Siemens Digital Industries Software announces the latest release of its Simcenter FLOEFD software, a CAD-embedded computational fluid dynamics (CFD) tool. Simcenter FLOEFD is part of the Simcenter portfolio of simulation and test solutions that help engineers simulate fluid flow and thermal problems quickly and accurately within their preferred CAD environment. The latest version offers new modules and improvements that can improve accuracy and solve rates.

The software helps users frontload CFD simulation early into the design process to understand the behavior of their concepts and eliminate the less attractive options. The software can reduce overall simulation time by as much as 65-75% and offers up to 40 times user productivity enhancement. Part of the Xcelerator portfolio, Simcenter FLOEFD also helps design engineers contribute to the creation of a highly accurate digital twin.

The new Electronics Cooling Center module combines existing best electronics-specific capabilities and integrates new ones from Simcenter Flotherm software inside the CAD-embedded interface to enhance electronics cooling functionality. A second new module helps users create a compact Reduced Order Model (ROM) that solves at a faster rate, while still maintaining a high level of accuracy. The Power Electrification module can now simulate an electrical device as an electro-thermal compact model, which can save significant user and computational time.

Siemens Digital Industries Software
www.sw.siemens.com

The latest release of Simcenter™ STAR-CCM+ software, part of the Simcenter portfolio of simulation and test solutions for optimizing design, includes improvements to simulation time and accuracy, and enhanced collaboration. These features give customers a comprehensive digital twin to drive predictive simulations. In this release, Siemens is introducing a new parallel polyhedral mesher for faster, more effective meshing, as well as a model-driven adaptive mesh refinement (AMR) solution. The latest release also includes automatic coupled solver control for reduced set up time. Convergence speed is improved through a collaborative virtual reality (VR) feature in a CFD code for enhanced team collaboration on simulation results.

The fully-rewritten parallel polyhedral mesher builds meshes up to 30 times faster than in serial, for a consistent mesh regardless of the cores used and a more effective mesh distribution with the same accuracy and robustness. New adaptive mesh refinement (AMR) technology intelligently refines the mesh based on the physics. This can lead to less user interaction as well as computational overhead and reduces overall mesh size.

Collaborative VR in Simcenter STAR-CCM+ allows teams across the globe to interact in the same immersive virtual environment in real time, enhancing communication and decision-making. Multiple VR clients can now be connected and synchronized to the same simulation, with avatars showing the location of other users and providing the ability to tether users to get the same experience.

Simcenter STAR-CCM+ is an integrated solution for computational fluid dynamics (CFD) and multiphysics simulation that brings automated design exploration and optimization within the grasp of all simulation engineers. Simcenter and Simcenter STAR-CCM+ are part of Xcelerator portfolio, Siemens’ integrated portfolio of software, services and application development platform.

Siemens Digital Industries Software
www.sw.siemens.com

Siemens Digital Industries Software announced the latest version of Simcenter 3D software, part of the Simcenter portfolio of simulation and test solutions. Simcenter 3D helps product engineering teams be more productive and produce consistent simulation results with a unified, easy-to-use shared platform covering most simulation disciplines. The latest version delivers the most comprehensive, fully-integrated CAE solution on the market today, to help optimize design and deliver innovations faster and with greater confidence.

The latest release of Simcenter 3D includes many improvements in four key areas:

Multidiscipline Integration: Simcenter 3D offers new simulation methods that increase realism and deliver better insight into product performance. Industrially validated rotor dynamics simulation capabilities have been extended, to include nonlinear connection elements, for example, allowing engineers to minimize rotational unbalance and unnecessary external forces in applications such as aircraft engines, gas turbines, automotive engines, industrial equipment, and even electronics, for example when computer disk drives spin at high rates.

Faster CAE Processes: New Noise Vibration and Harshness (NVH) composer tool helps engineers quickly create system-level finite-element (FE) models, starting from subassembly models such as an automotive body-in-white, door, suspension, and more. Automating the full-vehicle FE model increases process speed and helps reduce human error.

Ties to the Digital Thread: The seamless integration with data management from Simcenter is extended to enhanced ties to the physical testing group. Deeper test/analysis correlation capabilities from Simcenter 3D, such as new pre-test planning for determining sensor locations, can help determine the best methods to use for physical testing and increase confidence that simulations are accurately predicting real-world results.

