Probabilistic Analysis of Passive Cooling Strategies and Occupant Behaviour

For improving the summer comfort conditions in apartments of the Santiago real estate market

Overheating appears as a recurrent problem in apartments of the real estate market of Santiago, since their architectural design frequently does not incorporate passive cooling techniques and some occupants may not be completely aware of their impact on the thermal comfort. This situation is encouraged by a Thermal Regulation that allows extensive single glazing surfaces and that does not propose any criteria for limiting the risk of overheating during summer. To deal with this entire scenario, we proposed the application of passive cooling strategies with the aim of obtaining adequate conditions of summer comfort and avoiding the use of air conditioning in apartments of the real estate market of Santiago. This thesis establishes the definition of apartment typologies through a multidimensional approach, a sensitivity analysis with the aim of assessing the possibilities to reduce the risk of overheating and two questionnaire surveys related to occupant behaviour and to the interest and willingness to purchase solar protection devices.

The results obtained suggest that the best performance in terms of summer comfort can be obtained from the combination of diverse variables that would be significant in respect to the reduction of the risk of overheating. In this sense, the presence of solar protection devices and night ventilation constitute very significant input parameters, especially with respect to living rooms and bedrooms, respectively. Finally, the approach proposed for this thesis not only allows introducing improvements in terms of summer thermal conditions, but also suggests the integration of a series of attributes, such as the incorporation of solar protection devices as part of the architectural design, with the aim of being developed at the level of their value chain.

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Presses universitaires de Louvain
Felipe Encinas,
Thèses de la Faculté d'architecture, d'ingénierie architecturale, d'urbanisme
Catégorie (éditeur)
Sciences appliquées > Architecture et génie civil
Catégorie (éditeur)
Sciences appliquées
BISAC Subject Heading
Code publique Onix
06 Professional and scholarly
CLIL (Version 2013 )
3076 Architecture/Urbanisme
Description public visé
Architecture durable, architecture climatique
Date de première publication du titre
15 juillet 2012
Subject Scheme Identifier Code
Thema subject category: RPC
Type d'ouvrage

