characterised by the difference in thermomechanical properties of the constituents and the presence of interfaces of different scales and geometries. In this study, the deformation and fracture of an aluminium alloy with a metal matrix composite coating under thermomechanical loading are numerically investigated at the micro-, meso- and macroscales. Complex microstructure of the composite material corresponding to the experimentally observed one is taken into account explicitly in the calculations. The constitutive equations for an isotropic elastic-plastic Al6061T6 matrix and elastic-brittle boron carbide particles are integrated into the ABAQUS/Explicit software package via user-defined subroutines. An energy-based fracture criterion formulated in terms of equivalent stresses is used to take into account the fracture of ceramic particles in local regions of tension or compression. The influence of residual stresses on the composite macroscopic strength, plastic strain localisation in the aluminum matrix and crack initiation and propagation in the particles is investigated under uniaxial tension or compression of the composite, with the volume fraction of particles in the coating being varied.
Microstructure-based numerical simulation
Copyright (c) 2025 Ruslan Balokhonov, Aleksandr Zemlianov, Diana Gatiyatullina, Varvara Romanova (Author) https://creativecommons.org/licenses/by/4.0
Frequency-Amplitude Relationship in Nonlinear Oscillators with Irrational Nonlinearities
This study investigates the frequency-amplitude relationship in nonlinear oscillators with irrational nonlinearities, which pose significant challenges to traditional analytical methods such as the homotopy perturbation method and variational iteration method. By employing a simplified frequency formulation, we analyze the impact of irrational nonlinearities on oscillation dynamics and derive a frequency-amplitude relationship in a single-step calculation. For small amplitudes, our results are consistent with those obtained by the homotopy perturbation method, validating the proposed approach. This research provides new insights into the complex dynamics of nonlinear oscillators and offers practical implications for fields such as physics, engineering, and applied mathematics. Additionally, it contributes to the design and optimization of MEMS systems and suggests future research directions, including the incorporation of damping and external forces for a more comprehensive understanding of system behavior.
Copyright (c) 2025 Ji-Huan He (Author) https://creativecommons.org/licenses/by/4.0
A Smart Decision Framework for Sustainable Management of C&D Waste Using Picture Fuzzy Decision Model
Urbanization and rapid population growth have significantly accelerated the development of urban infrastructure, resulting in an unprecedented surge in construction and demolition (C&D) waste. The unregulated accumulation of this waste poses severe environmental and societal challenges, including greenhouse gas emissions, groundwater contamination, and land degradation. This issue is particularly critical in developing countries, where waste generation is directly linked to population density and industrialization. Given the limited availability of landfill space and the adverse environmental impacts of conventional dumping, the implementation of efficient and sustainable waste management strategies has become imperative. Although several waste treatment and recycling methods exist, selecting the most suitable alternative remains a complex multi-criteria decision-making (MCDM) problem due to the interplay of technical, environmental, and economic factors. This study proposes a systematic decision-making framework under a picture fuzzy MCDM environment to evaluate and rank sustainable C&D waste management solutions. A subjective weighting technique is utilized to determine the relative importance of each criterion, while a compromise ranking method is applied to identify the most promising alternative. The findings reveal that carbonation emerges as the optimal solution due to its potential for maximum waste reduction and enhanced sustainability. The proposed framework provides valuable insights for industry professionals and policymakers, facilitating effective C&D waste management practices and contributing to broader global sustainability objectives.
Weighted aggregated sum product assessment
Copyright (c) 2025 Samayan Narayanamoorthy, Michael Sandra, Naif Almakayeel (Author) https://creativecommons.org/licenses/by/4.0
A Novel BWM-RADAR Approach for Multi-Attribute Selection of Equipment in the Automotive Industry
This study examines the application of Multi-Attribute Decision Making (MADM) techniques for selecting an optimal technical solution in the automotive industry, specifically addressing the automatic adjustment and control device of a parking brake cable. The research begins by using the Best-Worst Method (BWM) to determine the weights of criteria, such as device speed, price, weight, and calibration period, based on expert input from maintenance professionals and operators at an automotive original equipment manufacturer in automotive industry. The main objective is to identify the solution that best balances operational efficiency with long-term stability and adaptability to production requirements. In the subsequent phase, both the RADAR method and its modified version, RADAR II, are applied to rank the alternatives. The original RADAR method, which employs ratio-based normalization, tends to favor alternatives that demonstrate stable performance across all criteria, whereas RADAR II, utilizing difference-based normalization, accentuates alternatives that excel in particular aspects. Comparative analysis reveals that although both methods produce generally consistent overall rankings, nuances in the normalization process can lead to differences in the relative prominence of certain solutions. Sensitivity analysis further confirms the robustness and reliability of these approaches, underscoring the importance of selecting a method that aligns with the specific decision-making context. Ultimately, the study demonstrates that a carefully tailored MADM approach, integrating both RADAR and RADAR II techniques, provides valuable insights and supports effective decision-making in complex industrial environments.
