ansys-simulation

name ansys-simulation description Automate ANSYS Fluent CFD simulations via Python scripting and journal files category integrations domain fluids complexity advanced dependencies [] ANSYS Simulation Integration Comprehensive guide for automating ANSYS Fluent CFD (Computational Fluid Dynamics) simulations using Python scripting, journal files, and the PyAnsys ecosystem. Overview ANSYS Fluent is a leading commercial CFD solver used for simulating fluid flow, heat transfer, and related phenomena in complex geometries. This skill covers automation approaches for: ANSYS Workbench : Unified platform for CAD integration, meshing, and workflow management ANSYS Fluent : Advanced CFD solver with extensive physics models PyAnsys : Python API ecosystem for programmatic control Journal Files : Text-based scripting for batch operations ANSYS Workbench and Fluent Architecture ANSYS Workbench Project-based workflow environment Integrates multiple ANSYS tools (Fluent, CFX, Mechanical, etc.) Supports parametric studies and design optimization Provides geometry and meshing tools (DesignModeler, SpaceClaim, Meshing) ANSYS Fluent Finite volume-based CFD solver Extensive turbulence models (k-epsilon, k-omega SST, LES, DES) Multiphase flow capabilities Heat transfer and combustion modeling User-defined functions (UDFs) in C Text User Interface (TUI) for scripting Licensing Requirements Commercial Licensing ANSYS products require commercial licenses managed through the ANSYS License Manager: Fluent License Types : HPC licenses for parallel computing Solver licenses (increment-based) PrepPost licenses for pre/post-processing License Server Setup : # Set license server environment variable export ANSYSLMD_LICENSE_FILE=1055@license-server.company.com # Or in Windows set ANSYSLMD_LICENSE_FILE=1055@license-server.company.com License Checkout : Licenses are checked out when starting Fluent and returned on exit HPC Licensing : Additional licenses required for parallel runs (typically cores/4) Academic Licensing Student/teaching licenses available with limitations Typically limited mesh size and solver capabilities Separate license file required Important Notes Always verify license availability before batch runs Consider license usage in automated workflows Use -t flag to specify number of processors for HPC licensing PyAnsys - Python API Introduction PyAnsys provides a Pythonic interface to ANSYS products, enabling: Remote or local session management Programmatic control of simulation setup Data extraction and post-processing Integration with Python data science stack Installation # Install PyFluent (for Fluent automation) pip install ansys-fluent-core # Install other PyAnsys packages as needed pip install ansys-mapdl-core # For Mechanical pip install ansys-dpf-core # For post-processing pip install ansys-geometry # For geometry operations Basic PyFluent Usage from ansys.fluent.core import launch_fluent # Launch Fluent session session = launch_fluent(precision= 'double' , processor_count= 4 , mode= 'solver' ) # Access TUI commands session.tui.file.read_case( 'case_file.cas' ) # Execute commands session.tui.solve.iterate( 100 ) # Clean exit session.exit() Key PyAnsys Components ansys-fluent-core : Main Fluent automation package ansys-fluent-visualization : Post-processing and visualization ansys-geometry : CAD operations and geometry manipulation ansys-meshing : Automated meshing workflows Journal File Scripting Journal files are text-based scripts containing TUI commands executed sequentially by Fluent. Journal File Format ; Comments start with semicolon ; Commands follow TUI menu structure /file/read-case case_file.cas /solve/initialize/initialize-flow /solve/iterate 1000 /file/write-data result.dat /exit yes Running Journal Files # Run Fluent in batch mode with journal file fluent 3ddp -g -i journal.jou > fluent.log # Flags: # 3ddp: 3D double precision # -g: Run without GUI # -i: Input journal file # -t4: Use 4 processors Journal File Best Practices Use absolute paths for file I/O Include error checking where possible Add comments for maintainability Test interactively before batch execution Redirect output to log files for debugging Common Workflow 1. Geometry Import Via PyFluent: from ansys.fluent.core import launch_fluent solver = launch_fluent(precision= 'double' , processor_count= 4 ) # Import geometry solver.tui.file.import_.cad_geometry( 'geometry.scdoc' , 'yes' # Confirm import ) Via Journal File: /file/import/cad-geometry geometry.step yes 2. Meshing Setup Mesh Generation Strategy: Surface mesh extraction from CAD Volume mesh generation (tetrahedral, hex, poly) Boundary layer refinement for wall-bounded flows Mesh quality checks PyFluent Meshing: from ansys.fluent.core import launch_fluent meshing = launch_fluent(precision= 'double' , processor_count= 4 , mode= 'meshing' ) # Import geometry meshing.workflow.InitializeWorkflow(WorkflowType= 'Watertight Geometry' ) # Set meshing parameters meshing.meshing.GlobalSettings.set_state({ 'MaxSize' : 0.1 , 'MinSize' : 0.001 , 'GrowthRate' : 1.2 }) # Generate mesh meshing.meshing.GenerateMesh() # Switch to solver solver = meshing.switch_to_solver() Journal File Meshing: /mesh/scale 0.001 0.001 0.001 /mesh/check /mesh/repair-improve/repair 3. Physics Setup Turbulence Models: k-epsilon: General purpose, wall functions k-omega SST: Better for adverse pressure gradients, boundary layers LES/DES: Large eddy simulation for transient, high-fidelity Material Properties: Fluid properties (density, viscosity, thermal conductivity) Solid properties for conjugate heat transfer PyFluent Physics Setup: # Enable energy equation solver.tui.define.models.energy( 'yes' ) # Set turbulence model (k-omega SST) solver.tui.define.models.viscous.kw_sst( 'yes' ) # Define material properties solver.tui.define.materials.change_create( 'water-liquid' , 'water' , 'yes' , 'constant' , 998.2 , # Density 'yes' , 'constant' , 0.001003 # Viscosity ) # Assign material to cell zone solver.tui.define.boundary_conditions.fluid( 'fluid-zone' , 'yes' , 'water' , 'no' , 'no' , 'no' , 'no' , 0 , 'no' , 0 , 'no' , 0 , 'no' , 'no' ) Journal File Physics: /define/models/energy yes no no no no /define/models/viscous kw-sst yes /define/materials/change-create air air yes constant 1.225 yes constant 1.7894e-05 4. Boundary Conditions Common BC Types: Velocity inlet Pressure outlet Wall (stationary, moving, rotating) Symmetry Periodic PyFluent BC Setup: # Velocity inlet solver.tui.define.boundary_conditions.velocity_inlet( 'inlet' , 'yes' , 'no' , 'yes' , 'yes' , 'no' , 10 , # Velocity magnitude (m/s) 'no' , 0 , 'no' , 0 , 'no' , 300 , # Temperature 'no' ) # Pressure outlet solver.tui.define.boundary_conditions.pressure_outlet( 'outlet' , 'yes' , 'no' , 0 , # Gauge pressure 'no' , 300 , 'no' , 'yes' ) # Wall with no-slip solver.tui.define.boundary_conditions.wall( 'wall' , 'yes' , 'no' , 'no' , 0 , 'no' , 0 , 'no' , 'yes' , 'no' , 0 ) 5. Solver Settings Solution Methods: Pressure-velocity coupling (SIMPLE, SIMPLEC, PISO, Coupled) Discretization schemes (first-order, second-order upwind, QUICK) Gradient evaluation (least squares, Green-Gauss) PyFluent Solver Configuration: # Set pressure-velocity coupling solver.tui.solve. set .p_v_coupling( 24 ) # 24 = Coupled # Set discretization schemes solver.tui.solve. set .discretization_scheme.pressure( 12 ) # Second order