scholarly journals 330) On the Periodic Variation of outdoor Temperature and Solar Radiation : For heating load (I)(Scientefic Basis of Planning Building)

1957 ◽  
Vol 57.2 (0) ◽  
pp. 117-120
Author(s):  
Takashi Hirayama ◽  
Heizo Saito ◽  
Koyo Maekawa
Keyword(s):  
Solar Radiation ◽  
Periodic Variation ◽  
Outdoor Temperature ◽  
Heating Load

scholarly journals Selection and Evaluation of influencing Parameters for Heat Load Forecasting Model

2021 ◽  
Vol 252 ◽  
pp. 03027
Author(s):  
Yuli Wu ◽  
Rui Li
Keyword(s):  
Prediction Model ◽  
Temperature Difference ◽  
Hot Water ◽  
Outdoor Temperature ◽  
Domestic Hot Water ◽  
Model Input ◽  
Average Temperature ◽  
Average Temperature Difference ◽  
Input Parameters ◽  
Heating Load

This paper analyses the factors affecting the heating consumption of a heating substation. The input parameters of neural network prediction model are analysed and selected. The average absolute error, average absolute percentage error, and mean square error are used to evaluate the effect of the prediction model. The results show that when the model input parameters are the maximum outdoor temperature, the average outdoor temperature, the average temperature difference between the primary supply and return of domestic hot water, the heating load in the previous three days, the heating load in the previous two days, the heating load in the previous day and when the model input parameters are the maximum outdoor temperature, the minimum outdoor temperature, the average outdoor temperature, the average temperature difference between the primary supply and return of domestic hot water, the heating load of the previous three days, the heating load of the previous two days, the heating load of the previous day, the effects are better.

A test development of a data driven model to simulate chlorophyll data at Tongyeong bay in Korea

2020 ◽  
Author(s):  
Sung Dae Kim ◽  
Sang Hwa Choi
Keyword(s):  
Solar Radiation ◽  
Periodic Variation ◽  
Training Data ◽  
Training Dataset ◽  
Sequence Length ◽  
Observation Data ◽  
The Public ◽  
Ocean Science ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Hidden Layer

<p>A pilot machine learning(ML) program was developed to test ML technique for simulation of biochemical parameters at the coastal area in Korea. Temperature, chlorophyll, solar radiation, daylight time, humidity, nutrient data were collected as training dataset from the public domain and in-house projects of KIOST(Korea Institute of Ocean Science & Technology). Daily satellite chlorophyll data of MODIS(Moderate Resolution Imaging Spectroradiometer) and GOCI(Geostationary Ocean Color Imager) were retrieved from the public services. Daily SST(Sea Surface Temperature) data and ECMWF solar radiation data were retrieved from GHRSST service and Copernicus service. Meteorological observation data and marine observation data were collected from KMA (Korea Meteorological Agency) and KIOST. The output of marine biochemical numerical model of KIOST were also prepared to validate ML model. ML program was configured using LSTM network and TensorFlow. During the data processing process, some chlorophyll data were interpolated because there were many missing data exist in satellite dataset. ML training were conducted repeatedly under varying combinations of sequence length, learning rate, number of hidden layer and iterations. The 75% of training dataset were used for training and 25% were used for prediction. The maximum correlation between training data and predicted data was 0.995 in case that model output data were used as training dataset. When satellite data and observation data were used, correlations were around 0.55. Though the latter corelation is relatively low, the model simulated periodic variation well and some differences were found at peak values. It is thought that ML model can be applied for simulation of chlorophyll data if preparation of sufficient reliable observation data were possible.</p>

scholarly journals Experimental Validation of EnergyPlus® Simulation of a Single Storey Building

2011 ◽  
Vol 2 (1) ◽  
pp. 12-17 ◽  
Author(s):  
Azhaili Baharun ◽  
Siti Halipah Ibrahim ◽  
Mohammad Omar Abdullah ◽  
Ooi Koon Beng
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Indoor Air ◽  
Experimental Validation ◽  
Global Solar Radiation ◽  
Outdoor Temperature ◽  
Night Time ◽  
The Heat Balance ◽  
Red Radiation ◽  
Storey Building

