Search Results (88)

This review provides a comprehensive overview of the evolution and application of artificial intelligence (AI) and large language models (LLMs) in engineering, with a specific focus on chemical engineering. The review traces the historical development of LLMs, from early rule-based systems and statistical models like N-grams to the transformative introduction of neural networks and transformer architecture. It examines the pivotal role of models like BERT and the GPT series in advancing natural language processing and enabling sophisticated applications across various engineering disciplines. For example, GPT-3 (175B parameters) demonstrates up to 87.7% accuracy in structured information extraction, while GPT-4 introduces multimodal reasoning with estimated token limits exceeding 32k. The review synthesizes recent research on the use of LLMs in software, mechanical, civil, and electrical engineering, highlighting their impact on automation, design, and decision-making. A significant portion is dedicated to the burgeoning applications of LLMs in chemical engineering, including their use as educational tools, process simulation and modelling, reaction optimization, and molecular design. The review delves into specific case studies on distillation column and reactor design, showcasing how LLMs can assist in generating initial parameters and optimizing processes while also underscoring the necessity of validating their outputs against traditional methods. Finally, the review addresses the challenges and future considerations of integrating LLMs into engineering workflows, emphasizing the need for domain-specific adaptations, ethical guidelines, and robust validation frameworks. Full article

Wire Arc Additive Manufacturing holds promise for on-board metal part production in maritime settings, yet its implementation remains limited due to the vibrational instability inherent to shipborne environments. This study addresses this critical technological barrier by analyzing the effects of marine vibrations on process stability and proposing an integrated solution based on adaptive process control, gyrostabilized platforms, and real-time monitoring systems. The research establishes specific technical requirements for WAAM instrumentation under maritime conditions and evaluates the capabilities and limitations of existing hardware and software tools. A set of engineering recommendations is presented for improving digital modeling, thermal–mechanical monitoring, and feedback control systems. Additionally, the study highlights material-related challenges by examining the influence of alloy properties on print quality under dynamic loads. The proposed approach enhances WAAM process resilience, laying the groundwork for reliable, high-quality additive manufacturing at sea. These findings are particularly relevant to shipboard maintenance, repair, and remote fabrication tasks, marking a significant step toward the industrial adoption of WAAM in marine engineering. Full article

This paper describes creating a new course for engineering technology students at Southeast Missouri State University that focuses on application-based mathematics instruction through laboratory experiments. The course structure comprises beginning the semester with pre-calculus and trigonometry and progressing to calculus and differential equations. The topics are covered from the engineering and engineering technology applications standpoint, with examples from electrical and mechanical systems. A hands-on, problem-based learning approach is selected for teaching the application of mathematics to engineering technology students. This entails students being presented with real-world problems, solving them using mathematical concepts, and then verifying results by using software tools. Specifically, twelve laboratory exercises using Scilab have been incorporated into the course. For engineering students, using engineering examples improves both their ability to understand the material’s relevance and their understanding of mathematical techniques that may be applied to real-world problems that they will likely encounter in their future jobs. Full article

This article describes the use of 3D printing as a tool for the design of a dosing device for intramuscular injections by nursing professionals. A device that is safer against accidental punctures, easy to use, and functional. After the analysis of the problem by a multidisciplinary team, which included nurses and engineers, a first basic prototype has been built for testing. In the process, software for solid modeling has been used; functional prototypes have been developed from the virtual models by rapid prototyping using fused deposition modeling technology (FDM), in Polylactic Acid (PLA) material, and have been tested to verify their mechanical properties and suitability for function. The project has developed a functional design that has been patented, and is in the clinical trials phase. This study demonstrates the efficacy of three-dimensional (3D) printing technologies to expedite the design process and build low-cost functional prototypes. The dosing and needle-protection mechanisms are driven by compression springs; the forces needed for both mechanisms were initially estimated through theoretical calculations and verified through empirical testing. Full article

