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Windows and blinds selection for enhancing subjective well-being
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology.ORCID iD: 0000-0003-1835-7158
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Earlier studies in the context of windows and blinds selection have mostly tried to increase the awareness regarding various effects of windows and blinds selection on subjective well-being, including their effect on visual comfort, thermal comfort, energy consumption and life cycle cost. However, the main problem is the potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. Increased awareness about the contradictory effect of windows and blinds selection on subjective well-being on one hand and lack of a feasible method in managing the conflicts on the other hand may bind individuals, as decision-makers, in a situation where they follow the immediate economic benefits rather than the long-term visual and thermal benefits. To solve the mentioned problem, this study analysed first the degree of the conflicts between average daylight illuminance and total energy consumption in Sweden. This decision was made due to large variation in solar elevation angle and solar intensity between summer and winter in Sweden, which has significant effects on daylight illuminance and total energy consumption. Analysing the conflicts was accomplished by developing two multivariate linear regression models for calculating average daylight illuminance and total energy consumption. Comparison and analysis of the multivariate linear regression models showed the existence of a high degree of conflicts, which makes window and blind selection a rather complex multidimensional problem. Specifying the degree of the conflicts formed a hypothesis as: “A multi criteria decision-making method increases the controllability and manages the conflicts in selecting windows and blinds”. The developed hypothesis was later tested by employing analytical hierarchy process, as widely used multi criteria decisionmaking method. The analytical hierarchy process prioritizes decision-maker’ preferences and introduces a desired trade-off solution. The results of employing analytical hierarchy process showed the capability of it in managing the conflicts among visual comfort, thermal comfort, energy consumption and life cycle cost. Finally, the application of the analytical hierarchy process was expanded by integrating it with nondominated sorting genetic algorithm-II, as an optimization algorithm. Through this integration, optimization algorithm combines windows’ and blinds’ design variables and analyses a large number of solutions, while analytical hierarchy process ranks the solutions based on decision-makers’ preferences and introduces a desired trade-off solution. The integration between analytical hierarchy process and the nondominated sorting genetic algorithm-II was presented later as a conceptual framework. The developed conceptual framework can be used for selecting windows and blinds II in both residential and commercial buildings. In selecting windows and blinds, the conceptual framework is a novel solution to the lack of a feasible method for increasing the controllability for decision-makers and obtaining a desired trade-off solution.

Abstract [sv]

Tidigare studier avseende val av fönster och solskydd har främst försökt fastställa olika effekter som valet av fönster och solskydd har på det subjektiva välbefinnandet. Detta inkluderar dessa föremåls effekt på den visuella komforten, den termiska komforten, energiförbrukningen och livscykelkostnaderna. Det huvudsakliga problemet är dock de potentiella konflikterna mellan visuell komfort, termisk komfort, energiförbrukning och livscykelkostnader. Avsaknaden av en metod för att hantera denna konflikt leder till att beslutfattaren fastnar i en situation där de snarare gör sitt val utifrån omedelbara ekonomiska fördelar än de långsiktiga visuella och termiska fördelarna. För att lösa ovan nämnda problem analyserades konflikterna mellan det genomsnittliga dagsljusinsläppet och den totala energiförbrukningen i Sverige. En av huvudanledningarna till konflikterna är att solens infallsvinkel och intensitet varierar kraftigt mellan sommar och vinter i Sverige. Detta har betydande effekter på dagsljusinfallet och den totala energiförbrukningen. Konflikterna analyserades genom att utveckla två multivariata linjära regressionsmodeller för att beräkna det genomsnittliga dagsljusinfallet och den totala energiförbrukningen. En jämförelse och analys av de multivariata linjära regressionsmodellerna påvisade en hög grad av konflikter, vilket gör valet av fönster och solskydd till ett komplext och flerdimensionellt problem. Bestämningen av graden av konflikt formade följande hypotes: ” En multikriterieanalysbaserat beslutsstöd ökar kontrollerbarheten och hanterar konflikter vid valet av fönster och solskydd”. Den utvecklade hypotesen testades senare med hjälp av Analytical Hierarchy Process (AHP), en ofta använd multikriterieanalys metod för beslutsfattande. Metoden tar fram lösningar genom att göra prioriteringar enligt beslutsfattarens preferenser. Resultaten av att tillämpa metoden visade metodens förmåga att lösa konflikterna kring visuell komfort, termisk komfort, energiförbrukning och livscykelkostnad. Slutligen utökades metoden genom att integrera AHP med optimeringsalgoritmen Non-dominated sorting genetic algorithm-II. Genom denna integrering kombinerar optimeringsalgoritmen fönstrens och solskyddens design variabler till ett stort antal lösningsförslag. Dessa lösningsförslag analyseras och till sist rangordnas lösningsförslagen med hjälp av AHP baserat på beslutsfattarnas preferenser. Integreringen av AHP och optimeringsalgoritmen presenterades som ett konceptuellt ramverk. I valet av fönster och solskydd är det konceptuella ramverket en ny lösning för att öka den upplevda kontrollen och därmed förstärka det subjektiva välbefinnandet.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2017. , p. 65
Series
Lnu Licentiate ; 1
Keywords [en]
Subjective well-being, perceived control, controllability, analytical hierarchy process, non-dominated sorting genetic algorithm-II
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
URN: urn:nbn:se:lnu:diva-65211ISBN: 978-91-88357-76-2 (print)OAI: oai:DiVA.org:lnu-65211DiVA, id: diva2:1108763
Presentation
2017-06-12, M1088, George Lückligs väg, Växjö, 10:00 (English)
Opponent
Supervisors
Projects
ProWood
Funder
Knowledge Foundation, 20130245Available from: 2017-06-27 Created: 2017-06-13 Last updated: 2017-06-28Bibliographically approved
List of papers
1. Multivariate linear regression model for estimating average daylight illuminance
Open this publication in new window or tab >>Multivariate linear regression model for estimating average daylight illuminance
2017 (English)In: Advanced Science Letters, ISSN 1936-6612, E-ISSN 1936-7317, Vol. 23, no 7, p. 6p. 6163-6167Article in journal (Refereed) Published
Abstract [en]

