Turbulent flow, the transpor＇t of inclusions and bubbles, and inclusion removal by fluid flow, transport and by bubble flotation in the strand of the continuous slab caster are investigated using computational models...Turbulent flow, the transpor＇t of inclusions and bubbles, and inclusion removal by fluid flow, transport and by bubble flotation in the strand of the continuous slab caster are investigated using computational models, and validated through comparison with plant measurements of inclusions. Steady 3-D flow of steel in the liquid pool in the mold and upper strand is simulated with a finitedifference computational model using the standard k-εturbulence rondel. Trajectories of inclusions and bubhles tire calculated by integrating each local velocity, considering its drag and buoyancy forces, A ＂random walk＂ model is used to incorporate the effect of turbulent fluctuations on the particle motion. The attachment probability of inclusions on a bubble surface is investigated based on fundamental fluid flow simulations, incorporating the turbulent inclusion trajectory and sliding time of each individual inclusion along the bubble surface as a function of particle and bubble size. The chunge in inclusion distribution due to removal by bubble transport in the mold is calculated based on the computed attachment probability of inclusions on each bubble and the computed path length of the bubbles. The results indicate that 6%-10% inclusions are removed by fluid flow transport. 10% by bubble flotation, and 4% by entrapment to the submerged entry nozzle （SEN） walls. Smaller bubbles and larger inclusions have larger attachment probabilities. Smaller bubbles are more efficient for inclusion removal by bubble flotation, so Inng as they are not entrapped in the solidifying shell A larger gas flow rate favors inclusion removal by bubble flotation. The optimum bubble size should be 2-4mm.展开更多
The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to...The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.展开更多
The second-order random walk has recently been shown to effectively improve the accuracy in graph analysis tasks.Existing work mainly focuses on centralized second-order random walk(SOW)algorithms.SOW algorithms rely ...The second-order random walk has recently been shown to effectively improve the accuracy in graph analysis tasks.Existing work mainly focuses on centralized second-order random walk(SOW)algorithms.SOW algorithms rely on edge-to-edge transition probabilities to generate next random steps.However,it is prohibitively costly to store all the probabilities for large-scale graphs,and restricting the number of probabilities to consider can negatively impact the accuracy of graph analysis tasks.In this paper,we propose and study an alternative approach,SOOP(second-order random walks with on-demand probability computation),that avoids the space overhead by computing the edge-to-edge transition probabilities on demand during the random walk.However,the same probabilities may be computed multiple times when the same edge appears multiple times in SOW,incurring extra cost for redundant computation and communication.We propose two optimization techniques that reduce the complexity of computing edge-to-edge transition probabilities to generate next random steps,and reduce the cost of communicating out-neighbors for the probability computation,respectively.Our experiments on real-world and synthetic graphs show that SOOP achieves orders of magnitude better performance than baseline precompute solutions,and it can efficiently computes SOW algorithms on billion-scale graphs.展开更多
受Deshpande and Prabhu Ajgaonkar(1982)设计的思想启发,本文给出了一种新的n=2时的严格πps抽样设计.当辅助变量值满足Xi/X<1/2时,提出的新设计既容易实施,又容易计算一阶和二阶包含概率.同时,可以得到Horvitz-Thompson估计量的一...受Deshpande and Prabhu Ajgaonkar(1982)设计的思想启发,本文给出了一种新的n=2时的严格πps抽样设计.当辅助变量值满足Xi/X<1/2时,提出的新设计既容易实施,又容易计算一阶和二阶包含概率.同时,可以得到Horvitz-Thompson估计量的一个非负的方差估计.通过数值比较提出设计和经典πps抽样设计,说明提出方法具有潜在应用价值.展开更多
文摘Turbulent flow, the transpor＇t of inclusions and bubbles, and inclusion removal by fluid flow, transport and by bubble flotation in the strand of the continuous slab caster are investigated using computational models, and validated through comparison with plant measurements of inclusions. Steady 3-D flow of steel in the liquid pool in the mold and upper strand is simulated with a finitedifference computational model using the standard k-εturbulence rondel. Trajectories of inclusions and bubhles tire calculated by integrating each local velocity, considering its drag and buoyancy forces, A ＂random walk＂ model is used to incorporate the effect of turbulent fluctuations on the particle motion. The attachment probability of inclusions on a bubble surface is investigated based on fundamental fluid flow simulations, incorporating the turbulent inclusion trajectory and sliding time of each individual inclusion along the bubble surface as a function of particle and bubble size. The chunge in inclusion distribution due to removal by bubble transport in the mold is calculated based on the computed attachment probability of inclusions on each bubble and the computed path length of the bubbles. The results indicate that 6%-10% inclusions are removed by fluid flow transport. 10% by bubble flotation, and 4% by entrapment to the submerged entry nozzle （SEN） walls. Smaller bubbles and larger inclusions have larger attachment probabilities. Smaller bubbles are more efficient for inclusion removal by bubble flotation, so Inng as they are not entrapped in the solidifying shell A larger gas flow rate favors inclusion removal by bubble flotation. The optimum bubble size should be 2-4mm.
基金supported by the National Natural Science Foundation of China (70871117 70571086)the Development Foundation of Dalian Naval Academy
文摘The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.
文摘The second-order random walk has recently been shown to effectively improve the accuracy in graph analysis tasks.Existing work mainly focuses on centralized second-order random walk(SOW)algorithms.SOW algorithms rely on edge-to-edge transition probabilities to generate next random steps.However,it is prohibitively costly to store all the probabilities for large-scale graphs,and restricting the number of probabilities to consider can negatively impact the accuracy of graph analysis tasks.In this paper,we propose and study an alternative approach,SOOP(second-order random walks with on-demand probability computation),that avoids the space overhead by computing the edge-to-edge transition probabilities on demand during the random walk.However,the same probabilities may be computed multiple times when the same edge appears multiple times in SOW,incurring extra cost for redundant computation and communication.We propose two optimization techniques that reduce the complexity of computing edge-to-edge transition probabilities to generate next random steps,and reduce the cost of communicating out-neighbors for the probability computation,respectively.Our experiments on real-world and synthetic graphs show that SOOP achieves orders of magnitude better performance than baseline precompute solutions,and it can efficiently computes SOW algorithms on billion-scale graphs.
文摘受Deshpande and Prabhu Ajgaonkar(1982)设计的思想启发,本文给出了一种新的n=2时的严格πps抽样设计.当辅助变量值满足Xi/X<1/2时,提出的新设计既容易实施,又容易计算一阶和二阶包含概率.同时,可以得到Horvitz-Thompson估计量的一个非负的方差估计.通过数值比较提出设计和经典πps抽样设计,说明提出方法具有潜在应用价值.
