Challenge For Designers Research Articles

The John Mitchell Lecture 2022: thinking conceptually about groundwater problems

Many excavations and tunnels experience problems and instability caused by uncontrolled groundwater inflows or groundwater pressures that influence stability and soil behaviour. A range of groundwater control measures can be used to overcome these problems and create stable and workably dry conditions below groundwater level. A key challenge for designers is that the performance of the various different techniques is strongly influenced by the hydrogeological conditions at a site. Furthermore, the available ground investigation data may have data gaps or considerable uncertainty regarding key parameters such as hydraulic conductivity or hydraulic boundary conditions. This means that, when working with real-world data sets, there are some groundwater problems where analysis involves so many assumptions and uncertainties that the design outcomes are of little practical value. This paper will discuss how thinking conceptually about groundwater problems can be of great benefit when developing of groundwater control schemes, and that a robust conceptual model helps reduce the risk of designs being developed using inappropriate techniques. Historic examples from the 19 th Century and early 20 th century (before sophisticated methods of groundwater analysis were available) are described, where developing a conceptual understanding of groundwater conditions was vital in developing practical engineering solutions.

A Survey on Quantum Computing Architectures: Implications for Electrical Circuit Design and Optimization

Quantum computing, a paradigm shift with the potential to revolutionize fields ranging from cryptography to optimization, is rapidly evolving. This survey delves into the key quantum computing architectures—gate-based and quantum annealing—and their profound impact on circuit design and optimization. Gate-based systems, such as those utilizing superconducting qubits and trapped ions, offer versatile platforms capable of executing a broad array of quantum algorithms. However, they present unique challenges for circuit designers, including noise sensitivity, scalability, and the need for complex error correction circuits. Quantum annealing, exemplified by D-Wave systems, offers a more specialized approach to solving optimization problems, requiring distinct circuit design considerations focused on energy efficiency and coherence preservation.This paper reviews the foundational research on these architectures, compares their respective design challenges, and examines the optimization techniques that have emerged in response to these challenges. Gate count reduction, error correction, and hybrid quantum-classical methods are highlighted as key approaches for improving circuit efficiency and scalability in quantum systems. Furthermore, this survey emphasizes the importance of interdisciplinary collaboration between quantum physicists, electrical engineers, and computer scientists to address the complex challenges associated with quantum circuit design. By combining expertise from these fields, researchers can develop innovative solutions that bridge the gap between theoretical concepts and practical hardware implementations. Ultimately, this survey underscores the need for continued innovation at the intersection of quantum computing and electrical engineering, as researchers strive to overcome current limitations and develop practical, large-scale quantum systems that can harness the full potential of this revolutionary technology.

Nonlinear Modeling of a Piezoelectric Actuator-Driven High-Speed Atomic Force Microscope Scanner Using a Variant DenseNet-Type Neural Network

Piezoelectric actuators (PEAs) are extensively used for scanning and positioning in scanning probe microscopy (SPM) due to their high precision, simple construction, and fast response. However, there are significant challenges for instrument designers due to their nonlinear properties. Nonlinear properties make precise and accurate control difficult in cases where position feedback sensors cannot be employed. However, the performance of PEA-driven scanners can be significantly improved without position feedback sensors if an accurate mathematical model with low computational costs is applied to reduce hysteresis and other nonlinear effects. Various methods have been proposed for modeling PEAs, but most of them have limitations in terms of their accuracy and computational efficiencies. In this research, we propose a variant DenseNet-type neural network (NN) model for modeling PEAs in an AFM scanner where position feedback sensors are not available. To improve the performance of this model, the mapping of the forward and backward directions is carried out separately. The experimental results successfully demonstrate the efficacy of the proposed model by reducing the relative root-mean-square (RMS) error to less than 0.1%.

Generating efficient circulant-like MDS matrices for implementation

The exploration of maximal distance separable codes (MDS codes) has been a longstanding focus in error-correcting code theory and holds significant relevance in cryptography. Numerous approaches have been investigated for constructing MDS matrices, including deriving them from MDS codes, utilizing Hadamard matrices, Cauchy matrices, Vandermonde matrices, circulant matrices, circulant-like matrices, among others. However, a major challenge for cryptography designers is finding MDS matrices with low implementation cost. In this paper, we propose algorithms for generating efficient circulant-like MDS matrices of size , and for implementation. Subsequently, we evaluate the fixed points, the number of XOR operations of the proposed MDS matrices, and compare them with MDS matrices of other well-known ciphers. These proposed MDS matrices can become promising candidates for many cryptographic algorithms in the future.

