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This paper explores the artificial intelligence (AI) concept for complex engineering design processes in the shipping industry. It is driven by the computer technologies advancement for fast and concurrent tasks processing, machine learnability, and data-centric approach. While AI has been adopted in many industries, it is still lacking the structured approaches for practical implementation. This is especially on the generality of the methodologies and explaining AI to the non-technical members and their preparedness. Therefore, this work proposed a conceptual framework to systematically extract, represent and visualize the ship design knowledge, to develop and deploy the machine learning (ML) models, and to demonstrate the AI-based ship design processes. Comparisons to the generic ship design model were made and discussed to highlight the improvements observed. It is found that while the conventional algorithmic approach procedures were faster in terms of execution time, the stepwise empirical models were often limited by the dataset and the design assumptions with restricted estimation capabilities for solving the nonlinear ship design problems. The findings presented the impact in improving the existing processes and effectively reducing its cycle. Additionally, the approach emphasised on the validated ship design data thus its generalization for fast and wide adoptions at scales. [ABSTRACT FROM AUTHOR]

The Garden in Motion is a concept that was developed by Gilles Clément in the early 1980s as the result of the experimentation conducted in his garden-house, La Vallée. Clément’s interest in promoting this garden archetype based on managing neglected land led him to write a number of works in order to explain the conceptual underpinnings of his model, with the ultimate aim of having them published. From the writing of the first manuscripts, dating from 1984, to the first edition of “Le jardin en movement” in 1991, he produced a series of different documents that would form the basis of the text that was finally published. It was a long process in which Clément not only had to fully develop his ideas but also to overcome the difficulties involved in finding a company to publish what he called his ‘petit livre’. The aim of this article is to show the creative process behind Clément’s book and its relationship with the creative process of building his garden, while endeavouring to reply to the question of whether it is possible to establish an equivalence between both processes. This is made possible through the analysis of documents kept by Clément in his personal archive, some of which have never been published.

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]

Lluny d'emprar el terme transmèdia com un simple adjectiu que pot qualificar a certs substantius, actualment es pot considerar la transmedialitat com una veritable manera d'executar projectes abordant la complexitat de l'escenari mediàtic contemporani. L'objectiu d'aquest treball és definir la disciplina de Disseny Transmèdia mitjançant la descripció de les activitats de projecte i d'investigació desenvolupades en el Politècnic de Milà, amb especial atenció al projecte Plug Social TV. Plug Social TV és un projecte posat en marxa el 2013 en dos barris perifèrics de la ciutat de Milà amb la participació dels estudiants del curs de Disseny de Comunicació, dirigits per l'equip d'investigació Imagis Lab. L'objectiu principal del projecte és experimentar els processos i els instruments de comunicació que, a través de la construcció de mons narratius i la seva distribució estratègica i multicanal (analògica i digital), poden suportar la formació d'un diàleg entre els interessats presents en el territori.

The paper presents aspects regarding the structure, themes and content of graduation papers in the specialization of Industrial Design within Petru Maior University of Târgu Mures.

Tot producte està pensat perquè es vengui a nombrosos consumidors potencials; per això, les responsabilitats associades a aquest procés són grans. Els compromisos mediambientals, socials i ètics dels dissenyadors industrials estan establint principis universals en un esforç comú per fomentar una societat sostenible i més harmoniosa.

En aquest món en constant evolució, els objectes "intel.ligents" (amb tecnologia incrustada) han envaït la nostra vida quotidiana. Aquestes superfícies intel.ligents que emeten llum poden crear ambients o assistents de navegació de l'espai interior, a la vegada que ofereixen als dissenyadors opcions d'il.luminació sostenibles i flexibles. Quin efecte té la interacció amb aquestes superfícies il.luminades en l'experiència personal que es té dels ambients interiors?.

Paper-based analytical devices (PADs) are very popular for point-of-care diagnostics, which provide a fast, cost-effective and possible multiplexed detection of a spectrum of molecules. They have been matching forward proudly to contribute to the modern analytical science and life science. Accompanying with their advantages and huge potentials, low detection sensitivity is continuing to challenge the application of PADs from bench to bedside. In order to improve the sensitivity and enhance the signal readout, variable signal amplification strategies have been investigated and applied for PADs. In this review, we have firstly classified formats of PADs according to the engineering design. Advances for improving sensitivity of PADs in recent five years are then summarised according to three popular types of signal amplification strategies (nanomaterial based, nucleic acid based, and engineering of PADs based). Pros and cons of each signal amplification approach have been discussed accordingly. Finally, the future perspectives of PADs are proposed. • Advances on signal amplification strategies to enhance sensitivity of paper based analytical devices (PADs) are outlined. • Three signal amplification strategies (nanomaterial, nucleic acid, and engineering of PADs based) are discussed. • The pros and cons of different signal amplification strategies are compared. • Future perspectives for signal amplification on PADs are proposed. [ABSTRACT FROM AUTHOR]

