• Title/Summary/Keyword: probabilistic constraint

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Designs of Pipe Fitting with Three Dimensional Measurement and Kinematic Constrained Equations (파이프 체결을 위한 3차원 측정 및 기구적 구속조건 기반의 설계 방식)

  • Yang, Jeong-Yean
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.54-61
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    • 2022
  • Ship is a huge system including a variety of pipe arrangements. Pipes are installed according to the design layout, however the end poistion of pipes are not well matched owing to its measurement and construction errors. In this situation, the customized pipe fitting is frequently designed to connect with both pipes, the position of which are manually measured. This paper focused that these two coordinates are measured by point cloud from RGBD sensor and the relative transformation induced by positional and orientational differences is calculated by inverse kinematics in robotics theory. Therefore, the result applies for the methodology of the pipe connection design. The pipe coordinate that is estimated by the matching and the probabilistic RANSAC method will be verified by experiments. The kinematic design parameters are computationally calculated by using the minimum degree of freedom that connects both pipe coordinates.

A study on the estimation of container terminal capacity and its implication to port development planning of Korea (국내 컨테이너 부두시설 확보제도 개선방향 연구)

  • Yang, Chang-Ho
    • Journal of Korea Port Economic Association
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    • v.26 no.3
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    • pp.198-220
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    • 2010
  • This paper investigate the problems of standard container port handling capacity in establishing national port development plan in Korea. Considering container port developing, it's not easy to adopt container port service quality parameters such as lay time constraint of very large container ships by using the standard guideline of container port handling capacity. A simple methodology that connects vessel waiting to service time(w/s) and berth occupancy to costs has been used to evaluate the performance of a container terminal. But the total handling capacity have to be calculated by the performance of the handling system and number of equipments and layout of terminal by using computer simulation that represents of reality events needs to be performed by probabilistic techniques. A simulation model of estimation of container terminal capacity is introduced in order to establish a hub terminal for very large container ships that focus the port's quality of service and also suggest as tool for policy maker to justify a required port investment.

An Improved Reliability-Based Design Optimization using Moving Least Squares Approximation (이동최소자승근사법을 이용한 개선된 신뢰도 기반 최적설계)

  • Kang, Soo-Chang;Koh, Hyun-Moo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1A
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    • pp.45-52
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    • 2009
  • In conventional structural design, deterministic optimization which satisfies codified constraints is performed to ensure safety and maximize economical efficiency. However, uncertainties are inevitable due to the stochastic nature of structural materials and applied loads. Thus, deterministic optimization without considering these uncertainties could lead to unreliable design. Recently, there has been much research in reliability-based design optimization (RBDO) taking into consideration both the reliability and optimization. RBDO involves the evaluation of probabilistic constraint that can be estimated using the RIA (Reliability Index Approach) and the PMA(Performance Measure Approach). It is generally known that PMA is more stable and efficient than RIA. Despite the significant advancement in PMA, RBDO still requires large computation time for large-scale applications. In this paper, A new reliability-based design optimization (RBDO) method is presented to achieve the more stable and efficient algorithm. The idea of the new method is to integrate a response surface method (RSM) with PMA. For the approximation of a limit state equation, the moving least squares (MLS) method is used. Through a mathematical example and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

Prediction of Expected Residual Useful Life of Rubble-Mound Breakwaters Using Stochastic Gamma Process (추계학적 감마 확률과정을 이용한 경사제의 기대 잔류유효수명 예측)

  • Lee, Cheol-Eung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.3
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    • pp.158-169
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    • 2019
  • A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.