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Earthquake-induced soil liquefaction is a catastrophic phenomenon that can damage existing building foundations and other structures, resulting in significant economic losses. Traditional mitigation techniques against liquefaction present critical aspects, such as high construction costs, impact on surrounding infrastructure and effects on the surrounding environment. Therefore, research is ongoing in order to develop new approaches and technologies suitable to mitigate liquefaction risk. Among the innovative countermeasures against liquefaction, Induced Partial Saturation (IPS) is considered one of the most promising technologies. It consists of introducing gas/air bubbles into the pore water of sandy soils in order to increase the compressibility of the fluid phase and then enhance liquefaction resistance. IPS is economical, eco-friendly and suitable for urbanised areas, where the need to reduce the risk of liquefaction must be addressed, taking into account the integrity of existing buildings. However, IPS is still far from being a routine technology since more aspects should be better understood. The main aim of this review is to raise some important questions and encourage further research and discussions on this topic. The review first analyses and discusses the effects of air/gas bubbles on the cyclic behaviour of sandy soils, focusing on the soil volume element scale and then extending the considerations to the real scale. The use of useful design charts is also described. Moreover, a section will be devoted to the effect of IPS under shallow foundations. The readers will fully understand the research trend of IPS liquefaction mitigation and will be encouraged to further explore new practical aspects to overcome the application difficulties and contribute to spreading the use of this technology. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue in the journal Applied Sciences titled "Feature Review Papers in Mechanical Engineering." The issue covers various topics in mechanical engineering, including crank-slide actuating mechanisms, industrial robots, cellular manufacturing systems, shape memory alloys, and the application of Constructal theory. The articles explore the advancements, challenges, and potential solutions in these areas, aiming to enhance efficiency, adaptability, sustainability, and control in mechanical systems. The research presented in this special issue offers valuable insights and directions for further study in the field of mechanical engineering. [Extracted from the article]

Engineering design often involves representation in at least two levels of abstraction: the system-level, represented by lumped parameter models (LPMs), and the geometric-level, represented by distributed parameter models (DPMs). Functional design innovation commonly occurs at the system-level, followed by a geometric-level realization of functional LPM components. However, comparing these two levels in terms of behavioral outcomes can be challenging and time-consuming, leading to delays in design translations between system and mechanical engineers. In this paper, we propose a simulation-free scheme that compares LPMs and spatially discretized DPMs based on their model specifications and behaviors of interest, regardless of modeling languages and numerical methods. We adopt a model order reduction (MOR) technique that a priori guarantees accuracy, stability, and convergence to improve the computational efficiency of large-scale models. Our approach is demonstrated through the model consistency analysis of several mechanical designs, showing its validity, efficiency, and generality. Our method provides a systematic way to compare system-level and geometric-level designs, improving reliability and facilitating design translation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Higher Education & Science / Yüksekögretim ve Bilim Dergisi is the property of Zonguldak Bulent Ecevit Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Design processes can be decomposed into several steps, including information acquisition and application. Retrieving prior knowledge and experience is an important method of acquiring design information, thus designers' precedents retrieval styles reflect their design thinking. The obvious difference between industrial (ID) and mechanical design (MD) education is well known: ID education focuses on cultivating design thinking abilities, while MD education focuses on cultivating technical abilities. The background discipline influences design thinking methods. This study aims at exploring the similarities and differences between ID and MD students' precedents retrieval styles in the design process. Forty-eight junior and senior undergraduate students participated in a brainstorming experiment using the think-aloud method. Participants' prior knowledge and experience retrieved during brainstorming were coded and the frequency ratios were analyzed. We conclude that ID students are more inclined to extract and apply episodic precedents than MD students. Compared with semantic precedents, episodic precedents have a greater possibility for being applied to the final solution. [ABSTRACT FROM AUTHOR]

