Early Design Research Articles

A Novel Decision-Support Framework for Supporting Renewable Energy Technology Siting in the Early Design Stage of Microgrids: Considering Geographical Conditions and Focusing on Resilience and SDGs

This research is focused on microgrid design supporting tools and presents an innovative framework for renewable energy (RE) sources’ site selection, integrating multicriteria decision-making (MCDM) methods with resilience considerations and alignment to the Sustainable Development Goals (SDGs). It addresses present climatic challenges, identifies key causes of possible power failures, and develops strategies to mitigate their effects, while providing tools for energy managers and decision-makers to select suitable RE sources/technologies, based on geographical and sustainability criteria. The framework categorizes criteria into quantitative and qualitative types, adopting a cost (C)- and benefit (B)-based approach. The Analytic Hierarchy Process (AHP) calculates criteria weights to ensure accuracy and compatibility in decision-making, integrating SDG objectives into the evaluation process. This study focuses on five major RE options, photovoltaic (PV), wind, wave, tidal, and geothermal, analyzing more than 50 criteria for each energy type. This evaluation incorporates the expertise of over 50 experts and case studies, making it one of the most extensive research efforts in RE site selection. By systematically addressing resilience challenges and linking them with SDG priorities, this study provides a robust framework for evaluating and optimizing RE options. Its methodologies offer significant contributions to advancing sustainable energy development and enhancing energy systems’ resilience to climate and infrastructural challenges.

Optimizing urban block layouts and density distribution: a generative design framework for neighborhood performance

PurposeIn many countries, urban block layouts follow rigid and outdated design guidelines; however, these approaches fail to effectively address settlement construction, neighborhood planning, the design of old urban contexts and the rapid development of emerging cities, as seen in the new towns of Iran and various other regions worldwide. Revising these guidelines requires early-stage decision-making to evaluate building layouts based on their impact on the built environment. This study introduces a workflow for optimizing urban block layouts with constant density while considering design constraints, climate and environmental performance. This framework assists planners and policymakers in refining site density distribution and building massing.Design/methodology/approachA computational urban design method was developed utilizing a grasshopper-based algorithm and Python for data generation. It introduces an innovative approach by incorporating buildings’ placement coordinates as design variables alongside dimensions and orientation. The Wallacei tool optimizes layouts by considering energy use intensity (EUI), outdoor thermal comfort and facades’ received radiation employing Ladybug Tools. Spatial daylight autonomy (sDA) and urban heat island (UHI) effects are also integrated into the workflow. The framework is applied to a hypothetical residential district in Tehran, consisting of nine blocks, each containing nine plots.FindingsThe results for a set of optimal solutions demonstrate that beyond existing urban design policies, environmentally prioritized designs are achievable. Radiation differences between the optimal models and the conventional parallel layout range from 41.3 to 61.1%. However, changes in EUI and universal thermal climate index (UTCI) are minimal; significant improvements are observed in sDA, with 7, 8 or all 9 buildings meeting the acceptable threshold compared to none in the parallel layout. These findings highlight the effectiveness of the design method framework proposed in this research, which has the potential to significantly influence urban planning practices across various regions globally.Originality/valueThe methodology of this study provides a flexible decision-making framework for early design phases, enabling policymakers, architects and urban designers to address the gap between current urban design methods and environmentally driven approaches. Sensitivity analysis of optimal solutions further offers valuable insights into the correlation between design variables and evaluation metrics.