Empathy design method based on immersive interactive experiential spaces: A case study of Parkinson’s disease in China

It is a common challenge for designers to truly understand users’ behaviours and specific needs for universal design in the healthcare setting. This study proposes a new design method that allows designers to not only consciously understand the special user group, but also design for them in embodied scenarios. It aims to explore the effectiveness of experiential spaces in fostering designers’ empathy, stimulating design creativity, and proposing quality design solutions. Taking Parkinson’s disease (PD) as an example, this study developed the ‘PD Room’, an immersive and interactive experiential space. Participants were allowed to experience story scenarios of Parkinsonian under the development of symptoms from early to late stages. The results proved that the immersive interactive experience space method is an effective tool to assist designers in idea generation and multi-dimensional creativity. We hope that this method can be generalized to support practices of universal design through immersive empathic experiences.

Promoting Plant-Based Sustainable Diet to Support Future Development: Emotional Design Card Development

The quest for a plant-based sustainable diet has significant value for promoting future development, posing novel challenges for designers. This study involved a five-step design process, encompassing a case study, an experimental study, prototype conception, user testing, and design refinement, with the aim of developing a “Plant-based Sustainable Diet 3P Emotional Design Method” card set that enables individuals to devise personalized sustainable diet plans. The results demonstrated that the instinctive level originates from the product itself, signifying the efficacy of sensory design cues for plant-based foods. The behavioral level stems from the interactive content generated by the product, denoting the efficacy of design cues and highlighting the advantages of transitioning to healthier ingredients for the body. The reflective level arises from the reflection and contemplation of the product, signifying the efficacy of value perception and design cues pertaining to economic, environmental, and social sustainability knowledge. The study analyzed the influencing factors of diet choices through emotional design and provided insights into the underlying psychological mechanisms. The theoretical contribution of this study lies in the novel integration of emotional design and sustainable diet research, while its practical contribution is the introduction of methods and tools that facilitate the adoption of plant-based sustainable diet practices at the individual level.

Experimental and Numerical Analysis of an Innovative Combined String–Cable Bridge

Suspension bridges, such as stress-ribbon, are among the simplest structural bridge systems and have the lowest structural height. The flexibility of these elegant bridges poses great challenges for designers to minimize their deformability under asymmetrical operational loads. Due to the small initial sag, such load-bearing structures also cause significant tensile forces, which requires them to have large cross-sections and massive anchor foundations. This paper analyzes an innovative suspension steel bridge structure combined with a string and a cable. More attention is paid to asymmetric loading as this is more relevant for suspension structures. The new structure is studied numerically and experimentally. It is established that the string stabilizes the displacements of the bridge under asymmetric loading. The stabilization efficiency is proportional to the value of the pre-tension force of the string. The obtained results reveal the behavior of the structure and enable an evaluation of the accuracy of the numerical results, as well as the applied modeling. In addition, the experimentally obtained results allow the evaluation of more aspects of the behavior of the new bridge, which will be useful in further studies of this type of structures.

Neural Network-Based Surrogate Modeling for Buckling Performance Optimization of Lightweight-Composite Collapsible Tubular Masts.

The collapsible tubular mast (CTM) can be compactly folded for transport and deployed in orbit to serve as a key structural element. Once deployed, the CTM is vulnerable to buckling under axial load and bending moments, compromising its load-bearing capacity. The intricate relationship between the CTM's cross-section and its buckling behavior poses a significant challenge for designers. This is due to the ultra-thin nature of the CTM, which gives rise to highly localized buckling modes rather than global ones. To overcome this challenge, we developed surrogate models using a neural network (NN) trained with data from finite element analysis (FEA). These NN-based surrogate models provide high computational accuracy in predicting nonlinear buckling loads under axial force and bending moments around the two principal axes of the CTM's cross-section, achieving R2 values of 0.9906, 0.9987, and 0.9628, respectively. These models also significantly improve computational efficiency, reducing prediction time to a fraction of a second compared to several minutes with FEA. Furthermore, the NN-based surrogate models enable the usage of the non-dominated sorting genetic algorithm (NSGA-II) for multi-objective optimization (MOO) of the CTMs. These models can be integrated in the NSGA-II algorithm to evaluate the objective function of existing and new individuals until a set of 1000 non-dominated solutions, i.e., cross-sectional configurations optimizing buckling performance, is identified. The proposed approach enables the design of ultra-thin CTMs with optimized stability and structural integrity by promoting design decisions based on the quantitative information provided by the NN-based surrogate models.

