In rapid thermal processing of a semiconductor wafer, it is important to keep a given temperature rising speed of the wafer during the temperature rising process. We made an experimental apparatus to measure the tempe...In rapid thermal processing of a semiconductor wafer, it is important to keep a given temperature rising speed of the wafer during the temperature rising process. We made an experimental apparatus to measure the temperature rising speed of a ceramic ball of 2 mm in diameter heated with four halogen lamp heaters. The heating rate of the halogen lamp heaters was controlled by computer to keep a given temperature rising speed of 50 ℃/s with a controlling time interval of 0.1 s. We examined the effect of various heating control methods on the error of the temperature rising speed of the ceramic ball. We found that a combined method of control with prepared correlation and PID （proportional integral derivative） control is a good method to decrease the error of the temperature rising speed. The average error of the temperature rising speed is 0.5 ℃/s, and the repetition error is almost zero for the temperature rising speed of 50 ℃/s from 330 ℃ to 370 ℃. We also measured the effects of artificial control delay time and measuring error of the monitoring temperature on the error of the temperature rising speed.展开更多
A one-dimensional linear inverse heat conduction problem is studied in this paper.This ill-posed problem is replaced by the perturbed problem with a non-localized boundary condition.After the derivation of its closed-...A one-dimensional linear inverse heat conduction problem is studied in this paper.This ill-posed problem is replaced by the perturbed problem with a non-localized boundary condition.After the derivation of its closed-form analytical solution,the calculation error can be determined by the comparison between the numerical and exact solutions.展开更多
Support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, was proposed to establish a model to predict the thermal conductivity of polymer-based composites under d...Support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, was proposed to establish a model to predict the thermal conductivity of polymer-based composites under different mass fractions of fillers (mass fraction of polyethylene (PE) and mass fraction of polystyrene (PS)). The prediction performance of SVR was compared with those of other two theoretical models of spherical packing and flake packing. The result demonstrated that the estimated errors by leave-one-out cross validation (LOOCV) test of SVR models, such as mean absolute error (MAE) and mean absolute percentage error (MAPE), all are smaller than those achieved by the two theoretical models via applying identical samples. It is revealed that the generalization ability of SVR model is superior to those of the two theoretical models. This study suggests that SVR can be used as a powerful approach to foresee the thermal property of polymer-based composites under different mass fractions of polyethylene and polystyrene fillers.展开更多
文摘In rapid thermal processing of a semiconductor wafer, it is important to keep a given temperature rising speed of the wafer during the temperature rising process. We made an experimental apparatus to measure the temperature rising speed of a ceramic ball of 2 mm in diameter heated with four halogen lamp heaters. The heating rate of the halogen lamp heaters was controlled by computer to keep a given temperature rising speed of 50 ℃/s with a controlling time interval of 0.1 s. We examined the effect of various heating control methods on the error of the temperature rising speed of the ceramic ball. We found that a combined method of control with prepared correlation and PID （proportional integral derivative） control is a good method to decrease the error of the temperature rising speed. The average error of the temperature rising speed is 0.5 ℃/s, and the repetition error is almost zero for the temperature rising speed of 50 ℃/s from 330 ℃ to 370 ℃. We also measured the effects of artificial control delay time and measuring error of the monitoring temperature on the error of the temperature rising speed.
文摘A one-dimensional linear inverse heat conduction problem is studied in this paper.This ill-posed problem is replaced by the perturbed problem with a non-localized boundary condition.After the derivation of its closed-form analytical solution,the calculation error can be determined by the comparison between the numerical and exact solutions.
基金supported by the Program for New Century Excellent Talents in University of China (Grant No. NCET-07-0903)the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Ministry of Education, China (Grant No. 2008101-1)+2 种基金the Fundamental Research Funds for the Central Universities (Grant Nos. CDJXS10101107, CDJXS10100037)the Natural Science Foundation of Chongqing, China (Grant No. CSTC2006BB5240)the Innovative Talent Training Project of the Third Stage of "211 Project", Chongqing University (Grant No. S-09109)
文摘Support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, was proposed to establish a model to predict the thermal conductivity of polymer-based composites under different mass fractions of fillers (mass fraction of polyethylene (PE) and mass fraction of polystyrene (PS)). The prediction performance of SVR was compared with those of other two theoretical models of spherical packing and flake packing. The result demonstrated that the estimated errors by leave-one-out cross validation (LOOCV) test of SVR models, such as mean absolute error (MAE) and mean absolute percentage error (MAPE), all are smaller than those achieved by the two theoretical models via applying identical samples. It is revealed that the generalization ability of SVR model is superior to those of the two theoretical models. This study suggests that SVR can be used as a powerful approach to foresee the thermal property of polymer-based composites under different mass fractions of polyethylene and polystyrene fillers.