Technical Vocational Education and Training (TVET) colleges are career-focused educational institutions designed to equip students with lifelong technical skills thereby contributing significantly to economic growth. The purpose of this study was to investigate mechanical engineering equipment in three TVET colleges in three South African provinces. The three provinces included in the study were Gauteng, Limpopo, and Free State. The equipment was investigated in an effort to integrate virtual and cyber-physical learning. The research utilized interviews with campus managers and senior lectures on Engineering and Related Design (ERD) to acquire data. A structured questionnaire was also distributed to former ERD students who are currently employed in the mining industry. The equipment of TVET colleges was contrasted to that of the mining industry. According to the research, TVET college equipment is outdated and inadequate, and their practical assessments are not routinely updated. The colleges do not yet have a virtual and cyber-physical learning system in existence, but preparations have been made. However, no intentions for the practical portion of the studies using virtual systems have been considered. The study affirms the need for virtual learning, Virtual Reality (VR), and Augmented Reality (AR) technologies to help students learn about current technology equipment used in the mining industry, as well as to provide sufficient time for practical learning. [ABSTRACT FROM AUTHOR]

The process of opportunity recognition is pivotal to engineering design, fostering technological innovation and entrepreneurship. Although there are multiple studies conducted in the area of opportunity recognition studying the behaviors of entrepreneurs, examining engineering students' approaches have been underexplored. There is a lack of research in regards to opportunity recognition processes among engineering students, particularly in the context of design education. The presented study addresses this gap by qualitatively examining approaches to opportunity recognition among mechanical engineering students enrolled in an engineering design course. Using a sample of 23 mechanical engineering students, the approaches to opportunity recognition were analyzed using students' responses to open-ended survey questions and student group discussions. From the analysis of the qualitative data, four key themes emerged regarding the improvement of the device and process, user consideration, environmental sustainability, and information and resources accessed by students. The findings provide a deeper understanding that can be used to inform educational practices and further research in the area of opportunity recognition in engineering education settings. [ABSTRACT FROM AUTHOR]

As computer-aided design (CAD) tools have become an essential aspect of modern mechanical engineering design, the demand for CAD experts has increased significantly. The development from novice, to proficient, to expert user is of particular interest to the industrial and academic design communities. Yet little is known about the development of modeling choices, strategies, and patterns that characterize expert CAD skills; much of the past work that reports user action data is based on student or novice data. We compared the CAD modeling process across nine proficient and ten expert designers as they were tested to complete the same design task. Under identical conditions-the same time constraints in the same CAD platform and with the same task-the expert users were able to complete a larger proportion of the task with higher dimensional accuracy. While the experts were able to dissect and retrieve geometries from manufacturing drawings more efficiently than proficient users, they were also able to plan a modeling strategy that required less effort and revisions. With our experimental findings, we identify the demand for procedural knowledge-building for young engineers, with the ultimate goal of more effectively developing experts in engineering design with CAD. [ABSTRACT FROM AUTHOR]

