Numerical Simulation of Heat Exchanges for a Desert House Type ADRAR

2017 ◽  
Vol 24 ◽  
pp. 63-75 ◽  
Author(s):  
A. Oudrane ◽  
B. Aour
Keyword(s):  
Ambient Temperature ◽  
Thermal Inertia ◽  
Research Unit ◽  
Meridian Plane ◽  
Algebraic Equations ◽  
Climate Data ◽  
Nodal Method ◽  
Recent Climate ◽  
Wind Exposure ◽  
Heat Exchanges

The main objective of this work is to study the thermal exchanges in a habitable enclosure located in a desert region of Algeria (Adrar). This latter is considered as an air volume of parallelepiped shape limited by horizontal and vertical flat walls. The walls are the only capacitive elements of the enclosure. They are thermally coupled by convection and radiation and are the seat of conductive flux. The external facades of the enclosure are the seat of a convective flux with the external air and radiative exchanges with the environment (ground and sky). Openings (cracks, sealing defects, infiltration orifices, renewal orifices, etc.) allow the air to circulate inside the habitable enclosure and between the inside and the outside. Thermal exchanges are studied using the balance equations established at each wall of the enclosure. These equations have been discretized by an implicit finite difference method. The systems of algebraic equations thus obtained have been solved by the Gauss algorithm using the nodal method. The effects of the outdoor ambient temperature, the density of the incident solar flux on the facades and the orientation of the habitable enclosure in the meridian plane on the temperature distributions of the internal walls and the filled air in the enclosure havec been analyzed on the basis of recent climate data measured at the ADRAR Saharan Renewable Energy Research Unit. An analysis of the evolution of the internal ambient temperature as a function of the wind exposure factor of the heated space and of the degree of leaktightness of the doors and windows was also carried out at the end of this work. An acceptable agreement was found between the numerical results and those measured by the radiometric station. Moreover, the results obtained show that the building material used in this region causes undesirable overheating due to its thermal inertia.

scholarly journals Multi-Criteria Performance Evaluation of Gridded Precipitation and Temperature Products in Data-Sparse Regions

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1597
Author(s):  
Ibrahim Mohammed Lawal ◽  
Douglas Bertram ◽  
Christopher John White ◽  
Ahmad Hussaini Jagaba ◽  
Ibrahim Hassan ◽  
...  
Keyword(s):  
Decision Making ◽  
Performance Metrics ◽  
Research Unit ◽  
Climate Data ◽  
Meteorological Forcing ◽  
Lake Chad ◽  
Climate Research ◽  
Princeton University ◽  
Lake Chad Basin ◽  
Precipitation And Temperature

Inadequate climate data stations often make hydrological modelling a rather challenging task in data-sparse regions. Gridded climate data can be used as an alternative; however, their accuracy in replicating the climatology of the region of interest with low levels of uncertainty is important to water resource planning. This study utilised several performance metrics and multi-criteria decision making to assess the performance of the widely used gridded precipitation and temperature data against quality-controlled observed station records in the Lake Chad basin. The study’s findings reveal that the products differ in their quality across the selected performance metrics, although they are especially promising with regards to temperature. However, there are some inherent weaknesses in replicating the observed station data. Princeton University Global Meteorological Forcing precipitation showed the worst performance, with Kling–Gupta efficiency of 0.13–0.50, a mean modified index of agreement of 0.68, and a similarity coefficient SU = 0.365, relative to other products with satisfactory performance across all stations. There were varying degrees of mismatch in unidirectional precipitation and temperature trends, although they were satisfactory in replicating the hydro-climatic information with a low level of uncertainty. Assessment based on multi-criteria decision making revealed that the Climate Research Unit, Global Precipitation Climatology Centre, and Climate Prediction Centre precipitation data and the Climate Research Unit and Princeton University Global Meteorological Forcing temperature data exhibit better performance in terms of similarity, and are recommended for application in hydrological impact studies—especially in the quantification of projected climate hazards and vulnerabilities for better water policy decision making in the Lake Chad basin.

scholarly journals Rule-Based Control Strategy to Increase Photovoltaic Self-Consumption of a Modulating Heat Pump Using Water Storages and Building Mass Activation

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6282
Author(s):  
Maria Pinamonti ◽  
Alessandro Prada ◽  
Paolo Baggio
Keyword(s):  
Boundary Conditions ◽  
Heat Pump ◽  
Control Strategy ◽  
Control Strategies ◽  
Residential Buildings ◽  
Thermal Inertia ◽  
The Self ◽  
Thermal Mass ◽  
Climate Data ◽  
Rule Based

