以浮式液化天然气存储再气化装置(LNG-Floating Storage and Regasification Unit,LNG-FSRU)为研究对象,针对其常年处于水域中受到波浪的冲击、船体始终处于晃荡状态、对其液舱充注过程中LNG的稳定程度造成影响的问题,采用FLUENT软件,...以浮式液化天然气存储再气化装置(LNG-Floating Storage and Regasification Unit,LNG-FSRU)为研究对象,针对其常年处于水域中受到波浪的冲击、船体始终处于晃荡状态、对其液舱充注过程中LNG的稳定程度造成影响的问题,采用FLUENT软件,选取合适的湍流模型、多相流模型、耦合运动模型等进行数值模拟。假设初始液货舱内LNG密度均匀,没有发生分层,且充注过程中液货舱始终处于运动状态,仿真其内部LNG的扰动变化过程。通过控制变量法,分别设置多组不同的充注速度、充注密度、充注量的情况来进行对比分析。研究成果对LNG-FSRU充注过程中控制LNG稳定性具有一定的参考价值。展开更多
本文采用物理过程扰动方法,针对中国东南地区建立了基于Weather Research and Forecas-ting(WRF)模式的短期集合预报系统.利用美国国家环境预报中心全球数据同化系统的高空资料和预报区域内1000多个站点(包括基准站、基本站和一般站)的...本文采用物理过程扰动方法,针对中国东南地区建立了基于Weather Research and Forecas-ting(WRF)模式的短期集合预报系统.利用美国国家环境预报中心全球数据同化系统的高空资料和预报区域内1000多个站点(包括基准站、基本站和一般站)的地面观测资料对短期集合预报系统2010年5、6月份的预报结果进行了检验,分析了物理过程参数化方案和集合平均方法对气象要素预报效果的影响.结果表明:基于WRF模式的短期集合预报系统对我国东南地区高空及地面要素有一定的预报能力.从单个模式成员和集合平均的结果来看,在整个预报时段(60h)内都能较好地预报;不同高度上的气象要素和不同量级的降水对物理过程参数化方案的敏感性不同,预报效果也存在差异.集合平均方法对于大部分气象要素场的预报效果超过单个模式成员.展开更多
A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for produc...A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.展开更多
A generalized wave-activity density, which is defined as an absolute value of production of three-dimensional vorticity vector perturbation and gradient of general potential temperature perturbation, is introduced and...A generalized wave-activity density, which is defined as an absolute value of production of three-dimensional vorticity vector perturbation and gradient of general potential temperature perturbation, is introduced and its wave-activity law is derived in Cartesian coordinates. Constructed in an agoestrophic and nonhydrostatie dynamical framework, the generalized wave-activity law may be applicable to diagnose mesoscale weather systems leading to heavy rainfall. The generalized wave-activity density and wave-activity flux divergence were calculated with the objective analysis data to investigate the character of wave activity over heavy-rainfall regions. The primary dynamical processes responsible for disturbance associated with heavy rainfall were also analyzed. It was shown that the generalized wave-activity density was closely correlated to the observed 6-h accumulative rainfall. This indicated that the wave activity or disturbance was evident over the frontal and landfall-typhoon heavy-rainfall regions in middle and lower troposphere. For the landfall-typhoon rainband, the portion of generalized wave-activity flux divergence, denoting the interaction between the basic-state cyclonic circulation of landfall typhoon and mesoscale waves, was the primary dynamic process responsible for the evolution of generalized wave-activity density.展开更多
An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong ...An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.展开更多
文摘以浮式液化天然气存储再气化装置(LNG-Floating Storage and Regasification Unit,LNG-FSRU)为研究对象,针对其常年处于水域中受到波浪的冲击、船体始终处于晃荡状态、对其液舱充注过程中LNG的稳定程度造成影响的问题,采用FLUENT软件,选取合适的湍流模型、多相流模型、耦合运动模型等进行数值模拟。假设初始液货舱内LNG密度均匀,没有发生分层,且充注过程中液货舱始终处于运动状态,仿真其内部LNG的扰动变化过程。通过控制变量法,分别设置多组不同的充注速度、充注密度、充注量的情况来进行对比分析。研究成果对LNG-FSRU充注过程中控制LNG稳定性具有一定的参考价值。
文摘本文采用物理过程扰动方法,针对中国东南地区建立了基于Weather Research and Forecas-ting(WRF)模式的短期集合预报系统.利用美国国家环境预报中心全球数据同化系统的高空资料和预报区域内1000多个站点(包括基准站、基本站和一般站)的地面观测资料对短期集合预报系统2010年5、6月份的预报结果进行了检验,分析了物理过程参数化方案和集合平均方法对气象要素预报效果的影响.结果表明:基于WRF模式的短期集合预报系统对我国东南地区高空及地面要素有一定的预报能力.从单个模式成员和集合平均的结果来看,在整个预报时段(60h)内都能较好地预报;不同高度上的气象要素和不同量级的降水对物理过程参数化方案的敏感性不同,预报效果也存在差异.集合平均方法对于大部分气象要素场的预报效果超过单个模式成员.
基金Supported by the National Natural Science Foundation of China （60404012, 60674064）, UK EPSRC （GR/N13319 and GR/R10875）, the National High Technology Research and Development Program of China （2007AA04Z193）, New Star of Science and Technology of Beijing City （2006A62）, and IBM China Research Lab 2007 UR-Program.
文摘A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.
基金National Basic Research Program of China (2009CB421505)National Natural Sciences Foundations of China (40875032)
文摘A generalized wave-activity density, which is defined as an absolute value of production of three-dimensional vorticity vector perturbation and gradient of general potential temperature perturbation, is introduced and its wave-activity law is derived in Cartesian coordinates. Constructed in an agoestrophic and nonhydrostatie dynamical framework, the generalized wave-activity law may be applicable to diagnose mesoscale weather systems leading to heavy rainfall. The generalized wave-activity density and wave-activity flux divergence were calculated with the objective analysis data to investigate the character of wave activity over heavy-rainfall regions. The primary dynamical processes responsible for disturbance associated with heavy rainfall were also analyzed. It was shown that the generalized wave-activity density was closely correlated to the observed 6-h accumulative rainfall. This indicated that the wave activity or disturbance was evident over the frontal and landfall-typhoon heavy-rainfall regions in middle and lower troposphere. For the landfall-typhoon rainband, the portion of generalized wave-activity flux divergence, denoting the interaction between the basic-state cyclonic circulation of landfall typhoon and mesoscale waves, was the primary dynamic process responsible for the evolution of generalized wave-activity density.
基金Supported by the National Creative Research Groups Science Foundation of China （60721062） and the National High Technology Research and Development Program of China （2007AA04Z162）.
文摘An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.