Copyright (c) 2025 Nikola Komatina (Author) https://creativecommons.org/licenses/by/4.0
Nonclassical and Nonlinear Stability Analysis of Viscous Fluidic Piezoelectric Biomedical Nanosensor
In this paper, nonlinear vibration and stability analysis of viscous fluidic piezoelectric biomedical nanosensor (VFBNS‎) based on cylindrical nanoshell is investigated using the electro-elastic Gurtin–Murdoch surface/interface (S/I) theory. This piezoelectric nanoresonator is simultaneously subjected to visco-pasternak medium, electrostatic and harmonic excitations. The Hamilton’s principle, the assumed mode method combined with Euler – Lagrange and also Complex averaging method combined with arc-length method are used to achieve the governing equations, boundary conditions and also the effect of different material, structural and excitations parameters on dimensionless natural frequency (DNF) (undamped and damped , critical fluid velocity, nonlinear vibration and stability analysis of piezoelectric biomedical nanosensor. It is shown that the fluid velocity has major unpredictable effects on parametric studies of the system and one should precisely consider their effects. Also, it is concluded that ignoring the surface /interface effects leads to inaccurate results in vibrational response of the VFBNS‎. By changing the surface/interface parameters, the system stiffness is changed leading to nonlinear behavior of the system, which can be more or less pronounced compared to the case without the S/I effects accounted for. The obtained results of this study are useful for designing of nano/micro electro mechanical system and other nano-/micro-smart structures.
Copyright (c) 2025 Sayyid Habibollah Hashemi Kachapi, Sayyideh Gh. Hashemi Kachabi (Author) https://creativecommons.org/licenses/by/4.0
The Effect of a Fully Asymmetric Discontinuity in the Elastic Layer of a Geometrically Nonlinear Double-Beam Coupled Mechanical System
This paper presents the effect of an antisymmetric discontinuity in a Winkler nonlinear elastic layer and compares it with the case of a double Timoshenko beam system without discontinuities. The effects of geometric nonlinearity are considered, and the obtained results represent a time-domain analysis. A modified p-version finite element method is applied to analyse the vibrations of mechanical systems with discontinuities. The main contribution of this work is a comparative analysis of a double beam system without discontinuities and a double beam system with an antisymmetric discontinuity in the Winkler elastic layer. The study demonstrates significant deviations in the beam response under a concentrated periodic external force when an antisymmetric discontinuity is present. Its qualitative and quantitative characteristics are illustrated through time histories, showing amplitude variations in the steady-state oscillation regime. Forced vibrations in the time domain are analysed using the Newmark direct integration method. The cases of deviations in the antisymmetric model are explained, highlighting their potential applications in technical practice as well as in the field of deformable bodies and structures.
Copyright (c) 2025 Dunja Milić, Jian Deng, Deli Li, Vladimir Stojanović (Author) https://creativecommons.org/licenses/by/4.0
Investigation of the Settlement Behavior of Ballasted Railway Tracks Due to Dynamic Loading
This study investigates the settlement behavior of ballasted railway tracks under dynamic loading, providing a comprehensive evaluation of track deterioration models using extensive field data. Leveraging regression analysis, the research examines logarithmic and exponential settlement trends based on operational conditions and highlights key influences, such as ballast compactness and maintenance interventions. Validated against historical ORE (Research and Testing Office) studies, the results suggest refinements in constants to better predict contemporary track behavior. The integration of advanced computational and experimental techniques is proposed to improve model accuracy, ensuring effective maintenance planning and enhanced track durability.