The use of photovoltaic (PV) energy in combination with heat pump systems for heating and cooling of residential buildings can lead to renewable energy self-consumption, reducing the energy required from the grid and the carbon footprint of the building uses. However, energy storage technologies and control strategies are essential to enhance the self-consumption level. This paper proposes and analyzes a new control strategy for the operation of a modulating air-source heat pump, based on the actual PV availability. The solar energy surplus is stored as thermal energy by the use of water tanks and the activation of the thermal capacitance of the building. The efficacy of the control strategy is evaluated considering different rule-based strategies, and different boundary conditions. The effect of climate data, building insulation level and thermal inertia are investigated and compared. The results show the efficacy of the proposed strategy to decrease up to 17% the amount of electricity purchased from the grid and to increase the self-consumption by 22%, considering a high-insulated building in Bolzano, Northern Italy. The thermal mass activation is found effective to increase the self-consumption of the system. Nonetheless, the achievable energy reduction depends largely on the building characteristics and the boundary conditions.

Analysis of Rice Yield in CHINA by Climate Change using Deep Neural Network

2020 ◽  
Author(s):  
Su-Bin Cho ◽  
Yang-Won Lee
Keyword(s):  
Neural Network ◽  
Climate Change ◽  
Deep Neural Network ◽  
Rice Yield ◽  
Research Unit ◽  
United States Department ◽  
Climate Data ◽  
Department Of Agriculture ◽  
Meteorological Observations ◽  
The Relationship

<p>Climate change is an important factor in crop growth, and it is significant to understand the relationship between climate change and rice yield. This study used annual rice yield from the USDA(United States Department of Agriculture) for each of China’s 16 administrative regions from 1979 to 2009, as well as average climate data from July to August, which were meteorological observations collected from the CRU(Climate Research Unit). The relationship between selected rice yield and climate change was nonlinear and modelled using a deep neural network to train even rows and verify odd rows of data. This study is expected to contribute to better food self-sufficiency and forecast future grain yields in China.</p>

Effects of Viewing Distance, Low Ambient Temperature and Wind Exposure on Binocular Depth Discrimination

1969 ◽  
Vol 28 (2) ◽  
pp. 647-656
Author(s):  
John L. Kobrick
Keyword(s):  
Ambient Temperature ◽  
Exposure Duration ◽  
Relative Sensitivity ◽  
Viewing Distance ◽  
Ambient Temperatures ◽  
Depth Discrimination ◽  
Wind Exposure ◽  
Natural Terrain ◽  
Main Effects ◽  
Binocular Depth

A study was conducted of the effects of exposure to combinations of low ambient temperatures (70°, 20°, 0°, −20°, −40°F) and wind (3, 10, 20, 30 mph) upon binocular depth discrimination at three viewing distances (20, 40, 60 ft.). 60 groups of 8 Ss each were randomly assigned to one of 60 possible treatment combinations in a factorial design, and binocularly performed depth equality settings using the Howard-Dolman task. The results indicated significant main effects for temperature, wind, and viewing distance, as well as a significant T × W interaction, which occurred for a very brief exposure duration of 1 min. The results are interpreted in light of previous findings for binocular viewing over natural terrain, supporting the notion of two types of stereoscopic threshold, i.e., true stereopsis (ηt) and relative sensitivity in commonplace viewing (ηR).

scholarly journals Technical Note: Low Cost Mesocosms Design for Studies of Tropical Marine Environments

2019 ◽  
Author(s):  
Ruben R. Raygosa-Barahona ◽  
Sebastien Putzeys ◽  
Jorge Herrera ◽  
Daniel Pech
Keyword(s):  
Ambient Temperature ◽  
Aquatic Environment ◽  
Low Cost ◽  
Thermal Inertia ◽  
Climatic Conditions ◽  
Technical Note ◽  
Cooling Systems ◽  
Temperature Variations ◽  
Tropical Environments

Abstract. Mesocosms are an alternative to in situ ocean environmental studies which are very difficult to implement due to the challenges that the aquatic environment impose. The design of a mesocosm should consider as many variables as possible of the ecosystem to be studied, in order to obtain results that are similar to those that would be obtained in the environment. The effects of tropical climatic conditions on a mesocosm enclosure were studied in order to evaluate their possible influence on the biological community. The mesocosm was equipped with an electric marine thruster as a means of avoiding stratification in the water contained in it. Also, the system is submerged in water to increase the thermal inertia and maintain the temperature variations within reasonable ranges. The design does not include auxiliary forcing cooling systems. The results revealed the influence of climatology on the mesocosms’ temperature and showed the feasibility of the proposed design in tropical environments. With high variations of ambient temperature (> 20 ºC, during the day), the variations in the mesocosm temperature were only 3 ºC. The range of temperature variations were similar to those that occur in certain tropical environments.

scholarly journals Integrated Heat and Electricity Dispatch for District Heating Networks with Constant Mass Flow: A Generalized Phasor Method

