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Numerical simulation of fatigue crack growth (FCG) is presented, based on the application of the extended finite element method (XFEM). Couple of case studies are presented, as a review of recent experience of the Belgrade school of XFEM simulations, established at the Faculty of Mechanical Engineering. Case studies comprised Charpy specimen with initial crack at the notch tip, oil rig pipe with an axial surface crack, pressure vessels with a crack at the welded joint with connecting pipe, turbine shaft with a crack at the transition radius, optimization of a wing spar in respect to FCG, the effect of mesh size on fatigue life estimation of a stringer panel, fatigue life estimation of wing‐to‐fuselage connecting lug, geometry effect on fatigue life of orthopedic plates and fatigue life of hip implant. Based on these case studies, XFEM is discussed in respect to its accuracy and efficiency. It is concluded that XFEM is a versatile tool for simulation of FCG, providing an excellent option for precise and reliable fatigue life of a cracked component. [ABSTRACT FROM AUTHOR]

Extrusion is a versatile process capable of producing a variety of new and novel foods and ingredients, thus increasing manufacturing opportunities. Further, it could provide nutritious, safe, sustainable, and affordable foods, especially directed at individualized consumer needs. In addition to past research efforts, more investigations should be conducted in order to refine, redesign, or develop new extrusion processing technologies. The present review highlights the current advances made in new and novel food product development by considering the extrusion process, the influencing parameters, and product characteristics and properties; the most promising extrusion processes that can be used in novel food product and ingredient development, such as extrusion cooking, hot-melt extrusion, reactive extrusion, and extrusion-based 3D printing; the possibilities of using various raw materials in relation to process and product development; and the needs for product development modeling along with extrusion process design and modeling. In correlation with extruded product development, topics that merit further investigation may include structure formation, plant and animal biopolymers functionalization, biopolymer reactions, process simulation, modeling and control, engineering and mechanical aspects of extruders, analysis of pre-processing treatments, as well as prototyping, risk analysis, safety, sensory and consumer acceptance. [ABSTRACT FROM AUTHOR]

Snow and ice animation methods are becoming increasingly popular in the field of computer graphics (CG). The applications of snow and ice in CG are varied, ranging from generating realistic background landscapes to avalanches and physical interaction with objects in movies, games, etc. Over the past two decades, several methods have been proposed to capture the time‐evolving physical appearance or simulation of snow and ice using different models at different scales. This state‐of‐the‐art report aims to identify existing animation methods in the field, provide an up‐to‐date summary of the research in CG, and identify gaps for promising future work. Furthermore, we also attempt to identify the primarily related work done on snow and ice in some other disciplines, such as civil or mechanical engineering, and draw a parallel with the similarities and differences in CG. [ABSTRACT FROM AUTHOR]

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]

Given its ongoing struggles at attaining demographic diversity and its key role in nations' economies, the engineering workforce receives considerable attention from researchers and policymakers. Yet, prior studies and STEM recruitment initiatives have often underemphasized the variety among available engineering jobs and careers. It therefore remains unclear which attributes of engineering work are most salient in shaping students' choices to persist in or depart from engineering pathways. This study introduces a novel conjoint survey experiment conducted with over 1000 senior year mechanical engineering students. This randomized experiment allows the authors to disentangle supply-side and demand-side factors to assess engineering job attributes' marginal influences on students' occupational preferences, as well as to examine these attributes' interaction effects with supply-side factors. Toward strengthening persistence in engineering pathways, findings suggest that broad STEM recruitment initiatives, though potentially advantageous in pre-college years, should give way to more targeted campaigns that increase university students' awareness about key dimensions of variety across engineering work roles. [ABSTRACT FROM AUTHOR]

Modeling of structural nonlinear dynamic behavior is a central challenge in civil and mechanical engineering communities. The phase space embedding of response time series has been demonstrated to be an efficient coordinate basis for data-driven approximation of the modern Koopman operator, which can fully capture the global evolution of nonlinear dynamics by a linear representation. This study demonstrates that linear and nonlinear structural dynamic vibrations can be represented by a universal forced linear model in a finite dimension space projected by time-delay coordinates. Compared with the existing methods, the proposed approach improves the performance of finite linear representation of nonlinear structural dynamics on two essential issues including the robustness to measurement noise and applicability to multidegree-of-freedom (MDOF) systems. For linear structures, the dynamic mode shapes and the corresponding natural frequencies can be accurately identified by using the time-delay dynamic mode decomposition (DMD) algorithm with acceleration response data experimentally measured from an 8-story shear-type linear steel frame. Modal parameters extracted from the time-delay DMD matched well with those identified from traditional modal identification methods, such as frequency domain decomposition (FDD) and complex mode indicator function (CMIF). In addition, numerical and experimental studies on nonlinear structures are conducted to demonstrate that the finite-dimensional DMD based on the discrete Hankel singular value decomposition (SVD) coordinate is highly symmetrically structured, and is able to accurately obtain a linear representation of structural nonlinear vibration. The resulting linearized data-driven equation-free model can be used to accurately predict the responses of nonlinear systems with limited training data sets. [ABSTRACT FROM AUTHOR]

