Hasil untuk "Details in building design and construction. Including walls, roofs"

Jenifer Godoy Daltrozo, Nicole Lucia Peiter, Elaise Gabriel et al.

Daylighting is a key aspect of educational building design, supporting both visual comfort and energy efficiency. However, design practice often reduces the role of windows to aperture ratios, with limited attention to the influence of window geometry on daylight performance. This study investigates how different fenestration morphologies affect daylighting performance in a real university classroom located in southern Brazil. Two window configurations were compared: the existing irregular floor-to-ceiling design and a standardized rectangular layout, both maintaining equal glazing area (25 m², ≈20% of floor area). Annual climate-based simulations were conducted using daylight metrics defined in LM-83: spatial Daylight Autonomy (sDA300, 50%) and Annual Sunlight Exposure (ASE1000, 250h). Five glazing types with visible transmittance values of 88%, 87%, 76%, 52%, and 13% were tested. The standardized window layout consistently increased daylight availability, reaching sDA values up to 98%, but also led to high levels of overexposure, with ASE rising to 46%. In contrast, the irregular floor-to-ceiling configuration limited overexposure to a maximum of 23%, though daylight autonomy decreased substantially, in some cases to 41%. When assessed against LEED daylighting thresholds, neither configuration achieved full compliance: the standardized layout exceeded ASE limits, while the irregular geometry often fell below sDA requirements. To synthesize these trade-offs, a ranking framework was developed to enable comparisons across window geometries and glazing options. This research demonstrates that window geometry, independent of aperture ratio, is a decisive factor shaping daylight performance. By isolating morphology as a design variable, the study provides architects and designers with evidence-based guidance to balance daylight sufficiency and overexposure in educational spaces. These findings contribute to bridging the gap between performance-based simulation and architectural decision-making, offering actionable insights for both new classroom designs and retrofit strategies in existing buildings.

Ruhan Yang, Ellen Yi-Luen Do

Building robots is an engaging activity that provides opportunities for hands-on learning. However, traditional robot-building kits are usually costly with limited functionality due to material and technology constraints. To improve the accessibility and flexibility of such kits, we take paper as the building material and extensively explore the versatility of paper-based interactions. Based on an analysis of current robot-building kits and paper-based interaction research, we propose a design space for devising paper robots. We also analyzed our building kit designs using this design space, where these kits demonstrate the potential of paper as a cost-effective material for robot building. As a starting point, our design space and building kit examples provide a guideline that inspires and informs future research and development of novel paper robot-building kits.

Ali Goharian, Mohammadjavad Mahdavinejad, Sana Ghazazani et al.

The design and evaluation of adaptive facades (AFs) have become increasingly complex due to advancements in morphology, control strategies, and adaptability techniques. This study introduces a Novel Kinetic Adaptive Facade (NKAF) incorporating photovoltaic (PV) panels and Plexiglas to enhance daylight and view performance in office buildings. The research focuses on two objectives: (1) the innovative design of the NKAF, and (2) dynamic assessment of its daylight performance using advanced simulation methodologies. Annual daylight simulations, conducted with Radiance and a cutting-edge dynamic-objects workflow, evaluated three adaptability strategies: blocking direct sunlight, tracking solar trajectories, and minimizing facade movement. Results indicate that the fully dynamic sun-blocking logic significantly improved useful daylight illuminance (UDI 100-3000 lux) from 49% to 90%. Additionally, post-processing with NSGA-II multi-objective optimization provided an optimal framework for annual performance, effectively balancing multiple design goals. This novel methodology enables the simulation of dynamic environments and facades, addressing a key gap in previous daylighting research.

Salman Oukati Sadegh, Emad Tabadkani, Mahmoud Oukati Sadegh

Shading systems are associated by their ability to control various factors such as energy consumption, visual comfort, and natural ventilation. To fulfill such economic, environmental, and social requirements, the use of integrated modular fiber-Reinforced Concrete (FRC) shading systems has become popular in recent years. While being more environmentally friendly, Fiber-reinforced concrete panels are also associated with lower costs. However, designing such systems are often associated with onerous time-consuming processes which has impacted their market uptake. To support designers since the early design phase, this research proposes an integrated systemic framework. The proposed framework benefits from integrating Multi-objective Evolutionary Algorithms (MOEAs). Such algorithms have proven to address conflicting parameters effectively while providing a range of different solutions to problems. Furthermore, the proposed framework incorporates the use of Pareto-front and Ranking method to better support decision making. Moreover, case study validates the efficacy of the framework in daylighting performance evaluation of an integrated modular FRC shading device for an office room. Finally, the results indicate that the proposed framework can provide a variety of optimal solutions to conflicting goals and further support performance evaluation of an integrated modular fiber-reinforced shading system.

