Design Space Research Articles

Comparison of ANN and XGBoost surrogate models trained on small numbers of building energy simulations.

Surrogate optimisation holds a big promise for building energy optimisation studies due to its goal to replace the use of lengthy building energy simulations within an optimisation step with expendable local surrogate models that can quickly predict simulation results. To be useful for such purpose, it should be possible to quickly train precise surrogate models from a small number of simulation results (10-100) obtained from appropriately sampled points in the desired part of the design space. Two sampling methods and two machine learning models are compared here. Latin hypercube sampling (LHS), widely accepted in building energy community, is compared to an exploratory Monte Carlo-based sequential design method mc-intersite-proj-th (MIPT). Artificial neural networks (ANN), also widely accepted in building energy community, are compared to gradient-boosted tree ensembles (XGBoost), model of choice in many machine learning competitions. In order to get a better understanding of the behaviour of these two sampling methods and two machine learning models, we compare their predictions against a large set of generated synthetic data. For this purpose, a simple case study of an office cell model with a single window and a fixed overhang, whose main input parameters are overhang depth and height, while climate type, presence of obstacles, orientation and heating and cooling set points are additional input parameters, was extensively simulated with EnergyPlus, to form a large underlying dataset of 729,000 simulation results. Expendable local surrogate models for predicting simulated heating, cooling and lighting loads and equivalent primary energy needs of the office cell were trained using both LHS and MIPT and both ANN and XGBoost for several main hyperparameter choices. Results show that XGBoost models are more precise than ANN models, and that for both machine learning models, the use of MIPT sampling leads to more precise surrogates than LHS.

Coiled Coil Peptide Tiles (CCPTs): Expanding the Peptide Building Block Design with Multivalent Peptide Macrocycles.

Owing to their synthetic accessibility and protein-mimetic features, peptides represent an attractive biomolecular building block for the fabrication of artificial biomimetic materials with emergent properties and functions. Here, we expand the peptide building block design space through unveiling the design, synthesis, and characterization of novel, multivalent peptide macrocycles (96mers), termed coiled coil peptide tiles (CCPTs). CCPTs comprise multiple orthogonal coiled coil peptide domains that are separated by flexible linkers. The constraints, imposed by cyclization, confer CCPTs with the ability to direct programmable, multidirectional interactions between coiled coil-forming "edge" domains of CCPTs and their free peptide binding partners. These fully synthetic constructs are assembled using a convergent synthetic strategy via a combination of native chemical ligation and Sortase A-mediated cyclization. Circular dichroism (CD) studies reveal the increased helical stability associated with cyclization and subsequent coiled coil formation along the CCPT edges. Size-exclusion chromatography (SEC), analytical high-performance liquid chromatography (HPLC), and fluorescence quenching assays provide a comprehensive biophysical characterization of various assembled CCPT complexes and confirm the orthogonal colocalization between coiled coil domains within CCPTs and their designed on-target free peptide partners. Lastly, we employ molecular dynamics (MD) simulations, which provide molecular-level insights into experimental results, as a supporting method for understanding the structural dynamics of CCPTs and their complexes. MD analysis of the simulated CCPT architectures reveals the rigidification and expansion of CCPTs upon complexation, i.e., coiled coil formation with their designed binding partners, and provides insights for guiding the designs of future generations of CCPTs. The addition of CCPTs into the repertoire of coiled coil-based building blocks has the potential for expanding the coiled coil assembly landscape by unlocking new topologies having designable intermolecular interfaces.

