4 resultados para Train Control

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Motivated by the design and development challenges of the BART case study, an approach for developing and analyzing a formal model for reactive systems is presented. The approach makes use of a domain specific language for specifying control algorithms able to satisfy competing properties such as safety and optimality. The domain language, called SPC, offers several key abstractions such as the state, the profile, and the constraint to facilitate problem specification. Using a high-level program transformation system such as HATS being developed at the University of Nebraska at Omaha, specifications in this modelling language can be transformed to ML code. The resulting executable specification can be further refined by applying generic transformations to the abstractions provided by the domain language. Problem dependent transformations utilizing the domain specific knowledge and properties may also be applied. The result is a significantly more efficient implementation which can be used for simulation and gaining deeper insight into design decisions and various control policies. The correctness of transformations can be established using a rewrite-rule based induction theorem prover Rewrite Rule Laboratory developed at the University of New Mexico.

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Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.

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Condensation of steam in a single microchannel, silicon test section was investigated visually at low flow rates. The microchannel was rectangular in cross-section with a depth of 30 pm, a width of 800 mu m and a length of 5.0 mm, covered with a Pyrex glass to allow for visualization of the bubble formation process. By varying the cooling rate during condensation of the saturated water vapor, it was possible to control the shape, size and frequency of the bubbles formed. At low cooling rates using only natural air convection from the ambient environment, the flow pattern in the microchannel consisted of a nearly stable elongated bubble attached upstream (near the inlet) that pinched off into a train of elliptical bubbles downstream of the elongated bubble. It was observed that these elliptical bubbles were emitted periodically from the tip of the elongated bubble at a high frequency, with smaller size than the channel width. The shape of the emitted bubbles underwent modifications shortly after their generation until finally becoming a stable vertical ellipse, maintaining its shape and size as it flowed downstream at a constant speed. These periodically emitted elliptical bubbles thus formed an ordered bubble sequence (train). At higher cooling rates using chilled water in a copper heat sink attached to the test section, the bubble formation frequency increased significantly while the bubble size decreased, all the while forming a perfect bubble train flowing downstream of the microchannel. The emitted bubbles in this case immediately formed into a circular shape without any further modification after their separation from the elongated bubble upstream. The present study suggests that a method for controlling the size and generation frequency of microbubbles could be so developed, which may be of interest for microfluidic applications. The breakup of the elongated bubble is caused by the large Weber number at the tip of the elongated bubble induced by the maximum vapor velocity at the centerline of the microchannel inside the elongated bubble and the smaller surface tension force of water at the tip of the elongated bubble.