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Executive SummaryUltrasonic nondestructive evaluation (NDE) and inspection of cast austenitic stainless steel (CASS) components used in the nuclear power industry is neither as effective nor reliable as is needed. With current ultrasonic methods these limitations are in large part due to the detrimental effects of wavemicrostructure interactions on the interrogating ultrasonic beam and interference that results from ultrasonic backscatter. The root cause of these phenomena is the coarse-grain microstructure inherent to this class of materials. Some ultrasonic techniques are found to perform better for particular microstructural classifications and this has led to the hypothesis that an ultrasonic inspection can potentially be optimized for a particular microstructural class. For optimized ultrasonic technique selection, methods will be needed to reliably classify the microstructure in-situ, which is then used to guide the selection and optimization of the inspection. This document summarizes scoping experiments that investigate potential in-situ ultrasonic methods for classification and/or characterization of the material microstructures in CASS components, when making measurements from the outside surface of a pipe.The focus of this preliminary study was to evaluate ultrasonic measurement methods to determine if responses from different known microstructures can be differentiated and hence if in-service characterization of cast austenitic stainless steel (CASS) is potentially feasible. On the basis of an initial literature evaluation, two ultrasonic parameters, (i) the time-of-flight ratio between shear and longitudinal waves and (ii) the attenuation for normal incidence longitudinal waves, were selected for investigation. Scoping experiments were performed to determine the ability of these measured parameters to discriminate between different microstructures in CASS components. The objective was to determine if a more thorough and staged exploration would be justified in progressing toward the real-time characterization of CASS for use as feedback to optimize current or new ultrasonic in-service inspection methodologies. With this objective in mind, measurements were restricted to techniques that potentially should be robust if carried forward to an eventual field implementation.The first parameter investigated was a time-of-flight ratio of a normal incidence shear wave to that of a normal incidence longitudinal wave (TOFRSL). The ratio removes dependency on component thickness which may not be accurately known or reported in the field. The second parameter was the attenuation of a normal incidence longitudinal wave. The selected CASS specimens used for the experimental study were five equiaxed-grain material samples and five columnar-grain material samples, and these were used for a two-class discrimination problem.TOFRSL estimates and a threshold algorithm classified all 10 material samples correctly and indicated a potentially reliable and robust technique. Qualitative longitudinal wave attenuation estimate...

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Abstract-Despite having a wide-spread applicability of evolutionary optimization procedures over the past few decades, EA researchers still face criticism about the theoretical optimality of obtained solutions. In this paper, we address this issue for problems for which gradients of objectives and constraints can be computed either exactly, or numerically or through subdifferentials. We suggest a systematic procedure of analyzing a representative set of Pareto-optimal solutions for their closeness to satisfying Karush-Kuhn-Tucker (KKT) points, which every optimal solution must also satisfy. The procedure involves either a least-square solution or an optimum solution to a set of linear system of equations involving Lagrange multipliers. The procedure is applied to a number of differentiable and non-differentiable test problems and to a highly nonlinear engineering design problem. The results clearly show that EAs are capable of finding solutions close to theoretically optimal solutions in various problems. As a by-product, the error metric suggested in this paper can also be used as a termination condition for an EA application. Hopefully, this study will bring EAs and its research closer to classical optimization studies.