Background: Due to its counter-intuitive nature, understanding the dynamics of nonlinear systems has given rise to many challenges to overcome. This has brought about so many quests to answer because most engineering systems are ubiquitously nonlinear in nature. Vibration analysis is found to be one of the dominant and predictive maintenance techniques. It ranges from budding problems to catastrophic failure of the rotating machinery. It leads to acceptance testing, quality control, loose part detection, noise control, leak detection, machine design and engineering.For example, vibration analysis is found to be a significant approach in the industries for analyzing the performance of rotating machinery. Purpose: The study of vibrational resonance is important in many branches of engineering. For example, in mechanical and civil engineering design, vehicle design, the design of steam-turbine rotor-bearing systems, and bridge design, and the design of vibration controllers and isolators. Understanding vibrational resonance is important to ensure an appropriate running condition, increase the effiency of machines and a desired behavior of the systems. Method: In this work,vibrational resonance for a class of velocity-dependent potentials and nonpolynomial type oscillator is studied. By using the method of separation of motions (MSM) an analytical equation for the slow oscillations of the systems is obtained in terms of the parameter of the fast signal. The analytical computations are verified by fourth order Runge-Kutta method. Result: The analytical findings concure well with numerical studies. The response amplitude (Q) of the system depending on the amplitude of high-frequency drive forcing strength. The effects of damping and strength of nonlinearity on the emergence of vibrational resonances and resonant frequencies are analyzed. It is intresting to note that decreasing the strength of the nonlinearity significantly contributies to the emergence of VR in the lower values of amplitude of high-frequency drive forcing strength. When the damping term is increseaed the response amplitude (Q) is reduced. Conclusion: In this paper, we have proposed the new avenue in a broad class of velocity-dependent potential systems and nonpolynomial oscillators, which are typically found in physical and mechanical situations. The results are useful for the study of energy transfer phenomena for this class of nonlinear systems and for investigating the effects of damping on the nonlinear behaviour. These results are important for the design and fault diagnosis of mechanical systems and structures which can be described by this nonlinear model. As a result, the study of the dynamics of nonlinear systems has drawn the attention of researchers in various fields such as for instance, engineering and cognitive sciences. [ABSTRACT FROM AUTHOR]

Hydrogels are porous biomaterials widely used in tissue engineering (TE), but they require a mechanism to enhance their mechanical properties. Electrospun nanofibrous yarn (EN yarn) can be a suitable candidate for reinforcing hydrogels. In this study, aiming to improve mechanical performance, hydrogel-based scaffolds reinforced by EN yarns (yarn reinforced hydrogel) were fabricated. The morphological characterization, swelling measurement, and tensile tests were performed to evaluate the physical, mechanical, and biological function of the designed yarn reinforced hydrogel. The measured mechanical properties were used as inputs in the mathematical model of the modified rule of mixtures to predict the mechanical behavior of different yarn reinforced hydrogels, which could be used as scaffolds for different tissues. Cell-scaffold interactions were also evaluated by in vitro assays. This study indicated that adding EN yarns to the neat hydrogel decreased the porosity and swelling, while the tensile strength and Young's modulus were improved. In vitro assays showed that cells had better adhesion and spread on the surface of the yarn reinforced hydrogel than those on the surface of the neat hydrogel. Regarding the improvement in mechanical and cellular properties, the yarn reinforced hydrogel has the potential to be used as a novel scaffold in TE. [ABSTRACT FROM AUTHOR]

In the era of the competitive environment, the improvement in current products is ensured through activities aimed at increasing a product’s quality level and, consequently, reducing the amount of waste. The dynamically changing production environment and sudden changes in customer expectations force us to take precise and well-thought-out development steps. Furthermore, it is important to anticipate favourable product changes to prepare for market changes over time. This is still an open problem. The aim of this study was to develop a method to predict the quality of potential product prototypes resulting from the proposed modifications of the product features. This methodology takes into account current customer expectations. The method was created based on the principles of creating Quality Function Deployment (QFD) in the context of taking into account current and future customer expectations regarding product features. This is a new approach to analysing product quality within the principles of the traditional QFD method. The originality of the study is the technique used in the method to estimate the expected values of product features and their importance (weights), taking into account current customer expectations. Its originality is also manifested in drawing conclusions supporting the decision-making process of product improvement, because it involves ensuring the pro-quality modification of selected features of current products in the order that is most advantageous from the customer’s point of view. The use of the proposed method allows for the analysis of the impact of modifying the current value of a product feature. The method is illustrated with an example of a vacuum cleaner for home use. However, the proposed method can be applied to the design of any product to predict products that will meet customer expectations.

