A Markov chain-based stochastic model （MCM） is developed to simulate the movement of particles in a 2D bubbling fluidized bed （BFB）. The state spaces are determined by the discretized physical cells of the bed, an...A Markov chain-based stochastic model （MCM） is developed to simulate the movement of particles in a 2D bubbling fluidized bed （BFB）. The state spaces are determined by the discretized physical cells of the bed, and the transition probability matrix is directly calculated by the results of a discrete element method （DEM） simulation. The Markov property of the BFB is discussed by the comparison results calculated from both static and dynamic transition probability matrices. The static matrix is calculated based on the Markov chain while the dynamic matrix is calculated based on the memory property of the particle movement. Results show that the difference in the trends of particle movement between the static and dynamic matrix calculation is very small. Besides, the particle mixing curves of the MCM and DEM have the same trend and similar numerical values, and the details show the time averaged characteristic of the MCM and also expose its shortcoming in describing the instantaneous particle dynamics in the BFB.展开更多
为研究声屏障降噪的主要影响因素及规律,基于边界元理论,结合高速列车实测声源识别结果,建立了高速铁路声屏障降噪效果预测模型,研究了包括高速列车不同位置声源、声屏障高度、声屏障截面形状和吸声边界条件对插入损失的影响,并在此基...为研究声屏障降噪的主要影响因素及规律,基于边界元理论,结合高速列车实测声源识别结果,建立了高速铁路声屏障降噪效果预测模型,研究了包括高速列车不同位置声源、声屏障高度、声屏障截面形状和吸声边界条件对插入损失的影响,并在此基础上提出了对现役声屏障结构的改进方案.研究结果表明,列车声源高度对声屏障插入损失有重要影响,现有2.15 m高声屏障只对车体下方噪声有降噪效果;随着声屏障高度增加,插入损失逐渐增大,声屏障高于6.15 m时,插入损失达到25 d B（A）以上;对于不同截面形式的声屏障,降噪效果从优到劣依次为Y型、倾斜型、T型、外折型、直立型和内折型,其中Y型比直立型插入损失高0.7～1.5 d B（A）;对于任一类型声屏障,吸声引起的具体降噪效果与声屏障形式有关,有吸声边界条件的降噪效果要优于＂刚性光滑＂边界条件,前者与后者相比,其插入损失可提高0.3～6.4 dB（A）。展开更多
基金The National Science Foundation of China(No.51276036,51306035)the Fundamental Research Funds for the Central Universities(No.KYLX_0114)
文摘A Markov chain-based stochastic model （MCM） is developed to simulate the movement of particles in a 2D bubbling fluidized bed （BFB）. The state spaces are determined by the discretized physical cells of the bed, and the transition probability matrix is directly calculated by the results of a discrete element method （DEM） simulation. The Markov property of the BFB is discussed by the comparison results calculated from both static and dynamic transition probability matrices. The static matrix is calculated based on the Markov chain while the dynamic matrix is calculated based on the memory property of the particle movement. Results show that the difference in the trends of particle movement between the static and dynamic matrix calculation is very small. Besides, the particle mixing curves of the MCM and DEM have the same trend and similar numerical values, and the details show the time averaged characteristic of the MCM and also expose its shortcoming in describing the instantaneous particle dynamics in the BFB.
文摘为研究声屏障降噪的主要影响因素及规律,基于边界元理论,结合高速列车实测声源识别结果,建立了高速铁路声屏障降噪效果预测模型,研究了包括高速列车不同位置声源、声屏障高度、声屏障截面形状和吸声边界条件对插入损失的影响,并在此基础上提出了对现役声屏障结构的改进方案.研究结果表明,列车声源高度对声屏障插入损失有重要影响,现有2.15 m高声屏障只对车体下方噪声有降噪效果;随着声屏障高度增加,插入损失逐渐增大,声屏障高于6.15 m时,插入损失达到25 d B（A）以上;对于不同截面形式的声屏障,降噪效果从优到劣依次为Y型、倾斜型、T型、外折型、直立型和内折型,其中Y型比直立型插入损失高0.7～1.5 d B（A）;对于任一类型声屏障,吸声引起的具体降噪效果与声屏障形式有关,有吸声边界条件的降噪效果要优于＂刚性光滑＂边界条件,前者与后者相比,其插入损失可提高0.3～6.4 dB（A）。