Polymers are one of the most popular materials for next-generation flexible sensing device fabrication due to their tunable mechanical and electrical properties. A series of prior research studies in the field of smart flexible and wearable sensing illustrates the potential of various polymer and composite materials to be applied in sensor development. In this direction, mechanical compliance plays a vital role as it ensures the stability and reliability of the fabricated sensor. Therefore, engineering mechanical compliance for the development of smart flexible solutions has emerged as a significant area of research. Furthermore, the usage of flexible sensing devices is rapidly increasing in the field of healthcare devices and robotic automation. This feature article summarizes the relevant contributions of the authors in the field of engineered polymers and composites for flexible sensor development with a focus on healthcare and physical sensing applications. We discuss the polymer and composite materials, their characteristics, fabrication technologies, finite element method analysis, and examples of flexible physical sensors, i.e. pressure, strain, and temperature sensors, for various wearable healthcare applications and robotic automation. Finally, we discuss examples of multi-sensory systems having flexible sensors. [ABSTRACT FROM AUTHOR]

The challenge for a non-linear vibration system in a fractal space is more fractal dimensions than frequency-amplitude relationship, the system energy consumption depends upon its fractal property, so its best-case scenario is to establish a relationship among the fractal dimensions, frequency and amplitude. For this purpose, this paper studies a fractal-fractional vibration system of a mass attached to a stretched elastic wire in a fractal space, and its asymptotic periodic property is elucidated, the effect of the fractal dimensions on the vibration system is discussed. This paper offers a new road to fast and reliable analysis of fractal oscillators with high accuracy. [ABSTRACT FROM AUTHOR]

Educators must conduct assessments in their learning; it determines students' weaknesses in the teaching material they follow during learning. Unfortunately, the implementation of assessment by educators was not optimal, and the weakness was that the existing assessment method was only fixated on assessing students without providing feedback on the assessment. At the same time, this feedback was essential for students in learning, which can help learners assess performances that cannot be seen and felt by themselves, as well as a tool to motivate students, notification or information, and reinforcement. Therefore, this research aimed to develop a Constructivist Feedback-Based Assessment Method for learning assessment. The method used in this research was Research and Development (R&D). After development, the Constructivist Feedback-Based Assessment Method for learning assessment will be implemented to see its effect on students' adaptive capacity, decision-making, problem-solving, and creativity skills. Independent sample t-test and linear regression analysis were used as data analysis techniques describing the impact of the assessment on those skills. The results showed that the Constructivist Feedback-Based Assessment Method has five stages: preparing the assessment material, diagnostic assessment, assessment for learning, assessment of learning, and reflection. It effectively affects students' skills, such as adaptive capacity, decision-making, problem-solving, and creativity. It can be concluded that the Constructivist Feedback-Based Assessment Method can improve students' adaptive capacity, decision-making, problem-solving, and creativity. Novelty in this research was the existence of constructivism integrated into feedback-based assessment, which the existing assessment has not highlighted the constructivist side of assessment. [ABSTRACT FROM AUTHOR]

Diatoms captivate both biologists and engineers with their remarkable mechanical properties and lightweight design principles inherent in their shells. Recent studies have indicated that diatom frustules possess optimized shapes that align with vibrational modes, suggesting an inherent adaptation to vibratory loads. The mode shape adaptation method is known to significantly alter eigenfrequencies of 1D and 2D structures to prevent undesired vibration amplitudes. Leveraging this insight, the diatom-inspired approach to deform structures according to mode shapes was extended to different complex 3D structures, demonstrating a significant enhancement in eigenfrequencies with distinct mode shapes. Through extensive parameter studies, frequency increases exceeding 200% were obtained, showcasing the method's effectiveness. In the second study part, the studied method was integrated into a user-friendly, low-code software facilitating swift and automated structural adjustments for eigenfrequency optimization. The created software tools, encompassing various components, were successfully tested on the example structures demonstrating the versatility and practicality of implementing biomimetic strategies in engineering designs. Thus, the present investigation does not only highlight the noteworthiness of the structural adaptation method inspired by diatoms in maximizing eigenfrequencies, but also originate software tools permitting different users to easily apply the method to distinct structures that have to be optimized, e.g., lightweight structures in the mobility or aerospace industry that are susceptible toward vibrations. [ABSTRACT FROM AUTHOR]

