Design Phase Research Articles

Transformation of Early Reading Ability Through Smart Wheel Media Based on the TGT Learning Model

This study introduces the Kintar/Smarwheel learning media, a one meter diameter Smart Wheel media that was developed using the Team Game Tournament (TGT) learning model to improve the initial reading skills of grade 1 elementary school students. The problem of urgency is highlighted by the low reading ability of the average grade 1 child, encouraging the development of effective learning media. This research aims to develop, validate and evaluate the effectiveness of Kintar in improving student learning outcomes in early reading. This study uses a development approach, integrating the product design phase, feasibility validation by media and materials experts, and effectiveness testing through small and large scale trials involving grade 1 students from SDN Purwoyoso 03, Semarang City. Feasibility assessments by experts confirmed a high degree of suitability for educational use, with significant improvements in student learning outcomes observed during the pilot. The small scale trial showed an average increase from pretest to posttest scores from 46.67 to 70.00, with a significant difference of 23.33. The large-scale trial showed a mean increase from 61.47 to 81.47, with a striking difference of 20.00. The N-Gain test results show a moderate impact, with values ​​of 0.3959 and 0.5298 for small and large scale tests, respectively. This study concludes that Kintar, integrated with the TGT learning model, is a powerful educational tool for improving early reading skills. Positive feedback from students and teachers underscores its effectiveness in generating engagement and improving learning outcomes in the classroom.

Strategic Effectiveness: Search - Solve - Create - Participate - Evaluate - in the Middle School Students’ Achievement on Arabic

This study aims to determine the effectiveness of various strategies—search, solve, create, participate, and evaluate—in improving middle school students' achievement in Arabic. The experimental group was designed with partial control, following quasi-experimental design phases to meet research objectives. Before implementing the experiment, the researcher ensured comparable competencies between the two groups, constructed an Arabic achievement test, and confirmed its psychometric qualities. After implementation, the researcher also conducted additional tests.The study discovered that using the search-solve-create-participate-evaluate strategy in teaching Arabic raises academic achievement among sixth-grade middle school students. The experimental group outperformed the control group in the Arabic language achievement test. This demonstrates the effectiveness of the search-solve-create-participate-evaluate strategy in enhancing middle school students' Arabic language achievement.

Insight into profiled CNT/polymer interphase: A molecular dynamic simulation study of load transfer and shock response

In this paper, by utilising molecular dynamic simulations, profiled carbon nanotubes (CNT), represented by CNT containing bead and spiral structure, were built from warping graphene layers with carefully introduced defects. The tensile behaviour of profiled CNTs, pulling and shock response of profiled CNTs within the polyamide matrix were investigated and compared to the corresponding conventional CNT. The result indicates that as mechanically interlocked with the matrix, profiled CNT could effectively relieve the stress concentration during load transfer by distributing the stress into a larger part of the matrix. In this case, a more efficient load transfer could be achieved, thus contributing to the mechanical performance of the composite without modification of the chemical structure. However, the profiling geometry, which is shaped by defects, will introduce stress concentration within the profile CNTs when subject to a tensile load. The stress concentration may not only deteriorate the tensile performance of CNTs, such as ultimate load at break and modulus but also result in an earlier deformation. In this case, care should be taken during the design phase of the profiled CNT. For shocking responses, profiled CNTs were capable of constraining the local chain move thus contributing to the integrity of the composite system during shockwave propagation.

Is Spartina alterniflora eradication project in Chongming Island a nature-based solution?

