Design Domain Research Articles

Good-Quality mHealth Apps for Endometriosis Care: Systematic Search.

Mobile health (mHealth) apps are increasingly being used by community members to track symptoms and manage endometriosis. In addition, clinicians use mHealth apps for continued medical education and clinical decision-making and recommend good-quality apps to patients. However, poor-quality apps can spread misinformation or provide recommendations that are not evidence-based. Therefore, a critical evaluation is needed to assess and recommend good-quality endometriosis mHealth apps. This study aimed to evaluate the quality and provide recommendations for good quality endometriosis mHealth apps for the community and clinicians. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines informed the search of mHealth apps on the Google Play Store and Apple App Store. The search terms included "endometriosis," "adenomyosis," and "pelvic pain." mHealth apps were eligible if they were (1) related to the search terms, (2) were in the English language, and (3) were available free of cost. Only the free content of the eligible mHealth apps was assessed. ENLIGHT, a validated evaluation tool for mobile and web-based interventions, was used to assess the quality across 7 domains such as usability, visual design, user engagement, content, therapeutic persuasiveness, therapeutic alliance, and general subjective evaluation. mHealth apps with a total score of ≥3.5 were classified as "good" according to the ENLIGHT scoring system and are recommended as good-quality mHealth apps for endometriosis care. In total, 42 mHealth apps were screened, and 19 were included in the quality assessment. A total of 6 good-quality mHealth apps were identified (QENDO, Bearable, Luna for Health, Matilda Health, Branch Health: Pain Management, and CHARLI Health). These apps provided symptom-tracking functions and self-management support. A total of 17 apps were designed for community use, while 2 apps provided a digital endometriosis classification tool to clinicians. Most mHealth apps scored well (≥3.5) in the domains of usability (16/19, 84.2%), visual design (14/19, 73.7%), user engagement (11/19, 57.9%), and content (15/19, 78.9%). Few eHealth websites scored well on therapeutic persuasiveness (6/19, 31.6%), therapeutic alliance (9/19, 47.4%), and general subjective evaluation (6/19, 31.6%). Although time and geographical location can influence the search results, we identified 6 "good-quality" endometriosis mHealth apps that can be recommended to the endometriosis community. mHealth apps designed for community use should evaluate their effectiveness on user's endometriosis knowledge, self-recommended management strategies, pain self-efficacy, user satisfaction, and user quality of life. Digital technology should be leveraged to develop mHealth apps for clinicians that contribute to continued medical education and assist clinical decision-making in endometriosis management. Factors that enhance usability, visual design, therapeutic persuasiveness, and therapeutic alliance should be incorporated to ensure successful and long-term uptake of mHealth apps. PROSPERO CRD42020185475; https://tinyurl.com/384dkkmj.

Operational Design Domain of Automated Vehicles at Freeway Exit Terminals

Operational Design Domain of Automated Vehicles at Freeway Exit Terminals

Social Innovation Perspective on Regional Design and Sustainable Development Research

In today’s world, the development of regional industries and cross-regional cultural integration have brought about environmental damage and cultural erosion. However, there are many shortcomings in the research and countermeasures for the problem, especially in China. The greater participation of the whole society in innovative regional design has a huge impact on the sustainable development of the region. This research aims to provide a more comprehensive understanding framework for regional design and strategic guidance for future research directions and practical paths. We adopted the methods of a literature review and a case analysis to discuss the importance of social cooperation in social innovation from the perspectives of cultural inheritance, community participation, industrial upgrading, and brand building. Based on Professor Kiyoshi Miyazaki’s “Human Culture Land Production Landscape” resource integration model, combined with specific regional goals, five major design domains have been constructed to address five issues. In specific regional design practices, participatory design, value co-creation, and resource integration design methods have been applied. Research has found that these theoretical and practical paths have achieved good results and played a positive role in promoting the Sustainable Development Goals (SDG9 and SDG11).

A Method for Synthesizing Ontology-Based Textual Design Datasets: Evaluating the Potential of Large Language Model in Domain-Specific Dataset Generation