During the dry machining of 6061 aluminum alloy, cemented carbide tools often suffer from severe wear and built-up edge (BUE) formation, which significantly shortens tool life. Inspired by the non-smooth surface structure of dung beetles, this study proposes an elliptical dimple–groove composite bionic micro-texture, applied to the rake face of cemented carbide tools to enhance their cutting performance. Four types of tools with different surface textures were designed: non-textured (NT), single-groove texture (PT), circular dimple–groove composite texture (AKGC), and elliptical dimple–groove composite texture (TYGC). The cutting performance of these tools was analyzed through three-dimensional finite element simulations using the Deform-3D (version 11.0, Scientific Forming Technologies Corporation, Columbus, OH, USA) software program. The results showed that, compared to the NT tool, the TYGC tool exhibited the best performance, with a reduction in the main cutting force of approximately 30%, decreased tool wear, and significantly improved chip-breaking behavior. Based on the simulation results, a response surface model was constructed to optimize key texture parameters, and the optimal texture configuration was obtained. In addition, a theoretical model was developed to reveal the mechanism by which the micro-texture reduces interfacial friction and temperature rises by shortening the effective contact length. To verify the accuracy of the simulation and theoretical analysis, cutting experiments were further conducted. The experimental results were consistent with the simulation trends, and the TYGC tool demonstrated superior performance in terms of cutting force reduction, smaller adhesion area, and more stable cutting behavior, validating both the simulation model and the proposed texture design. This study provides a theoretical foundation for the structural optimization of bionic micro-textured cutting tools and offers an in-depth exploration of their friction-reducing and wear-resistant mechanisms, showing promising potential for practical engineering applications. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

The use of computer-aided engineering (CAE) tools has become essential in modern design processes, significantly streamlining mechanical design tasks. The integration of optimization algorithms further enhances these processes by facilitating studies on mechanical behavior and accelerating iterative operations. A key focus lies in understanding and mitigating the detrimental effects of cavitation on injector surfaces, as it can reduce the injector lifespan and induce material degradation. By combining advanced numerical finite element tools with algorithmic optimization, these adverse effects can be effectively mitigated. The incorporation of computational tools enables efficient numerical analyses and rapid, automated modifications of injector designs, significantly enhancing the ability to explore and refine geometries. The primary goal remains the minimization of cavitation phenomena and the improvement in injector performance, while the collaborative use of specialized software environments ensures a more robust and streamlined design process. Specifically, using the simulated annealing algorithm (SA) helps identify the optimal configuration that minimizes cavitation-induced effects. The proposed approach provides a robust set of tools for engineers and researchers to enhance injector performance and effectively address cavitation-related challenges. The results derived from this integrated framework illustrate the effectiveness of the optimization methodology in facilitating the development of more efficient and reliable injector systems. Full article

Computer-Aided Design (CAD) plays a critical role in modern engineering education by supporting technical accuracy and fostering innovation in design. This study compares the performance of beginner CAD users employing general-purpose AutoCAD 2025 with those using the specialized AutoCAD Mechanical 2025. Fifty undergraduate mechanical engineering students, all with less than one year of CAD experience and no prior exposure to AutoCAD Mechanical, were randomly assigned to complete six mechanical drawing tasks using one of the two software environments. Efficiency was evaluated through command usage, frequency, and task completion time, while creativity was assessed using a rubric covering originality, functionality, tool proficiency, and graphical quality. Results show that AutoCAD Mechanical significantly improved workflow efficiency, reducing task execution time by approximately 50%. Creativity scores were also notably higher among users of AutoCAD Mechanical, particularly in functionality and tool usage. These gains are attributed to automation features such as parametric constraints, standard part libraries, and automated dimensioning, which lower cognitive load and support iterative design. The findings suggest that integrating specialized CAD tools into engineering curricula can enhance both technical and creative outcomes. Limitations and future research directions include longitudinal studies, diverse user populations, and exploration of student feedback and tool adaptation. Full article

Process models constitute essential tools in business process management and software engineering for representing and managing real-world business processes. Hence, the proper comprehension of these models is crucial for enabling an effective and efficient communication among stakeholders. While several studies have examined factors affecting process model comprehension, such as the used modeling notation or process complexity, there is a lack of in-depth research on the cognitive processes important to comprehend process models deeper. This systematic literature review explores the cognitive mechanisms underlying process model comprehension by integrating insights from relevant disciplines such as cognitive neuroscience and psychology. Key areas of cognition include perception, attention, memory, language, problem solving, emotion, and metacognition. This review was conducted following the well-established Kitchenham methodology and included an extensive search in the following digital libraries: Web of Science, IEEE Xplore, ScienceDirect, ACM Digital Library, PubMed, and SpringerLink. By analyzing 47 studies, this literature review identifies gaps in current research, emphasizing the need for further investigation into these cognitive processes to improve model comprehensibility. Full article

