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A new design method for frontier contexts is given a classroom assessment. The method adds the formal consideration of the design context to traditional customer needs assessment. Testing under both controlled and classroom conditions shows the new method is extremely effective, easy to use and well received by students. Implementation at three US schools has shown positive results signifying broad applicability in education as well as field practice. Here we present the essence of the method, results of testing and examples. [ABSTRACT FROM AUTHOR]

The article discusses the concept of creation and its relationship to informational categories. The use of categories and their representations are emphasized in enhancing the generation of concepts for product development, engineering design problems, and innovation access. The concept generated are then implemented for practical application in the real-world, societal problems and marketplaces. The paper discusses some concept generalization methods and formulated open research questions that can be use as a genesis for collegial debate. These questions represent opportunities to understand the art of design, collaborate the field of psychology and engineering and embody the potential for learnable principles for designers to become the next Edisonian contributors.

• A holistic design approach for residential net-zero energy building (NZEB) is introduced. • Daylighting, natural cooling, energy efficiency and life cycle cost are optimized. • A case study of designing NZEBs in a tropical climate is conducted. • The most influential design variables are identified by sensitivity analysis. • The environmental, social and economic aims do not necessarily contradict each other. The concept of net-zero energy buildings is an important element and dimension of the sustainable built environment. This paper introduces a holistic design approach for residential net-zero energy building (NZEB) by adopting the Triple Bottom Line (TBL) principles: social, environmental, and financial. The social need is mapped to human comfort and nature contact (i.e. thermal comfort achieved by natural cooling, and visual comfort achieved by daylighting); the environmental need is mapped to energy efficiency; and the financial need is mapped to life cycle cost (LCC). Multi-objective optimizations are conducted in two phases: the first phase optimizes the utilization rate of natural cooling and daylighting, and the second phase optimizes energy efficiency and LCC. Sensitivity analysis is conducted to identify the most influential variables in the optimization process. The approach is applied to the design of residential NZEBs in a tropical country, Singapore. The potential of building residential NZEBs in Singapore is evaluated with two typical residential building types: a landed house and apartment building. The required capacity of a renewable energy system (RES) is calculated. Results show that while it is achievable to build a net-zero energy landed house with only rooftop solar panels, it is much more difficult to achieve net-zero energy for apartment buildings. Further design considerations and analysis show that for a 25-floor H-shaped residential building with a solar panel integrated facade, the produced electricity is able to meet the energy demand of up to 19 floors. Findings and derived insights from the case study show that although some variables need to be carefully selected to balance daylighting and natural cooling, the two objectives do not always contradict each other regarding certain variables. Similarly, environmental aims and economic aims do not always contradict each other on certain variables. Also, the social aims do not contradict environmental and economic aims, as the findings show that designing for daylighting and natural cooling contributes to the improvement of energy efficiency and cost effectiveness. These results provide a framework and modeled cases for design insights, parametric design, and trade-off analysis toward sustainable and livable built structures. [ABSTRACT FROM AUTHOR]

Design-by-analogy (DbA) is a design methodology wherein new solutions, opportunities, or designs are generated in a target domain based on inspiration drawn from a source domain; it can benefit designers in mitigating design fixation and improving design ideation outcomes. Recently, the increasingly available design databases and rapidly advancing data science and artificial intelligence (AI) technologies have presented new opportunities for developing data-driven methods and tools for DbA support. In this study, we survey existing data-driven DbA studies and categorize individual studies according to the data, methods, and applications into four categories, namely, analogy encoding, retrieval, mapping, and evaluation. Based on both nuanced organic review and structured analysis, this paper elucidates the state-of-the-art of data-driven DbA research to date and benchmarks it with the frontier of data science and AI research to identify promising research opportunities and directions for the field. Finally, we propose a future conceptual data-driven DbA system that integrates all propositions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Highlighting the status, inherent barriers, and challenges of multi-material 4D printing. • A strategic research roadmap based on the opportunities and challenges in engineering and interdisciplinary design. • Proposal of a design for 4D printing framework. The combination of scientific advances in additive manufacturing (AM) and smart materials (SMs) has enabled the development of a new interdisciplinary research area: 4D printing. This technology offers – via stimuli-responsive materials – promising transformation capabilities to objects whether at the functional, shape, or property levels. By considering such capabilities, researchers from multiple disciplines have investigated a large spectrum of stimuli-SMs associations with proofs-of-concept built from either commercial or custom 3D printers. Despite the abundant initiatives, 4D printing requires additional developments to meet robust system applications for the industry. The paper aims to highlight the status, inherent barriers, and challenges of 4D printing to be addressed from a product-systems design perspective. It firstly reminds the fundamentals of SMs, processes, stimulus, and AM to which a synthesis of significant research works related to 4D printing highlighting the current status as well as scientific, technical, and organizational limitations is provided. Beyond this comprehensive study, the paper emphasizes opportunities and challenges from multiple perspectives and draws a research roadmap for engineering design and cross-disciplinary design. The outcome of the work tends to structure research efforts for the next decade towards the development of smart products that meet use for humans and the industry. [ABSTRACT FROM AUTHOR]