Copyright (c) 2025 Szabolcs Fischer (Author) https://creativecommons.org/licenses/by/4.0
Evaluating and Prioritizing Blockchain Networks using Intuitionistic Fuzzy Multi-Criteria Decision-Making Method
Being a generalization of fuzzy set, intuitionistic fuzzy set (IFS) obtains a better representation of fuzziness and uncertainty. Inspired by this concept, this paper first proposes a logarithmic distance measure to calculate the degree of difference between IFSs. Moreover, this work develops a hybrid ranking model by combining the distance measure, rank-sum model, Stepwise Weight Assessment Ratio Analysis (SWARA) weighting tool, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods under the context of intuitionistic fuzzy environment. In the proposed method, the rank-sum model is used to compute the decision makers’ weights, while the SWARA model is applied to evaluate the criteria weights. To show the practicality of developed model, it is executed to a case study of determining the rank of blockchain networks in the healthcare management system. Comparative study is presented to confirm the advantages of proposed approach over the existing methods.
Copyright (c) 2025 Arunodaya Raj Mishra, Pratibha Rani (Author) https://creativecommons.org/licenses/by/4.0
Numerical Investigation of Large Vehicle Aerodynamics Under the Influence of Crosswind
This paper presents a numerical analysis aimed at estimating the impact of crosswinds on the aerodynamics of large vehicles using ANSYS Fluid Flow and Static Structural, offering insights into the qualitative behaviour of trucks under typical traffic conditions. The cases analysed focus on airflow distribution when a truck, traveling at approximately 100 km/h, passes under a portal while exposed to varying crosswind intensities: weak, moderate, and strong lateral winds. A detailed examination of the truck and portal reveals significant interactions between the induced airflow patterns, affecting truck handling and stability. This is evidenced by shifts in velocity and pressure distributions, changes in drag coefficients, and variations in turbulent kinetic energy, all of which are analysed and discussed in this study.
Copyright (c) 2025 Daniela Alic, Aleksandar Miltenovic, Milan Banic, Raul Vicente Zafra (Author) https://creativecommons.org/licenses/by/4.0
Disintegration of Bone Cement Using Pulsating Water Jet: A Comparative Study of Standard and Extended Nozzles
The paper deals with erosion of bone cement using a pulsating water jet at a pressure of 15 MPa, comparing the effectiveness of standard and extended nozzle with the length of 100 mm and diameter d = 0,3 mm. The research addresses the problem of optimizing bone cement removal techniques, which is critical for various medical applications, including revision surgeries and bone cement removal. The study employs an design of experiments where bone cement samples are subjected to erosion using a pulsating water jet system equipped with both standard and specially designed extended nozzles. Key parameters such as maximal depth, groove width and volume rate were measured and analyzed. Findings indicate that the extended nozzle significantly enhances the erosion process, achieving higher material removal rates and smoother surface finishes compared to the standard nozzle. The results demonstrate the potential of the extended nozzle design in improving the efficiency and precision of bone cement removal, offering valuable insights for medical practitioners and researchers in the field of orthopedic surgery.
Copyright (c) 2025 Akash Nag, Sergej Hloch (Author) https://creativecommons.org/licenses/by/4.0
Comparative Sensitivity Analysis in Composite Material Selection: Evaluating OAT and COMSAM Methods in Multi-criteria Decision-making
The decision-making process is critical across various fields, influencing essential aspects like performance, safety, and sustainability. In engineering and materials science, selecting suitable materials is a complex process involving multiple interdependent criteria, which impact the reliability and lifecycle of a design. Traditional sensitivity analysis methods, such as the one-at-a-time (OAT) approach, assess the effects of individual parameter changes but often fail to capture the cumulative impact of simultaneous modifications. It can limit the effectiveness of decision tools in real-world scenarios where multiple factors vary concurrently. This study utilizes the Comprehensive Sensitivity Analysis Method (COMSAM) to address limitations in traditional sensitivity analysis by modeling simultaneous parameter adjustments across multiple criteria. Specifically, the study aims to validate COMSAM’s effectiveness in the practical problem of composite material selection, comparing it with the traditional OAT approach within a multi-criteria decision-making (MCDM) framework. By integrating both sensitivity analysis techniques with the Characteristic Objects Method (COMET), this research ensures robust evaluation and mitigates vulnerabilities like the rank reversal paradox. The findings demonstrate that COMSAM provides enhanced insights into the impact of parameter interdependencies, offering a more resilient foundation for decision-making in high-stakes environments where material properties and performance are paramount.
