Three-dimensional Building Structures Research Articles

Characterizing the 3-D structure of each building in the conterminous United States

The three-dimensional building structure is crucial for understanding human activities and environmental interactions. Previous studies have estimated building height on a grid-scale, lacking height estimation results concurrently over large areas and at fine resolution. Here we mapped the height of each building in the conterminous US in 2020, using integrated multi-source datasets (i.e., satellite observations and geometry features). Our proposed model for height estimation is proven reliable (i.e., The model's R2 is 0.82, and RMSE is 3.35 m in the conterminous US) and superior in cross-validation with other existing datasets at different scales. We found an explicit pattern of buildings decaying from the urban core to rural areas, which is more noticeable in big cities (e.g., New York). Furthermore, we proposed the seamless and explicit Urban Canopy Parameters (UCPs) datasets, including six UCPs (e.g., building area fraction and height -to-width ratio) based on our height dataset. As key parameters used in climate models, our UCPs improved the fine-grained description of 3-D urban structures compared with those traditionally used. Overall, our building-by-building height dataset and UCP datasets reveal the significant heterogeneity of urban underlying surface, which can help socioeconomic and climatological urban studies.

RITZ METHOD IN THE DISCRETE APPROXIMATION OF DISPLACEMENTS FOR SLAB CALCULATION

Introduction: The FEM reduces the problem of structural analysis for various building structures to the formation and solution of a system of linear algebraic equations. For this purpose, there are techniques available for obtaining FE stiffness and flexibility matrices where the main structural deformation characteristics are taken into account. However, the FEM can also be considered as a special case of the Ritz method in the discrete approximation of the required functions. In the functional of full potential deformation energy with regard to the considered structure, all adopted stress-strain state characteristics are taken into account. Since it is difficult or impossible to find continuous approximation functions both in the classic version of the Ritz method and in the Bubnov–Galerkin method for some types of edge restraint in such building structures as beams, slabs, or shells, it is possible to use the Ritz method in the discrete approximation of the required functions (by analogy with the FEM). This paper presents a method of such calculations using slab calculations as an example. It is shown that, due to introducing some notations (operators), the process of finding the coefficients of the system of linear algebraic equations creates no difficulties and is easily programmable. The proposed method is not an alternative to the FEM, which is the most effective numerical method for the calculation of complex three-dimensional building structures. Purpose of the study: We aimed to create a method for calculating slabs by the Ritz method in the discrete approximation of the deflection function for edge restraint cases when it is difficult or impossible to find continuous approximation functions in the classic version of the Ritz method and the Bubnov–Galerkin method. Methods: Based on the application of the Ritz variational method in the discrete approximation of displacements for slab calculation, all the basic relations for rectangular finite elements with 12 degrees of freedom are obtained, and an algorithm for forming the coefficients of the system of linear algebraic equations is developed. Results: For the first time, the solution by the Ritz method in the discrete approximation of slab displacements is obtained for the case when two edges of the slab are rigidly restrained and other two edges are free. In this case, the correct solution of the above problem is possible only with the use of the proposed method and FEM. For the test problem, we performed a comparison of the results of the calculation using the proposed method with the results using the classic Ritz method, which showed their very close agreement. The accuracy of the obtained results was assessed.

Does cropland threaten urban land use efficiency in the peri-urban area? Evidence from metropolitan areas in China

In recent decades, cropland policies have been recognized as crucial tools for ensuring food security and managing urban growth. However, whether cropland conservation undermines urban land use efficiency (ULUE) in peri-urban areas has not been adequately studied. This study investigated the impact of cropland on ULUE in the peri-urban areas of 36 rapidly urbanizing metropolitan areas in China. Multiple open-source datasets were used, including land use, land cover, three-dimensional building structure, and nighttime light (NTL) data. Urban construction land patterns (infilling, edge, outlying) were categorized to examine the intermediate role of urban form in the correlation between cropland and ULUE. The findings indicated that: (1) high proportion of cropland area within the peri-urban areas significantly undermined ULUE; (2) although the conservation of cropland is conducive to compact urban growth, the infilling expansion pattern that compelled by cropland conservation would not sustain intensive human activity; and (3) reducing the spatial separation between conserved cropland and urban construction land was conducive to the dual objectives of protecting cropland and promoting ULUE. This study contributed to the development of a nuanced understanding of cropland protection policies that balance national food security and urbanization efficiency.