Beyond trial and error: toward construction-aware early design optimization considering robotic capabilities

Beyond trial and error: toward construction-aware early design optimization considering robotic capabilities

Developing surrogate models for the early-stage design of residential blocks using graph neural networks

Abstract Building simulation based on physical modeling is commonly adopted for performance prediction, but the high time costs hinder its application in the early design stage of buildings. Data-driven surrogate models have been proposed as a means to replicate computationally expensive simulation models. However, existing surrogate models for sustainable residential block design are limited in scope, focusing either on individual buildings or on specific cases within multi-block projects. This study leverages graph neural networks to develop optimal surrogate models incorporating inter-building effects to predict multiple indicators of sustainable performance for residential blocks at a region level. A graph schema is proposed to represent the general geometric features and relations among buildings in residential block design. A regional dataset is generated for model training and testing, using real residential zones in Hong Kong. The surrogate models are developed and evaluated, using two kinds of architectures (individual architectures for specific indicators and an integrative architecture) and three different neural networks (graph attention network (GAT), graph convolutional network, and artificial neural network). The results showed that the surrogate models using the individual architectures and GAT outperform the models using other architectures and neural networks. These surrogate models achieve a high prediction accuracy with CV(RMSE)s of 11.79%, 7.63%, and 8.00% in terms of energy consumption, indoor thermal comfort, and daylighting, respectively, on the regional test set. Moreover, they enable a significant acceleration of the performance evaluation, reducing the calculation time from 6.346 min to 1.565 ms (243,297 times) per case compared to physics-based simulations.

Parent-implemented early intervention design for improving speech and language skills among Mandarin-speaking infants and toddlers with cleft lip and/or palate

Parent-implemented early intervention design for improving speech and language skills among Mandarin-speaking infants and toddlers with cleft lip and/or palate

A Review of Recent Developments in Quadruped Robots

Quadrupedal robots have emerged as a leading platform for navigating complex and uneven terrains, owing to their biomimetic design and superior adaptability compared to wheeled and tracked counterparts. This review provides an overview of the historical development of quadruped robots, from early mechanical designs to modern advancements in actuation, control, and artificial intelligence. Recent progress in hydraulic, electric, and pneumatic actuation systems, combined with improvements in motion planning algorithms and terrain recognition technologies, have significantly enhanced the performance of these robots in real-world applications. Additionally, key trends such as the integration of artificial intelligence for autonomy and the use of advanced materials for flexible body designs are highlighted. The paper concludes with a discussion of future research directions aimed at further improving the efficiency, stability, and versatility of quadrupedal robots

Enhancing Sustainability with LCA: A Comparative Analysis of Design and Manufacturing Processes

This study evaluates the feasibility and effectiveness of the Life Cycle Assessment (LCA) methodology. Two widely used products with the same functionality but different designs and production processes were selected for comparative analysis. SimaPro 9.6.0 software was used for the calculations and LCA of both assemblies. The analysis covered all phases of the life cycle, taking into account factors such as energy, materials and water consumption. The results allowed a comparison of the environmental impacts of the two assemblies, identifying the life cycle phases with the highest impact and the most relevant impact categories. The analysis revealed that the metal trolley exhibited a 40% higher environmental impact during production compared to the polypropylene trolley, primarily due to the material extraction and processing phases. Additionally, the polypropylene trolley showed higher long-term impacts in landfill scenarios due to carcinogenic substance emissions. These findings highlight the significance of design and material selection in reducing environmental impacts. Applying the LCA methodology to the two mechanical assemblies allowed us to identify opportunities for improvement in the design and manufacturing processes, with the aim of reducing the environmental impact and increasing the competitiveness of the products. By considering the full life cycle of a product from the early design phases, more sustainable design and manufacturing decisions can be made, and by using this analysis, companies can develop more sustainable products and reduce costs.

Uncovering the implicit dimensions of empathy in architectural design: seeing through empathy

ABSTRACT This article examines the implicit dimensions of empathy in the early architectural design process, utilizing think-aloud protocols to reveal how designers engage empathically with their creations. Grounded in early 20th-century empathy theories, phenomenological philosophy, and design cognition, we developed the ‘Feeling AS’ empathy framework, which identifies three core modes of empathy: (1) user, (2) space, and (3) movement. Analysis of design protocols demonstrates how empathy shapes design thinking, influences problem reframing, and uncovers spatial affordances tied to user embodiment. Empathy contributes to the design process in two key ways. First, it aids in problem identification, ideation, and a deep understanding of users’ needs during the conceptual stage. Second, empathy enables designers to refine design solutions by revisiting decisions and reframing problems from the users’ perspective as the process evolves. The study portrays empathy as a perceptual and reflective tool, akin to sketching, that facilitates diverse perspectives and establishes embodied connections with users and spaces. We frame this process as ‘seeing through empathy,’ encompassing empathic framing, spatial affordances, and embodiment. This research broadens the scope of empathy research to include spatial dimensions, emphasizing its inherent role and extending it beyond conscious strategies to become an embedded aspect of the creative process.