This paper proposes a method of using machine learning and an evolutionary algorithm to solve the flexible job shop problem (FJSP). Specifically, a back propagation (BP) neural network is used as the machine learning method, the most widely used genetic algorithm (GA) is employed as the optimized object to address the machine-selection sub-problem of the FJSP, and particle swarm optimization (PSO) is utilized to solve the operation-order sub-problem of the FJSP. At present, evolutionary algorithms such as the GA, PSO, ant colony algorithm, simulated annealing algorithm, and their optimization algorithms are widely used to solve the FJSP; however, none of them optimizes the initial solutions. Because each of these algorithms only focuses on solving a single FJSP, they can only use randomly generated initial solutions and cannot determine whether the initial solutions are good or bad. Based on these standard evolutionary algorithms and their optimized versions, the JSON object was introduced in this study to cluster and reconstruct FJSPs such that the machine learning strategies can be used to optimize the initial solutions. Specifically, the BP neural networks are trained so that the generalization of BP neural networks can be used to judge whether the initial solutions of the FJSPs are good or bad. This approach enables the bad solutions to be filtered out and the good solutions to be maintained as the initial solutions. Extensive experiments were performed to test the proposed algorithm. They demonstrated that it was feasible and effective. The contribution of this approach consists of reconstructing the mathematical model of the FJSP so that machine learning strategies can be introduced to optimize the algorithms for the FJSP. This approach seems to be a new direction for introducing more interesting machine learning methodologies to solve the FJSP. [ABSTRACT FROM AUTHOR]

This study introduces an immersed boundary (IB) method based on coefficient array transformations of discrete equations for local cells and local flow pattern reconstruction, for the simulation of turbulent flow and combustion chemistry inside combustors with complex structure. This IB method is combined with a geometric scanning algorithm that traverses each fluid grid point in the vicinity of the wall, and based on the exact wall positions and normal vectors obtained from the scanning, the coefficient matrices of the individual grid points and their discrete forms of the governing equations are transformed, and the boundary conditions are added implicitly and exactly. The effectiveness of the method is validated through simulations of a cylinder, a gas turbine model combustor [Meier et al., "Spray and flame structure of a generic injector at aeroengine conditions," in Proceedings of the ASME 2011 Turbo Expo: Power for Land, Sea, and Air (American Society of Mechanical Engineers, 2011), pp. 61–72 and Freitag et al., "Measurement of initial conditions of a kerosene spray from a generic aeroengine injector at elevated pressure," Atomization Sprays 21, 521 (2011)], and a specific aero-engine combustor, demonstrating precision comparable to traditional body-fitted mesh approaches, especially for complex combustor structures. The simulation demonstrates that the IB method achieves accuracy comparable to a fitted grid when it provides boundary information of similar quality and detail for control equations. The locally reconstructed IB method introduced in this paper successfully delivers high-precision boundary conditions, making it valuable for practical engineering applications. [ABSTRACT FROM AUTHOR]

A compact fiber-optical curvature sensor based on the hollow-core fiber (HCF) assisted microbubble Mach–Zehnder interferometer (HMZI) is proposed and experimentally demonstrated. Transmission spectral characteristics of the proposed curvature sensor have been investigated with a maximum intensity-interrogated sensitivity of − 1.48 dB/m−1 in a curvature range from 1.22 m−1 to 3.46 m−1. The temperature-induced instability is measured below 0.30 dB in a large temperature range of 35 °C to 60 °C, suggesting a good temperature resistance performance. The overall sensing size is controlled to be around 600 μm. Hence, the HMZI curvature sensor has several desirable merits such as wide measurement range, temperature insensitivity, and ease of integration, which make it a promising candidate in curvature-related mechanical engineering and structural health monitoring applications. [ABSTRACT FROM AUTHOR]

This study delves into the convergence of operators and the viscoelastic properties of fractal ladder and tree structures. It proves the convergence of fractal stiffness operators through operator algebra, revealing a fundamental connection between operator sequence limits and fractal operator algebraic equations. Our findings demonstrate that, as the hierarchical levels of these structures increase, their viscoelastic responses increasingly align with the fractional viscoelastic behavior observed in infinite-level fractal structures. We explore the similarity in creep and relaxation behaviors between fractal ladders and trees, emphasizing the emergence of ultra-long characteristic times in steady-state creep and pronounced tailing effects in relaxation curves. This research provides novel insights into the design of fractional-order viscoelastic structures, presenting significant implications for materials science and mechanical engineering. [ABSTRACT FROM AUTHOR]

