Building Geometry Research Articles

Analysis of Diaphragm Force on Reinforced Concrete Building Structures with Horizontal Irregularities of Diaphragm Discontinuity

The diaphragm plays a crucial role in distributing seismic forces within buildings during earthquakes, affecting both regular and irregular structures differently. This study investigates the seismic behavior of diaphragms in various building geometries resembling the letters I, T, L, and O, focusing on their influence on structural performance and reinforcement requirements. Using analytical methods, diaphragm seismic forces, slab shear stresses, and internal forces were calculated for a sample of buildings with different geometrical irregularities. The study reveals significant differences in diaphragm earthquake forces between regular and irregular buildings, with irregular geometries exhibiting distinct patterns of shear stress distribution. Particularly, the building with an L-shaped plan and concentrated stress points showed the highest maximum shear stresses in both orthogonal directions. Analysis of internal forces—axial, shear, and moment—highlighted varying reinforcement needs among the studied buildings. While axial and shear forces necessitated minimal additional reinforcement across all structures, moment forces indicated substantial reinforcement requirements, particularly in the L-shaped building. These findings underscore the importance of tailored diaphragm design strategies for buildings with irregular geometries to mitigate potential structural vulnerabilities during seismic events. The study contributes insights into optimizing diaphragm design practices and emphasizes the need for further research in this critical area of structural engineering.

Using Passive Multi-Modal Sensor Data for Thermal Simulation of Urban Surfaces

Abstract. This paper showcases an integrated workflow hinged on passive airborne multi-modal sensor data for the simulation of the thermal behavior of built-up areas with a focus on urban heat islands. The geometry of the underlying parametrized model, or digital twin, is derived from high-resolution nadir and oblique RGB, near-infrared and thermal infrared imagery. The captured bitmaps get photogrammetrically processed into comprehensive surface models, terrain, dense 3D point clouds and true-ortho mosaics. Building geometries are reconstructed from the projected point sets with procedures presupposing outlining, analysis of roof and fac¸ade details, triangulation, and texturing mapping. For thermal simulation, the composition of the ground is determined using supervised machine learning based on a modified multi-modal DeepLab v3+ architecture. Vegetation is retrieved as individual trees and larger tree regions to be added to the meshed terrain. Building materials are assigned from the available visual, infrared and surface planarity information as well as publicly available references. With actual weather data, surface temperatures can be calculated for any period of time by evaluating conductive, convective, radiative and emissive energy fluxes for triangular layers congruent to the faces of the modeled scene. Results on a sample dataset of the Moabit district in Berlin, Germany, showed the ability of the simulator to output surface temperatures of relatively large datasets efficiently. Compared to the thermal infrared images, several insufficiencies in terms of data and model caused occasional deviations between measured and simulated temperatures. For some of these shortcomings, improvement suggestions within future work are presented.

Towards Auto-Calibrated UBEM Using Readily Available, Underutilized Urban Data: A Case Study for Ithaca, NY

The shift toward urban decarbonization, which involves transitioning to heat pumps and integrating photovoltaic (PV) energy generation, poses substantial challenges to electricity grids in cities. Ithaca, NY, with its commitment to the Green New Deal, serves as a case study for cities confronted with these challenges. This paper explores how various building electrification scenarios might affect Ithaca's net-zero ambitions. We show that our reduced-order Urban Building Energy Modeling (UBEM) approach can accurately predict building energy consumption and rooftop solar PV energy generation for the 6114 buildings in the City of Ithaca. Building on that, we present three increasingly ambitious decarbonization scenarios that offer a holistic perspective on Ithaca's future electrification potential. In automating the reconstruction of building geometry from readily available LiDAR data, along with automated BEM setup and calibration, our methodology offers a robust toolkit to plan holistic decarbonization efforts. We argue that our approach, which forecasts both UBEM and PV for all residential and commercial buildings within a single framework, provides insights that cannot be reached with siloed methods. In the future, we believe that the abundance of readily available urban data sets will allow us to transition our approach to other jurisdictions across the US.