Window design and the selection of glazing system have significant effect on daylight illuminance. Occupants’ productivity is highly dependent on daylight, as it associates with numerous health advantages. Hence conducting a systematic investigation considering the performance of various window designs and glazing systems is highly important at the early stage of design process. For this purpose, this study attempts to develop a multivariate linear regression model for estimating the average daylight illuminance. To perform the simulations, an office room prototype was modelled by COMFEN 5Beta software. The prototype is a hypothetical office room, as its size, HVAC system and envelopes construction are based on the common practice in construction in Sweden. Because average daylight illuminance is sensitive to window size, orientation, glazing system, design model and position, 544 simulations were performed based on thses variable to create an extensive dataset.  A multivariate linear regression model was developed based on 90% dataset, which was chosen randomly. The obtained R² value was exceeded 96%, which shows an excellent fit for the developed model. The interaction between variables was also studied. The remaining 10% of dataset was utilized for validating the developed model. The validity of the model was further compared with another multivariate linear regression model, developed based on 50% of the dataset.The results show the effectiveness of multivariate linear regression models in supporting architects and predicting average daylight illuminance in early stage of design analysis.

Publisher
p. 6
Keywords
Multivariate linear regression, Daylight Illuminance, interaction analysis
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
urn:nbn:se:lnu:diva-59687 (URN)10.1166/asl.2017.9228 (DOI)000431480900032 ()
Conference
International Conference on Architecture and Built Environment. October 5–6, 2016, Kuala Lampur, Malaysia
Projects
ProWOOD
Available from: 2017-01-09 Created: 2017-01-09 Last updated: 2018-12-14Bibliographically approved
2. Multivariate linear regression model for estimating total energy consumption
Open this publication in new window or tab >>Multivariate linear regression model for estimating total energy consumption
2017 (English)In: : The 3rd Asia conference of International Building Performance Simulation Association - ASim2016, Nov. 27-29, 2016, South Korea, International Building Performance Simulation Association (IBPSA), 2017, , p. 8Conference paper, Published paper (Refereed)
Abstract [en]

Windows as essential elements of buildings have a significant effect on total energy consumption, including heating and cooling demand in Sweden. A statistical reliable model for estimating the total energy consumption associated with various window designs and glazing systems helps architects and designers in the early stage of the design process. Most of the introduced models in literature utilized a mathematic sampling algorithm such as Monte Carlo to develop a simple linear regression model for estimating the total energy consumption. A simple linear regression model cannot describe the effect of different groups of a categorical variable. Hence this study considers four variables related to the window characteristics, including window size, design model, orientation, glazing system and develops a categorical multiple linear regression model for estimating the total energy consumption. 544 simulations were performed by COMFEN Beta5 software. The results were used as a database for developing a categorical multiple linear regression model. The accuracy of developed model was studied by the coefficient of determination, R- square value (R²). The obtained R² exceeded by 94%. Furthermore, the predicted total energy consumptions obtained by the developed regression model were compared with the simulated values by COMFEN software. Results show a strong linear relationship between predicted and simulated values.  Developed multivariate linear regression model can be utilized in early stage of design process for estimating the total energy consumption associated with various window designs and glazing systems.

