Early Design Energy Analysis Using Building Information Modeling Technology

Stumpf, Annette L.; Kim, Hyun‐Joo; Jenicek, Elisabeth M.

doi:10.21236/ada552789

Cited by 10 publications

(14 citation statements)

References 4 publications

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“…For the operational GHG emissions, a dynamic simulation approach was selected. The simulation software package Green Building Studio (GBS) (Autodesk 2019) was used due to its relevance for the early design stage (Stumpf, Kim, & Jenicek 2011).…”

Section: Methods For Quantifying Life-cycle Ghg Emissionsmentioning

confidence: 99%

Integrating life-cycle GHG emissions into a building’s economic evaluation

Schmidt¹,

Crawford²,

Warren‐Myers

2020

Buildings and Cities

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Buildings contribute to greenhouse gas (GHG) emissions throughout their life-from material extraction and production to building demolition and disposal. Current GHG emission reduction efforts largely focus on building operation, typically ignoring embodied emissions. One of the main barriers affecting the uptake of embodied GHG emissions considerations is the uncertainty related to the economic value of a building with reduced life-cycle GHG emissions. A conceptual approach is presented for integrating the life-cycle GHG emissions of a building into an economic evaluation. A case study detached residential dwelling located in Melbourne, Australia, is used to demonstrate the approach using a range of economic valuation approaches. One approach, using a carbon tax, shows that the effective cost for a single household would be over A$2000 for the first year, rising to almost A$5000 in 10 years. Across the range of evaluation approaches considered, the total cost to the householder is found to be between A$4600 and A$7860. With the embodied GHG emissions accounting for over 66% of the case study's life-cycle GHG emissions, the majority of the economic liability for the householder relates to the initial construction and ongoing material replacement of the building. Policy relevance This research provides a comprehensive and integrated approach to GHG emissions and economic assessment of residential buildings. This could be used to drive better decisions in building construction and operation through policy improvement, generating greater understanding of the GHG emissions of buildings and the economic value of GHG emissions. By quantifying the total GHG emissions over a building's life-cycle and examining ecological and financial implications, new data can provide the basis for policy measures that transform the value of GHG emissions in property. The total life-cycle approach to GHG emissions can be used by developers or builders, for example, to demonstrate the potential financial implications of their choices. However, given its current format, there is a need to improve policy measures such as improved carbon tax strategies and the generation of an annual tax for the economic value implications to be realised.

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Section: Methods For Quantifying Life-cycle Ghg Emissionsmentioning

confidence: 99%

Integrating life-cycle GHG emissions into a building’s economic evaluation

Schmidt¹,

Crawford²,

Warren‐Myers

2020

Buildings and Cities

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“…1. The time saved from recreating the geometry could be better spent on alternative testing; therefore, value could be added to energy consulting (Moon, et al 2011, Stumpf, Kim andJenicek 2011). 3.…”

Section: The Benefits Of Bim-based Energy Analysismentioning

confidence: 99%

Investigating building information model to building energy model data transfer integrity and simulation results

Sun¹

2021

Preprint

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Traditional energy modeling methods are usually time-consuming and labour-intensive, so energy simulation is rarely performed early in building design. If a Building Energy Model (BEM) can be seamlessly generated from a Building Information Modeling (BIM) model, the energy simulation process can be much more efficient and better integrated in design. The concerns about BIM to BEM data transfer integrity and the reliability of simulation results are preventing wider adoption of BIM-based energy simulation. This study aimed to address these two obstacles and increase energy modelers’ confidence in using BIM for energy analysis. Green Building Studio (GBS) was used to simulate energy use and generate eQuest and EnergyPlus input files. Two building types were modeled in Revit with various iterations and BEM input files downloaded from GBS were compared line by line to identify and classify discrepancies. Simulation results from BIM-based and traditional modeling were compared to test reliability and showed unexpectedly good agreement across methods.

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“…Furthermore, there is ambiguity and uncertainty regarding the interoperability between BIM and BEM tools, as some critical information may be lost or misinterpreted during the process (Dong et al, 2007;Moon et al, 2011;Gourlis and Kovacic, 2017;Han et al, 2018;Solmaz, 2019). As emphasized by USGSA (2015), several BEM tools disregard construction and mechanical information, or lack the competence to verify the integrity of the model and completeness after being imported; these interoperability issues usually take place during certain phases of the process including, mapping data to the BIM file under certain file standards such as IFC or gbXML, mapping BIM data to a readable file for the BEM tool, and mapping data to the simulation engine (Kamel and Memari, 2019), which can lead to deceptive energy modeling results (Stumpf et al, 2011;Chen et al, 2018). Therefore, any attempt to standardize the data exchange process and its mechanism will significantly save time, reduce errors, and lead to overall process improvements (Hitchcock and Wong, 2011;Kamel and Memari, 2019).…”

Section: Review Of Interoperabilitymentioning

confidence: 99%

Building Information Modeling-Based Building Energy Modeling: Investigation of Interoperability and Simulation Results

Elnabawi

2020

Front. Built Environ.

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There is increasing need to apply building information modeling (BIM) to low energy buildings, this includes building energy modeling (BEM). If a building energy model can be flawlessly generated from a BIM model, the energy simulation process can be better integrated within the design, can be more competent, and timesaving. However, concerns about both the reliability and integrity of the data transfer process and the interoperability between the BIM and BEM prevent any implementation of BIM-based energy modeling on a large scale. This study addresses the accuracy and integrity of BIM-based energy modeling by investigating how well Autodesk's Revit (BIM), in conjunction with two of the most used energy modeling programs (BEM) known as DesignBuilder and Virtual Environment (IES-ve), were integrated in terms of interoperability, including location and weather files, geometry, construction and materials, thermal zones, occupancy operating schedules, and HVAC systems. All misrepresented data during the interoperability process were identified, followed by benchmarking between the BIM-based energy modeling simulation outcomes and the actual energy consumption of the case study, to assess the reliability of the process. The investigation has revealed a number of interoperability issues regarding the BIM data input and BEM data interpretation. Overall, BIM-based energy modeling proved to be a promising tool for sustainable and low energy building design, however, the BIM to BEM process is a non-standardized method of producing building energy models as it varies from one modeler to another, and the BIM to BEM process. All these might slow down any possible application for the process and might cause some uncertainties for the professionals in the field applying it.

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Early Design Energy Analysis Using Building Information Modeling Technology

Cited by 10 publications

References 4 publications

Integrating life-cycle GHG emissions into a building’s economic evaluation

Integrating life-cycle GHG emissions into a building’s economic evaluation

Investigating building information model to building energy model data transfer integrity and simulation results

Building Information Modeling-Based Building Energy Modeling: Investigation of Interoperability and Simulation Results

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