Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Alsager Alzayed; Mohammad, Miller, Scarlett R., McComb, Christopher Pages: 369 - 383 Abstract: Over the past decade, engineering design research has seen a significant surge of the discussion of empathy. As such, design researchers have been devoted in devising and assessing empathic design activities. While prior research has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer's empathic tendencies in driving creative concept generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in an engineering design student project. In order to achieve this objective, a study was conducted with 103 first-year engineering students during two design stages of an 8-week design project (concept generation and concept selection). The main findings from this paper highlighted that empathic concern tendencies positively impacted the generation of more ideas while personal distress tendencies negatively impacted the generation of more ideas. During concept selection, perspective-taking tendencies positively impacted participants’ propensity for selecting elegant ideas. This research took the first step in encouraging empirical investigations aimed at understanding the role of trait empathy across different stages of the design process. PubDate: 2022-02-02 DOI: 10.1017/S0890060421000196
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Al Sayed; Kinda, Cheng, Peter C H., Penn, Alan Pages: 423 - 437 Abstract: This paper presents a preliminary study into the spatial features that can be used to distinguish creativity andefficiency in design layouts, and the distinct pattern of cognitive and metacognitive activity that is associated with creative design. In a design experiment, a group of 12 architects were handed a design brief. Their drawing activity was recorded and they were required to externalize their thoughts during the design process. Both design solutions and verbal comments were analysed and modelled. A separate group of experienced architects used their expert knowledge to assign creativity and efficiency scores to the 12 design solutions. The design solutions were evaluated spatially. Protocol analysis studies including linkography and macroscopic analysis were used to discern distinctive patterns in the cognitive and metacognition activity of designs marked with the highest and least creativity scores. Entropy models of the linkographs and knowledge graphs were further introduced Finally, we assessed how creativity and efficiency correlates to experiment variables, cognitive activity, metacognitive activity, spatial and functional distribution of spaces in the design solutions, and the number and type of design constraints applied through the course of design. Through this investigation, we suggest that expert knowledge can be used to assess creativity and efficiency in designs. Our findings indicate that efficient layouts have distinct spatial features, and that cognitive and metacognitive activity in design that yields a highly creative outcome corresponds to higher frequencies of design moves and higher linkages between design moves. PubDate: 2022-01-03 DOI: 10.1017/S0890060421000251
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Shekhawat; Krishnendra, Jain, Rahil N., Bisht, Sumit, Kondaveeti, Aishwarya, Goswami, Dipam Pages: 438 - 459 Abstract: This paper aims at automatically generating dimensioned floorplans while considering constraints given by the users in the form of adjacency and connectivity graph. The obtained floorplans also satisfy boundary constraints where users will be asked to choose their preferred location based on cardinal and inter-cardinal directions. Further, spanning circulations are inserted within the generated floorplans. The larger aim of this research is to provide alternative architecturally feasible layouts to users which can be further refined by architects. PubDate: 2022-02-02 DOI: 10.1017/S0890060421000275
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Authors:Rahimian; Mina, Duarte, Jose Pinto, Iulo, Lisa Domenica Pages: 353 - 368 Abstract: This paper discusses the development of an experimental software prototype that uses surrogate models for predicting the monthly energy consumption of urban-scale community design scenarios in real time. The surrogate models were prepared by training artificial neural networks on datasets of urban form and monthly energy consumption values of all zip codes in San Diego county. The surrogate models were then used as the simulation engine of a generative urban design tool, which generates hypothetical communities in San Diego following the county's existing urban typologies and then estimates the monthly energy consumption value of each generated design option. This paper and developed software prototype is part of a larger research project that evaluates the energy performance of community microgrids via their urban spatial configurations. This prototype takes the first step in introducing a new set of tools for architects and urban designers with the goal of engaging them in the development process of community microgrids. PubDate: 2021-12-28 DOI: 10.1017/S0890060421000184
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Authors:Bhatt; Apoorv Naresh, Majumder, Anubhab, Chakrabarti, Amaresh Pages: 384 - 403 Abstract: Literature suggests that people typically understand knowledge by induction and produce knowledge by synthesis. This paper revisits the various modes of reasoning – explanatory abduction, innovative abduction, deduction, and induction – that have been proposed by earlier researchers as crucial modes of reasoning underlying the design process. First, our paper expands earlier work on abductive reasoning – an essential mode of reasoning involved in the process of synthesis – by understanding its role with the help of the “SAPPhIRE” model of causality. The explanations of abductive reasoning in design using the SAPPhIRE model have been compared with those using existing models. Second, the paper captures and analyzes various modes of reasoning during design synthesis with the help of the “Extended Integrated Model of Designing”. The analysis of participants' verbal speech and outcomes shows the model's ability to explain the various modes of reasoning that occur in design. The results indicate the above models to provide a more extensive account of reasoning in design synthesis. Earlier empirical validation of both the models lends further support to the claim of their explanatory capacity. PubDate: 2021-12-27 DOI: 10.1017/S0890060421000214
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Authors:Ji; Hao, Jin, Yan Pages: 404 - 422 Abstract: Self-organizing systems (SOS) are developed to perform complex tasks in unforeseen situations with adaptability. Predefining rules for self-organizing agents can be challenging, especially in tasks with high complexity and changing environments. Our previous work has introduced a multiagent reinforcement learning (RL) model as a design approach to solving the rule generation problem of SOS. A deep multiagent RL algorithm was devised to train agents to acquire the task and self-organizing knowledge. However, the simulation was based on one specific task environment. Sensitivity of SOS to reward functions and systematic evaluation of SOS designed with multiagent RL remain an issue. In this paper, we introduced a rotation reward function to regulate agent behaviors during training and tested different weights of such reward on SOS performance in two case studies: box-pushing and T-shape assembly. Additionally, we proposed three metrics to evaluate the SOS: learning stability, quality of learned knowledge, and scalability. Results show that depending on the type of tasks; designers may choose appropriate weights of rotation reward to obtain the full potential of agents’ learning capability. Good learning stability and quality of knowledge can be achieved with an optimal range of team sizes. Scaling up to larger team sizes has better performance than scaling downwards. PubDate: 2021-12-27 DOI: 10.1017/S089006042100024X
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