This paper aims to develop an integrated Quality–Cost–Environmental (QCE) indicator for the selection of photovoltaic panels (PVps) offered to customers, considering the following criteria: (i) quality satisfaction; (ii) cost-effectiveness; and (iii) environmental impact throughout the life cycle. The proposed QCE indicator was developed within a framework that incorporated an FAHP (Fuzzy Analytic Hierarchy Process), cost-effectiveness analysis (CEA), and life cycle assessment (LCA). The model test confirmed its effectiveness in choosing a PVp which combines environmental friendliness throughout its entire life cycle with satisfactory quality and a reasonable purchase price for customers. The proposed model can be utilized by individuals, businesses, and public entities for the selection of high-quality, cost-efficient, and environmentally friendly PVps—thereby promoting sustainable development. [ABSTRACT FROM AUTHOR]

The targeted improvement of design methods requires validation studies to record and evaluate difficulties in the application of the investigated methods. Current analysis methods for the validation of design methods are limited to the collection and evaluation of the design outcome and do not consider the applicability of the design method. In this paper, the authors evaluate an analysis method which, in addition to the benefits of a design method, also detects difficulties in its applicability. The Attention-Comprehension-Application-Performance analysis (ACAP analysis) method has been newly developed for this purpose. It investigates the applicability and captures metrics attention, comprehension, and correctness of application as well as the benefit of the design method. To evaluate the ACAP analysis method, a method for sheet metal design was examined in a laboratory study with 25 university students with mechanical engineering as their major subject. The results of the evaluation showed that the ACAP analysis method (1) identifies difficulties in the applicability of the design method; (2) determines the benefit of the design method; and (3) captures the impact of the identified difficulties on the benefit. Thus, the ACAP analysis method can evaluate causes of existing difficulties using objective metrics. [ABSTRACT FROM AUTHOR]

The purpose of the article is to analyse the manufacturing factors that affect the cost of manufacturing a part. Nowadays the cost of equipment used for metal 3D printing, as well as metal powders, are still very expensive. The cost of additive manufacturing of metal parts is mainly dependent on the volume of printing, therefore, reducing the volume of printing can lead to a significant reduction in the cost of manufacturing the part. Manufacturing of a metal shell, the cavity of which is filled with a cheap metal polymer, can be an excellent alternative to an all-metal part. The article provides a method for calculating the cost of manufacturing a lever part using various technologies: subtractive, additive, and composite part manufacturing technology. According to the calculated data, the dependence of the cost of manufacturing a part on piece time has been built, which can be interpreted as the amount of machining. The constructed linear dependence can give an idea of the effectiveness of the application of a particular technology for obtaining a part. In addition, non-economic factors affecting the possibility of using various technological processes for manufacturing a part are described. [ABSTRACT FROM AUTHOR]

Background: Engineering culture research to date has described the culture as rigid, chilly, and posing many barriers to entry. However, the COVID‐19 pandemic provided an important opportunity to explore how engineering culture responds to a major disruption. Purpose: The purposes of this study are to understand how elements of engineering culture emerged in mechanical engineering students' perceptions of their classroom experiences during the pandemic and how their experiences varied across two national contexts. Method: This qualitative comparative case study examines undergraduate mechanical engineering students' perceptions of their experiences taking courses during the pandemic at two universities—one in the United States and one in South Africa. Semistructured interviews were conducted across both sites with 21 students and contextualized with 3 faculty member interviews. Student interviews were analyzed using an iterative process of deductive coding, inductive coding, and pattern coding. Results: We identified two key themes that characterized participants' experiences during the pandemic: hardness and access to resources. We found that students at both sites experienced two types of hardness—intrinsic and constructed—and were more critical of constructed forms of hardness. We found that the South African university's response to facilitating student access to resources was viewed by students as more effective when compared with the US university. Conclusions: We found that hardness remained a central feature of engineering culture, based on student perceptions, and found that students expressed awareness of resource‐related differences. A key distinction emerged between intrinsic and constructed hardness. [ABSTRACT FROM AUTHOR]

Background: In taking up educational technology tools and student‐centered instructional practice, there is consensus that instructors consider the unique aspects of their instructional context. However, tool adoption success is often framed narrowly by numerical uptake rates or by conformity with non‐negotiable components. Purpose: We pursue an alternative ecosystems framing which posits that variability among contexts is fundamental to understanding instructors' uptake of instructional tools and the ways their teaching trajectories develop over time. Design/Method: Through a multiple‐case study approach using interviews, usage data, surveys, and records of community meetings, we examine 12 instructors' trajectories to illustrate the dynamic uptake of a technology tool. Results: Cross‐case analysis found that instructors' trajectories are tool‐mediated and community‐mediated. We present five cases in detail. Two foreground ways that instructors gained insight into student learning from student responses in the tool. Two illustrate the role played by the project's Community of Practice (CoP), an extra‐institutional support for deepening practice. The final case illustrates the complexity of an evolving instructional ecosystem and its role in instructors' satisfaction and continued use. Conclusions: Use of the educational technology tool perturbed ecosystems and supported instructors' evolving trajectories through mediation of instructor and student activity. Instructors' goals guided initial uptake, but both goals and practice were adapted using information from interactions with the tool and the CoP and changes in instructional contexts. The study confirms the need to understand the complexity of the uptake of innovations and illustrates opportunities for educators, developers, and administrators to enhance uptake and support diversity goals. [ABSTRACT FROM AUTHOR]

