Design Space Research Articles

Research on the division of heat dissipation spaces for multiple heat sources based on the adiabatic characteristic of heat flow lines

Due to the pressing need for compact layouts, the spacing between high-power devices is gradually decreasing, making the mutual influence between multiple heat sources unavoidable. Therefore, this paper proposes a method based on the adiabatic characteristics of heat flow lines and their convergence positions to evaluate the rationality of the thermal space design of each heat source. This method has been validated for applicability in one-dimensional, two-dimensional, and three-dimensional multi-heat-source conjugate convection heat transfer. Heat flow lines have significant advantages in describing energy flow, as they align with the direction of the temperature gradient. In thermal spaces with adiabatic boundaries or mutual influences between multiple heat sources, heat flow lines converge at certain positions. The relationship between adiabatic boundaries and heat flow line convergence positions has been studied, and a more interpretative decoupling scheme for multi-heat-source systems has been proposed. The main feature of this scheme is the separation of each heat source in the same steady-state thermal space and assigning adiabatic boundaries to the solid partition surfaces, allowing efficient observation of the thermal conditions of individual heat sources and targeted layout optimization. Results indicate that this method can utilize changes in heat flow line convergence positions to assess current thermal conditions and can be used to compare the thermal performance of different shaped heat sinks. Simulation results show that under the same mass conditions, thin-fin heat sinks perform 47 % better than thick-fin heat sinks, providing a more comprehensive and intuitive assessment compared to metrics such as thermal resistance and average temperature. The proposed method offers new ideas for multi-heat-source layout optimization, heat flow control, multi-heat-source partitioned simulation, and abnormal heating detection in multiple heat sources.

Rural activity spaces integration with creative market models

AbstractAs urbanization advances and societal shifts unfold, the integration of rural development and activity spaces has become a focal point in academic discourse. This study aims to explore the synergistic effects of the creative market model on rural activity spaces, dissecting its role in shaping these spaces, enhancing community engagement, and generating socio-economic benefits. Empirical findings highlight the affirmative role of the creative market model in this fusion. The research on community participation and spatial design reveals how creative markets enhance residents' sense of involvement and explores the influence of activity space design on community interaction. This study, by thoroughly examining the integration of the creative market model and rural activity spaces, offers theoretical and empirical support for advancing rural development.

Semiautomatic Exploration of Conceptual Design Spaces through Parametric Shape Variability and Additive Manufacturing

Design ideation activities that involve the manipulation of geometry rely heavily on manual input. For feasibility reasons, the generation of design alternatives must often be limited, particularly when these alternatives need to be prototyped and tested. This paper describes a conceptual design strategy that leverages variational three-dimensional geometry to automatically generate a large number of design alternatives from a template model and their corresponding physical prototypes for evaluation and testing. In our approach, 3D geometric variations are produced automatically from a single design concept modeled parametrically, which are then used to generate 3D-printable files. Our method is suitable for design scenarios where real-world testing is preferred over virtual simulation and requires designers to consider a concept idea as a family of solutions, instead of a single design option. Our strategy enables an effective exploration of conceptual design spaces in highly constrained situations and facilitates parallel prototyping, which is known to produce better results than serial prototyping. We demonstrate the feasibility and effectiveness of the proposed method through a case study that involves the design of an instrument for ophthalmic surgery for extracting an intraocular lens (IOL) from the eye. Using our approach, nine unique concept families comprising a total of 150 designs were rapidly and successfully prototyped and tested.

Shape optimization of non-matching isogeometric shells with moving intersections

While shape optimization using isogeometric shells exhibits appealing features by integrating design geometries and analysis models, challenges arise when addressing computer-aided design (CAD) geometries comprised of multiple non-uniform rational B-splines (NURBS) patches, which are common in practice. The intractability stems from surface intersections within these CAD models. In this paper, we develop an approach for shape optimization of non-matching isogeometric shells incorporating intersection movement. Separately parametrized NURBS surfaces are modeled using Kirchhoff–Love shell theory and coupled using a penalty-based formulation. The optimization scheme allows shell patches to move without preserving relative location with other members during the shape optimization. This flexibility is achieved through an implicit state function, and analytical sensitivities are derived for the relative movement of shell patches. The introduction of differentiable intersections expands the design space and overcomes challenges associated with large mesh distortion, particularly when optimal shapes involve significant movement of patch intersections in physical space. Throughout optimization iterations, all members within the shell structures maintain the NURBS geometry representation, enabling efficient integration of analysis and design models. The optimization approach leverages the multilevel design concept by selecting a refined model for accurate analysis from a coarse design model while maintaining the same geometry. We adopt several example problems to verify the effectiveness of the proposed scheme and demonstrate its applicability to the optimization of the internal stiffeners of an aircraft wing.

