Remote Sensing For Building Energy Simulation Input – A Field Trial

Gorzalka, Philip; Schmiedt, Jacob Estevam; Göttsche, Joachim; Hoffschmidt, Bernhard; Linkiewicz, Magdalena; Patel, Dhruvkumar; Plattner, Stefan; Schorn, Christian; Frommholz, Dirk

doi:10.26868/25222708.2019.210186

Cited by 4 publications

(3 citation statements)

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“…As a result, window detection failed for several facades and delivered visibly erroneous results for others. However, it has been shown that image-based detection can work well if high-resolution textures are available [44,45].…”

Section: Window Areamentioning

confidence: 99%

Calculating urban heat demands: An analysis of two modelling approaches and remote sensing for input data and validation

Dochev

Gorzalka

Weiler

et al. 2020

Energy and Buildings

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Section: Window Areamentioning

confidence: 99%

Calculating urban heat demands: An analysis of two modelling approaches and remote sensing for input data and validation

Dochev

Gorzalka

Weiler

et al. 2020

Energy and Buildings

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“…With the point cloud (visualised in Figure 2) as input, the method of Frommholz et al [29] delivered a textured 3D polygonal model of the building envelope. Windows were recognised on the textures using a colour-based approach [39]. CityGML was chosen as the data exchange format due to its comprehensible structure combining semantic and positional data and because it was designed to be created from measurements, which makes it more suitable for surface-based modelling tasks than the BIM formats usually created during a building design phase [40].…”

Section: Data Collectionmentioning

confidence: 99%

Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery

et al. 2021

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An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment.

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“…In the second part, similar measurements have been performed in a real office building to investigate this method's applicability in field testing (Section 3). This work is part of ongoing research activities to make remote sensing techniques applicable to thermal 4 energy analyses in buildings [37,38]. The overall goal is to develop a toolbox of measurement and analysis methods to determine the thermal properties of building envelopes quickly and accurately.…”

Section: Introductionmentioning

confidence: 99%

Quantification of air leakage paths: a comparison of airflow and acoustic measurements

Kölsch

Walker

Schiricke

et al. 2021

International Journal of Ventilation

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Today, the fan pressurization method is the most frequently used method to evaluate a buildings' airtightness. However, the localization and quantification of leaks remain difficult. In this paper, an acoustic method is introduced to estimate the leakage size of single leaks.Acoustic and airflow measurements were conducted and compared in laboratory tests within the same boundary conditions. This work aims to investigate if various leak sizes can be predicted using acoustic measurement methods. The test apparatus consists of two chambers, separated by a test wall. This wall represents a single characteristic air leakage path. Various types of wall structures with different slit geometries, wall thicknesses, and insulation materials were investigated. The acoustic measurements were performed with a sound source placed in one chamber and ultrasonic microphones located in both chambers. These results were compared to measured airflows through the test wall to provide estimates of uncertainty in the acoustic approach, which indicate a linear trend. Finally, these laboratory measurements were compared to the same measurements at a real office building. Although the acoustic measurement uncertainty is still significant (greater than +/-50 %), the acoustic method has the potential to give an order of magnitude of single leak sizes.

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Remote Sensing For Building Energy Simulation Input – A Field Trial

Cited by 4 publications

References 0 publications

Calculating urban heat demands: An analysis of two modelling approaches and remote sensing for input data and validation

Calculating urban heat demands: An analysis of two modelling approaches and remote sensing for input data and validation

Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery

Quantification of air leakage paths: a comparison of airflow and acoustic measurements

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