TRIANGULAR MESH APPROACH FOR AUTOMATIC REPAIR OF MISSING SURFACES OF LOD2 BUILDING MODELS

3D city models are increasingly being used to represent the complexity of today’s urban areas, as they aid in understanding how different aspects of a city can function. For instance, several municipalities and governmental organisations have constructed their 3D city models for various purposes. These 3D models, which are normally complex and contain semantics information, have typically been used for visualisation and visual analysis purposes. However, most of the available 3D models open datasets contain many geometric and topological errors, e.g., missing surfaces (holes), self-intersecting surfaces, duplicate vertices, etc. These errors prevent the datasets from being used for advanced applications such as 3D spatial analysis which requires valid datasets and topology to calculate its volume, detect surface orientation, area calculation, etc. Therefore, certain repairs must be done before taking these models into actual applications, and hole-filling (of missing surfaces) is an important one among them. Several studies on the topic of automatic repair of the 3D model have been conducted by various researchers, with different approaches have been developed. Thus, this paper describes a triangular mesh approach for automatically repair invalid (missing surfaces) 3D building model (LOD2). The developed approach demonstrates an ability to repair missing surfaces (with holes) in a 3D building model by reconstructing geometries of the holes of the affected model. The repaired model is validated and produced a closed-two manifold model.

Research on the Use of Neural Network for the Prediction of College Students’ Mental Health

A healthy mental status of students plays an important role in getting quality of education. Hence, research on the prediction of college students’ mental health status is of great importance and considered as a hot area of research. In this specific research study, back propagation (BP) algorithm is adopted to learn verities of characteristics of different students from the historical data of the students including: psychological characteristics, basic personal characteristics, and socio-economic characteristics. In the initial stage of the modeling, data preprocessing steps are used to prepare the data to be used by the BP algorithm for building model. The rationales behind the use of BP algorithm are its capability of handling heterogeneity of data and exploring correlations among different characteristics. The proposed model enhances the capability of BP algorithm for risk prediction of psychological problem of the students and achieves higher precision of psychological problem prediction. The results obtained show that the error between the predicted and measured values is 0.88%.

Tsunami evacution building model (TEBM) in Teluk Palu (Palu Bay) area

The research was conducted in the coastal area of Palu Bay, Lere Village. Data were collected using observation, interviews, and literature study techniques. The data were analyzed using qualitative descriptive methods and focused on the concept of the design of the tsunami evacuation building on the coast of Palu Bay. Data analysis was carried out to obtain an overview of the problems that occurred at the planning location which was analyzed with the concept of architectural design by considering the existing conditions of the site and the surrounding environment, as well as utilizing the potential of the site so that it has the potential for building functions. The conclusion obtained is based on the results of data analysis, it is necessary to have a building that can function as an evacuation container for the community when a disaster occurs in the coastal area of Palu Bay, thereby reducing the number of casualties. The benefit of this research is that it is a solution for local people to save themselves when the tsunami disaster.

Modelling Buildings in CityGML LOD1: Building Parts, Terrain Intersection Curve and Address Features

3D city models integrate heterogeneous urban data from multiple sources in a unified geospatial representation, combining both semantics and geometry. Although in the last decades, they are predominantly used for visualization, today they are used in a large range of tasks related to exploration, analysis, and management across multiple domains. The complexity of urban processes and the diversity of urban environment bring challenges to the implementation of 3D city models. To address such challenges, this paper presents the development process of a 3D city model of a single neighborhood in Sofia city based on CityGML 2.0 standard. The model represents the buildings in LOD1 with a focus on CityGML features of related to the buildings like building part, terrain intersection curve and address. Similar building models of 18 cities provided as open datasets are explored and compared in order to extract good modeling practices. As a result, workflows for generation of 3D building models in LOD1 are elaborated and improvements in the feature modeling are proposed. Two options of building model are examined: modeling of a building as a single solid and modeling of a building with separate building parts. Finally, the possibilities for visualization of the model in popular platforms such as ArcGIS Pro and Cesium Ion are explored.

