Mechanical Engineering Design Research Articles

Weibull strength distribution and reliability S-N percentiles for tensile tests

Based on the true stress, the ultimate material’s strength, and the fatigue slope b values, the probabilistic percentiles of the S-N curve of ductile materials are formulated. The Weibull β and η parameters used to determine the product’s reliability are determined directly from the material’s strength values corresponding to 103 and 106 cycles. And since in Table corresponding to the properties of this A538 A (b) steel and collected by table 23-A of Shigley Mechanical Engineering Design book; authors present the σt, Sut, and b values of several materials, then the Weibull parameters for each one of these materials as well as the 95% and 5% reliability percentiles of their S-N curves are given. A step-by-step application to the steel A538 A (b) material is presented. And based on the maximum and minimum applied stress values, the corresponding Weibull stress distribution was fitted and used with the Weibull strength distribution, in the stress/strength reliability function to determine the element’s reliability.

PROYEK PENGGUNAAN KEMBALI SAMPAH KARDUS MENJADI BENDA PAKAI UNTUK SATUAN PENDIDIKAN DI KABUPATEN BANGKA

Inorganic waste in the form of cardboard waste can be reused into various recycled creations that have economic value. This service project aims to provide direct benefits from recycling cardboard waste into disposable objects for educational units in Bangka Regency. The cardboard waste recycling method starts from collecting cardboard waste around the Polman Negeri Babel environment and implementing a creation class. The creation class was attended by several students of Mechanical Design Engineering study program. The design of disposable objects is made using AutoDesk Inventor software according to the theme and design form. In making the design, the main thing that must be considered is that the dimensions of the used object must be adjusted to the size of the cardboard that is available or used. The result of this service project is that the UKS Shelf consists of three objects, namely the UKS shelf, first aid kit and file box, each made in 4 copies, so that there are 4 Education Units in Bangka Regency that will benefit directly from this project.

A hybrid binary dwarf mongoose optimization algorithm with simulated annealing for feature selection on high dimensional multi-class datasets

The dwarf mongoose optimization (DMO) algorithm developed in 2022 was applied to solve continuous mechanical engineering design problems with a considerable balance of the exploration and exploitation phases as a metaheuristic approach. Still, the DMO is restricted in its exploitation phase, somewhat hindering the algorithm's optimal performance. In this paper, we proposed a new hybrid method called the BDMSAO, which combines the binary variants of the DMO (or BDMO) and simulated annealing (SA) algorithm. In the modelling and implementation of the hybrid BDMSAO algorithm, the BDMO is employed and used as the global search method and the simulated annealing (SA) as the local search component to enhance the limited exploitative mechanism of the BDMO. The new hybrid algorithm was evaluated using eighteen (18) UCI machine learning datasets of low and medium dimensions. The BDMSAO was also tested using three high-dimensional medical datasets to assess its robustness. The results showed the efficacy of the BDMSAO in solving challenging feature selection problems on varying datasets dimensions and its outperformance over ten other methods in the study. Specifically, the BDMSAO achieved an overall result of 61.11% in producing the highest classification accuracy possible and getting 100% accuracy on 9 of 18 datasets. It also yielded the maximum accuracy obtainable on the three high-dimensional datasets utilized while achieving competitive performance regarding the number of features selected.

Sketch-Based Modeling in Mechanical Engineering Design: Current Status and Opportunities

