The paper presents a system for supporting optimization-based design exploration, with a special focus on comparing design strategies for early design stages. The system is developed to facilitate designers to conduct multiple optimization runs so as to compare the strengths and weaknesses among different design strategies. The system connects Rhino-Grasshopper to a web-based evaluation server. In Rhino-Grasshopper, designers can encode different design strategies and input these parametrized strategies into the optimization workflow that connects to the evaluation server. The evaluation server records the data sent from Rhino-Grasshopper and provides various interfaces to visualize and analyze optimization results. To demonstrate its utility, a case study is presented to demonstrate the utility of the system in urban design.

Smart city initiatives have been a driving force for city-level dataset collection and the development of data-driven applications that benefit effective city management. There is a need to demonstrate use cases for effective city management using the available dataset. Urban Digital Twin (UDT) is a 3D city model that can integrate multi-disciplines and improve systems operability on a digital platform. However, UDTs are developed within organisations, and there is only limited availability of authoritative open 3D datasets to explore the potential of UDT concepts. This paper reports a methodology for creating a UDT platform for visualising and querying city energy data. We demonstrate a bottom-up approach to constructing an integrated 3D city dataset and create a query system for rapid access and navigation of the 3D city dataset through a visualisation platform using Cesium Ion. Various use cases are explored based on the dataset, such as building material stock management, energy demand simulation, electric vehicles (EV) demand and flexibility, and estimation of greenhouse gas (GHG) emissions. These use cases can help decision-makers and stakeholders involved in city planning and management. Furthermore, it provides a guideline for developers willing to create UDT applications for smart city initiatives.

Painterly Expansion seeks to develop a novel workflow that interfaces digital sculpting processes and algorithmic geometry production to generate complex spatial and surface qualities. The research speculates that the combination of human intuition and algorithmic processes will generate novel hybridised geometric outcomes. The workflow seeks to mask indexical qualities inherent in isolated processes of mesh based folding algorithms and procedural deformation techniques whilst exploring opportunities to extract emergent geometric qualities. The methodology is evaluated recursively with each iteration split into three stages, that encompass the layering of algorithmic, parametric, and manual modelling processes. The purpose of shifting between modelling processes is to counter the linear application of indexical qualities that originate from a singular process with the intention of producing emergent topological and ornamental effects. The algorithmic approach explores the application of differential growth logic in combination with procedural retopology and manual sculpting.

This paper presents a methodology designed to study the visual impact of a tall building located in the vicinity of a protected area of exceptional cultural scenic value listed by the UNESCO World Heritage. Digital analyses of the city were carried out using the following methods: a) the Visual Impact Size (VIS), which allows to determine both the visual impact field and the domination of architectural objects in space; b) simulations of selected views from the human eyesight level. The proposed cityscape survey methodology is presented based on the example of the city of Toru? (Poland) in relation to the location of a planned high-rising building. The study used a 3D Digital Surface Model of the city (DSM). All simulations were carried out using proprietary software (C++).

As an auxiliary space in engineering projects, the process of parking lot design is often under-appreciated, which is highly repetitive, time-consuming, and leaves little space for creativity. Thus, optimizing existing design methods and improving design efficiency is an aspiration of the industry. Based on integer programming, this paper focuses on the surface parking lot as the main research object and explores the possibility of changing the parking lot plan design from manual to computer-generated. According to the research of relevant norms, this paper classifies the parking lot plan in terms of organisation mode and summarises 27 kinds of parking lot plan modes by analysing the state of the inner ring, traffic organisation, and parking angle. The model can efficiently solve the problems related to parking lot arrangements, such as whether to arrange parking spaces in the inner- ring of the contour and how to choose the internal parking angle, which saves manpower and improves the design efficiency and quality.

Sound, an often easily overlooked part of the urban composition, plays a crucial role in urban studies regarding how people perceive urban acoustic environments. Influenced by variable natural and artificial acoustic elements, the multi-level nature of urban soundscapes reflects multidimensional urban characteristics and thus demands thorough investigations. Unravelling the acoustic complexity and understanding its influence on public spaces' popularity will benefit the interpretation of urban soundscapes and help to build a more vibrant public life. In this paper, we utilize DepthMapX and QGIS to select specimen sites for further investigation. The behavioural analysis is performed through principle components analysis (PCA) and K-Means analysis based on data obtained within the city of London. This project seeks to develop digital strategies to investigate the relationship between urban public spaces and their soundscapes: to infer the correlation between people's emotions and the richness of urban environments. Through integrating machine-learning analytic approaches into visualizing how citizens perceive or experience the urban sound environment, our research aims to positively assist and inform urban practitioners in planning and designing more benign acoustic environments.

