Roof Of Building Research Articles

Housing and social sustainability in Uganda; case of Pagirinya Refugee Settlement in Adjumani district

Purpose This paper aims to respond to the need for “socially sustainable settlements for all” and the need for successful integration within the settlements through building strong social constructs among the settlers. Design/methodology/approach Mixed methods were used in this study. A sample size of 332 households in Pagirinya Refugee Settlement was used. The settlement is divided into six blocks, each block is subdivided into clusters. Each cluster comprises of 100 households. Due to variations in the number of households in each settlement block, the authors used a proportional sampling approach to determine the number of respondent households in each settlement block. Data was collected through questionnaires, interviews and focus group discussions. Chi-square and an interdependent multivariate statistical analysis were performed to establish the relationship between housing and social sustainability. Findings The study finds a significant relationship between housing and social sustainability when considered jointly on the variables of roofs of buildings and how often the refugee respondents meet with neighbours (p = 0.018) and when considered jointly on the variables of the width of access roads and how knowledgeable the refugee respondents are about their neighbours (p = 0.018). The study also finds a significant relationship between housing and social sustainability when considered jointly on the variables of the number of direct access roads to the households and the number of friends of the refugee respondents (p = 0.019). Originality/value With limited literature, this is a novel approach. To the best of the authors’ knowledge, no previous studies focused on the specifics of a building and analysed its relationship with the social dynamics, especially in settlement studies.

A Novel Deep Learning Based Classification of Building Roof Types Using Point Cloud Data

A Novel Deep Learning Based Classification of Building Roof Types Using Point Cloud Data

City-wide Solar Radiation Potential Analysis by Coupling Physical Modelling and Machine Learning

Abstract. Addressing the challenges posed by climate change and meeting urban energy demands is of utmost importance in today's world. Building Integrated Photovoltaics (BIPV) emerges as a crucial solution for energy conservation and carbon emissions reduction in urban environments. However, traditional methods of assessing solar radiation on buildings using physical models are often computationally intensive and time-consuming. This paper introduces a novel hybrid approach that integrates physical model-based solar radiation calculation with machine learning techniques to analyze Solar Radiation Potential (SRP) across city-wide building infrastructure. The proposed approach precisely evaluates the SRP of representative blocks by leveraging computing-intensive physical models integrated with 3D building data. Subsequently, two machine learning models are developed to effectively predict the SRP of building roofs and facades across the entire city. To validate the efficacy of this approach, an experiment was conducted in Shenzhen, China, yielding insightful results. The findings reveal that Shenzhen has a huge potential for BIPV solar power generation, with mean annual total building roof and facade solar radiation values of 9.22*107 kwh and 2.47*108 kwh, respectively. It can be further observed that relying solely on rooftop installations is insufficient to meet electricity demand. This study not only provides an innovative alternative for city-wide SRP estimation by combining physical modeling and machine learning but also offers valuable insights for fostering low-carbon urban environments and informing data-driven and model-driven urban planning and management strategies.

Possibility of Substitution of LOD1 Data for LOD2 Data on Photovoltaic Potential Estimation at City Districts Level Using a 3D City Model

Abstract. We developed a system to estimate the photovoltaic (PV) potential of urban buildings using a 3D city model at level of detail 2 (LOD2), considering an arrangement of solar panels. Although the PV potential estimation of buildings at the level of city districts prefers LOD2 data, many urban city districts with buildings capable of installing solar panels on façades do not have LOD2 data owing to the high production cost of LOD2 data. Therefore, we investigated the possibility of utilising LOD1 data instead of LOD2 data in the PV potential estimation of buildings at the level of city districts. We conducted an experiment in the investigation using 3D city model data from 24 city districts, which are most of the large cities with LOD2 data in Japan. The experiment results suggest that LOD1 would not be a substitute for LOD2 data in the PV potential estimation of building roofs. The cause of the inadaptability is that most roofs in LOD2 buildings have more small polygons than LOD1 building roofs. Roofs of a LOD2 building with many small polygons have fewer solar panels than roofs of a LOD1 building with a large polygon. On the contrary, the experiment results indicate that LOD1 may be a substitute directly for LOD2 in the PV potential estimation of building façades that are expected to be used as a mounting platform for solar panels in urban buildings from now on. The average of the relative differences in the calculated PV potential of building façades between using LOD1 data and using LOD2 data is approximately 10% in the experiment.

