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Multivariate linear regression model for estimating average daylight illuminance
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology.ORCID iD: 0000-0003-1835-7158
Linnaeus University, Faculty of Technology, Department of Built Environment and Energy Technology. (SBER)ORCID iD: 0000-0003-4405-1056
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.

Place, publisher, year, edition, pages
Ingenta Connect , 2017. Vol. 23, no 7, p. 6p. 6163-6167
Keywords [en]
Multivariate linear regression, Daylight Illuminance, interaction analysis
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
URN: urn:nbn:se:lnu:diva-59687DOI: 10.1166/asl.2017.9228ISI: 000431480900032Scopus ID: 2-s2.0-85030233490OAI: oai:DiVA.org:lnu-59687DiVA, id: diva2:1063040
Conference
International Conference on Architecture and Built Environment. October 5–6, 2016, Kuala Lampur, Malaysia
Projects
ProWOODAvailable from: 2017-01-09 Created: 2017-01-09 Last updated: 2019-09-05Bibliographically approved
In thesis
1. Windows and blinds selection for enhancing subjective well-being
Open this publication in new window or tab >>Windows and blinds selection for enhancing subjective well-being
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
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:nbn:se:lnu:diva-65211 (URN)978-91-88357-76-2 (ISBN)
Presentation
2017-06-12, M1088, George Lückligs väg, Växjö, 10:00 (English)
Opponent
Supervisors
Projects
ProWood
Funder
Knowledge Foundation, 20130245
Available from: 2017-06-27 Created: 2017-06-13 Last updated: 2017-06-28Bibliographically approved

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Jalilzadehazhari, ElahehMahapatra, Krushna

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