Engineering Design Research Articles

Three-dimensional numerical simulation on failure mechanical characteristics of fissured sandstone specimens under true triaxial conditions

Understanding intermediate principal stress influences on deformation characteristics and failure mechanism of fractured rock from deep engineering often necessitates long term on-site detection and complex experimental research, although very limited efficacy can be obtained. With presently available experimental data on conventional triaxial cuboid noncoplanar fissured sandstones, this study further investigated the effects of differential stress (σ2 − σ3) and rock bridge inclination angle (β30°, β60°, β90°, β120°, and β150°) on their damage evolution processes and failure modes based on 3D discrete element methods (PFC3D). Numerical simulation results indicated that the peak strength of the fissured sandstone under the same state of horizontal principal stress shows an overall increasing pattern with the increase of the inclination angle of the rock bridge, while its peak strain displays a decreasing and then increasing trend. Besides, in this work, five failure modes, nine crack types and two kinds of stress–strain curves are summarized which are significantly affected by the horizontal principal stress, rock bridge inclinations or cooperative interaction. Differential stress value of 15 MPa is an important threshold for determining the residual strength of the stress–strain curve from present to absent. The cracking and force chain evolution processes of five failure modes were analyzed in order to discover the corresponding failure mechanisms. Finally, differential stress and flaw inclination influences on rock mechanical parameters and failure behavior have significant implications for strategies of the design, operation, and maintenance of rock engineering under severe conditions in the underground.

Virtual design on the heat pump refrigeration cycle: challenges and approaches

Virtual product design (VPD) of the refrigeration cycle has long been a major subject of many engineers and manufacturers. Issues should be the question of how simulation gets close to the real world in virtual ways. It is especially true when we consider variable refrigerant flow (VRF) heat pumps, having various types of indoor unit combinations, long and complicated piping configurations, and simultaneous cooling and heating functions under extreme weather conditions. In this regard, model-based systems engineering (MBSE) or model-based design (MBD) guides a methodology to make a virtual model easily. Now, there are plenty of engineering platforms and tools to make a strong simulation model, which provides interfacing technology among multiple physics, different dimensions, and codes in different languages. In the study, the authors share their experience in the virtual design for a VRF heat pump system including the architecture, multiple physics, and the connection with the control SW. Modelica, an acausal and object-oriented modeling language, constructs the backbone of the model to describe the dynamic behavior of refrigerants and to combine external components in the form of functional mock-up units (FMUs). The developed virtual model is validated against measured data, showing it can reproduce all the essential physics of interest both in qualitative and quantitative ways.

Reaction Environment Regulation for Electrocatalytic CO2 Reduction in Acids.

The electrocatalytic CO2 reduction reaction (CO2RR) is a sustainable route for converting CO2 into value-added fuels and feedstocks, advancing a carbon-neutral economy. The electrolyte critically influences CO2 utilization, reaction rate and product selectivity. While typically conducted in neutral/alkaline aqueous electrolytes, the CO2RR faces challenges due to (bi)carbonate formation and its crossover to the anolyte, reducing efficiency and stability. Acidic media offer promise by suppressing these processes, but the low Faradaic efficiency, especially for multicarbon (C2+) products, and poor electrocatalyst stability persist. The effective regulation of the reaction environment at the cathode is essential to favor the CO2RR over the competitive hydrogen evolution reaction (HER) and improve long-term stability. This review examines progress in the acidic CO2RR, focusing on reaction environment regulation strategies such as electrocatalyst design, electrode modification and electrolyte engineering to promote the CO2RR. Insights into the reaction mechanisms via in situ/operando techniques and theoretical calculations are discussed, along with critical challenges and future directions in acidic CO2RR technology, offering guidance for developing practical systems for the carbon-neutral community.

Numerical Analysis of the Ultimate Bearing Capacity of Strip Footing Constructed on Sand-over-Clay Sediment