Measurement and prediction of vertical temperature distribution above urban building roofs at an ultra-microenvironment scale

Microenvironment is critical for building thermal performance. Heat transfer through building envelope (such as roof and window) and mass transfer through building mechanical systems that are adjacent to building surfaces (such as roof-top unit) are influenced directly by the air conditions near the surfaces (e.g., within 1.5 m). These air environments are within the sublayer of the air thermal boundary layer around the buildings – here defined as ultra-microenvironments, to be distinct from the conventional microenvironment scale of 2–5 m from building surfaces. This study particularly investigates the vertical temperature profiles within the ultra-microenvironments above urban building roofs. Field tests were conducted on two roof tops in Wuhan, China and Boulder, US, respectively. Consistent vertical air temperature profiles above the roofs were observed for both days and nights. The study further identifies one recent above-roof air temperature model and validates it with the field test data, which can effectively predict the vertical air temperature at various heights within the ultra-microenvironment above the roof. Applications of this model using different local and climate data including weather station data are analyzed and discussed, along with their performance on prediction accuracy.

Application on ac station service system for gathering station based on roof photovoltaic system

Abstract With the increasingly severe global energy crisis and environmental pollution, it is imperative to develop and utilize clean and renewable energy. In order to achieve carbon peak and carbon neutrality as soon as possible, and reduce the proportion of fossil energy generation, decarbonization in the power industry is imperative. This article focuses on the design of rooftop photovoltaic systems at gathering stations. By installing solar photovoltaic panels on the roof of the gathering station building, a photovoltaic power generation system is constructed to convert solar energy radiated into electricity. The DC power generated by the solar photovoltaic power generation system is converted by an inverter and connected to the 380V bus of the station power system as a supplementary power supply for the station load, thereby increasing the proportion of green electricity consumption in the collection station and achieving the goal of carbon reduction

Effect of Cool Roof Paint Application on Metal Roof Surface Temperature and Indoor Air Temperature in Tropical Climates

Abstract Increasingly hot environmental temperatures and less comfortable indoor temperatures are the impacts of inappropriate choices of building roof materials. An effort to mitigate this problem is by using a cool roof. This study was conducted through a field experiment by applying cool roof paint to the metal roof of a building in Malang, Indonesia. Field measurement results show that the cool roof paint application can reduce the maximum surface temperature above the metal roof by up to 6.6ºC and under the metal roof by up to 6.3ºC, as well as the maximum indoor air temperature by up to 0.8ºC at a height of 120 cm above the floor and up to 1.2º C at a height of 50 cm below the metal roof.

Perencanaan Pembangkit Listrik Tenaga Surya (PLTS) Sistem Hybrid Pada Jaringan Kelistrikan Di Rumah Sakit Umum Yarsi Pontianak

Electrical energy is very important in everyday life to support the activities of various sectors. Fossil fuels as an energy source are a top priority, therefore renewable energy is an alternative to replace the limitations of fossil fuels which is the main priority in efforts to generate electrical energy in Indonesia. The high intensity of sunlight in Indonesia, especially in Pontianak City, is very suitable for building a Solar Power Plant (PLTS). The aim of this research is to find out how much potential PLTS has using applications PVsyst 7.3by utilizing the roof of the hospital building. This research uses three methods for economic analysis and analyzing the feasibility of PLTS. The method used isNet Present Value (NPV), Profitability Index (PI), and Discounted Payback Period (DPP). The results of research carried out using Software PVsyst 7.3 It was found that the PLTS system was installed on the roof of YARSI Pontianak General Hospital with a slope angle of 4O namely 115 kWp with the type of solar panel used being the Jinko Solar Tiger Neo N-type 72HL4-BDV 580Wp 198 units, 3 inverters of the SUN2000-30/36/40KTL-M3 type with a capacity of 40 kW, and batteries with type Sunlight RES OPzS with a capacity of 3060 Ah. Based on the results of calculations that have been carried out, the initial investment required is IDR. 1,578,472,422. Analysis of the economic feasibility of PLTS using 3 methods has been carried out to obtain an NPV value of Rp. 797.610.941,86, PI value of 1.505, and DPP value of 14 years. The three methods used in this research show that PLTS is feasible.