Invasive species profoundly impact ecosystems globally, not only threatening biodiversity by displacing native species but also disrupting ecological balances and imposing significant economic burdens. This has led countries to actively combat these pervasive threats. In China, Spartina alterniflora, an invasive species, has taken over more than 70 % of the coastal zone in just 50 years, especially in salt marsh. This study aims to assess the Spartina alterniflora eradication project in Dongtan of Chongming Island, Shanghai, based on the IUCN Global Standard for Nature-based Solutions (NBS). To ensure the comprehensiveness and diversity of the assessment process, stakeholders with diverse backgrounds were invited. The Dongtan project was qualitatively evaluated using the IUCN self-assessment tool for its adherence to the IUCN NBS Standard, identifying its strengths, weaknesses, improvement areas, and contributions to the national eradication campaign. The results show that the Dongtan Project closely aligns with the NBS standard, achieving an 88 % match, and demonstrates excellence in addressing societal challenges, enhancing biodiversity, and offering multiple benefits. Nevertheless, improvements can be made in Economic Feasibility (Criterion 4), Inclusive Governance (Criterion 5), and Balance Trade-offs (Criterion 6). The study underscores the importance of employing NBS standards for self-assessment in the project design phase, which facilitates the identification and refinement of potential design issues. The success of the Dongtan Project, exemplified by its effective Spartina alterniflora eradication strategies, serves as a compelling model for similar national campaigns.

Flat-top plasma operational space of the STEP power plant

Abstract STEP is a spherical tokamak prototype power plant that is being designed to demonstrate net electric power. The design phase involves the exploitation of plasma models to optimise fusion performance subject to satisfying various physics and engineering constraints. A modelling workflow, including integrated core plasma modelling, MHD stability analysis, SOL and pedestal modelling, coil set and free boundary equilibrium solvers, and whole plant design, has been developed to specify the design parameters and to develop viable scenarios. The integrated core plasma model JETTO is used to develop individual flat-top operating points that satisfy imposed criteria for fusion power performance within operational constraints. Key plasma parameters such as normalised beta, Greenwald density fraction, auxiliary power and radiated power have been scanned to scope the operational space and to derive a collection of candidate non-inductive flat-top points. The assumed auxiliary heating and current drive is either from electron cyclotron systems only or a combination of electron cyclotron and electron Bernstein waves. At present stages of transport modelling, there is a large uncertainty in overall confinement for relevant parameter regimes. For each of the two auxiliary heating and current drive systems scenarios, two candidate flat-top points have been developed based on different confinement assumptions, totalling to four operating points. A lower confinement assumption generally suggests operating points in high-density, high auxiliary power regimes, whereas higher confinement would allow access to a broader parameter regime in density and power while maintaining target fusion power performance.

Patient Perspectives on a Digital Assistant for Medication Reconciliation: An Interview Study Comparing Socioeconomic Groups.

Medication reconciliation, the process of documenting a patient's medication, is currently a time-consuming and labor-intensive process. To make medication reconciliation more efficient, digital assistants (DAs) offer a promising solution. Especially since human-like digital interfaces tend to be appreciated by more vulnerable populations such as patients in a low socioeconomic position (SEP). Despite the potential of DAs for low-SEP populations in particular, these groups are often not involved during the development and design phase of such digital health interventions. This exclusion may explain the lower adoption rates of digital interventions among low-SEP patients and exacerbate the so-called digital divide. We explored the perceptions and needs of patients across the SEP gradient using a participatory design approach. Patients of low-, middle-, and high-SEP backgrounds were asked to interact with a DA developed for this study and were interviewed afterward. A thematic analysis revealed seven themes regarding design, input method, comprehensibility, privacy concerns, benefits, the intention to use, and reassurance. Overall, patients were afraid to make mistakes in their medication entries and therefore valued feedback from the system or caregivers. Low-SEP patients specifically seemed to value more structured input methods when using the DA, while high-SEP patients emphasized the importance of a secure environment for the DA and sought clarity about its functionalities. Our study demonstrates the importance of involving patients across the socioeconomic gradient when developing a digital health tool and offers concrete recommendations for inclusive DA design for researchers and developers.