Visitors’ Behaviors and Perceptions of Spatial Factors of Uncultivated Internet-Famous Sites in Urban Riverfront Public Spaces: Case Study in Changsha, China

This article takes representative uncultivated riverfront internet-famous sites (uncultivated RIFSs) in Changsha city, China, as an example to explore the internal mechanism of their formation and finds that they are closely related to the “urban subculture” and the “informality of urban public space”. In terms of methodology, through questionnaire surveys and in-depth interviews, this study investigates the behavioral characteristics of onsite visitors, the overall perceptions and satisfaction of public spaces, and the perceptions of spatial and humanistic elements of visitors. The main findings are as follows: ① Onsite visitors are mainly male, with local tourists and nearby residents accounting for over 80%. Furthermore, over half of the visitors have limited understanding of the uncultivated RIFSs. ② People’s overall attitudes towards the uncultivated RIFSs are positive. And the ability to carry out meaningful activities and find comfort and safety are of the greatest concern to onsite tourists. ③ Among the visiting reasons, leisure stays accounted for the highest proportion, followed by sightseeing, sports stays and social stays. ④ The onsite visitors’ main focus of spatial elements and humanistic elements is different according to the different sites. However, visitors’ dissatisfaction is mainly reflected in poor site safety and sanitation conditions, inadequate facilities and poor surrounding environments. This paper also compares the online–offline differences in the spatial perceptions of the uncultivated RIFSs between this study and previous research; instead of focusing on the urban physical spaces, online social media users pay more attention to their self-presentation. Meanwhile, the visitors place greater emphasis on the functionality, practicality and experiential activities of the urban physical spaces. Finally, this article proposes optimization strategies for uncultivated RIFSs from planning and governance and public space design aspects to protect and strengthen the composite utilization of space, therefore enhancing diverse vitality.

Research on Optimization Design of Corridor Entry Space of Elderly Facilities Based on Visual–Perceptual and Electroencephalogram Feedback Mechanisms

Research on Optimization Design of Corridor Entry Space of Elderly Facilities Based on Visual–Perceptual and Electroencephalogram Feedback Mechanisms

Evolutive 3D Urban Data Representation through Timeline Design Space

AbstractCities are constantly changing to adapt to new societal and environmental challenges. Understanding their evolution is thus essential to make informed decisions about their future. To capture these changes, cities are increasingly offering digital 3D snapshots of their territory over time. However, existing tools to visualise these data typically represent the city at a specific point in time, limiting a comprehensive analysis of its evolution. In this paper, we propose a new method for simultaneously visualising different versions of the city in a 3D space. We integrate the different versions of the city along a new way of 3D timeline that can take different shapes depending on the needs of the user and the dataset being visualised. We propose four different shapes of timelines and three ways to place the versions along it. Our method places the versions such that there is no visual overlap for the user by varying the parameters of the timelines, and offer options to ease the understanding of the scene by changing the orientation or scale of the versions. We evaluate our method on different datasets to demonstrate the advantages and limitations of the different shapes of timeline and provide recommendations so as to which shape to chose.

A novel artificial intelligence‐based antenna designing model for optimizing 5G mobile communication

AbstractAntenna designing involves the creation of devices to transmit or receive electromagnetic signals for various applications. It encompasses optimizing parameters such as size, shape, and frequency response to achieve desired performance characteristics, including signal strength, bandwidth, and efficiency, across diverse communication systems and frequencies. In this research, we intend to establish a novel artificial intelligence (AI)‐based antenna designing model for optimizing 5th generation (5G) mobile communication. We proposed Multi‐Objective Zebra Optimization (MOZO) to enhance 5G antenna design, aiming to minimize return loss () and maximize gain (G) concurrently. MOZO efficiently explores design space, offering Pareto‐optimal solutions that balance objectives. This approach ensures optimal antenna performance across the desired frequency range, advancing 5G communication efficiency. Our model enhances the functionality of a small, rectangular patch antenna designed for the 5G band, specifically operating at 30 GHz. Additionally, we conducted a comparative analysis between the performance of our optimized rectangular 5G antenna and several recently employed 5G‐millimeter wave (mmWave) antennas. This comparison sheds light on the efficacy and competitiveness of our optimized design within the 5G‐mmWave antenna landscape.