Housing is among the most pressing issues in China. Researchers are eager to identify housing property's internal and geographic factors influencing residential property prices. However, few studies have examined the relationship between social media users' point of interest (POI) data and house prices using big data. This paper presents a machine learning model for regression analysis to reveal the relationship between housing prices and check-in POI density in Futian District, Shenzhen. The results show that our proposed price prediction model using additional features based on POI data proved to provide higher prediction accuracy. Our results indicate that incorporating POI features based on current feeds from location-based social networks can provide more up-to-date estimates of housing market price trends.

The quality of the outdoor environment relates to urban ventilation performance. Poor wind conditions in high-density urban districts may lead to severe air pollution and deteriorate outdoor thermal comfort. The increase of openings in building geometry is one of the effective passive design strategies for enhancing the porosity of urban morphology and benefitting urban ventilation. However, the outdoor wind environment correlates with the opening configurations of building geometry complicatedly. For seeking the optimal opening configurations, a decision support tool is urgently needed. Our study proposes a genetic algorithm-based optimization workflow for the opening configurations of building geometry design by integrating Computational Fluid Dynamics simulation and parametric design. A residential block in Shenzhen, China is chosen as an example to show this workflow. The results demonstrate that when the porosity is 15%, the pedestrian-level mean wind speed, the wind speed dispersion, and the pressure difference between the front and rear of the downstream building can be optimized by 20.00%, 19.35%, and 183.33% on maximum. When the porosity is increased to 30%, these values are 42.22%, 16.13%, and 483.33%. The resultant opening distribution probability maps can support building design at an early stage to achieve a comfortable urban environment.

This paper focuses on a specific aspect of human visual discrimination from computationally generated solutions for CAAD ends. The bottleneck at work here concern informational ratios of discriminative rates over generative ones. The amount of information that can be brought to a particular sensory modality for human perception is subject to bandwidth and dimensional limitations. This problem is well known in Brain-Computer Interfaces, where the flow of relevant information must be maintained through such interaction for applicative ends and adoption of use in many fields of human activity. While architectural modeling conveys a high level of complexity in its processes, let alone in the presentation of its generated design solutions, promises in applicative potentials of such interfaces must be made aware of these fundamental issues and need developments of appropriate sophistication. This paper addresses this informational bottleneck by introducing a method to retrieve spatial information from the rapid serial visual presentation of generated pictures. This method will be explained and defined as inverse modeling, based on inverse graphics, and its relation to human visual processing.

The thermal performance of buildings is measured as heat energy transfer between the buildings and the surrounding environment, and there are several heat exchange possibilities. This paper presents the thermal performance of 12 non-air-conditioned low-income single dwellings in warm-humid climates. The Building and material characteristics of the dwellings, including field measurements of the 12 cases, were meticulously documented through a primary survey. The critical indicator for assessing and evaluating the performance of the dwelling unit was hourly simulated indoor temperature data for an entire year. Further, potential planning and design components, viz. building orientation, roof and wall insulation, window size, property & locations, clerestory window, increased floor-to-ceiling height, site setback, and roof profile, were iterated to improve the thermal performance of low-income dwellings. Indoor temperatures as high as 45.9 C were recorded, the mean indoor temperature for the summer months (March-July) was over 34.64 C, and it was always higher than 30 C for the rest of the month. The findings show that the inhabitants are subjected to temperatures exceeding 34 degrees Celsius for more than half of the year. The paper concludes with some suggested design measures to improve the thermal performance of low-income houses. The study also emphasizes the importance of refined early design phase assessment and decision-making to improve the indoor thermal environment.

This paper leverages the specific food-architecture duality as an exemplary site to evaluate how seemingly insurmountable act of bisociation or conceptual blending might be achieved successfully, first by previous state-of-the-art AI models based on generative adversarial networks (GANs) such as CycleGAN and VQGAN-CLIP; and followed by today’s state-of-the-art diffusion-based AI models such as OpenAI’s DALL-E 2 and Midjourney. Such a workflow necessitates the creation of not only a dataset of images consisting of architecture and food, but also their respective text descriptions. Instead of using textual input prompts to generate images of architecture with the discipline’s own vocabulary, the research equally extracts and merges that with the vocabulary of food, thus exploiting and blending their formal aesthetics in novel ways. Although comparisons between DALL-E 2 and Midjourney have been made ‘in the wild’ on some social media platforms, none have focused on a detailed and systematic analysis of bisociating two aesthetic domains, namely, food and architecture. The research is the first to explore the creative design affordance of today's deep generative models, through a familiar fairy tale consisting of food and architecture, in provoking discussion of the technology with respect to its critical appropriation for architectural design in the near future.