Evaluation and quantification of sound intelligibility (SdI): Metro commercial spaces as an example

Sound intelligibility (SdI) is investigated in the context of modelling aural comfort in the design of metro commercial spaces. The term describes an individual's clear aural perception of their surrounding environment. The present paper describes the key objective variables used to evaluate and quantify SdI for inclusion in models predicting aural comfort. In-situ and laboratory questionnaire surveys were conducted to measure SdI in various spatial forms of metro commercial spaces. The significantly influencing factors were studied using Pearson correlation and linearity analysis. The results show that acoustic parameters such as sound levels, sound source, and reverberation time (RT) are not key factors in the evaluation of SdI, but the variables of spatial form and sound absorptions are. Based on the findings of analyzing the key influencing factors, prediction models for quantifying SdI were developed. The results show that there is no holistic approach to quantifying SdI for all kinds of metro commercial space, due to the distinct spatial form of each type of the spaces.

Homing into school to create the ideal classroom: young people want to combine the best of home and school learning environments

ABSTRACT We asked 28 young people (16–18 Years old) from two schools in Lancashire to reflect on their COVID-19 experience and Co-Design the ideal learning environment. In this paper, we present young people’s vision for the ideal classroom that combines the best of the home and school learning environments. Young people would like to have flexible furniture arrangements, with space for group and individual activities, a bespoke learning environment that can be appropriated and adjusted according to individual preferences (e.g. sound, light, temperature, ventilation levels). Furthermore, they aim for comfortable environments with earth colours, natural materials and a direct connection with nature. We argue the importance of taking young people's perspectives presented here to inform future policy, the design of learning spaces and school rebuilding programmes.

Comparison of Optimization Methods for the Attitude Control of Satellites

The definition of multiple operational modes in a satellite is of vital importance for the adaptation of the satellite to the operational demands of the mission and environmental conditions. In this work, three optimization methods were implemented for the initial calibration of an attitude controller based on fuzzy logic with the purpose of performing an initial exploration of optimal regions of the design space: a multi-objective genetic algorithm (GAMULTIOBJ), a particle swarm optimization (PSO), and a multi-objective particle swarm optimization (MOPSO). The performance of the optimizers was compared in terms of energy cost, accuracy, computational cost, and convergence capabilities of each algorithm. The results show that the PSO algorithm demonstrated superior computational efficiency compared to the others. Concerning the exploration of optimum regions, all algorithms exhibited similar exploratory capabilities. PSO’s low computational cost allowed for thorough scanning of specific interest regions, making it ideal for detailed exploration, whereas MOPSO and GAMULTIOBJ provided more balanced performance with constrained Pareto front elements.

Evaluating Apartment Satisfaction in Erbil City: The Impact of Interior Space Quality Indicators before, during, and after the COVID-19 Pandemic

Human existence and development have always relied on suitable shelter. The dual-directional relationship of human residence has always been a material dealt with to enhance residential living conditions. The emergence of the COVID-19 pandemic introduced abrupt and dramatic changes to human life protocols that exerted clear pressure on different sectors within the built environment. Housing experienced a great impact due to the need for social distancing and quarantine obligations to support human life. In this study, in order to measure human adaptation and residence alterations following new residential requirements, the quality of interior space investigations to promote a better built environment for occupants was facilitated using the theory of residential dissatisfaction, already adopted in the current study. Residents’ responses were extracted regarding their dissatisfaction by applying the Likert scale for measurement and evaluation. This study focused on homogenous housing estates in Erbil City. Apartments were precisely selected with different plans and building layouts for widespread use in the city. They were occupied during the three stages of the study to extend beyond investigating the direct impact of the pandemic on the permanence of alterations and adaptation even after the pandemic. The reasons for changed dissatisfaction levels were investigated to improve the reliability of formulating final conclusions and recommendations. The findings showed increased dissatisfaction during the pandemic in most spaces; apartment layout and space design significantly affected responses and demands. The levels of dissatisfaction after the pandemic changed from stable to a slight decline in dissatisfaction. The effect of limited external spaces in apartments limited the possibility of managing pressure. This case might be less demanding in single-family housing due to the availability of private gardens. The results indicate that five distinct spaces were affected by the pandemic: the living room, family dining area, children’s bedroom, laundry room, and storage area. The dissatisfaction with these spaces increased during the pandemic and either remained unchanged or continued to rise afterward.