ENERGY SAVING FACTORS IN WINTER CONCRETING

This article considers energy-saving technologies for winter concreting of building structures and constructions. Various authors have studied mathematical models of the thermal regime of a three-dimensional building structure. The mathematical model of the heat balance equations in the concrete structure, the thermal conductivity coefficient, the dependences of the heat balance equations in the concrete structure and the junction, the thermal conductivity coefficient, the volumetric thermal conductivity, respectively, in the erected fragment and the previously erected part of the wall was implemented on a computer. The article considers the processes of cement and concrete strength gain during early freezing of concrete. In previous studies by various authors, it was found that with an increase in the time for gaining critical strength, the cost of electricity is reduced by 25-50%, due to the use of thermal inertia of the structure. The rate of cooling of monolithic structures at negative temperatures is revealed. The chemistry of cement hardening processes during early freezing is shown. Thermodynamic calculations set the limits of negative temperatures at which concrete strength curing stops, but under the action of repeated positive temperatures, the cement hydration process resumes and concrete continues to harden. The aluminum minerals of Portland cement clinker are usually the first to hydrate when the cement hardens with water, and in the presence of gypsum they form calcium hydrosulfoaluminate. This connection is very fragile and is destroyed by mechanical stress (repeated vibration) and over time even at normal temperatures. The article reviews the foreign experience of winter concreting and the preferred methods of work in this case.

Probabilistic Seismic Response Prediction of Three-Dimensional Structures Based on Bayesian Convolutional Neural Network

Seismic response prediction is a challenging problem and is significant in every stage during a structure’s life cycle. Deep neural network has proven to be an efficient tool in the response prediction of structures. However, a conventional neural network with deterministic parameters is unable to predict the random dynamic response of structures. In this paper, a deep Bayesian convolutional neural network is proposed to predict seismic response. The Bayes-backpropagation algorithm is applied to train the proposed Bayesian deep learning model. A numerical example of a three-dimensional building structure is utilized to validate the performance of the proposed model. The result shows that both acceleration and displacement responses can be predicted with a high level of accuracy by using the proposed method. The main statistical indices of prediction results agree closely with the results from finite element analysis. Furthermore, the influence of random parameters and the robustness of the proposed model are discussed.

Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure

Understanding urban morphology is essential for various urban management studies and local environmental issues and guiding sustainable city development. Existing studies mainly focus on analyzing urban morphology from the horizontal aspect, while the urban vertical structure has rarely been discussed due to the scarcity of reliable and fine-scale urban three-dimensional (3-D) building data. This study develops an effective data-fusing methodology to estimate the heights of individual buildings at a city scale. We examined a machine-learning regression model by collecting public materials, including multi-source remote sensing-(RS)-based products, building-derived features, and relevant data to verify its performance in building height estimation. By applying the model in Shenzhen City, a dense city in the Guangdong-Hong Kong-Macao Greater Bay Area, results demonstrated that integrating rich multi-source explanatory variables could achieve high-accuracy building height retrieval. Using multiple building morphological metrics derived by building height data as proxy measures, the urban 3-D form patterns were further analyzed to understand current heterogeneous urban morphological structures. The proposed methodology can be conveniently applied to worldwide cities for urban 3-D morphology retrieval. Also, the available building height information is useful for planners to design morphological control for cities and thus contributes to sustainable and smart city development.

Analyzing the impact of three-dimensional building structure on CO2 emissions based on random forest regression

Carbon dioxide (CO2) is the primary greenhouse gas that increasingly threatens environmental conditions and public health. In addition to conventional socio-economic mitigation measures, a healthy urban design can substantially contribute to the reduction of CO2 emissions. Nevertheless, previous attempts only concentrated on the impacts of horizontal landscape pattern and spatial structure on CO2 emissions. The relationship between three-dimensional building structure and CO2 emissions remains to be explored. To fill this knowledge gap, our study analyzed which building indicators matter most to CO2 emissions in high-density areas. First, we discovered the linear relationships between CO2 emissions and various potential spatial drivers based on Pearson correlation test. Second, we examined whether the additional consideration of different building-related indicators can better explain the variation in CO2 emissions using random forest regression. These experiments indicated that building coverage ratio, mean building number, spatial congestion degree, and floor area ratio can exert substantial impacts on CO2 emissions in the study area. Building structure is a key factor affecting CO2 emission volumes. For example, our improved model yields a lower root relative squared error (32.53%) than the benchmark model (34.68%). This methodological framework, which can be easily applied to any other regions, is expected to provide valuable information for the reduction of CO2 emissions from the perspective of vertical urban planning. Policy-makers should carefully consider the impact of building structure on CO2 emissions at an earlier stage of the healthy urban design.

