Improving Accuracy of Wind Analysis with Multiple Sampling Rates of Wind Measurement

The sampling rate in wind measurement has influences on accuracy of wind analysis. Missing wind data problem can be prevented with high sampling rates. However, a lot of data are unnecessarily required in wind analysis. In this work, optimal sampling rates are determined in real time by the Nyquist sampling theorem according to varying wind conditions. It is found that all statistical results in wind analysis are obtained with percentage errors of less than 1% while the amount of wind data is decreased significantly from the benchmark at fixed sampling rate of 10 Hz

Real-Time Determination of Overall Heat Transfer Coefficient from the Seebeck Effect by Using Adaptive Learning-Rate Optimization

It is challenging to determine the actual overall heat transfer coefficient under thermal conditions during processes. In a conventional approach, they are obtained as a constant with the empirical formula for the given conditions. In this study, the Adaptive moment estimation (Adam) technique is investigated for adaptive learning-rate optimization in the real-time determination of the overall heat transfer coefficient via the Seebeck effect in the thermoelectric modules. Two thermoelectric modules detect heat transfer as solid surfaces exposed to the outdoor air. The principle of energy balance and the Seebeck effect determine the overall heat transfer coefficients over time. The heating/cooling process of a copper plate is considered with exposure to the outdoor air. The overall heat transfer coefficient is determined with the proposed methodology over time. The temperature of the copper plate is numerically determined by the mathematical models with the obtained values of the overall heat transfer coefficient. It is confirmed that the calculated values of temperature are close to the measured values, with RMSE = 0.07 °C

Maximizing cooling/heating performance of thermoelectric modules across variable thermal loads via optimal control based on COP curves

The thermoelectric module has high potential as a compact electrothermal actuator in the generation of cooling/heating effects without any moving part. However, one difficulty of the design is that the fundamental principles of optimal cooling/heating performance of thermoelectric modules are not yet fully understood and implemented. The purpose of this paper is to propose a mathematical optimization to gain insight and implement the most effective usages. In the proposed analysis, it is found that the coefficients of performance (COP) are dependent on the driving voltage and the ceramic-substrate temperatures of the thermoelectric module at both the cold and hot sides. The thermoelectric properties of a 91.2W thermoelectric module are used to simulate the proposed performance analysis to find the optimal driving voltage at desired operating temperatures at both sides on COP curves. The coefficient of determination R2 of 0.9832 indicates strong agreement on the coefficients of performance between the analysis and the experiments under one hundred thirty-seven operating conditions. With the proposed methodology, the 91.2W thermoelectric module can be operated at the maximum coefficient of performance across variable thermal loads of airflow where the optimal driving voltage is determined from desired operating temperatures at both sides