Hey Building! Novel Interfaces for Parametric Design Manipulations in Virtual Reality

Parametric Design enables designers to formulate and explore new ideas through parameters, typically by manipulating numerical values. However, visualising and exploring the design space of an established parametric design solution is natively difficult through desktop displays for designers due to screen space constraints and requiring familiarity with visual-language programming interfaces. Thus, we sought to explore Virtual Reality (VR), inspired by Natural User Interfaces (NUI), to develop and explore new interfaces departing from traditional programming interfaces, that could complement the spatial and embodied affordances of contemporary VR devices. Informed by two industry-led focus groups with architects we developed and examined the usability of three different interfaces: 1) Paramaxes , an axes-based interface that allows designers to distribute and manipulate parameter visualisations around them in physical space; 2) ParamUtter , a Voice-based User Interface (VUI) that allows designers to manipulate parameter visualisations through natural languages; 3) Control Panel , which presents the parameters as sliders in a scrollable pane and acts as baseline comparison. We ran an exploratory study with experts and found that the Control Panel was ultimately the preferred interface for a design manipulation task. However, participants commented favorably towards qualities in the unconventional interfaces, with ParamUtter scoring highest in System Usability Scores (SUS), and participants valuing the potential of using physical space to explore design spaces with Paramaxes .

Hybrid Surrogate Modeling Approach for Data Reduction and Design Space Exploration of Turbine Blades

Hybrid Surrogate Modeling Approach for Data Reduction and Design Space Exploration of Turbine Blades

A comprehensive validation of GRA with ant colony optimization for robust optimal design: A case study on the forming process

Sheet metal forming design involves numerous factors and controlling all these parameters to prevent cracks is a major challenge to maintain the quality. Therefore, the careful selection of process parameters is critical for ensuring product longevity. Several researchers employed different techniques for optimal selection of process parameters but consistency among the techniques and validation of results in real time scenarios will play a pivotal role in determining the suitable parameters. Therefore, the current work presents a validation method of Grey Relational Analysis (GRA) results with Ant Colony Optimization (ACO) for the robust optimum design with an illustrative example of forming process. Al 6061 – T6 alloy was chosen as a material for deep drawing process and L27 Orthogonal Array was planned to conduct experiments with four input parameters such as blank thickness, Die and Blank Temperature, Die Speed, Lubrication at three levels each. Punch force and Thickness variation were considered as the output parameters. GRA Technique was implemented to find the best optimal combination and regression equation was developed to predict the nature of objective function. These results were given as an input to ACO, a nature inspired algorithm to search for the optimal solution with in the design space. Sensitivity analysis has also been performed to highlight the effectiveness of the proposed solution in terms of solution quality and computational efficiency. The ACO method, GRA technique and the experimental results are almost similar with a margin of acceptable deviation. The results indicated the robustness of the projected approach in achieving the quality of solution.

Identification of Crashworthy Designs Combining Active Learning and the Solution Space Methodology

Abstract This study introduces a novel methodology for vehicle development under crashworthiness constraints. We propose coupling the solution space method (SSM) with active learning reliability (ALR) to map global requirements, i.e., safety requirements on the whole vehicle, to the design parameters associated with a component. To this purpose, we use a classifier to distinguish between the design that fulfills the requirements, the safe domain, and those that do not, the failure domain. This classifier is trained on finite element simulations, exploiting the learning strategies used by ALR to efficiently and precisely identify the border between the two domains and the information provided on these domains by the SSM. We then provide an exemplary application where the efficiency of the method is shown: the safe domain is identified with 270 samples and an average total error of 2.5%. The methodology we propose here is an efficient method to identify safe designs at a comparatively low computational budget. To the best of our knowledge, there is currently no methodology available that can identify regions in the design space that result in designs satisfying the local requirements set by the SSM due to the complexity and strong nonlinearity of crashworthiness simulations. The proposed coupling exploits the information of SSM and the capabilities of ALR to provide a fast mapping between the global requirements and the design parameters, which can, in turn, be made available to the designers to inexpensively evaluate the crashworthiness of new shapes and component features.