Landscape Design of Memorial Garden Based on Computer Vision Communication and Realization by Visual Quality Prediction

This paper discusses the balance between artistry and science in the landscape design of memorial gardens, which relies on visual quality prediction. This paper introduces the theoretical basis of vision quality prediction, including the definition, evaluation method and prediction model of vision quality. This paper analyzes the artistry and scientificity of memorial garden landscape design. It expounds that artistry emphasizes the designer’s innovation and aesthetic expression, while scientificity focuses on the feasibility and practicability of design. Finding a balance between the two, so that the design can meet aesthetic and practical needs is an essential challenge for designers. The application of visual quality prediction in memorial garden landscape design and its influence on the balance between artistic and scientific design are discussed in detail. It is found that visual quality prediction can provide a scientific basis for designers to make decisions and help them create high-quality visual effects while meeting practical needs. The research results are summarized, and the future research direction is prospected. With the development of computer technology and artificial intelligence technology, visual quality prediction will play an increasingly important role in landscape design.

Design frameworks for ventilative cooling: Perceptions from building design practitioners in Ireland and the United Kingdom

The global increase in building cooling demands poses a challenge for designers striving for net zero energy consumption. The prevalent use of mechanical cooling underscores the necessity for designers to consider Ventilative Cooling as a viable alternative in the early stages of building design. This paper presents findings from an exploratory survey and semi-structured interviews of industry experts in Ireland and the United Kingdom about their design processes and experienced-based approaches to designing Ventilative Cooling. The findings suggest that the pre-design stage has the same influence for promoting ventilative cooling strategies as the schematic and detailed design stages for practitioners, yet limited impactful decision making occurs at this stage. Over 70 % of the survey respondents reported satisfaction with current Ventilative Cooling tools used in building design. Only 8 % of architects use a ventilative cooling tool, while engineers always do, showing that separate design advice is needed for architects and engineers. The interview findings indicate that early-stage design interventions for Ventilative Cooling can be improved if there was more empirical evidence of how strategies perform available as design guidance in ventilative cooling design guidelines. Additionally, engineers highlighted that post-occupancy evaluation and site monitoring of existing buildings are crucial stages of further research that can identify the effectiveness of Ventilative Cooling design decisions. In their building designs, the practitioners reported a need for preparedness to assess resilience to extreme future climate events such as heat waves. Effective communication between industry and academic research can help improve the built environment industry's future readiness.

Towards interculturally adaptive conversational AI

Abstract Among the many ways that AI technologies are becoming embedded in our social worlds is the proliferation of Conversational User Interfaces, such as voice assistants (e.g. Apple Siri and Amazon Alexa), chatbots and voice-based conversational agents. Such conversational AI technologies are designed to draw upon the designers’ understanding of interactional practices employed in human–human conversation, and therefore have implications for intercultural communication (ICC). In this paper, we highlight some of the current shortcomings of conversational AI, and how these relate to ICC. We also draw on findings from Conversation Analysis to discuss how pragmatic norms vary across linguacultural groups (see Risager, Karen. 2019. Linguaculture. In Carol A. Chapelle (ed.). Encyclopedia of applied linguistics. Wiley-Blackwell for a discussion of the term ‘linguaculture’), noting that this poses further challenges for designers of conversational AI systems. We argue that the solution is to work towards what we call interculturally adaptive conversational AI. Finally, we propose a framework for how this can be conceptualised and researched, and argue that researchers with expertise in language and ICC are uniquely placed to contribute to this endeavour.

