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yao last won the day on April 7 2014

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  1. To get date in desired format, first get the complete set of nodes from Nodal Output, then parse that for just the nodes on the surface. If you are using Linux (or cygwin on Windows) you can do the following: 1. Extract the nodes for the surface in question - let's say the surface set is Wall_1 and the EBC file in MESH.DIR is Wall_1.ebc reform -3,100,1 Wall_1.ebc | sort -nu > Wall_1.nbc Wall_1.nbc will have the node numbers on the surface Wall_1 2. Get the nodes, coordinates, and temperature for the model using acuTrans: acuTrans -out -extout -to table -outv node,coordinates,temperature Let's say this creates a file called problem1_step100.out 3. Extract the information from the .out file for only the nodes on the surface: unique -i Wall_1.nbc problem1_step100.out > Wall_1.temp This will extract the lines from problem1_step100.out that have the same first column (the node number) as Wall_1.nbc. Both reform and unique are in the /tools/ directory of the Linux installation. These will also work on Windows as well if you have Cygwin installed (or some other Unix/Linux emulator).
  2. Method 1: acuRun -np 6 -hosts node1,node2 Result: The node list is repeated to use the specified number of processors. The processes are assigned: node1, node2, node1, node2, node1, node2 Method 2: acuRun -np 6 -hosts node1,node1,node2,node2,node1,node2 Result: The processes are assigned: node1, node1, node2, node2, node1, node2 Method 3: acuRun -np 6 -hosts node1:2,node2:4 Result: The processes are assigned: node1, node1, node2, node2, node2, node2
  3. 1. The head node needs to be able to RSH or SSH (without password prompt) to each compute node, and each compute node needs to be able to RSH or SSH (without password prompt) to the head node. 2. The installation and problem directories need to be 'seen' in the same location on the head node and on the compute nodes. Basically this means NFS mounted disks or the like.
  4. Early versions of ofed had a bug in the implementation of the fork() function. This function is needed byAcuSolve to properly launch parallel processes. This bug is known to appear in ofed 1.1. To determine the version of ofed installed on your system, execute the following command: rpm -q -a | grep ofed If you are having trouble launching AcuSolve in parallel, and the ofed version is 1.1, please set the following environment variable before launching the solver: setenv ACUSIM_LIC_TYPE "LIGHT" This will force AcuSolve to spawn the parallel processes using a method that works around the bug in ofed. Note that the bug was fixed in ofed 1.2 and newer.
  5. HP-MPI requires a remote shell command to spawn remote processes. AcuSolve allows users to select this remote shell via the -rsh command line parameter. This allows users to use standard UNIX/Linux utilities such as rsh or ssh in addition to custom wrapper scripts that may be necessary on some systems. Although this provides a high level of flexibility, most systems simply use ssh to perform the remote shell calls. However, this requires that the system be set up to permit password free logins. To accomplish this, the following procedure should be followed. Execute the following sequence of commands from a shell prompt: $ ssh-keygen -t dsa Press return when prompted for a password (i.e. leave it blank). $ cd ~/.ssh $ cat id_dsa.pub >> authorized_keys $ chmod go-rwx authorized_keys $ chmod go-w ~ ~/.ssh $ cp /etc/ssh/ssh_config $HOME/.ssh/config $ echo "CheckHostIP no" >> $HOME/.ssh/config $ echo "StrictHostKeyChecking no" >> $HOME/.ssh/config It may be necessary to repeat the above procedure using rsa instead of dsa (i.e. ssh-keygen -t rsa)
  6. The binding of processes to compute cores is not handled by AcuSolve itself. However, when using HP-MPI as the message passing interface, it is possible to control how the processes are distributed on each host. Consider an example involving 2 compute nodes having dual socket motherboards, and quad core processors in each socket (total of 8 cores per node). A typical core map is shown below, illustrating the socket ID and processor rank of each core: Socket Id CPU Rank 0 0,2,4,6 1 1,3,5,7 With this in mind, the following environment variable can be used to force HP-MPI to fill the cores by rank id: setenv MPIRUN_OPTIONS="-cpu_bind=v,rank" When this is set, the first process on the host will be assigned to socket 0 (filling the core with rank 0), the second process to socket 1 (filling the core with rank 1), and so on. The appropriate acuRun command to place 1 process on each socket of a dual socket quad core system would simply be: acuRun -np 4 -hosts host1,host2
  7. AcuSolve contains a set of boundary conditions that automatically sets a boundary layer profile at an inlet boundary. When using the inflow boundary condition types of mass_flux, flow_rate, and average_velocity,AcuSolve computes an appropriate boundary layer profile for the velocity and turbulence fields based on the the distance from no-slip walls, and estimated Reynolds Number. The profile is re-computed at each time step such that deforming meshes are properly accounted for in the calculation. This boundary condition provides a robust method of automatically specifying physically realistic inlet conditions. It is much more realistic than specifying a constant velocity condition for internal flow applications.