توظيف التكنولوجيا في تصميم الإعلان الرقمي وتمثلاتها الإبداعية في نتاجات طلبة التربية الفنية

The research dealt with the topic of (employing technology in the design of digital advertising and its creative representations in the products of art education students). The research contained four chapters. The first chapter dealt with: the methodological framework of the research, represented by the research problem that was revealed in the following question: How has technology contributed to employment in the design of digital advertising? They have no role in enriching the creative process and are represented in their artistic productions. The researcher determined the limits of the research, which were represented by the products of the students of the Department of Art Education - First Stage / College of Fine Arts/ University of Baghdad for the academic year (2020-2021), and then the researcher moved to the second semester, which included two sections. The title of the first section was employing technology artistically for advertising, and the section included the second is the creative process and aesthetic standards in the artistic achievement, and the researcher extracted a number of indicators that resulted from the theoretical framework: 1. The use of digital technical methods in employing shapes by following the technique of assembling and composing photographs, and generating a main rhythm between images and color values, served the functional aspect and the creative process of the advertising poster. 2. The computer showed a kind of diversity and excitement in the use of letters and their formal formulation in the design space. Among the most important conclusions is that the use of digital technology in the field of art education for practical academic subjects has given students the ability to diversify the styles of artistic production and facilitate the procedures used in producing these artistic works.

How to catch prospective use? A comparative study of virtual environment movie and guided imaginary for projecting future users in a public space

Focusing on the design of a public space, we propose a methodological contribution to integrate possible future users to studies in prospective ergonomics. Our objective is to establish a rigorous protocol for comparing two methods of projecting potential usage. First, a projection interview based on a virtual environment movie and second, a Guided Imaginary Projection interview. We sought to determine to what extent these two methods provide participants with the ability to live a ‘quasi-experience’ of the space. This ‘quasi-experience’ is measured by a questionnaire inspired by the concepts of presence and absorption and by the analysis of the embodiment level of the discourse produced during the interviews, from embodied to general discourse. The results show that while the two methods produce similar results in terms of the level of projection experience, the virtual environment movie projection produces significantly more general discourse.

Point-enhanced convolutional neural network: A novel deep learning method for transonic wall-bounded flows

Low order models can be used to accelerate engineering design processes. Ideally, these surrogates should meet the conflicting requirements of large design space coverage, high accuracy and fast evaluation. Within the context of aerospace applications at transonic conditions, this can be challenging due to the associated non-linearity of the flow regime. Different methods have been investigated in the past to predict the flow-field around shapes such as airfoils or cylinders. However, they usually have reduced spatial resolution, limiting the prediction capabilities within the boundary layer which is of interest for transonic wall-bounded flows. This work proposes a novel Point-Enhanced Convolutional Neural Network (PCNN) method that combines the advantages of the well-established PointNet and convolutional neural network approaches. The PCNN model has relatively low memory requirements in the training process, preserves the spatial correlation in the domain and has the same resolution as a traditional computational method. The architecture is used for the flow-field prediction of civil aero-engine nacelles in which it is demonstrated that the flow features of peak isentropic Mach number (Mis), pre-shock isentropic Mach number and shock location (X/Lnac) are captured within ΔMis = 0.02, ΔMis=0.04, ΔX/Lnac=0.007, respectively. The PCNN model successfully predicts the integral parameters of the boundary layer, in which the incompressible displacement thickness, momentum thickness and shape factor are typically within 5% of the CFD. Overall, the PCNN method is demonstrated for transonic wall-bounded flows for a range of flow physics that include shock waves and shock-induced separation.

Tscluster: A python package for the optimal temporal clustering framework

Temporal clustering extends the conventional task of data clustering by grouping time series data according to shared temporal trends across sociospatial units, with diverse applications in the social sciences, especially urban science. The two dominant methods are as follows: Time Series Clustering (TSC), with dynamic cluster centres but static labels for each entity, and Sequence Label Analysis (SLA), with static cluster centres but dynamic labels. To implement the universe of models spanning the design space between TSC and SLA, we present tscluster, an open-source Python framework. tscluster offers: (1) several innovative techniques, such as Bounded Dynamic Clustering (BDC), that are not available in existing libraries, allowing users to set an upper bound on the number of label changes and identify the most dynamically evolving time series; (2) a user-friendly interface for applying and comparing these methods; (3) globally optimal solutions for the clustering objective by employing a mixed-integer linear programming formulation, enhancing the reproducibility and robustness of the results in contrast to existing methods based on initialization-sensitive local optimization; and (4) a suite of visualization tools for interpretability and comparison of clustering results. We present our framework using a case study of neighbourhood change in Toronto, comparing two methods available in tscluster. Supplemental materials provide an additional case study of local business development in Chicago and a detailed mathematical exposition of our framework. tscluster can be installed via PyPI (pypi.org/project/tscluster), and the source code is accessible on Github (github.com/tscluster-project/tscluster). Documentation is available online at the tscluster website (tscluster.readthedocs.io).

