Assessing impact of material transition and thermal comfort models on embodied and operational energy in vernacular dwellings (India)

Vernacular dwellings are well-suited climate-responsive designs that adopt local materials and skills to support comfortable indoor environments in response to local climatic conditions. These naturally-ventilated passive dwellings have enabled civilizations to sustain even in extreme climatic conditions. The design and physiological resilience of the inhabitants have coevolved to be attuned to local climatic and environmental conditions. Such adaptations have perplexed modern theories in human thermal-comfort that have evolved in the era of electricity and air-conditioned buildings. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Types of energy use associated with a buildings life cycle include its embodied energy, operational and maintenance energy, demolition and disposal energy. Embodied Energy (EE) represents total energy consumption for construction of building, i.e., embodied energy of building materials, material transportation energy and building construction energy. Embodied energy of building materials forms major contribution to embodied energy in buildings. Operational energy (OE) in buildings mainly contributed by space conditioning and lighting requirements, depends on the climatic conditions of the region and comfort requirements of the building occupants. Less energy intensive natural materials are used for traditional buildings and the EE of traditional buildings is low. Transition in use of materials causes significant impact on embodied energy of vernacular dwellings. Use of manufactured, energy intensive materials like brick, cement, steel, glass etc. contributes to high embodied energy in these dwellings. This paper studies the increase in EE of the dwelling attributed to change in wall materials. Climatic location significantly influences operational energy in dwellings. Buildings located in regions experiencing extreme climatic conditions would require more operational energy to satisfy the heating and cooling energy demands throughout the year. Traditional buildings adopt passive techniques or non-mechanical methods for space conditioning to overcome the vagaries of extreme climatic variations and hence less operational energy. This study assesses operational energy in traditional dwelling with regard to change in wall material and climatic location. OE in the dwellings has been assessed for hot-dry, warm humid and moderate climatic zones. Choice of thermal comfort models is yet another factor which greatly influences operational energy assessment in buildings. The paper adopts two popular thermal-comfort models, viz., ASHRAE comfort standards and TSI by Sharma and Ali to investigate thermal comfort aspects and impact of these comfort models on OE assessment in traditional dwellings. A naturally ventilated vernacular dwelling in Sugganahalli, a village close to Bangalore (India), set in warm - humid climate is considered for present investigations on impact of transition in building materials, change in climatic location and choice of thermal comfort models on energy in buildings. The study includes a rigorous real time monitoring of the thermal performance of the dwelling. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Results of the study and appraisal for appropriate thermal comfort standards for computing operational energy has been presented and discussed in this paper. (c) 2014 K.I. Praseeda. Published by Elsevier Ltd.

Impacts of modern transitions on thermal comfort in vernacular dwellings in warm-humid climate of Sugganahalli (India)

Sugganahalli, a rural vernacular community in a warm-humid region in South India, is under transition towards adopting modern construction practices. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete (RCC)/tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Vernacular architecture evolves adopting local resources in response to the local climate adopting passive solar designs. This paper investigates the effectiveness of passive solar elements on the indoor thermal comfort by adopting modern climate-responsive design strategies. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Age-old traditional design considerations were found to concur with modern understanding into bio-climatic response and climate-responsiveness. Modern transitions were found to increase the average indoor temperatures in excess of 7 degrees C. Such transformations tend to shift the indoor conditions to a psychrometric zone that is likely to require active air-conditioning. Also, the surveyed thermal sensation votes were found to lie outside the extended thermal comfort boundary for hot developing countries provided by Givoni in the bio-climatic chart.

PMV model is insufficient to capture subjective thermal response from Indians

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 degrees C to 33 degrees C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with subject's physiological parameters (skin (T-sk) and oral temperature (T-c)) and subjective thermal sensation responses (TSV). From T-sk and T-c, body temperature (T-b) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's T-sk equation was used to accommodate adaptive response. Step-wise regression analysis result showed T-b was better predictor of TSV than T-sk and T-c. Regional skin temperature response, suppressed sweating without dipping, lower sweating threshold temperature and higher cutaneous threshold for sweating were observed as thermal adaptive responses. These adaptive responses cannot be considered in PMV model. To incorporate subjective adaptive response, mean skin temperature (T-sk) is considered in dry heat loss calculation. Along with these, PMV-model and other two methodologies are adopted to calculate PMV values and results are compared. However, recent literature is limited to measure the sweat rate in Indians and consideration of constant Ersw in PMV model needs to be corrected. Using measured T-sk in PMV model (Method(1)), thermal comfort zone corresponding to 0.5 <= PMV <= 0.5 was evaluated as (22.46-25.41) degrees C with neutral temperature of 23.91 degrees C, similarly while using TSV response, wider comfort zone was estimated as (23.25-26.32) degrees C with neutral temperature at 24.83 degrees C, which was further increased to with TSV-PPDnew, relation. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained from the population distribution of TSV response with an asymmetric distribution of hot-cold thermal sensation response from Indians. The calculations of human thermal stress according to steady state energy balance models used on PMV model seem to be inadequate to evaluate human thermal sensation of Indians. Relevance to industry: The purpose of this paper is to estimate thermal comfort zone and optimum temperature for Indians. It also highlights that PMV model seems to be inadequate to evaluate subjective thermal perception in Indians. These results can be used in feedback control of HVAC systems in residential and industrial buildings. (C) 2014 Elsevier B.V. All rights reserved.

