General Design Tool Research Articles

Incorporating sparse model machine learning in designing cultural heritage landscapes

Managing, protecting, and the evolutionary development of historical landscapes require robust frameworks and processes for forming datasets and advanced decision support tools. Despite the great potential, using pattern language, machine learning, and regenerative and generative design tools has yet to be adopted in historic landscape research due to the need for suitable training datasets. To address this theoretical and technical gap, this paper describes a three-step workflow, namely photogrammetry, feature extraction and discriminative feature analytics, to help facilitate the use of advanced ML tools for cultural heritage decision support. Sparse-Learning-Modelling (SLM) was used to help with feature extraction from small datasets. The developed tool was successfully tested on the 3D point cloud models of 13 heritage sites, and these could be replicated in other heritage sites with distinctive Cultural DNA worldwide. The findings of this research can extend the discourse of adopting advanced AI/digital tools in heritage landscape design.

Multimaterial Topology Optimization of Adhesive Backing Layers via J-Integral and Strain Energy Minimizations

Abstract Strong adhesives often rely on reduced stress concentrations obtained via specific functional grading of material properties. This can be seen in many examples in nature and engineering. Basic design principles have been formulated based on parametric optimization, but a general design tool is still missing. We propose here the use of topology optimization to achieve optimal stiffness distribution in a multimaterial adhesive backing layer, reducing stress concentration at selected (crack tip) locations. The method involves the minimization of a linear combination of (i) the J-integral around the crack tip and (ii) the strain energy of the structure. This combination is due to the compromise between numerical stability and accuracy of the method, where (i) alone is numerically unstable and (ii) alone cannot eliminate the crack tip stress singularity. We analyze three cases in plane strain conditions, namely, (1) double-edged crack and (2) center crack, in tension, as well as (3) edge crack under shear. Each case evidences a different optimal topology with (1) and (2) providing similar results. The optimal topology allocates stiffness in regions that are far away from the crack tip, and the allocation of softer materials over stiffer ones produces a sophisticated structural hierarchy. To test our solutions, we plot the contact stress distribution across the interface. In all observed cases, we eliminate the stress singularity at the crack tip, albeit generating (mild) stress concentrations in other locations. The optimal topologies are tested to be independent of the crack size. Our method ultimately provides the robust design of flaw tolerant adhesives where the crack location is known.

OBSERVATIONS ON THE IMPLICATIONS OF GENERATIVE DESIGN TOOLS ON DESIGN PROCESS AND DESIGNER BEHAVIOUR

AbstractDevelopments in artificial intelligence (AI) are opening the possibilities for the development of more advanced design tools. An example of these innovations are generative design tools, in which the generation of complex and high performing products is possible. This study investigates the use of generative design tools and how they may influence the design process and designer behaviour. Six interviews of interdisciplinary designers were conducted to understand the implications of using generative design tools. It was observed that generative design tools primarily allow for quantitative inputs to the tool while qualitative metrics, such as aesthetics, are considered indirectly by designers. The subjectivity of the designer and how they incorporate the quantitative and qualitative metrics in the generative design tool can lead to differing outcomes between designers. Notable differences in tool usage are also observed between expert and novice computational designers. Additional studies should be conducted to further understand the extent generative design tools impact the design process, designer behaviour, and design outcomes.

DESIGN TEACHING INTEGRATING ADDITIVE MANUFACTURING CONSTRAINTS

AbstractAdditive manufacturing (AM) processes are now integrated in industry. Therefore, new methods to design AM parts taken into consideration capabilities and limitations are necessary. It is very difficult for teachers to effectively guide students with ideas emerging from generative design tools. AM requires significant preparation and compromises. Topological optimization is also used depending on requirements. A significant impact on the final part quality is related to the part orientation and geometric dimensions. Therefore, this white paper focuses on detailed design steps to prepare future technicians and engineers to design for additive manufacturing. Active teaching pedagogy guideline is proposed. Students have to think in 3D and use analysis tools to create and validate the optimised design. They use immersive tools to review constraints and model diagnostic algorithm to generate data. Present approaches with design guidelines and tools enable to create AM rules based on it. Questionnaire shows that students need explicit knowledge information. Features recognition and geometry diagnostic are mandatory for complex model. Immersive tool helps to evaluate post-processing. They can now relate AM product-process relationship.

