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In many practical engineering problems, distributions of some random variables may not be precisely known or even only the variation ranges can be given, due to which the Reliability-Based Design Optimization (RBDO) methods cannot be applied directly. In this paper, a hybrid RBDO model is established to deal with hybrid uncertainties including random variables with interval distribution parameters and coexistence of random and interval variables. The hybrid uncertainties lead to an interval of reliability, thus giving rise to a triple-loop optimization problem, which burdens the computational effort significantly. Therefore, an extended Sequential Optimization and Reliability Assessment (SORA) method is proposed, where the worst-case point over the bounded domain of interval uncertainty is employed to replace reliability constraint with deterministic optimization. Therefore, the hybrid RBDO problem can be efficiently solved by a series of deterministic optimization procedures. The efficiency and accuracy of the proposed method are illustrated through several numerical examples. [ABSTRACT FROM AUTHOR]

Eigenvalues of the dielectric-filled waveguide are of great importance to its transmission characteristic analysis and optimization design, which could be easily affected by spatially uncertain dielectric parameters. For the sake of quantifying their influence on eigenvalues of the dielectric-filled waveguide and overcoming the limitation of less samples, an interval vector finite element method (IVFEM) is proposed to acquire the lower and upper bounds of the eigenvalues with spatial uncertainty of the medium parameters Firstly, the uncertain dielectric material properties are described by the interval field model and the corresponding interval Karhunen-Loève (K-L) approximate method. Secondly, by inserting the interval uncertainties into the constitutive relationship of the standard generalized eigenvalue equations of the dielectric-filled waveguide, an interval standard generalized eigenvalue equation is then formulated. At last, the lower and upper bounds of the eigenvalues are calculated according to the first-order perturbation method, which can be used to estimate the transmission properties of the waveguide efficiently. Three kinds of the dielectric-filled waveguides are analyzed by the proposed IVFEM and verified by Monte Carlo simulation method. [ABSTRACT FROM AUTHOR]

This paper presents an effective sequence interval and correlation inverse strategy for the uncertain inverse problem, aiming to identify the uncertainties and non-probabilistic correlations of the structural parameters simultaneously. First, an ellipsoidal convex model is adopted to quantify the uncertainty boundary of the measured responses with limited samples. Then, the uncertain inverse problem based on the ellipsoidal convex model is decoupled into an interval inverse problem and a correlation inverse problem. For the interval inverse problem, a subinterval decomposition analysis method constrained by the ellipsoidal convex model is developed to evaluate the intervals of the structural responses with a low computational cost. For the correlation inverse problem, the correlation propagation equations are derived to calculate the non-probabilistic correlation coefficient matrix of the structural responses. After that, by using optimization algorithms to circularly reduce the errors of the intervals and the correlation coefficients between the measured responses and calculated structural responses, the intervals and the non-probabilistic correlation coefficient matrix of the structural parameters are identified effectively, and an ellipsoidal convex model of the structural parameters can be established eventually. Two numerical examples and one experimental example are investigated to verify the effectiveness and accuracy of the proposed sequence interval and correlation inverse strategy. [ABSTRACT FROM AUTHOR]

In this paper, an electromagnetic stochastic finite element method is presented to calculate the statistical moments of electromagnetic problems with spatially uncertain dielectric parameters. First, the random field model of the dielectric material is represented by the Karhunen–Loève expansion and inserted into the scalar Helmholtz wave equations. The stochastic equilibrium equations are thus constructed according to the node-based finite element method. Second, the first-order and second-order perturbation stochastic finite element methods are developed for calculating the statistical moments of electromagnetic responses. Finally, the feasibility and validity of the proposed method are verified by three numerical examples. [ABSTRACT FROM AUTHOR]

