An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression

In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly

Interoperability and computational framework for simulating open channel hydraulics: application to sensitivity analysis and calibration of Gironde Estuary model

Water resource management is of crucial societal and economic importance, requiring a strong capacity for anticipating environmental change. Progress in physical process knowledge, numerical methods and computational power, allows us to address hydro-environmental problems of growing complexity. Modeling of river and marine flows is no exception. With the increase in IT resources, environmental modeling is evolving to meet the challenges of complex real-world problems. This paper presents a new distributed Application Programming Interface (API) of the open source TELEMAC-MASCARET system to run hydro-environmental simulations with the help of the interoperability concept. Use of the API encourages and facilitates the combination of worldwide reference environmental libraries with the hydro-informatic system. Consequently, the objective of the paper is to promote the interoperability concept for studies dealing with such issues as uncertainty propagation, global sensitivity analysis, optimization, multi-physics or multi-dimensional coupling. To illustrate the capability of the API, an operational problem for improving the navigation capacity of the Gironde Estuary is presented. The API potential is demonstrated in a re-calibration context. The API is used for a multivariate sensitivity analysis to quickly reveal the most influential parameters which can then be optimally calibrated with the help of a data assimilation technique

Multiphysics Design and Sensitivity Analysis of Nuclear Heated Critical Heat Flux Pool Boiling Test Devices in TREAT.

Following the events of the 2011 Fukushima Daiichi accident, there has been a drive to develop accident tolerant fuels (ATF) capable of enhancing safety margins provided by conventional light water reactor (LWR) materials, with a focus on the critical heat flux (CHF) behavior under fast transient heating irradiation conditions. Presented in this dissertation, is the modeling scope of a current effort aimed at elucidating the mechanisms of CHF under in-pile fast transient irradiation conditions using the Transient Reactor Test (TREAT) facility. A heater rodlet made from stainless steel type-304 with tailored natural boron content was held within experimental pool boiling capsules, to induce CHF in the surrounding coolant when submitted to a power pulse. The experimental aspect of this project is focused on studying the CHF impacts of radiation-induced surface activation (RISA), as well as rapid surface heating effects. The initial unique contributions of the computational studies in this dissertation, depict the multiphysics design process of an experimental separate effects borated heater apparatus that was inserted into TREAT in December of 2019. Boron concentrations between 0.1-2.09 wt.% were considered. A self-shielding study determined that a borated tube could be used instead of a solid rod. Following, a thermal hydraulics study determined that the current borated tube configuration achieved a maximum CHF multiplier value of 7.8 using a 1400 MJ power pulse in TREAT. Following, sensitivity studies analyzed the potential impacts of the CHF event on the heat transfer of more complex integral TREAT experiments under rapid heating conditions, utilizing the heat transfer time constant (HTTC) as the fundamental basis. The analysis showed the maximum fuel centerline temperature is independent of the CHF event, and the UO2 volumetric heat capacity is the only significant HTTC parameter. For the peak outer cladding temperatures (POCTs), the occurrence of DNB was determined to be dominant on the heat transfer mechanisms of these experimental fuel designs. For the cases where the DNB event manifested, the HTTC was resolved to have significant impacts on the predictions of the POCTs. Furthermore, when studying the time occurrence of the CHF, the variations in the gap thickness was dominant