There are growing efforts to mine public and common-sense semantic network databases for engineering design ideation stimuli. However, there is still a lack of design ideation aids based on semantic network databases that are specialized in engineering or technology-based knowledge. In this study, we present a new methodology of using the Technology Semantic Network (TechNet) to stimulate idea generation in engineering design. The core of the methodology is to guide the inference of new technical concepts in the white space surrounding a focal design domain according to their semantic distance in the large TechNet, for potential syntheses into new design ideas. We demonstrate the effectiveness in general, and use strategies and ideation outcome implications of the methodology via a case study of flying car design idea generation. [ABSTRACT FROM AUTHOR]

Data-driven conceptual design methods and tools aim to inspire human ideation for new design concepts by providing external inspirational stimuli. In prior studies, the stimuli have been limited in terms of coverage, granularity, and retrieval guidance. Here, we present a knowledge-based expert system that provides design stimuli across the semantic, document and field levels simultaneously from all fields of engineering and technology and that follows creativity theories to guide the retrieval and use of stimuli according to the knowledge distance. The system is centered on the use of a network of all technology fields in the patent classification system, to store and organize the world's cumulative data on the technological knowledge, concepts and solutions in the total patent database according to statistically-estimated knowledge distance between technology fields. In turn, knowledge distance guides the network-based exploration and retrieval of inspirational stimuli for inferences across near and far fields to generate new design ideas by analogy and combination. With two case studies, we showcase the effectiveness of using the system to explore and retrieve multilevel inspirational stimuli and generate new design ideas for both problem solving and open-ended innovation. These case studies also demonstrate the computer-aided ideation process, which is data-driven, computationally augmented, theoretically grounded, visually inspiring, and rapid. [ABSTRACT FROM AUTHOR]

Early-stage ideation is a critical step in the design process. Mind maps are a popular tool for generating design concepts and in general for hierarchically organizing design insights. We explore an application for high-level concept synthesis in early stage design, which is typically difficult due to the broad space of options in early stages (e.g., as compared to parametric automation tools which are typically applicable in concept refinement stages or detail design). However, developing a useful mind map often demands a considerable time investment from a diverse design team. To facilitate the process of creating mind maps, we present an approach to crowdsourcing both concepts and binning of said concepts, using a mix of human evaluators and machine learning. The resulting computer-aided mind map has a significantly higher average concept novelty, and no significant difference in average feasibility (quantity can be set independently) as manually generated mind maps, includes distinct concepts, and reduces cost in terms of the designers' time. This approach has the potential to make early-stage ideation faster, scalable and parallelizable, while creating alternative approaches to searching for a breadth and diversity of ideas. Emerging research explores the use of machine learning and other advanced computational techniques to amplify the mind mapping process. This work demonstrates the use of the both the EM-SVD, and HDBSCAN algorithms in an inferential clustering approach to reduce the number of one-to-one comparisons required in forming clusters of concepts. Crowdsourced human effort assists the process for both concept generation and clustering in the mind map. This process provides a viable approach to augment ideation methods, reduces the workload on a design team, and thus provides an efficient and useful machine learning based clustering approach. [ABSTRACT FROM AUTHOR]