SELECTION OF OPTIMAL SOLAR PANEL ORIENTATION PARAMETERS

The article investigates the issue of optimising the installation parameters of solar panels to maximise their efficiency in the conditions of modern Ukraine, where the traditional energy infrastructure is severely damaged due to military operations. Particular attention is paid to parameters such as the angle of inclination and orientation of solar panels relative to the sun, which affect the overall performance of the system. The study was carried out on the basis of a solar power plant located on the roof of the educational building of the Ukrainian State University of Science and Technology in Dnipro. A detailed analysis of the plant's operation was carried out with the solar arrays oriented to the southwest (azimuth 222˚) and the results were compared with the calculations obtained using the PVWatts® calculator developed by the US National Energy Laboratory (NREL). The results of the study showed that the actual annual electricity generation was 3917 kWh, which is close to the predicted 3973 kWh obtained using PVWatts®. The analysis also demonstrated that changing the orientation of the solar panels from southwest to south (180˚ azimuth) could increase the annual electricity generation to 4227 kWh, which confirms the maximum efficiency of the southern orientation. The findings can be used to optimise existing and future solar power plant projects, ensuring more efficient use of resources and improving the overall efficiency of power systems. This knowledge will help to reduce dependence on fossil energy sources, reduce greenhouse gas emissions and ensure uninterrupted electricity supply for the population and critical facilities in the face of the destruction of traditional energy infrastructure.

The Role of Solar Photovoltaic Roofs in Energy-Saving Buildings: Research Progress and Future Development Trends

The Role of Solar Photovoltaic Roofs in Energy-Saving Buildings: Research Progress and Future Development Trends

Review of the Benefits of Green Roofs

Green roofs installed on rooftop of buildings in urban communities have multiple environmental, economic, energy and social benefits. They promote the urban sustainability and the well-being of the local residents. The impact of green roofs in buildings, in the environment and in local communities have been studied. Green roofs remove atmospheric pollutants including carbon dioxide, release oxygen, mitigate the urban heat island effect, reduce the energy consumption in buildings, improve the rainwater management, promote urban agriculture, enhance urban green spaces and bring nature closer to local residents. The development of green roofs results in many benefits in the buildings that have been constructed as well as in the broader community. Their construction is financially subsidized in several countries due to their multiple external benefits. In the era of climate change and of sustainable development construction of green roofs in urban environments has multiple positive impacts. Therefore, local and municipal authorities should promote their construction in public and private buildings. The current work emphasizes the benefits of green roofs and it could be useful to policy makers, to public and municipal authorities as well as to architects, construction companies and buildings’ owners who should promote their development in urban communities.

Gastropods on the green roof of a high-rise building in a large European city

Understanding the distribution and diversity of terrestrial snails on green roofs (GR) can facilitate insights into the ecological functioning of these urban habitats. While green roofs have been shown to provide suitable habitat for mobile species such as birds and insects, there needs to be more research concerning the colonisation and persistence of less mobile animal groups, including terrestrial gastropods. The present study investigates the species richness of terrestrial gastropods on green roofs of high-rise buildings in Bratislava, Slovakia. The study examined four distinct types of green roofs: The green roofs were classified according to their management intensity, resulting in four categories: extensive, semi-intensive GR-A, semi-intensive GR-B, and intensive. The categories differed in terms of vegetation, substrate depth, irrigation, and sun exposure. The survey employed a variety of methods, including pitfall trapping, vegetation sweeping, soil sampling, and microhabitat investigations. The survey yielded evidence of 11 species of terrestrial gastropods (six snails and five slugs) inhabiting three GR types. The semi-intensive GR-A, which is characterised by dense vegetation and minimal management, supported all 11 species. No gastropods were observed on the extensive GR with shallow substrate and Sedum sp. vegetation. The presence of native and non-native species, including the non-native slug Ambigolimax valentianus, indicates that terrestrial gastropods can colonise GR. These findings emphasise the potential of GR to support urban biodiversity and highlight the need for further research on less mobile species in these habitats.

Requirements for partial turbulence simulations using nondimensional turbulence energy contributions

Quantifying turbulence effects is crucial for understanding building aerodynamics and for ensuring accurate wind tunnel test methods. This is especially important in wind tunnel methods that require post-experiment adjustments because approximate wind fields are used, such as the Partial Turbulence Simulation (PTS) approach. Understanding and analyzing these effects enables load adjustments since the PTS method only requires matching the high frequency portions of the upstream spectra of the longitudinal velocity component in model and full-scale. However, the limits for which the PTS method is applicable are unclear in terms of the allowable range of wind field characteristics that can be used in the wind tunnel simulation. To address this, the paper utilizes two nondimensional parameters, one representing the small-scale turbulence energy, ES, and the other the large-scale turbulence energy, EL, to elaborate the aerodynamic effects of turbulence intensity and integral length scales in the upstream wind. The results show that the maximum allowable mismatch ratio of integral length scales and of Jensen numbers between model and full-scale simulations depend on the target small-scale turbulence energy and the maximum allowable deviation of small-scale energy. By quantifying the effects of ES and EL on area-averaged pressure coefficients, the allowable limits are identified for wind tunnel test parameters that lead to negligible differences in the resultant pressure coefficient statistics in regions of separated-reattaching flow on the roof of a low-rise building.

