Characterization of an airflow network model by sensitivity analysis: parameter screening, fixing, prioritizing and mapping

Monari, Filippo; Strachan, Paul

doi:10.1080/19401493.2015.1110621

Cited by 22 publications

(11 citation statements)

References 41 publications

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“…18,19 This approach, however, can give much more accurate results only when the building model and flow network are defined correctly. 20 Therefore, as has also been stated in Prignon and Van Moeseke, 21 further research should focus on the development of a new model of air leakage prediction based on detailed leak data from the inventory.…”

Section: Introductionmentioning

confidence: 91%

“…In order to perform a numerical leak test, a computer model of the building must be developed. 20 The network method consists of the spatial description of a building divided into zones, along with the determination of interactions between zones. In this method, network nodes represent a set of parameters of a given volume (zone).…”

Section: Modelling Of Airflow Through Leaksmentioning

confidence: 99%

“…External environment parameters are defined through external nodes. 20 During the simulation of the building air-tightness test, the pressure value inside and outside the building is constant and known. Each node in the network has a reference height assigned to the reference level specified once for a given model.…”

Section: Modelling Of Airflow Through Leaksmentioning

confidence: 99%

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Modelling building infiltration using the airflow network model approach calibrated by air-tightness test results and leak detection

Heim

Miszczuk

2020

Building Services Engineering Research and Technology

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This paper presents a computational approach to air infiltration modelling and simulation validated by the blower door test results. In order to evaluate the potential of the airflow network method, three simulation models of the infiltration test were developed and calibrated by field measurements of leaked air change rate per hour at 50 Pa. Models were developed for existing building designs and constructed in low-energy standards differing in construction type and tightness. All leaks were precisely measured during field tests, defined as openings or cracks, numerically described and included in the model. The simulation results of calibrated models for other pressure differences revealed that the models’ accuracy is satisfactory. The differences between field tests and simulation results do not exceed 2.5%. Additionally, the calibrated models were used to estimate the infiltration heat losses of buildings in three different locations under continental climatic conditions. The results were compared with the steady-state method calculations made for the same building models and climatic conditions. It was proved that the steady-state method gives higher results of heat demand to cover infiltration losses than the simulation method. The final results depend on building location and vary between four and nine times. Practical application: The computational modelling and building performance simulations are increasingly commonly used in engineering design. The proposed method of air-tightness modelling and calibration can be used at any phase of a building’s lifecycle, from design and construction to exploitation and maintenance. Using the proposed techniques, it is possible to estimate more realistic processes of air infiltration and its effect on a building’s energy consumption in comparison with the steady-state method. Moreover, the analysis includes the dynamic effect of boundary conditions (external air temperature, wind speed and direction), as well as the effects of the building site and the surroundings.

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Section: Introductionmentioning

confidence: 91%

Section: Modelling Of Airflow Through Leaksmentioning

confidence: 99%

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Modelling building infiltration using the airflow network model approach calibrated by air-tightness test results and leak detection

Heim

Miszczuk

2020

Building Services Engineering Research and Technology

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“…Sensitivity analysis (SA) in existing literature and textbooks, as applied in the automotive industry, illustrates that the use of various SA methods have been widely performed. Depending on the type of study and mathematical skills of the designers, the level of contribution and methodology selection vary; factor prioritization [1][2][3][4][5][6], factor fixing [6][7][8][9][10], variance cutting [5][6] [11], and factor mapping [6] [12][13] are employed in engineering applications such as automotive. Fully electric and hybrid electric vehicles (EV/HEV)s designers particularly should: a.…”

Section: Introductionmentioning

confidence: 99%

Overview of Sensitivity Analysis Methods Capabilities for Traction AC Machines in Electrified Vehicles