A full-scale experimental investigation of natural gas explosion in a 710-m long utility tunnel with multiple pipelines

Natural gas poses significant risks to the safe operation of utility tunnels, which house multiple critical infrastructure systems, including natural gas pipelines. To date, no full-scale gas explosion tests in utility tunnels have been published, and there is ongoing debate about whether pipelines can withstand such explosions. This study presents the first-ever 1:1-scale experiments conducted in a 710-meter-long tunnel with cross-sectional dimensions of 3.2 m × 2.6 m. Three pipelines, each approximately 25 m in length and constructed to industrial standards, were used to investigate potential damage. The experiments comprehensively captured the development of flow fields, including flame images, flame signals, temperature, and overpressure, as well as pipeline responses. Results revealed that variations in overpressure within the combustion region were driven by both positive and negative feedback loops. A significant pressure drop was also observed as airflow passed through a local expansion. The experiments further demonstrated that while pipelines within utility tunnels are unlikely to be directly damaged by gas explosions, accessories such as racks are at high risk of severe destruction. These findings offer essential insights for improving the safety design, construct, and operation of tunnel-like spaces involving flammable gases.

Move, Connect, Interact: Introducing a Design Space for Cross-Traffic Interaction

Rising diversity through novel forms of mobility and increasing connectivity through intelligent systems and wireless connection is leading to a complex traffic environment. However, traditional automotive interface research often focuses on the interaction between vehicle and driver, passenger, or pedestrian, not capturing the interconnected relationships among various traffic participants. Therefore, we developed a design space for Cross-Traffic Interaction (CTI) based on a focus group with six HCI experts, encompassing the dimensions: (1) interaction partners, (2) their traffic situations, and (3) their interaction relationship. Through a systematic literature review, we classified 116 publications, showing less-studied interaction possibilities. Illustrating the practical application of our design space, we developed three interactive prototypical applications: Shooting Stars, Flow Rider, and Road Reels. A study (N=12) shows that the applications were received well and could improve traffic experience. Overall, our design space serves as a foundational tool for understanding and exploring the challenges and diverse opportunities within CTI, bridging the gap between traditional automotive interface research and the complex realities of modern traffic environments.

Variation-aware automated design and optimization of sub-1V bandgap voltage reference

A robust systematic gm/ID-based design procedure for a CMOS low-voltage bandgap reference is introduced. The proposed approach is technology node independent, and it eliminates invoking the simulator in the loop by using precomputed lookup tables (LUTs) generated once. The proposed methodology is capable of addressing the impact of PVT corners and random mismatch. The proposed procedure is verified against Spectre simulations and yields very accurate results. Moreover, the bandgap reference automated synthesis procedure is fully vectorized, enabling the concurrent synthesis of multiple design points in a short time. As a result, large datasets can be generated to span the whole design space, which enables global optimization. Next, local optimization algorithms can be utilized to quickly determine the degrees of freedom of an optimal design point that meets a set of specifications. The speedup of the proposed methodology is around 140x compared to simulation-based optimization in addition to accomplishing better results.

Edge-Light: Exploiting Luminescent Solar Concentrators for Ambient Light Communication

A recent advance in embedded Internet of Things (IoT) exploits ambient light for wireless communication. This new paradigm enables highly efficient links via simple light modulation, but the design space has a fundamental constraint: in most State of the Art (SoA) studies, the link can only follow the propagation direction of ambient light. Consider, for example, a swarm of drones and ground robots that want to communicate with sunlight. Drone-to-robot communication could be possible because sunlight travels downwards from the air (drone) to the ground (robot), allowing drones to modulate light to send information to robots beneath them. Robot-to-robot communication, however, is not possible because sunlight does not travel sideways (parallel to the ground). To allow 'lateral communication' with ambient light, we propose using Luminescent Solar Concentrators (LSC). These optical components receive ambient light on their surface and re-direct part of the spectra towards their edges. Considering this optical property of LSC, our work has three main contributions. First, we benchmark various optical properties of LSC to assess their performance for ambient light communication. Second, we combine LSC with liquid crystal (LC) shutters to form lateral links with ambient light. Third, we test our links indoors and outdoors with artificial and natural ambient light, by enhancing two robots with our LSC transceivers and showing that they can exchange basic commands and coordinate tasks by communicating only with sunlight.

