Model based analysis of forced and natural convection effects in an electrochemical cell

High purity copper, suitable for electrical applications, can only be obtained by electro-winning. The hallmark of this process is its self-induced natural convection through density variations of the electrolyte at both anode and cathode. In order to accelerate the process, first its full dynamic complexity needs to be understood. Thus, an OpenFoam®-based 2D model has been created. This finite-volume multiphysics approach solves the laminar momentum and copper-ion species conservation equations, as well as local copper-ion conversion kinetics. It uses a Boussinesq approximation to simulate the species-momentum coupling, namely natural draft forces induced by variations of the spatial copper concentration within the fluid. The model shows good agreement with benchmark-cases of real-life electrochemical cells found in literature. An additional flow was imposed at the bottom of a small-scale electrochemical cell in order to increase the ionic transport and thereby increase the overall performance of the cell. In a small-scale electrochemical cell in strictly laminar flow, the overall performance could be increased and stratification decreased

Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns

In the scope of this study an experimental powder coating setup is designed and the method to extract statistically significant trends from the data generated is developed. The ultimate goals are to i) validate a previously developed 3D Euler-LaGrangian numerical solver and to ii) characterize the essential parameters for industrial powder coating processes in subsequent phases. The experiments involved coating a flat plate substrate with a corona spraying pistol. The resulting coating thickness has been quantified through the state of the art Coatmaster technology. The raw data generated from the Coatmaster has been filtered and rigorously analyzed to identify statistically significant trends. Furthermore, characteristic variables have been constructed for subsequent comparison to the numerical solver. This study reveals the challenges involved in assessing experimental data to extract meaningful comparisons for numerical solver validation

Simulation-based investigation of tar formation in after-treatment systems for biomass gasification

Even-though biomass-gasification remains a promising technology regarding de-centralized sustainable energy supply, its main limitations, namely the issues of unsteady operation, tar-formation in after-treatment systems and consequential high maintenance requirements, have never been fully overcome. In order to tackle the latter two deficiencies and to increase the understanding of thermodynamic and thermokinetic producer gas phase phenomena within the after-treatment zones, a numerical system-dynamic model has been created. Thereby naphthalene has been chosen to represent the behaviour of tars. The model has been validated against a wide variety of measured and simulated producer-gas compositions. This work particularly focuses on the investigation and minimization of tar-formation within after-treatment systems at low-pressures and decreasing temperatures. Model-based analysis has led to a range of recommended measures, which could reduce the formation tendency and thus the condensation of tars in those zones. These recommendations are i) to decrease gas residence time within pipes and producer gas purification devices; ii) to increase temperatures in low-pressure zones; iii) to increase hydrogen to carbon ratio as well as iv) to increase oxygen to carbon ratio in the producer gas. Furthermore the numerical model has been included into the cloud-computing platform KaleidoSim. Thus a wider range of process parameter combinations could be investigated in reasonable time. Consequentially a simulation-based sensitivity analysis of producer-gas composition with respect to process parameter changes was conducted and the validity-basis of above recommendations was enlarged

Multiphysics Eulerian-Lagrangian electrostatic particle spray- and deposition model for OpenFOAM® and KaleidoSim® cloud-platform

A finite volume based Eulerian-Lagrangian model has been created within OpenFOAM® in order to predict the behavior of particle clouds as well as particle deposition thicknesses on substrates under the influence of electro-static effects. The model resolves close to electrode effects as well as phenomena within the entire coating chamber. It considers fluid dynamic effects, particle inertia, gravity, electric- as well as mechanic particle-particle interaction, corona formation, dynamic particle charging mechanisms, and coupling of particle motion to Reynolds-Averaged Navier-Stokes (RANS) based flow simulations. Resulting coating pattern predictions were experimentally validated. It is demonstrated qualitatively and quantitatively that the measured coating thicknesses and patterns vary by; i) applied voltage, ii) airflow rate, pistol-substrate iii) -distance and iv) –angle. Furthermore, the software has been prepared such that it works on the cloud computing software KaleidoSim®, which enables the simultaneous browser-based running of hundreds of cases for large parameter studies