Copyright (c) 2025 Jakub Więckowski, Wojciech Sałabun (Author) https://creativecommons.org/licenses/by/4.0
State-of-the-art Review of Springback Behavior of Polymers
The spring-in and spring-back behavior of polymers is intricate and influenced by various process parameters and mechanisms, including interply slip, anisotropic thermal expansion, and crystallization, all of which can lead to residual stresses. Composite materials made of metal and polymer are being investigated by researchers as a promising alternative to monometallic materials due to their superior properties. However, the number of studies related to metal/polymer/metal laminates on the same topics is relatively limited. A comprehensive review study was carried out with a focus on research works that were conducted with the consideration of different process parameters, such as radius of die and punch, friction, and force applied by blank holder, in order to observe their impact on the springback behavior of polymers. Springback on polymer components depends on the accuracy of appropriate materials and the consideration of appropriate experimental strategies. However, due to their viscoelastic properties, polymers demonstrate distinctive springback behavior. Furthermore, when subjected to deformation, polymers experience a combination of elastic and viscous responses, resulting in immediate elastic recovery and time-dependent viscoelastic relaxation. This intricate behavior presents difficulties in precisely forecasting and managing springback. To enhance the control and optimization of springback in polymer-based manufacturing processes, it is essential to improve the understanding of polymer behavior under diverse loading conditions and to refine simulation techniques accordingly. This review focuses on springback prediction models specific to polymers.
Copyright (c) 2024 Emmanuel Chukwueloka Onyibo, Mohammed Asmael (Author) https://creativecommons.org/licenses/by/4.0
Traditional and Integrated MCDM Approaches for Assessment and Ranking of Laser Cutting Conditions
Multiple benefits and advantages that offer laser cutting technology are difficult to achieve if the laser cutting parameter conditions are not adequately set. Determining laser cutting conditions is not trivial task considering large number of controllable inputs, existence of multiple process performances which are often mutually opposed as well as effects of noise factors. Different scientific methods and engineering approaches represent more sophisticated approaches which aid assessment and determination of the most favourable (optimized) cutting conditions. This study is focused assessment and ranking of laser cutting conditions in CO2 laser cutting of AISI 316L stainless steel. Based on kerf width and surface roughness experimental data and estimation of material removal rate (MRR) and total variable costs, four criteria in the multi-criteria decision making (MCDM) model were considered. For solving the developed model, six well-known MCDM methods were applied, and in addition, in order to overcome ranking inconsistency, robust decision-making rule was developed upon which final ranking was obtained.
Copyright (c) 2024 Miloš Madić, Goran Petrović, Dušan Petković, Predrag Janković (Author) https://creativecommons.org/licenses/by/4.0
T-Bipolar Soft Semigroups and Related Results
The role of semigroups (SGs) is to operate as the tool for the study and modeling of systems and phenomena in which inverse operation is not relevant or necessary. SGs are encountered in the subject of automata theory, coding theory, language theory, and the study of discrete dynamical systems. Moreover, T-bipolar soft set is closer to bipolarity as compared to other theories on bipolar soft sets. Based on the idea of T-bipolar soft sets, here we explore the notion and properties of the T-bipolar soft semigroup (T-BSSG). These properties include the AND and OR product, the Restricted Union (Res-Union) and Restricted Intersection (Res-Intersection), and the Extended Union (Ext-Union) and Extended Intersection (Ext-Intersection) on T-BSSG. Further, we also devise the related algebraic properties of T-BSSG.
Copyright (c) 2024 Tahir Mahmood, Muhammad Asif, Ubaid ur Rehman, Jabbar Ahmmad (Author) https://creativecommons.org/licenses/by/4.0
The ever-increasing demands for vehicle emission control have resulted in an expansion of planetary gearbox applications in road vehicles, due to their possibility to change the transmission ratio under load in synchronism with engine operation. Modern boxes are designed to extract the maximum number of transmission ratios as possible from the least possible number of simple component planetary gear trains (PGTs). The application demands dictate whether the box will be built with the maximum number of transmission ratios, or built for ruggedness and reliability. Component interconnections are designed to avoid power circulation, hollow shafts, or complex planet carrier arrangements when possible. The subject of this paper are multi-speed complex planetary gearboxes having at least two interconnected simple component PGTs controlled by brakes and clutches. Several variants of complex PGTs are examined together with the placement of brakes and clutches on their external shafts, and their transmission ratio functions are derived. The kinematics of multi speed gear trains are analysed as combinations of two or more two-speed gear trains. Several gearbox layouts are analysed, and their transmission ratio functions provided. Finally, an overview of the procedure for the calculation of creation of multi-speed gear trains is provided.