Open and Scalable: Simcenter 3D is an open environment where engineers and designers can gain the benefits of faster CAE processes by using Simcenter 3D in connection with other CAE solvers. Added support for cyclic symmetry can help engineers simplify the modeling and simulation process for components when using the Abaqus solver.

Simcenter 3D and the Simcenter portfolio are part of the Xcelerator portfolio, Siemens’ integrated portfolio of software, services and application development platform.

Siemens Digital Industries Software
www.sw.siemens.com

Leveraging advanced 3D CAD-embedded CFD capabilities can add robustness and fidelity to a 1D system model.

By Mike Croegaert, Siemens Digital Industries Software

A common issue with modeling complex 1D systems is adding the required detail for complex components that cannot easily be represented through correlations or empirical data. To get the data for these types of components, engineers have two options: physical testing and 3D computational fluid dynamics (CFD) simulation and analysis. Physical testing can be costly and obtaining the data can be difficult for all possible operating scenarios. Whereas, 3D CFD can be time-consuming and often requires an expert to get reliable results.

Fortunately, we now have the option to use advanced 3D CAD-embedded CFD solutions in conjunction with 1D CFD tools to quickly and accurately characterize complex components without the need for a specialist, while providing an added level of robustness to a complex system model.

The basic fuel system: solving pump limitations
To illustrate the effectiveness of using this combination, a simple passenger aircraft fuel system example will be used. Figure 1 shows a 1D system model drawn on top of the basic fuel system schematic image. It includes source components for the boundary conditions and extra loss components for items such as filters and couplings. The thin link lines represent a direct connection between adjacent components, but they are not pipes themselves. Nodes sit in the middle of the links and serve as convenient points to enter elevation data and interrogate flow results of temperature and total pressure.

During normal operation, the fuel is drawn from the tanks with mechanical fuel pumps. However, most mechanical pumps must be fully wetted to function properly. This means sometimes unusable fuel is left in the bottom of the tank. To extract the residual fuel, jet pumps can be added with the suction side connected to the lowest sump point on the inner wing tank. This pump feeds the collector cell by using the motive energy provided by a small amount of high-pressure fuel bled directly from the mechanical fuel pumps. For this example, the jet pumps are placed in the lowest portion of the tank.

In contrast to most other components, this jet pump does not come pre-supplied with performance data. That leaves the designer with two options to define performance. The first method is to enter detailed geometry for the pump and the 1D CFD tool can apply a built-in empirical correlation for jet pump behavior. The second option is a more rigorous databased approach. The pump requires a curve of flow ratio versus head ratio and a curve of motive flow rate versus pressure difference between the motive and suction arms. This data can come from many sources, including the vendor of the pump, physical testing, or 3D CFD characterization and analysis.

3D-1D characterization
Sophisticated 3D CAD-embedded CFD programs have key technologies that facilitate 1D data generation. These tools can be used by the typical engineer as well as seasoned CFD analysts. They apply automated modified wall functions to capture boundary layer effects properly, regardless of the density of the mesh in the boundary layer. They also have an automated solver to determine the flow regime between laminar, turbulent, or transitional without intervention. The most advanced 3D CAD-embedded CFD software has a unique and automated mesher that is geometry aware. If the CAD geometry changes, the mesh changes automatically, updating as the problem solves, intelligently putting more mesh where it is needed. Because these tools are completely CAD-embedded, the designer can run parametric studies, by not only varying flow conditions, but also changing the actual geometry over the course of a study, feeding data back to the 1D CFD software as seamlessly as possible.

Using an intuitive graphical interface, the designer inputs the key variables—choosing the units, the physics to consider in the simulation (including heat transfer, gravity effects and rotation), the fluids to use in the simulation, and lastly, the initial conditions such as temperature, pressure, and initial velocity. The 3D software then calculates a computational domain surrounding the relevant fluid geometry. The design engineer can resize the domain area or even slice the volume in half and do an axisymmetric simulation to save computational resources. The mesh (Figure 2), although highly automated, can be manually driven to add grid cells where needed and manually refined by selecting specific geometry, adding optional control planes, or even disabled bodies into the CAD model to serve as the mesh structure.