This paper analyzes the bearing capacity of two-layered soil medium using finite element (FE) software ABAQUS/CAE 2023. Although geotechnical engineers design foundations for layered soil, majorly current geotechnical studies emphasize single homogenous soil. So, this research has significant novelty as it focuses on layered soil and adds to the current literature. A nonlinear FE model was prepared and analyzed to determine the ultimate bearing capacity of two-layered soil (sandy soil over clayey soil). The Drucker–Prager and Mohr–Coulomb models were used to represent sandy soil and clayey soil layers, respectively. Strip footing material properties were considered isotropic and linearly elastic. This study performed parametric studies to understand the effects of thickness, unit weight, and the modulus of the elasticity of sandy soil on the ultimate soil bearing capacity. Additionally, it also analyzed the effect of the cohesive strength of clayey soil on layered soil bearing capacity. Results showed that an increase in sandy soil layer thickness strengthens the layered soil, and thus, improves the bearing capacity of soil. Increasing the sandy soil layer thickness over footing width (h1/B) ratio from 0.15 to 2.0 improved the ultimate bearing capacities with elastic settlements of 350 mm and 250 mm by 145.62% and 101.66%, respectively. Additionally, for a thicker sandy soil layer, an increase in the unit weight and modulus of the elasticity of sandy soil led to higher ultimate bearing capacity. Furthermore, it was concluded that an increase in clayey soil’s cohesive strength from 20 kPa to 30 kPa resulted in a 24.31% and 3.47% increase in soil bearing capacity for h1/B = 0.15 and h1/B = 2.0, respectively. So, the effect of cohesion is prevalent in the case of a thicker clayey soil layer.

Bond strength between recycled aggregate concrete and rebar: Interpretable machine learning modeling approach for performance estimation and engineering design

Recycled aggregate concrete has a large potential for application as a sustainable building material. To assist in guiding the engineering design of this low-carbon material, the complex relationship between its bond strength to the rebar and various design parameters was modeled. Comparative studies of multiple machine learning methods have shown that the extreme random tree model demonstrates outstanding performance with root mean square error of 1.982, mean absolute error of 1.202 and coefficient of determination of 0.954. To determine the role of design parameters in performance prediction, importance analysis and sensitivity analyses for parameters were used to explore the complex relationship in the model. The results indicated that rebar type, water-cement ratio, anchorage length, and compressive strength are crucial factors affecting the bond strength between recycled aggregate concrete and rebar. In addition, to further demonstrate the reliability and accuracy of machine learning models, explicit models in some specifications were used for comparative analysis. Due to variability in influencing factors, limited test data, and variability in material properties, the explicit models have limited accuracy for bond strength between recycled aggregate concrete and rebar. Therefore, the interpretable modeling approach can provide an accurate estimate of the bond strength between recycled concrete aggregates and rebar and guide the engineering design of this structure.

Computational assessment of carbon fabric reinforced polymer made prosthetic knee: Mechanics, finite element simulations and experimental evaluation.

A prosthetic knee is designed to replace the functionality of an anatomical knee in transfemoral amputees. The purpose of a prosthetic knee is to restore mobility and compensate amputees for their impairment. In the present research numerical modelling and simulation of a carbon fabric reinforced polymer made polycentric prosthetic knee with four-bar mechanism was performed. Virtual prototyping with computer-aided design and computer-aided engineering software ensured geometric and structural stability of the knee design. The linkage mechanism, instantaneous centre's location and trajectory were investigated using multibody dynamics and analytical formulations. Computational simulations with a non-linear finite element model were employed with joints, contact formulations and an orthotropic material model to predict the displacement, stress formulated and life of the knee prosthesis under static and cyclic loading conditions. Finite element analysis assessed the strength and durability of knee in accordance to standards. Maximum Principal stress of 155 MPa and life expectancy of 3.1 × 106 cycles were determined for the composite knee through numerical simulations ensuring a safe design. Experimental testing was also conducted as per standards and the percentage error was estimated to be 2.52%, thereby establishing the validity of the finite element model deployed. This type of simulation-based approach can be implemented to efficiently and affordably design and prototype a prosthetic knee with desired functioning criteria.

Fatigue Crack Propagation of 51CrV4 Steels for Leaf Spring Suspensions of Railway Freight Wagons.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible, which can lead to economic and human catastrophes. The aim of this document was to precisely characterise the mechanical crack growth behaviour of the chromium-vanadium alloyed steel representative of leaf springs under cyclic conditions, that is, the crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio were also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

Global perspectives and methodological innovations in STEM education: a systematic mapping analysis of engineering design-based teacher training

PurposeThis study investigates a novel educational strategy in science, technology, engineering and mathematics (STEM) teaching that integrates the engineering design process (EDP) as a framework. The strategy aims to help teachers explain STEM concepts in a simplified way. We employed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to enable a systematic review that evaluated the effectiveness of this approach in improving both teaching and learning in STEM subjects.Design/methodology/approachIn order to fulfill the objectives of the review, key data were extracted from each of the 400 articles that were reviewed from three databases: Scopus, ProQuest Central and EBSCO. Two types of analysis were conducted, namely descriptive analysis and literature classification.FindingsThis systematic review analyzed 44 articles on the EDP, focusing on 18 detailed studies mainly from ProQuest, SCOPUS and EBSCO. It revealed a limited focus on gender’s impact on EDP and a trend toward interdisciplinary use and integrated research approaches. The study underscores the need for further exploration of demographic influences and preparation programs in EDP across various disciplines, aiming to inform future research and educational policies.Originality/valueThe study’s value lies in its comprehensive assessment of engineering design (ED) research over the past decade, serving as a key reference point. It highlights progress in the field, consolidates findings and provides insights into the field’s evolution, guiding future research directions in ED.