Cognitive characteristics of concept derivation phase in environmental art design: A epistemic network analysis of design scheme construction process

Currently, there is a lack of in-depth research on the associative evaluation and developmental trajectory of the environmental design scheme construction process. Epistemic Network Analysis (ENA) is an analytical method for describing individual or group cognitive framework patterns, which can dynamically represent the cognitive characteristics of designers in the design process. In this paper, through experimental research, ‘Discover, Define, Develop’ are taken as coding dimensions for the design scheme process, and ENA is used to identify network relationships between cognitive elements of different groups, visually expressing the cognitive characteristics of the design scheme construction process. Excellent groups demonstrate cognitive patterns of divergence to convergence, and in the ideation phase, they can deeply contemplate specific design modules. Strategies are proposed from the perspectives of design education, and selection of design thinking paths to assist in cultivating innovative thinking in environmental art design.

Applying Engagement Marketing And Human-Centered Design to Cocreate a Digital Decision Support Tool for Research Participation with LGBTQIA+ Community Members.

We used engagement marketing and human-centered design principles to cocreate a digital decision support tool for research participation with LGBTQIA+ community members to help them make an informed decision about joining the All of Us Research Program. Building on results from the research phase, we conducted eight problem validation and solutioning workshops with 48 LGBTQIA+ community members. Community members validated barriers to engagement with All of Us and brainstormed 47 potential digital solutions. We developed potential solutions into 27 concepts (descriptive text and visual storyboards) and assessed acceptability, appropriateness, feasibility, and engagement in a set of 10 concept testing workshops with 57 community members. We developed one of the highest rated concepts, the "Decide Later Tool," into a prototype and tested it with 45 LGBTQIA+ community members and 14 community advisory group members to assess acceptability, appropriateness, feasibility, usability, and engagement. Prototype testing participants indicated that the tool provides information to help with decision making, provides a clear value or benefit to them, was designed for someone like them, provides the right amount of information, and is easy to use; they also offered constructive feedback to improve it. Across the design and development phases, community members indicated that the process of engaging them demonstrated integrity, competence, dependability, trust, and collaboration; fostered a sense of connection to All of Us; and will enhance future engagement with All of Us. Our next steps are to develop the prototype into a fully functioning web tool and pilot test it in community and health care settings.

Unlocking inherent values of manufacturing metadata through digital characteristics (DC) alignment

Data form the backbone of manufacturing sciences, initiating a revolutionary transformation in our understanding of manufacturing processes by unravelling complex scientific patterns embedded within them. Digital characteristics (DC) is defined as a strategic framework mapping the manufacturing metadata and integrates essential information across the entire spectrum spanning from the design, manufacturing, and application phases of manufactured products. By carrying these inherent distinctive features, DC serves as the ‘DNA’ for every manufacturing process. Through enormous experimental and simulation efforts, a digital characteristics space (DCS) was established to provide access to the up-to-date and information-rich DC repository containing over 140 manufacturing processes. In digital manufacturing, sensing networks play a pivotal role in metadata acquisition, contributing nearly 2000 petabytes of metadata annually. However, an overwhelming majority-nearly 100 %-of the data collected through sensing networks can be categorised as ‘fragmental data’, encompassing only a few (e.g., 1–2) essential pieces of information. Moreover, the current absence of efficient metadata identification methods presents an emerging and critical need to enable industry to unlock the full potential of manufacturing metadata. To this end, the authors of the present paper developed a physics-based alignment filter, considering DCS as an alignment reference similar to the ‘GenBank’. Specifically, the origins of naturally unattributed fragmental data were identified with an overall probability exceeding 82 % with a minimum length of 10 data points. The probability increased to 99 % when aligning the fragmental data with length of 100 data points. This was realised by comparing the thermo-mechanical DC of fragmental data with their counterparts stored in the DCS. Subsequently, we analysed the distinct DC of this identified manufacturing process to facilitate digitally-enhanced research. This study introduces a pioneering methodology developed to extract latent values embedded in manufacturing metadata derived from unattributed fragmental data. By revolutionising insights into advanced manufacturing sciences, our work provides an enabling approach for identifying and leveraging fragmental data sourced from sensing networks. This empowers the exploration of manufacturing metadata, promising transformative implications for the field.

