Determination of crack growth kinetics in non-reinforced semi-crystalline thermoplastics using the linear elastic fracture mechanics (LEFM) approach

The aim of this study was to find a satisfactory method to characterize the fatigue crack growth behavior of non-reinforced, semi-crystalline thermoplastic polymers using linear elastic fracture mechanics (LEFM). For this, crack growth curves (crack length versus cycle number) as well as crack growth kinetics curves (crack growth rate da/dN versus amplitude stress intensity factor ΔK) had to be generated. As methods suggested by ISO 15850 and ASTM E 647-11 failed to provide satisfactory results for the crack growth curves, a more advanced method was searched for and finally found in the literature. Regarding the crack growth kinetics curve, the idea of the calculation was based on methods recommended in ISO 15850 and ASTM E 647-11. However, these methods had to be considerably modified and improved in order to get accurate results with little scatter. The whole methodology was developed and verified with fatigue crack growth tests on two semi-crystalline thermoplastics (polyoxymethylene POM and polyetheretherketone PEEK).     

基于失效情景的应急设施选址问题

非常规突发事件巨大的破坏力以及发生时间、地点和规模的不确定性,使应急系统内设施有可能被破坏而失效,因此选址时必须考虑设施失效情景的发生.给出以最大限度覆盖用户需求为目标,基于失效设施数目具有不确定性情景的设施选址双层随机规划模型;通过计算模型上下界,给出减小规模的等价模型,降低了双层规划求解难度;最后实验验证了模型的合理性,并给出新增选址方案.     

Third‐order sensitivity analysis for robust aerodynamic design using continuous adjoint

Robust design problems in aerodynamics are associated with the design variables, which control the shape of an aerodynamic body, and also with the so‐called environmental variables, which account for uncertainties. In this kind of problems, the set of design variables, which leads to optimal performance, taking into account possible variations in the environmental variables, is sought. One of the possible ways to solve this problem is by means of the second‐order second‐moment approach, which requires first‐order and second‐order derivatives of the objective function with respect to the environmental variables. Should the minimization problem be solved using a gradient‐based method, algorithms for the computation of up to third‐order sensitivity derivatives (twice with respect to the environmental variables and once with respect to the shape controlling design variables) must be devised. In this paper, a combination of the continuous adjoint variable method and direct differentiation to compute the third‐order sensitivities is proposed. This is shown to be the most efficient among all alternative methods provided that the environmental variables are much less than the design ones. Apart from presenting the method formulation, this paper focuses on the assessment of the so‐computed up‐to third‐order mixed derivatives through comparison with costly finite‐difference schemes. To this end, the robust design of a two‐dimensional duct is performed. Then, using the validated method, the robust design of a two‐dimensional cascade airfoil is demonstrated. Although both cases are handled as inverse design problems, the method can be extended to other objective functions or three‐dimensional problems in a straightforward manner. Copyright © 2012 John Wiley & Sons, Ltd.     

Reprint of : Connection between wave transport through disordered 1D waveguides and energy density inside the sample: A maximum-entropy approach

We study the average energy – or particle – density of waves inside disordered 1D multiply-scattering media. We extend the transfer-matrix technique that was used in the past for the calculation of the intensity beyond the sample to study the intensity in the interior of the sample by considering the transfer matrices of the two segments that form the entire waveguide. The statistical properties of the two disordered segments are found using a maximum-entropy ansatz subject to appropriate constraints. The theoretical expressions are shown to be in excellent agreement with 1D transfer-matrix simulations.     

On safe tractable approximations of chance constraints

A natural way to handle optimization problem with data affected by stochastic uncertainty is to pass to a chance constrained version of the problem, where candidate solutions should satisfy the randomly perturbed constraints with probability at least 1 − ?. While being attractive from modeling viewpoint, chance constrained problems “as they are” are, in general, computationally intractable. In this survey paper, we overview several simulation-based and simulation-free computationally tractable approximations of chance constrained convex programs, primarily, those of chance constrained linear, conic quadratic and semidefinite programming.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

Wave propagation across a finite heterogeneous interphase modeled as an interface with material properties

Mechanical problems involving an interphase between two well-defined, and eventually different, materials are of interest. The aim of this paper is to present a simplified model that, for low frequency regime, is appropriate for this situation: an interface model with elastic and inertial properties. We present, together with the equations of motion, an identification procedure that is valid for any mass density profile along the thickness of the interphase. For evaluating the accuracy of the model, computations of the reflection coefficients in some relevant cases are shown. Besides, a finite element method is used as a benchmark for both the high and low frequency regimes. It is worth to be noted that the numerical test has been inspired by the problem of the interphase that is formed at the bone-implant boundary.     

Application of the transmission line matrix method for outdoor sound propagation modelling – Part 1: Model presentation and evaluation

The present paper deals with an original time-domain approach applied to outdoor sound propagation under meteorological effects. The transmission line matrix method, based on the Huygens’ principle, had already been validated over impedant grounds and complex topography. The presented formulation proposes to take into account meteorological effects (wind speed and temperature) through the relative sound speed. The necessary wavefront direction is determined through the calculation of the averaged intensity vector direction. A good agreement is found between simulations of both the transmission line matrix and parabolic equation methods. A relevant use of the method is shown in the framework of environmental acoustics and initial applications are proposed in Part 2.     

Infinite propagation speed of a weakly dissipative modified two-component Dullin–Gottwald–Holm system

We consider the infinite propagation speed of a weakly dissipative modified two-component Dullin–Gottwald–Holm (mDGH2) system. The infinite propagation speed is derived for the corresponding solution with compactly supported initial data that does not have compact support any longer in its lifespan.     

A safe minimum standard,the elasticity of substitution,and the cleanup of the Ganges in Varanasi

Despite repeated calls for a thorough cleanup of water pollution in the Ganges river, there are only two papers in the social sciences by Batabyal and Beladi (2017, 2019) that have shed theoretical light on this cleanup problem and its connection to the sustainability of tourism in Varanasi. Hence, we extend the above‐mentioned analyses and focus on two specific questions. First, we introduce the notion of a safe minimum standard (SMS) into the study and show how to analyze a probabilistic model of the Ganges cleanup problem when the SMS is accounted for. Second, for a representative citizen of Varanasi, we study how the magnitude of the elasticity of substitution between a composite consumption good and water quality in the Ganges—modeled by the SMS—affects the tradeoff between consumption and water quality maintenance.