This study evaluates the performance of learning CNC machining in mechanical engineering degree programs by assessing students' mental workload (MWL). Both subjective (NASA-Task Load Index) and objective (increasing ratio of heart rate, IRH) evaluation methods were employed to assess the MWL of 46 students randomly assigned to two groups: a traditional training group and a combined simulation training group. The results demonstrate the significant impact of the training method on students' MWL. Specifically, the MWL and IHR values of the combined simulation training group were 54.3 and 9.2, respectively, while those of the traditional training group were 58.3 and 13.2. Additionally, the correlation analysis showed a significant correlation between the IHR value and the MWL score of NASA-TLX. These findings suggest that implementing simulated software and the combined simulation training method effectively reduces students' MWL, thereby promoting active knowledge acquisition. Consequently, students' MWL can be utilized to evaluate the effectiveness of technical education with the aim of enhancing training efficiency and quality. [ABSTRACT FROM AUTHOR]

Dump slope is mainly attributed to the deep excavation of a mine. In the present work, the dump in Kunyang phosphate mine located in Sanjia Village was investigated. The geographic and geologic settings were first studied according to the field investigation. Aiming at the actual dump scenario, a rainfall system was designed to simulate the process of dump instability induced by rainfall. The novelty lies in conducting comprehensive tests on fundamental parameters, including water content, particle size, compactness, and engineering mechanical properties, through analogous simulation experiments. In addition, the SLIDE software was adopted to analyse the dumps in each mining area and subsequently determine the sliding disaster mode of the dumps in Kunyang phosphate mine. The comparative analysis of the dumps in these different mining areas showed that the dump in No. 6 mining area has a greater factor of safety (FS) and better stability (instability will not occur). Secondly, the stability of the dumps in No. 2, No. 3 and No. 4 is better than that in No. 5, but they have not reached the ultimate equilibrium state (instability will not occur). Nevertheless, the FS of the dump in No. 1 mining area approached or even fell below 1. Thus, it is predicted that a small‐scale landslide disaster may have occurred (instability). Moreover, the dynamic evolution characteristics of dump disasters with different accumulation densities were revealed by model device tests. Finally, the obvious tube surge phenomenon before sliding was observed. [ABSTRACT FROM AUTHOR]

Adhesive bonding has been increasingly employed in multiple industrial applications. This has led to a large industrial demand for faster, simpler, and cheaper characterization methods that allow engineers to predict the mechanical behavior of an adhesive with numerical models. Currently, these characterization processes feature a wide variety of distinct standards, specimen configurations, and testing procedures and require deep knowhow of complex data-reduction schemes. By suggesting the creation of a new and integrated experimental tool for adhesive characterization, it becomes possible to address this problem in a faster and unified manner. In this work, following a previous numerical study, the mode I and II components of fracture-toughness characterization were validated experimentally in two different configurations, Balanced and Unbalanced. For mode I, it was demonstrated that both configurations presented similar numerical and experimental R-curves. The relative error against standard tests was lower than ±5% for the Balanced specimen; the Unbalanced system showed higher variations, which were predicted by the numerical results. Under mode II, the Balanced specimen displayed plastic deformation due to high deflections. On the contrary, the Unbalanced specimen did not show this effect and presented a relative error of approximately ±2%. Nonetheless, it was proven that this approach to obtain such data by using a single unified specimen is still feasible but needs further development to obtain with similar precision of standard tests. In the end, a conceptual change is proposed to solve the current mode II issues. [ABSTRACT FROM AUTHOR]

Finite element analysis has become an essential tool for simulating and understanding crack growth. This technique holds significant importance in the field of mechanical engineering, where it finds wide application in the design and optimization of structural components and material properties. This work began with the identification of critical zones and estimated the number of load life repeats through fatigue analysis, specifically applied to automotive rims utilizing innovative finite element methods. To investigate crack behavior, we are used the Extended Finite Element Method (XFEM) with the volumetric approach to compute the Stress Intensity Factor (SIF). The results obtained by our study align closely with experimental tests in terms of detecting the critical zone where a crack can appear. Our findings contribute to the understanding of fatigue behavior in automotive rims, offering new insights into their structural integrity and performance under various load conditions. [ABSTRACT FROM AUTHOR]

