Exploring Existing 3d Reconstruction Tools for the Generation of 3d City Models at Various Lod From a Single Data Source

Abstract. The use of three-dimensional (3D) city models has increased in a wide range of applications beyond visualisation. However, generation and maintenance of 3D data comes at a high cost, time, and workload. The purpose of the generalisation where coarser versions are obtained from a source data is of great interest for National Mapping and Cadastral Agencies (NMCA), which would benefit obtaining multiple 3D versions of an area from a single source. The main aim of the exploration presented in this paper is to study the potential of downsizing point clouds as an approach to generate 3D city models at multiple levels of detail from a single source and evaluate the steps required to ensure the output is fit for real world applications from an NMCA context. While interesting results are obtained when testing with sample data, no software managed to semi-automatically reconstruct 3D model for buildings of rather complicated geometry

Impact of Climate Change on the Heating Demand of Buildings. A District Level Approach

There is no doubt that during recent years, the developing countries are in urgent demand of energy, which means the energy generation and the carbon emissions increase accumulatively. The 40 % of the global energy consumption per year comes from the building stock. Considering the predictions regarding future climate due to climate change, a good understanding on the energy use due to future climate is required. The aim of this study was to evaluate the impact of future weather in the heating demand and carbon emissions for a group of buildings at district level, focusing on two areas of London in the United Kingdom. The methodological approach involved the use of geospatial data for the case study areas, processed with Python programming language through Anaconda and Jupyter notebook, generation of an archetype dataset with energy performance data from TABULA typology and the use of Python console in QGIS to calculate the heating demand in the reference weather data, 2050 and 2100 in accordance with RCP 4.5 and RCP 8.5 scenarios. A validated model was used for the district level heating demand calculation. On the one hand, the results suggest that a mitigation of carbon emissions under the RCP4.5 scenario will generate a small decrease on the heating demand at district level, so slightly similar levels of heating generation must continue to be provided using sustainable alternatives. On the other hand, following the RCP 8.5 scenario of carbon emission carrying on business as usual will create a significant reduction of heating demand due to the rise on temperature but with the consequent overheating in summer, which will shift the energy generation problem. The results suggest that adaptation of the energy generation must start shifting to cope with higher temperatures and a different requirement of delivered energy from heating to cooling due to the effect of climate change

3D Generalisation of Building Components – An Initial Proof of Concept

A varied range of applications make use of 3D models nowadays, for instance in urban planning, energy demand studies, solar irradiation, or noise estimation. Acquisition, maintenance, and production of 3D spatial data is costly and laborious, especially at a national level, a great challenge for National Mapping and Cadastral Agencies (NMCAs) – such as Ordnance Survey (OS) for Great Britain. Generalisation is designed to address this challenge, where new datasets are created from a single source by the selection of the desired information and reduction of the amount of detail and data volume. Extensive literature exists in the context of 2D generalisation and automated algorithms exist to remove unwanted detail, however, adding a third dimension complicates the process significantly. Here, a methodology to address this issue is proposed, where the façades of a 3D building are decomposed, rotated, and translated from 3D environment to 2D. Existing automated 2D generalisation operators are applied to building elements and once generalised, they are rotated back to 3D. The outer shell of the resulting generalised 3D building is reconstructed with the independently generalised façade. The results demonstrate a potential flexible, component-based method for 3D generalisation, that could benefit NMCAs

Evaluating the Influence of Program Type Building Parameters on UBEM: A Case Study for the Residential Stock in Nottingham, UK

In the midst of rising concern about the implications of climate change, the European Union and the United Kingdom appears to be on the verge of establishing policies to reduce greenhouse gas emissions. The urban building energy models could inform energy analyzers and decision makers for the future results that specific comprehensive energy refurbishment strategies and energy supply infrastructure changes might have. Nonetheless, the data challenges that emerge are various. The lack of data availability and reliability, the data computing issue and data privacy are, only, some of the challenges of building energy modelling, which are intensified in urban scale. Therefore, the investigation of the influence of building parameters on the energy demand results is deemed necessary, in order both to understand the minimum data requirements for urban energy modelling, and the impact of them before the design phase for the new constructions. Therefore, this Paper’s intention is to inform stakeholders from energy analysts to data capture companies, about the influential building parameters, as regards to the Program Type, such as the infiltration, the domestic hot water and the ventilation. An UBEM physics-based approach, for the estimation of the annual energy demand, is implemented with the use of Grasshopper software, and the visualization of the results is done with the QGIS software. The case study is in Nottingham city, in UK, and the energy demand for the whole year of the dwelling stock is estimated. Then, a sensitivity analysis for the influence of the Program Type building parameters is presented. The results have shown that the most impactful parameter among the three under-tested is the infiltration (airtightness) of a dwellin

