Field studies of thermal comfort across multiple climate zones for the subcontinent: India Model for Adaptive Comfort (IMAC)-Reference-Cited by-同舟云学术

Field studies of thermal comfort across multiple climate zones for the subcontinent: India Model for Adaptive Comfort (IMAC)

Published:2016-03 Issue: Volume:98 Page:55-70
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Manu Sanyogita^ORCID,Shukla Yash,Rawal Rajan,Thomas Leena E.,de Dear Richard

Funder

Ministry of New and Renewable Energy

Shakti Sustainable Energy Foundation

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference44 articles.

1. City Census 2011, Census 2011;Census Organization of India,2011

2. Assessment of Air Velocity Preferences and Satisfaction for Naturally Ventilated Office Buildings in India;Manu,2014

3. Total Commercial Floor Space Estimates for India;Kumar,2010

4. National Skill Development Corporation, Human Resource and Skill Requirements in the Building Construction and Real Estate Sector, New Delhi, n.d. http://www.nsdcindia.org/sites/default/files/files/Building-Construction-Real-Estate.pdf.

5. Power and Energy, Plan. Comm. Govt. India;Planning Commission,2014

Cited by 260 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Developing building-specific, occupant-centric thermal comfort models: A methodological approach;Journal of Building Engineering;2024-10

2. Analyzing the thermal performance of walling systems in low-income housing through computational fluid dynamics approach;Energy and Buildings;2024-09

3. Building Thermal Comfort Modulation Through Phase Change Material;Advancements in Non‐Conventional Cooling and Thermal Storage Strategies;2024-08-23

4. Impact of indoor thermal environment on human thermal comfort, psychological response, and performance during winter in Jaipur, India;Building and Environment;2024-08

5. A physics-informed deep learning-based urban building thermal comfort modeling and prediction framework for identifying thermally vulnerable building stock;Smart and Sustainable Built Environment;2024-07-17