A Polynomial-Time Algorithm for Detection of Uncovered Transitions in a Petri Net-Based Concurrent System

This paper introduces a novel algorithm for the efficient verification of a Petri net-based concurrent control system. The proposed method is based on the computation of transition invariant coverage to detect possible errors in the modelled system. Transition invariants play a crucial role in ensuring the correctness and reliability of such systems; however, existing methods often struggle with high computational demand, especially in the case of large and complex systems. The proposed approach addresses this challenge by performing a fast polynomial-time analysis to identify uncovered transitions, thereby streamlining the verification process. The effectiveness and efficiency of the proposed technique is verified experimentally with a set of 386 test modules (benchmarks) and compared against two well-known established methods: the classical method proposed by Martínez–Silva (as a reference algorithm) and PIPE (Platform Independent Petri Net Editor) tool. The results of the experiments confirm high performance of the presented algorithm, which was able to compute results for all the tested cases. In contrast, both the reference algorithm as well as the PIPE tool failed to deliver results for all examined models within one hour. The proposed algorithm is especially useful in early design stages, offering system designers timely insights into potential issues.

Navigating the Complexities of Range of Motion in Reverse Shoulder Arthroplasty: Innovations and Future Directions.

With the growing popularity and broadening indications for Reverse Shoulder Arthroplasty (RSA), increasing modularity in design and adjustments to each component can enhance postoperative range of motion (ROM), thus expanding treatment capabilities. This review outlines the advancements developed to optimize ROM through modifications in glenoid and humeral components and the integration of computational tools for surgical planning. Enhancements in glenoid component design aim to mitigate complications like scapular notching and improve ROM, particularly in abduction and external rotation. Modifications to the humeral component, including adjustments in neck-shaft angle and lateralization, also contribute to ROM optimization. The integration of computational modeling and intraoperative navigation is advancing towards a more tailored approach to RSA to increase postoperative ROM. While RSA has evolved considerably since the introduction of the Grammont prosthesis, current research continues to improve upon implant design and positioning to overcome early design limitations. Modifications such as glenoid lateralization and inferior positioning and humeral neck-shaft angle and lateralization contribute to better postoperative ROM. The integration of these advancements in implant adjustments with computational modeling for surgical planning has the potential to enhance ROM and patient-specific outcomes. Translating these biomechanical improvements into clinical benefit remains a key area for future investigation.

Zonal Safety and Particular Risk Analysis for Early Aircraft Design

Safety is paramount in aircraft design, and increasing aircraft complexity necessitates safety assessments early in design. For unconventional aircraft with novel propulsion or system technologies, it becomes even more critical to investigate safety as early as possible to avoid unfeasible configurations. In this context, the particular risk analysis (PRA) and the zonal safety analysis (ZSA) are essential to assess early, as they impact the aircraft configuration. These analyses require a three-dimensional (3D) aircraft model and substantial manual effort, limiting the ability to perform rapid iterations required to support design space exploration and multidisciplinary design optimization (MDO). To analyze many aircraft configurations and system architectures, the 3D parametric model and the PRA and ZSA require automation. This paper reviews methodologies for performing the ZSA and PRA from a systems point of view and proposes parametric zone definition, identification of risk zones, and a conceptual-level analysis of the component placement strategy. The effectiveness of the proposed approach is demonstrated with an aft equipment bay of a business aircraft for varying geometrical granularity and system electrification. Overall, the presented method is a step toward integrating system safety analysis into MDO environments, thus increasing conceptual design maturity and reducing development time.