Anna Pestka, Paweł Kłosowski, Marcin Krajewski

Matteo Castiglioni, Junjie Chen

In this paper, we initiate the computational problem of jointly designing information and contracts. We consider three possible classes of contracts with decreasing flexibility and increasing simplicity: ambiguous contracts, menus of explicit contracts and explicit single contract. Ambiguous contracts allow the principal to conceal the applied payment schemes through a contract that depends on the unknown state of nature, while explicit contracts reveal the contract prior to the agent's decision. Our results show a trade-off between the simplicity of the contracts and the computational complexity of the joint design. Indeed, we show that an approximately-optimal mechanism with ambiguous contracts can be computed in polynomial time. However, they are convoluted mechanisms and not well-suited for some real-world scenarios. Conversely, explicit menus of contracts and single contracts are simpler mechanisms, but they cannot be computed efficiently. In particular, we show that computing the optimal mechanism with explicit menus of contracts and single contracts is APX-Hard. We also characterize the structure of optimal mechanisms. Interestingly, direct mechanisms are optimal for both the most flexible ambiguous contracts and the least flexible explicit single contract, but they are suboptimal for that with menus of contracts. Finally, motivated by our hardness results, we turn our attention to menus of linear contracts and single linear contracts. We show that both the problem of computing the optimal mechanism with an explicit menu of linear contracts and an explicit single linear contract admits an FPTAS.

Tony Metger, Alexander Poremba, Makrand Sinha et al.

Uniformly random unitaries, i.e. unitaries drawn from the Haar measure, have many useful properties, but cannot be implemented efficiently. This has motivated a long line of research into random unitaries that "look" sufficiently Haar random while also being efficient to implement. Two different notions of derandomisation have emerged: $t$-designs are random unitaries that information-theoretically reproduce the first $t$ moments of the Haar measure, and pseudorandom unitaries (PRUs) are random unitaries that are computationally indistinguishable from Haar random. In this work, we take a unified approach to constructing $t$-designs and PRUs. For this, we introduce and analyse the "$PFC$ ensemble", the product of a random computational basis permutation $P$, a random binary phase operator $F$, and a random Clifford unitary $C$. We show that this ensemble reproduces exponentially high moments of the Haar measure. We can then derandomise the $PFC$ ensemble to show the following: (1) Linear-depth $t$-designs. We give the first construction of a (diamond-error) approximate $t$-design with circuit depth linear in $t$. This follows from the $PFC$ ensemble by replacing the random phase and permutation operators with their $2t$-wise independent counterparts. (2) Non-adaptive PRUs. We give the first construction of PRUs with non-adaptive security, i.e. we construct unitaries that are indistinguishable from Haar random to polynomial-time distinguishers that query the unitary in parallel on an arbitary state. This follows from the $PFC$ ensemble by replacing the random phase and permutation operators with their pseudorandom counterparts. (3) Adaptive pseudorandom isometries. We show that if one considers isometries (rather than unitaries) from $n$ to $n + ω(\log n)$ qubits, a small modification of our PRU construction achieves general adaptive security.

Diganta Das, Dipanjali Kundu, Anichur Rahman et al.

Exterior painting of high-rise buildings is a challenging task. In our country, as well as in other countries of the world, this task is accomplished manually, which is risky and life-threatening for the workers. Researchers and industry experts are trying to find an automatic and robotic solution for the exterior painting of high-rise building walls. In this paper, we propose a solution to this problem. We design and implement a prototype for automatically painting the building walls' exteriors. A spray mechanism was introduced in the prototype that can move in four different directions (up-down and left-right). All the movements are achieved by using microcontroller-operated servo motors. Further, these components create a scope to upgrade the proposed remote-controlled system to a robotic system in the future. In the presented system, all the operations are controlled remotely from a smartphone interface. Bluetooth technology is used for remote communications. It is expected that the suggested system will improve productivity with better workplace safety.