Optimization of Jiyang depression block X shale condensate reservoir well spacing based on geology–engineering integration

Appropriate well spacing is crucial for the efficient development of shale reservoirs, as it is closely related to the degree of resource utilization. Well spacing design is influenced by both fracturing processes and geological characteristics. While increasing well density can enhance reservoir recovery, it may lead to higher investment costs and significant well interference issues. In this study, we adopted an integrated geological–engineering approach, combining fracture propagation simulation, EDFM (Embedded Discrete Fracture Modeling), and numerical simulation methods to comprehensively analyze well interference under different well spacings in shale condensate reservoirs. Development well spacing was optimized using the degree of resource utilization and well interference rate as key indicators. There are three main research findings: (1) The geological engineering integration approach allows for differentiated well spacing according to specific research areas. Combining this integrated approach with EDFM and leveraging quantitative evaluation, we have developed an efficient and precise methodology for well spacing optimization. (2) When well spacing is less than the length of hydraulic fractures, inter-well fractures exhibit an entangled pattern, reducing the effectiveness of fracturing treatments and causing severe well interference. As well spacing increases, interference between fractures from different wells diminishes, but unstimulated volumes gradually emerge, leading to a decrease in reservoir recovery. (3) Considering both well interference and resource utilization, a well spacing of 400 m is recommended in the study area. At this spacing, interference between hydraulic fractures from different wells is minimal. After 10 years of production, the estimated reservoir recovery is 39.16%, with a production rate of 25.58% and a well interference rate of 13.58%. These research outcomes provide valuable insights for optimizing the well spacing of hydraulic fractured horizontal wells in shale condensate reservoirs.

Chinese Art and Design of Bathroom Space for the Elderly

Chinese Art and Design of Bathroom Space for the Elderly

Exploring the Mediating Role of Physical Activity in the Relationship between Green Space Exposure and Well-being: Results from the AUGS Survey

Although previous studies have shown that exposure to nature has a positive impact on physical and mental health, the factors that produce such benefits are still not well established, especially in high- and middle-income countries. In the present study, we implemented a mediation approach between green space exposure and psychological distress, body fat percentage and well-being index in Tirana (Albania), through the mediation of physical activity. The significant direct effects of green space on body fat percentage index (BFPI), psychological distress index (PDI) and well-being index, together with the relatively smaller mediating role of physical activity, offer insightful implications for the design and prioritization of urban green spaces. The differential impact on health outcomes suggests a complex association that is not only mediated by physical activity, but also offers clear benefits by reducing psychological distress (as indicated by PDI scores) and significantly improving overall well-being. This dichotomy highlights the multifaceted role of green spaces in public health, requiring a broad lens that goes beyond physical health metrics to include mental health and subjective well-being. Our findings also confirm the intrinsic value of green spaces in improving well-being and reducing psychological distress, independent of the physical activities they may promote.

Interactive design of new media images and architectural space: taking Hangzhou as an example

ABSTRACT Traditional architectural space design often relies on fixed display boards, paper guides, and static displays. Viewers can only passively receive information and lack opportunities to interact with the displayed content, making it difficult to generate deep participation and personalized experiences. This article applied new media images into the interactive design of architectural spaces, transforming and innovating traditional architectural spaces, and providing audiences with a richer and more attractive spatial experience. The navigation service was set as the architectural space design goal, and analyzed using the Leifeng Tower building in Hangzhou as an example. Building Information Modeling (BIM) was used to digitally model the Leifeng Tower building, accurately simulating the building structure, spatial layout, and landscape information. By adding virtual information annotations and navigation routes, tourists were provided with a more diverse and colorful architectural space experience. The experimental results showed that among 400 tourists, the highest number of tourists using augmented reality navigation was 204, and the average satisfaction score of tourists with augmented reality navigation reached 90. Moreover, presenting the guide content in a multimodal form can better enhance the spatial experience of tourists. The use of augmented reality in architectural spatial interaction design can enrich tourists’ perception and experience in the architectural space, enabling them to interact with the building in a more vivid and interactive way.