The search process in population-based metaheuristic algorithms (MAs) can be classified into two primary behaviours: diversification and intensification. In diversification behaviour, the search space will be explored considerably based on randomization. Whereas intensification alludes to the search for a promising region locally. The success of MAs relies on the balance between two search behaviours. Nonetheless, it is strenuous to get the right balance between these behaviours due to the scholastic nature of MAs. Chaotic maps are proven an excellent tool to enhance both behaviours. This work incorporates the Logistic chaotic map into the recently proposed population-based MA called Electromagnetic field optimization (EFO). This suggested algorithm is named chaotic EFO (CEFO). An improved diversification step with chaos in EFO is presented to efficiently control the global search and convergence to the global best solution. CEFO is tested on different case studies, 40 unconstrained CEC 2014 and CEC 2019 benchmark functions, seven real-world nonlinear systems and three mechanical engineering design frameworks. All experiments are compared with other recent and improved algorithms in the literature to show the performance and effectiveness of the proposed algorithm. Two nonparametric statistical tests, the Wilcoxon rank-sum and the Friedman test, are performed on CEFO and other compared algorithms to determine the significance of the results and show the efficiency of CEFO over other algorithms. [ABSTRACT FROM AUTHOR]

As the most prestigious award in the field of machine design, the ASME Machine Design Award relishes its prestige and prominence. In the past 65 years since its inception in 1958, 60 eminent scholars have received this honor. This paper reviews the history of this prestigious award, including a summary of the contributions to the field of all 60 recipients, and acts as an archival document. Reviewing these awards in the past 65 years by following the tracks of its recipients elucidates developments in the field and significant contributions to the advancement of knowledge in machine design. In particular, novel contributions and remarkable achievements in the fields of mechanical engineering and machine design and development are recorded. This should be of interest to those interested in the study and in the historical development of mechanical engineering, particularly in machine design. [ABSTRACT FROM AUTHOR]

Flexible reinforcements are a promising option in slope engineering owing to their mechanical strength and ecological restoration. An in-depth understanding of the mechanical behavior of a slope reinforced by an anchored geomat system is required to analyze the slope stability and to optimize engineering design. In this study, physical modeling experiments are conducted to investigate the global performance and ultimate capacity of the reinforced slope under different loading levels. A stability model of the reinforced slope and the corresponding computing method are proposed based on a limit equilibrium framework in integral form. Subsequently, the contribution of a flexible protection system and its components to safety factors are quantified against loading tests. The results show that lateral deformation is concentrated in the middle of the reinforced slope, from which the potential failure surface can be derived. The stability enhancement of the reinforced slope is primarily attributed to the anchor bolts, and an increase in cohesion and internal friction angle increases the safety factor more significantly under low-level overloads. This study provides a benchmark for slopes reinforced by an anchored geomat system, which is promising for application in slope engineering. [ABSTRACT FROM AUTHOR]

In the optimization area, particle swarm optimization is an excellent optimization algorithm. It influenced thru position and velocity update of the particles. Particles velocity update significantly depend on its factor inertia weight (with previous velocity) and acceleration coefficients (with cognitive and social components). Also, PSO has various advantages like simplicity and fast convergence. However, PSO easily trapped into local optima due to simple search procedure. To improve the presentation of PSO, this article advises an updated-PSO (U-PSO) for solving mechanical engineering design optimization problems. In U-PSO, novel parameters (inertia weight, acceleration coefficients and lively coefficient) for velocity update and position update equation are employed to retain exploitation and exploration. To verify the efficiency and robustness, proposed U-PSO applied to solve two complex mechanical engineering designs optimization problems. The experimental outcomes validate that the suggested U-PSO has significant advantages over the compared algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Problems of Mechatronics. Armament, Aviation, Safety Engineering / Problemy Mechatroniki. Uzbrojenie, lotnictwo, Inżynieria Bezpieczeństwa is the property of Index Copernicus International and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Research & Development / Revista de Investigación & Desarrollo is the property of ECORFAN-Mexico S.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper describes goals, process, and results in the effort to introduce new curricula at The Faculty of Technical Sciences of University Mother Theresa - Skopje fully devoted to teach students in the direction of sustainable development. The idea was born in the process of reaccreditation of the old curricula named "Mechanical Engineering and management" at The Faculty of Technical Sciences. The authors of this paper, and the idea for reconstruction were fully aware of the direction Mechanical Engineering needs to go to contribute to the sustainable development of the country and wider. Therefore, that idea led the developing process into new curricula titled: "Sustainable Design in Mechanical Engineering". From total of 40 courses, 15-20 are fully related to sustainable development goals and the curricula includes also a number of projects and diploma work by which students will additionally have an opportunity to add to their understanding and knowledge of sustainable development tools. The new curricula successfully passed the process of accreditation and it is now a part of this University offer. Based on this curricula, a number of courses for lifelong learning will be developed. It is expected that this curricula will attract attention both of the new students, but also of the professionals at different companies, state and municipality institutions. [ABSTRACT FROM AUTHOR]