Asef

Lapthorn

2021

IEEE Access

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A robust design in electrified powertrains substantially helps to enhance the vehicle's overall efficiency. Robustness analyses come with complexity and computational costs at the vehicle level. The use of sensitivity analysis (SA) methods in the design phase has gained popularity in recent years to improve the performance of road vehicles while optimizing the resources, reducing the costs, and shortening the development time. Designers have started to utilize the SA methods to explore: i) how the component and vehicle level design options affect the main outputs i.e. energy efficiency and energy consumption; ii) observing sub-dependent parameters, which might be influenced by the variation of the targeted controllable (i.e. magnet thickness) and uncontrollable (i.e. magnet temperature) variables, in nonlinear dynamic systems; and iii) evaluating the interactions, of both dependent, and sub-dependent controllable/uncontrollable variables, under transient conditions. Hence the aim of this study is to succinctly review recent utilization of SA methods in the design of AC electric machines (EM)s used in vehicle powertrains, to evaluate and discuss the findings presented in recent research papers while summarizing the current state of knowledge. By systematically reviewing the literature on applied SAs in electrified powertrains, we offer a bibliometric analysis of the trends of application-oriented SA studies in the last and next decades. Finally, a numericalbased case study on a third-generation TOYOTA Prius EM will be given, to verify the SA-related findings of this paper, alongside future works recommendations.INDEX TERMS Automotive engineering, AC machines, electric vehicles, robustness, sensitivity analysis, permanent magnet machines, time series analysis, statistics.

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“…In addition to the inaccuracy of the orifice-based models for the large openings due to the idealized Bernoulli's equation, there are other sources of discrepancy in these models such as the one associated with the input parameters as addressed in [33][34][35][36][37][38]. The input parameters (e.g.…”

Section: Introductionmentioning

confidence: 99%

Development of an adaptive discharge coefficient to improve the accuracy of cross-ventilation airflow calculation in building energy simulation tools

Shirzadi

Mirzaei

Naghashzadegan

2018

Building and Environment

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Airflow network (AFN) model embedded in building energy simulation (BES) tools such as EnergyPlus is extensively used for prediction of cross-ventilation in buildings. The noticeable uncertainty in the measurement of the surface pressure, discharge coefficient, and simplifications applied to the orifice-based equation result in considerable discrepancies in the prediction of the cross-ventilation airflow rate values. Computational Fluid Dynamics (CFD) provides more accurate results comparing to the orifice-based equations although with an excessive computational cost.The aim of this study is, therefore, to improve the accuracy of the orifice-based model by development of an adaptive correlation for the discharge coefficient using CFD. Hence, a validated CFD model for the cross-ventilation of an unsheltered building is firstly developed using an experimental study. In the next step, by exploiting Latin hypercube sampling (LHS) approaches, a large CFD dataset of 750 scenarios for different building geometries (i.e. square cube, cuboid and long corridor) is generated; the dataset is then coupled to the AFN crossventilation model to obtain an adaptive correlation for the discharge coefficient as a function of the openings' geometries and location using response surface (RSM) and radial basis function (RBF) models.Results show that the newly developed adaptive correlation successfully increases the accuracy of AFN model for the cross-ventilation modeling of unsheltered buildings as the relative errors for the airflow rate prediction of different building geometries are significantly decreased up to 28% in comparison with the cases with constant discharge coefficient and surface-averaged and local-surface wind pressure coefficients. Results, also demonstrate the importance of considering the value of the local-surface wind pressure in the AFN model for the square cube and cuboid building models.

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Characterization of an airflow network model by sensitivity analysis: parameter screening, fixing, prioritizing and mapping

Cited by 22 publications

References 41 publications

Modelling building infiltration using the airflow network model approach calibrated by air-tightness test results and leak detection

Modelling building infiltration using the airflow network model approach calibrated by air-tightness test results and leak detection

Overview of Sensitivity Analysis Methods Capabilities for Traction AC Machines in Electrified Vehicles

Development of an adaptive discharge coefficient to improve the accuracy of cross-ventilation airflow calculation in building energy simulation tools

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