Towards feasible and credible building modelling reflecting the operational energy use and indoor environment – Nordic climate case study

Credible building modelling is essential to the building energy certification and building renovation towards better energy performance and indoor climate. The primary objective of this work is to assess the consequences related to the level of effort necessary to simulate the building geometry and its facilities and to guide practitioners in building modelling by providing insights about the model simplification consequences both for the energy performance and comfort. This work focuses on the sensitivity of model geometry simplification and heating system and the influence of these on the energy and thermal comfort KPIs in standard simulation conditions. Moreover, the study presents models verification towards operational performance, investigates the complexity of adapted simulation conditions, e.g., heating setpoint, actual people load on the model credibility comparing to monitored data. The sensitivity study main conclusion is that there are relatively small differences in heating demand among models with different zoning methods of geometries, while the implementation of detailed heating systems in the simulation has a more noticeable effect on the results of all output KPIs. The Model verification activity main conclusion is that adapted people’s load can improve the model accuracy. Models with detailed geometry, lead to more accurate results when the heating set-point in the model is defined as monitored data per apartment. For dwellings with a limited number of IAQ measured points, use of the standard set-point is advised instead of monitored. For the apartments with sufficient IAQ sensors, adapted heating setpoint and people load can significantly improve the model predictions.

Optimal Positioning of Small Wind Turbines Into a Building Using On-Site Measurements and Computational Fluid Dynamic Simulation

Abstract Renewable energy solutions are essential for addressing several pressing issues, including climate change, the fossil fuels supply chain fragility and fuel price fluctuations. One promising technological solution is rooftop-mounted turbines into buildings. This study presents an evaluation of the potential for wind energy utilization on the rooftop of a 29 m tall building. The primary objective of this research is to develop a methodology that can effectively investigate the integration of small wind turbines (SWTs) into urban buildings, intending to promote energy sufficiency in urban areas. A robust framework has been developed that consists of seven steps. These steps include site selection, evaluating urban wind energy with computational fluid dynamics (CFD) simulation and on-site measurements, selecting an appropriate SWT, estimating the annual energy production (AEP), conducting an evaluation of the environmental impact, resilience, and economic analysis, and finally, installing the system. This straightforward yet reliable framework provides a comprehensive approach to assessing the viability of wind energy utilization in urban areas. The findings revealed that the most suitable location for installation had an estimated AEP of around 1030 kWh, leading to a reduction in emissions of 0.64 tCO2/y. Additionally, it was observed that the building's geometry and orientation significantly affected the wind flow, causing a substantial decrease in wind speed downstream. Selecting optimal sites and considering wind patterns are essential for maximizing energy generation in wind energy projects.

A comparative life cycle assessment of building sustainability across typical European building geometries

In recent years, significant progress has been made in the sustainability assessment of building materials and buildings. The introduction of Environmental Product Declarations (EPDs), the development of Level(s), and the release of relevant series of standards have helped to improve the sustainability of buildings. However, a research question that remains unresolved is the lack of information related to the comparison of the sustainability performance of building units across Europe and the significance of conducting such research. This study addressed this question by implementing a comparative whole-building Life Cycle Assessment (LCA) across buildings in Europe. The study emphasizes the necessity of considering typical building geometries and thermal performance of buildings across Europe and introduces six typical building geometries for three different European clusters (northern-western, central-eastern, southern cluster). The results of this study revealed that the sustainability performance of buildings is not similar across the EU and that cost-optimal minimum thermal performance requirements for building structures have a significant impact on their environmental performance. Particularly, single-family houses in Central and Eastern Europe are responsible for 324.42 kgCO2e/m2. Contrary to this, Northern and Western European single-family buildings have the lowest environmental impact with 268.97 kgCO2e/m2. Multifamily houses in Southern Europe are responsible for 321.82 kgCO2e/m2, in Northern and Western Europe the environmental impact is 275.37 kgCO2e/m2. The outcome of this study is significant for the scientific community involved in assessing the sustainability of buildings in Europe, as it provides valuable insights into their environmental performance, considering the energy efficiency and sustainability aspects of buildings. The study's findings should be considered when setting minimum LCA-related requirements, in view of the provisions of the new EU policies expressed in the Energy Performance of Buildings Directive (EPBD) recast for defining the Global Warming Potential (GWP) of new buildings.