Efficient Sizing and Layout Optimization of Truss Benchmark Structures Using ISRES Algorithm

This paper presents a comprehensive investigation into the application of the Improved Stochastic Ranking Evolution Strategy (ISRES) algorithm for the sizing and layout optimization of truss benchmark structures. Truss structures play a crucial role in engineering and architecture, and optimizing their designs can lead to more efficient and cost-effective solutions. The ISRES algorithm, known for its effectiveness in multi-objective optimization, is adapted for the single-objective optimization of truss designs with multiple design constraints. This study encompasses a wide range of truss benchmark structures, including 10-bar, 15-bar, 18-bar, 25-bar, and 72-bar configurations, each subjected to distinct loading conditions and stress constraints. The objective is to minimize the truss weight while ensuring stress and displacement limits are met. Through extensive experimentation, the ISRES algorithm demonstrates its ability to efficiently explore the solution space and converge to optimal solutions for each truss benchmark structure. The algorithm effectively handles the complexity of the problems, which involve numerous design variables, stress constraints, and nodal displacement limits. A comparative analysis is conducted to assess the performance of the ISRES algorithm against other state-of-the-art optimization methods reported in the literature. The comparison evaluates the quality of the solutions and the computational efficiency of each method. Furthermore, the optimized truss designs are subjected to finite element analysis to validate their structural integrity and stability. The verification process confirms that the designs adhere to the imposed constraints, ensuring the safety and reliability of the final truss configurations. The results of this study demonstrate the efficacy of the ISRES algorithm in providing practical and reliable solutions for the sizing and layout optimization of truss benchmark structures. The algorithm’s competitive performance and robustness make it a valuable tool for structural engineers and designers, offering a versatile and powerful approach for complex engineering optimization tasks. Overall, the findings contribute to the advancement of optimization techniques in structural engineering, promoting the development of more efficient and cost-effective truss designs for a wide range of engineering and architectural applications. The study’s insights empower practitioners to make informed decisions in selecting appropriate optimization strategies for complex truss-design scenarios, fostering advancements in structural engineering and sustainable design practices.

Integrating the engineering design process into the conceive-design-implement-operate model for promoting high school students’ STEM competence

Integrating the engineering design process into the conceive-design-implement-operate model for promoting high school students’ STEM competence

Experimental and simulative study on seismic performance of stiffener‐plate PEC beam‐column joint

AbstractAn innovative assembled stiffener‐plate PEC beam‐column joint (SP‐PEC) is proposed to improve better constructability. In this paper, 12 PEC beam‐column joint specimens were subjected to quasi‐static cyclic tests. The design parameters included the thickness of the stiffener‐plate (equal‐stiffness thickness at load standard combination, full‐stiffness thickness of the cross‐section, and 120% of full‐stiffness thickness of the cross‐section) and the beam‐column connection with or without the stub beam. The results revealed that the assembled SP‐PEC beam‐column joint exhibited better seismic performance than the conventional PEC beam‐column concrete joint. The strength degradation coefficients of SP‐PEC beam‐column nodes are all greater than 0.92, and the stiffness decreases slowly. The specimens had good bearing capacity, deformation ability, energy dissipation capacity, and stiffness under a reasonable stiffener‐plate thickness. Then, the bearing capacity calculation formulae of the novel joint with certain prediction accuracy were proposed. Besides, the finite element models of the test specimens were established in ABAQUS and validated against the test results. Finally, further investigations of the SP‐PEC joint configuration by finite element analysis and engineering design recommendations for the assembled SP‐PEC beam‐column joint were provided.

Advances in biotin biosynthesis and biotechnological production in microorganisms.