Abstract In engineering disciplines, leveraging generative language models requires using specialized datasets for training or fine-tuning the preexisting models. Compiling these domain-specific datasets is a complex endeavor, demanding significant human effort and resources. To address the problem of domain-specific dataset scarcity, this study investigates the potential of generative large language models (LLMs) in creating synthetic domain-specific textual datasets for engineering design domains. By harnessing the advanced capabilities of LLMs, such as GPT-4, a systematic methodology was developed to create high-fidelity datasets using designed prompts, evaluated against a manually labeled benchmark dataset through various computational measurements without human intervention. Findings suggest that well-designed prompts can significantly enhance the quality of domain-specific synthetic datasets with reduced manual effort. The research highlights the importance of prompt design in eliciting precise, domain-relevant information and discusses the balance between dataset robustness and richness. It is demonstrated that a language model trained on synthetic datasets can achieve a level of performance comparable to that of human-labeled, domain-specific datasets in terms of quality, offering a strategic solution to the limitations imposed by dataset shortages in engineering domains. The implications for design thinking processes are particularly noteworthy, with the potential to assist designers through GPT-4's structured reasoning capabilities. This work presents a complete guide for domain-specific dataset generation, automated evaluation metrics, and insights into the interplay between data robustness and comprehensiveness.

Product Innovation using Rattan in the Production of Furniture Crafts

Producers must continuously adapt and innovate to develop products that address the evolving needs and preferences of their communities, with one crucial requirement being the creation of comfortable and aesthetically pleasing spaces for rest and relaxation. Furniture, as fundamental piece for comfort, play a central role in meeting this need, and their design must strike a balance between functionality and aesthetic appeal. Rattan, a sustainable and versatile material, offers a promising solution for Furniture construction due to its strength and environmental advantages. This study introduces an innovative rattan Furniture design that blends creativity and practicality, presenting a novel approach without compromising quality. The Furniture's structure, composed of rattan rods, is both lightweight and durable, while a marble finish enhances its visual appeal, imparting a dynamic and sophisticated look. The application of dowel construction facilitates easy assembly, obviating the need for complex tools or expertise. Ultimately, the design offers a comfortable and relaxing seating experience, contributing to sustainable and innovative solutions in the domain of leisure furniture design.

Verification of Vulnerable Road User Pre-Crash Scenarios in Vision-Based Safety Applications

<div>Verifying training datasets in vision-based vehicle safety applications is crucial to understanding the potential limitations of detection capabilities that may result in a higher safety risk. Vision-based pedestrian safety applications with crash avoidance technologies rely on prompt detection to avoid a crash. This research aims to develop a verification process for vulnerable road user safety applications with vision-based detection functionalities. It consists of reviewing the application’s safety requirements, identifying the target objects of detection in the operational design domain and pre-crash scenarios, and evaluating the safety risks qualitatively by examining the training dataset based on the results of pre-crash scenarios classification. As a demonstration, the process is implemented using open-source pedestrian tracking software, and the pre-crash scenarios are classified based on the trajectories of pedestrians in an example training dataset used in a pedestrian automatic emergency braking system. The dataset provides abundant vulnerable road users under various operating conditions. Results show that the dataset does not cover snowy weather, fog, smoke, smog, and dust/dirt of particulate matter conditions. Crossing, cut-in, and front pre-crash scenarios are less well-represented in the dataset than pedestrians on the sidewalk. Very few pedestrians were found in the front-near zone, which suggests the dataset lacks sufficient imminent pre-crash scenarios that pose the greatest safety risk. The performance of the pedestrian tracking software is evaluated and future research for improving the proposed mechanism is discussed.</div>

Topology optimization method of facesheet-to-skeleton connection area’s distribution design for alleviating strain concentration of flexible skins

During the morphing of flexible skins, local strain concentration may occur in the face-sheet due to different bonding methods between the face-sheet and the skeleton. To overcome this problem, we propose a strategy to improve the uniformity of the strain distribution through rationally distributing the connection areas between the face-sheet and skeleton of the sandwich-flexible-skin, and develop a topology optimization method for determining the optimal distribution of the connection areas. In this method, the connection areas between the face-sheet and the support skeleton are considered as the virtual adhesion layer comprising of adhesion materials. Based on the topology optimization idea, the distribution of connection areas is described by allocating the presence and absence of the adhesion material. The optimization model is established with minimizing the globe stress of the face-sheet as the objective function, the volume fraction of the design domain as the constraint. The effectiveness of the proposed method is verified through examples involving tensile and rotational states of the sandwich-flexible-skin with Ω-shaped honeycomb structure, and the results show that the optimization method can significantly improve the strain distribution of the face-sheet. Finally, a variable-sweep structure for unmanned aerial vehicles (UAVs) is designed to explore the practical value of the proposed method.