Urban agricultural systems will be configured over the following years to respond to increasing climate change, urbanisation, and population growth. Controlled environment agriculture (CEA) is an increasing trend since it can be easily integrated into the built environment. However, this food production system requires intensive capital and energy resources, with artificial lighting as the primary contributor to its high operational impacts. New methods and tools for planning and design can provide innovative solutions for shifting urban agriculture toward sustainability. This paper addresses the food security challenge in cities by introducing a sunlight-based computational approach for indicating the agricultural possibilities of three-dimensional urban surfaces according to crop-centric environmental suitability. The procedure aims to improve CEA efficiency through a passive natural lighting optimisation strategy, indicating the sunlight thresholds for various crop species. The methodology interconnects solar radiation values measured through sunlight simulations with crops’ daily light integrals, using Singapore and Chennai (India) as case studies. The results suggest that urban areas with high solar radiation levels possess large degrees of year-round harvesting potential. This methodology can assist designers (architects, urban planners, and engineers) and local governments in strategizing urban agriculture developments and provide decision-making support for crop harvesting initiatives in cities.

Building information modeling (BIM) is critical to the industry's digital transition. Its diffusion is also expected to improve project economics. However, maintaining adequate information in the common data environment (CDE) typically becomes the bottleneck. Conversations still take place outside of the model workflow, easily becoming untraceable. This article proposes the fusion of the BIM and metaverse, which can serve as a CDE (MaCDE). The metaverse workspace hosts the project meetings, presenting the model as the virtual venue. Avatars' utterances can be automatically recorded, indexed, and tracked. The enhanced traceability of information reduces the burden of dealing with contractual issues and motivates professionals to join, stay, and utilize the model environment. The concept demonstrates that the model can be continuously leveraged regardless of its Level of Development. The increased visibility helps align stakeholder expectations with the model deliverable. The improved coverage and searchability of the archive help recapture the lost revenue, improving the project profitability and the ongoing effort to enhance productivity.

The working population has increased in cities with urbanization. Providing a supportive built environment with reasonable amenities distribution for them is becoming more important. Previous GIS-based approaches to urban planning for this issue tend to be subjective with high labour costs. This paper uses the generative adversarial network (GAN) to explore the relationship between amenities distributions and urban morphology, thus effectively predicting and visualizing the ideal amenities distributions in fast-growing cities based on the condition of well-developed megacities. In this research, we take Shanghai, one of the global cities in China with a big labour market, as the research sample. First, we use the Point of Interest (POI) data to draw the heatmap of urban amenities that support workers’ daily life and collect the corresponding city maps. Then, we cut them into hundreds of image pairs as the training set and train a GAN model for predicting the future amenities distributions in other cities. To implement the model, we further collect the city maps of Jiaxing, one of the second-tier cities near Shanghai, as the testing set. Results show that our trained model can accurately predict amenities distributions for its future. The GAN-based prediction could effectively support detailed urban planning.

Afforestation in drylands is an active ecosystem restoration strategy shown to increase ecosystem services in these regions, which are highly prone to land degradation. Nevertheless, seedling recruitment is difficult in such projects due to various biotic and abiotic stresses. This paper proposes a methodology for providing tree seedlings in drylands with 3D-printed soil-based bioclimatic envelopes. The workflow suggests key aspects in transforming locally sourced soils to 3D printable, bioclimatically performable materials. Essential robotic tooling aspects and processing parameters are proposed. In addition, ways to embed site-specific data to algorithmically conceive a customized envelope according to the tree species are suggested.

As the digitalization in the architecture, engineering, and construction (AEC) industry has been rapidly progressing, building end users will require more coverage of quality data for their built environment. Despite its obvious need, it is seldom for the building information modeling (BIM) to be distributed for such broad use cases thus far. A potential reason for the situation is the lack of the public repository that can provide the adequate access control for various users. Distributed Ledger Technology (DLT), including blockchain, is one of the promising resolutions for the problem. Numbers of preceding proposals for DLT-based BIM repository systems (BIM-DLT system) have proved the utility to date. Understanding the statistical facts of their configurations will become a significant assistance to determine the plausible data distribution system, and thus, to strengthen the project information life cycle. This article aims to build a representative framework through the integrated literature review (ILR). The review results showed that the system’s data flow was classified into two patterns. The judgment criteria for selecting the pattern of the system are expected to depend on the purpose of system implementation, and the purpose of automation through smart contracts is more important than the oracle problem.