Biotin, also known as vitamin H or B7, acts as a crucial cofactor in the central metabolism processes of fatty acids, amino acids, and carbohydrates. Biotin has important applications in food additives, biomedicine, and other fields. While the ability to synthesize biotin de novo is confined to microorganisms and plants, humans and animals require substantial daily intake, primarily through dietary sources and intestinal microflora. Currently, chemical synthesis stands as the primary method for commercial biotin production, although microbial biotin production offers an environmentally sustainable alternative with promising prospects. This review presents a comprehensive overview of the pathways involved in de novo biotin synthesis in various species of microbes and insights into its regulatory and transport systems. Furthermore, diverse strategies are discussed to improve the biotin production here, including mutation breeding, rational metabolic engineering design, artificial genetic modification, and process optimization. The review also presents the potential strategies for addressing current challenges for industrial-scale bioproduction of biotin in the future. This review is very helpful for exploring efficient and sustainable strategies for large-scale biotin production.

A Study on the Preference of Electric Vehicle Front Design Elements

In order to invigorate Korea’s pure electric vehicle market, innovative changes are imperative in both technological advancements and exterior design aesthetics. The front fascia, being the nucleus of car design, profoundly influences not only brand perception but also consumer preferences and purchasing decisions. Hence, the significance of front-end design in pure electric vehicle engineering is becoming increasingly evident. This study aims to assess the front-end design of electric vehicles and delineate the design aesthetics favored by consumers. Focusing on the exterior design aspects of electric vehicles, the study participants were limited to adults aged 20 or above. Utilizing Maximum Difference Scaling, a questionnaire was formulated, and preferences for front-end elements (headlamps, bonnet, bumper, grille, and side mirrors) were scrutinized through cross-tabulation analysis. The findings revealed the bonnet as the most preferred element, with a preference towards simplistic designs observed across all elements, including the bumper, grille, and side mirrors. Headlamps ranked as the second most preferred element, with a tendency towards emotionally evocative designs. This study offers insights into consumer preferences regarding the front-end elements of electric vehicles and is poised to contribute to the revitalization of Korea’s pure electric vehicle market by providing pertinent information to future electric vehicle manufacturers.

Microbial chassis design and engineering for production of gamma-aminobutyric acid.

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA.

Prediction of Conveying Resistance for a Novel Hydraulic-mechanical Hybrid Vertical Lifting System

Objective: Recently a novel hydraulic-mechanical hybrid vertical lifting system was proposed for deep-sea mining. Accurate prediction of conveying resistance is important for the engineering design of the system. Plug flow of coarse particles is the main flow regime in the system. So far rare attention has been paid to the pressure drop prediction of plug flow of coarse particles. This paper aims to investigate eight theoretical pressure drop models on the applicability to predict the pressure drop of plug flow. Methods: Eight theoretical pressure drop models were studied. In addition, a hydraulic-mechanical hybrid vertical lifting test setup was developed. The novelty of this experimental work is that plug flow of coarse particles is formed and the lifting force of the plug can be measured with the test setup. Tests were conducted with varying particle sizes, lifting speeds and plug weights. The particle size is varied among 13, 18, and 25mm. The lifting speed is varied from 0.02m/s to 0.1m/s. The plug weight varies from 5 to 10kg. The range of Reynolds number for the tested particles is between 208 and 2,000. Results: Prediction errors of eight pressure drop models are derived and compared with the experimental data collected during this study. It was found that similar prediction trends are observed for all pressure drop models under most test conditions. Except the Rose model, all models produce average prediction errors less than 15%. The average prediction error for the Rose model is 20.59%. The average prediction error for the Ergun model is 12.43%. Conclusion: From this study it can be seen that the Ergun model produces the smallest prediction error among the eight selected pressure drop models for the given experimental conditions. Therefore, the Ergun model is considered to be most applicable for the calculation of the conveying resistance for the proposed vertical lifting system.

Multi-objective Geometric Mean Optimizer (MOGMO): A Novel Metaphor-Free Population-Based Math-Inspired Multi-objective Algorithm

This research introduces a novel multi-objective adaptation of the Geometric Mean Optimizer (GMO), termed the Multi-Objective Geometric Mean Optimizer (MOGMO). MOGMO melds the traditional GMO with an elite non-dominated sorting approach, allowing it to pinpoint Pareto optimal solutions through offspring creation and selection. A Crowding Distance (CD) coupled with an Information Feedback Mechanism (IFM) selection strategy is employed to maintain and amplify the convergence and diversity of potential solutions. MOGMO efficacy and capabilities are assessed using thirty notable case studies. This encompasses nineteen multi-objective benchmark problems without constraints, six with constraints and five multi-objective engineering design challenges. Based on the optimization results, the proposed MOGMO is better 54.83% in terms of GD, 64.51% in terms of IGD, 67.74% in terms of SP, 70.96% in terms of SD, 64.51% in terms of HV and 77.41% in terms of RT. Therefore, MOGMO has a better convergence and diversity for solving un-constraint, constraint and real-world application. Statistical outcomes from MOGMO are compared with those from Multi-Objective Equilibrium Optimizer (MOEO), Decomposition-Based Multi-Objective Symbiotic Organism Search (MOSOS/D), Non-dominated Sorting Genetic Algorithm (NSGA-II), Multi-Objective Multi-Verse Optimization (MOMVO) and Multi-Objective Plasma Generation Optimizer (MOPGO) algorithms, utilizing identical performance measures. This comparison reveals that MOGMO consistently exhibits robustness and excels in addressing an array of multi-objective challenges. The MOGMO source code is available at https://github.com/kanak02/MOGMO.