Once the model is prepared, the boundary conditions set, and goals determined, the simulation is ready to run launching the solver. The solver is the only aspect of 3D CAD-embedded CFD that does not operate directly in the CAD environment. Instead, a second window is launched to monitor the progress of the solution. Custom-defined preview plots for parameters such as pressure, velocity, and even the mesh can be created. Goals can also be plotted to have a real-time monitor on current value and their trend toward convergence. Parametric studies can also be performed on multiple machines at once to improve performance.

Once complete, the results are loaded back into the CAD interface, the first example of a result is a cut plot that shows the contours of velocity with overlaid streamlines (Figure 3). The cut plane can be manually adjusted with a live preview. 3D CAD-embedded CFD can also generate three dimensional flow trajectories inside of the fluid region.

Typically, for characterizing a component using 1D CFD software, multiple simulations are needed to generate data over a range of flow conditions. Once the study is complete, the results can be saved to a file that acts as a raw record of the flow conditions at each boundary at each experiment point. Each point contains data for flow rate, pressure, temperature, density, viscosity, enthalpy, and heat capacity. From this data, non-dimensional curves can be created so that the software can extrapolate performance of the part over a range of fluids, temperature, and pressures.

After the curves are created, they can be imported into the 1D CFD tool either as an individual data curve or as a complete component. The software will parse the data and automatically determine what type of component to create. Once this step is done, the 1D CFD software adds the component to the catalog and automatically populates it with the data just generated.

Before using the component in the fuel system model, it will first be verified in a unit test. Unlike most components, components sourced from the 3D CAD-embedded CFD program require no further data to use because relevant data such as the curves are pre-applied. All that is required to run a unit test is to add boundary conditions and run an analysis, and the component should perform exactly as the software predicted during the characterization step. After the unit test has verified the component was created correctly, the jet pump can be added to the fuel system model (Figure 4), and the designer can run a series of analyses.

In this example, two transient simulation scenarios will be examined. In the first simulation, the jet pump has been included but blocked the motive flow, so the tanks will only feed into the collector cell via gravity. The connection between each section of the tanks is through a series of holes in the ribs that separate each compartment. These holes span almost the entire height of the tank, but the bottom 2-in. of the tank is blocked by structure.

As shown in Figure 5a with the blue line, the outer tank is draining briefly into the inner tank marked in red. The outer tank stops flowing as the level of fuel drops below the holes in the rib. Rendering the remaining 2-in. of fuel in that tank unusable. The inner tank in red, and the collector cell in green both drain together. The collector cell is drained via the mechanical fuel pumps, and the inner tank drains via gravity into the cell until it too reaches about 2 in. of height and can no longer drain. The tank is exhausted of all usable fuel in about 125 seconds.

The second case shown in Figure5b has the jet pump enabled. Here, the jet pump is moving fuel from the inner tank to the collector cell at a rate of about 10 gal per minute. In this case, the inner tank drains much faster, but that fuel is being transferred to the collector cell to feed the pumps. Because the suction inlet to the jet pump can be placed at the lowest point in the tank, it can drain almost all of the fuel out of it before it stops providing flow. At this point, the fuel level in the collector cell starts to drop quickly until it is completely exhausted. In this case, because more fuel is available, the tank does not drain for 320 seconds, a significant improvement.

Leveraging advanced 3D CAD-embedded CFD capabilities can add robustness and fidelity to a 1D system model. The 3D CFD solution does this by characterizing complex components within the CAD environment and then automatically importing the results into the 1D model. Here, a common issue with 1D system models of aircraft fuel systems was examined: how to add the required detail to the model for complex components that cannot easily be represented through correlations or empirical data. Siemens 3D CFD software, Simcenter FLOEFD, runs inside of several CAD packages including Siemens NX and Solid Edge, CATIA V5, PTC Creo, and a standalone version. This example also uses Siemens Flomaster 1D CFD software for the system simulation.

Until recently, designers had to choose between costly physical testing and time-consuming 3D CFD that usually requires an expert to obtain reliable results. This approach that combines 3D CAD-embedded CFD and 1D CFD can be used to quickly and accurately characterize complex components without the need for a CFD analyst and provide an added level of robustness to complex models such as the aircraft fuel system.

Siemens Digital Industries Software
www.sw.siemens.com