AN RBF BASED HIGH-DIMENSIONAL MODEL REDUCTION APPROACH IN BUILDING OPTIMIZATION

Building optimization has gained importance with the recent push to create the most economical and efficient buildings possible. As the effects of optimization are a function of the building size, it is crucial to understand and further develop optimization techniques for large-scale building structures. Practical structural optimization of buildings requires the use of a structural analysis software package and an iterative optimization procedure. As a result, finite element (FE) software shall be linked with an optimization solver. It is an expensive process which requires extensive computer coding. Alternative methods are available, including metamodeling methods, which are used to create simple and approximate functions based on complex FE simulations. In this study, the approximate functions are generated using a high-dimensional model representation (HDMR) framework. The HDMR framework is a model reduction approach and is found to be very accurate for different functions. The component functions of HDMR are expressed using augmented radial basis functions (RBFs). To further improve the numerical efficiency of the metamodels and reduce the total required number of structural analyses, a few different HDMR sampling approaches are investigated, including one static approach and two iterative strategies. An existing nonlinear programming (NLP) solver is employed in the design process. To illustrate the proposed approach, a three-dimensional building structure is selected as a numerical example. The numerical optimization is conducted to reduce the torsional response of the building. The proposed optimization method works very well and the results from different HDMR techniques are compared.

Gibbs Sampling for Damage Detection Using Complex Modal Data from Multiple Setups

This paper presents a novel Gibbs sampling approach for structural health monitoring (SHM) with detection of structural changes/damages using incomplete complex modal data measured with a limited number of sensors. The usual difficulty with the availability of sensors in SHM practices and enforcing data acquisition in multiple setups is thoroughly addressed. Structural modeling incorporated with damping is considered in this proposed inverse problem exercise to calibrate damping parameters along with the stiffness and mass parameters facilitating SHM. Both proportional and nonproportional viscous damping are adopted in structural modeling. Detailed formulations on the probabilistic detection of changes/damages are presented in detail. Moreover, a Gibbs sampling technique is introduced to quantify uncertainties of the various sets of uncertain parameters, where samples of the conditional probability density function of a parameter set are obtained iteratively. The proposed approach retains the typical advantage of the nonrequirement of mode-matching. A validation exercise is performed using a three-dimensional building structure (attached with supplementary viscous dampers) and a laboratory steel structure considering multiple damage cases and different sensor placements. The proposed methodology is observed to be efficient for SHM using incomplete complex modal data measured with a limited number of sensors.

Limited Sensor-Based Probabilistic Damage Detection Using Combined Normal–Lognormal Distributions

A methodology for probabilistic damage detection in Bayesian framework without any requirement of mode matching is presented with detailed formulations on finite element model updating using incomplete modal data measured using limited number of sensors. Multiple modal measurement/data sets from multiple different sensor set-ups can be used in the proposed methodology with further scope for using repeated measurements from any single sensor set-up. Combined normal–lognormal multivariate distribution is considered in the Bayesian framework. Strictly positive random parameters are assigned with lognormal distribution, while the remaining random parameters are assigned with normal distribution. In this work, the normal distribution is incorporated for the likelihood function, which consists of the eigen-system equation error and the error between the system mode shapes and experimental mode shapes. On the other hand, mass and stiffness parameters are assigned with the lognormal distribution. Detailed formulations for probabilistic identification of changes/damages are also developed. The proposed approach is validated using a three-dimensional building structure considering multiple simulated damage cases. Performance in updating and damage detection is evaluated based on multi-set-up and multi-dataset considerations. Besides, the proposed technique is compared with the similar Bayesian updating solely based on normal distribution and the Gibbs sampling.

Frequency-Domain Physical-Parameter System Identification of Building Structures with Stiffness Eccentricity

A frequency-domain method of physical-parameter system identification is developed for three-dimensional building structures with stiffness eccentricity. Equations of motion in the time domain are transformed into the frequency domain. The dynamic equilibrium of the free body above the j-th story is used to identify the j-th story stiffness and damping. It is required to measure the horizontal and rotational accelerations at all stories to identify the story stiffness and damping coefficients of all stories. Compared to the previous approach using the special identification function, the limit manipulation at zero frequency is unnecessary and is robust for noise. Furthermore, it should be remarked that the quantities of eccentricities in all stories can be identified using the slopes of the functions for torsional stiffness identification in the frequency domain.

Direct Linear System Identification Method for Multistory Three-dimensional Building Structure with General Eccentricity

A method of physical-parameter system identification is proposed here for three-dimensional (3D) building structures with in-plane rigid floors in which the stiffness and damping coefficients of each structural frame in the 3D building structure are identified from the measured floor horizontal accelerations. A batch processing least-squares estimation method for many discrete time-domain measured data is proposed for the direct identification of the stiffness and damping coefficients of each structural frame. While previous researches on the system identification of 3D building structures are limited to a class of structures with regular eccentricity, the present paper removes this limitation. Advantageous features of the proposed identification method are that it is unnecessary to specify the stiffness eccentricities (location of center of stiffness) before identification and the identification of all stiffness and damping parameters can be performed simultaneously. The reliability and accuracy of the proposed method are demonstrated by numerical simulations.