The Competitive Swarm Optimizer (CSO) has emerged as a prominent technique for solving intricate optimization problems by updating only half of the population in each iteration. Despite its effectiveness, the CSO algorithm often exhibits a slow convergence rate and a tendency to become trapped in local optimal solutions, as is common among metaheuristic algorithms. To address these challenges, this paper proposes a hybrid approach combining the CSO with the Salp Swarm algorithm (SSA), CL-SSA, to increase the convergence rate and enhance search space exploration. The proposed approach involves a two-step process. In the first step, a pairwise competition mechanism is introduced to segregate the solutions into winners and losers. The winning population is updated through strong exploitation using the SSA algorithm. In the second step, non-winning solutions learn from the winners, achieving a balance between exploration and exploitation. The performance of the CL-SSA is evaluated on various benchmark functions, including the CEC2017 benchmark with dimensions 50 and 100, the CEC2008lsgo benchmark with dimensions 200, 500 and 1000, as well as a set of seven well-known constrained design challenges in various engineering domains defined in the CEC2020 conference. The CL-SSA is compared to other metaheuristics and advanced algorithms, and its results are analyzed through statistical tests such as the Friedman and Wilcoxon rank-sum tests. The statistical analysis demonstrates that the CL-SSA algorithm exhibits improved exploitation, exploration, and convergence patterns compared to other algorithms, including SSA and CSO, as well as popular algorithms. Furthermore, the proposed hybrid approach performs better in solving most test functions. [ABSTRACT FROM AUTHOR]

This study proposes a novel population-based metaheuristic algorithm called the Gazelle Optimization Algorithm (GOA), inspired by the gazelles' survival ability in their predator-dominated environment. Every day, the gazelle knows that if it does not outrun and outmaneuver its predators, it becomes meat for the day, and to survive, the gazelles have to escape from their predators consistently. This information is vital to proposing a new metaheuristic algorithm that uses the gazelle's survival abilities to solve real-world optimization problems. The exploitation phase of the algorithm simulates the gazelles grazing peacefully in the absence of the predator or while the predator is stalking it. The GOA goes into the exploration phase once a predator is spotted. The exploration phase consists of the gazelle outrunning and outmaneuvering the predator to a safe haven. These two phases are iteratively repeated, subject to the termination criteria, and finding optimal solutions to the optimization problems. The robustness and efficiency of the developed algorithm as an optimization tool were tested using benchmark optimization test functions and selected engineering design problems (fifteen classical, ten composited functions, and four mechanical engineering design problems). The results of the GOA are compared with nine other state-of-the-art algorithms. The simulation results obtained confirm the superiority and competitiveness of the GOA algorithm over nine state-of-the-art algorithms available in the literature. Also, the standard statistical analysis test carried out on the results further confirmed the ability of GOA to find solutions to the selected optimization problems. It also showed that GOA performed better or, in some cases, was very competitive with some state-of-the-art algorithms. Also, the results show that GOA is a potent tool for optimization that can be adapted to solve problems in different optimization domains. [ABSTRACT FROM AUTHOR]