Highlights: • A bio-inspired textured surface enables fully texture-driven fog harvesting. • The textures simultaneously maximize fog condensation and droplet disposal. • Consequently, the surface exhibits nearly six-fold increase in fog harvesting efficiency. • The texture is fabricated by a single-step nanoimprinting on large-area substrates. Abstract Fog harvesting is recognized as one of the most sustainable means of freshwater collection. Synthetic fog harvesting surfaces have been predominantly inspired from the desert beetle's exoskeleton which exhibits a bumpy topography. This topography underlies an alternating hydrophilic-hydrophobic pattern which has been the basis of several bio-inspired fog harvesting surfaces. However, replication of such hydrophilic-hydrophobic patterns involves multiple processing steps and tedious incorporation of functional/chemical groups at precise locations. On the other hand, surface topography or texture has proven to be insufficient in realizing an efficient fog harvesting surface. This is because micro- or nano-scale textures alone fail to simultaneously maximize the rate of droplet condensation and disposal, which are the two key aspects of efficient fog harvesting. Herein, we report that a hierarchically-textured surface, consisting of micro-lenses arrays covered with high aspect-ratio nanoscale fibrils, can fulfil these two key requirements for maximizing fog harvesting efficiency. While the micro-lenses enable faster droplet condensation, the cluster of nanoscale fibrils impart superhydrophobicity that aids in intermittent droplet disposal. Together, the topography achieves a fog collection efficiency ∼5–6 times higher than that of the planar counterpart. Moreover, this hierarchical texture is fabricated by a simple one-step nanoimprinting approach which is scalable to arbitrarily large-area flexible substrates. [ABSTRACT FROM AUTHOR]

Located near the equator, Singapore has a tropical rainforest climate with high temperature and high humidity. In hospitals of Singapore, the subsidized patient wards are designed to be naturally ventilated, considering the affordability for patients. However, due to the high occupant density of the patient wards and the hot humid climate, occupants may feel discomfort, especially in the older hospital wards which were not well designed for natural ventilation. In this paper, the thermal comfort level of occupants at Singapore's Changi General Hospital (CGH) is evaluated based on both in-situ measurements and modeling analysis. Against this backdrop, several low energy solution concepts that potentially improve the thermal comfort level of occupants in patient wards are analyzed and simulated using detailed building thermodynamic and airflow simulation. We found that this approach of combining thermodynamics, computational fluid dynamics, and thermal comfort level models was effective for analyzing and comparing the thermal comfort impact of alternative, low-energy building retrofit concepts. We also found that passive solutions to ventilation could be used effectively for a patient hospital ward, even in the tropical warm climate of Singapore. [ABSTRACT FROM AUTHOR]

This paper studies an interdisciplinary approach for improving building energy efficiency. In particular, the proposed approach integrates design innovation (DI) techniques, existing energy audit methods (EAM), and data-driven & engineering modeling techniques (DET) in the process of sustainable smart energy system design. From this perspective, DI methods are extended and modified to suit the content of sustainable smart energy system design and a DI 4D (Discover, Define, Develop and Deliver) framework is introduced to guide the design process. The motivation behind and the implementation procedure of each of the DI phases is explained separately, and the process of integrating DI methods, EAM and DET in developing a sustainable smart energy system is demonstrated. The proposed approach is deployed within the campus of a tertiary education institution to show its effectiveness in designing a smart sustainable energy system. • A design innovation (DI) approach is proposed for smart energy system design. • A comprehensive background of the proposed DI framework is provided. • How DI can be used to design smart energy system is demonstrated. • Experimental case studies are provided to show the benefit of the proposed scheme. [ABSTRACT FROM AUTHOR]

Disability has been redefined by the World Health Organization as a function of a person's interaction with the environment and not merely an innate part of a person. This redefinition highlights the need for inclusiveness in design solutions. To aid this, we apply and test the potential of different tools that restrict designers' physical abilities at deriving inclusive design perspectives among designers. Various tools and simulated conditions are often adopted in user-centered design to sup-port need-finding by eliciting rich data on users' needs and guide designers to empathize with users. Simulation tools that restrict designers' physical abilities have been applied to understand certain perspectives of people with physical challenges, yet these tools lack the ability to evoke an inclusive design perspective among designers. Through a co-creation workshop, participants were exposed to two forms of simulations: direct and situational physical impairments. This was achieved using different tools that simulate the same physical restriction. In this study, a noise- canceller and earphones were used to simulate a reduced hearing attention. Participants were asked to generate user needs and design functions by applying both the simulation tools. The study results comprise the outcomes of 33 participants who volunteered to participate in a co-design workshop that provided a venue for them to interact and work alongside users with physical challenges. This paper analyses the inclusiveness attained through different types of simulated conditions. With a growing need to create tools and technologies that delight the user, it is necessary to equip designers with the tools that would help them with the process. The study demonstrates the application and impact of one such tool.

Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.