Open-Source Data Formalization through Model-Based Systems Engineering for Concurrent Preliminary Design of CubeSats

Market trends in the space sector suggest a notable increase in satellite operations and market value for the coming decade. In parallel, there has been a shift in the industrial and academic sectors from traditional Document-Based System Engineering to Model-based systems engineering (MBSE) combined with Concurrent engineering (CE) practices. Due to growing demands, the drivers behind this change have been the need for quicker and more cost-effective design processes. A key challenge in this transition remains to determine how to effectively formalize and exchange data during all design stages and across all discipline-specific tools; as representing systems through models can be a complex endeavor. For instance, during the Preliminary design (PD) phase, the integration of system models with external mathematical models for simulations, analyses, and system budgeting is crucial. The introduction of CubeSats and their standard has partly addressed the question of standardization and has aided in reducing overall development time and costs in the space sector. Nevertheless, questions about how to successfully exchange data endure. This paper focuses on formalizing a CubeSat model for use across various stages of the PD phase. The entire process is conducted with the exclusive use of open-source tools, to facilitate the transparency of data integration across the PD phases, and the overall life cycle of a CubeSat. The paper has two primary outcomes: (i) developing a generic CubeSat model using Systems modeling language (SysML) that includes data storage and visualization through the application of Unified modeling language (UML) stereotypes, streamlining in parallel information exchange for integration with various simulation and analysis tools; (ii) creating an end-to-end use case scenario within the Nanostar software suite (NSS), an open-source framework designed to streamline data exchange across different software during CE sessions. A case study from a theoretical academic space mission concept is presented as the illustration of how to utilize the proposed formalization, and it serves as well as a preliminary validation of the proposed formalization. The proposed formalization positions the CubeSat SysML model as the central data source throughout the design process. It also supports automated trade-off analyses by combining the benefits of SysML with effective data instantiating across all PD study phases.

An approximate decoupled reliability-based design optimization method for efficient design exploration of linear structures under random loads

Reliability-based design optimization (RBDO) provides a promising approach for achieving effective structural designs while explicitly accounting for the effects of uncertainty. However, the computational demands associated with RBDO, often due to its nested loop nature, pose significant challenges, thereby impeding the application of RBDO for decision-making in real-world structural design. To alleviate this issue, an approximate decoupled approach is introduced for a class of RBDO problems involving linear truss structures subjected to random excitations, with the failure event defined by compliance. This contribution aims to provide an approximate but efficient way for design exploration to facilitate decision-making during the initial design phase. Specifically, the proposed approach converts the original RBDO problem into a deterministic optimization problem through a modest number of reliability analyses by the probability density evolution method (PDEM). Once the deterministic optimization problem is obtained, the solution of the whole RBDO problem can be obtained by solving this equivalent problem without further reliability analysis, resulting in notable enhancement in terms of computational efficiency. In this way, this contribution expands the frontier of application of the operator norm theory within the RBDO framework. Numerical examples are conducted to illustrate the effectiveness and capabilities of the proposed approach.

Indoor Environment Design and Energy Saving Analysis of Sustainable Development Integrated with Green Building