ntroduction-- Robotic rehabilitation devices for motor impairment patients are widely used since they significantly impact the rehabilitation process by offering a uniform exercise plan without typical variations due to different human therapists. These devices require force sensors to monitor the patient recovery evolution. Among the rehabilitation robotic devices is the two degree-of-freedom MIT-MANUS model used in patients with upper limbs motor problems. In order to complement the use of a MIT-MANUS system, it is necessary to equip it with planar sensing forces capability. Unfortunately, commercial devices are very expensive and not very accessible in countries like Colombia. Therefore, the research objective is to develop a force sensor for a robotic MIT-MANUS system that is simple, robust, economical and reliable. Objective-- Develop an in-plane sensing device capable of detecting, with good precision and an acceptable measurement error, the forces exerted by girls and boys up to 10 years of age. Methodology-- A Mechanical Engineering methodological design approach was used, based on the phases of conception, design, CAE validation, construction, assembly and experimental tests. Results-- The research main result was the construction of an experimentally validated sensing device capable of measuring force up to 60 N in the plane. Conclusions-- After carrying out the tests and experimental trials, it was possible to verify that the sensor is reliable when measuring a force in the plane. The maximum measurement error of a vertical or horizontal force component is 10%, which is reduced to 6% when the resultant force value is calculated. The source of the errors is diverse, due to the non-homogeneity of the metallic element, the type of gauge that was used, the chemicals used to weld the gauge to the mechanical element, ADC conversion problems, among others, but their acceptable values allow using of the gauge in the application initially planned. [ABSTRACT FROM AUTHOR]

The CanSat Competition is an international design/build/fly engineering competition held yearly in Stephenville, Texas and provides students with an opportunity to design an aerospace system. It is designed to reflect a small-scale aerospace program and includes the project design life cycle from preliminary design review to post mission review. Teams of up to 10 undergraduate students build CanSats, which must complete a mission that changes every year. In this year’s mission, the CanSat will be launched to 700 meters using a high-powered model rocket, and must perform a controlled descent while transmitting data from its onboard sensors to a ground station computer. The CanSat consists of a container that must protect the science payload from damage during the launch and deployment. Initially, both descend under a parachute. At 400 meters, the payload is released and continues its descent using an autogyro propeller. The CanSat must be equipped with sensors for environmental conditions (temperature, pressure, GPS position, altitude) and system performance (orientation, battery voltage, auto-gyro spin rate). It must be capable of transmitting this data in real-time to a ground station computer. The scope of our project is designing and building the CanSat and ground station. The launch system (a high-power model rocket) is provided by the competition organizers to standardize launches. Our team represents UC Irvine in this international competition. Members of CanSat UCI will follow the engineering design process from concept generation through integration and test, actual operation of the system, and the concluding post-mission summary and debrief. This year’s objective is to build a probe (the CanSat) that transmits environmental data to a ground station and performs a controlled descent using a parachute and auto-gyro propeller. The mission and its requirements reflect aspects of real world missions, including telemetry requirements, communications, and autonomous operations. Our project deliverables are the Preliminary Design Review and Critical Design Review presentations, the CanSat and ground station hardware, and the post-mission review. We follow a yearly design cycle, adhering to deadlines and requirements imposed by the competition. This ensures all teammates gain experience with the full engineering design process.Faculty Advisor:  Professor RangelEmail:  cansatuci@gmail.comWebsite:  https://sites.google.com/a/uci.edu/cansat/

The present paper proposes self-adaptive multi-population elitist (SAMPE) Rao algorithms and chaotic Rao algorithms for design optimization of selected mechanical engineering components. The proposed algorithms are applied to 25 benchmark problems and 15mechanical engineering design optimization problems to examine their performance. The Friedman rank test is utilized to demonstrate the significance of the proposed algorithms and the algorithms are ranked according to their performance. The results obtained using the proposed algorithms are compared with the results obtained using other advanced optimization algorithms to demonstrate the effectiveness of the proposed algorithms. It is observed that the performance of the proposed algorithms is either better or competitive to the basic Rao algorithms and the other advanced optimization algorithms. [ABSTRACT FROM AUTHOR]