Optimization design of multi-scale TPMS lattices based on geometric continuity fusion and strain energy driven

3D lattice structure is a kind of advanced metamaterial structure with excellent performance, such as lightweight, high specific strength and stiffness, shock damping, heat dissipation, and electromagnetic shielding capabilities. With the development of additive manufacturing technology, it has been widely concerned and developed rapidly in recent years. In order to further integrate the performance of lattice structures with mesoscale units into multi-scale optimization, this paper proposes an optimization design method for the multi-scale TPMS (Triply Periodic Minimal Surfaces) lattices based on geometric continuity fusion and strain energy driven. Regarding the challenge of geometric continuity problem of complex transition boundaries in multi-TPMS lattices, interface interpolation and density factor optimization methodologies are studied. At the same time, the mapping mechanism between lattice configuration and mechanical properties of multi-TPMS lattices is discussed in view of the requirements of multi-scale design from macro to micro configurations. Then, the multi-TPMS lattice density and configuration fields in the design domain are co-designed with the strain energy driven. Simulation and experimental results show that the mechanical properties of the multi-scale TPMS lattice designed by the proposed method are significantly improved compared with the traditional single-configuration gradient lattice, including the stiffness of the cantilever beam optimized structure is improved by 20.5% and the flexural stiffness of the three-point flexural beam optimized structure is improved by 51.3%.

Design of compliant thermal actuators using topology optimization involving design-dependent convection and pressure load

This study presents a topology optimization method for thermal actuators that accounts for boundary conditions influenced by variables such as thermal convection and pressure load. Thermal actuators with gripper-like designs are essential for handling hot and brittle materials. The objective of this study is to design actuator shapes that achieve an optimal balance between flexibility and stiffness in high-temperature environments. Unlike previous studies that consider load conditions imposed on fixed boundaries within the design domain, this research introduces a high-temperature fluid as the driving source and employs a novel approach to boundary condition setting by integrating fictitious physical problems. This approach allows for the precise specification of various boundary conditions across multiple domains. A weighted-sum method is applied to optimize three objective functions related to deformability, stiffness, and thermal diffusibility of the actuators. To address the issue of excessively thin structures compromising deformability and the poor convergence of the optimization process, stress constraints based on the optimization history are introduced. The proposed method is validated through numerical examples, demonstrating improvements in structural deformability while controlling deformation on the target surface plane. The numerical results confirm that the objective function decreases and stress is suppressed, verifying the effectiveness of the proposed approach.

Mixing Linters with GUIs: A Color Palette Design Probe.

Visualization linters are end-user facing evaluators that automatically identify potential chart issues. These spell-checker like systems offer a blend of interpretability and customization that is not found in other forms of automated assistance. However, existing linters do not model context and have primarily targeted users who do not need assistance, resulting in obvious-even annoying-advice. We investigate these issues within the domain of color palette design, which serves as a microcosm of visualization design concerns. We contribute a GUI-based color palette linter as a design probe that covers perception, accessibility, context, and other design criteria, and use it to explore visual explanations, integrated fixes, and user defined linting rules. Through a formative interview study and theory-driven analysis, we find that linters can be meaningfully integrated into graphical contexts thereby addressing many of their core issues. We discuss implications for integrating linters into visualization tools, developing improved assertion languages, and supporting end-user tunable advice-all laying the groundwork for more effective visualization linters in any context.

Topology optimization using variable-porosity metal foams: design of conduction paths for cooling a heat generating disc and comparison with tree-shaped architectures

Abstract Topology optimization (TO) is a design algorithm providing the optimal material layout within a design domain to minimize/maximize an objective function. In thermal science, for instance, it can be used to optimize the design of heat sinks to minimize thermal compliance, entropy generation, average temperature, etc. Recently, classical TO frameworks have been enhanced in multi-material TO in order to include more materials, thereby enhancing the degrees of freedom of the system, and thus ensuring better thermal performance. This work implements both TO and multi-material TO (MMTO) to address a benchmark heat conduction problem, i.e., the cooling of a circular heat generating volume through heat conduction paths. The heat generation is uniform in the disc, the rim is adiabatic, while the centre is set at a fixed temperature – Dirichlet boundary condition – and serves as heat sink. In TO the choice is between void and high-conductivity material, while in MMTO variable-porosity metal foams are integrated. The interpolation of the materials’ thermal conductivity is conducted via an ordered solid isotropic material penalization (SIMP) algorithm. The distinction between materials is attained by setting different thresholds in the interpolation and projection functions. The dimensionless global thermal resistance and domain average temperature are alternately addressed as objective functions to be minimized at equal weight of the system. The findings unveil that MMTO outperforms TO, which outperforms constructal tree networks, considering in the latter case different configurations of different complexity.

Topology optimization on a jacket structure for offshore wind turbines by altering structural design domain

Topology optimization on a jacket structure for offshore wind turbines by altering structural design domain

Frequency and time domain 19F ENDOR spectroscopy: role of nuclear dipolar couplings to determine distance distributions.