Dissipative devices for earthquake resistant composite steel structures: bolted versus welded solution

This paper investigates and compares the seismic performance of two types of innovative repairable fuse devices for earthquake resistant composite steel frames through experimental tests and numerical analyses. The fuses are energy dissipating devices consisting of steel plates that can be welded or bolted to the beam web and bottom flange. The numerical analyses performed in this study are based on the results of experimental tests carried out on beam-to-column sub-assemblages equipped with both the types of fuse devices. The main differences in terms of hysteretic behavior and failure modes of the fuses are identified through the experimental campaign. Detailed three-dimensional finite element models of the beam-to-column sub-assemblages are then created to provide a deeper insight into both the response and the effectiveness of the two investigated devices. On the basis of the results of both the experimental tests and numerical analyses, simplified models of different types of fuses are developed in order to study the effects of bolted and welded devices on the seismic response of composite steel frames. The results are then extended to the case of three-dimensional building structures with different number of storeys. The experimental and numerical investigations prove the effectiveness of the fuses and highlight the main differences between the two possible solutions.

Numerical study on the importance of radiative heat transfer in building energy simulation

ABSTRACTA neural network-based model for interior longwave radiative heat transfer has been developed and implemented into a new computer code, BERHT (Building Energy with Radiative Heat Transfer). The model accounts for the non-gray effect of absorbing species in a building environment and the geometric effect of a three-dimensional building structure. Numerical studies have been carried out on a rectangular single-story building. For nominal concentration of CO2, H2O, and small particulates, results show that the effect of radiative heat transfer is important. The surface emissivity of enclosure walls and optical properties of the absorbing/emitting medium are demonstrated to have significant effects on the distribution of heat transfer between convection and radiation, as well as the transient behavior of the indoor air temperature. Supplemental studies provide an insight that the one-zone, well-mixed model used in building energy simulation generates a “fictitious” non-local heat transfer behavior, leading to uncertainties in the understanding of the radiative heat transfer effect.

초고밀도 고층복합빌딩시스템의 최적설계

In this study, we propose an innovative lateral force distribution building system between tall buildings by utilizing the difference of moment of inertia, as the alternative design for highly integrated city area. Considering a tri-axial symmetric conditions and boundary conditions for the three-dimensional building structure system, a two-dimensional model is composed. In the proposed indeterminate structural model, important design variables are determined for obtaining minimum horizontal deflections, reactions and bending moments at the ground level of the buildings. Regarding a case of the provided two spatial structures connected to 4 buildings, the optimum location of middle located spatial structure is 45% from the top of the building, which minimize the end moments at the bottom of the buildings. In the considered verification examples, reduced drifts at the top location of the building systems are validated against static wind pressure loads and static earthquake loads. The suggested hybrid building system will improve the safety and reliability of the system due to the added internal truss-dome structures in terms of more than 30% reduced drift and vibration through the development of convergence of tall buildings and spatial structures.

Optimal Allocation of Non-Linear Viscous Dampers for Three-Dimensional Building Structures

A new approach has been proposed by the authors and applied to allocate linear viscous dampers optimally for twoand three-dimensional building structures recently. This approach is extended to search for the optimal allocation of non-linear viscous dampers in this paper. The same initial damper placement is used for conducting the analysis. However, instead of carrying out the linear time-history seismic analysis, the non-linear time-history seismic analysis is performed first to obtain the inter-story drift ratio. Then, check the inter-story drift ratio for the locations where dampers were added and move the damper in the location with the minimal inter-story drift ratio to the location with the maximal inter-story drift ratio. Finally, repeat this process until the prescribed stop criterion is met. The nonlinear viscous dampers with two exponents, including 0.3 and 0.5, and two seismic records, including the El Centro earthquake and Chi-Chi earthquake, are used in this paper. Three examples, including two 10-story and one 20-story three-dimensional unsymmetrical building structures, are used to demonstrate the efficiency and accuracy of the proposed approach. The results are compared with those obtained using the simplified sequential search algorithm (SSSA) and are also compared with the optimal placement of linear viscous dampers obtained using the proposed approach. It is found that the proposed approach requires much fewer analyses than the SSSA while their accuracy is comparable. The efficiency of the proposed approach for allocating non-linear viscous dampers is also comparable to or better than for allocating linear viscous dampers.

The performance of composite-steel-framed building structures in fire

This paper outlines the behaviour of steel and composite structures in fire, and reviews recent research developments in this field, and describes the practical implications for designers. The initial focus is on isolated beams, columns and slabs. The effect of structural continuity afforded by skeletal frame construction is considered, and the importance of connection stiffness discussed. Finally, the importance of considering the behaviour of complete three-dimensional building structures is demonstrated, and the direction suggested by this major research area is outlined.