Data-driven modeling for drop size distributions

The prediction of the drop size distribution (DSD) resulting from liquid atomization is key to the optimization of multiphase flows from gas-turbine propulsion through agriculture to healthcare. Obtaining high-fidelity data of liquid atomization, either experimentally or numerically, is expensive, which makes the exploration of the design space difficult. First, to tackle these challenges, we propose a framework to predict the DSD of a liquid spray based on data as a function of the spray angle, the Reynolds number, and the Weber number. Second, to guide the design of liquid atomizers, the model accurately predicts the volume of fluid contained in drops of specific sizes while providing uncertainty estimation. To do so, we propose a Gaussian process regression (GPR) model, which infers the DSD and its uncertainty form the knowledge of its integrals and of its first moment, i.e., the mean drop diameter. Third, we deploy multiple GPR models to estimate these quantities at arbitrary points of the design space from data obtained from a large number of numerical simulations of a flat fan spray. The kernel used for reconstructing the DSD incorporates prior physical knowledge, which enables the prediction of sharply peaked and heavy-tailed distributions. Fourth, we compare our method with a benchmark approach, which estimates the DSD by interpolating the frequency polygon of the binned drops with a GPR. We show that our integral approach is significantly more accurate, especially in the tail of the distribution (i.e., large, rare drops), and it reduces the bias of the density estimator by up to 10 times. Finally, we discuss physical aspects of the model's predictions and interpret them against experimental results from the literature. This work opens opportunities for modeling drop size distribution in multiphase flows from data

First principles investigations of the electronic, magnetic and chemical bonding properties of CeTSn (T=Rh,Ru)

The electronic structures of CeRhSn and CeRuSn are self-consistently calculated within density functional theory using the local spin density approximation for exchange and correlation. In agreement with experimental findings, the analyses of the electronic structures and of the chemical bonding properties point to the absence of magnetization within the mixed valent Rh based system while a finite magnetic moment is observed for trivalent cerium within the Ru-based stannide, which contains both trivalent and intermediate valent Ce.Comment: 6 pages, 7 figures, for more information see http://www.physik.uni-augsburg.de/~eyert

Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Modelica-Based Model for Activated Sludge System

Activated sludge system is the most important stage in municipal wastewater treatment process. It is a biological operation used for treating sewage by means of microorganism. One type of activated sludge systems is the oxidation ditch. In this work, models derived through object-oriented programming will be used to build a simulation model for a typical oxidation ditch. The derived model was constructed and programmed using Modelica language. The simulation model will help better understand the system behavior. Thereby, the model will be provided as an assessment or evaluation tool for the performance of control schemes. The tool gave the expected results, in terms of reducing the concentration of organic matter in wastewater coming out from oxidation ditche

Accurate low-order modeling of electrified falling films at moderate Reynolds number

The two- and three-dimensional spatio-temporal dynamics of a falling, electrified leaky dielectric film are studied. The method of weighted residuals is used to derive high-order models that account for both inertia as well as second-order electrostatic effects. The models are validated against both linear theory and direct numerical simulations of the Navier-Stokes equations. It is shown that a simplified model offers a rapid computational option at the cost of a minimal decrease in accuracy. This model is then used to perform a parametric study in three dimensions

Reduced models for thick liquid layers with inertia on highly curved substrates

A method is presented for deriving reduced models for fluid flows over highly curved substrates with wider applicability and accuracy than existing models in the literature. This is done by reducing the Navier-Stokes equations to a novel system of boundary layer like equations in a general geometric setting. This is accomplished using a new, relaxed set of scalings that assert only that streamwise variations are ‘slow’. These equations are then solved using the method of weighted residuals, which is demonstrated to be applicable regardless of the geometry selected. A large number of results in the literature can be derived as special cases of our general formulation. A few of the more interesting cases are demonstrated. Finally, the formulation is applied to two thick annular flow systems as well as a conical system in both linear and nonlinear regimes, which traditionally has been considered inaccessible to such reduced models. Comparisons are made with direct numerical simulations of the Stokes equations. The results indicate that reduced models can now be used to model systems involving thick liquid layers