Collaborative and integrated working between general practice and community pharmacies: A realist review of what works, for whom, and in which contexts.

Collaborative and integrated (C + I) working between general practice and community pharmacies has the potential to increase accessibility to services, improve service efficiency and quality of care, and reduce health care expenditures. Many existing studies report challenges and complexities inherent in establishing effective C + I ways of working. The aim of our review is to understand how, when and why working arrangements between General Practitioners (GP) and Community Pharmacists (CP) can provide the conditions necessary for effective communication, decision-making, and C + I working. We conducted a realist review to explore the key contextual factors and mechanisms through which GP-CP C + I working may be achieved. MEDLINE, Embase, CINAHL, PsycINFO, HMIC, Web of Science, IBSS, ASSIA, Sociological Abstracts, Sociology Database and the King's Fund Library Database were searched for articles and grey literature published between January 2000 and April 2022. A total of 136 documents were included in the final synthesis. Our findings highlight the importance of mutually beneficial remuneration models to support effective integration of services; supportive organisational cultures and values; flexible and agile IT systems/technologies; adequate physical infrastructure and space design to support multidisciplinary teamworking; the importance of establishing patient's trust in collaborative processes between GP-CP; and the need to acknowledge, support and utilise effective triadic relationships. Our research generates new insights regarding how, why and in which contexts C + I working can be achieved between GPs and CPs. The findings of our review can be used to inform future policy, research and clinical practice guidelines for designing and delivering C + I care.

Comparative Analysis of Space Efficiency in Skyscrapers with Prismatic, Tapered, and Free Forms

This study offers a thorough comparative analysis of space efficiency in skyscrapers across three distinct forms: prismatic, tapered, and free. By examining case studies from each form category, this research investigates how architectural and structural design features impact space utilization in supertall towers. The findings reveal form-based differences in space efficiency and design element usage. In prismatic skyscrapers, which are primarily residential and utilize concrete outrigger frames, the average space efficiency was around 72%, with the core occupying 24% of the gross floor area (GFA). Tapered skyscrapers, commonly mixed-use with composite outrigger frames, showed an average space efficiency of over 70%, with a core-to-GFA ratio of 26%. Freeform towers, often mixed-use and using composite outrigger frames, demonstrated a space efficiency of 71%, with an average core-to-GFA ratio of 26%. Despite these variations, a consistent trend emerged: as the height of a building increases, there is a general decline in space efficiency, highlighting the challenges in optimizing space in taller structures. This analysis adds to the understanding of skyscraper design and space utilization, providing important insights for architects and urban planners aiming to improve the efficiency of future high-rise developments.

Computational design of 4D printed shape morphing lattices undergoing large deformation

Abstract In 4D Printing, active materials are embedded in structures such that the application of an external stimulus, usually coming from the environment, results in a structural response. To design structures that achieve a targeted shape change for a defined stimulus, also known as shape morphing, the material distribution and structure needs to be tuned. However, the computational design of such material distributions and structures is a challenging task and remains, despite recent advances, unable to fully leverage the entire design freedom offered by state-of-the-art 4D printing technology. Notable gaps concern the handling of large and complex deformations, the high computational cost, and the exploration of the design space by the generation of alternative solutions. In this article, a method is presented to fill this gap. First, an artificial neural net is trained that represents a deformation map that occurs during actuation. Then, a shape morphing truss is designed that achieves this deformation during actuation. The method is used to solve four shape morphing problems, where superior capabilities are demonstrated in terms of magnitude and complexity of deformations that can be handled, efficient generation of alternative solutions and versatility. Due to these capabilities, the method enables exploration of the full potential of 4D printing technology to create stimuli-responsive, multifunctional structures.