A massive simultaneous cloud computing platform for OpenFOAM

Today the field of numerical simulation in is faced with increasing demands for data-intensive investigations. On the one hand Engineering tasks call for parameter-studies, sensitivity analysis and optimization runs of ever-increasing size and magnitude. In addition the field of Artificial Intelligence (AI) with its notorious hunger for data, urges to provide ever more extensive, numerically derived learning-, testing- and validation input for training e.g. Artificial Neural Networks (ANN). On the other hand the current ‘age of cloud computing’ has set the stage such that nowadays any user of simulation software has access to potentially limitless hardware resources. In the light of these challenges and opportunities, Zurich University of Applied Sciences (ZHAW) and Kaleidosim Technologies AG (Kaleidosim) have developed a publically available Massive Simultaneous Cloud Computing (MSCC) platform for OpenFOAM. The platform is specifically tailored to yield vast amounts of simulation data in minimal Wall Clock Time (WCT). Spanning approximately nine-man-years of development effort the platform now features: • An instructive web-browser-based user interface (Web Interface); • An Application Programming Interface (API); • A Self-Compile option enabling users to run self-composed OpenFOAM applications directly in the cloud; • The Massive Simultaneous Cloud Computing (MSCC) feature which allows the orchestration of up to 500 cloud-based OpenFOAM simulation runs simultaneously; • The option to run Paraview in Batch Mode such that (semi-) automated cloud-based post-processing can be performed; • The Katana File Downloader (KFD) allowing the selective download of specific output dat

Simulation based investigation of an electrostatic method for deflecting charged particle clouds

Invited talk held by V. Lienhard at NIC National Institute of Chemistry - Kemijski Institute, Ljubljana, Slovenia on January 16th 2020This invited talk focusses on the creation any application of a simulation based investigation method to predict Lagrangian particle trajectories within superposed flow- and electro-static fields. Electrically charged particles are injected into a turbulent air-flow, traced past a high-voltage electrode and towards a grounded metallic substrate. Resulting deposition patterns are studied both experimentally and via OpenFoam based simulation

Massive simultaneous cloud computing (MSCC) for multiphysics-simulation applications

The Massive Simultaneous Cloud Computing concept allows appliers and developers of Multiphysics simulation software to utilize any number of cloud-based computers simultaneously. Thus novel workflows in simulation based research and development can be introduced, focusing on simultaneous rather than on sequential computation of individual cases. On the basis of this capability the simulation-researcher/-engineer can (i) dramatically increase the parameter space of any computational parameter study, (ii) devise novel concepts of conducting optimization procedures and (iii) can ultimately even proceed to produce sufficient simulation data in order to train e.g. artificial neuronal networks. The cloud-based software platform Kaleidosim has been devised to effectively enable the handling of MSCC simulation run series of up to 500 simultaneous cloud runs. Case studies will be presented where a speed up factor of 100 has been achieved in terms of comparing MSCC based parameter studies to the standard workflow on in-house hardware

Dynamic modeling of ionized oxygen distribution within powder coating pistols

It is well known that a stable corona of ionized oxygen forms in the proximity of electrodes within powder coating pistols. What remains unclear though is the extention and shape of the ionized oxygen field, as well as its interaction with geometric boundary conditions. Therefore a Eulerian charge transport model was created within OpenFoam. It considers convective, diffusive and electro-static effects on charge distribution, as well as a dynamic coupling to the electric field. The latter is shown to be essential for obtaining a stationary solution, which amounts to a stable corona. Analysis of the result reveals unexpected yet plausible charge distribution effects within the application. The solution is validated by comparison to the point-wise measurement of potential field strength evolution on the outside of the pistol. Furthermore the new model is applied within a coupled powder coating solver which includes flow-, electric- and particle dynamic effects. This Multiphysics solver is then used to predict the corona-effect on particle charging-efficiency, as well as to compare pistol-design options and their respective impacts

Experimental characterization and simulation of a piezo-actuated micro dispensing valve

The dispensing behavior of a piezo-actuated micro-valve that closes the gap between the nanoliter range (e.g., inkjet technology) and the microliter range (e.g., standard displacement technology) has been investigated by experimental and numerical means. Water and different Newtonian model fluids with defined fluid properties were utilized for experimental characterization. The dispensed amount per single dispensing event could be freely adjusted from a few nanoliters to several hundred microliters showing the large working range and flexibility of the micro-valve, while maintaining a high accuracy with a low relative standard deviation. A correlation between fluid properties, dispensing parameters, and the resulting steady-state mass flow was established, showing good consistency of the experimental data. Furthermore, a three-dimensional numerical model for the quantitative simulation of the micro-valve's dispensing behavior regarding fluid mass flow was developed and validated, showing a high degree of correspondence between the experiments and simulations. Investigations of the transient behavior after the opening of the micro-valve revealed a nonlinear relationship between the valve opening time and dispensed mass for short opening times. This behavior was dependent on the working pressure but independent of the type of fluid