A REVIEW OF THE DISTINGUISHING FEATURES OF THE HISTORICAL BUILDINGS IN SAFRANBOLU REGION FOR THE PURPOSE OF CLASSIFICATION FOR SEMANTICALLY ENHANCED 3D BUILDING MODEL

In addition to making our daily life easier with the use of it in different areas of our lives, technology continues to be used increasingly with different applications in many sectors.With the increase of developments in the construction sector, which is the locomotive of many sectors, different applications have been used in the field of modelling. But a building needs many projects such as static, dynamic, electricity, installation, furniture, etc. While these sectors are working with different software specific to them, it has been possible to work on these building projects in a single project by the help of BIM (Building Information Modelling).In addition to its function of projecting new buildings, BIM is an important development and building model in terms of preserving historical buildings, easily creating original building details, and transferring them to future generations without deterioration. The term HBIM (Historic / Heritage Building Information Modelling) has been brought to the literature by using the BIM model in historical buildings.The known history of Safranbolu district of Karabük in Turkey dates back to 3000 years. Safranbolu, which has hosted Roman, Byzantine, Seljuk and Ottoman empires in its history, has buildings that are still preserved with their originality. These structures were built in the pre-Ottoman, the Ottoman and the Republic periods.In our study, historical buildings such as houses, commercial houses, places of worship, inns, baths, fountains, and clock towers will be examined. Building models and distinctive features were examined to classify these structures by modeling them with BIM.While the differentiation of the buildings can be made easily by the building model, the distinguishing features of the houses built in different periods or by different civilizations were also determined in order to distinguish the housing types.While structures such as baths, clock towers or inns are not in a number that can be classified, it has been observed that there are residences, businesses and places of worship that can be classified. It has been determined that it is possible to classify the buildings by their materials, building sizes and shapes, and by their other features that can be used to classify.

Automatic, Multiview, Coplanar Extraction for CityGML Building Model Texture Mapping

Most 3D CityGML building models in street-view maps (e.g., Google, Baidu) lack texture information, which is generally used to reconstruct real-scene 3D models by photogrammetric techniques, such as unmanned aerial vehicle (UAV) mapping. However, due to its simplified building model and inaccurate location information, the commonly used photogrammetric method using a single data source cannot satisfy the requirement of texture mapping for the CityGML building model. Furthermore, a single data source usually suffers from several problems, such as object occlusion. We proposed a novel approach to achieve CityGML building model texture mapping by multiview coplanar extraction from UAV remotely sensed or terrestrial images to alleviate these problems. We utilized a deep convolutional neural network to filter out object occlusion (e.g., pedestrians, vehicles, and trees) and obtain building-texture distribution. Point-line-based features are extracted to characterize multiview coplanar textures in 2D space under the constraint of a homography matrix, and geometric topology is subsequently conducted to optimize the boundary of textures by using a strategy combining Hough-transform and iterative least-squares methods. Experimental results show that the proposed approach enables texture mapping for building façades to use 2D terrestrial images without the requirement of exterior orientation information; that is, different from the photogrammetric method, a collinear equation is not an essential part to capture texture information. In addition, the proposed approach can significantly eliminate blurred and distorted textures of building models, so it is suitable for automatic and rapid texture updates.

3D AIR POLLUTION COMPUTATIONAL FLUID MODELLING DATA ANALYSIS USING TERRESTRIAL LASER SCANNING (TLS) AND UNMANNED AERIAL VEHICLE (UAV) APPROACH