This research examines a digitalization of workflow to assist design and construction with irregular wood in its natural form at a location close to logging areas with restrictions on processing methods. Currently, wood availability is determined by closed distribution channels with standardized production. Simple and effective use of irregularly shaped branches allows us to escape this limitation. We have attempted to develop a method of building structures with the following three features with only certain branches available, limited to chainsawing and bolted joints that can be used in the mountains. First, modeling systematically irregularly shaped branches by converting photogrammetry scanned standing trees into simplified data while preserving shape features. Second, supporting assembly design of the structure by dynamic segmentation of irregularly shaped branches as parts before cutting down the tree. Third, cutting with mixed reality guidance for joints is automatically generated from assembly geometry. To test these methods we experimented with fabricating a structure from a single-standing tree with a chainsaw. In conclusion, the construction of a data flow connecting raw materials to structures was verified to be effective in realizing pre-felling design studies and simple on-site processing for the use of natural wood in mountainous areas.

Agent-based modeling method was used in the study to simulate the behaviour of the crowd pushing against the "bottleneck" areas in the building. The described research involved a simulation testing of the throughput of the staircase used for the evacuation of a building located on a university campus.   The study proposes a proprietary method for investigating throughput in a two-dimensional model using the horizontal compound of the average speeds achieved on the stairs by users, considering their age. The method used makes it relatively simple to study the maximum throughput of a stairwell separately from other factors affecting evacuation performance. Based on the results obtained in simulations, the capacity value in the studied situation was determined and several behaviours related to crowd density and stairway speed were observed. This method can be used to simulate the distribution and number of emergency exits from a building using only the maximum number of evacuated occupants, without modeling all floors of the building.
 

What modernism has failed discuss is the sheer diversity of forms that can come with a singular function. Their order led to the systematisation of standardised architectural elements that are now widely used around the world. However, functions of architecture have manifested into a multitude of forms across different cultures. For instance, the roof of the Korean traditional architectural type, Hanok, can be easily differentiated from the Victorian gable roof. The function-form relationship in architecture has long been investigated, but there is a lack of objective tool or technique that directly contributes to categorisation or diversification of existing architectural forms. With the advent of novel Machine Learning techniques, especially Generative Adversarial Networks (GANs), architectural forms can now be traced with objective methodologies such as a probabilistic-based model. This paper seeks to increase architectural diversity, borrowing the objectivity of state-of-the-art machine learning techniques in three dimensions such as 3D GAN.
 

Industrial Revolution 4.0 offers an opportunity for the globe to rethink the meaning of building information that breaks the territorial borders of building information systems that are not based project-wise but follow a geopolitical structure. It expands the conventional thought process of being limited to a building to a city/ planetary urbanisation level. As a response to the new urban design theory, the paper posits an approach that amalgamates “Design for Disassembly (DFD)” and “Digital Twins” which have gained traction because of “Circular Economy” and “Industrial Revolution 4.0” respectively, to create an information framework for the urban ecology that focuses on system management rather than project management via “Material Passport (MP) 2.0”. It identifies the gaps within the existing MP and creates a foundational framework for the added information (termed “Material Strategies”) that needs to be a part of MP 2.0 that arise while working across systems by augmenting DFD and Digital Twins via the lens of materials. The material strategies are further investigated through a correlation matrix to understand their interdependency to finally create a JavaScript Object Notation (JSON)-based serialisation of materials to reinstate the material circularity and reduce the carbon emissions that the construction sector accounts for.

The paper discusses a novel design approach that applies artificial intelligence as an auxiliary tool throughout typology research and architectural design. The method attempts to utilize neural network as a research tool to detect and identify features of a typical architectural type within the specific society context and demonstrate its potential for regional design under the theme of human centric. Typology classification, computational vision, and human-machine collaboration are entwined throughout machine learning and architectural design. The paper aims to demonstrate the ability of 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions (TreeGAN) to study the inherent principle and characteristic of an architectural type and its potential to provide possible design inspirations based on the typological formation principles concluded by Deep Learning. The article exhibits the key result generated by TreeGAN in a specific architecture type—churches, as the prototype of a design method and conducts a project in Manhattan.
 