solver.tui.solve. set .discretization_scheme.mom( 1 ) # Second order upwind solver.tui.solve. set .discretization_scheme.k( 1 ) solver.tui.solve. set .discretization_scheme.omega( 1 ) # Set under-relaxation factors solver.tui.solve. set .under_relaxation.pressure( 0.3 ) solver.tui.solve. set .under_relaxation.mom( 0.7 ) # Initialize flow field solver.tui.solve.initialize.initialize_flow() # Run iterations solver.tui.solve.iterate( 1000 ) Convergence Criteria: # Set residual convergence criteria solver.tui.solve.monitors.residual.convergence_criteria( '1e-6' , # continuity '1e-6' , # x-velocity '1e-6' , # y-velocity '1e-6' , # z-velocity '1e-6' , # energy '1e-6' , # k '1e-6' # omega ) 6. Post-Processing Data Extraction: # Create surface for reporting solver.tui.surface.iso_surface( 'pressure' , 'iso-surface-1' , 'fluid-zone' , '()' , 101325 ) # Export data solver.tui.file.export. ascii ( 'surface-data.csv' , 'iso-surface-1' , '()' , 'yes' , 'pressure' , 'velocity-magnitude' , '()' ) # Calculate force on wall solver.tui.report.forces.wall_forces( 'yes' , 'wall-zone' , '()' , 'yes' , 'no' , 'yes' ) Visualization: # Generate contour plot (requires GUI mode or visualization package) solver.tui.display. set .contours.filled_contours( 'yes' ) solver.tui.display.contour( 'pressure' , 'pressure' , 0 , 0 , 'surface-1' , '()' ) # Save image solver.tui.display.save_picture( 'pressure_contour.png' ) Batch Mode Execution Linux/Unix Batch Execution #!/bin/bash # batch_fluent.sh # Set license server export ANSYSLMD_LICENSE_FILE=1055@license-server.com # Set number of processors NPROCS=8 # Run Fluent in batch mode fluent 3ddp -g -t ${NPROCS} -i simulation.jou > fluent_ ${NPROCS} cores.log 2>&1 # Check exit status if [ $? -eq 0 ]; then echo "Simulation completed successfully" else echo "Simulation failed - check log file" exit 1 fi Windows Batch Execution @echo off REM batch_fluent.bat set ANSYSLMD_LICENSE_FILE=1055@license-server.com set NPROCS=8 "C:\Program Files\ANSYS Inc\v241\fluent\ntbin\win64\fluent.exe" 3ddp -g -t%NPROCS% -i simulation.jou > fluent.log 2>&1 if %ERRORLEVEL% EQU 0 ( echo Simulation completed successfully ) else ( echo Simulation failed - check log file exit /b 1 ) Python-Based Batch Execution import subprocess import os from pathlib import Path def run_fluent_batch ( journal_file, num_procs= 4 , log_file= 'fluent.log' ): """ Run Fluent in batch mode with journal file. Args: journal_file: Path to journal file num_procs: Number of processors log_file: Output log file name Returns: bool: True if successful, False otherwise """ # Set license server os.environ[ 'ANSYSLMD_LICENSE_FILE' ] = '1055@license-server.com' # Build command cmd = [ 'fluent' , '3ddp' , # 3D double precision '-g' , # No GUI f'-t {num_procs} ' , # Number of processors '-i' , journal_file ] # Run simulation with open (log_file, 'w' ) as log: result = subprocess.run( cmd, stdout=log, stderr=subprocess.STDOUT, text= True ) return result.returncode == 0 # Example usage if __name__ == '__main__' : success = run_fluent_batch( journal_file= 'simulation.jou' , num_procs= 8 , log_file= 'fluent_run.log' ) if success: print ( "Simulation completed successfully" ) else : print ( "Simulation failed - check log file" ) Parametric Studies import numpy as np from ansys.fluent.core import launch_fluent def parametric_study ( velocities, case_file ): """ Run parametric study varying inlet velocity. Args: velocities: List of inlet velocities to test case_file: Base case file """ results = {} for velocity in velocities: print ( f"Running simulation with velocity = {velocity} m/s" ) # Launch Fluent solver = launch_fluent(precision= 'double' , processor_count= 4 ) # Read base case