Background: In response to China's rapidly aging population and increasing healthcare service demands, the Chinese government is developing a universal medical insurance system. This study aimed to assess healthcare utilization patterns and analyze the impacts of medical insurance schemes on healthcare utilization among the middle-aged and elderly in China.Methods: Data was extracted from the China Health and Retirement Longitudinal Study in 2011, 2013 and 2015. Healthcare utilization was measured by outpatient and inpatient service utilization. Univariate analysis was deployed to examine the impacts of different medical insurance schemes on healthcare utilization. The factors associated with healthcare utilization were estimated using a random-effects logistic regression model.Results: During the study period, the number of individuals involved was 17,250, 18,195 and 19,842, respectively. The proportion of individuals who received outpatient service was 18.6, 20.7 and 18.7% and those who used inpatient service was 9.6, 13.8 and 14.3%, respectively. We identified that medical insurance was a major protective factor for improving healthcare utilization but different medical insurance schemes exerted various impacts on the middle-aged and the elderly.Conclusions: Despite the growing population coverage, the Chinese government should make every effort to bridge the gap among people with different medical insurance schemes. Further evaluation is needed to assess whether the expanded medical insurance schemes could protect the middle-aged and elderly households from catastrophic health expenditure. [ABSTRACT FROM AUTHOR]

Recently, the authors proposed a new mathematical model called as the "interval process model" for quantifying uncertainty of time–varying parameters by making extension of the interval method into the time domain. In the interval process model, the imprecision of a time-varying parameter at arbitrary time point is described using an interval rather than the precise probability distribution, which makes the interval process model having some advantages over the traditional stochastic process in uncertainty quantification. Further, the authors proposed the important conceptions of limit, continuity, differential and integral of interval process, enriching the theory of interval process model. This paper applies the newly developed conceptions of differential and integral of interval process into the vibration analysis of mechanical structures or systems subjected to uncertain external excitations. By means of this application, the formulations of dynamic bounds of the velocity and acceleration responses are derived for the linear/multiple single degree of freedom (SDOF/MDOF) vibration systems subjected to dynamic uncertain excitations, which can provide some important reference information for reliability analysis and safety design of many practical mechanical structures or systems. The effectiveness of the proposed method are validated by investigating a spring-mass-damper system and a vehicle vibration problem. [ABSTRACT FROM AUTHOR]

During the manufacturing process of dielectric materials used in electromagnetic engineering, the electromagnetic parameters are often spatially uncertain due to the processing technology, environmental temperature, personal operations, etc. Traditionally, the random field model can be used to measure the spatial uncertainties, but its construction requires a large number of samples. On the contrary, the interval field model only needs the upper and lower bounds of the spatially uncertain parameters, which requires much less samples and furthermore is easy to understand and use for engineers. Therefore, in this paper, the interval field model is introduced to describe the spatial uncertainties of dielectric materials, and then an interval finite element method (IFEM) is proposed to calculate the upper and lower bounds of electromagnetic responses. Firstly, the interval field of the dielectric material is represented by the interval K-L expansion and inserted into the scalar Helmholtz wave equations, and thus the interval equilibrium equations are constructed according to the node-based finite element method. Secondly, a perturbation interval finite element method is developed for calculating the upper and lower bounds of electromagnetic responses such as the electric strength and magnetic strength. Finally, the effectiveness of the proposed method is verified by three numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, a new non-probabilistic reliability-based topology optimization (NRBTO) method is proposed to account for interval uncertainties considering parametric correlations. Firstly, a reliability index is defined based on a newly developed multidimensional parallelepiped (MP) convex model, and the reliability-based topology optimization problem is formulated to optimize the topology of the structure, to minimize material volume under displacement constraints. Secondly, an efficient decoupling scheme is applied to transform the double-loop NRBTO into a sequential optimization process, using the sequential optimization & reliability assessment (SORA) method associated with the performance measurement approach (PMA). Thirdly, the adjoint variable method is used to obtain the sensitivity information for both uncertain and design variables, and a gradient-based algorithm is employed to solve the optimization problem. Finally, typical numerical examples are used to demonstrate the effectiveness of the proposed topology optimization method. [ABSTRACT FROM AUTHOR]