A Robust Approach For The Calibration of the Material Properties in an Existing Wall

Prada, Alessandro; Gasparella, Andrea; Baggio, Paolo

doi:10.26868/25222708.2019.210570

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…The wall properties were then optimized in order to reproduce the measured heat flow densities on both sides and the calibrated wall models were implemented in the baseline model of the building floor. At this stage, the calibration procedure based on the optimization of RMSE and a penalty function was followed [12], due to the availability of design documentation and material certificates. The penalty function (P) is calculated as the sum of the individual penalty functions of each j-th calibrated material property (v j ), by penalizing values that deviate too far from the value declared in the data sheets (IG j ).…”

Section: Automatic Calibration With Detailed Data Setmentioning

confidence: 99%

See 1 more Smart Citation

Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

et al. 2023

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Calibration of the existing building simulation model is key to correctly evaluating the energy savings that are achievable through retrofit. However, calibration is a non-standard phase where different approaches can possibly lead to different models. In this study, an existing residential building is simulated in parallel by four research groups with different dynamic simulation tools. Manual/automatic methodologies and basic/detailed measurement data sets are used. The calibration is followed by a validation on two evaluation periods. Monitoring data concerning the windows opening by the occupants are used to analyze the calibration outcomes. It is found that for a good calibration of a model of a well-insulated building, the absence of data regarding the users’ behavior is more critical than uncertainty on the envelope properties. The automatic approach is more effective in managing the model complexity and reaching a better performing calibration, as the RMSE relative to indoor temperature reaches 0.3 °C compared to 0.4–0.5 °C. Yet, a calibrated model’s performance is often poor outside the calibration period (RMSE increases up to 10.8 times), and thus, the validation is crucial to discriminate among multiple solutions and to refine them, by improving the users’ behavior modeling.

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Section: Automatic Calibration With Detailed Data Setmentioning

confidence: 99%

“…However, not all of them may be representative of the actual building behavior outside of the calibration period. Validation, namely testing the calibrated model predictions on a different period, is usually recommended, often leading to a refinement of the calibrated model [12].…”

Section: Introductionmentioning

confidence: 99%

Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

et al. 2023

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“…Other approaches use heat flux meter data to identify the local thermal transmittance or thermal resistance at the respective measurement spot [20,24]. Arregi et al compare a steady-state approach with a lumped resistance-capacitance that contains a single capacitor and a distributed capacitance model.…”

Section: Introductionmentioning

confidence: 99%

A Model Calibration Approach to U-Value Measurements with Thermography

Patel,

Estevam Schmiedt,

Röger

et al. 2023

Buildings

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The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like the thermal transmittance (U-value) or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

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A Model Calibration Approach to U-value Measurements with Thermography

Patel¹,

Schmiedt²,

Röger³

et al. 2023

Preprint

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The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like U-values or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

show abstract

A Robust Approach For The Calibration of the Material Properties in an Existing Wall

Cited by 3 publications

References 17 publications

Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

A Model Calibration Approach to U-Value Measurements with Thermography

A Model Calibration Approach to U-value Measurements with Thermography

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