Design optimization of lightweight automotive seatback through additive manufacturing compression overmolding of metal polymer composites

With the growing demand for enhanced automotive fuel efficiency and environmental sustainability, there is a need for lightweighting automotive components through innovative design and manufacturing processes. This study leverages a combination of numerical iterative design optimization and hybrid additive manufacturing–compression molding (AM-CM) technique for metal polymer composites to lightweight an automotive seatback. The AM-CM process enables robust mechanical interlocking between metals and composites, boasting high stiffness and strength with low overall density. Replacing metallic components with such metal polymer composites allows for comparable mechanical performance while significantly reducing the overall weight. First, the automotive seatback design space is reduced to critical load carrying regions using topology optimization and high stress concentration areas are identified using finite element analysis. Next, a lightweight metal polymer subcomponent is designed for a high stress concentration region. The full seatback frame with spatially heterogeneous material-specific design is then iteratively optimized to enable enhanced stiffness with minimal weight. Overall, the automotive seatback frame designed with location-specific metal, polymer, and metal polymer composite materials weighs 20% less than the metal-only design while exhibiting similar stiffness.

Synthetic Protein Nanoparticles via Photoreactive Electrohydrodynamic Jetting.

Protein nanoparticles are an attractive class of materials for nanomedicine applications due to the intrinsic biocompatibility, biodegradability, and intrinsic functionality of their constituent proteins. Despite the clinical success of select protein nanoparticles, this class of nanocarriers remains understudied and underdeveloped compared to lipid and polymer nanoparticles due to challenges related to formulation optimization, large design space, and their structural complexity. In this work, a modular strategy for protein nanoparticle preparation based on the concept of photoreactive jetting is introduced. The process relies on continuous ultravioletirradiation during electrohydrodynamic (EHD) jetting of protein solutions that contain a homobifunctional photocrosslinker. Protein nanoparticles exhibit nanogel-like architectures comprised of proteins that are linked via synthetic moieties. Compared to conventional protein nanoparticles, this method reduces nanoparticle processing times to minutes, rather than hours to days. The inclusion of an emissive structural motif as the molecular scaffold of the photocrosslinker is used to study the supramolecular architecture of the stable nanoparticles via time-resolved fluorescence spectroscopy.

Design and Optimization of a Magnetic Field Generator for Magnetic Particle Imaging with Soft Magnetic Materials

Magnetic field generators are a key component of Magnetic Particle Imaging (MPI) systems, and their power consumption is a major obstacle on the path to human‐sized scanners. Despite their importance, a focused discussion of these generators is rare, and a comprehensive description of the design process is currently lacking. This work presents a methodology for the design and optimization of selection field generators operating with soft magnetic materials outside the linear regime in the context of MPI. Key elements are a mathematical model of magnetic field generators, a formalism for defining field sequences, and a relationship between power consumption and field sequence. These are used to define the design space of a field generator given its system requirements and constraints. The design process is then formulated as an optimization problem. Subsequently, this methodology is then utilized to design a new magnetic field generator specifically for cerebral imaging studies. The optimization result outperforms our existing MPI field generator in terms of power consumption and field of view size, providing a proof‐of‐concept for the entire methodology. As the approach is very general, it can be extended beyond the MPI context to other areas such as magnetic manipulation of medical devices and micro‐robotics.

GOLDBAR: A Framework for Combinatorial Biological Design.

With the rise of new DNA part libraries and technologies for assembling DNA, synthetic biologists are increasingly constructing and screening combinatorial libraries to optimize their biological designs. As combinatorial libraries are used to generate data on design performance, new rules for composing biological designs will emerge. Most formal frameworks for combinatorial design, however, do not yet support formal comparison of design composition, which is needed to facilitate automated analysis and machine learning in massive biological design spaces. To address this need, we introduce a combinatorial design framework called GOLDBAR. Compared with existing frameworks, GOLDBAR enables synthetic biologists to intersect and merge the rules for entire classes of biological designs to extract common design motifs and infer new ones. Here, we demonstrate the application of GOLDBAR to refine/validate design spaces for TetR-homologue transcriptional logic circuits, verify the assembly of a partial nif gene cluster, and infer novel gene clusters for the biosynthesis of rebeccamycin. We also discuss how GOLDBAR could be used to facilitate grammar-based machine learning in synthetic biology.