Dielectric Modulated Nanotube Tunnel Field-Effect Transistor with Core-Shell Cavity as a Label-Free Biosensor: Proposal and Analysis.

Dielectric Modulated Field-Effect Transistors (DMFETs) have emerged as promising candidates for label-free bioanalyte detection. However, the inherent short-channel effects in conventional DMFETs increase their static power dissipation significantly and limit their scalability and sensitivity. Therefore, FETs based on alternate conduction mechanism such as tunneling (TFETs), which are immune to the short-channel effects, appear to be a lucrative alternative to the MOSFETs for biosensing application. In this work, we propose a novel Dual Cavity Dielectric Modulated Nanotube Tunnel FET (DCDM NTTFET)-based label-free biosensor consisting of a Ge source and nanocavities within the core as well as a shell gate stack, which not only outperforms the conventional MOSFET and advanced nanowire (NW) TFET-based biosensors in terms of energy-efficiency and scalability but also exhibits a significantly high drain current sensitivity (SION = 2.9 × 108) and a threshold voltage sensitivity (SVth = 0.85), and a considerably high selectivity of more than 6 orders of magnitude. We also perform a comprehensive design space exploration for the proposed DCDM NTTFET and provide necessary design guidelines to further improve its performance considering the practical artifacts such as steric hindrance.

A 3D Spatial Model to integrate Stormwater Drainage Design into Public Space

Abstract. This paper explores the integration of water sensitive urban design within public space planning using integrated 3D digital technologies. In traditional design processes, drainage and public space design often utilise distinct software and are led by different professionals, which creates significant communication barriers.Although civil and hydraulic engineers have made significant strides in integrating hydrology analysis with multi-objective space design, the collaboration of conventional 2D hydrology with 3D landscape design still presents challenges. To address these challenges, this study proposes a novel approach that integrates drainage analysis and design within a 3D design model. This methodology is specifically designed to aid landscape and urban designers in incorporating stormwater management and drainage systems early in the design process. The approach involves three key steps: (1) identifying critical factors that impact, or are impacted by, drainage design; (2) translating these factors into specific spatial parameters; and (3) developing a workflow to integrate these parameters. This integration not only streamlines the design process, making it more cohesive and efficient but also mitigates potential conflicts between drainage requirements and spatial design, thereby reducing unnecessary revisions. Ultimately, this approach enhances the incorporation of essential drainage considerations into urban and landscape planning, leading to more sustainable and functional public spaces.

Real-Time Visibility Assessment in an Interactive Immersive Virtual Reality Application for Urban Public Space Design

Abstract. The design of urban public spaces (UPSs) aims to facilitate users’ physical and mental well-being by facilitating dynamic and stationary activities. The success of a UPS is often measured by its users’ engagement and experiences. However, UPSs frequently exhibit varying usage patterns, with some areas being heavily frequented and others neglected. This discrepancy is often due to users’ perceptions of safety, comfort, and liveliness. Failure to anticipate and address these aspects during the design phase of UPSs can result in dysfunctional urban spaces that fail to meet users’ needs. People experience UPSs primarily through their senses, with vision being the predominant sense and key to spatial cognition in UPSs. Therefore, adequate visibility of the spatial configuration must be integral to UPS design as a design goal. As a result of recent advances in Immersive Virtual Reality (IVR) end-users can participate in, interact and experience the possible UPS design scenarios, however, most IVR applications do not provide real-time feedback for design goals such as visibility. Established methods exist for analyzing visibility in UPS. However, these techniques are not usually integrated into VR apps to assess the effects of the designs. This paper addresses the gap for the lack of real-time visibility feedback within IVR applications for UPS design and its technical challenge. Building on a previous IVR application, CoHeSIVE, which was developed for UPS design, we integrated a ray-casting method and Unity’s built-in callbacks for dynamic visibility assessment of the features within the user’s field of view. The visibility assessment is then presented on a dashboard within the IVR app. This study serves as a cornerstone for future real-time feedback mechanisms of visibility assessment within IVR applications for urban design, facilitating informed design decisions.