Multi-functional complexes have gradually become a new trend in the development of gymnasiums. Different types of layout patterns, such as space combination, space depth ratio, and atrium forms, will have a more obvious impact on the indoor energy consumption and comfort of the gymnasium. The genetic algorithm SPEA-2 and the Pareto optimal multi-objective optimization workflow were introduced in this study to help architects improve the layout design of the gymnasium in the early design stage. This workflow can optimize radiation energy load and indoor thermal comfort by adjusting plan parameters. The study combined with test cases to explore the Pareto frontier solution set (30 generations) of the layout morphological parameters?LMP? under different layout combination modes, and to explore in which combination mode, the energy load and the indoor thermal environment comfort can achieve a relative balance. Part of the optimal solution is selected for quantitative analysis of the performance improvement ratio, so as to verify the simulation test results.

Traditional pre-design investigation includes conceptual studies, site analysis, and programming processes to analyze the site and design for users. Instead, designers and architects should consider users' ideas and their actual usage of space, which are recorded and reflected on the social media platform. To introduce more citizens' voices in the design and learn more about people's expression of Detroit city and its housing, we propose to involve the machine learning analysis in the earlier stage of the housing project using users' reflections from social media to support the conceptual design. This paper introduces a novel design framework that deals with the lacking public programs in Detroit using an online data clustering platform and demonstrates a conceptual open-source community housing design according to related findings. This framework incorporates data collection from the Twitter platform, implementation of clustering for user-oriented programs, and design applications based on the findings. Our research demonstrates an efficient and flexible approach to the open-source community housing project.

In this article, we present Variable Aggregate Impact Printing (VAIP), a novel additive manufacturing methodology for the automated assembly of traditional cob using a six-axis robotic arm and custom tool. This methodology enables the aggregation of discrete particles composed of soft heterogeneous material containing aggregates of multiple sizes. Single-particle experiments were conducted to optimize particle geometry and study the behaviour of individual soft particles under compression. Multiple particle prototypes were produced to understand the behaviour of soft particle aggregation under sequential compression. Variation in individual block size and aggregate content are accommodated due to the tolerances afforded by the malleability of the blocks. A model for the tolerance of soft particle aggregations is developed for particle positioning and orientation in relation to particle deformation. Finally, a large-scale installation was fabricated as a proof-of-concept prototype for the scalability of natural earth-based materials using computational design and robotic manufacturing technologies.

After experiencing the Covid-19 pandemic, remote communication became one of the key issues in almost every field and discourse. Digital fabrication is no exception, and architects hope to seek a user-friendly way for human-machine interactions. This paper presents experimental research using Augmented Reality (AR) for robotic remote programming. The research tries to develop a unique pipeline and workflow which allows users from different locations to program robots and communicate with machines through AR. A sample workflow has been tested as a series of simple brick assemblies in an online workshop with remote participants. The pipeline allows all users to be able to remotely program and control a robot in AR. For this workshop, we transform the robotic coding method from the traditional computer science way to the plugin-oriented AR visual programming way in Grasshopper. As for the physical outcomes, participants all assembled brick-based structures successfully by programming and operating the robotic arm in AR remotely at the end. Associating the interaction in AR with the robotic arm and programming it with interactive visual input methods will make it easier for architectural practitioners to simulate and control industrial robots for complex structure assembly.

Many studies have shown that the non-visual effects of daylighting have a positive effect on human physiological health.  However, due to non-visual effects are different from visual effects in spectral distribution, influencing factors and evaluation standards, the existing lighting simulation software cannot satisfy both visual and non-visual evaluation simultaneously.  Based on a review of the latest non-visual studies, the research team developed a climate-based simulation framework devised to investigate both the visual and non-visual effects of daylighting in buildings simultaneously by using multi-objective optimization tool. The simulation framework integrates four functional modules, including boundary conditions input, simulation of visual and non-visual effects, multi-objective optimization calculation, and result output and analysis. A total of 12 computing components are written through Ghpython for data processing and visual expression. The applicability of the simulation framework is demonstrated using a real standardized classroom in Nanjing, P.R. China.  The simulation framework generated three optimal daylight design schemes, which significantly improved indoor visual and non-visual effects of daylight.  The results suggest that the framework can be used to assess the performance of various daylighting design strategies which simultaneously consider visual and non-visual effects.

Researchers have leveraged machine learning technologies and physics-based modelling and simulation techniques to generate fast predictions of factors relevant to building daylighting, energy use, and other performance metrics. However, in the current literature, there is no generalized method outlining the thought process behind whether to implement physics-based simulation, machine learning, or both methods. This paper first proposes a conceptual framework that identifies the considerations researchers might ask when developing their workflow. Second, it presents an example case study developed according to the framework. The case study used daylight simulation and parametric modelling software to generate synthetic data automatically to train a conditional generative adversarial framework. The model was hosted on an interactive web app allowing users to create their building designs and provide design performance metrics and improved design simultaneously.