2020 ◽  
Author(s):  
Yuwei Chen ◽  
Qinglai Guo ◽  
Hongbin Sun ◽  
Zhaoguang Pan
Keyword(s):  
Mass Flow ◽  
Electrical Power ◽  
Thermal Inertia ◽  
District Heating ◽  
Continuous Model ◽  
Discrete Models ◽  
Convex Programming Problem ◽  
Algebraic Equations ◽  
Constant Mass ◽  
Electrical Power System

Using thermal inertia in district heating systems (DHSs) to improve the dispatch flexibility and economy of integrated heat and electricity systems (IHESs) is a research hotspot and difficulty. In most existing studies, the partial differential equations (PDEs) of thermal inertia are approximated by discrete-time models, making it difficult to accurately describe the continuous dynamic processes. In this paper, we propose a novel generalized phasor method (GPM) for thermal inertia in DHSs with constant mass flow. Based on the analytical solution of the PDEs and the Fourier transform, the intractable PDEs are transformed into a series of complex algebraic equations represented by phasors. The GPM has higher accuracy compared to traditional discrete models because it is essentially a continuous model in the time domain. Then, we present a different representation of an integrated heat and electricity dispatch (IHED) model combining a DHS model in phasor form and a traditional electrical power system model. The IHED model is a convex programming problem and can be easily solved. The effectiveness of the proposed GPM and dispatch model is verified in three test systems. Compared with traditional methods for modeling the thermal inertia, the proposed GPM is more accurate.

scholarly journals DEEP LEARNING-BASED ANALYSIS OF THE RELATIONSHIPS BETWEEN CLIMATE CHANGE AND CROP YIELD IN CHINA

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 93-95
Author(s):  
S. Cho ◽  
Y.-W. Lee
Keyword(s):  
Climate Change ◽  
Rice Yield ◽  
Research Unit ◽  
Rice Production ◽  
United States Department ◽  
Climate Data ◽  
Department Of Agriculture ◽  
Vegetation Growth ◽  
Meteorological Observations ◽  
The Relationship

<p><strong>Abstract.</strong> Climate change is an important factor in vegetation growth, and it is very significant to understand the relationship between climate change and rice yield. China is a food-importing country whose grain consumption is higher than grain production, and which relies on imports of rice, soybean, wheat and other grains. Therefore, in order to secure food security for 1.6 billion people in China, it is necessary to grasp the relationship between climate change and rice yield. In this study, 16 administrative districts in China were selected and designated as study area. This study used annual rice production from the USDA (United States Department of Agriculture) for each of China’s major administrative regions from 1979 to 2009, as well as average climate data from July to August, which were meteorological observations collected from the CRU (Climate Research Unit). Using this data, the rice crop was increased in 10 administrative regions in China and the reduction in rice harvest in 6 administrative areas was confirmed. The relationship between selected rice production and climate change was nonlinear and modelled using a deep neural network, and the validation statistics showed that the performance of DNN was 32-33% better than that of MLR (multiple linear regression). Therefore, a more quantitative analysis of the relationship between climate change and rice yield changes has been made possible through our prediction model. This study is expected to contribute to better food self-sufficiency in China and forecast future grain yields.</p>

scholarly journals Climate variability slows evolutionary responses of Colias butterflies to recent climate change

2015 ◽  
Vol 282 (1802) ◽  
pp. 20142470 ◽  
Author(s):  
Joel G. Kingsolver ◽  
Lauren B. Buckley
Keyword(s):  
Climate Variability ◽  
Climate Warming ◽  
Fitness Function ◽  
Natural Populations ◽  
Directional Selection ◽  
Climate Data ◽  
Egg Survival ◽  
The Past ◽  
Recent Climate ◽  
Mean Climate

How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii , in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias . Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats.

scholarly journals Future retreat of Great Aletsch Glacier

2019 ◽  
Vol 65 (253) ◽  
pp. 869-872 ◽  
Author(s):  
Guillaume Jouvet ◽  
Matthias Huss
Keyword(s):  
Emission Scenario ◽  
Climate Projections ◽  
European Alps ◽  
Climate Data ◽  
Three Dimensional Model ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Climate Conditions ◽  
Future Evolution ◽  
Recent Climate

AbstractWe model the future evolution of the largest glacier of the European Alps – Great Aletsch Glacier, Switzerland – during the 21st century. For that purpose we use a detailed three-dimensional model, which combines full Stokes ice dynamics and surface mass balance forced with the most recent climate projections (CH2018), as well as with climate data of the last decades. As a result, all CH2018 climate scenarios yield a major glacier retreat: Results range from a loss of 60% of today's ice volume by 2100 for a moderate CO2 emission scenario (RCP2.6) being in line with the Paris agreement to an almost complete wastage of the ice for the most extreme emission scenario (RCP8.5). Our model results also provide evidence that half of the mass loss is already committed under the climate conditions of the last decade.

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