Designing Zero Carbon Buildings Using Dynamic Simulation Methods

Jankovic, Ljubomir

doi:10.4324/9780203135754

Cited by 25 publications

(29 citation statements)

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“…In both parts, internal air temperature is obtained starting from a simplified heat balance equation, adapted from Jankovic [3], p. 261:…”

Section: Methodsmentioning

confidence: 99%

“…In the case of the physical test, the curve fitting is carried out with reference to measured internal temperatures as per Equations (3) and (4), and in the case of the simulated test, the curve fitting is carried out with reference to simulated internal temperatures using the same equations.…”

Section: Methodsmentioning

confidence: 99%

“…It is critical to establish thermal properties of an existing building accurately in order to be able to design performance improvements with confidence. There are two types of physical tests that can be carried out on a building that enable thermal properties to be determined: a co-heating test [3], p. 251, and a dynamic heating test [3], p. 259. The former involves heating a building with supplementary electric heaters over a period of several days, as well as monitoring internal and external air temperatures and the more realistic design improvements to be made through deep energy retrofitting.…”

Section: Introductionmentioning

confidence: 99%

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Improving Building Energy Efficiency through Measurement of Building Physics Properties Using Dynamic Heating Tests

Jankovic

2019

Energies

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Buildings contribute to nearly 30% of global carbon dioxide emissions, making a significant impact on climate change. Despite advanced design methods, such as those based on dynamic simulation tools, a significant discrepancy exists between designed and actual performance. This so-called performance gap occurs as a result of many factors, including the discrepancies between theoretical properties of building materials and properties of the same materials in buildings in use, reflected in the physics properties of the entire building. There are several different ways in which building physics properties and the underlying properties of materials can be established: a co-heating test, which measures the overall heat loss coefficient of the building; a dynamic heating test, which, in addition to the overall heat loss coefficient, also measures the effective thermal capacitance and the time constant of the building; and a simulation of the dynamic heating test with a calibrated simulation model, which establishes the same three properties in a non-disruptive way in comparison with the actual physical tests. This article introduces a method of measuring building physics properties through actual and simulated dynamic heating tests. It gives insights into the properties of building materials in use and it documents significant discrepancies between theoretical and measured properties. It introduces a quality assurance method for building construction and retrofit projects, and it explains the application of results on energy efficiency improvements in building design and control. It calls for re-examination of material properties data and for increased safety margins in order to make significant improvements in building energy efficiency.

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“…In both parts, internal air temperature is obtained starting from a simplified heat balance equation, adapted from Jankovic [3], p. 261:…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving Building Energy Efficiency through Measurement of Building Physics Properties Using Dynamic Heating Tests

Jankovic

2019

Energies

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“…Estos análisis utilizan con frecuencia simulaciones térmi-cas de los edificios (Krygiel y Nies, 2008;Hensen y Lambert, 2011;Jankovic, 2012;Anderson, 2014), que consideran resultados del total del ambiente interior, sin diferenciar los distintos recintos, en especial en los edificios de tamaño pequeño, como las viviendas unifamiliares, que poseen varias habitaciones, simplificándolas en modelos unizona (Hendron y Engebretch, 2010). Sin embargo, cuando se realizan mediciones de variables ambientales, como temperatura, humedad, iluminación o calidad del aire, suelen evidenciarse diferencias entre habitaciones (Sarmiento y Hormazábal, 2003;León, Muñoz, León y Bustamante, 2011;Beizaee, Lomas y Firt, 2013).…”

Section: Introductionunclassified

Desempeño ambiental de recintos habitacionales. Comparación de simulaciones, monitorización y percepción de residentes en seis viviendas de Concepción, Chile

Álvarado

Ojeda

Viveros

et al. 2016

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Los estudios y proyectos habitacionales consideran las viviendas de manera unitaria, sin diferenciar las condiciones ambientales por recintos, aunque en la vivencia cotidiana se reconocen variaciones. Este artículo realiza una comparación entre los datos proporcionados por simulaciones computacionales de desempeño térmico y monitoreos físicos de recintos, que registran valores existentes, y percepciones de sus habitantes en torno a su ambiente residencial en seis viviendas de Concepción, Chile. Con el fin de caracterizar las diferencias ambientales que surgen en los hogares, como también las originadas en los distintos recintos, en lo que es la construcción de la confortabilidad. Las simulaciones expresan algunas diferencias relevantes entre recintos (demandas energéticas anuales de 12 kW h/m2 hasta 330 kW h/m2), mientras las mediciones físicas revelan valores más acotados (diferencias entre temperaturas ambientales de menos de 5°C). Las entrevistas y observación de residentes sugieren apreciaciones similares, pero a la vez aportan otros aspectos (como una mayor valoración de los niveles superiores y habitaciones con mayor luminosidad). Los resultados y conclusiones emanados del estudio aportan datos que pueden resultar de interés comparativo para la planificación y diseño habitacional en la zona, pero también un análisis que integra las distintas dimensiones trabajadas del confort residencial y sus variaciones entre los recintos habitacionales, lo que resulta incidente para el ámbito de las políticas y acciones de mejoramiento ambiental de las viviendas, destinadas a aumentar la calidad residencial.

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“…These three properties enable the simulation model to calculate thermal diffusivity of the material [2], which is subsequently used in the dynamic simulation. Moisture transfer property is specified through vapor resistivity.…”

Section: Introductionmentioning

confidence: 99%

Reducing Simulation Performance Gap in Hemp-Lime Buildings Using Fourier Filtering †

Jankovic

2016

Sustainability

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Abstract:Mainstream dynamic simulation tools used by designers do not have a built-in capability to accurately simulate the effect of hemp-lime on building temperature and relative humidity. Due to the specific structure of hemp-lime, heat travels via a maze of solid branches whilst the capillary tubes absorb and release moisture. The resultant heat and moisture transfer cannot be fully represented in mainstream simulation tools, causing a significant performance gap between the simulation and the actual performance. The author has developed an analysis method, based on a numerical procedure for digital signal filtering using Fourier series. The paper develops and experimentally validates transfer functions that enhance simulation results and enable accurate representation of behaviour of buildings built from hemp-lime material using the results of a post-occupancy research project. As a performance gap between design simulation and actual buildings occurs in relation to all buildings, this method has a wider scope of application in reducing the performance gap.

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Designing Zero Carbon Buildings Using Dynamic Simulation Methods

Cited by 25 publications

References 0 publications

Improving Building Energy Efficiency through Measurement of Building Physics Properties Using Dynamic Heating Tests

Improving Building Energy Efficiency through Measurement of Building Physics Properties Using Dynamic Heating Tests

Desempeño ambiental de recintos habitacionales. Comparación de simulaciones, monitorización y percepción de residentes en seis viviendas de Concepción, Chile

Reducing Simulation Performance Gap in Hemp-Lime Buildings Using Fourier Filtering †

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