Project-Based Learning methodology (PBL) for the acquisition of Transversal Competences (TCs) and integration of Sustainable Development Goals (SDGs) in mechanical engineering subjects

This research is carried out within the framework of a two-year Educational Innovation and Improvement Project (EIIP) to be implemented at the Universitat Politècnica de València (UPV) during the academic years 2023-2024 and 2024-2025. The project aims to design and apply a Project-Based Learning methodology (PBL) for a proper acquisition of Transversal Competences (TCs) and integration of the Sustainable Development Goals (SDGs) in a mechanical engineering subject that is taught in the first year of the master’s degree in Mechatronic Engineering from the School of Design Engineering. Based on an assessment by the teaching staff of the current situation and the aspects to be improved, this article explains how the PBL methodology will be applied and performs an analysis through surveys and personal interviews with the students of their level of knowledge regarding the TCs and the SDGs that are worked on in the subject at the beginning of the academic year. The results show the need to continue working in the project and implementing active teaching techniques, such as PBL methodologies, to achieve a more attractive and motivating subject, closer to the labour market and a sustainable society.

Theoretical and simulation of central elliptical hole with rectangular plate

A study on design engineering components with slot, notches is very important, because there is a stress increases/failure region area, where the force/stress is concentrating more and more. The elastic stress concentration mainly depends on the mode of loading, materials, and geometry of the design engineering components. The design engineers, academicians, and researchers concentrated and focused on fail-safe design and safe life design. A Plate is considered with different slots, such as circular and elliptical. The main objective of this study is to find out the stress concentration factor in plates with various cutout shapes. This concept is used in design components/structures, for finding the elastic stress concentration. The methods compared are tabulated with their findings. Singularities of the circular hole and elliptical hole in rectangular plates are considered in the present study. The finite Element Method (FEM) was used for fine mesh and ANSYS WORKBENCH software was used for extracting the results and results were validated by analytical or experimental methods.

A novel hippo swarm optimization: for solving high-dimensional problems and engineering design problems

Abstract In recent years, scholars have developed and enhanced optimization algorithms to tackle high-dimensional optimization and engineering challenges. The primary challenge of high-dimensional optimization lies in striking a balance between exploring a wide search space and focusing on specific regions. Meanwhile, engineering design problems are intricate and come with various constraints. This research introduces a novel approach called Hippo Swarm Optimization (HSO), inspired by the behavior of hippos, designed to address high-dimensional optimization problems and real-world engineering challenges. HSO encompasses four distinct search strategies based on the behavior of hippos in different scenarios: starvation search, alpha search, margination, and competition. To assess the effectiveness of HSO, we conducted experiments using the CEC2017 test set, featuring the highest dimensional problems, CEC2022 and four constrained engineering problems. In parallel, we employed 14 established optimization algorithms as a control group. The experimental outcomes reveal that HSO outperforms the 14 well-known optimization algorithms, achieving first average ranking out of them in CEC2017 and CEC2022. Across the four classical engineering design problems, HSO consistently delivers the best results. These results substantiate HSO as a highly effective optimization algorithm for both high-dimensional optimization and engineering challenges.

Research on transient temperature rise characteristics of composite cylindrical roller bearings

Composite roller bearings have received extensive attention from bearing design engineers because of their good contact and running performance. According to the contact mechanical characteristics of composite cylindrical roller, a bearing heat generation power calculation model is established. Then, using the local heat source analysis method, and considering the heat conduction mode, the transient temperature solution model of bearings is established. The influence of filling ratio, radial force, angular velocity and roller numbers on the heat generation power and steady-state temperature of the bearing components is calculated and analyzed. The calculated results are in good agreement with the experimental results, which verifies the correctness of the model. The model can accurately predict the temperature distribution of bearings, providing new ideas and methods for temperature rise analysis, and laying the foundation for temperature analysis of bearings.