Copyright (c) 2024 Željko Vrcan, Sanjin Troha, Kristina Marković, Dragan Marinković (Author) https://creativecommons.org/licenses/by/4.0
SITW Method: A New Approach to Re-identifying Multi-criteria Weights in Complex Decision Analysis
Multi-Criteria Decision Analysis (MCDA) addresses complex decision-making problems across various fields such as logistics, management, medicine, and sustainability. MCDA tools provide a structured approach to evaluating decisions with multiple conflicting criteria, assisting decision-makers in navigating intricate scenarios. Engaging experts is crucial for identifying multi-criteria models due to the diverse aspects of decision-making problems. Techniques such as pairwise comparisons and criterion weight assignment are commonly used to incorporate expert knowledge into decision models. Criterion weight assignment allows experts to indicate the importance of each criterion; however, issues can arise if model parameters are lost or experts become unavailable. To mitigate these issues, techniques like entropy or standard deviation can determine weights without direct expert input. In this context, the Stochastic Identification of Weights (SITW) method utilizes existing assessment samples to re-identify models and obtain weights that replicate the rankings of a reference model. This study compares information-based methods (Entropy, STD) with the SITW method in re-identifying the TRI medical function as a benchmark. The effectiveness of these methods is evaluated using Spearman's weighted correlation coefficient across various scenarios and alternative numbers. Results indicate that the SITW method provides more significant results than other methods in identifying multi-criteria weights by leveraging previously evaluated alternatives. Future research could explore broader approaches and uncertainty scenarios to ensure comprehensive decision support in complex contexts.
Copyright (c) 2024 Bartłomiej Kizielewicz, Wojciech Sałabun (Author) https://creativecommons.org/licenses/by/4.0
A Bibliometric Analysis of Material Selection Using MCDM Methods: Trends and Insights
The selection of appropriate materials is a critical decision-making process in engineering, impacting both performance and sustainability. Multi-Criteria Decision-Making (MCDM) methods have become increasingly popular for navigating the complex trade-offs involved in material selection. This study presents a comprehensive bibliometric analysis of research on material selection using MCDM methods, covering publications from 2010 to 2024. Using tools like VOSviewer 1.6.20, this analysis identifies key trends, influential authors, prominent institutions, and geographic distribution of research contributions. The findings reveal a significant growth in publications, particularly after 2010, reflecting the expanding recognition of MCDM’s importance in material selection processes. Notable contributors, including key researchers and leading institutions, have shaped the field through high-impact studies. The geographic analysis highlights a strong concentration of research in regions such as Asia and Europe, underscoring their leadership in advancing MCDM methodologies. This paper provides valuable insights into the evolution of material selection research using MCDM, offering a foundation for future studies and applications in engineering and beyond.
Copyright (c) 2024 Sushil Kumar Sahoo, Bibhuti Bhusan Choudhury, Prasant Ranjan Dhal (Author) https://creativecommons.org/licenses/by/4.0
Optimum production lot size for a perishable product under exponential demand with partial backordering and rework
The management of inventory significantly impacts an organization's profitability. Numerous researchers have developed the production model tailored for decaying items to boost sales and minimize inventory, thereby increasing turnover ratios. This study focuses on the EPQ model for reworkable items under exponential combined with inventory dynamics. The primary objective is to optimize the production plan to manage maintenance costs effectively, ensuring optimal Leveraging human and technological resources. The research determines the optimal cycle length, backordered quantities, and production quantities to minimize overall costs. Specifically, penalties are incurred for excessive production times during rework and non-rework phases. This model finds applications in industries such as printed circuit board assembly in semiconductor manufacturing, metal parts, and plastic molding. The study concludes with numerical examples comparing total costs under the proposed model, supplemented by sensitivity analyses that explore the impacts of parameter variations on decision-making.
Copyright (c) 2024 Nagarajan Deivanayagampillai, V. Kuppulakshmi, C. Sugapriya (Author) https://creativecommons.org/licenses/by/4.0