[Display omitted] • Robust probe is designed by engineering biomimic MOFs with specific pockets. • The probe gives "key-lock" identification and sensitive quantitative information. • Innovatively integrating the probe with filter paper could avoid ring-like deposit. • The well-distributed interface is harvested to reduce colorimetric signal fluctuation. • Self-adaptive signal model allows for monitoring pesticide in colored matrices. Excessive residual pesticides have raised overall environmental damage and health hazard issues, thus the development of facile and sensitive means for pesticide monitoring in different environmental field is desperately needed but challenging. In this work, a flexible paper-based colorimetry beating coffee-ring effect is achieved toward sensing environmental pesticide exposure in user-friendly mode. First, to circumvent poor performance of biomolecules, robust probe is designed by imprinting metal-organic frameworks (MOFs) with specific pockets, enabling to provide "key-lock" identification and sensitive quantitative information under harsh environment. Innovatively, integrating the MOF-mediated probe with filter paper, a well-distributed sensing interface is harvested to reduce colorimetric signal fluctuation for reliable detection properties, which is ascribed to superior wetting behavior of filter paper for avoiding ring-like deposit formation. Additionally, the uniform profile is simulated by Fluent numerical software. Further exploiting smartphone-assisted image acquisition and self-adaptive signal model, the simple-to-perform system exhibits good accuracy toward ppb-level thiacloprid free of colored background interference. A low limit of detection of 0.04 μM thiacloprid (corresponding to 0.01 μg g−1 by weight) is achieved. Moreover, it allows for in-filed monitoring thiacloprid exposure in agricultural wastewater, soil, fresh vegetables with satisfactory recoveries ranging from 92.7 % to 109.0 %, verifying the broad potential applications for point-of-use tracking of environmental pesticide and eventually bringing benefits to ecosystem protection in resource-deficient settings. [ABSTRACT FROM AUTHOR]

This Special Issue on "Selected Papers from IEEE ICASI 2018" includes excellent papers presented at the IEEE ICASI 2018 regarding the "applied system innovation" topic. Mechanical engineering and design innovations are both academic and practical engineering fields, which involve systematic technological materialization through scientific principles and engineering designs. Technological innovations in mechanical engineering include IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanosciences and nanotechnology. The aim is to encourage the attendees at the IEEE ICASI 2018 to publish their experimental and theoretical research relating to applied system innovation. [ABSTRACT FROM AUTHOR]

Digital twin technology assists physical entities better to achieve functional perfection through the interactive cointegration of physical entities and virtual spaces. In this view, this paper proposes a digital twin inspired intelligent diagnosis method for bearing faults based on adaptive correlation filtering and an improved stack autoencoder (SAE) classification model. First, the adaptive correlation filtering algorithm is designed to filter the engineering signal in physical space, in which the noise-free ideal bearing fault signal spectrum in the virtual space is used as the comparison. In this filtering, the optimal cut-off frequency is determined adaptively with the condition that the similarity between the simulated spectrum and the engineering spectrum is maximized. Second, the Tan activation function is used in the SAE classification model to enhance the signal differentiation and avoid the problem of large computation of the traditional sigmoid function. Finally, the accuracy of the method in this study is verified on the basis of engineering experiments and Case Western Reserve University bearing fault dataset. Experimental results show that the method can achieve 100% correct diagnosis rate of bearing faults. [ABSTRACT FROM AUTHOR]

The editor reflects on the special issue of the periodical which is based on the 2012 International Microwave Symposium held on June 17-22, 2012 in Montreal, Quebec. He mentions that due to increased number of submissions to the special issue, it has been divided into two issues the first one was published in December 2012, and the next one in January 2013. He adds that the aim behind including conference papers in the issue is to present results that might help improve engineering designs.

The accurate characterization of typhoon wind profile properties is of great importance in the field of wind engineering and wind design of high-rise structures. In this paper, the average typhoon wind profile characteristics are investigated using the 930 m height measurement data of Typhoon Lekima 2019 obtained from the observations of the mobile acoustic profiling radar deployed in the coastal area. Specifically, this paper adopts a cohesive hierarchical cluster analysis method to classify the mean wind profiles of Super Typhoon Lekima 2019, and the optimal number of clusters is obtained as two classes by the profile coefficient with the sum of squares of clustering errors, the Calinski–Harabasz index, and the Davies–Bouldin index, and the two classes of typical wind profiles are named as cluster 1 type and cluster 2 type. The model fitting analysis of the two types of typical wind profiles was carried out in the height range of 0~300 m after classification, and the effects of fitting the cluster 1-type mean wind profiles with the Vickery model and the Snaiki and Wu model and the cluster 2-type mean wind profiles with the Power-law model, the Log-law model, and the Deaves–Harris and Gryning models were discussed. The results show that the cohesive hierarchical cluster analysis method used in this paper can effectively categorize the mean typhoon profiles. In addition, this paper has some reference significance for future research on the characteristics of measured typhoon wind profiles and engineering applications such as the wind-resistant design of high-rise structures. [ABSTRACT FROM AUTHOR]

Abstract: This article uses lightweight J2EE tools based on B/S architecture to design an auto-generated paper management system. This system includes several modules, namely: user management, subject management, classification management, question entry, question management, paper generation, and paper management. The design process performs the analysis and composes the examination paper using an efficient algorithm with a high possibility of success. With this algorithm, the user needs to identify the subject, the question type and the difficulty level. From this input, the examination paper will be generated automatically. On the basis of a study of the JSP and Microsoft Word interface, we find that the system combines with Word very well. Therefore the editing of questions and answers is performed using Word and the final paper may be stored as “.doc” files. The system has characteristics such as easy operation, a good interface, good usability, high security, high stability, and reliability. [Copyright &y& Elsevier]