CiaBOT: the circular design of an experimental microarchitecture between material and immaterial values

The transition to a circular economy entails new challenges for architects and designers. Among these, one challenge is to look at waste not only as new resources, from an environmental perspective, but also as bearers of information capable of communicating their history and origin. Moreover, waste can be considered as a means of activating unexpected knowledge and social connections. The article illustrates a circular design experimentation, conducted with architecture and design students and a wine farm, which led to the creation of the CiaBOT project, a belvedere aimed at enhancing the landscape and providing a temporary stopping point in the Monferrato hills (UNESCO World Heritage Site, Italy). CiaBOT is not only a belvedere but is a microarchitecture capable of conveying both material and immaterial cultural values. Its form and materials are intimately connected with the territory with and for which it was designed. These make CiaBOT a “space” of hybridization and dialogue between agricultural tradition and innovation. But it is also a “space” of fieldwork education and knowledge co-generation in which academic and non-academic stakeholders have measured themselves. Through the description of the different stages of the design process, the article is part of the debate on new sustainable ways of designing and building, reflecting on new models of circular economy based as much on design strategies and processes as on the enhancement of human labor and the use of technologies appropriate to the context and actors.

The Application of Space Syntax to Enhance Sociability in Public Urban Spaces: A Systematic Review

Public urban spaces are vital settings for fostering social interaction among people. However, understanding how spatial layouts can promote positive social behaviors remains a critical and debated challenge for urban designers and planners aiming to create socially sustainable environments. Space syntax, a well-established theory and research method, explores the influence of spatial configurations on social aspects. Despite its significant contributions, there is a lack of comprehensive systematic reviews evaluating its effectiveness in enhancing social interaction within urban public spaces. This study aims to identify the existing scientific gaps in the domain of space syntax studies, with a primary focus on sociability in public urban spaces. Following the PRISMA framework, a thorough literature search was conducted in the Scopus database, yielding 1107 relevant articles. After applying screening and eligibility criteria, 26 articles were selected for in-depth review. This review adopted a novel approach to synthesizing and analyzing the findings for identifying underexplored scientific gaps. The findings suggested a wide variety of research gaps to address, encompassing evidence, knowledge, practical, methodological, empirical, theoretical, and target populations to provide a thorough overview of the current state of knowledge in this field. In conclusion, by exploring the interplay between space syntax and design elements such as the urban infrastructure, landscaping, and microclimate in these areas, future research can bridge this gap, particularly when considering a cross-cultural lens. This study underscores the importance of space syntax in promoting social interaction in urban public spaces, offering a robust foundation for future research and practical applications to create more socially engaging environments.

A Review of Tunable Inductors for Power Electronics: Techniques and Applications

Magnetic components are recently being researched and believed to be a main source of losses, and increasing the weight of power converters, which has become a real challenge for designers. Controlled magnetics for power electronic applications is a promising but still-evolving technology that started to gain momentum as it enabled circuit designers to achieve an extra degree of control freedom and greater optimization in terms of cost, losses, and size during the design stages of different power converters. In this paper, a comprehensive review is carried out on practical tunable magnetic techniques that may turn out to be a viable solution and find their usage in power electronic applications. In addition, several technologies that can be used in the realization of controlled magnetic components, including but not limited to current-controlled magnetics, voltage-controlled magnetics, and self-regulated magnetics, are being investigated to define the merits and drawbacks of each technology for potential future usage. This article is mainly focused on controlled power inductors for various power electronic applications, and its main goal is to assist designers in selecting the suitable technology for their applications.

Research on the Movement Speed of Situational Map Symbols Based on User Dynamic Preference Perception

When designing situational maps, selecting distinct and visually comfortable movement speeds for dynamic elements is an ongoing challenge for designers. This study addresses this issue by conducting two experiments to measure the human eye’s ability to discern moving speeds on a screen and examines how symbol movement speeds within situational maps affect users’ subjective experiences, task performance, and visual comfort. The first experiment measured participants’ speed discrimination capabilities for Landolt Ring of varying sizes moving at 0–256°/s, yielding speed discrimination thresholds of 7–23% and a sensitive velocity range of 1–64°/s. The second experiment evaluated observers’ visual perceptions of moving elements within a cognitive task across the same range of 1–64°/s, identifying three significant benchmarks—8°/s, 16°/s, and 32°/s. These can be utilized to categorize slow-, moderate-, and fast-moving symbols in situational maps. The findings can aid in designing human–machine interface environments with improved viewer experience and visual comfort for both Air Traffic Control interfaces and situational maps.