Soohwan Lee, Seoyeong Hwang, Kyungho Lee

This paper investigates the potential of LLM-based conversational agents (CAs) to enhance critical reflection and mitigate design fixation in group design work. By challenging AI-generated recommendations and prevailing group opinions, these agents address issues such as groupthink and promote a more dynamic and inclusive design process. Key design considerations include optimizing intervention timing, ensuring clarity in counterarguments, and balancing critical thinking with designers' satisfaction. CAs can also adapt to various roles, supporting individual and collective reflection. Our work aligns with the "Death of the Design Researcher?" workshop's goals, emphasizing the transformative potential of generative AI in reshaping design practices and promoting ethical considerations. By exploring innovative uses of generative AI in group design contexts, we aim to stimulate discussion and open new pathways for future research and development, ultimately contributing to practical tools and resources for design researchers.

Seyed Morteza Hosseini, Milad Heiranipour, Julian Wang et al.

The number of desk workers who frequently conduct their jobs at home has increased dramatically during Covid-19. Work-from-home flexibility makes it attractive for workers and companies, resulting in a “Work-Style Reform” after the Covid-19 pandemic. However, the quick conversion of home spaces into workplaces cannot always sufficiently respond to users’ visual comfort and daylight performance needs which are primary contributors to occupant well-being and productivity. Therefore, this study adopts a mixed-methodology method that integrates parametric thinking, biomimetic, conceptual design, kinetic strategy and the DIVA approach to develop a real-time parametric-generative circular design for multi-objective adaptability that optimizes visual comfort and electric lighting energy efficiency for multiple occupants simultaneously. Parametric simulations of 1458 different options (five different runs per case: a total of 7290) were conducted to assess how the louvers perform regarding daylight, glare, and electric energy usage. Implementing an interactive kinetic louver greatly improved daylight performance in all orientations while simultaneously avoiding visual discomfort for multiple occupants. Furthermore, the use of this façade modification resulted in a substantial decrease in electrical lighting energy consumption, reducing the values from 14.22 to 0.2 kWh/m2/year, 8.1 to 0.18 kWh/m2/year, and 12.88 to 0.18 kWh/m2/year for South, East, and West orientations, respectively. Integrating users' lighting level preferences and the dynamic transitory sensitive area on the façade considerably reduces electric lighting consumption by around 99% compared to the ASHRAE 90.1 standard's lighting profile.

Mahya Fani, Nina Sharp

The impacts of lighting conditions on human circadian rhythms, sleep quality, and cognitive performance have been extensively investigated in the past two decades; however, these studies have yielded inconclusive and variable outcomes. For older adults who are at a higher risk of developing serious physiological and mental illnesses, such as Alzheimer’s or dementia, light therapy has emerged as a low-risk intervention to improve sleep quality and cognitive function. Nevertheless, the optimal methodology for evaluating the efficacy of light therapy in older adults remains unclear. This review has been conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and critically analyzes methodologies in previous studies on lighting's impact on sleep and cognitive performance in healthy older adults, focusing on how these approaches affect the findings. The review is structured into six domains: study setting and type, participant characteristics, lighting conditions, study design, sleep quality evaluation methods, and cognitive performance evaluation methods. Diverse study designs, methods, and population characteristics have influenced the outcomes. Bright light, applied from early morning to early evening, has been shown to enhance sleep and cognitive functions, notably working memory and concentration. It also benefits from dawn simulation throughout the day, which regulates circadian rhythms and improves sleep quality, although the ideal timing is yet to be determined. Intense short-wavelength lights and strong placebo conditions can counteract these positive effects, and using bright light in the evening may impair sleep and indirectly worsen cognitive performance in older adults. Further real-world experimental studies on this demographic, meticulous study designs, a combination of objective and subjective evaluation methods, and comprehensive reporting of lighting interventions are crucial for identifying the optimal lighting design approach for this population.

Zhen Qian, Min Chen, Zhuo Sun et al.

