• Solar Energy
• /
• v.7 no.2
• /
• pp.37-53
• /
• 1987

This study has been prepared for the purpose of developing the system performance prediction method of natural circulation solar hot water system. The storage tank of the natural circulation solar hot water system equipped with flat-plate solar collector is located at higher elevation than the solar collectors. Therefor, the storage tank temperature distribution formed accordance with configuration of storage tank by flow rate of circulating fluid affect system collection efficiency. In this study measure the storage tank temperature distribution with various experimental system under real sun condition and present the theoretical prediction method of the storage tank temperature. Moreover measure the flow rate not only day-time but also night-time reverse flow rate with die injection visual flow meter. Main conclusion obtain from the present study is as follows; 1) The storage tank temperature distribution above the connecting pipe connection position is the same as that of the fully mixed tank and below the connection position is the same as that of stratified tank. 2) The system performance sensitive to the storage tank temperature distribution. Therefore detailed tank model is necessary. Average storage tank temperature can be calculate 3% and storage tank temperature profile can get less than 10% difference with this model system.

• KIEAE Journal
• /
• v.17 no.5
• /
• pp.69-76
• /
• 2017

Purpose: This study aimed at developing an Artificial Neural Network (ANN) model for predicting the amount of cooling energy consumption of the variable refrigerant flow (VRF) cooling system by the different set-points of the control variables, such as supply air temperature of air handling unit (AHU), condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. Applying the predicted results for the different set-points, the control algorithm, which embedded the ANN model, will determine the most energy efficient control strategy. Method: The ANN model was developed and tested its prediction accuracy by using matrix laboratory (MATLAB) and its neural network toolbox. The field data sets were collected for the model training and performance evaluation. For completing the prediction model, three major steps were conducted - i) initial model development including input variable selection, ii) model optimization, and iii) performance evaluation. Result: Eight meaningful input variables were selected in the initial model development such as outdoor temperature, outdoor humidity, indoor temperature, cooling load of the previous cycle, supply air temperature of AHU, condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. The initial model was optimized to have 2 hidden layers with 15 hidden neurons each, 0.3 learning rate, and 0.3 momentum. The optimized model proved its prediction accuracy with stable prediction results.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.11
• /
• pp.13-20
• /
• 2023

In this paper, we propose a water temperature prediction method using feature extraction and reconstructed data based on LSTM-Autoencoder. We used multivariate time series data such as sea surface water temperature in the Naksan area of the East Sea where the cold water zone phenomenon occurred, and wind direction and wind speed that affect water temperature. Using the LSTM-Autoencoder model, we used three types of data: feature data extracted through dimensionality reduction of the original data combined with multivariate data of the original data, reconstructed data, and original data. The three types of data were trained by the LSTM model to predict sea surface water temperature and evaluated the accuracy. As a result, the sea surface water temperature prediction accuracy using feature extraction of LSTM-Autoencoder confirmed the best performance with MAE 0.3652, RMSE 0.5604, MAPE 3.309%. The result of this study are expected to be able to prevent damage from natural disasters by improving the prediction accuracy of sea surface temperature changes rapidly such as the cold water zone.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.92-102
• /
• 2017

Purpose: Reliability prediction standards consider environmental conditions, such as temperature, humidity and vibration in order to predict the reliability of the electronics components. There are many types of standards, and each standard has a different failure rate prediction model, and requires different environmental conditions. The purpose of this study is to make a sensitivity analysis by changing the temperature which is one of the environmental conditions. By observing the relation between the temperature and the failure rate, we perform the sensitivity analysis for standards including MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES. Methods: we establish environmental conditions in accordance with maneuver weapon systems's OMS/MP and mission scenarios then predict the reliability using MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES through the case of DC-DC Converter. Conclusion: Reliability prediction standards show different sensitivities of their failure rates with respect to the changing temperatures.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.9
• /
• pp.2271-2279
• /
• 1993

In the case of life prediction on the structures and machines after long service, it is natural to consider a degradation problems. Most of degradation data form practical structures are isolated data obtained at the time of periodical inspection or repair. From such data, it may be difficult to obtain the degradation curve available and necessary for life prediction. In this paper, for the purpose of obtaining a degradation curves, developed the simulate degradation method and fatigue test and Charpy impact test were conducted on the degraded, simulate degraded and recovered materials. Fatigue life prediction were conducted by using the relationship between fracture transition temperature (DBTT : vTrs) obtained from the Charpy impact test through the degradation process and fatigue crack growth constants of m and C obtained from the fatigue test.

