A framework for producing gbXML building geometry from Point Clouds for accurate and efficient Building Energy Modelling

The industrial sector accounts for 17% of end-use energy in the United Kingdom, and 54% globally. Therefore, there is substantial scope to accurately simulate and efficiently assess potential energy retrofit options for industrial buildings to lower end use energy. Due to potentially years of facility renovation and expansion Building Energy Modelling, also called Building Energy Simulation, applied to industrial buildings poses a complex challenge; but it is an important opportunity for reducing global energy demand especially considering the increase of readily available computational power compared with a few years ago. Large and complex industrial buildings make modelling existing geometry for Building Energy Modelling difficult and time consuming which impacts analysis workflow and assessment options available within reasonable budgets. This research presents a potential framework for quickly capturing and processing as-built geometry of a factory, or other large scale buildings, to be utilised in Building Energy Modelling by storing the geometry in a green building eXtensible Mark-up Language (gbXML) format, which is compatible with most commercially available Building Energy Modelling tools. Laser scans were captured from the interior of an industrial facility to produce a Point Cloud. The existing capabilities of a Point Cloud processing software and previous research were assessed to identify the potential development opportunities to automate the conversion of Point Clouds to building geometry for Building Energy Modelling applications. This led to the novel identification of a framework for storing the building geometry in the gbXML format and plans for verification of a future Point Cloud processing solution. This resulted in a sample Point Cloud, of a portion of a building, being converted into a gbXML model that met the validation requirements of the gbXML definition schema. In conclusion, an opportunity exists for increasing the speed of 3D geometry creation of existing industrial buildings for application in BEM and subsequent thermal simulation

Geometry Extraction for High Resolution Building Energy Modelling Applications from Point Cloud Data: A Case Study of a Factory Facility

The industrial sector accounts for 17% of end-use energy in the UK, and 54% globally. Therefore, there is substantial scope for simulating and assessing potential energy retrofit options for industrial buildings. Building Energy Modelling (BEM) applied to industrial buildings p oses a complex but important opportunity for reducing global energy demand, due to years of renovation and expansion. Large and complex industrial buildings make modelling existing geometry for BEM difficult and time consuming. This paper presents a potential solution for quickly capturing and processing as-built geometry of a factory to be utilized in BEM. Laser scans were captured from the interior of an industrial facility to produce a Point Cloud. The existing capabilities of a Point Cloud processing software were assessed to identify the potential development opportunities to automate the conversion of Point Clouds to building geometry for BEM applications. In conclusion, scope exists for increasing the speed of 3D geometry creation of an existing industrial building for application in BEM and subsequent thermal simulation

A review of energy simulation tools for the manufacturing sector

Manufacturing is a competitive global market and efforts to mitigate climate change are at the forefront of public perception. Current trends in manufacturing aim to reduce costs and increase sustainability without negatively affecting the yield of finished products, thus maintaining or improving profits. Effective use of energy within a manufacturing environment can help in this regard by lowering overhead costs. Significant benefit can be gained by utilising simulations in order to predict energy demand allowing companies to make effective retrofit decisions based on energy as well as other metrics such as resource use, throughput and overhead costs. Traditionally, Building Energy Modelling (BEM) and Manufacturing Process Simulation (MPS) have been used extensively in their respective fields but they remain separate and segregated which limits the simulation window used to identify energy improvements. This review details modelling approaches and the simulation tools that have been used, or are available, in an attempt to combine BEM and MPS, or elements from each, into a holistic approach. Such an approach would be able to simulate the interdependencies of multiple layers contained within a factory from production machines, process lines and Technical Building Services (TBS) to the building shell. Thus achieving a greater perspective for identifying energy improvement measures across the entire operating spectrum and multiple, if not all, manufacturing industries. In doing so the challenges associated with incorporating BEM in manufacturing simulation are highlighted as well as gaps within the research for exploitation through future research. This paper identified requirements for the development of a holistic energy simulation tool for use in a manufacturing facility, that is capable of simulating interdependencies between different building layers and systems, and a rapid method of 3D building geometry generation from site data or existing BIM in an appropriate format for energy simulations of existing factory buildings

The effect of age of the sward on the relationship between water-soluble carbohydrate accumulation and drought survival in two contrasted populations of cocksfoot (Dactylis glomerata L.)

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