Lower costs and higher employee satisfaction are some of the benefits driving organizations to adopt dispersed and virtual working arrangements. Despite these advantages, product design engineering teams—those who develop physical products—have not widely adopted this working style due to perceived critical dependence on physical facilities and the belief that it is ineffective to communicate technical details virtually. This paper uses the mass shift in working conditions caused by the COVID-19 pandemic to explore the feasibility of virtual and distributed work in product design engineering. We conducted 20 semi-structured interviews with product design engineers working virtually to uncover current challenges of, and the beginning of promising strategies for, effective virtual engineering work. We categorize and analyze Tangible Design activities, Intangible Design activities, and Communication and Project Management activities throughout the product design process. Contrary to present opinions, we found that much of a product design engineer's work is realizable in a virtual and distributed setting. However, there are still many challenges, especially when attempting Tangible Design activities—those that require physical products and tools—from home. These challenges, missing from existing virtual product design engineering literature, include but are not limited to individuals' lessened sense of accountability, fewer de-risking opportunities before product sign-off, and limited supervision of production staff. Product design engineers described novel strategies that emerged organically to mitigate these challenges, such as creating digital alternatives for engineering reviews and sign-offs and leveraging rapid prototyping. Recent advances in technology, an increased commitment to reducing environmental impact, and better work-life balance expectations from new generations of workers will only push society faster towards a distributed working model. Thus, it is critical that we use this opportunity to understand the existing challenges for distributed product design engineers, so that organizations can best prepare and become resilient to future shocks. [ABSTRACT FROM AUTHOR]

With biped and quadruped robots becoming more prevalent in society, there is a strong push for universities to update their robotics curriculum to teach students how to design, build, and program legged robotic systems. One of the challenges associated with developing legged robotics curriculum is finding opportunities for students to engage in hands-on legged robotic activities that complement theory and enhance the overall learning process. This challenge is particularly evident at smaller universities or universities with limited research budgets where the cost of purchasing a quadruped platform can be prohibitive. With the recent release of several open-source quadruped robot designs, there is now an opportunity to incorporate quadruped platforms into more university classrooms. This paper outlines our approach to modifying one of these open-source designs to support our department's education, outreach, and research goals. The development of our modified, opensource quadruped platform (OpenMutt) was conducted under the auspices of a capstone mechanical engineering design project to demonstrate how the platform builds on existing curriculum and to identify areas where additional robotic instruction may be warranted. Our results indicate that it is possible to use capstone engineering design projects to identify and address potential gaps in existing curriculum. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos del Centro de Estudios de Diseño y Comunicación is the property of Cuadernos del Centro de Estudios de Diseno y Comunicacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Real‐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. [ABSTRACT FROM AUTHOR]

The goal of this research is to understand, explore, and align the motivation and value that industry gains from sponsoring senior level mechanical engineering capstone design projects at Clemson University. This research compares the expected values of capstone projects from the perspectives of both the sponsoring companies and university faculty. If faculty understand the expected value from the sponsor, faculty could more effectively solicit and scope sponsor-based projects. Interviewing was used as the data collection method to explore faculty and company sponsor perceptions regarding the capstone design program. Interview results are linked and evaluated to extract thematic patterns in the responses. Conclusions of this work show that faculty anticipate companies continue to sponsor projects if the final products generated by the student teams are beneficial to the company. Companies tend to gain value from sponsoring capstone by providing low priority projects to garner solutions with minimal investment. Further, the realized benefit of the projects for the sponsoring companies depends on the structuring of the program, the proximity of the university, and the relationship between the company and university. [ABSTRACT FROM AUTHOR]