Microclimate Effect on Cooling Energy for Buildings in Hot, Humid Climates: A Comparative Analysis of Shaded and Unshaded Environments

This paper explores the influence of microclimates on changes in air temperature and the often-overlooked aspect of their effect on energy savings across varying microclimatic conditions. The study compares the cooling energy requirements of two identical single-story buildings in distinct microclimates: one characterized by concrete ground devoid of shade and the other featuring soil ground with tree shade. Climatic environmental data were collected over 15 days in the concrete-exposed field and shaded area beneath the trees to conduct the investigation. These datasets were input into EnergyPlus 9.6 to model the energy demands and consumption of buildings subject to the specified climatic conditions. The validation of the simulated model against actual energy demand data from a classroom building demonstrated agreement. The findings reveal notable differences in air temperature, with the shaded area experiencing temperatures 0.8°C to 8.0°C lower than the concrete-exposed monitoring location. The building in the tree-shaded microclimate exhibited a lower peak cooling load than its concrete-exposed counterpart, resulting in a 35% reduction in the electrical energy requirements for the air-conditioning system. The study recommends implementing 0.08-m polyurethane insulation for the building walls and roof to equalize the energy demand and consumption of the concrete-exposed building with that of its shaded counterpart. Furthermore, building design in shaded areas can maximize the window glass area while consuming less energy than buildings on concrete-exposed grounds. The study advocates leveraging the microclimate associated with surrounding buildings in the design process to enhance the overall energy savings.

Flow characteristics over flat building roof with different edge configurations for wind energy harvesting: A wind tunnel study

The impact of climate change and global warming makes it imperative to seek sustainable solutions for the built environment. To facilitate the design of future sustainable buildings, wind tunnel tests are conducted in this study to investigate the flow characteristics and wind energy potential over a flat building roof with different edge configurations. Specifically, this study addresses the effect of parapet walls and roof edge-mounted solar panels on the wind flow over a flat-roof tall building. The results show that parapet walls generally slow down the wind speed and increase turbulence intensity as well as skewness angle, which compromises the efficiency of traditional turbine-based wind energy harvesting. On the other hand, the presence of solar panels on the roof edge (or on the top of the parapet wall) further alters flow separation and has the potential to enhance wind energy harvesting over the roof, especially for the solar panel inclined at 30°. In addition to providing valuable data for validating computational fluid dynamics (CFD) simulations, this study could also help to guide the design of wind energy harvesting devices on the building roof and explore the promising synergy with solar panels.

An Integrated Method Using a Convolutional Autoencoder, Thresholding Techniques, and a Residual Network for Anomaly Detection on Heritage Roof Surfaces

The roofs of heritage buildings are subject to long-term degradation, resulting in poor heat insulation, heat regulation, and water leakage prevention. Researchers have predominantly employed feature-based traditional machine learning methods or individual deep learning techniques for the detection of natural deterioration and human-made damage on the surfaces of heritage building roofs for preservation. Despite their success, balancing accuracy, efficiency, timeliness, and cost remains a challenge, hindering practical application. The paper proposes an integrated method that employs a convolutional autoencoder, thresholding techniques, and a residual network to automatically detect anomalies on heritage roof surfaces. Firstly, unmanned aerial vehicles (UAVs) were employed to collect the image data of the heritage building roofs. Subsequently, an artificial intelligence (AI)-based system was developed to detect, extract, and classify anomalies on heritage roof surfaces by integrating a convolutional autoencoder, threshold techniques, and residual networks (ResNets). A heritage building project was selected as a case study. The experiments demonstrate that the proposed approach improved the detection accuracy and efficiency when compared with a single detection method. The proposed method addresses certain limitations of existing approaches, especially the reliance on extensive data labeling. It is anticipated that this approach will provide a basis for the formulation of repair schemes and timely maintenance for preventive conservation, enhancing the actual benefits of heritage building restoration.