Sketch-Based Modeling (SBM) is a field of study that focuses on the automatic creation of 3D models from freehand drawings. Today, two related branches coexist: one aimed at facilitating input for 3D content creation, and the other aimed at routing engineering designs into CAD/CAM/CAE. The latter is the goal of this position paper. Early attempts concentrated on the problem of line-drawing interpretation , but efforts switched toward geometric reconstruction as the “inverse projection” problem became the most challenging step to produce 3D models from 2D line-drawings. The term SBM was popularized when sketches began to displace line-drawings as main input. In the context of engineering design, interest in SBM has somewhat decreased, as studies have shown that current SBM tools are not as usable as paper and pencil sketches, nor do they yet provide any additional value to traditional media. Furthermore, engineers feel reasonably comfortable with current Mechanical CAD (MCAD) paradigms based on parametric modeling, and fail to recognize the potential benefits of interacting with computers via sketches. However, new technological trends such as personal fabrication and the democratization of CAD and manufacturing can significantly benefit from improved SBM tools. In this paper, we conduct a meta-review of the SBM literature which we view as a combination of three elements: geometry (shape), psychology (perception), and engineering (function). We advocate for a new approach to SBM based on reformulating the weights of these elements as an approach for searching the set of intentions in sketches conveyed through cues which, when perceived, reveal regularities and features of the object. Finally, we consider quality of CAD models not just as error-free models, reusable models, or even models that convey design intent, but models that consider these interrelated aspects as a whole. B-Rep models produced by current SBM approaches are “dumb models” without parametrization or procedures required to enable reusability and ensure that the design intent of the sketch is properly conveyed. We advocate for improved analysis approaches aimed at revealing higher-level design information embedded in engineering sketches, as a critical stage to generate richer 3D MCAD models. • A review of Sketch-Based Modeling (SBM) for Engineering Design is provided. • Two different branches of SBM research coexist: one geared toward “artistic” purposes and the other governed by “engineering” principles. • The two branches must be studied separately, because of the fundamentally different goals of artistic vs. engineering sketches and the different nature of the 3D models that must be generated. • While the automatic conversion of artistic sketches into 3D models has made significant progress in recent years, the problem of producing CAD models with controllable, semantic, and parametric solid geometry has not yielded significant contributions to the scholarly literature. • Future opportunities, research directions, and recommendations on SBM approaches for engineering design are discussed.

Biomathematical Analysis on Mechanical Engineering during COVID-19 Pandemic

In mechanical engineering research and design process will involve a large number of mathematical applications. In order to analyze the significance and application of mathematics in the research and design of mechanical engineering, this paper lists and analyzes the basic mathematical equations, mathematical models and finite element related problems in some fields of learning. The results show that the application of mathematics in mechanical engineering is not limited to higher mathematics, but also covers the related knowledge of numerical processing, matrix theory and other courses during COVID-19 pandemic.

Fire Hawk Optimizer: a novel metaheuristic algorithm

This study proposes the Fire Hawk Optimizer (FHO) as a novel metaheuristic algorithm based on the foraging behavior of whistling kites, black kites and brown falcons. These birds are termed Fire Hawks considering the specific actions they perform to catch prey in nature, specifically by means of setting fire. Utilizing the proposed algorithm, a numerical investigation was conducted on 233 mathematical test functions with dimensions of 2–100, and 150,000 function evaluations were performed for optimization purposes. For comparison, a total of ten different classical and new metaheuristic algorithms were utilized as alternative approaches. The statistical measurements include the best, mean, median, and standard deviation of 100 independent optimization runs, while well-known statistical analyses, such as Kolmogorov–Smirnov, Wilcoxon, Mann–Whitney, Kruskal–Wallis, and Post-Hoc analysis, were also conducted. The obtained results prove that the FHO algorithm exhibits better performance than the compared algorithms from literature. In addition, two of the latest Competitions on Evolutionary Computation (CEC), such as CEC 2020 on bound constraint problems and CEC 2020 on real-world optimization problems including the well-known mechanical engineering design problems, were considered for performance evaluation of the FHO algorithm, which further demonstrated the superior capability of the optimizer over other metaheuristic algorithms in literature. The capability of the FHO is also evaluated in dealing with two of the real-size structural frames with 15 and 24 stories in which the new method outperforms the previously developed metaheuristics.

Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems

Because of their superior problem-solving ability, nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization problems. Engineering academics have recently focused on meta-heuristic algorithms to solve various optimization challenges. Among the state-of-the-art algorithms, Differential Evolution (DE) is one of the most successful algorithms and is frequently used to solve various industrial problems. Over the previous 2 decades, DE has been heavily modified to improve its capabilities. Several DE variations secured positions in IEEE CEC competitions, establishing their efficacy. However, to our knowledge, there has never been a comparison of performance across various CEC-winning DE versions, which could aid in determining which is the most successful. In this study, the performance of DE and its eight other IEEE CEC competition-winning variants are compared. First, the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions, and the performances have been compared. One unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems, out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite, have been solved to compare the performances. Statistical analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm’s ability statistically. Performance analysis exposes that none of the DE variants can solve all the problems efficiently. Performance of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.

Research on Post Competency of Mechanical Design Engineer in Small and Medium-sized Manufacturing Enterprises under the Background of Industrial Upgrading

In view of the poor matching of mechanical design engineers in small and medium-sized enterprises under the background of industrial transformation and upgrading, this paper analyzes the requirements of this post for practitioners from the five dimensions of quality, motivation, knowledge, ability and psychology by constructing the competency model of this post. Through the investigation of small and medium-sized enterprises, 40 specific requirements indexes are determined, and the weight of each index is obtained by quantitative analysis with Likert rating scale analysis method, which can further distinguish the key indexes. Thus, it provides a basis for enterprises in talent recruitment, training and assessment, which can effectively improve the matching degree of talents and posts, and inject vitality into the development of small and medium-sized enterprises.

A modular nonlinear stochastic finite element formulation for uncertainty estimation

The Monte Carlo method is widely used for the estimation of uncertainties in mechanical engineering design. However, while flexible, this method remains impractical in terms of computational time and scalability. To bypass these limitations, other more efficient approaches such as the Galerkin stochastic finite element method (GSFEM) or the collocation method have been proposed. GSFEM provides accurate output statistics, has the advantage of being sampling independent and can be modular in terms of operations, albeit code intrusive. While linear elasticity has been extensively covered in the literature, the application of GSFEM to nonlinear mechanical behaviour remains relatively unexplored, in part due to the difficulty to capture nonlinear effects with the traditional GSFEM interpolants. To this end, we propose a seamless and efficient modular framework avoiding the need to know a priori the material law. In particular, the method makes use of a wavelet based formulation able to capture simultaneously continuous and discontinuous behaviours, and stochastic operators are proposed to straightforwardly adapt any material model. Finally, the flexibility of this approach is illustrated with two problems: (i) a 3D hyperelastic example with nonlinear behaviour arising from buckling uncertainty, and (ii) the evaluation of the displacement of a point within a structure based on how much of the external accessible structural deformation is known.

Exploring the Design of Highly Energy Efficient Forestry Cranes using Gravity Compensation

Although most mechanized forestry work relies heavily on cranes for handling logs along the supply chain, there has been little research on how to improve cranes design. In addition, the available research has mainly focused on improving current designs, so there is a lack of application of modern methods for designing cranes with improved efficiency.This paper analyzes how a mechanical engineering design method, known as gravity compensation, can be used to make a new generation of highly energy efficient forestry cranes. To introduce this design approach, a standard forwarder crane with two booms is used as a model system on which to apply gravity compensation concepts. The design methodology follows a procedure based on physics and mathematical optimization, with the objective of minimizing the energy needed to move the crane by using gravity compensation via counterweights. To this end, we considered to minimize mechanical power, because this quantity relates to how fuel and hydraulic fluid are converted into mechanical motion.This analysis suggests that using gravity compensation could reduce energy consumption due to crane work by 27%, at the cost of increasing the crane total mass by 57%. Thus, the original crane mass of 559 kg increases to 879 kg after applying gravity compensation with counterweights. However, overall reductions in energy consumption would depend on both the crane work and the extraction distance. The greater the extraction distance, the lower the total savings. However, energy consumption savings of around 2% could be achieved even with an extraction distance of 1 km.From a design perspective, this study emphasized the need to consider gravity compensation in the design philosophy of forestry cranes, not only for its ability to minimize energy consumption, but also due to all the inherited properties it provides. This initial study concludes that designing cranes with a combination of gravity compensation concepts could yield a new generation of highly energy efficient cranes with energy savings exceeding those reported here.