Characterization of material flow behavior in friction stir welded AA2014 aluminum alloy joints

Abstract Steel rivets serve as a substitute material for connecting similar and dissimilar materials within the structural fabrication industries. However, the use of steel rivets can result in a significant increase in the structure’s weight and may trigger corrosion at the interface due to galvanic coupling. Combining dissimilar alloys through the fusion welding process poses numerous challenges for manufacturers and designers. A solid-state welding technique called friction stir welding (FSW) has been developed. FSW can effectively join materials without reaching their melting points, relying on severe plastic deformation and recrystallization to form a welded joint. The proper selection of the tool and process parameters is essential for achieving a sound weld. The findings of this study indicate that plastic deformation, material flow, and recrystallization play pivotal roles in the strength of the joint. This implies that FSW represents an ideal joining process for high-strength alloys and serves as a viable alternative to replace permanent joints like rivets.

Redefining Future Expectations: How to unlock differentiation in the era of generative AI

We are on the cusp of a customer-service revolution, driven by generative AI. The technology, with its ability to derive deep insights and generate new content based on vast stores of structured and unstructured data, opens the opportunity to craft richer, more satisfying experiences. This, of course, is a significant opportunity for organisations looking to deepen their relationships with internal employees and end customers. But it also poses a genuine challenge for service designers: As gen AIraises expectations for targeted, relevant and useful interactions, designers will increasingly be charged not just with meeting those expectations, but constantly exceeding them.

Urban morphology as a key parameter for mitigating urban heat? – A literature review

Abstract More frequent and intense heat waves, especially in urban centers, represent a growing challenge for urban designers and building planners. In the last five years, extensive research has been undertaken on the relation between urban form, including density, and urban heat phenomena. Dense urban configurations are often considered central drivers of hot microclimates. However, less dense cities easily cause other ecological (e.g. land consumption), functional (public mobility), and socioeconomic (social diversity) problems. Consequently, the current panoply of recommended heat mitigation and sustainability measures constitutes an unclear basis for strategic planning decisions. Thus, this study examines the literature on urban morphology in relation to urban heat events. Around 800 scientific articles and studies are categorized regarding the applied methodology, the studied geographic location, the observed urban form parameters, and the examined thermal parameter. Most identified literature uses traditional field measurement, remote sensing, numerical simulation, or a combination. Air temperature and land surface temperature are the most observed thermal parameters, while the growing number of studies that focus on human outdoor thermal comfort is highly relevant for effective heat mitigation and adaptation. This study suggests that from a scientific point of view, urban morphology measures do not principally carry a paramount role in heat mitigation compared to other aspects, such as vegetation or materialization. Current planning approaches for climate-resilient cities are highly case-specific, where no generally applicable rules or effective recipes regarding urban built form are available.

Precision refined: Integrating micromachining constraints for enhanced product accuracy through topology optimization

The deviation of micromachined products from their intended design poses a significant challenge for designers. To address this issue, numerical simulations can be employed for predicting such deviations. In this research paper, we present a methodology aimed at preserving accuracy in micromachining products resulting from topology optimization, particularly when intricate geometric features are involved. The accuracy of final products can be difficult to achieve due to the inherent limitations of microfabrication processes, specifically in lithography and etching. To overcome these limitations, our proposed methodology combines density filters and morphological operators to generate lithography masks that closely align with the surface of micromachined silicon. We have validated the efficacy of this methodology by selecting a benchmark problem focused on maximizing the stiffness of a cantilever beam across various volume fractions. The results demonstrate a significant improvement in accuracy while maintaining adherence to the desired design specifications. Additionally, we have conducted simulations of surface micromachining with photolithography to further substantiate the effectiveness of our proposed method in achieving enhanced accuracy for optimized topological structures. These findings hold practical implications for the design of Micro Electronic Mechanical Systems (MEMS) and other similar applications where accuracy is of paramount importance. By providing a means to compensate for the limitations inherent in microfabrication processes, our proposed methodology can contribute to the production of highly accurate and topologically optimized products.

Network on Chip and Its Low Power Techniques

The advent of Network-On-Chip (NoC) architecture has significantly revolutionized the design of complex System-On-Chip (SoC) systems by providing scalable and efficient communication infrastructures. NoC architectures offer advantages such as high bandwidth; low latency and better scalability compared with traditional bus-based communication architectures. However, the ever-increasing demand for higher performance and lower power consumption poses significant challenges for NoC designers. This article reviews the basic architectures and design issues of NoCs with SoCs and further extended with research challenges and low power techniques. Key Words: Network-On-Chip, System-On-Chip, latency and scalability