• Proceedings of the KSR Conference
• /
• 2009.05a
• /
• pp.1536-1541
• /
• 2009

When water inside the concrete member evaporates by high temperature, the evaporation heat which absorbs surrounding temperature occurs. The rate of increment of the internal temperature in concrete is reduced due to the evaporation heat in spite of continuously increasing external temperature. In this paper, the prediction method of internal temperature of high strength concrete members considering the evaporation heat under the high temperature is presented. Finite element method is employed to facilitate thermal analysis for any position of member. And the thermal characteristics models of high strength concrete affected by high temperature are proposed. To demonstrate the validity of this numerical procedure, the prediction by the proposed algorithm is compared with the test results of other researchers. The proposed algorithm shows a good agreement with the experimental results including the phenomenon that temperature is lost by the evaporation heat.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2001.05a
• /
• pp.307-313
• /
• 2001

In this Paper, friction welding optimization for 1Cr0.5Mo-STS304($\Phi$14mm), AE applications for the weld quality evaluation and the applications of various life prediction methods such as LMP(Larson-Miller Parameter) and ISM(initial strain method) were investigated : the creep behaviors of those steels and the friction welded joints under static load were examined by ISM combined with LMP at 400, 500, 550 and $600^{\circ}C$, and the relationship between these two kinds of phenomena was studied. The real-time predicting equations of elevated-temperature creep life(fracture time) under any creep stress at any elevated- temperature could be developed by LMP and LMP-ISM, It was confirmed that the life prediction equations by LMP and LMP-ISM are effective only up to 10$^2$hrs and can not be used for long times of 10$^3$-10$^{6}$ hrs, but by ISM it can be used for long times creep prediction of more than 10$^4$hrs with most reliability.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2016.05a
• /
• pp.199-200
• /
• 2016

Accurate fire diagnoses are needed to properly repair and strengthen buildings affected by fire. The current diagnosis method of fire takes time and is ineffective. In previous research, Melting point temperature of each sequence to grasp easily the temperature of the concrete up to 200 ~ 600 ℃ was to estimate the temperature by utilizing a different sequence representing material.But In the form of conventional hydrothermal temperature prediction simple measuring device, it is difficult in the future buried in application to the construction site, there is a problem of damage when concrete pouring, and only the extension of life measured by the zinc has a problem does not distinguish between 400 ℃ and 500 ℃. Therefore this study is conducted by utilizing a titanium metal changes the color depending on the temperature to check for the applicability of the simple apparatus for measuring the temperature prediction sequence.

• Journal of Welding and Joining
• /
• v.24 no.1
• /
• pp.77-87
• /
• 2006

Considering ferrite grain size in the base metal, the prediction model for $A_{c3}$ temperature and prior austenite grain size at just above $A_{c3}$ temperature was proposed. In order to predict $A_{c3}$ temperature, the Avrami equation was modified with the variation of ferrite grain size, and its kinetic parameters were measured from non-isothermal data during continuous heating. From calculation using a proposed model, $A_{c3}$ temperatures increased with increasing ferrite grain size and heating rate. Meanwhile, by converting the phase transformation kinetic model that predicts the ferrite grain size from austenite grain size during cooling, a prediction model for prior austenite grain size at just above the $A_{c3}$ temperature during heating was developed.

• Journal of Power System Engineering
• /
• v.6 no.2
• /
• pp.40-47
• /
• 2002

In this paper, friction welding optimization for 1Cr0.5Mo-STS304 (${\phi}14\;mm$), AE applications for the weld quality evaluation and the applications of various life prediction methods such as LMP (Larson-Miller Parameter) and ISM (initial strain method) were investigated : The creep behaviors of those steels and the friction welded joints under static load were examined by ISM combined with LMP at 400, 500, 550 and $600^{\circ}C$, and the relationship between these two kinds of phenomena was studied. The real-time predicting equations of elevated-temperature creep life (rupture time) under any creep stress at any elevated-temperature could be developed by LMP and LMP-ISM. It was confirmed that the life prediction equations by LMP and LMP-ISM are effective only up to 102 h and can not be used for long times of 103-106 h, but by ISM it can be used for long times creep prediction of more than 104 h with most reliability.