Modern architectural design has gradually distanced itself from the actual living needs of urban residents in the process of pursuing the integration of architecture and nature. To achieve the perfect combination of sustainable ecological concepts and effective energy utilization, green buildings have become an actively pursued design concept. Unlike relying solely on high-tech means, the core goal of green buildings is to build an environmentally friendly building environment by achieving sustainable and efficient utilization of energy and resources. In the design phase, green buildings should focus on functionality and economy, and be tailored to the local economic conditions, regional characteristics, natural resources, and climate conditions of the building's location to create green buildings with unique architectural and regional characteristics. This article endeavors to furnish both theoretical underpinnings and practical directives for the indoor environment design and energy conservation efforts of green buildings. By delving into the pivotal role of indoor environments as an essential architectural component, it integrates sustainable development principles with green building practices and delves into the intricate relationship between indoor environment design and energy efficiency, thus offering valuable insights and guidance for achieving sustainable and energy-efficient indoor spaces. In this process, this article examines the energy and resource utilization benefits that green building design can achieve, as well as the specific impact of indoor environment improvement on the quality of life of residents. Through an in-depth analysis of these aspects, this article aims to provide substantial contributions to achieving the sustainable development goals of green buildings. The experimental comparison results show that in terms of natural ventilation design, compared to mechanical ventilation, the proposed scheme can achieve an annual energy cost savings of 20%.

Optimizing the cost of the STEP programme.

The Spherical Tokamak for Energy Production (STEP) programme is a world-leading fusion power plant programme that has embedded a cost conscience in its design from the early phases. This firmly addresses the attitude of cost complacency of which many major infrastructure projects have historically been accused. While a detailed and highly accurate whole life cycle cost analysis is not possible, or even valuable, during the conceptual design stage, this early design phase is still the most critical programme phase where a focus on costs can drive longer term reductions and impact whole life cycle costs at the high level. Consequently, appropriate estimating methods for these early-stage designs and lessons learned from other industries are used to inform design decisions and ensure cost is part of the overall option analysis. Hence, while the overall programme cost estimate is too immature to be a reliable indicator for the final programme costs, significant effort has been undertaken to understand the major cost drivers and take action to make the STEP design as cost-effective as possible. This article is part of the theme issue 'Delivering Fusion Energy - The Spherical Tokamak for Energy Production (STEP)'.

Design of a PID Controller for Microbial Fuel Cells Using Improved Particle Swarm Optimization

The microbial fuel cell (MFC) is a renewable energy technology that utilizes the oxidative decomposition processes of anaerobic microorganisms to convert the chemical energy in organic matter, such as wastewater, sediments, or other biomass, into electrical power. This technology is not only applicable to wastewater treatment but can also be used for resource recovery from various organic wastes. The MFC usually requires an external controller that allows it to operate under controlled conditions to obtain a stable output voltage. Therefore, the application of a PID controller to the MFC is proposed in this paper. The design phase for this controller involves the identification of three parameters. Although the particle swarm optimization (PSO) algorithm is an advanced optimization algorithm based on swarm intelligence, it suffers from issues such as unreasonable population initialization and slow convergence speed. Therefore, this paper proposes an improved particle swarm algorithm based on the Golden Sine Strategy (GSCPSO). Using Circle chaotic mapping to make the distribution of the initial population more uniform, and then using the Golden Sine Strategy to improve the position update formula, not only improves the convergence speed of the population but also enhances convergence precision. The GSCPSO algorithm is applied to execute the described design process. The results of the simulation show that the designed control method exhibits smaller steady-state error, overshoot, and chattering compared with sliding-mode control (SMC), backstepping control, fuzzy SMC (FSMC), PSO-PID, and CPSO-PID.

