INTERVAL ARITHMETIC AND STATIC INTERVAL FINITE ELEMENT METHOD

When the uncertainties of structures may be bounded in intervals, through some suitable discretization, interval finite element method can be constructed by combining the interval analysis with the traditional finite element method (FEM). The two parameters, median and deviation, were used to represent the uncertainties of interval variables. Based on the arithmetic rules of intervals, some properties and arithmetic rules of interval variables were demonstrated. Combining the procedure of interval analysis with FEM, a static linear interval finite element method was presented to solve the non-random uncertain structures. ne solving of the characteristic parameters of n-freedom uncertain displacement field of the static governing equation was transformed into 2 n-order linear equations. It is shown by a numerical example that the proposed method is practical and effective.

Non-intrusive hybrid interval method for uncertain nonlinear systems using derivative information

This paper proposes a new non-intrusive hybrid interval method using derivative information for the dynamic response analysis of nonlinear systems with uncertain-but- bounded parameters and/or initial conditions. This method provides tighter solution ranges compared to the existing polynomial approximation interval methods. Interval arith- metic using the Chebyshev basis and interval arithmetic using the general form modified affine basis for polynomials are developed to obtain tighter bounds for interval computation. To further reduce the overestimation caused by the ＂wrap- ping effect＂ of interval arithmetic, the derivative information of dynamic responses is used to achieve exact solutions when the dynamic responses are monotonic with respect to all the uncertain variables. Finally, two typical numerical examples with nonlinearity are applied to demonstrate the effective- ness of the proposed hybrid interval method, in particular, its ability to effectively control the overestimation for specific timepoints.

A Reliable and Accurate Calculation of Excitation Capacitance Value for an Induction Generator Based on Interval Computation Technique

A squirrel cage induction generator （SCIG） offers many advantages for wind energy conversion systems but suffers from poor voltage regulation under varying operating conditions. The value of excitation capacitance （C exct ） is very crucial for the selfexcitation and voltage build-up as well as voltage regulation in SCIG. Precise calculation of the value of C exct is, therefore, of considerable practical importance. Most of the existing calculation methods make use of the steady-state model of the SCIG in conjunction with some numerical iterative method to determine the minimum value of C exct . But this results in over estimation, leading to poor transient dynamics. This paper presents a novel method, which can precisely calculate the value of C exct by taking into account the behavior of the magnetizing inductance during saturation. Interval analysis has been used to solve the equations. In the proposed method, a range of magnetizing inductance values in the saturation region are included in the calculation of C exct , required for the self-excitation of a 3-φ induction generator. Mathematical analysis to derive the basic equation and application of interval method is presented. The method also yields the magnetizing inductance value in the saturation region which corresponds to an optimum C exct（min） value. The proposed method is experimentally tested for a 1.1 kW induction generator and has shown improved results.

Hybrid method for global optimization using more accuracy interval computation

In this paper, a novel hybrid method is presented for finding global optimization of an objective function. Based on the interval computation, this hybrid method combines interval deterministic method and stochastic evolution method. It can find global optimization quickly while ensuring the deterministic and stability of the algorithm. When using interval computation, extra width constraints accuracy of interval computation results. In this paper, a splitting method to reduce the extra width is introduced. This method is easy and it can get a more precise interval computation result. When finding the global optimization, it can increase the efficiency of pruning. Several experiments are given to illustrate the advantage of the new hybrid method.

Numerical Robust Stability Estimation in Milling Process

The conventional prediction of milling stability has been extensively studied based on the assumptions that the milling process dynamics is time invariant. However, nominal cutting parameters cannot guarantee the stability of milling process at the shop floor level since there exists many uncertain factors in a practical manufacturing environment. This paper proposes a novel numerical method to estimate the upper and lower bounds of Lobe diagram, which is used to predict the milling stability in a robust way by taking into account the uncertain parameters of milling system. Time finite element method, a milling stability theory is adopted as the conventional deterministic model. The uncertain dynamics parameters are dealt with by the non-probabilistic model in which the parameters with uncertainties are assumed to be bounded and there is no need for probabilistic distribution densities functions. By doing so, interval instead of deterministic stability Lobe is obtained, which guarantees the stability of milling process in an uncertain milling environment, In the simulations, the upper and lower bounds of Lobe diagram obtained by the changes of modal parameters of spindle-tool system and cutting coefficients are given, respectively. The simulation results show that the proposed method is effective and can obtain satisfying bounds of Lobe diagrams. The proposed method is helpful for researchers at shop floor to making decision on machining parameters selection.

Power system transient stability simulation under uncertainty based on Taylor model arithmetic

The Taylor model arithmetic is introduced to deal with uncertainty.The uncertainty of model parameters is described by Taylor models and each variable in functions is replaced with the Taylor model(TM).Thus,time domain simulation under uncertainty is transformed to the integration of TM-based differential equations.In this paper,the Taylor series method is employed to compute differential equations;moreover,power system time domain simulation under uncertainty based on Taylor model method is presented.This method allows a rigorous estimation of the influence of either form of uncertainty and only needs one simulation.It is computationally fast compared with the Monte Carlo method,which is another technique for uncertainty analysis.The proposed method has been tested on the 39-bus New England system.The test results illustrate the effectiveness and practical value of the approach by comparing with the results of Monte Carlo simulation and traditional time domain simulation.

Numerical Integration Over Implicitly Defined Domains with Topological Guarantee

Numerical integration over the implicitly defined domains is challenging due to topological variances of implicit functions.In this paper,we use interval arithmetic to identify the boundary of the integration domain exactly,thus getting the correct topology of the domain.Furthermore,a geometry-based local error estimate is explored to guide the hierarchical subdivision and save the computation cost.Numerical experiments are presented to demonstrate the accuracy and the potential of the proposed method.