Infrared thermography has been under review in the last 30 years due to its versatility and potential in the detection of the thermal signature associated with intrinsic energy phenomena due to dissipative processes, specifically those relying on mechanical fatigue. Nowadays, it is a well‐established technique that can support mechanical and structural engineers to implement a damage‐tolerant design, assess the residual life, and finally characterize the fatigue behavior of materials. The aim of this work is to review all thermography‐based approaches and procedures for fatigue limit estimation by rapid tests, drawing considerations on the applicability of thermal methods in fatigue assessment of mechanical components, proposing the capabilities of different thermal indices in fatigue assessment, and discussing the pros and cons of each method as well as the open points. On one hand, this review intends to sum up what has already been done in the field; on the other hand, it provides a guideline to direct new researches toward issues that should be resolved or understood. [ABSTRACT FROM AUTHOR]

Ceramic aerogels are attractive for their promising applications in thermal insulation, ultrafiltration, catalysis, and many other areas, owing to their high porosity, low density, high specific surface area, low thermal conductivity, and thermal stability. However, the practical applications of conventional ceramic aerogels are usually impeded by brittleness. Resilient ceramic aerogels overcame the brittleness of conventional ceramic aerogels and realized reversible compressibility, but they usually show brittleness under tensile stress and limited load‐bearing ability. In this short review paper, we reviewed the strategies to modify the mechanical properties of resilient ceramic aerogel. These strategies were achieved through tuning the deformation and moving ability of the nanowire building blocks and the deformation resistance provided by the aerogel architecture. Perspectives for further modifying the mechanical properties of resilient ceramic aerogel are also discussed. [ABSTRACT FROM AUTHOR]

From connected sensors in soils, on animals or crops, and on drones, to various software and services that are available, "smart" technologies are changing the way farming is carried out. These technologies allow producers to look beyond what the eye can see by collecting non-traditional data and then using analytics tools to improve both food sustainability and profitability. "Smart Agriculture/farming" (SA) or "Digital Agriculture" (DA), often used interchangeably, refer to precision agriculture that is thus connected in a network of sensing and acting. It is a concept that employs modern information technologies, precision climate information, and crop/livestock developmental information to connect production variables to increase the quantity and quality of agricultural and food products. This is achieved by measuring and analyzing variables accurately, feeding the information into the cloud from edge devices, extracting trends from the various data, and subsequently providing information back to the producer in a timely manner. Smart agriculture covers many disciplines, including biology, mechanical engineering, automation, machine learning, artificial intelligence, and information technology-digital platforms. Minimum standards have been proposed for stakeholders with the aim to move toward this highly anticipated and ever-changing revolution. These foundational standards encompass the following general categories, including precise articulation of objectives, and baseline standards for the Internet of Things (IoT), including network infrastructure (e.g., stable 4G or 5G networks or a wireless local area network (WLAN) are available to end users). To sum up, SA aims to improve production efficiency, enhance the quality and quantity of agricultural products, reduce costs, and improve the environmental footprint of the industry. SA's ecosystem should be industry self-governed and collaboratively financed. SA stakeholders and end-users' facilities should meet standard equipment requirements, such as sensor accuracy, end data collectors, relevant industry compliant software, and trusted data analytics. The SA user is willing to be part of the SA ecosystem. This short perspective aims to summarize digital/smart agriculture concept in plain language. [ABSTRACT FROM AUTHOR]

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]

This document is an introduction to a special issue of the journal Foundations of Science. The special issue focuses on the field of History of Mechanism and Machine Science (MMS) and includes papers presented at the Seventh International Symposium on History of Machines and Mechanisms. The papers cover a wide range of topics related to the history of machine and mechanism science, such as nomograms, Spanish artifacts, water lifting machines, belt conveyors, mechanical engineering in the Americas, harmonographs, pulley systems, robots, stamp mills, and machinery. The articles provide historical context, analyze important phenomena, and discuss theoretical and practical achievements in the field. The special issue aims to promote recent advances and developments in the history of MMS. [Extracted from the article]

This work is the extended version of a paper presented at the conference HMM2021, about the history of mechanical engineering. First, the initial cultural and industrial steps in the robotic field in Japan are introduced, to display the beginning of this interlaced path, before WW2; then, in the context of the aftermaths of the war, some famous anime heroes are presented as ancestors of the coming mecha anime series. The rising research in the field of robotics and more generally the developments of contemporary Japanese automation industry are then drawn, as a technological substrate for mecha conception. In particular, Masahiro Mori studies are taken into consideration to identify an actual robot design pattern to apply to the following comparative description and examination of the different mecha; finally, thanks to this analysis, the common breeding ground whence robotics and mecha (and their reciprocal influences) arise, is outlined. [ABSTRACT FROM AUTHOR]