Prediction of Cooling Load of Tropical Buildings with Machine Learning

Cooling load refers to the amount of energy to be removed from a space (or consumed) to bring that space to an acceptable temperature or to maintain the temperature of a space at an acceptable range. The study aimed to develop a series of models and determine the most accurate ones in the prediction of the cooling load of low-rise tropical buildings based on their basic architectural and structural characteristics. In this context, a series of machine learning (regression) algorithms were tested during the research to determine the most accurate/efficient prediction model. In this regard, a data set consisting of ten features indicating the basic characteristics of the building (floor area, aspect ratio, ceiling height, window material, external wall material, roof material, window wall ratio north faced, window wall ratio south faced, horizontal shading, orientation) were used to predict the cooling load of a low-rise tropical building. The dataset was generated utilizing a set of generative and algorithmic design tools. Following the dataset generation, a series of regression models were tested to find the most accurate model to predict the cooling load. The results of the tests with different algorithms revealed that the relationship between the predictor variables and cooling load could be efficiently modeled through Histogram Gradient Boosting and Stacking models.

Engaging People Living with Dementia in The Design Process

This study explores how the integration of inclusive design, participatory design (PD), collaborative design, and generative design has led to new methods and tools for involving the elderly in the design process. particularly the elderly with dementia. Dementia is one of the many health issues that become more common among the elderly (though the exact risk factors vary depending on factors like diet, exercise, and genetics). There are approximately 55 million dementia patients globally, with the majority (58%) residing in low- and middle-income nations. Annually, 7.7 million new cases of dementia are diagnosed, and the number of people with dementia is projected to increase to 75,6 million by 2030 and nearly triple to 135.5 million by 2050. In Egypt, there are approximately 600,000 dementia patients, 60% of whom have Alzheimer's, and it is anticipated that by 2030, there will be 1,200,000 dementia patients. Till this day, People living with dementia are still subjected to significant stigmatization. As a result of their exclusion from research and design processes, the majority of newer technologies, products, and services either disregard the needs of older people with dementia or lean more towards the preferences of carers, resulting in designs that are inappropriate or inaccessible to the target population. However, we are currently confronted with significant environmental, social, and cultural obstacles. To be effective, design innovations must be accessible to all stakeholders. We can only use design to solve today's problems by thinking collectively and acting inclusively. By establishing inclusive design as the backbone of the design process and integrating participatory design (PD) techniques, as well as collaborative co-design and generative design research, we are able to better meet the needs of those who will be directly impacted by the final product. People from a wide range of fields need to be brought into the design process. ‘All people are creative and can participate in co-design if they are provided with relevant tools and the appropriate settings for their use.’ Liz Sanders Dementia seniors' inclusion and participation in research and development must therefore be carefully considered. (Specifically for the first three stages of the disease or communicative patients. Therefore, the following research problem arose:• Research Questions: 1-Is it possible for older people who are living with dementia to engage in the design process? 2-How can the role and insights of an industrial designer be utilised to include and involve older people with dementia in research and development, especially in the first three stages of the disease or for patients who are still able to communicate?. Research Significance: The significance of the study lies in the need to allow dementia patients to participate in various stages of the industrial design process while refocusing design efforts on meeting their needs and requirements rather than those expressed on their behalf by others. This prompted industrial designers to create more effective solutions for this elderly population by employing inclusive and co-design strategies. Permitting people with dementia to participate fully in the design process. Research Objectives: The aim of this research is shed light on the application of generative design tools in the context of industrial design processes involving people with dementia. Research Methodology: The research follows the descriptive method by using the investigative method, then the analytical method by gathering and sorting information, and then the deductive method. Research Results & Recommendations:1-It is recommended to use a mix of participatory design (PD) methods, co-design approaches, and generative design techniques to tackle complex design problems that might come up when collaborating with older people who have dementia. 2- The industrial designer must first think about the goal of the ongoing design process and then choose the tools that will facilitate people's thinking and talking about their experiences. 3- Industrial Designers must consider research ethics, safety, and tailoring toolkits to the specific requirements of the design process, as well as selecting materials to cater to participants' (PWD) preferences and providing explanations of how to use the TOOLS

Generative Design: Reframing the Role of the Designer in Early-Stage Design Process

AbstractGenerative design tools empowered by recent advancements in artificial intelligence (AI) offer the opportunity for human designers and design tools to collaborate in new, more advanced modes throughout various stages of the product design process to facilitate the creation of higher performing and more complex products. This paper explores how the use of these generative design tools may impact the design process, designer behavior, and overall outcomes. Six in-depth interviews were conducted with practicing and student designers from different disciplines who use commercial generative design tools, detailing the design processes they followed. From a grounded theory-based analysis of the interviews, a provisional process diagram for generative design and its uses in the early-stage design process is proposed. The early stages of defining tool inputs bring about a constraint-driven process in which designers focus on the abstraction of the design problem. Designers will iterate through the inputs to improve both quantitative and qualitative metrics. The learning through iteration allows designers to gain a thorough understanding of the design problem and solution space. This can bring about creative applications of generative design tools in early-stage design to provide guidance for traditionally designed products.