19F electron-nuclear double resonance (ENDOR) spectroscopy is emerging as a method of choice to determine molecular distances in biomolecules in the angstrom to nanometer range. However, line broadening mechanisms in 19F ENDOR spectra can obscure the detected spin-dipolar coupling that encodes the distance information, thus limiting the resolution and accessible distance range. So far, the origin of these mechanisms has not been understood. Here, we employ a combined approach of rational molecular design, frequency and time domain ENDOR methods as well as quantum mechanical spin dynamics simulations to analyze these mechanisms. We present the first application of Fourier transform ENDOR to remove power broadening and measure T2n of the 19F nucleus. We identify nuclear dipolar couplings between the fluorine and protons up to 14 kHz as a major source of spectral broadening. When removing these interactions by H/D exchange, an unprecedented spectral width of 9 kHz was observed suggesting that, generally, the accessible distance range can be extended. In a spin labeled RNA duplex we were able to predict the spectral ENDOR line width, which in turn enabled us to extract a distance distribution. This study represents a first step towards a quantitative determination of distance distributions in biomolecules from 19F ENDOR.

Diels-Alder reaction in hydrogel synthesis: Mechanisms and functional aspects.

The Diels-Alder reaction, a classical (4+2) cycloaddition process, holds significant standing within the realms of organic synthesis and polymer chemistry, frequently employed in areas such as pharmaceutical production and material science. Recently, hydrogels constructed via Diels-Alder reactions have garnered considerable attention from researchers. This review aims to summarize the advancements in utilizing the Diels-Alder reaction for hydrogel synthesis, exploring its impact on structural design, functionalization, and application domains. Initially, the fundamental principles of the Diels-Alder reaction are introduced alongside an examination of its benefits and characteristics in hydrogel fabrication. Subsequently, applications of Diels-Alder-generated hydrogels in biomedicine, smart responsive materials, drug delivery systems, among other fields, are comprehensively reviewed. Challenges and limitations encountered during hydrogel synthesis using this reaction are also discussed. Finally, prospective research directions and future prospects of Diels-Alder reactions in hydrogel synthesis are contemplated.

Determination of application limits of graph-analytical method of a single pile settlement calculation

The limits of application of the graph-analytical method for calculating the settlement of a single pile in a single-layer soil massif depending on the length and diameter of the pile are investigated. The graph-analytical method makes it possible to take into account non-linear work of the soil on the whole surface of the pile, exclusion from further work of the soil area along the lateral surface of the pile, where the ultimate strength of the soil was reached, mechanism of load distribution on the pile and friction reduction at the contact “pile–soil”. A comparative analysis of the results obtained by the graph-analytical method and numerical simulation performed in the Plaxis 2d software package was performed. According to the results of calculations, the graphs of dependence of settlements on loads were plotted and a comparative analysis of the character of deformation of the graphs, distribution of loads on the pile and values of settlements was performed. As a result, conclusions were drawn about the applicability of the graph-analytical solution for calculating pile settlements depending on their length and diameter, and recommendations were given for adjusting the design domain and pile load distribution to increase convergence with the numerical solution.

Integrating axiomatic design and design structure matrix into model‐based systems engineering: A case study for emergency response space mission design

AbstractWith the increasing complexity of space missions due to technological advancements, model‐based systems engineering (MBSE) has become a new paradigm for systems engineering (SE), providing a more formal and accurate system engineering process while reducing costs. However, MBSE does not offer a comprehensive approach for effective system function design. This study introduces a conceptual design approach that integrates axiomatic design (AD) and design structure matrix (DSM) into the MBSE paradigm and applies it to functional and logical design. The research focuses on utilizing the design knowledge encapsulated by system models to facilitate the development of new systems. System models have the potential to bridge different design domains in AD, reveal implicit associations, and offer functional and structural analysis capabilities. To validate our approach, we conducted a case study on an Emergency Response Remote Sensing mission system. This case study demonstrates that our proposed methodology lends formality to traditional AD by deriving AD matrices and DSMs from a system model, thereby enhancing the system's structure while curtailing elemental alterations during iterative design processes. The novelty of this research lies in realizing the integration of traditional design theory with the model paradigm of SE, leading to an effective design solution during the functional and logical design stages.