  8. If AcuFieldView is launched from AcuConsole, the default is to use the direct reader by selecting the desired problem.run.Log file. Once in AcuFieldView, a data file can be read using File > Data Input >AcuSolve [Direct Reader] > Browse to desired .Log file. Or if acuTrans or acuOut has been used to generate FieldView format data files: File > Data Input > AcuSolve [FV-UNS Export] > Browse to desired .fv file.
  9. The best way to reduce the size of ACUSIM.DIR is to write Nodal and Restart output for required time steps only. Also using the Number of saved states option for Restart Output will only save the latest restart files and can save some disk space. These things should be considered before running the simulation. In case if the simulation is already performed and a huge ACUSIM.DIR is present, User can extract the required files from ACUSIM.DIR. This can be done from command line by issuing commands acuCpProbeFiles and acuCpOutFiles to extract sufficient files for running acuProbe and Nodal output respectively.
  10. To get the nodal output on specific surfaces, indicate a non-zero value for 'Nodal time step frequency' or 'Nodal time frequency' under the SURFACE_OUTPUT command. Use 'acuTrans' as below to extract the nodal area and traction on the desired surface. The product of nodal area and nodal traction will be the nodal force components. acuTrans -osf -osfs "Wall" -osfv node,area,traction
  11. General Applications The starting point for most applications should be the steady state Spalart-Allmaras model. For most industrial applications, this model provides sufficient accuracy. For applications involving massive separation, the DES model may be used if a higher level of accuracy is required. Unsteady Simulations For the simulation of unsteady flows, users have the option of unsteady RANS (URANS), DES, or LES. Depending on the goal of the simulation, different turbulence models may be used. If the unsteadiness in the flow is driven by some type of thermal transient, then the use of URANS (i.e. the Spalart-Allmaras model in unsteady mode) is typically sufficient. If the unsteadiness is due to large scale separation and bluff body vortex shedding, the DES model or LES model should be used. For cases where small scale turbulent structure is of interest, the Dynamic LES model should be used.
  12. Disadvantages: The primary disadvantage of the Spalart-Allmaras model is seen when applied to free jet flows. For these applications, the rapid change in length scales associated with the transition from wall bounded to free shear proves to be problematic and alternative models may provide better predictions.
  13. Advantages: (a) Computational efficiency: The standard k-ε model is a classical model developed by turbulence researchers in the early 1970's, whereas the SA model is a recent model developed in the early 1990's with the objective of numerical efficiency and robustness. The SA model can perform much faster than the k-ε model for the same or better level of accuracy. ( Accuracy as Low-Re Model: Inherently, the SA model is effective as a low-Reynolds number model and provides a superior accuracy than the standard k-ε model for wall-bounded and adverse pressure gradients flows in boundary layers. The k-ε model does not perform well in boundary layers and requires additional terms to be added to the governing equations to produce boundary layer profiles. © Mathematics & Numerics: The standard k-ε model involves a two equation coupled differential system, which can lead to stiff algebraic system for non-diffusive & accurate flow solver like AcuSolve. Some numerically dissipative solvers can easily handle such stiff differential equations. On the contrary, the SA model possess a well-behaved one equation differential system.
  14. The Spalart-Allmaras model incorporates some of the recent advances in turbulence modeling that make it an excellent choice for prediction of industrial turbulent flows. Comparisons between the k-ε model and Spalart-Allmaras models regularly show that Spalart-Allmaras has equal or superior accuracy for nearly all classes of flows. In addition to this, the Spalart-Allmaras model is more computationally efficient than k-εbecause it only solves a single transport equation. Bardina, et. al. provide an excellent overview of some leading turbulence models that users can use as a reference.
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