Assessing Urban Building Energy Demand in Future Climate Scenarios: A Case Study in Nottingham,UK

The most recent report on climate change from the IPCC (Intergovernmental Panel on Climate Change), in 2023, states that urgent action is needed to tackle global warming. The IPCC points out that by 2040, there is a greater than 50% risk that the temperature worldwide will approach or exceed 1.5 degrees Celsius (2.7 degrees Fahrenheit). On top of that, under high-emissions scenarios, the global temperature could increase to that borderline even earlier, before 2037. Since building stock accounts for 40% of total global energy usage and 33% of greenhouse gas emissions each year, their continuous high demand for energy leads to the rapid growth of CO2 emissions. Accounting for that, the energy performance of buildings in urban scale under the future climate scenarios is a significant factor in immediately assisting with climate change mitigation. The purpose of this project was to estimate the influence of the climate change on the energy demand of two neighbourhoods in Nottingham, in United Kingdom, by comparing their current energy performance to the future. The methodology consists of the use of geospatial data for the building geometric parameters, in combination with energy-related data from the EPC (Energy Performance Certificate) dataset. The datasets were processed with Python programming language and the QGIS software, and the final dataset was imported to an energy model that was constructed with the use of Rhino and Grasshopper, with EnergyPlus simulations on the background. The model was run under 9 different climate scenarios, namely under the present, under 2050s and 2080s for 4 different future scenarios each year. The results have shown that the absence of building stock renovation will lead to an accountable decrease in the heating demand of buildings, while the risk of overheating will be critically escalating. </em

Impact of Terrain on Urban Building Energy Modelling: A Case Study in Nottingham, UK<strong> </strong>

More than 2/5 of world annual energy use comes from residential buildings, of which 97% of them are characterized as energy in-efficient. This means that the refurbishment rate of the housing stock should be increased, making Urban Building Energy Modelling essential for the rapid assessment of energy efficient measures. Nevertheless, due to data challenges, the investigation of the influential parameters on UBEM is needed. While previous research papers focused on wind patterns formed from the terrain surface, a research gap exists in understanding how the terrain surface, affects building energy demand. Therefore, the aim of this research was to estimate the effect of the terrain on Urban Building Energy Modelling. A physics-based bottom-up approach was applied in two neighbourhoods in Nottingham, UK. The results show that the terrain surface is a significant factor for Urban Building Energy modelling, as there is 3% energy demand difference when buildings are projected on the actual location, but the addition as shadow surrounding could be avoided due to the computational time and data storage issues

Characterization of rheological properties of rye arabinoxylans in buckwheat model systems

The aim of this investigation was to study the rheological properties (gelation profile, mixing and pastingproperties) of two rye arabinoxylans (AXs) (water-extracted (WEAXs), calcium hydroxide-extracted (CEAXs)) in buckwheat model systems using wholemeal and white flour. To promote gelation in these systems, pyranose 2-oxidase (POx) was added. AX characterization in solution showed a higher gelation profile for the CEAXs (G\u2019: 0.48 Pa, G\u2019\u2019: 0.25 Pa) compared with the WEAXs (G\u2019: 0.21 Pa, G\u2019\u2019: 0.14 Pa), probably due to differences in chemical and structural properties. In buckwheat batter systems, highest rheological properties were achieved when POx was added to the control flours (for wholemeal flour: G\u2019: 40.1 kPa, G\u2019\u2019: 8.6 kPa; for white flour: G\u2019: 18.7 kPa, G\u2019\u2019: 1.4 kPa), whereas most AX concentrations improved these properties to a lower degree. Nearly all wholemeal flour systems reached higher viscoelastic properties when containing CEAXs (G\u2019: 20.0e35.1 kPa; G\u2019\u2019: 4.2e6.7 kPa), while WEAXs improved the majority of these properties in systems made with white flour (G\u2019: 10.4e12.7 kPa; G\u2019\u2019: 2.2-2.3 kPa). No additional effect was seen in the batter viscoelasticity when POx was combined with these AXs. Pasting and mixing properties of the flour systems were mostly reduced by the addition of AXs, while the presence of POx displayed little or no further effect. These observations indicate that AXs could be applied as natural structure-forming agents in GF bread, when used in the right amount