Russian Technology of Industry 5.0. Metaontology

The methods and means of creating integrated intelligent systems for design and technological design in mechanical engineering are described. Introduced representation of knowledge modules for non-programmer

Road Safety Policies for Saudi Females: A Fuzzy Logic Analysis

Perceptions, attitudes and anticipated behavior represent very useful information for decision and policy makers before they implement proposed new policies. Road safety is one of the most critical fields in the built environment. In the Kingdom of Saudi Arabia, women started driving in 2019. There is a huge shortage of studies that investigate users’ attitudes and behavior, particularly women, in Saudi Arabia. It is very timely therefore, to assess their perceptions, attitudes and raise their awareness towards road safety. In this paper, the perceptions and attitudes towards road safety and relevant policies and programs were assessed and compared using two approaches: analytical and a fuzzy logic system. By means of a questionnaire, a total of 17 road safety policies, including engineering, enforcement programs, education programs and legislation programs, were presented to the participants and assessed. These policies were assessed from the viewpoint of Saudi women. The engineering policies included the use of road signs and marking, improving road network alignment, monitoring driver speed and engineering speed reduction measures. The assessment was in terms of the usefulness of the policies to reduce traffic accidents and improve road safety in Riyadh. A total of 375 participants were surveyed. Using a Likert scale response system to report the Saudi female participants’ opinions, two sets of indices were calibrated to evaluate the perceived usefulness and acceptability of the safety policies. A MATLAB simulation of a fuzzy logic system was utilized to assess, investigate and compare travel attitudes and perceptions of road safety. The results indicate overall encouragement for the safety programs and policies by the participants. Most of the support seems to be for the engineering program. The physical presence of traffic police was observed to have scored the highest. This is an interesting result that shows that enforcement policies are still perceived to be the most effective. In this category, the policy of enforcing speed limits showed high support, amongst the other policies. While a fuzzy logic analysis is typically used in hard engineering assessments and investigations, such as mechanical engineering and system design applications, the results obtained in this investigation show that the efficacy and adequacy of the proposed fuzzy logic control system in assessing attitudinal data was sufficiently good to be recommended for future research. The outcomes from both sets of approaches, the analytical and the fuzzy logic, showed comparable results, which also demonstrates the potential benefits of using the fuzzy system in many attitudinal and behavioral studies.

DeepPhysics: A physics aware deep learning framework for real‐time simulation

AbstractReal‐time simulation of elastic structures is essential in many applications, from computer‐guided surgical interventions to interactive design in mechanical engineering. The finite element method is often used as the numerical method of reference for solving the partial differential equations associated with these problems. Deep learning methods have recently shown that they could represent an alternative strategy to solve physics‐based problems. In this article, we propose a solution to simulate hyper‐elastic materials using a data‐driven approach, where a neural network is trained to learn the nonlinear relationship between boundary conditions and the resulting displacement field. We also introduce a method to guarantee the validity of the solution. In total, we present three contributions: an optimized data set generation algorithm based on modal analysis, a physics‐informed loss function, and a hybrid Newton–Raphson algorithm. The method is applied to two benchmarks: a cantilever beam and a propeller. The results show that our network architecture trained with a limited amount of data can predict the displacement field in less than a millisecond. The predictions on various geometries, topologies, mesh resolutions, and boundary conditions are accurate to a few micrometers for nonlinear deformations of several centimeters of amplitude.

