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A solution to stochastic unit commitment problem for a wind-thermal system coordination

B. SARAVANAN,Shreya MISHRA,Debrupa NAG

《能源前沿（英文）》 2014年第8卷第2期页码 192-200 doi: 10.1007/s11708-014-0306-x

摘要： Unit commitment (UC) problem is one of the most important decision making problems in power system. In this paper the UC problem is solved by considering it as a real time problem by adding stochasticity in the generation side because of wind-thermal co-ordination system as well as stochasticity in the load side by incorporating the randomness of the load. The most important issue that needs to be addressed is the achievement of an economic unit commitment solution after solving UC as a real time problem. This paper proposes a hybrid approach to solve the stochastic unit commitment problem considering the volatile nature of wind and formulating the UC problem as a chance constrained problem in which the load is met with high probability over the entire time period.

关键词： unit commitment (UC) randomness wind generation univariate chance constrained

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Inverse Kinematics Analysis of General 6R Serial Robot Mechanism Based on Groebner Base

WANG Yan, HANG Lu-bin, YANG Ting-li

《机械工程前沿（英文）》 2006年第1卷第1期页码 115-124 doi: 10.1007/s11465-005-0022-7

摘要：

This study presents a solution for the inverse kinematics problem in serial 6R manipulator. Using only seven equations composed of Duffy s four kinematical equations containing three angles and three corresponding angles identical equations instead of the traditional 14 equations, the authors reduced the inverse kinematics problem in the general 6R manipulator to a univariate polynomial with a minimum degree based on the Groebner Base method. From that, they concluded that the maximum number of the solutions is 16, generally. Also, the mathematics mechanization method can be extended to solve other mechanism problems involving nonlinear equations symbolically.

关键词： identical manipulator univariate polynomial mechanism traditional

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Robust topology optimization of multi-material lattice structures under material and load uncertainties

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

《机械工程前沿（英文）》 2019年第14卷第2期页码 141-152 doi: 10.1007/s11465-019-0531-4

摘要： Enabled by advancements in multi-material additive manufacturing, lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide array of functions. This work proposes a density-based robust topology optimization method for meso- or macro-scale multi-material lattice structures under any combination of material and load uncertainties. The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials, and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertainty. By formulating the objective function as a weighted sum of the mean and standard deviation of compliance, the tradeoff between optimality and robustness can be studied and controlled. Examples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit the efficiency and flexibility of the approach. The accuracy of univariate dimension reduction is validated by comparing the results to the Monte Carlo approach.

关键词： robust topology optimization lattice structures multi-material material uncertainty load uncertainty univariate dimension reduction