Computing formulae and solving equations are essential elements of scientific analysis. While today digital tools are almost always applied, analog computing is a rich part of the larger history of science and technology. Graphical methods are an integral element of computing history and still find some use today. This paper presents the history of nomograms, a historically-relevant tool for solving mathematical problems in various branches of science and engineering; in particular, we consider their role in mechanical engineering, especially for education, and discuss their mathematical properties. Each nomogram is a graphical description of a specific mathematical equation, designed such that the solution can be found through a simple geometric construction that can be performed with a straightedge. By design, using nomograms requires little skills and can be done even in adverse environments; a solution of sufficient accuracy for most purposes can then be found in a very short time. Another important advantage of nomograms is that they offer clear insight on the relationships between the variables, an insight which can be lost by looking at a complex equation. First introduced in the late 19 th century, nomograms were used by engineers and scientists due to their speed with respect to manual calculations, before being superseded by computers. While now mostly obsolete in practice, nomograms can still prove useful in workshops and teaching classes: we thus also discuss their educational applications and present a few original examples. [ABSTRACT FROM AUTHOR]

Companies' green competitive advantages result from the high coordination of economic, ecological, social and corporate subsystems. Thus, it is important to investigate the influence and coupling coordination degree (CCD) of the relevant components of green competitiveness. This paper justifies the relationship between green competitiveness and the coupling degree of its components. It hypothesizes that the increasing integrated index of companies' green competitiveness was determined by levels of coordination and communication between its components. The study applies the CCD model and correlation analysis to test the hypothesis. The objects of analysis were enterprises represented by three economic sectors: agro-industrial, mechanical engineering and food. The findings show that the highest coupling coordination degree among all components is represented by the companies with the highest green competitive index. These companies are characterized by the dominance of corporate components, which can increase the general level of green competitive advantages in various combinations with other determinants. [ABSTRACT FROM AUTHOR]

The advancement of quality and environmentally sustainable materials and products made from them has improved significantly over the last few years. However, a research gap is the lack of a developed model that allows for the simultaneous analysis of quality and environmental criteria in the life-cycle assessment (LCA) for the selection of materials in newly designed products. Therefore, the objective of the research was to develop a model that supports the prediction of the environmental impact and expected quality of materials and products made from them according to the design solution scenarios considering their LCA. The model implements the GRA method and environmental impact analysis according to the LCA based on ISO 14040. The model test was carried out for light passenger vehicles of BEV with a lithium-ion battery (LiFePO4) and for ICEV. The results indicated a relatively comparable level of quality, but in the case of the environmental impact throughout the life-cycle, the predominant amount of CO2 emissions in the use phase for combustion vehicles. The originality of the developed model to create scenarios of design solutions is created according to which the optimal direction of their development in terms of quality and environment throughout LCA can be predicted. [ABSTRACT FROM AUTHOR]

Flexible scaffolds made of polycaprolactone (PCL), and multi-walled carbon nanotubes (MWCNTs) were created and chemically verified through RAMAN. The most suitable coupling percentages for PCL were 1%, 3%, and 5% MWCNT. The scaffolds were very stable with high hardness values (10–12 GPa). The PCL/MWCNT 5% scaffold was the most flexible and least resistant, with adequate porosity, pore size, and interconnectivity for cell anchoring. Moreover, the scaffold exhibited low cytotoxicity with a cell viability of 90%. These flexible PCL/MWCNT scaffolds were developed to support tissue engineering by providing a mechanical response with flexibility and elasticity like the surrounding tissue. [ABSTRACT FROM AUTHOR]

Functionally graded materials have broad engineering applications including mechanical engineering, electronics, chemistry, and biomedical engineering. One notable advantage of such materials is that their stiffness distribution can be optimized to avoid stress concentration. A novel approach for solving the equations describing the longitudinal vibration of functionally graded rods with viscous and elastic boundary conditions is proposed. The characteristic equation of the system is derived for the solution of the undamped case for the constant stiffness rod. Then, a homotopy method is applied to compute the eigenvalues and mode shapes of graded rods for viscoelastic boundary conditions. The changes of the eigenvalues and mode shapes as function of the damping parameters are investigated. The optimal damping of the system is computed. It is shown that the qualitative behavior depends on the relation between the actual damping and the optimal damping of the system. The energy density distribution of graded rods is also discussed. An energy measure, the mean scaled energy density distribution is introduced to characterize the energy distribution along the rod in the asymptotic time limit. The significance of such a measure is that it reveals how the energy tends to distribute along the rod. It is shown that the energy distribution can be manipulated by changing the damping parameters. Qualitative changes depending on the relation between the actual damping and the optimal damping are highlighted. [ABSTRACT FROM AUTHOR]