Diminishing benefits of thermal mass in Iranian climate: Present and future scenarios

Thermal mass, a pivotal element in a building's performance, functions as an indoor thermal buffer. While literature underscores its advantages, the enduring impact of thermal mass amid climate change remains uncertain. This study methodically assesses thermal mass effects in 21 Iranian cities across contemporary and future climates, juxtaposing heavyweight and lightweight constructions. The EPSAP algorithm, a generative building design method, created a dataset of two-story single-family houses. Cooling and heating demands were evaluated in EnergyPlus, accounting for current and future system design efficiencies. Future climates were simulated using EC-Earth3 model estimations for the SSP5-8.5 scenario in 2050 and 2080 timeframes. The findings reveal that the energy efficiency advantage of heavyweight over lightweight buildings will diminish by up to 0.60 kW·h·m−2 in 2050 (40 % less than the present-day climate difference between constructions) and 0.93 kW·h·m−2 in 2080 (63 %) for cities in central and southern regions. The performance differences between constructions will sometimes be null, making thermal mass negligible. Conversely, only three cities in Northern Iran exhibit an opposing trend for mid to very-high thermal transmittances. Regarding building geometry, heavyweight construction correlates strongly with indexes related to building compactness, while lightweight construction aligns more with glazing-related indexes. However, as climates warm or we move towards warmer regions, discernible differences between lightweight and heavyweight constructions vanish for both shape- and glazing-related indexes. In conclusion, although the use of thermal mass will be less effective, building design professionals will have greater latitude for innovative construction and design solutions.

Machine learning‐based wind‐induced response analysis in rectangular building models with limbs

SummaryThis study investigates the impact of different positions of two limbs on the structural response of a rectangular building model to wind forces. The building's geometry assumes Z and + shapes based on specific limb configurations. Computational fluid dynamics (CFD) simulations are performed to quantify wind‐induced pressures, resulting in wind force coefficients. These coefficients are used to develop predictive machine learning models through Gene Expression Programming, Group Method of Data Handling‐combinatorial (GMDH‐Combi), Model Tree, and Artificial Neural Network (ANN) techniques. The ANN analysis explores various combinations of training algorithms, adaptation functions, activation functions, and performance functions to enhance model accuracy. Among these, the Levenberg–Marquardt (LM) with gradient descent with momentum (GDM) adaptation function and sigmoid activation function exhibit superior performance with high R‐squared values. These predictive models are then employed for a comprehensive comparative assessment of the maximum wind force coefficient (CF, max) concerning different limb positions and angles of attack (AOA). For CF, max vs Limb position, variations of limb position are examined for most critical cases of AOA. Similarly, the study of CF, max vs AOA involves an exhaustive investigation into the variation of AOA for the building with the worst limb position. The analysis reveals that changes in AOA have a more pronounced effect on CF, max compared to alterations in limb position. Interestingly, within the AOA range of 1.5 to 2.5, the CF, max consistently reaches a minimum across all models. However, the relationship between CF, max and the critical structural parameter ‘S' (representing limb position) remains less conclusive for the most significant AOAs.

Structural performance and fragility assessment of elevated residential buildings during 2017–2018 hurricanes in Texas and Florida

Elevating coastal houses on columns or piles is recognized as an effective technique for reducing the risks of flooding and storm surges. However, recent hurricanes have exposed a potential vulnerability in this approach, as many elevated residential structures sustained significant wind damage even at wind speeds below the current design level. Elevating a structure increases its exposure to stronger winds and leads to potential changes in the wind effects due to the air gap beneath the floor. However, there has been limited research comparing the performance of actual constructed elevated and slab-on-grade residential structures during realistic wind events. To fill this gap, authors utilized publicly available building performance datasets, collected by the Structural Extreme Events Reconnaissance (StEER) Network and others, to extract data on the performance of 851 elevated and 1536 slab-on-grade residential houses impacted by Hurricanes Irma, Harvey, and Michael. Effects of several key parameters were analyzed in terms of the intensity and distribution of the damage experienced by the different components. Furthermore, empirical fragility functions were developed for different roof shapes and cladding materials by combining the estimated wind speed that affected each structure and the assigned damage ratios for the roof and wall claddings. Analysis using the Wilcoxon rank-sum test demonstrated a statistically significant difference in the median wind speeds of various damage states of the components in both elevated and slab-on-grade houses. Additionally, a significant difference was observed in Texas slab-on-grade houses which experienced either no, minor, moderate, or severe damage, compared to their Florida counterparts. Results showed that elevated houses experience more damage than their slab-on-grade counterparts regardless of the roof shape, cladding materials, and construction age. Additionally, results showed that the elevated houses built in Texas exhibit the highest level of vulnerability among the various housing groups studied. Specifically, the percentage of elevated houses in Texas that experienced destroyed damage state surpassed those of slab-on-grade houses in Texas and elevated houses in Florida by 343 % and 166 %, respectively. The paper identified several knowledge gaps, and it emphasized the need for further experimental tests of building components and different building geometries to improve existing risk models.

