• International Journal of Aeronautical and Space Sciences
• /
• v.8 no.1
• /
• pp.66-78
• /
• 2007

A multi-point aerodynamic shape optimization technique has been developed for helicopter rotor blades in hover based on a continuous adjoint method on unstructured meshes. The Euler flow solver and the continuous adjoint sensitivity analysis were formulated on the rotating frame of reference. The 'objective function and the sensitivity were obtained as a weighted sum of the values at each design point. The blade section contour was modified by using the Hicks-Henne shape functions. The mesh movement due to the blade geometry change was achieved by using a spring analogy. In order to handle the repeated evaluation of the design cycle efficiently, the flow and adjoint solvers were parallelized based on a domain decomposition strategy. A solution-adaptive mesh refinement technique was adopted for the accurate capturing of the wake. Applications were made to the aerodynamic shape optimization of the Caradonna-Tung rotor blades and the UH-60 rotor blades in hover.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.49-54
• /
• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• Ocean and Polar Research
• /
• v.40 no.1
• /
• pp.37-48
• /
• 2018

The purpose of this study is to assess the climate change vulnerability of coastal and offshore fisheries in the South Sea of Korea using the RCP scenarios. Based on the vulnerability defined by IPCC, the indicator-based method was applied. Exposure indicator was calculated through weighted sum of the sea temperature and salinity forecasted by National Institute of Fisheries Science, and the weights were obtained from the time-space distribution of each fisheries. Sensitivity indicator was determined by applying the catch proportion of fisheries to the sensitivity of fish species. The adaptive capacity was measured by survey of fisheries which represent the ability of the fishermen well. As a result of summarizing the above indicators, vulnerability of coastal fisheries is higher than offshore fisheries. This shows that measures against coastal fisheries are needed. In addition, the results of each scenario are somewhat different, so it is considered that accurate prediction of climate change is important for adaptation measures.