This paper aims to propose a hybrid collaborative development model based on multi-dimensional behavioral information (HCDMB) to deal with systemic problems in modern software engineering, such as the low efficiency of cross-stage collaboration, the fragmentation of the intelligent tool chain, and the imperfect human–machine collaboration mechanism. This paper focuses on the stages of requirements analysis, software development, software testing and software operation and maintenance in the process of software development. By integrating the multi-dimensional characteristics of the development behavior track, collaboration interaction record and product application data in the process of project promotion, the mixture of experts (MoE) model is introduced to break through the rigid constraints of the traditional tool chain. Reinforcement learning combined with human feedback is used to optimize the MoE dynamic routing mechanism. At the same time, the few-shot context learning method is used to build different expert models, which further improve the reasoning efficiency and knowledge transfer ability of the system in different scenarios. The HCDMB model proposed in this paper can be viewed as an important breakthrough in the software engineering collaboration paradigm, so as to provide innovative solutions to the many problems faced by dynamic requirements and diverse scenarios based on artificial intelligence technology in the field of software engineering involving different project personnel. Full article

Fiber-reinforced polymer (FRP) composites demonstrate significant advantages in the reinforcement of timber structures, with basalt fiber-reinforced polymer (BFRP) and carbon fiber-reinforced polymer (CFRP) exhibiting distinct characteristics. This study systematically compares the mechanical performance differences between BFRP- and CFRP-reinforced Northeast larch timber columns. Uniaxial compression tests focused on the mechanical responses under different reinforcement conditions along the grain direction. The results indicate that BFRP-reinforced specimens exhibit superior cost-effectiveness, enhanced ductility, and improved damage tolerance, whereas CFRP-reinforced specimens demonstrate higher stiffness and ultimate load-bearing capacity. A damage constitutive model, developed based on Poisson distribution theory, accurately describes the damage evolution process of fully FRP-reinforced Northeast larch timber columns. Numerical simulations show excellent agreement with experimental results. The study provides critical guidance for FRP material selection and reinforcement strategies in timber structure engineering: BFRP is more suitable for general applications prioritizing cost efficiency and ductility, while CFRP is better suited for special structures requiring higher load-bearing capacity. Finite element models of CFRP- and BFRP-reinforced timber specimens under axial compression were established using ABAQUS 2020 software, with simulation results closely matching experimental data. The proposed constitutive model and finite element analysis method offer a reliable tool for predicting the mechanical behavior of FRP-wood composite structures. Full article

In the present paper, an evaluation of the damage behaviour of quasi-brittle composites exposed to mechanical, thermal, and other loads is studied by means of viscoelastic and/or viscoplastic material models, applying some non-local regularisation techniques to the initiation and development of damages. The methods above are presented as a strong tool for a deeper understanding of material structures in miscellaneous engineering disciplines like civil, mechanical, and many others. Nevertheless, all of the software packages reflect certain compromises between the need for effective computational tools, with parameters obtained from inexpensive experiments, within the possibilities and the complexity of both physical and geometrical descriptions of structure deformation within processes. The article is devoted to the mathematical aspects regarding a considerably wide class of computational modelling problems, emphasising the following ones: (i) the existence and the uniqueness of solutions of engineering problems formulated in terms of the deterministic initial and boundary value problems of partial differential equations theory; (ii) the problems of convergence of computational algorithms applied to (i). Both aspects have numerous references to possible generalisations and investigations connected with open problems. Full article