Understanding urban dynamics and promoting sustainable development requires comprehensive insights about buildings. While geospatial artificial intelligence has advanced the extraction of such details from Earth observational data, existing methods often suffer from computational inefficiencies and inconsistencies when compiling unified building-related datasets for practical applications. To bridge this gap, we introduce the Multi-task Building Refiner (MT-BR), an adaptable neural network tailored for simultaneous extraction of spatial and attributional building details from high-resolution satellite imagery, exemplified by building rooftops, urban functional types, and roof architectural types. Notably, MT-BR can be fine-tuned to incorporate additional building details, extending its applicability. For large-scale applications, we devise a novel spatial sampling scheme that strategically selects limited but representative image samples. This process optimizes both the spatial distribution of samples and the urban environmental characteristics they contain, thus enhancing extraction effectiveness while curtailing data preparation expenditures. We further enhance MT-BR's predictive performance and generalization capabilities through the integration of advanced augmentation techniques. Our quantitative results highlight the efficacy of the proposed methods. Specifically, networks trained with datasets curated via our sampling method demonstrate improved predictive accuracy relative to those using alternative sampling approaches, with no alterations to network architecture. Moreover, MT-BR consistently outperforms other state-of-the-art methods in extracting building details across various metrics. The real-world practicality is also demonstrated in an application across Shanghai, generating a unified dataset that encompasses both the spatial and attributional details of buildings.

Yu-Wen Lin, Tsz Ling Elaine Tang, Alberto L. Sangiovanni-Vincentelli et al.

Design automation, which involves the use of software tools and technologies to streamline the design process, has been widely adopted in the electronics industry, resulting in significant advancements in product development and manufacturing. However, building design, which involves the creation of complex structures and systems, has traditionally lagged behind in leveraging design automation technologies. Despite extensive research on design automation in the building industry, its application in the current design of buildings is limited. This paper aims to (1) compare the design processes between electronics and building design, (2) highlight similarities and differences in their approaches, and (3) examine challenges and opportunities associated with bringing the concept of design automation from electronics to building design.

Kevin Lin, Zhengyuan Yang, Linjie Li et al.

We introduce DEsignBench, a text-to-image (T2I) generation benchmark tailored for visual design scenarios. Recent T2I models like DALL-E 3 and others, have demonstrated remarkable capabilities in generating photorealistic images that align closely with textual inputs. While the allure of creating visually captivating images is undeniable, our emphasis extends beyond mere aesthetic pleasure. We aim to investigate the potential of using these powerful models in authentic design contexts. In pursuit of this goal, we develop DEsignBench, which incorporates test samples designed to assess T2I models on both "design technical capability" and "design application scenario." Each of these two dimensions is supported by a diverse set of specific design categories. We explore DALL-E 3 together with other leading T2I models on DEsignBench, resulting in a comprehensive visual gallery for side-by-side comparisons. For DEsignBench benchmarking, we perform human evaluations on generated images in DEsignBench gallery, against the criteria of image-text alignment, visual aesthetic, and design creativity. Our evaluation also considers other specialized design capabilities, including text rendering, layout composition, color harmony, 3D design, and medium style. In addition to human evaluations, we introduce the first automatic image generation evaluator powered by GPT-4V. This evaluator provides ratings that align well with human judgments, while being easily replicable and cost-efficient. A high-resolution version is available at https://github.com/design-bench/design-bench.github.io/raw/main/designbench.pdf?download=

Horre Toodekharman, Mahdieh Abravesh, Shahin Heidari

As advanced technologies become prevalent, they are being used more widely in numerous fields. The building sector is not an exception. One of these cutting-edge technologies is responsive facades, which are used in buildings and have an undeniable effect on daylighting. However, they have not been adequately evaluated for improving visual comfort in hospitals. This study investigates visual comfort in a standard patient room, based on applying four responsive facades. Simulations were conducted using HoneybeePlus, a plugin in the Grasshopper. Simulation-based results of annual indicators, including Annual Sunlight Exposure (ASE) and spatial Daylight Autonomy (sDA), showed that different facades could result in several optimal modes. Furthermore, a more comprehensive investigation should consider factors such as Daylight Glare Probability (DGP) and Daylight Glare Index (DGI). Glare indicators revealed that facade directly affects patient visual comfort and can even have an adverse effect. When the optimal responsive facade is chosen, it enhances users' visual comfort throughout the year, yet there will be still glare probability in some cases. Based on the results, this probability decreases as patient distance increases, and Window to Wall Ratio (WWR) is not particularly effective in reducing glare. Nevertheless, when it comes to daylight availability, WWR cannot be ignored, and the first façade with WWR 60% showed the best overall performance.

D.Debby Rifka, Faurantina Forlana Sigit, Rahmadhani Fitri et al.