Novel airfoil for improved supersonic aerodynamic performance

PurposeThis study aims to validate the linear flow theory with computational fluid dynamics (CFD) simulations and to propose a novel shape for the airfoil that will improve supersonic aerodynamic performance compared to the National Advisory Committee for Aeronautics (NACA) 64a210 airfoil.Design/methodology/approachTo design the new airfoil shape, this study uses a convex optimization approach to obtain a global optimal shape for an airfoil. First, modeling is conducted using linear flow theory, and then numerical verification is done by CFD simulations using ANSYS Fluent. The optimization process ensures that the new airfoil maintains the same cross-sectional area and thickness as the NACA 64a210 airfoil. This study found that an efficient way to obtain the ideal airfoil shape is by using linear flow theory, and the numerical simulations supported the assumptions inherent in the linear flow theory.FindingsThis study’s findings show notable improvements (from 4% to 200%) in the aerodynamic performance of the airfoil, especially in the supersonic range, which points to the suggested airfoil as a potential option for several fighter aircraft. Under various supersonic conditions, the optimized airfoil exhibits improved lift-over-drag ratios, leading to improved flight performance and lower fuel consumption.Research limitations/implicationsThis study was conducted mainly for supersonic flow, whereas the subsonic flow is tested for a Mach number of 0.7. This study would be extended for both subsonic and supersonic flights.Practical implicationsConvex optimization and linear flow theory are combined in this work to create an airfoil that performs better in supersonic conditions than the NACA 64a210. By closely matching the CFD results, the linear flow theory's robustness is confirmed. This means that the initial design phase no longer requires extensive CFD simulations, and the linear flow theory can be used quickly and efficiently to obtain optimal airfoil shapes.Social implicationsThe proposed airfoil can be used in different fighter aircraft to enhance performance and reduce fuel consumption. Thus, lower carbon emission is expected.Originality/valueThe unique aspect of this work is how convex optimization and linear flow theory were combined to create an airfoil that performs better in supersonic conditions than the NACA 64a210. Comprehensive CFD simulations were used for validation, highlighting the optimization approach's strength and usefulness in aerospace engineering.

Advancing Circular Buildings: A Review of Building Strategies for AEC Stakeholders

The uptake of a circular economy (CE) in the building sector is challenging, primarily due to the complexity associated with the design process and the dynamic interaction among architects, engineers, and construction (AEC) stakeholders. The standard and typical design process and construction methods raise concerns about building life cycles. Buildings should not only fulfill current needs, but one also needs to consider how they will function in the future and throughout their lifetime. To address these complexities, early planning is required to guide designers in holistically applying systems thinking to deliver CE outcomes. This paper outlines a critical review of CE implementation in buildings, with a proposed trifecta of approaches that significantly contribute to the development of circular buildings (CBs). The findings outline a proposed visualized framework with a conceptual formula that integrates CE design strategies to simplify and enhance AEC stakeholders’ perception of the circularity sequence in buildings. By strategically integrating loop-based strategies with the value retention process (VRP) and design for X (DFX) strategies, along with efficient assessment tools and technologies, it becomes feasible to embrace a CE during the design phase. The outcome of this review informs AEC stakeholders to systematically and strategically integrate the critical dimensions of a CE throughout the building life cycle, striking a balance between environmental concern, economic value, and future needs.

A Cooperative Game Approach for Optimal Design of Shared Energy Storage System

The energy sector’s long-term sustainability increasingly relies on widespread renewable energy generation. Shared energy storage embodies sharing economy principles within the storage industry. This approach allows storage facilities to monetize unused capacity by offering it to users, generating additional revenue for providers, and supporting renewable energy prosumers’ growth. However, high investment costs and long payback periods often hinder the development of battery storage. To address this challenge, we propose a shared storage investment framework. In this framework, a storage investor virtualizes physical storage equipment, enabling prosumers to access storage services as though they owned the batteries themselves. We adopt a cooperative game approach to incorporate storage sharing into the design phase of energy systems. To ensure a fair distribution of cooperative benefits, we introduce a benefit allocation mechanism based on contributions to energy storage sharing. Utilizing realistic data from three buildings, our simulations demonstrate that the shared storage mechanism creates a win–win situation for all participants. It also enhances the self-sufficiency and self-consumption of renewable energy. This paper provides valuable insights for shared storage investors regarding optimal design and benefit allocation among multiple stakeholders.

