Improved indoor environment through optimised ventilator and furniture positioning: A case of slum rehabilitation housing, Mumbai, India

Abstract This study optimized the ventilator and furniture location of a tenement unit in a low-income urban habitat to obtain maximum experiential indoor environmental quality (e-IEQ) over the breathing zone. Hypothetical interior layouts using a combination of the two design parameters of ventilator location and bed position were generated for optimizing the design layout. This layout could promote maximum indoor airflow and minimum indoor air temperature and contaminant concentration. In this study, an improved indoor environment is hypothesized to be attainable through improved natural ventilation and thermal performance in the occupied zones. A sequential methodology involving “parametric design modeling–computational simulation–multiobjective optimization–multicriteria decision making”-based framework was selected. Results exhibited that the currently designed tenement unit had a poor indoor environment, whereas the hypothesized iterated layout “optimized design layout, scenario 3 (ODL 3)” derived from the optimization and decision-making algorithm performed effectively in providing e-IEQ. An increase in experiential indoor air velocity by 0.2 m/s and a decrease in temperature by 2 °C were observed over the monitoring point in the ODL 3 considering the existing scenario. Therefore, this study can find a way toward the development of sustainable habitat design guidelines under upcoming slum redevelopment policies across the nation.

[1]  Yoshihide Tominaga,et al.  AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings , 2008 .

[2]  Blas Galván,et al.  Optimization of constrained multiple-objective reliability problems using evolutionary algorithms , 2006, Reliab. Eng. Syst. Saf..

[3]  David W. Coit,et al.  Multi-objective optimization using genetic algorithms: A tutorial , 2006, Reliab. Eng. Syst. Saf..

[4]  F. Battaglia,et al.  Numerical investigation of single-sided natural ventilation driven by buoyancy and wind through variable window configurations , 2018, Energy and Buildings.

[5]  Pradip P. Kalbar,et al.  Assessment of stormwater management options in urban contexts using Multiple Attribute Decision-Making , 2017 .

[6]  Madhavi Indraganti Thermal comfort in naturally ventilated apartments in summer: Findings from a field study in Hyderabad, India , 2010 .

[7]  Anh Tuan Nguyen,et al.  The effect of ceiling configurations on indoor air motion and ventilation flow rates , 2011 .

[8]  Yiqiang Jiang,et al.  Numerical Simulation of PM2.5 Distribution in Indoor Air , 2015 .

[9]  Evangelos Triantaphyllou,et al.  Multi-Criteria Decision Making: An Operations Research Approach , 1998 .

[10]  Ronita Bardhan,et al.  Gender, domestic energy and design of inclusive low-income habitats: A case of slum rehabilitation housing in Mumbai, India , 2019, Energy Research & Social Science.

[11]  Mark Sprowls,et al.  Assessing metabolic rate and indoor air quality with passive environmental sensors , 2018, Journal of breath research.

[12]  Ahmed Awad E. Ahmed,et al.  Effect of climate and design parameters on the temperature distribution of a room , 2018 .

[13]  Madhavi Indraganti,et al.  Adaptive use of natural ventilation for thermal comfort in Indian apartments , 2010 .

[14]  Markus Olhofer,et al.  Test Problems for Large-Scale Multiobjective and Many-Objective Optimization , 2017, IEEE Transactions on Cybernetics.

[16]  Nyuk Hien Wong,et al.  Enhancement of natural ventilation in high-rise residential buildings using stack system , 2004 .

[17]  Arnab Jana,et al.  Mumbai slums since independence: Evaluating the policy outcomes , 2015 .

[18]  Mohammad Taghi Rezvan,et al.  Multi-objective optimization of reliability-redundancy allocation problem with cold-standby strategy using NSGA-II , 2018, Reliab. Eng. Syst. Saf..

[19]  A Sarkar,et al.  A simulation based framework to optimize the interior design parameters for effective Indoor Environmental Quality (IEQ) experience in affordable residential units: Cases from Mumbai, India , 2019, IOP Conference Series: Earth and Environmental Science.

[20]  Vijay Nehra,et al.  Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: Case study of India , 2017 .

[21]  Enrique Mu,et al.  Understanding the Analytic Hierarchy Process , 2017 .

[22]  E. Chan,et al.  The Analytic Hierarchy Process (AHP) Approach for Assessment of Urban Renewal Proposals , 2008 .

[23]  Ali Malkawi,et al.  Design-based natural ventilation evaluation in early stage for high performance buildings , 2019, Sustainable Cities and Society.

[24]  Joseph Khedari,et al.  Thailand ventilation comfort chart , 2000 .

[25]  B. Abu-Hijleh,et al.  Increasing efficiency of atriums in hot, arid zones , 2019, Frontiers of Architectural Research.

[26]  Sherzad Hawendi,et al.  Impact of an external boundary wall on indoor flow field and natural cross-ventilation in an isolated family house using numerical simulations , 2017 .

[27]  Shugang Wang,et al.  Assessment of single-sided natural ventilation driven by buoyancy forces through variable window configurations , 2017 .

[28]  Kirk R. Smith,et al.  Pollutant emissions and energy efficiency under controlled conditions for household biomass cookstoves and implications for metrics useful in setting international test standards. , 2012, Environmental science & technology.

[29]  Haralambos Sarimveis,et al.  Optimization of window-openings design for thermal comfort in naturally ventilated buildings , 2012 .

[30]  Hisao Ishibuchi,et al.  Evolutionary many-objective optimization: A short review , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[31]  Mahmoud Bady,et al.  Numerical and experimental investigations of the impacts of window parameters on indoor natural ventilation in a residential building , 2017 .

[32]  P. Depecker,et al.  Characteristic of airflow as the effect of balcony, opening design and internal division on indoor velocity: A case study of traditional dwelling in urban living quarter in tropical humid region , 2002 .

[33]  Hisao Ishibuchi,et al.  Evolutionary many-objective optimization by NSGA-II and MOEA/D with large populations , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[34]  R. Bardhan,et al.  Optimal interior design for naturally ventilated low-income housing: a design-route for environmental quality and cooling energy saving , 2020, Advances in Building Energy Research.

[35]  L. Norford,et al.  Investigating the association of healthcare-seeking behavior with the freshness of indoor spaces in low-income tenement housing in Mumbai , 2018 .

[36]  Gholam R. Amin,et al.  Railway station site selection using analytical hierarchy process and data envelopment analysis , 2010, Comput. Ind. Eng..

[37]  Jeetika Malik,et al.  Low-income housing layouts under socio-architectural complexities: A parametric study for sustainable slum rehabilitation , 2018, Sustainable Cities and Society.

[38]  Fatemeh Montazeri,et al.  CFD simulation of cross-ventilation in buildings using rooftop wind-catchers: Impact of outlet openings , 2018 .