This study looks at a review of literature in regard to holographic construction within the period of 2012-2022, specifically analyses of its potential to aid circular design adaptation. The rationale behind this study is the lack of circularity context in holographic construction and augmented reality studies. The outcome of this literature review reveals aspects of holographic construction that lead to support for circular design opportunities. This paper provides a snapshot and is summarised with identified research gaps related to four key principles of circular buildings.

The packing and transportation of building materials is an important process in building construction. There are many small construction sites in Japan, where it is impossible to take all building materials out of the vehicles and store them on the site at one time. At the same time, many customized structural parts are often involved in building construction now. Their size and shape do not have fixed specifications like standardized building materials. In this article, automatic packing and analysis evaluation algorithms were written in Rhinoceros and Grasshopper environments to help users calculate and generate multiple results after loading the same wood in different order, and evaluate each result in multiple aspects. It is convenient for users to compare the advantages and disadvantages of different loading methods and finally choose the appropriate scheme. Finally, a packing case is analyzed by this algorithm, and the analysis results were obtained in a short time. Experimental results show that the algorithm can solve the problem effectively and successfully, and it has high practical value.

Currently, teleconferencing via the internet is widely used in society. However, physical models such as design study models, which are often used in face-to-face meetings in the fields of architecture and urban design, cannot be shared in teleconferences where information is shared on a display. Telepresence is a technology for sharing 3D real objects at a distance that gives the sensation of sharing and experiencing the environment and objects at a remote location. As one such technology, a system has been developed in which the point cloud of a real object acquired by a camera is divided into objects by instance segmentation, and the divided point cloud is transmitted to the remote user, who can manipulate it on mixed reality. There is a problem of missing point clouds in areas not seen by the RGB-D camera, such as occlusion and the back of the camera. This research aims to develop a system that can remotely manipulate point clouds with more accurate geometry by using a point cloud completion technique based on deep learning to complement missing point clouds. This system is expected to contribute to smoother teleconferencing of remote participants.

The principle of symmetry has beneficial applications in architecture. Symmetry mainly creates order and equilibrium in complex designs. This study presents a graph theoretic approach for the automatic generation of rectangular floorplans with block symmetry. Existing graph theoretical approaches focus on the floorplan’s outer boundary design, different room shapes, and spatial arrangements. This paper introduces block symmetry as a new concept in floorplan generation. Based on this concept, an algorithm is proposed for generating a rectangular floorplan with rectangular blocks for a given adjacency graph if one exists. Further, suppose two blocks are required to be symmetric, i.e., of equal size. In that case, an optimisation framework is used to equate the widths and heights of the blocks, resulting in the generation of a rectangular floorplan with block symmetry. A GUI is provided for users to perform the automatic generation of floorplans.

This practice-based research presents insights into the potential and challenges for augmented and mixed reality (AR/MR) technology to enhance Australian small-to-medium (SME) custom manufacturers’ agility to overcome existing Industry 4.0 (I4.0) workforce productivity and efficiency challenges. Moreover, it seeks to understand the technology’s ability to support custom manufacturers and the architectural, engineering and construction (AEC) sector transition to a more human-centric Industry 5.0 (I5.0) model, whereby the well-being of the fabricator is placed back at the centre of manufacturing processes. This qualitative study draws on interviews with eleven Australian custom manufacturing industry professionals to inform pertinent themes around fabricators’ current use and perceptions of mixed reality technology. Results indicate benefits for fabricators in reducing 2D drawing and task-related ambiguities in fabrication and assembly practices and reveal factors surrounding underutilisation. Synthesising insights and reflecting on Teixeira et al., (2021)’s XR-PACT framework, key research areas are identified for future AR/MR development centred on fabrication users’ distinct needs to improve accessibility, empower fabricators and ultimately assist the competitiveness of custom manufacturers and the AEC sector.

This paper investigates how the collective memory of an architectural setting can be captured, re-created, and re-experienced. The method uses a workflow to create a Virtual Environment (VE) from diverse sources in an interpretational and iterative process. A case study was implemented to test this workflow, focusing on the re-creation of a now demolished family home based on information from multiple generations of a family. The workflow's main output is a VE in which the family members can re-experience the house and give continuous feedback. The essence of this workflow is the constant negotiation between remembered space in memory and its digital interpretation in the VE. The output was assessed and refined according to the users' feedback, which is used to loop back to specific stages in the workflow. This process revealed undisclosed histories and enhanced our understanding of this demolished site and its wider context. Moreover, the workflow provides a model for studying conceptually recreated spaces based on subjective sources and provides a user-centred experience in the VE.