Iterative Investigation of Wind Environments Influenced by Bulge-Part Geometries of Typical T-Form High-Rise Buildings Using Parametric Modelling, CFD and IAs Analysis

Iterative Investigation of Wind Environments Influenced by Bulge-Part Geometries of Typical T-Form High-Rise Buildings Using Parametric Modelling, CFD and IAs Analysis

Users' Impact on Buildings' Energy Performance Gap

Prior to implementation of new building (or building retrofit) projects, buildings' future energy demand is regularly predicted for certification or optimisation purposes. However, there is often a deviation between the projected and actual energy use during buildings' operation. A number of different factors can contribute to this mismatch that is typically referred to as energy performance gap (EPG). These could be due to uncertainties regarding weather conditions, buildings' systems, construction, and geometry. Specifically, issues regarding occupants' behaviour and related control actions have recently been suggested to be a major cause for the EPG. However, evidence for such a claim is not conclusive. In this context, this contribution explores the impact of occupants' control-oriented behaviour (e.g., interactions with buildings' control components and systems, such as opening or closing windows or adjusting thermostats) on buildings' energy performance. The present contribution entails critical reflections on these issues. Moreover, strategies are discussed that could balance occupants' control opportunities and energy efficiency targets.

Comparative analysis of two evacuation simulation tools when applied to high-rise residential buildings

Currently there are numerous emergency evacuation simulation tools with varying levels of sophistication and differing capabilities. It is expected that investigating the same scenarios using different tools might not give the same outcome. This paper illustrates how a microscopic agent-based modelling tool (Pathfinder) and a macroscopic flow-based modelling tool (Evacuationz) can be setup to investigate high-rise residential building evacuations in comparable ways by varying configuration parameters. Both tools represent individual agents with associated characteristics (e.g., walking speed and pre-evacuation delay). These are varied in the scenarios examined to stress-test the designs or explore the impact of design/procedural changes.The two tools differ in how they deal with the building geometry and therefore have different algorithms to manage evacuee movement. In this work, assumed performance parameters (e.g., travel speeds, spacing, etc.) have been calibrated to better align the conditions represented in the tools and the outcomes produced across the scenarios examined. This then allows the tools to function at their respective levels of sophistication and granularity (providing different perspectives on performance) but adopt a more equivalent performance baseline given the calibration effort.The use of two tools increased confidence in the predictions, and also allowed for an examination of a wider range of scenario conditions such as number of stairs, stair width, and building size, given the different computational expense associated with the tools.

A drone-based approach to enhance spatial insight into surrounding air pollutant distributions for healthier indoor environments

Current investigations into the interplay between indoor and outdoor air quality in buildings often rely on limited measurements of a small subset of air pollutants taken outside the structure. Implicit in this methodology is the assumption of a homogeneous distribution of air pollutants around the building, a premise that may not accurately reflect real-world conditions. This study introduces a more accurate and consistent approach to comprehending air pollutant distributions around buildings through systematic measurements conducted using a drone platform equipped with essential air quality sensors. Employing a fully autonomous drone, the study adopts a parametric approach to collect numerous air pollutant measurements around buildings with unconventional shapes. The resulting air pollutant maps offer comprehensive insights into the spatial distribution of pollutants around the building. A detailed analysis, achieved by dividing the building surroundings into different zones, revealed that concentrations of NO2, CO, PM10, and PM2.5 on the inward facade of the ¾ torus-shaped building were 12.64%, 14.49%, 7.66%, and 15.77% higher, respectively, than in the other measured areas around the building. These findings highlight that air pollutants around the building are notably influenced by the building's geometry, challenging the assumption of homogeneity. Instead, pollutants tend to accumulate at specific points, underscoring the significance of considering these factors in air quality assessments. Furthermore, the noted uneven distribution of pollutants around the building has distinct effects on various sections within the structure, as revealed by indoor measurements. Bureaus on the inward facade, where higher levels of outdoor pollutants are measured, can exhibit up to 44% more indoor air pollutants than those on the other side. This study not only contributes to a nuanced understanding of air pollutant distributions but also showcases the superior potential of drone platforms in advancing such research.