Physiological and subjective thermal response from Indians

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 degrees C to 33 degrees C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with skin (T-sk) and oral temperature (T-core) from the subjects. From T-sk and T-c, body temperature (T-b) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's T-sk equation was used to accommodate adaptive response. Stepwise regression analysis result showed T-b was better predictor of TSV than T-sk and T-core. Regional skin temperature response, lower sweat threshold temperature with no dipping sweat and higher cutaneous sweating threshold temperature were observed as thermal adaptive responses. Using PMV model, thermal comfort zone was evaluated as (22.46-25.41) degrees C with neutral temperature of 23.91 degrees C, whereas using TSV response, wider comfort zone was estimated as (23.25-2632) degrees C with neutral temperature at 24.83 degrees C. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained with an asymmetric distribution of hot-cold thermal sensation response in Indians. (C) 2013 Elsevier Ltd. All rights reserved.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Design of a climate-responsive BIPV research facility in Bangalore

This paper describes the design and erection of a climate-responsive Building Integrated Photovoltaic (BIPV) structure in Bangalore, (12.58 N, 77.38 E) in the state of Karnataka, India. Building Integrated Photovoltaics integrate solar panels as part of a building structure (roofs and walls) with an aim to achieve self-sufficiency in the operation and occupant-comfort energy requirements. A joint collaboration between the Centre for Sustainable Technologies, Indian Institute of Science (IISc) and Bharat Heavy Electricals Limited (BHEL) is setting up a 70,000 US$ facility for research in BIPV structures. The structure utilizes low energy building materials like Stabilized Mud Blocks (SMB) integrated with a PV roof. Numerous challenges were overcome in the design of the BIPV roof including mechanisms for natural thermal comfort in response to Bangalore's climatic conditions. The paper presents the challenges overcome in the design and construction of a low energy, climate-responsive BIPV structure.

Speeded up Gaussian mixture model algorithm for background subtraction

Adaptive Gaussian Mixture Models (GMM) have been one of the most popular and successful approaches to perform foreground segmentation on multimodal background scenes. However, the good accuracy of the GMM algorithm comes at a high computational cost. An improved GMM technique was proposed by Zivkovic to reduce computational cost by minimizing the number of modes adaptively. In this paper, we propose a modification to his adaptive GMM algorithm that further reduces execution time by replacing expensive floating point computations with low cost integer operations. To maintain accuracy, we derive a heuristic that computes periodic floating point updates for the GMM weight parameter using the value of an integer counter. Experiments show speedups in the range of 1.33 - 1.44 on standard video datasets where a large fraction of pixels are multimodal.

Cell (module) temperature regulated performance of a building integrated photovoltaic system in tropical conditions

The performance of a building integrated photovoltaic system (BIPV) has to be commendable, not only on the electrical front but also on the thermal comfort front, thereby fulfilling the true responsibility of an energy providing shelter. Given the low thermal mass of BIPV systems, unintended and undesired outcomes of harnessing solar energy - such as heat gain into the building, especially in tropical regions - have to be adequately addressed. Cell (module) temperature is one critical factor that affects both the electrical and the thermal performance of such installations. The current paper discusses the impact of cell (module) temperature on both the electrical efficiency and thermal comfort by investigating the holistic performance of one such system (5.25 kW(p)) installed at the Centre for Sustainable Technologies in the Indian Institute of Science, Bangalore. Some recommendations (passive techniques) for improving the performance and making BIPV structures thermally comfortable have been listed out. (C) 2014 Elsevier Ltd. All rights reserved.

Discerning heat transfer in building materials

The function of a building is to ensure safety and thermal comfort for healthy living conditions. Buildings primarily comprise an envelope, which acts as an interface separating the external environment from the indoors environment. The building envelope is primarily responsible for regulating indoor thermal comfort in response to external climatic conditions. It usually comprises a configuration of building materials to thus far provide requisite structural performance. However, studies into building-envelope configurations to provide a particular thermal performance are limited. As the building envelope is exposed to the external environment there will be heat and moisture transfer to the indoor environment through it. The overall phenomenon of heat and moisture transfer depends on the microstructure and configuration within the building material. Further, thermal property of a material is generally dependent on its microstructure, which comprises a network of pores and particles arranged in a definite structure. Thermal behaviour of a building material thus depends on the thermal conductivities of the solid particles, pore micro-structure and its constituent fluid (air and/or moisture). The thermal response of a building envelope is determined by the thermal characteristics of the individual building materials and its configuration. Understanding the heat transfer influenced by the complex networks of pores and particles is a relatively new study in the area of building climatic-response. The current study reviews the heat-transfer mechanisms that determine the thermal performance of a building material attributed to its micro-structure. A theoretical basis for the same is being evolved and its relevance in regulating heat-transfer through building envelopes, walls in particular, is reviewed in this paper. (C) 2014 N.C. Balaji. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Disaggregation of LST over India: comparative analysis of different vegetation indices

The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.

Thermal decomposition of doped calcium hydroxide for chemical energy storage

Thermal decomposition of Ca(OH)2 with and without additives has been experimentally investigated for its application as a thermochemical energy storage system. The homogeneous reaction model gives a satisfactory fit for the kinetic data on pure and Ni(OH)2---, Zn(OH)2--- and Al(OH)3---doped Ca(OH)2 and the order of reaction is 0.76 in all cases except for the Al(OH)3-doped sample for which the decomposition is zero order. These additives are shown not only to enhance the reaction rate but also to reduce the decomposition temperature significantly. Some models for solid decomposition reactions, and possible mechanisms in the decomposition of solids containing additives, are also discussed.

A simple model for protein thermal denaturation

Whether proteins denature in all-or-none fashion or in a continuous fashion is as yet an unresolved problem. The all-or-none process implies that while the process of denaturation is going on, only two kinds of protein molecules can exist. One is completely unchanged and the other is altered. The altered protein molecules are indistinguishable. Underlying the 'continuum' models is the assumption that all the chains in a protein globule undergo similar changes so that it is enough to consider a single chain.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.