Evaluating and deciding on design alternatives is a collaborative activity involving design teams and other design stakeholders in the Architecture Engineering and Construction (AEC) industry. Current tools for design offer limited support for data-informed collaborative decision-making and fall short of encouraging discussions. In a user study with eight domain experts, we investigated how a meaningful data-informed collaboration can be enabled in design through interactive visualizations of design alternatives. We argue that receiving feedback from the design stakeholders as annotations directly on data representations can improve design decision-making. The initial results from our study reveal extensive needs for multi-target coordinated annotations, sorting, and organizing annotations, and agility in creating and accessing annotations. We propose a set of high-level interactions and requirements for coordinated annotation for engaging in collaborative decision-making.

This paper proposes a method to optimize 3D models with complex shapes based on 3D scan models into data that can be machined by 3-axis digital fabrication equipment by utilizing displacement mapping technique. In contemporary architecture, the collage technique is being increasingly used, with complex digital models including 3D scanned objects being used as collaged elements without simplification. Additive manufacturing and subtractive manufacturing are the major techniques used to create these forms, but they are difficult to fabricate on 3-axis machines. This paper first discusses the technical challenges of fabricating collaged models using a 3-axis machine, then the paper proposes a method to optimize the models into data that can be fabricated by 3-axis machines by utilizing displacement mapping technique. The paper introduces two cases of art installations designed and fabricated using the method proposed in this paper and discusses how the method is applied to them. Finally, the potential of this method and challenges to be addressed for the future will be discussed.

This study aims to respond to the 'human-centred' theme of digital heritage and visualisation by exploring a new approach to applying gamification mechanisms to design physical architectural exhibitions. This paper analyses the current exhibition's gamification design in three parts-core drivers, defining characteristics and development models. Then constructs a design model for "digital gamification". The history museum of Harbin Institute of Technology (Shenzhen) is selected as an example to conduct an empirical investigation. Finally, future experiments are proposed to evaluate the design process's effects on improving the platform's design. It is expected that the demonstration of this study will enrich the exploration of the application of the emerging design method of digital gamification mechanism in exhibition design. On the one hand, it attempts to construct the relationship between the influence of digital gamification mechanisms on the tangible and intangible information in the audience's cognitive space, thus providing new ideas for designing cultural experiences in future exhibition spaces. On the other hand, it gives new vitality to the exhibition design and enhances the audience's motivation to interact, which helps to expand cultural communication's influence.

The study intends at innovating a new relationship between modern digital fabrication technology and vernacular material of construction to break through the stagnation of the construction and design industry. Through this, the research objective is to revive vernacular cob houses in India by contextualising 3D printing to promote social acceptance of mud in a modern way and experiment with its printability to 3D print future cob buildings. To address this research objective, the study specifically explores the steps taken by the artisans to prepare the material mix suitable to build houses. Thus, through a prototype-driven process and rapid experimentation of soil, 3D-printed wall prototypes were tested at a 1:1 scale. The study will present and discuss these physical experiments carried out to develop the concepts of 3D printable mud in detail.

ICOMOS has pointed out that digital technologies have become important ways to protect heritages. Existing researches focus on the digital reconstruction of heritage in virtual spaces. Less attention is paid to the utilization of heritage entities and the potential for virtual heritage interaction to present complex values of heritages. Augmented reality (AR) can integrate text, images, and models into digital information to add to heritages in real sites. This paper takes the Grand Canal? a great masterpiece of Chinese civilization and even human history, as a research object. With the acceleration of the urbanization process and the change in transportation patterns, the contradiction between the preservation of it and urban development has become increasingly prominent. Based on the analysis of heritage values, this research reconstructs digital models of heritages and develops interactions with them in the Unreal Engine, relying on mobile AR to create a novel cultural landscape through a combination of virtual and real Grand Canal. This research contributes to improving the material and cultural living standards of citizens by integrating heritage preservation and urban design through the design and development of this digital system.