With the rapid advancement of digital technology, three-dimensional designs of Grid Information Models (GIMs) are increasingly applied in the power industry. Addressing the challenges of extracting key parameters during the GIM's process for power grid equipment, this paper explores an innovative approach that integrates artificial intelligence with image recognition technologies into power design engineering. The traditional methods of "template matching, feature extraction and classification, and symbol recognition" have enabled the automated processing of electrical grid equipment engineering drawings, allowing for the extraction of key information related to grid equipment. However, these methods still rely on manually designed and selected feature regions, which limits their potential for achieving full automation. This study introduces an optimized algorithm that combines enhanced Convolutional Neural Networks (CNNs) with Depth-First Search (DFS) strategies, and is specifically designed for the automated extraction of crucial GIM parameters from power grid equipment. Implemented on the design schematics of power engineering projects, this algorithm utilizes an improved CNN to precisely identify component symbols on schematics, and continues to extract text data associated with these symbols. Utilizing a scene text detector, the text data are matched with corresponding component symbols. Finally, the DFS strategy is applied to identify connections between these component symbols in the diagram, thus facilitating the automatic extraction of key GIM parameters. Experimental results demonstrate that this optimized algorithm can accurately identify basic GIM parameters, providing technical support for the automated extraction of parameters using the GIM. This study's recognition accuracy is 91.31%, while a traditional CNN achieves 71.23% and a Faster R-CNN achieves 89.59%. Compared to existing research, the main innovation of this paper lies in the application of the combined enhanced CNN and DFS strategies for the extraction of GIM parameters in the power industry. This method not only improves the accuracy of parameter extraction but also significantly enhances processing speed, enabling the rapid and effective identification and extraction of critical information in complex power design environments. Moreover, the automated process reduces manual intervention, offering a novel solution in the field of power design. These features make this research broadly applicable and of significant practical value in the construction and maintenance of smart grids. [ABSTRACT FROM AUTHOR]

Torsional oscillations greatly affect performance and. determine the bandwidth (BW) and damping of speed loops. Backlash due to gear reducers can also contribute to the triggering of oscillations, especially when the drive runs at very low load torque. This paper presents a detailed evaluation of these effects in typical electromechanical drive trains applied to paper machine sections. The cases evaluated consider torsional oscillations in two-mass and three-mass systems, and the effect of shaft diameter and length on the resonant frequencies of three typical paper machine sections. Time-domain response plots are evaluated to show the effect of speed response overshoot, reducer backlash, and step or ramp speed commands. Based on these results, mechanical design guidelines are given for the most significant drive train components in order to minimize torsional oscillations of the speed-controlled drive system. [ABSTRACT FROM AUTHOR]

Calls for papers for several conferences on engineering design and management in 2001.

The setting of parameter values will directly affect the performance of the neural network, and the manual parameter tuning speed is slow, and it is difficult to find the optimal combination of parameters. Based on this, this paper applies the improved Hunger Games search algorithm to find the optimal value of neural network parameters adaptively, and proposes an ATHGS-GoogleNet model. Firstly, adaptive weights and chaos mapping were integrated into the hunger search algorithm to construct a new algorithm, ATHGS. Secondly, the improved ATHGS algorithm was used to optimize the parameters of GoogleNet to construct a new model, ATHGS-GoogleNet. Finally, in order to verify the effectiveness of the proposed algorithm ATHGS and the model ATHGS-GoogleNet, a comparative experiment was set up. Experimental results show that the proposed algorithm ATHGS shows the best optimization performance in the three engineering experimental designs, and the accuracy of the proposed model ATHGS-GoogleNet reaches 98.1%, the sensitivity reaches 100%, and the precision reaches 99.5%. [ABSTRACT FROM AUTHOR]

Topology optimization focuses on the conceptual design of structures, characterized by a large optimization space and a significant impact on structural performance, and has been widely applied in industrial fields such as aviation and aerospace. However, most topology optimization methods prioritize structural stiffness and often overlook stress levels, which are critical factors in engineering design. In recent years, explicit topology optimization methods have been extensively developed due to their ability to produce clear boundaries and their compatibility with CAD/CAE systems. Nevertheless, research on incorporating stress constraints within the explicit topology optimization framework remains scarce. This paper is dedicated to investigating stress constraints within the explicit topology optimization framework. Due to the clear boundaries and absence of intermediate density elements in the explicit topology optimization framework, this approach avoids the challenge of stress calculation for intermediate density elements encountered in the traditional density method. This provides a natural advantage in solving topology optimization problems considering stress constraints, resulting in more accurate stress calculations. Compared with existing approaches, this paper proposes a novel component topology description function that enhances the deformability of components, improving the representation of geometric boundaries. The lower-bound Kreisselmeier–Steinhauser aggregation function is employed to manage the stress constraint, reducing the solution scale and computational burden. The effectiveness of the proposed method is demonstrated through two classic examples of topology optimization. [ABSTRACT FROM AUTHOR]

Soft robots present resilient and adaptable systems characterized by deformable bodies inspired by biological systems. In this paper, we comprehensively review existing design methods for soft robots. One unique feature of our review is that we first formulate criteria, which enables us to derive knowledge gaps and suggest future research directions to close these gaps and go further. Another distinctive feature of our review is that we pivot on the general engineering design process for soft robots. As such, we consider three criteria: (1) the availability of design requirements to start with the design of soft robots, (2) the availability of the so-called concept design or architecture design for soft robots, and (3) the systematic process that leads to the final design of soft robots. The review is conducted systematically, especially when searching for and selecting relevant publications in the literature. The main contribution of this review includes (i) identifying knowledge gaps and (ii) suggesting future research directions to close these gaps and go further. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT), big data, and machine learning (ML) has pioneered a transformation across several fields. Equipping electrical engineering students to remain abreast of the dynamic technological landscape is vital. This underscores the necessity for an educational tool that can be integrated into electrical engineering curricula to offer a practical way of learning the concepts and the integration of IoT, big data, and ML. Thus, this paper offers the IoT-Edu-ML-Stream open-source platform, a graphical user interface (GUI)-based emulation software tool to help electrical engineering students design and emulate IoT-based use cases with big data analytics. The tool supports the emulation or the actual connectivity of a large number of IoT devices. The emulated devices can generate realistic correlated IoT data and stream it via the message queuing telemetry transport (MQTT) protocol to a big data platform. The tool allows students to design ML models with different algorithms for their chosen use cases and train them for decision-making based on the streamed data. Moreover, the paper proposes learning outcomes to be targeted when integrating the tool into an electrical engineering curriculum. The tool is evaluated using a comprehensive survey. The survey results show that the students gained significant knowledge about IoT concepts after using the tool, even though many of them already had prior knowledge of IoT. The results also indicate that the tool noticeably improved the students' practical skills in designing real-world use cases and helped them understand fundamental machine learning analytics with an intuitive user interface. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic modeling method of motor driven electromechanical system is presented, and the uncertainty quantification of mechanism motion is investigated based on this method. The main contribution is to propose a novel mechanism-motor coupling dynamic modeling method, in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the system. The advantages of this include establishing intuitive coupling between the mechanism and motor, facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism, and enabling dynamic simulation with controller to take the randomness of the electric load into account. Dynamic simulation considering feedback control of ammunition delivery system is carried out, and the feasibility of the model is verified experimentally. Based on probability density evolution theory, we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty quantization. Our work can not only provide guidance for engineering design of ammunition delivery mechanism, but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the bearing capacity of cross-bracing in steel transmission tower structures. Design guidelines (ASCE 10-15, BS EN 50341-1, GB 50017-2017, and DL/T 5486-2020) related to the buckling capacity of the cross-bracing are summarized and compared with the experimental results. The current design provisions obtained the bearing capacity from the equivalent slenderness ratio, and then the stability coefficient and buckling capacity were derived. The calculated bearing capacity based on the design code tends to be overly progressive for smaller slenderness ratios (particularly those below 100), except for EN 50341-1-2012. Conversely, for larger slenderness ratios, ASCE 10-15 and DL/T 5486-2020 Class A design codes lean towards being overly progressive, while GB 50017-2017 and EN 50341-1-2012 codes tend to be more conservative. The design standard appears to exhibit unsafe predictions for Class A and B connections with low slenderness ratios and Class C connections. It needs to be noted that the effects of torsional stiffness and joint connection type are not considered in the current design codes, which are proved to be nonnegligible by the test results. In this paper, the bearing capacity calculation formula is proposed by introducing a modified effective length coefficient (K), and both the torsional stiffness and joint connection type are taken into account. The modified bearing capacity is verified with the test results; the correlation coefficient is 0.997, and the coefficient of variation is 0.04. It can provide a reference for the engineering design of steel lattice transmission tower structures. [ABSTRACT FROM AUTHOR]

Today's industrial processes use a variety of smart structure systems technologies. Various construction devices can significantly enhance a structure's ability to adapt to environmental changes. Smart structures are essential to the development of building technology. These forms of technologies are developing intelligent structural systems that behave like living systems and can perceive their environment. The objective of the research is to examine the connection of these professional systems, which become increasingly dependent over time. The research acknowledges and give emphasis to the significant role played by different types of systems (passive, semi-active, active, and hybrid) in formative the scope of construction through the analysis of novel techniques and innovative approaches. The paper state the assorted classification of smart structure schemes that have a significant role to serve the cycle life of the structure by reducing severe subjected damage to it. The study aims to investigate how these schemes of callings are inseparably connected, creating ever more advantageously as time goes on. The think about state and recognize the significant part of different categories of schemes (inactive, semi-active, active, and hybrid schemes) within the development scope through examination, unused methods and inventive strategies. The paper displayed the different categories of shrewd structure schemes that have a critical part to serve the cycle life of the structure by diminishing serious subjected harm to it.t. Furthermore, the research also demonstrated the smart structure's useful behavior, which is taken into account at every stage of the civil engineering design process. [ABSTRACT FROM AUTHOR]

Variable camber wing technology stands out as the most promising morphing technology currently available in green aviation. Despite the ongoing advancements in smart materials and compliant structures, they still fall short in terms of driving force, power, and speed, rendering mechanical structures based on kinematics the preferred choice for large long-range civilian aircraft. In line with this principle, this paper introduces a linkage-based variable camber trailing edge design approach. Covering coordinated design, internal skeleton design, flexible skin design, and drive structure design, the method leverages a two-dimensional supercritical airfoil to craft a seamless, continuous two-dimensional wing full-size variable camber trailing edge structure, boasting a 2.7 m span and 4.3 m chord. Given the significant changes in aerodynamic load direction, ground tests under cruise load utilize a tracking-loading system based on tape and lever. Results indicate that the designed single-degree-of-freedom Watt I mechanism and Stephenson III drive mechanism adeptly accommodate the slender trailing edge of the supercritical airfoil. Under a maximum cruise vertical aerodynamic load of 17,072 N, the structure meets strength requirements when deflected to 5°. The research in this paper can provide some insights into the engineering design of variable camber wings. [ABSTRACT FROM AUTHOR]

This document is an editorial published in the journal Frontiers in Physics, discussing advances in nonlinear systems and networks. Nonlinear systems have nonlinear relationships between input and output, and studying them is important for understanding natural phenomena and improving engineering design. The editorial highlights 10 articles in this research topic, covering various aspects of nonlinear systems and networks, including dynamic displacement estimation, complex propagation networks, representation learning, electricity scheduling, ternary logic gates, chaotic oscillators, vibration control, brain-like coupling synchronization, pinning synchronization, and medical image encryption. The authors emphasize the need for continuous advancement in the field and express gratitude to the authors, reviewers, editors, and staff involved in the publication. This document provides a valuable resource for researchers and library patrons interested in these areas of study. [Extracted from the article]

The introduction of a multi-population structure in differential evolution (DE) algorithm has been proven to be an effective way to achieve algorithm adaptation and multi-strategy integration. However, in existing studies, the mutation strategy selection of each subpopulation during execution is fixed, resulting in poor self-adaptation of subpopulations. To solve this problem, a dynamic multi-strategy integrated differential evolution algorithm based on reinforcement learning (RLDMDE) is proposed in this paper. By employing reinforcement learning, each subpopulation can adaptively select the mutation strategy according to the current environmental state (population diversity). Based on the population state, this paper proposes an individual dynamic migration strategy to "reward" or "punish" the population to avoid wasting individual computing resources. Furthermore, this paper applies two methods of good point set and random opposition-based learning (ROBL) in the population initialization stage to improve the quality of the initial solutions. Finally, to evaluate the performance of the RLDMDE algorithm, this paper selects two benchmark function sets, CEC2013 and CEC2017, and six engineering design problems for testing. The results demonstrate that the RLDMDE algorithm has good performance and strong competitiveness in solving optimization problems. [ABSTRACT FROM AUTHOR]

Optimization plays an important role in scientific and engineering research. This paper presents the effects of using the catenoidal shape to design the structure of a chimney cooling tower. The paper compares some geometrical variations of the catenoid with the reference existing hyperboloidal structure. It also compares internal forces, deformation and stability of the catenoidal structure. The comparison shows some predominance of the catenoid over the popular hyperboloid structure of the shell. The paper attempts to find an optimal shape of the cooling tower in order to reduce the amount of material and labor. The paper utilizes engineering tools and the designing process for chimney cooling towers. [ABSTRACT FROM AUTHOR]

During aircraft landing on water, the intense impact load may lead to significant local deformation of the fuselage skin. Ensuring the aircraft's integrity and reliability is of paramount importance. This paper investigates the fuselage skin's dynamic response during water entry. In the simulation of complex water entry problems, the smoothed particle hydrodynamics (SPH) method can fully leverage the advantages of the particle method. However, the traditional SPH method still suffers from the drawbacks of tensile instability, significantly affecting the computational accuracy. Therefore, this paper first introduces the improved SPH model addressing fluid and solid tensile instability issues. Furthermore, the Riemann-based contact algorithm at the fluid–solid interface is also demonstrated. Based on the above improved SPH model, the simulation of water entry of the elastic cylinder is performed to validate the efficacy of the improved SPH model. Then, the dynamic response characteristics of elastic fuselage skin and the skin–stringer–floor–column structure when it enters the water are analyzed, including the deformation features and slamming force. Lastly, based on the presented damage model, a study is conducted on the water entry of the metallic elastic–plastic skin–stringer–floor–column structure, analyzing the locations of failure and providing guidance for the structural safety design of engineering. [ABSTRACT FROM AUTHOR]

This paper proposes a modular modeling towards a health system integration of fuel cells by considering not only the dynamics of the gases but also fault models that affect the PEMFC performances. The main goal is to simulate the faulty state in order to overcome data scarcity, since running a fuel cell to generate a database under faulty conditions is a costly process in time and resources. The degradation processes detailed in this paper allow to introduce a classification of faults that can occur, giving a better understanding of the performance losses necessary to simulate them. The faults that are detailed and modeled are the flooding, drying and aging processes. This modeling is based on a system approach, so it runs faster than real-time degradation tests, allowing the training and validation of online supervisors, such as the energy management strategy (EMS) method or diagnosis. The faults are reproduced according to the study requirements to be a very effective support tool to help design engineers to include faulty conditions in early design stages toward a diagnosis process and health-conscious energy management strategies. [ABSTRACT FROM AUTHOR]

Socially engaged engineering provides for student learning of the design, analysis, and practices of engineering as well as the ways that engineering is situated in sociocultural contexts. This paper provides a conceptual framework regarding socially engaged engineering for K-8 educators, researchers, and curriculum designers. The framework identifies ways to support youth learning of engineering and considerations of technical, social, environmental, and ethical dimensions of engineering. As engineering enters K-8 educational settings, it is important to introduce the discipline in equity-oriented ways. We draw from the field of engineering for social justice to build this framework for examining engineering at the macro-, meso-, and microscales. Situating engineering in sociocultural contexts can be motivating to learners and provide perspectives on the nature of engineering. Our framework was concurrently designed with Youth Engineering Solutions (YES; https://YouthEngineeringSolutions.org) curricular units. To test the applicability of our principles, we applied them to K-8 YES curricula for school and out-of-school environments. Through the coevolution of principles and curricular materials, we developed age-appropriate learning objectives for three levels--lower elementary, upper elementary, and middle school. This paper shares the principles and progression, showing worked examples from curricula to demonstrate how the principles translate into curricular resources. We discuss constraints to the implementation of socially engaged engineering curricula, including those imposed in educational settings and the ideological assumptions about science, engineering, and STEM disciplines. [ABSTRACT FROM AUTHOR]

The use of in-hole imaging to investigate geological structure characteristics is one of the crucial methods for the study of rock mass stability and rock engineering design. The in-hole images are usually influenced by the lighting and imaging characteristics, resulting in the presence of interference noise regions in the images and consequently impacting the classification accuracy. To enhance the analytical efficacy of in-hole images, this paper employs the proposed optimal non-concentric ring segmentation method to establish a new database. This method establishes the transformation function based on the Ansel Adams Zone System and the fluctuation values of the grayscale mean, adjusting the gray-level distribution of images to extract two visual blind spots of different scales. Thus, the inner and outer circles are located with these blind spots to achieve the adaptive acquisition of the optimal ring. Finally, we use the optimal non-concentric ring segmentation method to traverse all original images to obtain the borehole image classification database. To validate the effectiveness of this method, we conduct experiments using various segmentation and classification evaluation metrics. The results show that the Jaccard and Dice of the optimal non-concentric ring segmentation approach are 88.43% and 98.55%, respectively, indicating superior segmentation performance compared to other methods. Furthermore, after employing four commonly used classification models to validate the performance of the new classification database, the results demonstrate a significant improvement in accuracy and macro-average compared to the original database, with the highest increase in accuracy reaching 4.2%. These results fully demonstrate the effectiveness of the proposed optimal non-concentric ring segmentation method. [ABSTRACT FROM AUTHOR]

This paper describes the design and implementation of a week-long engineering summer camp that engages pre-college learners in human-centered design principles. Students worked in small teams to create and present a viable prototype for a specified user group. The one-week camp engaged students in understanding, ideating, and low-fidelity prototyping. Takeaways from the camp design and implementation are described and possible adaptations to high school science classroom contexts are discussed. [ABSTRACT FROM AUTHOR]

In two recent papers, approximate solutions for compact non-axisymmetric contact problems of homogeneous and power-law graded elastic bodies have been suggested, which provide explicit analytical relations for the force–approach relation, the size and the shape of the contact area, as well as for the pressure distribution therein. These solutions were derived for profiles, which only slightly deviate from the axisymmetric shape. In the present paper, they undergo an extensive testing and validation by comparison of solutions with a great variety of profile shapes with numerical solutions obtained by the fast Fourier transform (FFT)-assisted boundary element method (BEM). Examples are given with quite significant deviations from axial symmetry and show surprisingly good agreement with numerical solutions. [ABSTRACT FROM AUTHOR]

The impact of reservoirs on downstream river hydrological characteristics is always a focal point in relevant studies exploring the relationship between rivers and dams. Anticipating river runoff patterns following the construction of new dams is crucial for the design of riverine engineering projects, particularly during dry periods. This paper presents a semi-theoretical estimation method based on the correlation between hydrological alterations and reservoir operation. The method incorporates differences in runoff increment distribution and the discrepancy between theoretical and practical results. It was validated and applied in the sub-basins of the upper reaches of the Yangtze River, namely the Jinsha River and Min River. The runoff increment during the driest month for the Jinsha River and the Min River is 817 m3/s and 434 m3/s, respectively. The estimated prediction biases were within 30% of the practical runoff increments observed in the Jinsha River and Min River, which is an acceptable range considering the inherent variability in such studies. Since the construction of the Wudongde and Baihetan dams in 2021, the average runoff during the driest month and the navigation assurance runoff at a 95% probability were predicted to be 2866 m3/s and 2174 m3/s, respectively. Therefore, the method developed in this paper provides a reasonable and straightforward tool for researchers, which can help prevent future engineering invalidation and minimize resource costs. Moreover, in the application process, this method requires careful consideration of the characteristics of the studied river section and the operation of the reservoir group. It relies on measured data to determine the differences between theoretical and actual runoff rather than simply generalizing to all watersheds. [ABSTRACT FROM AUTHOR]

Metal roof systems were widely utilized in various important buildings; however, cases of wind damage were often observed. In this paper, wind uplift tests of standing seam aluminum magnesium manganese and continuous welded stainless-steel roof systems were conducted, and the wind resistance bearing capacity and mechanical properties of key joints in the two roof systems were compared and analyzed. Strain gauges and displacement sensors were arranged at different structural layers and key nodes of the roof system to compare and analyze the stress and displacement changes. The results showed that the wind resistance capacity of the continuous welded stainless-steel roof system was more than 25% higher than that of the standing seam aluminum magnesium manganese roof system. The stress and displacement of the roof system gradually increased with the increase in wind load. Obvious differences in stress at different positions of the two roof systems were identified. The stress at the roof panel of the roof system was greater than that of other structural layers, and the maximum displacement of the roof panel in the elastic stage could reach more than 97.5 mm. The fitting coefficient between the test and the finite element was 0.976, and the ultimate bearing capacity of Specimen B was 479.64 MPa. The research results of this paper can provide some data support and reference for engineering design and applications. [ABSTRACT FROM AUTHOR]

Narratives about STEM (science, technology, engineering, and mathematics) education are strongly connected with conversations about developing learners' humanistic knowledge and their ability to listen with understanding and empathy. This is challenging because learners need to find resonance through first-hand contextual experiences with the issues at hand. In this paper, we describe and discuss an activity that was enacted to actively engage 74 teachers from Thailand in constructing a prototype cutting device for the blind to prepare food themselves. This activity underscores important considerations for inclusive design and offers affordances for teachers to develop their learners' inclusive mindsets. Findings were generated from voice recordings of reflections and written reflections collected after the activity. We highlight the importance of creating opportunities for learning to listen and resonate with others' experiences and argue that such STEM activities can offer a platform for learners to develop humanistic qualities such as social empathy. [ABSTRACT FROM AUTHOR]

The impact of the topological formation of wind farms upon the lightning induced overvoltages injected into the grid was not covered earlier in literature. However, this topic is highly important to be investigated to allow the usage of the most reliable topology against lightning strikes. For such reason, the paper investigates this point with consideration of most damaging cases as lightning strikes to multi-blades. The testing used ATP software for four main topologies, radial, single-sided ring SSR, double sided ring and star topology. The features defining the similarities in response and the variance range between these topologies were recorded and analyzed. The multi-blade strikes gave an expected increase of 15% to 100% in the injected overvoltage to the grid for all topologies. The star topology showed the most reliable performance by allowing the least injected overvoltage to the grid. The percentage of reduction in the magnitude of the injected overvoltages reached 50.78%, 66.07% and 89.04% for SSR, DSR and star topology respectively with respect to radial topology. Recommendation was provided for design engineers to consider star topology during design phase in terms of more reliable lightning protection. [ABSTRACT FROM AUTHOR]

Aiming at the problems of insufficient ability of artificial COA in the late optimization search period, loss of population diversity, easy to fall into local extreme value, resulting in slow convergence and lack of exploration ability; In this paper, an improved COA algorithm based on chaotic sequence, nonlinear inertia weight, adaptive T-distribution variation strategy and alert updating strategy is proposed to enhance the performance of COA (shorted as TNTWCOA). The algorithm introduces chaotic sequence mechanism to initialize the position. The position distribution of the initial solution is more uniform, the high quality initial solution is generated, the population richness is increased, and the problem of poor quality and uneven initial solution of the Coati Optimization Algorithm is solved. In exploration phase, the nonlinear inertial weight factor is introduced to coordinate the local optimization ability and global search ability of the algorithm. In the exploitation phase, adaptive T-distribution variation is introduced to increase the diversity of individual population under low fitness value and improve the ability of the algorithm to jump out of the local optimal value. At the same time, the alert update mechanism is proposed to improve the alert ability of COA algorithm, so that it can search within the optional range. When Coati is aware of the danger, Coati on the edge of the population will quickly move to the safe area to obtain a better position, while Coati in the middle of the population will randomly move to get closer to other Coatis. IEEE CEC2017 with 29 classic test functions were used to evaluate the convergence speed, convergence accuracy and other indicators of TNTWCOA algorithm. Meanwhile, TNTWCOA was used to verify 4 engineering design optimization problems, such as pressure vessel optimization design and welding beam design. The results of IEEE CEC2017 and engineering design Optimization problems are compared with Improved Coati Optimization Algorithm (ICOA), Coati Optimization Algorithm (COA), Golden Jackal Optimization Algorithm (GJO), Osprey Optimization Algorithm (OOA), Sand Cat Swarm Optimization Algorithm (SCSO), Subtraction-Average-Based Optimizer (SABO). The experimental results show that the improved TNTWCOA algorithm significantly improves the convergence speed and optimization accuracy, and has good robustness. Three‑bar truss design problem, The Gear Train Design Problem, Speed reducer design problem shows a strong solution advantage. The superior optimization ability and engineering practicability of TNTWCOA algorithm are verified. [ABSTRACT FROM AUTHOR]

Lunar bases for long-term human habitation are a topic of growing interest to engineers. Structures to be built on the surface of the Moon must be designed to resist extreme environmental hazards such as hard vacuum/no atmosphere, low gravity, ionizing radiation, large temperature variations, moonquakes, and meteoroid impacts. Protective regolith covers may provide adequate shielding from some of these hazards. This paper presents a methodology that utilizes established physics-based models to determine the immediate effects of hypervelocity impacts (HVI), including crater geometry and shock pressure, for engineering design of lunar structures. First, empirical equations and nondimensional scaling laws for computing geometric features of HVI craters are discussed. These damage estimation tools are adopted from the fields of spacecraft design and planetary impact cratering. Next, the planar impact approximation model is discussed, which utilizes one-dimensional shock wave physics and impedance matching conditions to estimate the peak initial pressures generated in HVI. Comprehensive parametric analyses, encompassing a wide range of impact velocities and impactor masses as well as a variety of impactor and target materials, are performed to demonstrate applications of the models to both regolith-shielded and unshielded structures. Crater geometry descriptors and peak shock pressures in HVI scenarios involving various impactor-target combinations are computed with in-house programs and compared with computational results reported in the literature. The analyses indicate that for a given target, the main factors determining cratering damage are impactor mass, impactor density, and impact velocity, while the initial shock pressure is influenced mainly by impact velocity and impactor density. A comparison of impact pressures experienced by monolithic unshielded targets and granular dry sand layers highlights the potential importance of providing regolith-like shielding to attenuate HVI effects. Practical implications of the study are discussed from an engineering design perspective, underscoring the considerable value of such models to practitioners. Practical Applications: A practical methodology for determining cratering and peak shock pressure due to hypervelocity meteoroid impacts on unshielded and regolith-shielded lunar structures is proposed in this work. The methodology utilizes well-established physics-based models of hypervelocity impact effects. These models have several advantages that make them suitable for inclusion in lunar structural design guidelines: (1) the models presented are relatively simple yet realistic, empirical, and analytical models; (2) the models do not rely on computationally expensive numerical methods and have been successfully implemented using a commonly available scientific computing platform; and (3) the models consider several essential aspects of the complex physics of hypervelocity meteoroid impacts, which is essential to ensure accurate prediction of the immediate effects of such impacts for lunar structure design. Additionally, this work also includes a wide-ranging parametric analysis that explores and compares the predictions of the physics-based models from an engineering design perspective, encompassing a variety of impact scenarios and impactor-target combinations. The results highlight the practical importance of providing a protective shield, composed of a regolith-like granular material, to mitigate the peak shock pressure sustained by lunar structures in hypervelocity meteoroid impacts. The models, applications, and results presented herein are of immediate relevance to practicing engineers. [ABSTRACT FROM AUTHOR]

Supply chain efficiency is a major challenge in today's business environment, where efficient resource allocation and coordination of activities are essential for competitive advantage. Traditional efficiency strategies often struggle for resources for the complex and dynamic network. In response, bio-inspired metaheuristic algorithms have emerged as powerful tools to solve these optimization problems. Referring to the random search nature of metaheuristic algorithms and emphasizing that no metaheuristic algorithm is the best optimizer for all optimization applications, the No Free Lunch (NFL) theorem encourages researchers to design newer algorithms to be able to provide more effective solutions to optimization problems. Motivated by the NFL theorem, the innovation and novelty of this paper is in designing a new meta-heuristic algorithm called Bobcat Optimization Algorithm (BOA) that imitates the natural behavior of bobcats in the wild. The basic inspiration of BOA is derived from the hunting strategy of bobcats during the attack towards the prey and the chase process between them. The theory of BOA is stated and then mathematically modeled in two phases (i) exploration based on the simulation of the bobcat's position change while moving towards the prey and (ii) exploitation based on simulating the bobcat's position change during the chase process to catch the prey. The performance of BOA is evaluated in optimization to handle the CEC 2017 test suite for problem dimensions equal to 10, 30, 50, and 100, as well as to address CEC 2020. The optimization results show that BOA has a high ability in exploration, exploitation, and balance them during the search process in order to achieve a suitable solution for optimization problems. The results obtained from BOA are compared with the performance of twelve well-known metaheuristic algorithms. The findings show that BOA has been successful in handling the CEC 2017 test suite in 89.65, 79.31, 93.10, and 89.65% of the functions for the problem dimension equal to 10, 30, 50, and 100, respectively. Also, the findings show that in order to handle the CEC 2020 test suite, BOA has been successful in 100% of the functions of this test suite. The statistical analysis confirms that BOA has a significant statistical superiority in the competition with the compared algorithms. Also, in order to analyze the efficiency of BOA in dealing with real world applications, twenty-two constrained optimization problems from CEC 2011 test suite and four engineering design problems have been selected. The findings show that BOA has been successful in 90.90% of CEC2011 test suite optimization problems and in 100% of engineering design problems. In addition, the efficiency of BOA to handle SCM applications has been challenged to solve ten case studies in the field of sustainable lot size optimization. The findings show that BOA has successfully provided superior performance in 100% of the case studies compared to competitor algorithms. [ABSTRACT FROM AUTHOR]

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing and encompassing, and capturing prey to refresh a jackal's position. However, the GJO has several limitations, such as a slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, and weak exploration and exploitation. To enhance the global detection ability and solution accuracy, this paper proposes a novel complex-valued encoding golden jackal optimization (CGJO) to achieve function optimization and engineering design. The complex-valued encoding strategy deploys a dual-diploid organization to encode the real and imaginary portions of the golden jackal and converts the dual-dimensional encoding region to the single-dimensional manifestation region, which increases population diversity, restricts search stagnation, expands the exploration area, promotes information exchange, fosters collaboration efficiency and improves convergence accuracy. CGJO not only exhibits strong adaptability and robustness to achieve supplementary advantages and enhance optimization efficiency but also balances global exploration and local exploitation to promote computational precision and determine the best solution. The CEC 2022 test suite and six real-world engineering designs are utilized to evaluate the effectiveness and feasibility of CGJO. CGJO is compared with three categories of existing optimization algorithms: (1) WO, HO, NRBO and BKA are recently published algorithms; (2) SCSO, GJO, RGJO and SGJO are highly cited algorithms; and (3) L-SHADE, LSHADE-EpsSin and CMA-ES are highly performing algorithms. The experimental results reveal that the effectiveness and feasibility of CGJO are superior to those of other algorithms. The CGJO has strong superiority and reliability to achieve a quicker convergence rate, greater computation precision, and greater stability and robustness. [ABSTRACT FROM AUTHOR]

In high-power photovoltaic systems, the inverter with an LCL filter is widely used to reduce the value of output inductance at which a lower switching frequency is required. However, the effect on the stability of the system caused by an LCL filter due to its resonance characteristic cannot be ignored. This paper studies the stability of a single-phase voltage source full-bridge inverter with an LCL filter through the bifurcation theory as it is a nonlinear system. The simulation results show that low-frequency oscillation appears when the proportional coefficient of the system controller increases or the damping resistance decreases to a certain extent. The average model is derived to analyze the low-frequency oscillation; the theoretical analysis demonstrates that low-frequency oscillation is essentially a period in which doubling bifurcation occurs, which indicates the intrinsic mechanism of the instability of the full-bridge inverter with an LCL filter. Additionally, the limitation of the existing damping resistor design standards, which only considers the main circuit parameters but ignores the influence of the controller on system stability, is identified. To solve this problem, the analytical expression of the system stability boundary is provided, which can not only provide convenience for engineering design to protect the system from low-frequency oscillation but also expand the selection range of damping resistance in practice. The experiments are performed to verify the results of the simulation and theoretical analysis, demonstrating that the analysis method can facilitate the design of the inverter with an LCL filter. [ABSTRACT FROM AUTHOR]

With the continuous development of computer technology, artificial intelligence has been widely applied across various industries. To address the issues of high computational cost and inefficiency in traditional numerical methods, this paper proposes a data-driven artificial intelligence approach for solving high-dimensional neutron transport equations. Based on the AFA-3G assembly model, a neutron transport equation solving model is established using deep neural networks, considering factors that influence the neutron transport process in real engineering scenarios, such as varying temperature, power, and boron concentration. Comparing the model's predicted values with reference values, the average error in the infinite multiplication factor kinf of the assembly is found to be 145.71 pcm (10−5), with a maximum error of 267.10 pcm. The maximum relative error is less than 3.5%, all within the engineering error standards of 500 pcm and 5%. This preliminary validation demonstrates the feasibility of using data-driven artificial intelligence methods to solve high-dimensional neutron transport equations, offering a new option for engineering design and practical engineering computations. [ABSTRACT FROM AUTHOR]

In this paper, the effect of size on the wind pressure coefficient on the surface of solar greenhouses is investigated using numerical simulations. The models were designed with consistent ratios of ridge height to span and north wall height to ridge height across different spans. To effectively understand the impact of dimensions on wind pressure distribution, two wind directions—0° (north wind) and 180° (south wind)—which have previously been shown to impose significant overall wind loads on solar greenhouses, are focused on. It was found that the wind load per unit area increases continuously with greenhouse size. Wind-induced suction is particularly concentrated along the ridge, with greater suction on the leeward side compared to the windward side. The wind suction near the ridge is more significantly affected by greenhouse size. This study provides valuable insights for the practical engineering design of solar greenhouses. [ABSTRACT FROM AUTHOR]