Developing a dual-modal surrogate model training framework for building performance prediction in early design stage

Developing a dual-modal surrogate model training framework for building performance prediction in early design stage

A geometry-based decomposition method for energy prediction in early design stages of residential buildings

PurposeThe purpose of the study is to develop a geometry-based energy estimation method for surrogate and metamodels to be used in the early design phase of buildings.Design/methodology/approachOptimizing building form and design variables in the early stages of the architectural design process, particularly during the conceptual phase, can significantly enhance overall design performance and energy efficiency at minimal cost. This study introduces a novel decomposition method for evaluating building energy performance by simplifying complex building forms into basic geometric shapes.FindingsThe developed method is applied to certain cases of design variation under specified boundary conditions, and the accuracy of heating and cooling energy loads is calculated with simulated energy models of these cases. As a result of the calculation, accuracy rates between 84.30 and 99.98% were founded.Originality/valueThis paper proposes a prediction model with a geometric identification method for an innovative geometry-based surrogate modeling method. This method also provides a way for artificial intelligence-based prediction models used in surrogate models to create a dataset and can be used in the training in future works.

Generative architectural plan drawings for early design decisions: data grounding and additional training for specific use cases

ABSTRACT This study shows the development of models for generating architectural plan drawings to support early design decisions in time – and cost-effective housing projects. Plan drawings are communicated through a combination of visual representations and accompanying textual descriptions. These elements play a crucial role in communicating design specifications to project stakeholders. In particular, by exploring the benefits of early decision-making during the planning phase, this paper explores specific use cases and demonstrates how existing data can be processed for additional training in image-generative models. These models have significantly advanced architectural visualization as a synthetic medium for visual representation. The methodology follows a structured approach: (1) evaluating the efficacy of default base models in generating plan drawings to determine the need for additional data grounding and training; (2) defining the scope of research through a theoretical examination of design requirements for specific use cases for training; (3) systematizing and generalizing the additional training process including data grounding (preparing and preprocessing data suitable for specific use cases), optimizing hyperparameters, and training (implementing models capable of generating images with the desired quality); and (4) demonstrating the proposed applications using the additional training model, specifically within the use case of ‘Korean urban residential housing projects’. This methodology aims to improve the efficiency of design communication during the initial stages of architectural design. By doing so, it enables more effective and strategic planning across a wide range of use cases and scenarios.

Longitudinal changes in teaming dimensions from self- and peer-feedback in early year design courses

The ability to work effectively in a team environment is critical to engineering practice, and a required accreditation element of engineering programs in Canada. Developing this ability often involves repeated cycles of team activity, peer feedback, and self-reflection. This work describes an exploratory study of longitudinal changes in student self- and peer-evaluated teaming dimensions on engineering teams as students progress through a sequence of design and professional practice courses. The data shows a positive trend in self- and peer-evaluated teaming, and most encouragingly a more significant improvement among students with initially low scores on their first teaming evaluation.

Sustainability Assessment during Early Stage Chemical Process Design: Comparing Two Different Methods of Synthesizing Noroxymorphone

Sustainability Assessment during Early Stage Chemical Process Design: Comparing Two Different Methods of Synthesizing Noroxymorphone

Conflicting Institutional Pressures During the Establishment of Tax Administrations in the Post-1990 Eastern German States

ABSTRACT The reunification of Germany in 1990 has been extensively analysed, yet little knowledge exists on how this critical period has impacted Germany’s system of tax administration. Drawing upon document analysis and semi-structured interviews with experts who were personally involved in the transition, this article investigates the key challenges faced during the establishment of tax administration infrastructures in the post-1990 eastern German states. Specifically, the article compares the transition process in two eastern German states, Saxony and Saxony-Anhalt, thereby illuminating how early administrative design choices explain subsequent differences between these states in their post-1990 tax administration performance. The article employs an historical institutional perspective, combined with an isomorphic institutional analysis, demonstrating that the institutional configuration of Germany’s system of tax administration is central to understanding the performance of eastern German tax administrations post-reunification. Conflicting interests between government actors, both vertically and horizontally, resulted in different views as to how the eastern German states’ tax systems should be developed. Whilst the reunification brought these institutional tensions to the surface in a uniquely clear manner, these tensions continue to affect Germany's present tax administration, making this study important from a historical perspective but also to better understand Germany’s contemporary system of fiscal administration.