A light-blocking greenhouse film differentially impacts climate control energy use and capsicum production

High-tech protected cropping holds great potential to improve global food security, but high cooling energy costs in warm climates pose difficulties in propagating the industry. Emerging technologies, such as diffuse glasses fitted with photoselective thin films, have interactions with crops and other cooling technologies which are not well-characterized for warm-climate glasshouses. A light-blocking film (LBF) was chosen as a high-tech, climate-controlled greenhouse cover permitting transmission of 85% of photosynthetically-active light and blocking heat-generating radiation. Two consecutive 7-month trials of two capsicum crops were grown under warm climate conditions partially impacted by bushfire smoke, with 2 cultivars (Gina and O06614) in the first trial, and 2 cultivars (Gina and Kathia) in the second trial. Capsicum fruit yield decreased by 3% in Gina and increased by 3% in O06614 for the first trial, and decreased by 13% in Gina, 26% in Kathia for the second trial. Cooling energy use increased by 11% and 12% for both capsicum crops in AE and SE respectively, with small but insignificant decreases in fertigation demand (2%–5%). Cooling potential was significantly different from material specifications, with indications that convection from LBF interfaces was responsible for higher heat loads. LBF and similar absorptive glasses may still be beneficial for reducing nutrient, water, and energy use in warm climate glasshouses. However, yield is cultivar-dependent and may decrease with below-optimal crop lighting, whereas energy savings are more dependent on LBF orientation and building geometry than outside climate.

Wind Effect on External Fire Spread through Openings under the Protection of Horizontal Projections or Vertical Spandrels—A Numerical Study

A numerical investigation has been conducted to analyse the effect of wind on the vertical spread of fire through a front opening in a building’s external walls. The study utilises a building geometry established from previous experimental work conducted by the National Research Council of Canada (NRCC). A horizontal projection or a vertical spandrel is introduced above the opening of the compartment of fire origin. The purpose of the projection or spandrel is to inhibit the vertical spread of the fire, following the relevant requirements in the Australian National Construction Code (NCC). A computational fluid dynamics (CFD) package for fire-driven fluid flow, namely the Fire Dynamics Simulator (FDS), is employed to simulate the fire behaviour. The FDS model is validated against the NRCC’s experimental results, and a good agreement is achieved. Winds from three horizontal directions (front wind is normal to the opening, side wind is parallel to the opening, and back wind is from behind the building) have been investigated, with speeds ranging up to 10 m/s for each wind direction. Front wind speeds below 1 m/s are found to slightly enhance the vertical spread of the fire, while speeds exceeding 1 m/s are inclined to promote horizontal spread. The impact of side wind on the vertical fire spread was also found to vary with wind speed. The increase in the speed of back wind influences flame buoyancy, resulting in an augmented vertical fire spread. Furthermore, the numerical results reveal that a vertical spandrel of 1100 mm height is less effective in preventing vertical fire spread through openings, compared to a 1100 mm deep horizontal projection. The study suggests that the fire safety design in reducing the hazard of vertical fire spread through openings in buildings’ external walls could be further improved if the effect of wind is considered.

Assessing vegetation distribution based on geometrical and morphological characteristics of the urban fabric to provide thermal comfort for pedestrians: A case study in Sanandaj

In previous studies, geometrical aspects of the buildings have been mainly considered in designing of the models, while the impacts of vegetation distribution have not been taken into account. The influence of building geometry on vegetation distribution to create a comfortable thermal environment for pedestrians has not received much attention. An examination of Sanandaj, a city in western Iran, in three fabrics, closed, linear, and open, has been conducted in this study. By using ENVI-met simulator, we studied the orientations, height-to-distance ratio of the buildings, and the geometric shapes of vegetation distributions. There have been two phases to the current research. The first phase includes evaluating the factors that may affect the modeling results in addition to validating ENVI-met software in selected fabrics. A comparison is also made of three model fabrics with and without vegetation in the first phase. The most important environmental factors in this research are air temperature, radiant temperature, wind speed, and physiological equivalent temperature (PET). The results show that there is a positive correlation between orientation and the level of comfort. In a closed fabric, the model with an east-west direction, height ratio of 0.12 and wholly vegetation distribution showed 15.31 % improvement in comfort level compared to the original fabric. The linear fabric with an east-west direction, height ratio of 0.42 and a central vegetation distribution indicated a 22.53 % improvement in the comfort level and in the open fabric, the model with height ratio of 0.75 and the central vegetation distribution improved comfort by 10.42 %.