This study analyses a cold-forged gear blank failure that was reported by the industry. In cold forged metal, the damage is seen as fissures running parallel to the thickness direction. Visual inspection, composition analysis, hardness, microstructure, residual stress measurement, and non-destructive testing like magnetic particle inspection, ultrasonic detection, and radiographic tests were performed and analyzed to investigate the problem. The thorough research found that the crack appeared during the material's evolution's earliest stages and acceptance standards. The same has been discussed with the end user to ascertain that this type of failure should not occur again. The objectives, methods, and anticipated results of the study are briefly summarised in the abstract. The project intends to provide significant insights to the field of mechanical engineering, leading future developments in gear design, manufacture, and performance optimisation by a thorough analysis of the failure evaluation of a gear blank. The significance of this investigation is due to its ability to improve the design and production of gear blanks and related components. Engineers and designers can improve the material choice, manufacturing processes, and operational circumstances by identifying the primary reasons of failure and comprehending the crucial aspects that caused the malfunction. As a result, gear systems may perform better, last longer, and be more reliable in a variety of applications. [ABSTRACT FROM AUTHOR]

In many mechanical systems, it is very common to bring together different structural elements or subsystems produced by different producers and create a whole coupled system. It is often not possible to manufacture an entire mechanical system in one place. Although the dynamic properties of each of the subsystems produced by different manufacturers are known, it is a matter that should be known and studied how the dynamic behavior of the new system will be after the creation of a new system by combining these subsystems. In this study, a method for structural coupling of mechanical systems is presented in order to contribute to the solution of structural dynamic problems. It is based on Sherman–Morrison formula known for solving mathematical inverse problems of modified matrices. The method is very useful and practical for real mechanical engineering applications due to only the frequency response functions belong to the coupling coordinates of the subsystems are used. The main highlight of the presented method is there is no need a matrix inversion for calculations. [ABSTRACT FROM AUTHOR]

• The failure modes of mechanical on-load tap-changer are analyzed. • Time-dependent reliability method for multiple failure modes is proposed. • The truncation moment is introduced to solve the time-dependent system reliability. • The method's effectiveness and efficiency are validated by previous methods. To regulate voltage level, the mechanical on-load tap-changer is a crucial series system of the ultra-high-voltage converter transformer. Whether its motion is reliable throughout the whole process is vital for the safe operation of converter transformer. Therefore, the time-dependent system reliability analysis is carried on for the mechanical on-load tap-changer with multiple failure modes based on the first-passage method. First, the failure modes of the mechanical on-load tap-changer are comprehensively analyzed according to the safety requirement, and then, the output error of each failure mode related to the moving mechanism of the system is modeled based on the motion equation to establish the varied limit-state functions of the time intervals over the whole motion. Then, the first-passage method is leveraged to solve this time-dependent reliability problem with multiple failure modes, in which the analytical formula of the outcrossing rate, the crucial element of the first-passage method, is derived by introducing the first-order moment of the doubly truncated multivariate Gaussian distribution. On this basis, the time-dependent system kinematic reliability is calculated using the Simpson integration algorithm. Finally, a numerical case is studied first, and in what follows, the practical engineering application to the mechanical on-load tap-changer is showcased in detail to demonstrate the effectiveness and efficiency of the proposed method by comparison with previous methods. [ABSTRACT FROM AUTHOR]

Growing evidence has underscored the importance of female students' relationships and interactions in Science, Technology, Engineering, and Mathematics (STEM) programs as crucial factors influencing their thriving within these programs. However, the discourse has seen a dearth of literature, especially in low-middle-income countries where deep-rooted cultural norms and values may complicate female students' interactions and relationships with their peers (male students and female colleagues). Drawing on a phenomenological approach, we engaged female students in Mechanical Engineering at a Ghanaian university to share their experiences studying in such a hardcore male-dominated space with a focus on how they interact and relate with their peers. Data from participants were analyzed thematically using NVivo. Female students who participated in the study revealed that the daily interactions with their peers reinforced gendered norms, illuminating male students' superiority in the program. Female students further asserted that the support from their male counterparts influenced their apathetic attitudes towards their female colleagues because they felt they had nothing to offer them academically, financially, and socially in the program. We argue the need to alter the perception of female students and promote a sense of relationship among them through seminars and support from women in STEM occupations. [ABSTRACT FROM AUTHOR]

Having the distinction of being one of the most extensively employed piezoelectric ceramic materials worldwide and multi-faceted, lead zirconate titanate (PZT) has numerous applications and characteristics. In 1954, a remarkable discovery happened at the Tokyo Institute of Technology, which was the development of PZT. Due to its excellent dielectric constant, piezoelectric value, polarization, high Curie temperature, and flexibility, it has been widely used in the field of mechanical engineering, along with other branches of sciences. The main interest of this review article is to describe the significance and involvement of PZT in the field of mechanical engineering. This article starts with a brief review of the history of PZT, after that different synthesis methods, and applications of PZT in relevance to the field of mechanical engineering have been discussed. Finally, this article concludes with the future scope of PZT in the field of mechanical engineering. [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]