BBPLK (Great Center for the Development of Job Training) is one of the job training centers in the city of Medan which is also known as the Indonesian Vocational Work Training (PLKI) under the coordination of the regional office of Indonesian workers in the province of North Sumatra. BBPLK itself has a park that has the potential to be used as an attractive plan, namely the welcome area where the site location is not well organized. The problem in this planning is how to plan the welcome area of the BBPLK park based on education and training landscapes with the Thematic Architecture approach. The design concept used is the concept of a clean cut thematic garden which is neatly based, well organized, and has three area divisions, namely the thematic garden area, the special training center area for landscapes, and the nursery placement area in the training park.

Jhon Alfred Alfred D.D, DVX. Deddy Kurniawan

Ende City as the capital of Ende Regency which has the potential to become a center of economic growth, has transportation facilities and infrastructure that support one of which is adequate air routes. Haji Hasan Aroeboesman Airport connects Ende City with several cities in East Nusa Tenggara Province and other cities in Indonesia such as Denpasar, Makassar and Surabaya. Haji Hasan Aroeboesman Airport annually experiences an increase in the number of passengers. Based on data from the Central Statistics Agency, the flow of passengers with total departures and arrivals in 2018 reached 213,590 passengers. The number of aircraft is 2451 aircraft, luggage is 857,741 kg, and goods are 98,208 kg. With this increase, this will have an impact on the capacity and facility needs in the airport terminal. Airports are also required to be able to accommodate changes in activities and developments that may occur in the future. This study aims to conduct studies related to theavailability of Haji Hasan Aroeboesman Airport services so that it can provide recommendations for efforts to improve the service capabilities of Haji Hasan Aroeboesman Airport.  The method used in this study uses a deductive method, where the data obtained are compared and then taken positive and useful things and consider the aspects of the shortcomings. The results of the study on the comfort and availability of departure room services at Haji Hasan Aroeboesman Airport in general are the need for a redesign to overcome various problems such as an increase in the number of passengers, aircraft and goods from year to year.  And specifically, various problems were found such as: the standard for space needs does not meet the LOS (Level of Service) standards set by IATA, does not have an area specifically for commercial areas and other supporting facilities, and the level of comfort felt by users (repondents) is only 26%.

Alireza Aslani, Caroline Hachem-Vermette

Lang Feng, Wenjian Liu, Chuliang Guo et al.

With the popularity of deep learning, the hardware implementation platform of deep learning has received increasing interest. Unlike the general purpose devices, e.g., CPU, or GPU, where the deep learning algorithms are executed at the software level, neural network hardware accelerators directly execute the algorithms to achieve higher both energy efficiency and performance improvements. However, as the deep learning algorithms evolve frequently, the engineering effort and cost of designing the hardware accelerators are greatly increased. To improve the design quality while saving the cost, design automation for neural network accelerators was proposed, where design space exploration algorithms are used to automatically search the optimized accelerator design within a design space. Nevertheless, the increasing complexity of the neural network accelerators brings the increasing dimensions to the design space. As a result, the previous design space exploration algorithms are no longer effective enough to find an optimized design. In this work, we propose a neural network accelerator design automation framework named GANDSE, where we rethink the problem of design space exploration, and propose a novel approach based on the generative adversarial network (GAN) to support an optimized exploration for high dimension large design space. The experiments show that GANDSE is able to find the more optimized designs in negligible time compared with approaches including multilayer perceptron and deep reinforcement learning.

Caroline Quinn, Ali Zargar Shabestari, Marin Litoiu et al.

Buildings Automation Systems (BAS) are ubiquitous in contemporary buildings, both monitoring building conditions and managing the building system control points. At present, these controls are prescriptive and pre-determined by the design team, rather than responsive to actual building performance. These are further limited by prescribed logic, possess only rudimentary visualizations, and lack broader system integration capabilities. Advances in machine learning, edge analytics, data management systems, and Facility Management-enabled Building Information Models (FM-BIMs) permit a novel approach: cloud-hosted building management. This paper presents an integration technique for mapping the data from a building Internet of Things (IoT) sensor network to an FM-BIM. The sensor data naming convention and timeseries analysis strategies integrated into the data structure are discussed and presented, including the use of a 3D nested list to permit timeseries data to be mapped to the FM-BIM and readily visualized. The developed approach is presented through a case study of an office living lab consisting of a local sensor network mimicking a BAS, which streams to a cloud server via a virtual private network connection. The resultant data structure and key visualizations are presented to demonstrate the value of this approach, which permits the end-user to select the desired timeframe for visualization and readily step through the spatio-temporal building performance data.