Reconstruction of 3D Information of Buildings from Single-View Images Based on Shadow Information

Accurate building geometry information is crucial for urban planning in constrained spaces, fueling the growing demand for large-scale, high-precision 3D city modeling. Traditional methods like oblique photogrammetry and LiDAR prove time consuming and expensive for low-cost 3D reconstruction of expansive urban scenes. Addressing this challenge, our study proposes a novel approach to leveraging single-view remote sensing images. By integrating shadow information with deep learning networks, our method measures building height and employs a semantic segmentation technique for single-image high-rise building reconstruction. In addition, we have designed complex shadow measurement algorithms and building contour correction algorithms to improve the accuracy of building models in conjunction with our previous research. We evaluate the method’s precision, time efficiency, and applicability across various data sources, scenarios, and scales. The results demonstrate the rapid and accurate acquisition of 3D building data with maintained geometric accuracy (mean error below 5 m). This approach offers an economical and effective solution for large-scale urban modeling, bridging the gap in cost-efficient 3D reconstruction techniques.

Effect of Build Geometry and Porosity in Additively Manufactured CuCrZr

Abstract The current work presents an understanding of microstructure and mechanical properties as a function of build geometry and build orientation in Cu-Cr-Zr via the laser powder bed fusion (LPBF) technique. Porosity, microstructure, and mechanical properties have been compared in as-printed (AP) and heat-treated (HT) LPBF Cu-Cr-Zr, between cylindrical and cube geometries, along the longitudinal (L) and transverse (T) build orientations. Varying porosity levels were observed that yielded parts with 96–97% relative density in the AP condition. The AP microstructure demonstrated a hierarchical microstructure, comprising grains (2.5–100 μm) with a cellular substructure (400–850 nm) and intracellular nanoscale (20–60 nm) precipitates. Unlike most materials in the AP condition, crystallographic texture was found to be absent; however, very distinct river-like patterns highlighted a novel feature of the LPBF Cu-Cr-Zr. Upon solutionizing and aging, Cr precipitates were seen heterogeneously nucleating along cell boundaries (0.5–1.3 μm), causing up to 45% enhancement in the strength and a 4–5% lower ductility. The yield strength along the transverse orientation was 10–16% higher than that of longitudinal orientation, in both the AP and HT conditions. Fracture surface of the tensile samples exhibited micro-voids, cleavage facets, and unmelted particles. Despite the porosity, overall mechanical properties matched well with those obtained in nearly dense (>99%) samples and the mechanical property debit was less than 10%.

Three-Dimensional Digitization of Documentation and Perpetual Preservation of Cultural Heritage Buildings at Risk of Liquidation and Loss—The Methodology and Case Study of St Adalbert’s Church in Chicago

This paper presents a three-dimensional (3D) digitization methodology for documenting the appearance and geometry of cultural heritage buildings using modern tools for data acquisition and processing. This work presents a method combining laser scanning of building dimensions with photographic texture acquisition techniques in order to develop accurate, photo-realistic 3D models. This work also presents a method for digital reconstruction of the elements of interiors. This case study presents the process and result of scanning the church of St Adalbert in Chicago along with its inner finishing elements, achieved during the interventional 3D scanning of a historical building interior. The obtained colorized point cloud has 3.5 billion points and a volume of 65 GB. Its creation took nearly 3.5 h on a high-end computer. The generated textured mesh model has 1.6 billion triangles and a volume of 60 GB. The analysis of the results showed that the elements of the church furnishings were reproduced with very high accuracy. The developed 3D model of the interior, appearance and dimensions of the church is its perpetual documentation. It can be used for various purposes, such as popularizing the appearance on the Internet, scientific research on interior artefacts, creating files for VR and shooting high-resolution films.

Possible Geometries for Precast Concrete Structures, through Discussing New Connections, Robotic Manufacturing and Re-Utilisation of the Concrete Elements

This study explores the potential use of new connections to shape precast building geometries, focusing on connection performance, robotic fabrication, and foldable structural elements. Three connection types, including coupled-bolts, hinges, and steel tubes, were initially proposed and assessed in beam and portal frame geometries. In contrast, the study introduces conceptual ideas; initial experimental and numerical studies were conducted to estimate connection capacities. Robotic fabrication for connecting elements to reused concrete and converting floor elements into beams was detailed, showcasing robotic technology’s performance and potential. These connections were employed in designing new precast element geometries, ranging from simple beams to multi-story buildings. Geometric properties and volume quantities of folded and opened geometries were studied using 37 CAD models. To properly discuss the joint performance reference, monolithic elements with exact dimensions were created for comparison. Despite varied connection capacity (38% to 100%), the steel tube exhibited the most desirable performance, resembling a monolithic element with an exact size. Some proposed foldable geometries showed a significant reduction (up to 7%) in element dimensions to facilitate transport and construction.