Livre broché

Details de produit
1 Couverture pelliculée
Date de publication
15 juillet 2012
Nombre de pages de contenu principal : 350
Dépôt Légal
Code interne
16 x 24 x 2 cm
562 grammes
34,00 €
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Abstract v
Acknowledgements vii
Acronyms and abbreviations ix
Table of contents xi
1. Introduction 1
1.1. General background 2
1.1.1. Air conditioning, energy supply and environmental
challenges 2
1.1.2. Risk of overheating and summer comfort in the national
context 7
1.1.3. Building envelope definitions and national
Thermal Regulation 11
1.1.4. Definition of building typologies in the context of the
Thermal Regulation 16
1.2. Research questions and methodological approach 19
1.2.1. Research questions of the thesis 21
1.2.2. Methodological approach of the thesis 23
1.3. References 26
2. Real estate market and building typologies
Towards a multidimensional market disaggregation 31
2.1. Mass housing and new production approaches 32
2.1.1. Building houses is not the same as building cars 32
2.1.2. Economical approaches in industrialised construction 34
2.1.3. Apartment buildings under the logic of industrialisation 35
2.2. Analysing supply through market disaggregation 37
2.2.1. Introduction to the real estate market of apartments
in Santiago 37
2.2.2. Towards a multidimensional market disaggregation 40
2.2.3. The variable of location in the Portal
database 43
2.3. Market disaggregation by means of cluster analysis 46
2.3.1. Cluster analysis as a classification method 46
2.3.2. Definition of typologies by means of clustering methods 48
2.3.3. Application of Principal Component Analysis 52
2.4. Definition of apartment typologies by means of a k-means
cluster analysis 58
2.4.1. Application of the k-means clustering method 58
2.4.2. Definition of representative models for the apartment
typologies 61
2.5. Conclusions for chapter 2 66
2.6. References 67
3. Sensitivity analysis in building simulation
A probabilistic approach to the summer comfort of apartments from
the Santiago real estate market 69
3.1. Uncertainty and sensitivity analysis 71
3.1.1. Introduction 71
3.1.2. Literature review of sensitivity analysis in building simulation 74
3.1.3. Factorial Design versus Monte Carlo Analysis (MCA) 83
3.1.4. Example of sensitivity analysis applied to the building
energy performance of apartment typologies 92
3.2. Passive cooling techniques 96
3.2.1. Introduction to the summer comfort and the risk of
overheating 96
3.2.2. Definition of passive cooling strategies 103
3.2.3. Ventilation strategies for reducing overheating 106
3.3. Thermal comfort models 112
3.3.1. Application of the Fanger's PMV for summer comfort
estimation 113
3.3.2. Application of the adaptive model for summer comfort and
risk of overheating estimation 116
3.4. Sensitivity analysis in building performance simulation for summer
comfort assessment with respect to apartment typologies 122
3.4.1. Definition of input parameters for sensitivity analysis 122
3.4.2. Definition of sample matrix by means of the Latin Hypercube
sampling (LHS) method 128
3.4.3. Thermal modelling and obtaining of simulation outputs 135
3.4.4. Global sensitivity analysis for summer comfort assessment
of apartment typologies in Santiago 141
3.4.5. Local sensitivity analysis for summer comfort assessment of
apartment typologies in Santiago 151
3.5. Conclusions for chapter 3 174
3.6. References 176
4. Definition of occupant behaviour patterns with respect to natural ventilation
by means of multivariate statistical techniques 183
4.1. Survey of the perception of thermal comfort and occupant behaviour
in an apartment building in Santiago’s real estate market 185
4.1.1. Introduction 185
4.1.2. Presentation of the pilot case study 188
4.1.3. Description of variables for the questionnaire survey 191
4.1.4. Content validity of the questionnaire survey by experts 193
4.1.5. Methodological aspects 196
4.2. Descriptive analysis of the survey 199
4.2.1. Analysis of results for segmentation variables 199
4.2.2. Analysis of results for perception of thermal comfort in
winter and summer 204
4.2.3. Analysis of results for building envelope improvements
with respect to the thermal comfort in winter and summer 208
4.2.4. Analysis of results for occupant behaviour with respect to
daytime and night ventilation 212
4.2.5. Analysis of results for occupant behaviour regarding the use of
HVAC appliances and indoor environmental quality problems 223
4.3. Definition of occupant behaviour patterns with respect to ventilation by
means of an explanatory analysis of the survey 229
4.3.1. Methodological approach 229
4.3.2. Definition of factor of behaviour by means of a Principal
Component Analysis 232
4.3.3. Estimation of the incidence of behaviour factors on the
overall thermal comfort by means of a discrete choice model 239
4.3.4. Definition of occupant behaviour patterns with respect to
natural ventilation by means of a cluster analysis 244
4.3.5. Assessment of the summer comfort applying the defined
occupant behaviour profiles 251
4.3.6. Sensitivity analysis of different parameters with respect to
ventilation rate and window operation 260
4.4. Conclusions for chapter 4 266
4.5. Annex for chapter 4 267
4.5.1. Questionnaire survey (translated English version) 267
4.6. References 276
5. Interest and willingness to purchase solar protection devices
in the real estate market of apartments of Santiago 279
5.1. Survey of interest and willingness to purchase solar protection
devices in the real estate market of apartments in Santiago 281
5.1.1. Introduction 281
5.1.2. Methodological aspects 283
5.2. Descriptive analysis of the survey 285
5.2.1. Analysis of results by question 285
5.2.2. Percentage distribution of results by crossing two or three
items of the survey 291
5.3. Estimation of the incidence of different variables on the willingness to
purchase solar protection devices by means of discrete choice models 296
5.3.1. Definition of the multivariate logistic regressions 298
5.3.2. Estimation of the odd ratios for the logistic regression models 302
5.4. Conclusions for chapter 5 3055.5. Annex for chapter 5 306
5.5.1. Questionnaire survey (translated English version) 306
5.6. References 308
6. Conclusions 309
6.1. Analysing the supply of apartments for establishing design strategies 310
6.2. Analysing the demand of apartments for identifying
occupant behaviour 312
6.3. Future work 315
6.4. References 318
7. Bibliography 320