Crystal structure optimization approach to problem solving in mechanical engineering design

PurposeIn this paper, the authors aim to examine and comparatively evaluate a recently-developed metaheuristic called crystal structure algorithm (CryStAl) – which is inspired by the symmetries in the internal structure of crystalline solids – in solving engineering mechanics and design problems.Design/methodology/approachA total number of 20 benchmark mathematical functions are employed as test functions to evaluate the overall performance of the proposed method in handling various functions. Moreover, different classical and modern metaheuristic algorithms are selected from the optimization literature for a comparative evaluation of the performance of the proposed approach. Furthermore, five well-known mechanical design examples are utilized to examine the capability of the proposed method in dealing with challenging optimization problems.FindingsThe results of this study indicated that, in most cases, CryStAl produced more accurate outputs when compared to the other metaheuristics examined as competitors.Research limitations/implicationsThis paper can provide motivation and justification for the application of CryStAl to solve more complex problems in engineering design and mechanics, as well as in other branches of engineering.Originality/valueCryStAl is one of the newest metaheuristic algorithms, the mathematical details of which were recently introduced and published. This is the first time that this algorithm is applied to solving engineering mechanics and design problems.

Using transformative learning theory to explore student points of view in a second-year mechanical engineering design course: A collaborative action research approach

ABSTRACT The goal of this work was to explore ways, within an existing engineering curriculum, to address the culture of disengagement by challenging the dominant engineering mindset. We conducted Collaborative Action Research to explore the implementation of Transformative Learning pedagogies in a Human-Centered Design context to understand how students make meaning of engineering contexts that involve unique sociotechnical considerations. Findings suggest that introducing students to such contexts allows them to use other points of view which can challenge the dominant engineering mindset and promote openness to the social nature of engineering, resulting in a more informed understanding of the nature of engineering overall. Furthermore, adopting Transformative Learning Theory as a framework for understanding and interpreting how the points of view students utilize can address the culture of disengagement by challenging the dominant engineering mindset. A framework connecting students’ points of view to their understanding of the nature of engineering is provided.

Determination of Eigenvalues in Problems on the Buckling of Compressed Rods (Part I)

In many technical academic courses and in the calculations of mechanical design engineers, buckling is a difficult problem. The applied methods of its solution are of a private nature and are unsuitable for modern, more complex structures in such sectors of the economy as mechanical engineering, construction, instrument making, oil and gas facilities, the nuclear industry, power networks, etc. complex problems of the stability of a compressed rod and at the same time achieve greater clarity and versatility with the proposed methods. Using specific examples, the application of the traditional analytical and the proposed analytical-graphic methods is shown. The proposed mathematical models and decision algorithms are verified using computational experiments. Based on the results obtained, practical conclusions are drawn.

An Optimized Chemical and Mechanical Engineering Design of an Ammonia Reactor

Design of an ammonia reactor was conceived as part of a series of item designs for an ammonia plant in Cyprus. The Chemical and Mechanical aspects of the design were considered. Optimization of these designs was studied, worked on, & discussed. The safety, environmental and legal regulations of relevant reactor regulations were followed in the design concerned.

Determining static stiffness of damper elastic rings

The article describes a method for experimental evaluation of the stiffness of an elastic damper ring. A thin-walled low-stiffness ring with uniformly distributed smooth protrusions on the inner and outer surfaces acts as a damper ring. Despite the widespread use of such a design in domestic and foreign mechanical engineering, control of the characteristics of this element and, accordingly, of the support as a whole remains quite difficult. A numerical model was developed, the reliability of which is confirmed by analytical calculations. To check the data obtained by numerical calculations, a special device was designed, which was installed on the galdabini tensile testing machine, where a series of measurements was carried out. Analysis of the data obtained showed a significant difference between the numerical, analytical and experimental data, which can be explained by the discrepancy between the equipment used and the boundary conditions of the theoretical model. The parameters of the device were selected in such a way that its rigidity was much higher than the rigidity of the elastic ring under study. The paper describes the improvement of both the design of the device and the method for determining the stiffness of the elastic ring of the damper using the specified measuring equipment. After making corrections, the obtained data on the scatter of the stiffness of the elastic ring are in good agreement with the analytical and numerical dependence, which makes it possible to use the data of the latter to refine the analytical methods in the future

Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: a comprehensive survey, applications, comparative analysis, and results

Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: a comprehensive survey, applications, comparative analysis, and results

What distinguishes a model of systems engineering from other models of designing? An ontological, data-driven analysis

This paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues.