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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 study is the first step of a research program organized to contribute to the dream of using recycled paper as a structural element for sustainable design in Civil Engineering. One of the important tasks is to understand the behavior of connections in paper materials. This study presents the results of experimental research carried out to investigate the behavior of paperboard laminate connections consisting of a single bolt in double shear. A simple and effective method to predict the bearing strength in bolted connection for paperboard laminates has been proposed. A total of 96 bolted connections were fabricated from paperboards oriented in both machine and cross direction. The effect of end distance and edge distance of bolt hole are investigated to address the limiting value for both variables. It was found that the failure is governed by both shear and bearing stresses developed around the hole. Finally, a straightforward design equation has been proposed for such connections. • Single bolt connections can be implemented on paperboard laminates. • Minimum end distance, and edge distance values should be 1.5 times the hole diameter. • Mixed-mode failure which is the combination of shear and bearing mode will govern. • Equation with max. radial compressive stress can be used conservatively for design. [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]

• The impact of NDRTs on TOT in the automated driving system has been examined. • Four dimensions of NDRTs were categorized to consolidate their effects on TOT. • Both Vi-Me-Mo and Vi-Me tasks could increase TOT. • Subgroup analysis and meta-regressions were employed to explore moderators. In the pre-era of fully automated vehicles, humans occupy a pivotal role within the driving system. Extensive research has been conducted to explore how drivers interact with automated vehicles across diverse scenarios. This article presents a meta-analysis of 42 papers to examine the influence of non-driving-related tasks (NDRTs) on takeover time (TOT). To consolidate the effect of NDRTs on TOT, this paper classified the NDRTs into four dimensions (visual, auditory, motoric, and mental), which aimed to provide a unified understanding of this impact. This paper employed the following three analyses to understand this impact. Firstly, a synthetical analysis was conducted to compare the effect sizes across primary studies. Secondly, a two-group analysis was performed on studies that included eligible control and experiment groups. Lastly, a moderator analysis, incorporating seven potential moderators, was conducted to further explore the underlying mechanism. The results from the synthetical and two-group analyses revealed that both visual-mental-motoric (Vi-Me-Mo) and visual-mental (Vi-Me) tasks could increase TOT, with the former having a greater effect than the latter. The moderator analysis, including subgroup analysis and meta-regression, further confirmed the significance of moderators within their respective subgroups. However, most moderators exhibited non-significant effects across different scenarios. The findings of this study underscore the crucial importance of attending to TOT and tailoring automated driving systems based on individual driver characteristics. Furthermore, this paper contributes significantly to the advancement of scientific research and engineering design by providing valuable insights into the automotive industry. [ABSTRACT FROM AUTHOR]

Digital servitization has emerged over the last years, at the convergence between digital- and service-oriented business strategies, leading manufacturing companies to transform their business models through the adoption of so-called Smart PSS (Smart Product-Service-Systems). As a contribution to the relatively recent scientific literature on Smart PSS design, this paper presents a framework for the design and engineering of Smart PSS offers, based on a value-driven approach. The added-value of the framework is notably to integrate (i) a smart PSS prototyping approach associated with (ii) a risk management process, all along the design process. When a manufacturing company has to shift from a 'product-centric' to a 'Smart PSS' business model, sPS2Risk Framework helps decision-makers anticipating and mitigating key innovation risks. The paper presents the generic framework and its experimentation for an industrial case study, in the heating appliance sector. [ABSTRACT FROM AUTHOR]

How to determine the unusual stratum load for metro tunnel under the influence of ground fissure is a major challenge faced by the construction of Xi'an Metro in China. In this paper, based on the theories of Bierbaumer and Terzaghi, a limit equilibrium form of stratum holding effect principle is proposed as an alternative solution for calculating the unusual stratum load experienced by metro tunnels crossing ground fissures at different intersection angles. Our methodology uses the movement mode of stratum-tunnel induced by active ground fissure to construct the analysis model, while considering soil properties and strength, holding force, tunnel buried depth, segment diameter, and the intersection angle between tunnel and ground fissure. Fundamental formulae for the development of soil fracture angle during this movement process are also derived and analyzed. The methodology is also illustrated and validated by two representative examples, and the sensitivity of parameters affecting the results is discussed as well, providing some design suggestions for practical engineering. The presented alternative way of calculating the unusual stratum load in the active ground fissure site might be helpful for the design of metro engineering to meet the necessary degree of safety. [ABSTRACT FROM AUTHOR]

Quantitative structure-activity relationship modeling techniques are widely employed in diverse areas of chemistry, including environmental risk assessment of compounds and virtual screening of drugs. The modeling process entails optimizing the hyper parameters of the model and selecting appropriate molecular descriptors. It is a typical optimization problem with high-dimensional, nonlinear, continuous and discrete variables coexisting. To address this challenge, this paper proposes an enhanced snake optimizer with multiple strategies. First, new food emergence and temperature change mechanisms are introduced to balance the exploration and exploitation. Second, a death and regeneration mechanism is employed to enhance the algorithm's ability to escape from local optima. Third, new formulas for food searching, fighting, mating and eating are designed to simplify the complexity of the algorithm and improve its search efficiency and accuracy. Fourth, the performance of the proposed algorithm is evaluated using the CEC2017 benchmark functions, eight engineering cases with continuous variables, and six feature selection cases with discrete variables. Experimental results demonstrate that the algorithm significantly outperforms comparison algorithms. Finally, the algorithm was applied to quantitative structure-activity relationship modeling for environmental toxicity prediction. Compared with other algorithms, the algorithm can better configure hyper-parameters and select fewer and more effective features for environmental toxicity prediction model. It will be an effective tool to improve the performance of quantitative structure-activity relationship models. • New food emergence and temperature change mechanisms are presented to better balance exploration and exploitation. • Death and regeneration mechanism is adopted to avoid local optima. • The performance of the proposed algorithm is validated in CEC2017, engineering design and feature selection problems. • A joint optimization approach is proposed for quantitative structure-activity relationship modeling. • An environmental toxicity prediction model is obtained by jointly optimizing hyper-parameters and molecular descriptors. [ABSTRACT FROM AUTHOR]

Predicting the behavior and mechanical properties of 3D-printed parts is crucial for 3D printer users. This study conducted experimental investigations on Onyx 3D-printed parts to identify the most important printing parameters. These parameters were specimen positioning and the number of specimen walls. The experimental results indicated that specimens oriented in the XZ direction were 48% stiffer than those oriented in the XY direction and 54% stiffer than those oriented in the ZX direction. Additionally, the results demonstrated that walls significantly influenced the mechanical properties of specimens in the XY and XZ orientations but had no effect on those in the ZX orientation. The Young's modulus increased by 60% between a specimen with one wall and another with eight walls. This paper presents an analytical model for predicting mechanical properties based on the number of walls, with a prediction error ranging from 1% to 15%. Additionally, a numerical simulation approach was proposed to predict the mechanical behavior of parts. The numerical and experimental results comparison showed a 1% to 9% prediction error and a good correlation between numerical and experimental curves. These findings can be a valuable aid to engineers in the design of 3D printed mechanical concepts. [ABSTRACT FROM AUTHOR]

The primary contribution of this paper is to investigate the effect of mechanical errors on the electromagnetic (EM) performance of the generalized deployable log-period dipole (GDLPDA) antenna. The concept of the "GDLPDA" is introduced first. Additionally, an electromechanical error analysis model is developed to assess the effects of dipole machining errors and deformations on the EM performance of GDLPDA. Based on this model, positional errors in two directions along the feedline are considered. Furthermore, an electromechanical error analysis model considering dipole rotational errors on cross-polarized electric fields is established. The actual positional and rotational errors are simulated to analyze the EM performance of GDLPDA. The simulation results show that the dipole positional and rotational errors can degrade the EM performance. Specifically, positional errors reduce gain and pointing accuracy, along with an increase in the 3 dB beamwidth. Rotational errors generate cross-polarization fields, decreasing the level of the co-polarization amplitude. This insight can help antenna design engineers to optimize GDLPDA to minimize the adverse effects of error on performance. [ABSTRACT FROM AUTHOR]

Functional modelling is an essential part of systematic design approaches and is often prescribed in engineering design textbooks. However, function models created with current function modelling techniques often lack formal and repeatable representation, limiting their use in computational reasoning. Therefore, this paper presents a new functional modelling method to support function models' creation with formal and repeatable representation. The key element of the proposed method is a Function Class – a function-modelling element that categorises defined functions on a function block level by specifying operating flow, input and output flows, and integrates primary rules for functional modelling such as conservation law. The formalisation on a function block level reduces the number of morphological errors and provides a theoretical framework for future computational processing of function models. This paper proposes a protocol for developing Function Classes and defines a theoretical function modelling framework through Function Class Method. The development and use of the Function Class Method are demonstrated through the development of Function Classes for the Design for Additive Manufacturing domain as the first step toward a universal function modelling approach. [ABSTRACT FROM AUTHOR]

The development of new products using social technologies among defined crowds of individuals or groups, commonly known as Social Product Development (SPD), has become a growing trend in engineering design and manufacturing literature. This paper proposes an approach to studying the actors involved in SPD from a complexity science point of view. Specifically, we suggest that organizational efforts towards SPD must be concentrated on human and technological elements to achieve success in New Product Development (NPD). The paper explores the differences and similarities between the creation of new products and SPD and proposes a differentiated approach, based on complexity science for the different stages of NPD and SPD. Our findings show that SPD requires the integration of the complexity approach due to the combination of the knowledge, skills, and abilities of those involved during the development of new products. In addition, it is recommended that engineering design managers consider the importance of leadership styles, work structure, and organizational culture to achieve the expected outcomes of SPD. [ABSTRACT FROM AUTHOR]

Assessing the circular economy (CE) performance of products has become an essential consideration in product design processes. While a growing body of literature is exploring the use of CE indicators to guide design processes, they typically assume broad design changes (e.g., material changes, end-of-life treatment) that may not accurately capture trade-offs in CE indicators, technical performance, and design feasibility. This paper aims to address the above gaps with the goal of incorporating CE assessment into simulation-based design. To this end, this paper defines a novel framework for using simulation-based design to analyze the effects of parametric changes in product design attributes on CE performance. First, the proposed framework describes the lifecycle information needed for computing resource-based, product-level CE indicators at the design stage. Depending on the set of selected CE indicators, corresponding simulation models are used to compute the effects of changing design parameters, and setting design/performance constraints, on the product's CE performance. Thus, the proposed framework enables the selection and optimization of product design attributes for achieving a specific level of CE performance, given specific technical performance requirements and other design constraints. The application of this framework is demonstrated using a case study conducted on a flywheel. [ABSTRACT FROM AUTHOR]

Honey badger algorithm (HBA) is a recent swarm-based metaheuristic algorithm that excels in simplicity and high exploitation capability. However, it suffers from some limitations including weak exploration capacity and an imbalance between exploration and exploitation. In this paper, an improved honey badger algorithm called ODEHBA is proposed to improve the performance of basic HBA. Firstly, an improved orthogonal opposition-based learning technique is employed to assist population in escaping local optimum. Secondly, differential evolution is utilized to ensure the enrichment of population diversity and to enhance convergence speed. Finally, the exploration capability of ODEHBA is boosted by an equilibrium pool strategy. To validate the efficacy of proposed ODEHBA, it is compared with 13 well-known metaheuristic algorithms on CEC2022 benchmark test sets. Friedman test and Wilcoxon rank-sum test are utilized to assess the performance of ODEHBA. Furthermore, three engineering design problems and Internet of Vehicles (IoV) routing problem are applied to validate the capability of ODEHBA. The simulation results demonstrate that ODEHBA excels in solving complex numerical problems, engineering design, and IoV routing problems. This holds significant practical implications for cost reduction and improved resource utilization. [ABSTRACT FROM AUTHOR]

This paper aimed to explore the application of SERVQUAL in assessing the performance of in-house detailed engineering design in an engineering management firm. The goal is to evaluate service quality and identify gaps between customer expectations and perceptions across the five service quality dimensions. Results show that customers are dissatisfied with the department's service quality, and negative gaps exist across all 22 questions. Improvements in reliability, assurance, and responsiveness are recommended to enhance customer satisfaction. The study demonstrates a strong correlation between service quality dimensions and contract retention, highlighting the importance of improving service quality for long-term business success. [ABSTRACT FROM AUTHOR]

The butterfly optimization algorithm (BOA) is a meta-heuristic algorithm that mimics foraging and mating behavior of butterflies. In order to alleviate the problems of slow convergence, local optimum and lack of population diversity of BOA, an enhanced adaptive butterfly optimization algorithm (EABOA) is proposed in this paper. First, a new adaptive fragrance model is designed, which provided a finer fragrance perception way and effectively enhanced the convergence speed and accuracy. Second, Lévy flight with high-frequency short-step jumping and low-frequency long-step walking is adopted to help the algorithm jump out of the local optimum. Third, the dimension learning-based hunting is employed to enhance information exchange by creating neighbors for each butterfly, thus improving the balance between local and global search and maintaining population diversity. In addition, the Fitness-Distance-Constraint (FDC) method is introduced to enhance constraint handling in EABOA (named FDC-EABOA). The proposed EABOA is compared with 8 well-known algorithms and 8 BOA variants in CEC 2022 test suite and the results were statistically analyzed using Friedman, Friedman aligned rank, Wilcoxon signed rank, Quade rank and multiple comparisons, analysis of variance (ANOVA) and range analysis. Finally, EABOA and FDC-EABOA are applied to seven engineering problems (parameter identification of photovoltaic module model, speed reducer design, tension/compression spring design, pressure vessel design, gear train design, welded beam design, SOPWM for 3-level inverters), and metrics such as Improvement Index (IF) and Mean Constraint Violation (MV) confirm that the proposed algorithms are satisfactory. Experimental results and statistical analysis show that the proposed algorithms outperform the comparison algorithms and demonstrate the strong potential for solving numerical optimization and engineering design problems. [ABSTRACT FROM AUTHOR]

Driven by a technological transition, paradigms such as Lean, Green, and Circular Economy are increasingly being addressed by manufacturers to provide increasingly complex solutions. Whether considering products or services, design plays a decisive role in this context. Concurrent engineering and approaches to Design for X (DFX) have become commonly related to products and services, revealing the prominent potential to enhance product quality, improve sustainability performance, increase consumer satisfaction, and support the design of products, processes, and systems. However, many researchers have developed several DFX techniques with modified applications for different domains. This diversity makes it hard for practitioners and researchers when considering advanced technologies, to suit the current DFX with an integrated lean, green, and circular design perspective. In this regard, this paper aims to present a literature analysis concerning a potential model for the integration of four paradigms of management: lean, green, circular economy, and Industry 4.0 while considering DFX approaches. As a result, a framework that illustrates the connection between the fourth paradigm considered and the DFX approaches is presented. Our analysis would be useful to academics and practitioners since it indicates the field's key limitations and research lines. [ABSTRACT FROM AUTHOR]

We summarized in this review paper the underlying degradation mechanisms of Mg anodes. [Display omitted] Rechargeable magnesium batteries (rMBs) have been regarded as one of the most promising battery systems among the post-lithium-ion batteries (post-LIBs) due to their high energy density, abundant reserves, low cost and environmental friendliness. Unfortunately, a major obstacle to commercial applications of rMBs is the undesired degradation phenomena of Mg anode induced by uneven Mg deposition and the passivation, which leads to inferior reversibility of Mg deposition/stripping. The recent progress in development of anode materials and their compatibility with electrolytes has provided valuable experience. In this review, the underlying degradation mechanisms of Mg anode are first systematically summarized and elucidated. In addition, several main strategies for building stable anodes and anode/electrolyte interfaces are intensively discussed. Finally, the remaining opportunities and challenges for future research are briefly elaborated in this field. This review is expected to provide a great impetus to enlighten novel material and structural design engineering, and thereby promote the electrochemical performance of magnesium-based and other related emerging battery systems. [ABSTRACT FROM AUTHOR]

Recent advancements in large language models (LLMs) demonstrate great potential in supporting engineering design, especially conceptual design. Prompt engineering plays an important role in facilitating designer-LLM collaboration in conceptual design. This paper proposes a new classification scheme that categorizes design-specific prompts into multiple classes. It also introduces different patterns for synthesizing design prompts, being grounded in the theoretical foundations of prompt engineering and domain-specific design methodology. A design experiment, utilizing ChatGPT, was conducted to investigate the impacts of different syntheses of design prompts on the effectiveness of LLM in concept generation, as measured by the metrics of novelty and diversity. [ABSTRACT FROM AUTHOR]

Rao algorithms that include three algorithms are very simple and parameter-less algorithms with effective and desirable performance. This paper modifies these three algorithms, merges them, and establishes a powerful group algorithm. In the first optimization step, the suggested algorithm is tested on 30 standard CEC2014 functions with 50 dimensions to compare it with main algorithms, several well-known algorithms, and modified versions of RAO algorithm. It becomes evident in the first test that the suggested optimizer is effective, and reliable for optimization of real-parameter functions, and it has shown its superiority to original RAO algorithm and several modern and modified versions of RAO algorithms for most of the test functions and achieved more acceptable results than them. Moreover, the suggested algorithm benefits a faster convergence characteristic than original RAO algorithms. The proposed Colonial Competitive RAO (CCRAO) has been applied on five popular engineering problems and its results have been compared with those of recent papers. According to the results, CCRAO is an effective, robust, and reliable optimizer for engineering design problems and can contain all useful features of RAO algorithms altogether. CCRAO has succeeded to converge to the best solution for these engineering problems and surpasses most of the other algorithms. [ABSTRACT FROM AUTHOR]

Search and retrieval remains a major research topic in several domains, including computer graphics, computer vision, engineering design, etc. A search engine requires primarily an input search query and a database of items to search from. In engineering, which is the primary context of this paper, the database consists of 3D CAD models, such as washers, pistons, connecting rods, etc. A query from a user is typically in the form of a sketch, which attempts to capture the details of a 3D model. However, sketches have certain typical defects such as gaps, over-drawn portions (multi-strokes), etc. Since the retrieved results are only as good as the input query, sketches need cleaning-up and enhancement for better retrieval results. In this paper, a deep learning approach is proposed to improve or clean the query sketches. Initially, sketches from various categories are analysed in order to understand the many possible defects that may occur. A dataset of cleaned-up or enhanced query sketches is then created based on an understanding of these defects. Consequently, an end-to-end training of a deep neural network is carried out in order to provide a mapping between the defective and the clean sketches. This network takes the defective query sketch as the input and generates a clean or an enhanced query sketch. Qualitative and quantitative comparisons of the proposed approach with other state-of-the-art techniques show that the proposed approach is effective. The results of the search engine are reported using both the defective and enhanced query sketches, and it is shown that using the enhanced query sketches from the developed approach yields improved search results. [Display omitted] • The first learning-based strategy to clean rough query sketches of 3D CAD models • Introduces SketchCleanNet — an end-to-end image translation scheme • SketchCleanNet aims to understand the mapping between rough sketches and clean query images • A novel scheme to calculate the loss is introduced • Dataset Contribution: The resulting enhanced query sketch dataset is made available publicly. • This paper will significantly contribute to the research community and give researchers opportunities to develop new algorithms for search and retrieval of 3D mechanical components. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) panels' photoelectric conversion efficiency will decrease as dust deposition on their surface. An approach to dust removal on the PV panel's surface by longitudinal high-speed airflow was investigated to increase the output power. In this paper, commercial CFD software was used to numerically simulate the characteristics of dust removal by longitudinal high-speed airflow. The PV panels' output characteristic model under the action of dust removal by high-speed airflow is established by Simulink software, and the influence of high-speed airflow on the output characteristic is studied. Firstly, the dust removal mechanism of the PV panel under high-speed airflow is studied. Secondly, the impact of different tilt angles of the PV panel, dust particle size, airflow velocity, and blowing time on the dust removal effect of the PV panel surface were studied. The optimal airflow velocity and blowing time were obtained according to the airflow velocity and blowing time and their influence on the dust removal rate. Finally, the effect of high-speed airflow dust removal on PV power generation's efficiency and output characteristics is studied. The findings demonstrate that as the tilt angle increases, so does the dust removal rate increases continuously. In addition, the rate at which dust is removed increases with airflow velocity and blowing time. When the tilt angle is 30°, the best airflow velocity of dust removal is 5 m/s, and the best blowing time is 8 s. When the tilt angle is 45°, the best airflow velocity of dust removal is 10 m/s, and the best blowing time is 5 s. With the increase in airflow velocity and blowing time, the output power of PV panels continues to increase. When the airflow velocity is 10 m/s, and the blowing time is 5 s, 7.5 s, 12.5 s, and 15 s, the maximum output power after dust removal is increased by 15.44 %, 23.05 %, 23.38 %, and 23.39 %. This paper's research results can guide the design of the practical engineering application of longitudinal blowing high-speed airflow in the dust removal of PV panels. • A dust removal method based on longitudinal high-speed airflow on the surface of PV panels. • Dust removal under the action of longitudinal high-speed airflow is simulated by CFD. • The effect of high-speed airflow dust removal on the output power is studied. [ABSTRACT FROM AUTHOR]

Engineering design review, which is a time-consuming task in the building permit process, faces challenges such as a scarcity of design review specialists, vulnerability to manipulation and corruption, and a lack of traceability and transparency. This paper explores the integration of blockchain and online service trading in addressing these challenges. This paper proposes a platform-based design review service trading scheme, engaging a distributed network of experts to overcome resource limitations and integrates blockchain technology to improve process traceability. The system model is presented, an access control model and a design version management method are proposed. A prototype system is developed, and a real-world project is used to illustrate the online design review process. Security, function, and performance evaluations show that the scheme is secure and efficient. This study highlights blockchain's potential in digital building permits. Future work can explore advanced service matching algorithms in online design review service trading platforms. • This study proposes a platform-based design review service trading scheme to engage a distributed network of design experts, aiming to overcome resource limitations. • The proposed scheme integrates blockchain technology to enhance immutability and traceability in the digital building permit process. • An access control model and design version management method are developed to achieve secure data transmission and trace design modifications in the design review process. • A real-world project is used as an example to simulated the proposed scheme. [ABSTRACT FROM AUTHOR]

• We have devised a composite gear transmission system, which comprises a RV reducer, two parallel shaft transmissions, and a planetary gear transmission. • A rescue module has been integrated into the driving system to ensure the necessary rescue operations for the manipulator. • The structural configuration of the relevant shells has been developed, with comprehensive explanation on dimensions, manufacturing methodology and strength assessment. • A detailed exposition on the internal architecture and rotational capabilities of these joints has been provided. • An effective internal cable routing scheme for the root joints has been proposed. This study concentrates on the engineering design and analysis of the root joints for the CFETR Multi-Purpose Overload Robot (CMOR), a crucial component in the China Fusion Engineering Test Reactor (CFETR). The CFETR tokamak is an engineering test reactor in China for magnet confinement fusion research. CMOR is a 7-DOF manipulator characterized by heavy-load capacity, high precision, and compact structures, designed for internal maintenance inside the CFETR. This presents significant challenges in its design. The design of the root joints is significant for the CMOR. This paper provides an in-depth exploration of the engineering design and analysis of the root joints. It offers a thorough explanation of the driving systems' design, including an integrated rescue module to address potential manipulator faults. Additionally, this paper delves into the conceptual design and manufacturing schemes of the corresponding shells, which are validated under various loading conditions—including regular and earthquake scenarios—through finite element analysis. The assembled root joints' internal structure and cable routing scheme are also discussed in-depth. This research provides valuable insights for future joint designs of the CMOR heavy load manipulator, advancing maintenance operations for fusion reactors. [ABSTRACT FROM AUTHOR]

Regolith sampling is one of the core missions in deep space exploration. The design, optimization, and fabrication of samplers are challenging tasks to meet the requirements of deep space exploration, often necessitating complex modeling with computer-aided design tools and demanding the expertise of experienced space engineers with lengthy design iterations. We propose an interactive design framework where designers collaborate with optimization tool to streamline the design process. With the operator adjusting the design goals, we introduce Bayesian optimization to automatically suggest the next sets of parameters to explore. This approach is suitable for optimization scenarios when the design goals cannot be well established as analytical functions and fewer design iterations are required. In this paper, we design and optimize the core structure of the sampler under both stress analysis and discrete element analysis, considering lower stress, greater sampling volume per unit power consumption, and smaller size. Both simulation and physical experimental results show that the design proposed by our framework outperforms existing designs with a small number of design iterations. [Display omitted] • A computational design framework for searching forms of planetary regolith samplers. • The introduction of Bayesian optimization to reduce the cost in optimizing the shape in terms of efficient interaction with granular material. • Simulation and physical experiments to validate the proposed design from our framework. [ABSTRACT FROM AUTHOR]

The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is O (ϵ − 3 − δ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be O (ϵ − 1) , we demonstrate that the result can be improved to O (ϵ − 2) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain O (ϵ − 1 log ⁡ (1 / ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty. [ABSTRACT FROM AUTHOR]

Modularized assembly tooling possesses the characteristics of high modularization and standardization. The modularized components enable the assembly tooling to be reusable and reconfigurable with low designing and manufacturing costs. However, the modularization will lead to a large number of tedious and repetitive manual constraint-creating operations in modeling, which goes against the idea of rapid design. This paper introduces the structure of modularized assembly tooling and proposes a series of algorithms according to modularized and parameterized CATIA models for rapid design, owning the characteristic of model rapid reconfiguration. The efficiency promotion is also assessed by the actual engineering design, proving the implementation of the digital rapid design of modularized assembly tooling based on CAA secondary development. [ABSTRACT FROM AUTHOR]

• The principle of the existing most unfavorable tunnel length (MUTL) was clarified. • The theory of MUTL for the interior pressure variation were established. • The concepts and calculation methods of MUTL-S and MUTL-L were proposed. • A number of tunnel length calculations were conducted based on the TWS method. When a high-speed subway passes through a tunnel, the external aerodynamic pressure of the train is transmitted into the train interior, which adversely affects the passenger comfort. The effect of tunnel length on the interior pressure variation of the train cannot be ignored. According to previous studies, there is a most unfavorable tunnel length (abbreviated as MUTL in this paper) for the exterior pressure of the train. However, MUTL for the interior pressure variation is still a research gap. In this study, the effect of tunnel length on the interior pressure variation of tunnel and train was investigated using numerical simulation and TWS method. Additionally, the theoretical formula of MUTL based on the internal pressure variation at the head and tail of the train was established and verified using the results of past field measurements and TWS method. The findings indicate that the interior pressure variation with tunnel lengths within a certain time interval is not monotonic. Moreover, there may be two or even more MUTLs, and the MUTL is also be influenced by the dynamic sealing index. MUTL decreases with increasing train speed and increases with increasing number of cars. The research findings of this paper address the research gap in the study of MUTL on the pressure variation inside trains. These findings offer new theoretical guidance for the research of aerodynamic effects in high-speed subway tunnels, and provide a valuable reference engineering design and optimization. [ABSTRACT FROM AUTHOR]

• 4 types of high-temperature nuclear loop with movable equipment elevated were compared. • Influence evaluation of U-type layout design parameters was made. • Application of U-type layout to the TMSR-LF1 was conducted. High temperatures could make nuclear power more efficient but also pose a huge challenge to the layout design. In this paper, based on the characteristics of the Thorium Molten Salt Reactor-Liquid Fuel 1 (TMSR-LF1) high-temperature nuclear loop, the schema design and optimization for four typical types of Linear-type, L-type, Z-type, and U-type loop layouts with moveable equipment were carried out. Then, the influencing factors for relevant design parameters of the proposed U-type layout were discussed. Finally, the compact layout with moveable equipment of the TMSR-LF1 loop was determined, and the finite element calculation results considering the creep-fatigue effect of the designed loop pipes met the requirements of the ASME-III-5-HCB code. Moreover, the experimental displacement of the molten salt pump in commissioning condition was basically consistent with the calculated results, which verified the rationality of the proposed loop layout. The research in this paper has practical engineering implications for the design of a high temperature nuclear loop. [ABSTRACT FROM AUTHOR]

Pipelines may be subject to displacement-controlled external loads exceeding yield strength of materials due to many causes, e.g., soil settlements and ground movement. It is important to ensure that strength of girth welds even- or over-matches that of pipe steel to avoid strain concentration in the weld leading to a premature failure of a pipeline. Unfortunately, a number of high strength pipeline failure incidents primarily associated with weld strength under-match had been reported. Currently most standards do not explicitly specify strength match requirements for girth welds in pipelines and it is a challenge to achieve weld strength over-match in high strength pipelines. This paper provides a comprehensive review on the characteristics of strength mismatch, the difficulties faced in achieving weld strength over-match in high strength pipelines and the impact of weld strength under-match on structural integrity of pipelines. It also introduces the research, failure incidents, operation practice and the relevant standards/codes associated with weld strength mismatch in high strength pipelines in China. The paper starts by briefly reviewing the historic origin for weld strength requirements, different definitions for weld strength mismatch are then described, the acceptance requirements for pipe steel and girth welds in several major standards and codes are introduced and their inadequacies are discussed. This paper also discusses macro- and micro-scale weld strength mismatch, the influence of weld strength under-match on failure of girth weld and both design and engineering construction requirements for weld strength over-match. Possible mitigation measures to avoid strength under-match are finally proposed. • The paper provides a comprehensive review on the characteristics of strength mismatch, the difficulties faced and the impact of weld strength under-match on structural integrity of pipelines. • It introduces the research, failure incidents, operation practice and the relevant standards/codes associated with weld strength mismatch in high strength pipelines in China. • Possible mitigation measures to avoid strength under-match of girth welds are proposed. [ABSTRACT FROM AUTHOR]

• We have devised a composite gear transmission system for the rotary joints' driving systems of the CMOR. • The engineering design of the joint driving systems for the CMOR has been successfully completed. • We have proposed fast testing methods for the transmission error and backlash error of the driving system. • The manufacturing and testing of joint J6's driving system for the CMOR have been successfully completed. This study focuses on the engineering design and testing of the rotary joints' driving systems for the China Fusion Engineering Test Reactor (CFETR) Multi-Purpose Overload Robot (CMOR). CMOR is a critical component in the CFETR. The CFETR tokamak serves as an engineering test reactor in China for magnet confinement fusion research. CMOR, a 7-DOF manipulator, is specifically designed for internal maintenance within the CFETR. This poses significant challenges in the design of the joint driving systems. The joint types of CMOR are categorized into three, comprising one translation joint, two swing joints, and four rotary joints. Using rotary joint J6 of CMOR as an example, this paper provides a detailed exploration of the engineering design and testing of the rotary joints' driving systems, offering a comprehensive explanation of their design specifications and principles. Specification and strength assessments are conducted on the engineering design results, meeting all requirements. Furthermore, the paper delves into the testing methods of the driving systems, including the assessment of transmission error and backlash error, two crucial indicators for the driving system. This research contributes valuable insights for future joint designs and testing of the CMOR heavy-load manipulator. [ABSTRACT FROM AUTHOR]

Optimization problems are prevalent in a variety of real-world applications, including medical, engineering, chemical, and others, and must be precisely solved to enhance the performance of these applications. Unfortunately, finding near-optimal solutions to these problems is regarded as a hard challenge due to their various characteristics. In a new attempt to solve these problems, this paper presents a new variant of the artificial gorilla troops optimizer (GTO) called ranking-based GTO (RGTO). This variant uses two strategies known as the ranking-based update strategy and the convergence acceleration strategy to improve both the classical GTO's exploitation and exploration capabilities. The first strategy is proposed to enhance each gorilla's local and global search abilities, whereas the latter is intended to enhance GTO's global search abilities to reach better solutions as quickly as possible. First, a recent and challenging benchmark, namely CEC-2017, is utilized to assess the RGTO's explorative and exploitative capabilities. After that, RGTO is used to solve three engineering optimization problems, including parameter estimation problems for both photovoltaic (PV) models and proton exchange membrane fuel cells (PEMFCs), as well as some engineering design problems, to demonstrate how well it performs for real-world optimization problems. Compared to several rival optimizers, the proposed algorithm provides outstanding outcomes for the three engineering optimization benchmark problems considered. [ABSTRACT FROM AUTHOR]

In this paper, isogeometric analysis (IGA) is used for the first time to explore the free and forced oscillation of two-directional functionally graded porous (2D-FGP) curved nanobeams with arbitrary boundary conditions. Materials used in the production of curved beams have mechanical qualities that change in both the longitudinal and thickness directions of the beam, as well as microscopic porosities that are distributed according to various regulations. The whole curving beam is reinforced by Pasternak's foundation with two parameters in a hygro-thermal condition. Hamilton's essence is based on a quasi-3D beam model, and the nonlocal elasticity hypothesis is used to derive the governing equation of a 2D-FGP curved nanostructure. The validity of the suggested model is determined by comparing the results of the current study to those of reputable publications. By taking into consideration the free and forced oscillation responses of the curved nanobeam, the influences of parameters such as the power-law index, nonlocal parameter, porosity coefficient, temperature and moisture change, the opening angle of the beam, the stiffness of the elastic substrate, arbitrary boundary conditions, and the thickness-to-length ratio can be investigated. The benchmark solutions that have been detailed in this work may in the future be used as a reference for the free and forced behavior of 2D-FGP nanobeams that have a curved form, and this may be possible because of the findings of this study, especially for structural design engineers of this type. [ABSTRACT FROM AUTHOR]

• A general model of sagged-cable-crosstie is established by introducing spatial and temporal nondimensionalization. • The general expression of the characteristic equation's 2N(M+1)-order coefficient matrix is given for the first time. • A minimal set of fundamental key dimensionless parameters that govern the system's modal characteristics are intuitively found. • The general model is degenerated into three models and is high-precisely verified by literature and FEM. Though crosstie has become a promising approach for vibration mitigation of long cables, its mechanism is yet to be fully understood, restricting the set of engineering design theory. Scholars worldwide have continuously proposed various mechanical models to investigate modal characteristics of cable-crosstie structures. However, first, dynamic equations were dimensional or not fully dimensionalized, hindering the definition of essential independent key parameters that govern the modal characteristics of the system; second, no general expression of the coefficient matrix in characteristic equations was given. This paper proposes a general sagged-cable-crosstie model applicable to structures with a generic number of cables and crossties. A universal dimensionless dynamic equation is derived by thorough dimensionless treatment, and the universal expression of a 2 N (M + 1) -order coefficient matrix is obtained by introducing boundary, equilibrium, and continuity conditions. A minimal set of dimensionless parameters that govern modal characteristics of any sagged-cable-crosstie system is found, i.e., crosstie positions ε j , p , Irvine parameters of cables λ j 2 , dimensionless wave speed parameters α j , and dimensionless crosstie stiffnesses k j , p. Subsequently, the general model degenerates into three representative models: double-cable-single-crosstie, three-cable-single-crosstie, and double-cable-double crosstie. Frequencies of each degenerated model are compared with that of literature and FEM, and good consistency is obtained. [ABSTRACT FROM AUTHOR]

The role of data mining in software engineering is obvious, but there is a lack of mining depth. In the past, engineering layout and function distribution problems in software development, and the framework construction was unreasonable. Therefore, this paper proposes a software system based on data mining technology. First, the software engineering project is divided, and the software engineering project design is carried out according to the interactive requirements to realize the preprocessing of software engineering. Then, according to the design criteria, the design collection of software engineering is formed, and the information system is analyzed in depth. MATLAB simulation shows that the design interactivity and accuracy of data mining are superior to traditional design methods under the condition that software engineering requirements are consistent. [ABSTRACT FROM AUTHOR]

With the advent of Internet information technology, data mining technology has been applied in various fields of China's social and industrial development, and has promoted the quality development of the industry [1]. Nowadays, people are widely influenced by Internet computer technology, and the application of computer technology has been indispensable in life, work and study. At the same time, data mining technology arises from Internet communication technology and is used as an important technical means of operation and development by various industries, especially the application of data mining technology in university software engineering teaching is becoming more and more widespread, but there are still many unavoidable problems that require scholars to pay more attention. The article analyzes and discusses the significance of applying data mining technology in software engineering [2] , and on this basis, the application path of data mining technology in software engineering database design is proposed, including: mining information, mining loopholes, mining execution records and open source. It is hoped that relevant technology users can efficiently apply data mining technology to make software engineering It is more reasonable and efficient, so that software engineering can be further developed. This paper presents the implementation and performance analysis of the teacher management decision-making system based on data mining, and introduces the implementation process of the system in detail. [ABSTRACT FROM AUTHOR]

• This paper presents an enhanced salp swarm algorithm for solving global optimization problems. • The random replacement strategy is used to accelerate the convergence speed of the basic salp swarm algorithm. • The double adaptive weighting strategy enhances the algorithm's global exploration and local exploitation capabilities. • The optimization performance of the improved algorithm is evaluated on basic test functions and practical problems. The salp swarm algorithm is a newly population-based search algorithm. Because the original salp swarm algorithm has low search efficiency and is easy to fall into local optimum, in this paper, we propose an enhanced salp swarm algorithm, which combines two strategies with the original salp swarm algorithm. One is the random replacement strategy, which can replace the current position with the optimal solution position with a certain probability of speeding up the convergence rate. The other tactic is double adaptive weight, which can expand the search scope throughout the early stages and enhance exploitation capability in the later stages. With the cooperation and guidance of the two mechanisms, the algorithm's convergence speed is accelerated, and the exploitation capacity is meritoriously increased. The proposed method's performance is compared with three mainstream meta-heuristics and four advanced algorithms on four necessary test cases. The extensive analysis and recorded results indicate that the proposed method outperforms these algorithms in terms of the accuracy of the solution and convergence speed. Finally, we apply the developed method to four well-known engineering design problems (welded beam design problem; cantilever beam design; I-beam design; and multiple disk clutch brake) to validate the algorithm's effectiveness for some constrained challenge. The results show that our algorithm has significant advantages in solving practical problems with constraints and unknown search spaces. [ABSTRACT FROM AUTHOR]

• A reanalysis theory method based on the inversion of block matrix based on change threshold. • Quickly obtain responses with different accuracy after the structure is modified according to the initial analysis. • The change threshold can control the accuracy and calculation time of the reanalysis results. In the mechanical design industry, it is very time-consuming to convert actual engineering design problems into finite element models, and it is repeatedly modified during the product design process. Each time the structure is modified, computer simulation analysis is repeated, and the product development cycle becomes longer. Therefore, in this paper, a re-analysis theoretical method based on the inversion of the block matrix based on the change threshold is proposed to quickly obtain responses with different accuracy after the structure is modified according to the initial analysis. By modifying the size of the change threshold, the accuracy and calculation time of the reanalysis results are controlled. This reanalysis method shortens a lot of calculation time under the premise of controllable response accuracy. In this paper, numerical calculations are given to show the accuracy of the response under different thresholds, and the efficiency of this method is proved by the finite element model under the same accuracy. [ABSTRACT FROM AUTHOR]

This paper presents the slope dynamic response of jointed rock slopes containing three groups of typical joints and analyzes the effect of input harmonic frequency and joint density on the peak horizontal acceleration (PGA) of the slope surface under vertically impinging SV wave (shear vertical wave) excitation. First, the dynamic response of the slope surface of the bedding slope was investigated with a large-scale shaking table test, and the reliability of the numerical model was verified by the physical modeling. Then, a series of jointed rock slope models with different joint densities were established based on the three-dimensional discrete element software 3DEC. It is found that the natural frequency f n of the jointed slope decreases with the increase of joint density. The effect of excitation frequency f on the slope surface dynamic response of the jointed slope is stronger than that of joint density. The closer the f is to the f n , the stronger the slope surface and slope crest dynamic response is. Notably, taking f n as the critical value of f , the slope surface dynamic amplification mode of jointed slope can be divided into two types: when f ≤ f n , the acceleration amplification factor of X-direction (AAF-X) of the slope surface amplifies monotonically with increasing elevation; when f > f n , the AAF-X of the slope surface shows a fluctuated amplification pattern with the increase of elevation. The results of this paper show that in the seismic design of slope engineering, the influence of site conditions on the frequency spectrum characteristics of ground motion should be considered, and then the optimal design should be carried out. • Input frequency mainly controls the amplification effect on the slope surface. • Increase in joint density causes a decrease of the natural frequency of the slope. • Input frequency near the natural frequency makes the amplification effect strongest. • Input frequency divides seismic response of a jointed slope surface into two forms. [ABSTRACT FROM AUTHOR]

In this study we provide a general review of research into district cooling. District cooling systems and services (DCS) are increasingly widely deployed and there is an associated increase in the rate of scientific production (research papers published) on the subject. In this paper, to facilitate discussion around the key parameters and issues which matter to the successful deployment of DCS, we objectively identify the central topics and themes of DCS research. To do see we employ a combination of bibliometric summary analysis, complemented by formal topic classification using a bespoke structural topic model, to inform a comprehensive literature review and summary. In doing so we verify the structure of existing research, and the spread of system design and engineering considerations that have been prominent in research to date. Moreover we are able to confirm some absences within the literature. With this, our study provides both a valuable overview of the early research into DCS, and also highlights potential research priorities for researchers planning to work on the topic. • District cooling systems (DCS) are widely used with a growing quantity of research. • In this paper, we objectively identify the central topics and themes of DCS research. • We use bibliometrics and topic classification using a structural topic model. • We present the structure of existing research, and absences within the literature. • We unveil potential research priorities for researchers planning to work on the topic. [ABSTRACT FROM AUTHOR]

Grey prediction evolutionary algorithm (GPE) is an emerging category of meta-heuristic algorithm based on mathematical model. It generates offspring by predicting the macroscopic evolutionary trend of population series. On the contrary, the mining of local evolutionary trend are flawed. To address this imperfection, this paper introduces a quadratic function as a surrogate model to mine the local evolutionary trend of population series for the first time. Thereby an improved grey prediction evolutionary algorithm called grey prediction evolutionary algorithm with a surrogate model based on quadratic interpolation (GPE-QI) is designed. The surrogate model based on quadratic interpolation is regarded as an external auxiliary tool to mine the local evolutionary trend of population series by using currently superior individuals. Through utilizing the mined local trend information, a donor population closer to the optimal solution is formed to improve the prediction direction of the algorithm. The performance of GPE-QI is tested on CEC2019, CEC2020 benchmark functions and six engineering design problems. The experimental results demonstrate the stronger competitiveness of GPE-QI to well-established algorithms in terms of solving accuracy and convergence rate. If this paper is accepted, MATLAB codes associated with this paper will be uploaded to https://github.com/Zhongbo-Hu/Prediction-Evolutionary-Algorithm-HOMEPAGE. • Improvement can be made by enhancing local search of grey prediction evolution. • Mine local evolutionary trend of population series by quadratic interpolation. • Construct a surrogate model by using the local evolutionary trend. • Design an improved grey prediction evolutionary algorithm with a surrogate model. • The proposed algorithm is more competitive than the well-established. [ABSTRACT FROM AUTHOR]

Large language model (LLM) is an important direction in the development of AGI, but its technology is still in rapid change, and its capabilities still have obvious deficiencies and imbalances, with persistent problems such as hallucination, value non-alignment, weak specialization, and black-box effect. In this case, how to apply LLM to different professional fields and develop high-quality AIGC industry applications has become a great challenge for ISVs. Building AIGC industry applications based on LLM is not simply a matter of functional realization. Although researchers and open-source communities have proposed numerous application development frameworks or tool components, there is a lack of overall architecture design for systems engineering and a lack of discussion on theories and methods of LLM application development in large-scale industry domains, such as healthcare, government affairs, finance, and media. This paper analyzes the basic ideas of LLM industry applications development, defines the functional requirements and feature requirements of LLM industry applications, puts forward the concept of Large Language Model Systems Engineering (LLM-SE), and develops an AI assisted clinical risk prediction system for amyloidosis disease based on the architecture of LLM-SE, which adopt knowledge engineering, quality engineering, etc., and verifies the LLM-SE development architecture and methodology. • This paper proposes the concept of large language model systems engineering (LLM-SE). • This paper proposes and defines the feature requirements for AIGC industry applications. • This paper proposes a framework for large language model systems engineering. • This paper realizes a clinical risk prediction system for amyloidosis based on LLM-SE. [ABSTRACT FROM AUTHOR]

In recent years the role of design has been expanding to tackle increasingly diverse and pressing societal challenges, known as 'wicked problems'. However, little research exists that explores the role of design in developing and facilitating solutions to a major reoccurring wicked problem: sectoral transitions. Therefore this paper explores the role of design in facilitating societally required sectoral transitions through business- and governance-model innovation. The results of 28 semi-structured interviews, led to the development of a new overarching design approach, which is the adaptation of the existing design innovation and business model innovation approaches. This new design approach named 'sectoral transition design', exemplifies the need for designers to adapt their existing approach to creating individual product or service solutions for businesses and government and deliver solutions capable of providing societal-level solutions that can then subsequently be converted to business- and governance-model solutions to facilitate necessary sectoral transitions. • Paper addresses a major recurring wicked problem that is currently facing society: sectorial transitions. • This paper proposes design to facilitate sectorial transitions through innovation in business and governance models. • The study employed 28 semi-structured interviews to inform the development of the new overarching design approach. • This approach emphasizes the need for designers to create solutions capable of providing societal-level solutions • Practical implications for designers, businesses and governments are provided. [ABSTRACT FROM AUTHOR]

Although DX initiatives have been mandated since the 2010s, the design of digital information systems can be influenced by business and technology aspects and have a significant impact on the attractiveness of services, but there is not enough design science research in this area. In addition, the design of information systems often consists of multiple people with diverse capabilities, and methods that effectively utilize diverse perspectives are needed to design attractive solutions. The authors are conducting research on the application of support systems in engineering (CDSS) to methodologies that support design (conceptual design) in the information systems field. Based on the results of applying CDSS to the digital field, this paper defines a new CDSS methodology that incorporates new "storytelling" and "digital business strategy" in the problem understanding phase to derive solutions to human and economic requirements. We will also incorporate World Cafe as a team discussion method into the storytelling and define CDSS for DX application design process. [ABSTRACT FROM AUTHOR]

• A comprehensive review of various artificial roughness in SAH is presented. • 72 distinct rib combinations in SAH are optimized using Machine Learning (ML). • Developed ML model predicts Nu and f with an average deviation of <3%. • Second law analysis of various ribbed triangular duct SAHs is presented. • Design recommendations of triangular SAH for future research are detailed. This paper presents a comprehensive review of various kinds of distinct artificial roughness employed in rectangular and triangular duct solar air heaters to aid prospective researchers in finding a critical gap in the domain of solar air heaters. A Machine Learning (ML) model is developed using 72 distinct rib combinations compiled to 454 datasets and trained using an Artificial Neural Network (ANN) to predict the performance of ribbed triangular duct Solar Air Heater (SAH). The developed ML model predicts the data with an average deviation of <3%. Owing to reasonably accurate predictions, the same could be increased when more cases (geometric or operating parameters) are added to the databases by retraining the ANN. Further, a second law analysis of the rib configurations features collector efficiency and entropy generation variation with Re for various rib parameters. For the Re range of 4000 to 18000, optimum parameters such as rib height, pitch, chamfer angle, and inclinations are obtained for triangular duct SAH. This could help design engineers obtain the performance parameters of ribbed triangular duct SAH with other artificial roughness designs, possibly with a combination of different geometrical and operating parameters, without having to perform tests. [ABSTRACT FROM AUTHOR]

Design, development, productization, and applications of advanced product concepts are pressing for higher multifunctionality, resilience, and maximization of available resources equitably to meet the growing and continuing demands of global customers. These demands have further accelerated during the recent COVID-19 pandemic and are continuing to be a challenge. Engineering designs are one of the most effective ways to endow products with functions, resilience, and sustainability. Biology, through millions of years of evolution, has met these acute requirements under severe resource and environmental constraints. As the manufacturing of products is reaching the fundamental limits of raw materials, labor, and resource constraints in terms of availability, accessibility, and affordability, new approaches are a call to action to meet these challenges. Understanding the designs in biology is an attractive, novel, and desired frontier for learning and implementation to meet this call to action. This is the focus of the paper discussed through examples for convergence of fundamental engineering design concepts and the lessons learned and applied from biology. [ABSTRACT FROM AUTHOR]

Modern version control strategies are highly capable at supporting the management of virtual artefacts. The process of developing a new product, however, is not limited to virtual artefacts. Today's fast-paced industrial processes require a diverse range of both virtual and physical artefacts to explore, refine, and evaluate designs. These virtual and physical artefacts are interrelated, and the information they embody, the knowledge they generate, and the transfer of learning between are fundamental to the design history. Consequently, there is a requirement to capture and curate both virtual and physical artefacts, iterations thereof, and the interrelationships between. The Digital Twin paradigm couples physical and virtual artefacts throughout the product life-cycle, providing a means to capture an evolving design irrespective of the medium in which the designer is working. Recent literature has, however, raised questions about the concept of a Digital Twin early in the product life-cycle when the design in question is conceptual (a cognitive model) rather than physical or virtual. This paper reflects on the challenges of implementing Digital Twin-based version control in the early-stage of new product development, moving towards integrated version control of virtual, physical and cognitive models/artefacts. Firstly, by presenting an argument that current design practices capture cognitive models through stakeholder creation and evaluation of physical and virtual boundary objects, the ambiguity surrounding conceptual design and the Digital Twin is addressed. Secondly, the principles of the Digital Twin and current version control strategies are reviewed to determine how one can maintain digital/physical synchronicity as a design evolves. Finally, this paper reflects on the implementation of such an approach and the proposed future work. [ABSTRACT FROM AUTHOR]

Manufacturing processes and associated supply chains are a recognised source of carbon emissions. In part these emissions are related to the design of the product itself. For example, decisions surrounding the selection of materials have a high impact on emissions and hence the embedded carbon in manufactured products. While there are tools that support the analysis of designs from environmental perspectives, they tend to require near complete design descriptions that are only available later in the design and development process when time and scope for change is limited, e.g., by scheduling and cost constraints. Further, there are often trade-offs to be made. For example, decisions related to the selection of materials impacts the embedded carbon of resources needed to manufacture a product but may also have a knock-on effect on transport and associated carbon emissions. This paper reports early work exploring the feasibility of establishing engineering design tools that are suitable for use early in the design process when the design definition is incomplete and there is scope for exploring a wider range of design options. An illustrative case study was used to consider the quantification of carbon costs associated with material selection and associated transportation. Discrete event simulation models were derived from early design descriptions coupled with a range of alternative material and supply chain scenarios. Early results are promising in that they can be used to compare carbon consequences of alternative design directions. [ABSTRACT FROM AUTHOR]