Extending the usability of the force-flow based topology optimization to the process of generative design

Topology optimization and Generative Design are two methods to create volume or stiffness optimized parts and they are used more frequently nowadays. However, the specific methods are often not well described and the connection between these two is not clearly explained. In this article, a force-flow based topology optimization process has been explained in detail and extended with a function to be able to use as a Generative Design tool. The proposed algorithm has been tested on three 2D shapes and the effectiveness was evaluated. This work clarifies the vague description of theoretical solutions by presenting in detail the operation of the algorithm and bridging the lack of information that exists between the shape or topology optimization procedure and the generative design solution.

Human-Centered Generative Design Framework: An Early Design Framework to Support Concept Creation and Evaluation

Generative design uses artificial intelligence-driven algorithms to create and optimize concept variants that meet or exceed performance requirements beyond what is currently possible using the traditional design process. However, current generative design tools lack the integration of human factors, which diminishes the efforts to understand and inject a broad set of human capabilities, limitations, and potential emotional responses for future human-centered product and service innovation. This paper demonstrates collaborative research in formulating a human-centered generative design framework that injects human factors early in the design for quick-and-dirty concept creation and evaluation. Three case studies overviewing our ongoing multidisciplinary research efforts in synthesizing human and mechanical attributes are presented. The results show that the framework has the potential to enhance human factors representation within generative design workflow. Strategies from a computational design perspective, such as data-driven generative design, digital human modeling, and mixed-reality validation, are discussed as alternative approaches that could be implemented to augment designers.

Аrtistic and рroject tools in the chronological іnfographics design

The purpose of the work is to reveal the visual and semantic essence of chronological infographics. Identifying design and artistic tools for its formation is also the aim of the study. The research methodology includes general scientific and special research methods. Comprehensive and analytical methods became the basis of this study. The method of visual observation is used for the initial analysis of the empirical basis; methods of systematization and generalization are used to classify infographics; method of comparative analysis – to identify semantic and visual differences of chronological infographics. Also, methods of modeling, forecasting and artistic-compositional analysis were used. The scientific novelty of the work lies in the theoretical substantiation of methods of designing chronological infographics, as well as in the systematization of visual techniques and compositional means of forming chronological infographics in various media formats and visual forms. Conclusions. It is revealed that today infographics is becoming an important means of transmitting information in various fields. It is determined that the method of designing chronological infographics involves the gradual implementation of information and communication; design and aesthetic functions. This can be achieved by accurately disclosing the content of the project; streamlining visual information; searching for connections between symbolic images; use of author's artistic means and receptions. The conceptual tasks of each stage of work form the designer's general design and artistic tools. Key words: information, chronological infographics, timeline, image, illustration, information visualization, art and design tools.

Machine learning for topology optimization: Physics-based learning through an independent training strategy

The high computational cost of topology optimization has prevented its widespread use as a generative design tool. To reduce this computational cost, we propose an artificial intelligence approach to drastically accelerate topology optimization without sacrificing its accuracy. The resulting AI-driven topology optimization can fully capture the underlying physics of the problem. As a result, the machine learning model, which consists of a convolutional neural network with residual links, is able to generalize what it learned from the training set to solve a wide variety of problems with different geometries, boundary conditions, mesh sizes, volume fractions and filter radius. We train the machine learning model separately from the topology optimization, which allows us to achieve a considerable speedup (up to 30 times faster than traditional topology optimization). Through several design examples, we demonstrate that the proposed AI-driven topology optimization framework is effective, scalable and efficient. The speedup enabled by the framework makes topology optimization a more attractive tool for engineers in search of lighter and stronger structures, with the potential to revolutionize the engineering design process. Although this work focuses on compliance minimization problems, the proposed framework can be generalized to other objective functions, constraints and physics.

