scholarly journals Dynamic analysis of daylight factor, thermal comfort and energy performance under clear sky conditions for building: An experimental validation

2021 ◽  
Author(s):  
Asim Ahmad ◽  
Om Prakash ◽  
Anil Kumar ◽  
S.M. Mozammil Hasnain ◽  
Puneet Verma ◽  
...  
Keyword(s):  
Dynamic Analysis ◽  
Thermal Comfort ◽  
Experimental Validation ◽  
Energy Performance ◽  
Clear Sky ◽  
Sky Conditions

A daylight factor model under clear sky conditions for building: An experimental validation

Solar Energy ◽  
2015 ◽  
Vol 115 ◽  
pp. 379-389 ◽  
Author(s):  
Madhu Sudan ◽  
G.N. Tiwari ◽  
I.M. Al-Helal
Keyword(s):  
Experimental Validation ◽  
Factor Model ◽  
Clear Sky ◽  
Sky Conditions

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

Efficient downscaling of satellite oceanographic data with convolutional neural networks

2021 ◽  
Vol 12 (3) ◽  
pp. 46-47
Author(s):  
Nikita Saxena
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Super Resolution ◽  
Sea Surface ◽  
Clear Sky ◽  
Oceanographic Data ◽  
Computationally Expensive ◽  
Sky Conditions ◽  
Data Inference

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.

scholarly journals Experimental Data and Simulations of Performance and Thermal Comfort in a Typical Mediterranean House

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3311
Author(s):  
Víctor Pérez-Andreu ◽  
Carolina Aparicio-Fernández ◽  
José-Luis Vivancos ◽  
Javier Cárcel-Carrasco
Keyword(s):  
Energy Efficiency ◽  
Thermal Comfort ◽  
Energy Demand ◽  
Natural Ventilation ◽  
Thermal Characterization ◽  
Energy Performance ◽  
Building Stock ◽  
Energy Demands ◽  
Dwelling House ◽  
Account Standard

The number of buildings renovated following the introduction of European energy-efficiency policy represents a small number of buildings in Spain. So, the main Spanish building stock needs an urgent energy renovation. Using passive strategies is essential, and thermal characterization and predictive tests of the energy-efficiency improvements achieving acceptable levels of comfort for their users are urgently necessary. This study analyzes the energy performance and thermal comfort of the users in a typical Mediterranean dwelling house. A transient simulation has been used to acquire the scope of Spanish standards for its energy rehabilitation, taking into account standard comfort conditions. The work is based on thermal monitoring of the building and a numerical validated model developed in TRNSYS. Energy demands for different models have been calculated considering different passive constructive measures combined with real wind site conditions and the behavior of users related to natural ventilation. This methodology has given us the necessary information to decide the best solution in relation to energy demand and facility of implementation. The thermal comfort for different models is not directly related to energy demand and has allowed checking when and where the measures need to be done.

scholarly journals Thermal Dynamic Behavior in Bi-Zone Habitable Cell with and without Phase Change Materials

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 41
Author(s):  
Hanae El Fakiri ◽  
Lahoucine Ouhsaine ◽  
Abdelmajid El Bouardi
Keyword(s):  
Thermal Behavior ◽  
Thermal Comfort ◽  
Phase Change ◽  
Dynamic Behavior ◽  
Phase Change Materials ◽  
Energy Performance ◽  
High Energy ◽  
Water Heater ◽  
Simplified Modeling

The thermal dynamic behavior of buildings represents an important aspect of the energy efficiency and thermal comfort of the indoor environment. For this, phase change material (PCM) wallboards integrated into building envelopes play an important role in stabilizing the temperature of the human comfort condition. This article provides an assessment of the thermal behavior of a “bi-zone” building cell, which was built based on high-energy performance (HEP) standards and heated by a solar water heater system through a hydronic circuit. The current study is based on studying the dynamic thermal behavior, with and without implantation of PCMs on envelope structure, using a simplified modeling approach. The evolution of the average air temperature was first evaluated as a major indicator of thermal comfort. Then, an evaluation of the thermal behavior’s dynamic profile was carried out in this study, which allowed for the determination of the PCM rate anticipation in the thermal comfort of the building cell.