The permeability of a porous material is the measure of the ability of fluids to pass through it. The ability to control permeability is valued by tissue engineers who manufacture tissue engineering scaffolds that house cells/tissue and facilitate tissue growth. Therefore, a scaffold design software in which permeability can be entered as a variable in determining the structure and strut topology would be a desirable tool for tissue engineering researchers. The ability to factor permeability directly into the design of scaffolds facilitates more effective bone tissue engineering by enabling optimal nutrient transport and waste removal at regeneration sites. Additionally, having the ability to control the mechanical environment by indicating a region of acceptable porosities for in vitro cell culturing is desirable. This desirability is a result of porosity being a major determining factor in permeability, where increasing porosity will generally mean a higher permeability. Thus, having an upper bound on porosity means that higher-permeability structures can be determined whilst maintaining high values of mechanical strength. In this software, a method is discussed for modifying the Kozeny–Carman equation by incorporating level-set equations for different triply periodic minimal surface (TPMS) structures. Topology analysis is computed on six different TPMS structures in the toolbox, and a relationship between a topological constant and permeability is derived through the Kozeny–Carman equation. This relationship allows for an input of permeability as a factor in the determination of pore size, porosity, and scaffold structure. This novel method allows for scaffold design based on a tailored permeability to assist successful tissue engineering. Full article

The range of sensor technologies for structural health monitoring (SHM) systems is expanding as the need for ongoing structural monitoring increases. In such a case, damage to the monitored structure elements is detected using an integrated network of sensors operating in real-time or periodically in frequent time stamps. This paper briefly introduces a new type of sensor, called a Customized Crack Propagation Sensor (CCPS), which is an alternative for crack gauges, but with enhanced functional features and customizability. Due to those characteristics, it is necessary to develop a family of computer-aided supporting models for rapid prototyping and analysis of the new designs of sensors of various shapes and configurations, which this paper presents by use of simulation tools. For a prototyping of the sensor lay out, an algorithm is elaborated, based on an application created in LabVIEW 2022 software, which generates two spreadsheets formatted by the requirements of Autodesk Inventor 2014 and COMSOL Multiphysics 5.6 software, based on data entered by the user. As a result, a tailored-in-shape CCPS layout is prepared. A parametric model of the sensor is prepared in Autodesk Inventor software, which automatically changes its geometric dimensions after changing data in an MS Excel spreadsheet. Then, the generated layout is analyzed to obtain electromechanical characteristics for defined CCPS geometry and materials used in the COMSOL Multiphysics software. Another application is devoted to purely mechanical analysis. The graphical user interface (GUI) add-on based on the Abaqus 2018 software engine is prepared for advanced mechanical analysis simulations of sensor materials in selected loading scenarios. The GUI is used for entering material libraries and the selection of loading conditions and a type of specimen, while the results of the numerical analysis are delivered through Abaqus. The main advantage of the developed GUI is the capacity for personnel inexperienced in using the Abaqus environment to perform analysis. Some results of simulation tests carried out in both COMSOL Multiphysics as well as Abaqus software are delivered in this paper, using a predefined parametric sensor model. For example, using a rigid epoxy resin for an insulating layer shows a negligible difference in the level of strain compared to the structure during a simulated tensile test, specifically in the tested layer thickness range of up to 0.3 mm. However, during bending tests, an approx. 17% change in principal strain level can be observed through the top to bottom edge of the epoxy resin layer. The adopted methodology for carrying out simulation studies assumes the parallel use of a set of various computer-aided tools. This approach allows for taking advantage of individual software environments, which allows for expanding the scope of analyses and using the developed models and applications in further research activities. Full article

DynPy is an open-source library implemented in Python (version 3.10.12) programming language which aims to provide a versatile set of functionalities for mechanical and electrical engineers. It enables the user to model, solve, simulate, and report analysis of dynamic systems with the use of a single environment. The DynPy library comes with a predefined collection of ready-to-use mechanical and electrical systems. A proprietary approach to creating new systems by combining independent elements defined as classes, such as masses, springs, dampers, resistors, capacitors, inductors, and more, allows for the quick creation of new, or the modification of existing systems. In the paper examples for obtaining analytical and numerical solutions of the systems described with ordinary differential equations were presented. The assessment of solver accuracy was conducted utilising a coupled electro-mechanical model of a direct current motor, with MATLAB/Simulink (R2022b) used as a reference tool. The model was solved in DynPy with the hybrid analytical–numerical method and fully analytically, while in MATLAB/Simulink strictly numerical simulations were run. The comparison of the results obtained from both tools not only proved the credibility of the developed library but also showed its superiority in specific conditions. Full article