Air pollution is a global event that can harm the environment and people. It is recommended that effective management be implemented to allow for the sustainable development of a specific area. The 3D building model is employed in the study to support air pollution modelling for this purpose. A proper mode of data acquisition is required to produce the building model. Many data acquisition (Terrestrial Laser Scanning and Unmanned Aerial Vehicle) approaches can be utilized, but the most appropriate one for the use in outdoor air pollution is needed. This is because it can assist in providing precise data for the modelling of a 3D building while maintaining the shape and geometry of the real-world structure. The accurate data can support modelling of surrounding air pollution concerning wind data and surrounding conditions, where different generated structures can influence the flow of the pollutants. The suitable model can be determined by using suitability analysis and with the implementation of Computational Fluid Dynamics (CFD) simulation. However, from these, no specific technique is chosen because the generated models presented incomplete model. Hence, it is suggested to combine both techniques to acquire building data as the missing surfaces from each technique can be completed by another technique. Thus, this study provides a good reference for responsible agencies or researchers in selecting the best technique for modelling the building model in air pollution-related studies.

Research on Optimal Placement of Actuators of High-Rise Buildings Considering the Influence of Seismic Excitation on Structural Modes

Presently, most of the common placement methods of actuators are based on the structural response and system energy to select the optimal locations. In these methods, the contribution of controllability and the energy of seismic excitations to each mode of the structure are not considered, and a large number of cases need to be calculated. To solve this problem, the Clough–Penzien spectral model is combined with the Luenberger observable normal form of the system to calculate the energy of each state. The modal disturbance degree, considering modal energy and controllability, is defined by using the controllability gramian matrix and PBH system controllability index, and the modes are divided into the main disturbance modes (MDMs) and the secondary disturbance modes (SDMs). A novel optimal placement method of actuators based on modal controllability degree is proposed, which uses MDMs as the main control modes. The optimal placement of actuators and the vibration control simulation of a 20-story building model are carried out. The results show that the vibration reduction effect of the proposed placement method is significantly better than that of the method of uniformly distributed actuators (Uniform method) and the classical placement method of actuators based on the system controllability gramian matrix (Classical method).

Numerical Investigation of the Effect of Sloped Terrain on Wind-Driven Surface Fire and Its Impact on Idealized Structures

In this study, a time-dependent investigation has been conducted to numerically analyze the impact of wind-driven surface fire on an obstacle located on sloped terrain downstream of the fire source. Inclined field with different upslope terrain angles of 0, 10, 20, and 30° at various wind-velocities have been simulated by FireFoam, which is a large eddy simulation (LES) solver of the OpenFOAM platform. The numerical data have been validated using the aerodynamic measurements of a full-scale building model in the absence of fire effects. The results underlined the physical phenomena contributing to the impact of varying wind flow and terrain slope near the fire bed on a built area. The findings indicated that under a constant heat release rate and upstream wind velocity, increasing the upslope terrain angle leads to an increase in the higher temperature areas on the ground near the building. It is also found that raising the inclined terrain slope angle from 0 to 30°, results in an increase in the integrated temperature on the surface of the building. Furthermore, by raising the terrain slope from 0 to 30°, the integrated temperature on the ground for the mentioned cases increases by 16%, 10%, and 13%, respectively.

Towards a Generic Residential Building Model for Heat–Health Warning Systems

A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings. The thermophysiological load in the interior and exterior environments can be reduced in the medium and long term, through urban planning and building physics measures. In the short term, an increasingly vulnerable population must be effectively informed of an impending heat wave. Building simulation models can be favorably used to evaluate indoor heat stress. This study presents a generic simulation model, developed from monitoring data in urban multi-unit residential buildings during a summer period and using statistical methods. The model determines both the average room temperature and its deviations and, thus, consists of three sub-models: cool, average, and warm building types. The simulation model is based on the same mathematical algorithm, whereas each building type is described by a specific data set, concerning its building physical parameters and user behavior, respectively. The generic building model may be used in urban climate analyses with many individual buildings distributed across the city or in heat–health warning systems, with different building and user types distributed across a region. An urban climate analysis (with weather data from a database) may evaluate local differences in urban and indoor climate, whereas heat–health warning systems (driven by a weather forecast) obtain additional information on indoor heat stress and its expected deviations.