Test on Ventilation Rates of Dormitories and Offices in University by the CO2 Tracer Gas Method

Zhang, Weining; Wang, Lixin; Ji, Zhenyu; Ma, Li; Yang, Hui

doi:10.1016/j.proeng.2015.08.1061

Cited by 29 publications

(14 citation statements)

References 3 publications

(2 reference statements)

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“…In this paper, the deterministic function is based on the principal of mass balance in a designated volume (V r ) [20,22,37,38]. The change in CO 2 concentration (C int ) in the room is expressed as:…”

Section: Modelling Processmentioning

confidence: 99%

“…The human emission rate of CO 2 estimated by the model is 12,793 mg/h (6.5 L/h). According to the literature [22], the human emission rate of CO 2 for an adult who is seated or reading or writing is 32,500 mg/h (16.5 L/h) for a female and 36,600 mg/h (18.6 L/h) for a male. The value of the human emission rate of CO 2 is 62% lower than the reference.…”

Section: Model Validationmentioning

confidence: 99%

“…The value of the human emission rate of CO 2 is 62% lower than the reference. As reported by other studies in the field [22], the reference value is calculated using a hypothesis that cannot be true for this case. However, the estimated value has the same order of magnitude.…”

Section: Model Validationmentioning

confidence: 99%

“…Usually, a deterministic approach is used to develop simple, low-order state space models for predicting room CO 2 concentrations [10] or calculating ventilation flow rates [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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Modelling indoor air carbon dioxide concentration using grey-box models

Macarulla

Casals

Carnevali

et al. 2017

Building and Environment

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Predictive control is the strategy that has the greatest reported benefits when it is implemented in a building energy management system. Predictive control requires low-order models to assess different scenarios and determine which strategy should be implemented to achieve a good compromise between comfort, energy consumption and energy cost. Usually, a deterministic approach is used to create low-order models to estimate the indoor CO2 concentration using the differential equation of the tracer-gas mass balance. However, the use of stochastic differential equations based on the tracer-gas mass balance is not common. The objective of this paper is to assess the potential of creating predictive models for a specific room using for the first time a stochastic grey-box modelling approach to estimate future CO2 concentrations. First of all, a set of stochastic differential equations are defined. Then, the model parameters are estimated using a maximum likelihood method. Different models are defined, and tested using a set of statistical methods. The approach used combines physical knowledge and information embedded in the monitored data to identify a suitable parametrization for a simple model that is more accurate than commonly used deterministic approaches. As a consequence, predictive control can be easily implemented in energy management systems.Peer ReviewedPostprint (author's final draft

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Section: Modelling Processmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling indoor air carbon dioxide concentration using grey-box models

Macarulla

Casals

Carnevali

et al. 2017

Building and Environment

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“…Carbon dioxide is one of the natural compounds of atmospheric air that can be used also as a tracer gas. Measurement technique with CO 2 as a tracer gas was described in [7,8,9,10,11,12]. The Rotronic meters have been used to measure: CO 2 concentration within the range of 0 to 5000 ppm with the accuracy of 30 ppm + 5% of sensor indication and the temperature with an accuracy of up to 0.3K.…”

Section: Measurement Of Building Airtightness and Air Infiltrationmentioning

confidence: 99%

Transition from n₅₀ to actual air exchange dependent on climatic conditions

2019

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The knowledge of the air flow and air exchange in the building is critical both on the design and operation stage of the building. Infiltration of air interferes with the mechanical ventilation and determines the proper functioning of the natural ventilation system, still commonly used in the standard buildings. The building airtightness can be described by n50 parameter, however it does not specify the real air exchange in natural conditions. According to the simple procedure of the standard EN ISO 13789, factor n50 may be easily converted to the monthly averaged air change rate. However, it is difficult to accept the same value of air change rate in any month of a year, as it is often done in the certification procedures. More precise, climate dependent conversion procedures have been elaborated in USA, but they were developed for the specific local building technology and local climate conditions. This paper presents the results of the preliminary measurements conducted in a single family house in Poland, built in a heavy-weight technology. The real air exchange rate was measured in various climatic conditions by means of gas tracing method, with CO2 as the tracer gas, in order to prove a relationship between the enhanced procedure and the external conditions. Acceptable agreement between the results of the measurement and model calculations was obtained. Based on the preliminary results, the authors determined the more realistic influence of the enhanced algorithm on the ventilation energy demand. The use of the simplified model resulted in case of the analyzed object in 15% overestimation of the ventilation thermal losses.

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