Efficient analysis and evaluation method for overall lifting of large-span spatial grid structures

Large-span spatial grid structures are commonly employed on the roofs of various public buildings and are typically installed via an overall lifting method. However, the process of overall lifting cannot ensure complete synchronization, which may result in damage to the structure or the lifting equipment. It is imperative to ascertain the limit state of the structure under asynchronous conditions and to develop an accurate model for rapidly assessing the critical response during the lifting process. This paper introduces an efficient approach for evaluating and analyzing the overall lifting process of large-span spatial grid structures. The iterative limit boundary (ILB) method is proposed in this paper, which facilitates the rapid determination of the limit boundary and the limit state for a structure-equipment system with asynchronous lifting. Furthermore, the genetic algorithm is integrated into the ILB method to enhance its efficiency when dealing with numerous lifting points. An agent model capable of outputting key structural responses is developed for the rapid evaluation of those responses throughout the lifting process. Both a numerical example and an engineering example are provided to validate the proposed method. The computational results indicate that the method proposed achieves accurate results with a computational cost merely 3 % of that of the Monte Carlo simulation. Additionally, the agent model established within the limit boundary, operates at a speed 200 times faster than finite element analysis, thereby enabling precise and real-time critical response assessments.

Data-driven prediction of wind pressure on low-rise buildings in complex heterogeneous terrains

This study presents a data-driven methodology for predicting the pressure coefficient statistics on the windward wall, roof, and leeward wall of low-rise buildings situated downwind of complex heterogeneous terrains. Two types of artificial neural network models were developed: the empirical parameter-based ANN (PANN) and the morphology-based ANN (MANN). Pressure data from wind tunnel tests on the Wind Engineering Research Field Laboratory (WERFL) building model (building height H = 4 m) in complex heterogeneous terrain were used to develop the ANN models. These models were evaluated against a non-linear fitted model to assess their predictive performances. PANN and MANN demonstrated superior performance in capturing the effects of terrain complexity on the mean (Cp,mean) and the root-mean-square (Cp,RMS) wind pressure coefficients for the windward wall, roof, and leeward wall. Optimal prediction was achieved with a terrain patch size of W × L = 4 × 2, equating to a full-scale area of approximately 72 m × 23 m. This suggests that the morphology within approximately 100 m × 50 m (25H× 12.5H) in front of a low-rise building has the greatest correlation with the wind pressure coefficient. Despite lower R2 values for max Cp,RMS on the leeward wall across all models, both PANN and MANN showed promising accuracy for the six outputs studied. Moreover, a global sensitivity analysis confirmed the impact of terrain roughness and complexity on the prediction models particularly on max Cp,RMS, and underscored the dominance of effective roughness length z0,eff and the coefficient of variation of roughness length COVz0 in influencing model outcomes.

Characterization of tornado-induced wind pressures on a multi-span light steel industrial building

This study presents the characteristics of external wind pressures of a multi-span light steel industrial building through wind pressure measurements conducted in a tornado simulator. The test model is designed as a three-span low-rise building with gable roofs according to the practical measured sizes and shapes of the light steel industrial building destroyed in the Shengze tornado, China (2021). The distance from the tornado-like vortex center to the building, building orientation, roof angle, and swirl ratio are considered as experimental parameters. The effects of the parameters on the most unfavorable peak and mean pressure coefficients of each surface are analyzed. The roof zoning specified in ASCE 7–16 was re-analyzed based on the characteristics of wind pressure coefficients, and the tornado design pressure coefficients were calculated. The results of the analysis illustrate that the wind-ward roof surface at a distance of around one vortex core radius from the center experience the most severe pressure coefficient under tornado, the most unfavorable zone of the pressure coefficients on the building roof changes with the building orientation, the model with a smaller roof angle has smoother pressure coefficient contours than that with a larger roof angle because of the cutting effect of the ridge, and the simulated tornado with the lower swirl ratio generate higher external pressure coefficients on the building model. Moreover, the roof zoning in ASCE 7–16 for the boundary layer wind is not precise for tornado, thus an updated roof zoning for the tornado design pressure coefficients is defined.

Automated generation and semantic segmentation of roof orthophoto for digital twin -based monitoring of slated roofs

Roofs are one of the building elements most exposed to environment-induced deterioration, and their deterioration can rapidly result in potential safety hazards to occupants or even buildings’ failure. In pursuit of cost-effective, efficient and pro-active building roof monitoring, this paper presents a computing pipeline for: 1. Automated roof orthophoto generation that uses as input the 3D reconstruction from structure-from-motion photogrammetry and the building’s Digital Twin (DT) model, and outputs occlusion-free panel orthophotos with metric resolution. 2. Automated orthophoto semantic segmentation using deep learning to extract visible roof sub-components from the orthophotos. Various segmentation models are tested and contrasted. The approaches are validated with three real case studies of traditional buildings with slated pitched roofs. The proposed approach employs a generic pipeline which could be applied to any element of the building fabric.