Computational design of passive grippers

This work proposes a novel generative design tool for passive grippers---robot end effectors that have no additional actuation and instead leverage the existing degrees of freedom in a robotic arm to perform grasping tasks. Passive grippers are used because they offer interesting trade-offs between cost and capabilities. However, existing designs are limited in the types of shapes that can be grasped. This work proposes to use rapid-manufacturing and design optimization to expand the space of shapes that can be passively grasped. Our novel generative design algorithm takes in an object and its positioning with respect to a robotic arm and generates a 3D printable passive gripper that can stably pick the object up. To achieve this, we address the key challenge of jointly optimizing the shape and the insert trajectory to ensure a passively stable grasp. We evaluate our method on a testing suite of 22 objects (23 experiments), all of which were evaluated with physical experiments to bridge the virtual-to-real gap. Code and data are at https://homes.cs.washington.edu/~milink/passive-gripper/

Navigating Design Spaces: Finding Designs, Design Collections, and Design Subspaces

Generative design systems can generate a wide panoply of solutions, from which designers search for those that best suit their interests. However, without guidance, this search can be highly inefficient, and many interesting solutions may remain unexplored. This problem is mitigated with automated exploration methods. Still, the ones typically provided by generative design tools are mostly based on black-box methods that drastically reduce the role of the designer, while more straightforward white-box mechanisms are dispersedly found in specific applications. This paper proposes the Navigator tool, which gathers a set of white-box mechanisms that automate the generation of default, random, similar and hybrid designs and design subspaces, while also supporting the generation of design collections. The proposed mechanisms were tested with two generative systems that create, respectively, tower and chair designs. We expect that, by providing understandable mechanisms for navigating design spaces, designers can become more engaged in the search process.

Use of Generative Design Tools in the Production of Design Products using 3D Printing Technology

Generative design uses machine learning to emulate nature's evolutionary approach to design. Designers and engineers put design parameters such as material, size, weight, strength, manufacturing methods and costs into generative design software that explores all possible solution combinations and quickly generates hundreds or even thousands of design options. The article describes the production of a design backrest of the chair by combining several rapidly developing technologies. The selected backrest of the chair was digitized and subsequently subjected to design modifications in the Generative Design module of the Creo Parametric 7.0 system. The new design of the product was produced by means of a 3D printer to point out the possibility of saving the used production material of the design properties of the product while maintaining the required strength properties in the waste-free production method by additive technology.

Performance-Driven Engineering Design Approaches Based on Generative Design and Topology Optimization Tools: A Comparative Study

The advent of Additive Manufacturing (AM) is uncovering the limits of the current CAD systems and, at the same time, is highlighting the potentials of the Topology Optimization (TO) and Generative Design (GD) tools that had not been fully exploited until now. Differently from the traditional design approach in which designers occupy a predominant role in each stage of the design process, the introduction of such tools in the product development process pushes toward simulation-driven design approaches which imply a significant change in the role of the designer. To this end, the paper presents a comparison of two different design methods for Additive Manufacturing based on the adoption of TO and GD tools. The comparison aims to offer a reflection on the evolution of the traditional approach when TO and GD tools are used, and to highlight the potential and limitations of these optimization tools when adopted in an integrated manner with the CAD systems. Furthermore, this comparative study can be a useful and practical source for designers to identify the most appropriate approach to adopt based on their needs and project resources. The comparative study is carried out through the design study of a prototype of a rocker arm and a brake pedal for the Formula Student race car. Their results, compared in terms of mechanical performances, show that both TO and especially GD tools can be efficiently adopted early in a design process oriented to AM to redesign components to make them lighter and stronger.

Open‐source terrestrial laser scanner for the virtualization of geometrical entities in AEC classrooms

AbstractThis paper depicts a case study that shows an open‐source Terrestrial Laser Scanner (TLS) for use on the virtualization of simple yet precise geometrical entities in AEC classrooms. For bringing this technology to AEC classrooms, an open‐source TLS was developed. The physical model was built using digital fabrication, its connectivity was established using accessible, affordable, open‐source sensors and actuators and its digital representation was developed using generative design tools. All elements together are synchronized in real‐time and the TLS becomes live, digitally twinned, geometry generator. The points that are generated by the TLS are gathered in a 3D virtual space in the form of virtual points. The present digitally twinned vision of laser scanning has thus three identified educational uses: (i) illustration of the measuring principle using open‐source hardware together with mathematics and statistics, (ii) illustration of the generation and visualization of point clouds in real‐time within a CAD environment, and (iii) perhaps with a vaster scope in AEC classrooms, illustration of the usage, analysis and identification of these point clouds. The development of this tool belongs to a vaster project for infusing Construction 4.0 technologies in AEC classrooms under development at the School of Civil Engineering of UPC‐BarcelonaTech. The illustration to students of all these concepts with accessible technological tools is expected to enlarge their vision of more advanced constructional technologies such as cyber‐physical systems for monitoring and surveying as well as digital technologies for reproducing “As‐Built” models.