EnergyPlus® simulated indoor temperatures of a single storey building at the east campus of Universiti Malaysia Sarawak, for April and June, are validated with measurements taken in 2007.The measured local outdoor temperature was used together with the global solar radiation, wind velocity, relative humidity and cloud cover measured at the Kuching airport to replace the typical meteorological year (TMY) values in the EnergyPlus® weather (EPW) file to fonn a Modified EPW weather file at the time/date of experiments. The remaining fields of the Modified EPW contain TMY data including the direct and diffuse solar radiations and the 'sky's' infrared radiation, which is also present at night.Analysis of the temperatures at the windows simulated with the EPW and Modified EPW weather files for the April and June experiments show the strong influence of the outdoor temperature and importance of the global solar radiation in the weather file and local outdoor temperature is used in the Modified EPW.Day time peak mismatches between the measured indoor air temperature and the indoor air temperature simulated with the Modified EPW is 2 to 3 deg C. These are due to the use of the TMY direct and diffuse solar radiations in the heat balance algorithms at the outside surfaces. The corresponding night time mismatches are less than 1 deg C because the TMY values of the long wave infra-red radiation emitted from molecules and particles in the atmosphere in the Modified EPW are used in simulation.

scholarly journals Glazed balconies impact on energy consumption of multi-story buildings

2019 ◽  
Vol 111 ◽  
pp. 06079
Author(s):  
Tiberiu Catalina ◽  
Daniel Bortis ◽  
Andreea Vartires ◽  
Cătălin Lungu
Keyword(s):  
Energy Consumption ◽  
Solar Radiation ◽  
Total Energy ◽  
Energy Saving ◽  
Thermal Performance ◽  
Energy Demand ◽  
Cold Period ◽  
Outdoor Temperature ◽  
Good Energy ◽  
The Difference

Through this research we have studied the influence of the closure of the balconies on the temperature and humidity. Three residential apartments with enclosed balconies are monitored simultaneously over two periods: a colder one in March and a warmer one in May providing an overview of the thermal performance of a balcony relative to the interior. The results of the balcony#1 simulations made with the Trnsys 17 software show a good energy saving in the cold period, but higher cooling consumption in warm weather.The total energy demand difference between closed and open balconies is about 840 kWh. The simulation also showed us the close connection between the temperature in the balcony and the solar radiation that both grow and decrease simultaneously. At the end of the two campaigns, we came to the conclusion that a closed and thermally rehabilitated balcony is the best solution, being proven to have a winter advantage, the difference between the outdoor temperature and the balcony temperature being around 15 °C, but a summer disadvantage when temperatures in the balcony greatly increase and may exceed 50 °C, with the risk of overheating the balcony.

scholarly journals Reuse Waste Material and Carbon Dioxide Emissions to Save Energy and Approach Sustainable Lightweight Portable Shelters

2020 ◽  
Vol 24 (1) ◽  
pp. 143-161
Author(s):  
Ammar Alkhalidi ◽  
Yara Nidal Zaytoun
Keyword(s):  
Solar Radiation ◽  
Carbon Dioxide Emissions ◽  
Concrete Slab ◽  
Winter Season ◽  
Thermal Storage ◽  
Thermal Mass ◽  
Night Time ◽  
Lightweight Structures ◽  
Heating Load ◽  
Simulation Results

AbstractDespite their great significance, lightweight structures have poor thermal inertia. In order to enhance the thermal comfort inside such buildings, architects need lightweight thermal storage. In this paper a model was used to experimentally investigate Heating Load profiles in lightweight shelters. The profiles were created for the climate in Jordan, then simulated for other climate zones. The proposed design concept was used to create a replacement for a thermal mass in lightweight structures such as shelters; by combining passive solar gain with energy storage embodied within the shelter floor (thermal-floor) to absorb solar radiation. This shelter design decreased the Heating Load during the winter season by acting as heat storage that releases energy at night time after being exposed to solar radiation during the day. The passive design depends on shading elements and overhangs shades to control solar gain during different seasons to prevent overheating during the summer. An experimental investigation of this model was performed to validate the simulation results. Validated simulation results showed that the designed thermal-floor is 25 % of the total shelter’s floor area, which was crucial for obtaining favourable results. With CO2 as a thermal mass, heat load was reduced up to 68 % compared to a 20 cm concrete slab floor. The use of this thermal storage material yielded a reduction in annual heating demand by 85 kWh/m2.

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