Place, publisher, year, edition, pages
International Building Performance Simulation Association (IBPSA), 2017. p. 8
Keywords
Multiple linear regression, categorical variable, interaction analysis
National Category
Architectural Engineering
Identifiers
urn:nbn:se:lnu:diva-59689 (URN)
Conference
The 3rd Asia conference of International Building Performance Simulation Association - ASim2016, Nov. 27-29, 2016, South Korea
Note

Ej belagd 170627

Available from: 2017-01-09 Created: 2017-01-09 Last updated: 2018-05-17Bibliographically approved
3. Application of analytical hierarchy process for selecting an interior window blind
Open this publication in new window or tab >>Application of analytical hierarchy process for selecting an interior window blind
2017 (English)In: Architectural Engineering and Design Management, ISSN 1745-2007, E-ISSN 1752-7589, Vol. 13, no 4, p. 308-324Article in journal (Refereed) Published
Abstract [en]

Window blinds have a substantial role in shaping the energy consumption and improving thermal comfort and visual comfort. However, difficulties in selecting a window blind remain, due to existence of potential conflicts between visual, thermal, energy and life cycle cost. To overcome this problem, this study evaluates the performance of interior blinds, including venetian with slat of 0° and 45°, roller and double pleated blinds with respect to visual, thermal, energy and life cycle cost. Later, the Analytical hierarchy method (AHP) is used for selecting the best blind based on trade-off among the visual, thermal, energy and life cycle cost. In using AHP, visual comfort is determined as most important objective with a weight of 52%. The results show that venetian blind with slat of 0° drawn 100% is the trade-off blind. Accomplishing the sensitivity analysis on blinds’ global weight shows that venetian blind with slat of 0° drawn 100% remains the trade-off blind until the weight of energy and life cycle cost is below 37% and 57% respectively and the weight of visual comfort is above 4%. However, changing thermal comfort weight has no impact on ranking of the blinds. This study shows the capability of AHP in managing the conflicts.

Place, publisher, year, edition, pages
Taylor & Francis, 2017
Keywords
Interior window blinds, Analytical hierarchy process, Energy consumption, Life cycle cost, Thermal comfort, Visual comfort
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
urn:nbn:se:lnu:diva-62606 (URN)10.1080/17452007.2017.1324402 (DOI)000402126900006 ()
Projects
ProWOOD
Available from: 2017-04-26 Created: 2017-04-26 Last updated: 2018-11-28Bibliographically approved
4. Developing a decision-making framework for resolving conflicts when selecting windows and blinds
Open this publication in new window or tab >>Developing a decision-making framework for resolving conflicts when selecting windows and blinds
2018 (English)In: Architectural Engineering and Design Management, ISSN 1745-2007, E-ISSN 1752-7589Article in journal (Refereed) Epub ahead of print
Abstract [en]

Windows and blinds play a significant role in both shaping energy consumption and enhancing indoor comfort. But there are still difficulties with selecting windows and blinds due to the existence of potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. A literature review was conducted with the purpose of developing a decision-making framework that resolves the conflicts, and allows selecting a window and blind design based on trade-off between visual comfort, thermal comfort, energy consumption and life cycle cost. The decision-making framework was developed by integrating non-dominated sorting genetic algorithm-II as an optimisation algorithm with analytical hierarchy process as a multi-criteria decision-making method. The optimisation algorithm considers different window and blind design variables and analyses multiple designs, while the multi-criteria decision-making method ranks the optimization results and selects a trade-off design. An operating package enabled the decision-making framework to be automated. The operating package was obtained by coupling EnergyPlus as a simulation tool and modeFRONTIER as an integration platform. The decision-making framework was developed to select a trade-off window and blind design through intelligent use of simulation in analysing big-data in built environment, energy and cost sectors. Application of the framework ensures the minimum visual and thermal comfort thresholds with the lowest energy demand and cost. Architects and designers can use the framework during the design or renovation phase of residential and commercial buildings.

 

Keywords
Trade-off design, big-data, optimization, multi-criteria decision-making, non-dominated genetic algorithm II, framework design, analytical hierarchy process
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
urn:nbn:se:lnu:diva-65866 (URN)10.1080/17452007.2018.1537235 (DOI)
Funder
Knowledge Foundation
Available from: 2017-06-27 Created: 2017-06-27 Last updated: 2018-12-03

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Licentiate Thesis (Extended Summary)(1812 kB)147 downloads
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Jalilzadehazhari, Elaheh

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