Thermal recoil force, telemetry, and the Pioneer anomaly

Precision navigation of spacecraft requires accurate knowledge of small forces, including the recoil force due to anisotropies of thermal radiation emitted by spacecraft systems. We develop a formalism to derive the thermal recoil force from the basic principles of radiative heat exchange and energy-momentum conservation. The thermal power emitted by the spacecraft can be computed from engineering data obtained from flight telemetry, which yields a practical approach to incorporate the thermal recoil force into precision spacecraft navigation. Alternatively, orbit determination can be used to estimate the contribution of the thermal recoil force. We apply this approach to the Pioneer anomaly using a simulated Pioneer 10 Doppler data set.Comment: 10 pages, 3 figures. Published versio

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 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

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

On establishing and applying a system dynamic modeling method in the context of investigating tar formation within wood gasification systems

Invited talk held by G. Boiger at NIC National Institute of Chemistry - Kemijski Institute, Ljubljana, Slovenia on January 16th 2020As a rather uncommon example for the application of a System Dynamic modelling method, this invited talk focusses on a modelling concept, devised for resolving the thermo-chemistry within a wood gasification reactor. It compares the modelling concept as well as its results to a classic, thermo-chemical solution algorithm based on the minimization of LaGrangian Multipliers for resolving the gasification equilibrium equations. In contrast to the latter, the System Dynamic solver can consider the impact of reaction kinetics as well as molecular mass transfer effects on the gasification equilibrium. Thus the transient production rates of methane, hydrogen, carbon (di-) oxide and water, as well as the residual amounts of pyrolysis gas and oxygen, which occur during the gasification of a wood particle, can be predicted

Development and validation of a Eulerian-Lagrangian model to predict particle motion and deposition in electrostatic fields

Invited Talk held by G. Boiger at NIC National Institute of Chemistry - Kemijski Institute, Ljubljana, Slovenia, January 16th 2020This invited talk focuses on a finite-volume based Eulerian-LaGrangian model created within OpenFoam®. Its purpose is 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 a coupling of particle motion to RANS based flow simulations. Resulting coating pattern predictions were experimentally validated. Qualitative and quantitative correspondence to measured coating -thicknesses and -patterns under the variation of i) applied voltage, ii) airflow rate, pistol-substrate iii) -distance and iv) –angle, can be demonstrated. 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

Tutorial on OpenFOAM & kaleidosim : EVAL function to rotate a wind channel

YouTubeThis is a tutorial video in Prof. Gernot Boiger's series on OpenFOAM and the cloud computing platform Kaleidosim. Here the focus lies on the 'EVAL' functionality within OpenFOAM v1912 (and later). Using the 'EVAL' function the user can prescribe (dynamic) boundary conditions from inside any OpenFOAM dict, based on a multitude of mathematical expressions. In this movie the 'EVAL' function is demonstrated based on an example surrounding the classical simpleFoam Motorbike tutorial case with a 'twist'. The 'twist' is about conducting a full #aerodynamic #CFD study of the #Motorbike frame, involving 360 individual simpleFoam #simulation runs simultaneously conducted within Kaleidosim #cloud platform. Thereby each run differs in that onset-airflow velocity vector as well as the entire bounding box of the simulation vicinity (wind channel) are rotated degree after degree (step size 1°) around the Motorbike, yielding 360 simulation cases. The 'EVAL' function performs the math to rotate the bounding box based on a 2D rotation matrix with respect to the angle-of-attack, while Kaleidosim's Kaleidoscope Feature conducts a parameter-study varying the angle-of-attack step-by-step. Furthermore the video contains a demonstration of how, thanks to Kaleidosim's MSCC Massive Simultaneous Cloud Computing capacity, the entire study can be completed in no more than 25min. Find links to related tutorial videos here: 1.) OpenFoam & Kaleidosim: Creating Python Macro for Paraview based Post-Processing in the Cloud https://youtu.be/EzmkmrDnu0Y 2.) OpenFOAM & Kaleidosim: Introducing the Kaleidoscope Feature https://youtu.be/6T08Li7gVqE 3.) Live Demo of Speeding up OpenFoam Parameter Study by Factor 50 https://youtu.be/rWe4KfFDPKs 4.) Compile and Run Custom OpenFoam Solvers in the Cloud using Kaleidosim https://youtu.be/3QoQAlaCQx

Tutorial on OpenFOAM & kaleidosim : introducing the kaleidoscope feature

YouTubeThe Kaleidoscope Feature is introduced within the Kaleidosim cloud platform: Using a couple of relatively simple Python utilities, OpenFoam v1912, simpleFoam solver and the Motorbike tutorial case, Prof. G. Boiger of ZHAW_ICP does a 19min live-demo of a work-flow that would have taken four full working days only six months ago: The famous OpenFoam 'Motorbike' tutorial case is modified such that relative onset flow velocity as well as the entire wind channel are being rotated in 360 steps (one step per degree and 360° in total) around the 'Motorbike'. One single base-case is prepared introducing variable parameters within 'initialConditions' and 'blockMeshDict' dictionaries such that: @Variable-Parameter-Name@. Here the variable parameter is the #Angle-of-Attack. The 'eval' function of OpenFoam v1912 is used as well as since wind-channel coordinates are modified with respect to variable angles and using 'sin' and 'cos' functions. The thus prepared base-case is uploaded to Kaleidosim cloud platform. Then the 'Kaleidoscope Feature' comes into play: 360 individual turbulent steady-state OpenFoam simulation cases are created automatically and run simultaneously in the cloud using Kaleidosim (MSCC Massive Simultaneous Cloud Computing). Drag- and lift- coefficients are being calculated and evaluated for each case from parsing terminal output. One Paraview image is being automatically created per simulation run in the cloud using Paraview-Batch-Mode via a prepared Python script that was uploaded along with the OpenFoam case. Results are selectively downloaded from the cloud using the #Katana File Downloader function and Paraview images are automatically forged into one movie, rotating the view around the 'Motorbike' along with resulting turbulent flow-field calculation. It is shown that the whole immense workflow, comprising 360 individual simulation runs on a 300k cell mesh, is completed in just 28min

Tutorial on OpenFoam & kaleidosim : creating Python macro for paraview based post-processing in the cloud

YouTubeIn this tutorial video Prof. G. Boiger of ZHAW_ICP demonstrates how to record and modify a Python script such that it can be used for automated Paraview - based post-processing using Kaleidosim cloud software. The demo-case is an OpenFOAM run using simpleFoam solver on the classic 'Motorbike' tutorial case. Activating Paraview's 'Python Trace' function in order to track the workflow, simulation results are visualised and screen shots are stored. After recording, the Python utility is stored and then manually modified such as to allow it to be run more generically... e.g. within Kaleidosim's cloud-based virtual machines. Here are links to other, related tutorial videos to which the speaker refers: OpenFOAM & Kaleidosim: Introducing the Kaleidoscope Feature https://youtu.be/6T08Li7gVqE Live Demo of Speeding up OpenFoam Parameter Study by Factor 50 https://youtu.be/rWe4KfFDPK