Rubric development and validation for assessing educational robotics skills

The current study describes the process of development and validation of a rubric for assessing educational robotics skills among middle school students. A multiphase method has been followed, including a literature study, expert consultation, content validation, pilot testing, reliability analysis, and construct validation. The resulting dual-category rubric designing and programming skills were further elaborated by specific criteria and performance levels. Content validation identified seven key criteria: stability and durability, motors, innovation, code organization, dependability and reliability, movement and rotation, and innovative use of sensors. The results of inter-rater reliability analysis for all criteria indicated good agreement, with Krippendorff’s alpha ranging from 0.941 to 1.000. Additionally, construct validation using exploratory factor analysis confirmed a two-factor structure that aligns with the intended domains of design and programming skills, explaining 67.4% of the total variance. The rubric was consistent with learning/teaching theories such as Bloom’s taxonomy, constructivist learning theory, and self-determination theory. This rubric fulfills the existing need for a specific assessment tool in educational robotics and supports educational practices through very detailed feedback to students on their performance. This adds much to educational assessment and education in robotics and enhances teaching and learning outcomes for STEAM education in various settings.

Topology Optimization: A Review for Structural Designs Under Statics Problems.

Topology optimization is a powerful structural design method that determines the optimal configuration by distributing materials efficiently within a given design domain while satisfying specified load, performance, and volume constraints. Unlike size and shape optimization, topology optimization is independent of the initial design, offering a broader design space. This paper provides a systematic review of topology optimization methods, covering two theoretical frameworks: linear elasticity and nonlinear theory. Specifically, the review focuses on sensitivity analysis, optimization criteria, and topology solution smoothing within the context of linear elasticity. In the context of nonlinear theory, the review primarily addresses nonlinear phenomena arising from stress constraints, geometric, material, and contact nonlinearities. The paper concludes by summarizing the current state of the field, identifying limitations in existing methods, and suggesting directions for future research.

Applications of topology optimization considering physical nonlinearity

Topology optimization is a powerful computational tool that assists designers in determining efficient structural configurations. In civil engineering, most applications are still limited to the field of theoretical/computational analysis. This limitation restricts the scope and applications of topology optimization concepts for practical problems. Extensive research has focused on topology optimization using isotropic material with linear elastic behavior. However, there is a paucity of studies comparing linear and nonlinear material behaviors, highlighting a research gap in result analysis and structural application fields. For concrete structures, in particular, there is generally a deeply nonlinear behavior, including effects such as cracking, creep, and shrinkage. Therefore, it becomes a challenge to realistically optimize this type of material. This study investigates the applications of topology optimization for evaluating the structural behavior of beams considering the physical nonlinearity of the material. Using the ABAQUS® software and the SIMP method, a finite element numerical analysis is conducted to determine the density distribution in a design domain. The obtained results of the optimized models are compared, and it is observed that the presence of plastic deformations influences relevant aspects of structural behavior. This study contributes to the dissemination of the use of nonlinear constitutive models, highlighting the potential of the concept of optimization-assisted design.

Performance-based design optimization of steel structures subjected to seismic actions

Finding an optimal design for a structural system subject to seismic actions to minimize failure probability, repair costs, and injuries to occupants, significantly contributes to the resilience of buildings in earthquake regions. This research presents a comprehensive framework for the performance-based design optimization of steel structures, incorporating the Performance-Based Earthquake Engineering (PBEE) methodology delineated in FEMA P-58 [1]. A selected set of ground motions, consistent with the seismic hazard intensity of interest, and a nonlinear finite element model, established using OpenSees, enable the assessment of the system's dynamic response. To address the computational complexity related to evaluating the probability of failure of the system during an optimization iteration when using the PBEE methodology for assessing performance, this study introduces metamodeling techniques as a substitute for the original high-fidelity nonlinear finite element model. In particular, Kriging is employed to approximate both the median and standard deviation of the Engineering Demand Parameters (EDPs) in the design domain. The parameters of the Kriging metamodels are derived from nonlinear dynamic analyses performed using the original high-fidelity model and an optimal sampling plan obtained through Latin Hypercube sampling. Under the assumption of a lognormal distribution, the metamodel is then used to generate a large number of simulated demand sets necessary for the Monte Carlo procedure adopted by FEMA P-58 to calculate the distribution of probable losses for any given value of the design variable vector. Additionally, the median and standard deviation of the fragility function modeling collapse are also approximated by a Kriging metamodel, in which the parameters are derived from an Incremental Dynamic Analysis (IDA) for any given value of the design variable vector. The scheme is illustrated in a full-scale case study consisting of the performance-based optimization of the buckling-restrained braces of a steel seismic force-resisting system in terms of expected losses and construction costs. The study demonstrates that the proposed risk-based optimization scheme effectively balances construction costs with expected financial losses from earthquakes, thus enhancing the seismic performance of the system.[1] Applied Technology Council, & National Earthquake Hazards Reduction Program (US). (2012). Seismic performance assessment of buildings. Federal Emergency Management Agency.