Patient and public involvement and engagement in the ASCEND PLUS trial: reflections from the design of a streamlined and decentralised clinical trial

IntroductionASCEND PLUS is a randomised controlled trial assessing the effects of oral semaglutide on the primary prevention of cardiovascular events in around 20,000 individuals with type 2 diabetes in the UK. The trial’s innovative design includes a decentralised direct-to-participant invitation, recruitment, and follow-up model, relying on self-completion of online forms or telephone or video calls with research nurses, with no physical sites. Extensive patient and public involvement and engagement (PPIE) was essential to the design and conduct of ASCEND PLUS.AimTo report the process and conduct of PPIE activity in ASCEND PLUS, evaluate effects on trial design, reflect critically on successes and aspects that could have been improved, and identify themes and learning relevant to implementation of PPIE in future trials.MethodsPPIE activity was coordinated centrally and included six PPIE focus groups and creation of an ASCEND PLUS public advisory group (PAG) during the design phase. Recruitment to these groups was carefully considered to ensure diversity and inclusion, largely consisting of adults living with type 2 diabetes from across the UK. Two members of the PAG also joined the trial Steering Committee. Steering Committee meetings, focus groups, and PAG meetings were conducted online, with two hybrid workshops to discuss PPIE activity and aspects of the trial.ResultsPPIE activity was critical to shaping the design and conduct of ASCEND PLUS. Key examples included supporting choice for participants to either complete the screening/consent process independently online, or during a telephone or video call interview with a research nurse. A concise ‘initial information leaflet’ was developed to be sent with the initial invitations, with the ‘full’ information leaflet sent later to those interested in joining the trial. The PAG reviewed the content and format of participant- and public-facing materials, including written documents, online screening forms, animated videos, and the trial website, to aid clarity and accessibility, and provided input into the choice of instruments to assess quality of life.ConclusionsPPIE is integral in ASCEND PLUS and will continue throughout the trial. This involvement has been critical to optimising the trial design, successfully obtaining regulatory and ethical approval, and conducting the trial.

Multi-objective optimization of cable-road layouts in smart forestry

ABSTRACT Current cable-road layouts for timber harvesting in steep terrain are often based on either manual planning or automated layouts generated from low-resolution GIS data, limiting potential benefits and informed decision-making. In this paper, we present a novel approach to improve cable-road design using multi-objective optimization based on realistic cable-road representations. We systematically compare the effectiveness of single-objective and multi-objective optimization methods for generating layouts using these representations. We implement and evaluate the performance of a weighted single-objective approach, the AUGMECON2 and NSGA-II multi-objective methods in comparison to a layout manually created by a forestry expert, taking into account installation costs, harvesting volumes, residual stand damage and lateral yarding workload. In addition to implementing the first linear programming multi-objective optimization for realistic cable-road representations by adapting AUGMECON2, we also present the first implementation of a multi-objective genetic algorithm (NSGA-II) with simulated annealing for this purpose and evaluate their respective strengths. We find that the use of multi-objective optimization provides advantages in terms of cost-effective, balanced and adaptable cable-road layouts while allowing economic and environmental considerations to be incorporated into the design phase.

Research and engineering application of layout optimization for lockbolt structures in railway wagons considering multidimensional failure modes based on MSNSGA-III

The lockbolt structure is essential in railway wagons, and a scientific lockbolt layout can ensure uniform load distribution, thereby preventing failure. However, current engineering lacks layout optimization methods that address multidimensional failure modes. This paper presents a new lockbolt structure layout optimization method based on submodel, parametric models, and a multi-strategy integrated NSGA-III (MSNSGA-III), adhering to the DVS EFB 3435-2 standard. This method simultaneously optimizes the number and spacing of lockbolts to prevent tensile, bearing, shear, and other static failure modes under specified load conditions. The proposed method was applied during the design phase of a container flatcar. Optimization results indicate that, compared to NSGA-III, this method achieves the best IGD and HV values across multiple complex test functions, demonstrating superior performance in solving complex Pareto front optimization problems. Additionally, the optimized lockbolt structure's safety margins increased by a maximum of 59.81%, passing the full vehicle strength test and significantly enhancing resistance to multidimensional failure modes. These results highlight the method's significant practical application value in addressing the optimization of railway wagon lockbolt structures under complex multidimensional failure modes.