Buildings with complex shapes are increasingly being constructed using digital fabrication tools. However, many building components nevertheless require specialised skills for their assembly at the construction site, even if the manufacturing has been streamlined. In this study, by practising an agile design process that repeats the method of  ‘Add-on the tool’ and  ‘feedback on form and material, we devised a construction method that allows unskilled workers to be involved in the fabrication of pavilions and the creation of complex curved surfaces without requiring special skills, so long as the rules of assembly are determined. In this study, a method of achieving large curvatures using wire bending of Y-shaped wooden units made of 4-mm thick lauan veneer boards was proposed, in which large curvatures were used to design two-dimensionally curved surfaces with continuous wavy shapes. This method was also used to control the force applied to the wires by controlling their lengths. The free curved surface with the elastic bending of the plywood allowed a height of 2.3 m and a span of 6 m.

Taking Street view map and Random forest model as the applications and four consumption places in Beijing as case studies, this study proposes a method that maps spatial perception preferences at the local scale to the global scale by following steps: Firstly, download street view images of consumption places from BaiduMap API, then combined the preference of the local street view images scores by the volunteers of both genders and the proportion of visual elements in the images, predicted the preference level of case areas at the global scale by the Random forest model, and finally, through FCN model and sDNA model, fully revealed the gender differentiation phenomenon of consumption places at the image, function and location contents. The results indicate that both genders have a preference for places of Catering function. Besides, females generally prefer consumption places with more conspicuous signboards, greening and better spatial design quality, and have clear pre-determined consumption targets; males generally prefer consumption places with more conspicuous columns, smaller signboards, and have less demand for the spatial design quality of consumption places.

Rammed earth construction has long been operated as a manual process involving unsaturated loose soil compacted inside a formwork. Earth soil is a type of highly sustainable naturalistic raw material decomposable with minimum environmental impact, with diverse colour and properties along by default. In addition, the high thermal resistance and moisture-absorbing quality of rammed earth walls significantly benefit the passive environmental comfort of the established environment. However, the manual process of rammed earth construction is excessively time and labour-intensive and highly dependent on skilled workers. More importantly, the visual effects on the vertical surface have long been overlooked by designers and builders, which has the potential to fulfil the aesthetic variety of facades. However, distributing the earth material with various colours to the specific position hinges upon the advanced fabrication accuracy and skilled workers. This process is similar to working in a black box, where it is hard to evaluate and detect the fabrication situation. Therefore, to tap into the potential of rammed earth construction, this research aims to develop an automatic robotic system capable of constructing rammed walls with a customisable distribution of different soil layers precisely.

This study evaluates the spatial configuration of existing traditional houses and their extension buildings to identify adaptation patterns applied by current generation occupants. As preserved by the community for their sacred values, transformation in traditional houses might seem slow, and an attachment to a new building could be disruptive. However, by tracing how the spatial configuration is being preserved, varied, and changed through computational modelling, this research shows that the space adaptation is more subtle than expected. The study formulated rules for traditional houses and their extension transformation using space syntax and shape grammar analysis. The rules simulation highlights consistent degrees of adaptation and evolution patterns in the four villages that were observed that were not immediately apparent visually. The adaptation pattern can be used as a reference for heritage conservation and future design precedence.

The paper presents a novel process of fabricating concrete columns using 3-dimensional (3D) knitted fabric in conjunction with an industrial robotic arm acting as scaffolding. The research explores the feasibility of using wool as a biomaterial for fabricating formwork, thereby reducing construction waste and weight compared to traditional steel, fibreglass, or timber techniques. By examining the knit architecture in conjunction with experiments in slump admixture and tensile testing of the fabric formwork, the research developed several full-scale prototypes. The outcomes were scanned and analysed to understand the geometric deviation as a result of repeat usage of the fabric as formwork. The research demonstrates the resilience of the knitted wool fabric as formwork for concrete casting.

The Digital Altarpiece is an immersive virtual temple that seeks to communicate a traditional funeral ritual from Ayacucho, Peru, and revive it in a contemporary environment. Due to the confinements in times of pandemic, these Peruvian Andean rituals of social integration were in danger of disappearing. The ancestral knowledge in humanity has a cultural and spiritual value. Through this project, the theory of dehumanization due to the excess of new technologies and the preservation of cultural memory using digital tools and machine learning are questioned. For this, digital memories were collected, photographs of physical spaces openly uploaded to the web by their authors. This data was extracted to learn features using GANs or Generative Adversarial Networks. The intention of using photographs from social networks was to reinterpret and discover a new local and collective perspective. Although artificial intelligences have the power to excite us with new figure proposals, we humans are experiencing the sensations of these pieces, and we can direct our technical explorations with new technologies that change so quickly, to cultural integration.