Exploring the Design Space for Human-Food-Technology Interaction: An Approach from the Lens of Eating Experiences

Embedded in everyday practices, food can be a rich resource for interaction design. This article focuses on eating experiences to uncover how bodily, sensory, and socio-cultural aspects of eating can be better leveraged for the design of user experience. We report a systematic literature review of 109 papers, and interviews with 18 professional chefs, providing new understandings of prior HFI research, as well as how professional chefs creatively design eating experiences. The findings inform a conceptual framework of designing for user experience leveraging eating experiences. These findings also inform implications for HFI design suggesting the value of multisensory flavor experiences, external and internal sensory stimulation and deprivation, aspects of eating for communicating meaning, and designing with contrasting pleasurable and uncomfortable experiences. The article concludes with six charts as novel generative design tools for HFI experiences focused on sensory, emotional, communicative, performative, and temporal experiences.

A generative design-to-BIM workflow for minimum weight plane truss design

Structural design has a significant impact on the overall cost of truss structures. In order to reduce the cost of a structure it is important to support designers' decision making starting from the early design phase. In this study, an optimization workflow is proposed, developed and implemented using well known generative design and Building Information Modeling (BIM) tools to achieve a cost-optimal design of a truss structure in the early design phase. Generative design aims to develop products that are lighter, stronger, more efficient and tailored to the specific needs of end users. Generative design tools allow users to create efficient designs via optimizing factors such as cost, weight, energy efficiency and performance. The aim of this study was to develop an optimization workflow to find and model the minimum weight / minimum cost design alternative in the early design phase using generative design, structural analysis and BIM tools in an integrated manner. The goal for the optimization was determined as finding the minimum weight (thus minimum cost) structure among the generated design alternatives. The single span steel truss was selected as the structure to be optimized, and optimization scenarios were prepared and implemented to determine the structural components of the truss with minimum weight. The results demonstrated that through integrated use of structural analysis, generative design and BIM tools minimum-weight truss design can be realized easily and practically.

A two-step parametric generative method for heat exchangers design in additive manufacturing

Additive Manufacturing(AM) liberates a lot for the hands of designers to create complex geometry and avoid many traditional manufacturing constrains. A set of advanced generative design and topological optimization tools are emerging to support the design for AM. However, many existing methods are based on traditional topological optimization methods, which are focusing more on lightweight design but have difficulty to optimize component’s functions. In heat exchanger design, the functional features, e.g. fluid tunnels, are usually fixed without changing during the lightweight optimization. This cannot guarantee an optimal functional performance for the design. To solve this problem, this paper proposes a two-step generative design method that can both help optimizing the functional features for performance improvement and lightweight design. This method has two generative optimization loops, including functional feature group optimization and lightweight optimization. A set of finite optimized candidate alternative solutions from the first optimization loop are inputs for the second lightweight optimization loop to form boundary conditions and freezing regions in lightweight design. With the topological optimization in the second loop, the pre-selected functional features can be combined with the optimal volume layouts in the original design space to form a final component with improved function performance and reduced mass. To demonstrate the proposed method, a design case of a heat exchanger with conformal cooling channels is presented. The method can be adopted for other similar design cases in additive manufacturing applications.

AI takes on city design [artificial intelligence - architecture

Advanced AI-powered generative design tools can now automate the design and planning of entire neighbourhoods and districts of cities, reducing complexity for architects and urbanists and providing a speedier route to construction. But how effective is the technology and could it remove the need for humans in the design process entirely? Yet greater reliance on AI raises concerns over the expanding role of computers in design decision-making. Does AI merely provide a helping hand in the process or wrest control away from the people we entrust to make crucial decisions about the places where we live and work? Will it lead to better quality and more inclusive urban development, or create a generation of cookie-cutter-style buildings and neighbourhoods devoid of character and individuality?