Parental Perceptions of Early Childhood In-Home Research with Monitoring: A Qualitative Study.

To explore perceptions, concerns, and enthusiasm from a diverse group of parents regarding early childhood research that involves home monitoring technologies for collecting environmental exposure data. A diverse group of new and expecting parents participated in semi-structured interviews. A single interviewer conducted all sessions and introduced a hypothetical longitudinal early childhood research study, which included novel home monitoring approaches: 1) wearable devices, 2) audio monitoring, and 3) environmental sampling. Interviews were audio-recorded, transcribed, and coded. Qualitative description guided the study, and a constant comparative approach was used to identify themes from transcripts. Twenty-four interviews were completed. Emerging themes included 1) Ready and Willing to Participate; 2) Helping Others, Helping Ourselves: Motivation for Participation; 3) Trust and Transparency: Understanding the "What?" and the "Why?"; 4) Data Privacy and Security: "What If It Gets into the Wrong Hands?"; 5) It's a Lot to Juggle: Logistical Realities. Perceptions were similar across racial, ethnic, and socioeconomic groups. Perceptions were positive, and participants desired additional information about study feasibility and purpose. Many had concerns related to wearable device safety and data privacy; a trusting relationship with the research team was a priority. Participants had positive sentiments regarding longitudinal observational studies involving pregnancy and infancy yet expressed concerns about safety, privacy, feasibility, and transparency. These findings can inform future early childhood research study design to ensure protocols are transparent, inclusive, and appealing to parents.

An English brass snaphance self-rotating revolver by Annely, ca.1730 (Royal Armouries object number xii.4745)

This article seeks to draw attention to a noteworthy early ‘self-rotating’ revolver in the Royal Armouries collection previously dated circa 1700. Taking the form of an object biography of sorts, it describes and illustrates the Annely form of this type, comparing and contrasting it with known counterparts including the likely progenitor of the type; the ‘Dafte’ revolver (also within the Armouries’ collection). It places the piece in technological and stylistic terms to about 1680 ‘Dafte’ example also in the RA collection and other important early revolver designs such as the Collier and the successful Colt. A revised date of about 1730 is proposed. Finally, although the ‘throughline’ from seventeenth and eighteenth century designs to Collier and Colt is far from clear, the article seeks to establish the significance of the piece as one of several ‘false starts’ made in the quest for practical, one-handed firepower.

Band Alignment of Stacked Crystalline Si/GaN pn Heterostructures Interfaced with an Amorphous Region Using X-Ray Photoelectron Spectroscopy.

The energy band alignment of a stacked Si/GaN heterostructure was investigated using X-ray photoelectron spectroscopy (XPS) depth profiling, highlighting the influence of the amorphous interface region on the electronic properties. The crystalline Si/GaN pn heterostructure was formed by stacking a Si nanomembrane onto a GaN epi-substrate. The amorphous layer formed at the stacked Si/GaN interface altered the energy band of the stacked heterostructure and affected the injection of charge carriers across the junction interface region. This study revealed the interfacial upward energy band bending of the stacked Si/GaN heterostructure with surface potentials of 0.99 eV for GaN and 1.14 eV for Si, attributed to the formation of the amorphous interface. These findings challenge the conventional electron affinity model by accounting for interfacial bonding effects. Electrical measurements of the stacked Si/GaN pn heterostructure diode exhibited a rectifying behavior, consistent with the XPS-determined energy band alignment. The diode outperformed early design with a low leakage current density of 5 × 10-5 A/cm2 and a small ideality factor of 1.22. This work underscores the critical role of the amorphous interface in determining energy band alignment and provides a robust methodology for optimizing the electronic performance of stacked heterostructures. The XPS-based approach can be extended to analyze and develop multi-layered bipolar devices.