scholarly journals Occupant behaviour and thermal comfort in buildings: Monitoring the end user

2019 ◽  
Vol 111 ◽  
pp. 04056
Author(s):  
Loes Visser ◽  
Boris Kingma ◽  
Eric Willems ◽  
Wendy Broers ◽  
Marcel Loomans ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
Energy Performance ◽  
The Body ◽  
Activity Level ◽  
Biophysical Model ◽  
Zone Model ◽  
Occupant Behaviour ◽  
Ambient Conditions ◽  
Skin Temperatures ◽  
Thermoregulatory Behaviour

Studies indicate that the energy performance gap between real and calculated energy use can be explained for 80% by occupant behaviour. This human factor may be composed of routine and thermoregulatory behaviour. When occupants do not feel comfortable due to high or low operative temperatures and resulting high or low skin temperatures, they are likely to exhibit thermoregulatory behaviour. The aim of this study is to monitor and understand this thermoregulatory behaviour of the occupant. This is a detailed study of two females living in a rowhouse in the city of Heerlen (Netherlands). During a monitoring period of three weeks over a time span of three months the following parameters were monitored: activity level, clothing, micro climate, skin temperatures and thermal comfort and sensation. Their micro climate was measured at five positions on the body to assess exposed near body conditions and skin temperature. Every two hours they filled in a questionnaire regarding their thermal comfort and sensation level (7-point scale), clothing, activities and thermoregulatory behaviour. The most comfortable (optimal) temperature was calculated for each person by adopting a biophysical model, a thermoneutral zone model. This study shows unique indivual comfort patterns in relation to ambient conditions. An example is given how this information can be used to calculate the buildings energy comsumption.

Intra-Day DNI Forecasting Under Clear Sky Conditions Using ANFIS

2014 ◽  
Vol 47 (3) ◽  
pp. 10361-10366 ◽  
Author(s):  
Rémi Chauvin ◽  
Julien Nou ◽  
Stéphane Thil ◽  
Stéphane Grieu
Keyword(s):  
Clear Sky ◽  
Sky Conditions

scholarly journals A Blended Sea Ice Concentration Product from AMSR2 and VIIRS

2021 ◽  
Vol 13 (15) ◽  
pp. 2982
Author(s):  
Richard Dworak ◽  
Yinghui Liu ◽  
Jeffrey Key ◽  
Walter N. Meier
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Infrared Imaging ◽  
High Spatial Resolution ◽  
Sea Ice Concentration ◽  
Clear Sky ◽  
Ice Concentration ◽  
Best Linear Unbiased ◽  
The Individual ◽  
Sky Conditions

An effective blended Sea-Ice Concentration (SIC) product has been developed that utilizes ice concentrations from passive microwave and visible/infrared satellite instruments, specifically the Advanced Microwave Scanning Radiometer-2 (AMSR2) and the Visible Infrared Imaging Radiometer Suite (VIIRS). The blending takes advantage of the all-sky capability of the AMSR2 sensor and the high spatial resolution of VIIRS, though it utilizes only the clear sky characteristics of VIIRS. After both VIIRS and AMSR2 images are remapped to a 1 km EASE-Grid version 2, a Best Linear Unbiased Estimator (BLUE) method is used to combine the AMSR2 and VIIRS SIC for a blended product at 1 km resolution under clear-sky conditions. Under cloudy-sky conditions the AMSR2 SIC with bias correction is used. For validation, high spatial resolution Landsat data are collocated with VIIRS and AMSR2 from 1 February 2017 to 31 October 2019. Bias, standard deviation, and root mean squared errors are calculated for the SICs of VIIRS, AMSR2, and the blended field. The blended SIC outperforms the individual VIIRS and AMSR2 SICs. The higher spatial resolution VIIRS data provide beneficial information to improve upon AMSR2 SIC under clear-sky conditions, especially during the summer melt season, as the AMSR2 SIC has a consistent negative bias near and above the melting point.

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