CONVERGE is a leading computational fluid dynamics (CFD) software package with an emphasis on accuracy, efficiency, and innovation. With truly autonomous meshing, state-of-the-art physical models, and the ability to easily accommodate complex moving geometries, CONVERGE is fully equipped to help you solve the hard problems.
Innovative Meshing
CONVERGE features fully autonomous meshing, which eliminates all user meshing time from the simulation process. In addition, CONVERGE’s novel cut-cell approach perfectly represents your geometry—no matter how complex—and easily accommodates moving boundaries. This approach avoids the numerical viscosity generated by deforming meshes and offers accurate results without intensive hands-on setup. Moreover, Adaptive Mesh Refinement allows you to efficiently achieve the best solution possible for a given computational expense by adding cells when and where they are needed to resolve key flow phenomena.
Capture Essential Physical Processes
Going beyond a visually appealing simulation to obtaining useful, realistic results requires accurate physical modeling. CONVERGE contains an extensive suite of well-validated physical models for simulating everything from fluid-structure interaction and conjugate heat transfer to spray and combustion. In addition, CONVERGE includes the SAGE detailed chemistry solver, which is fully coupled with the flow solver for maximum accuracy and efficiency. If you’re interested in implementing a custom model, you can easily do so through user defined functions (UDFs) to customize CONVERGE to meet your needs.
Accelerate R&D
CONVERGE is designed to simplify and expedite the research and design process for an expansive range of applications, from gas turbine engines to mechanical heart valves. With CONVERGE, you can perform a comprehensive system analysis and optimization to find the best design before building an expensive physical prototype. Since 3D CFD simulations can require long runtimes, CONVERGE enables highly parallel simulations on many processors and demonstrates excellent scaling even on thousands of cores. Taking advantage of these capabilities can drastically reduce time-to-solution for your simulations. Overall, incorporating CONVERGE into your R&D workflow can reduce costs across the board and enable you to bring your product to market sooner.
What’s New in CONVERGE 5?
CONVERGE 5, the latest major release of our CFD software, includes many exciting new features and enhancements that expand both the capability and usability of the code across industries and applications.
Rockets
The conditions inside of a liquid rocket combustor span an immense range of pressures and temperatures during operation. Combustion temperatures can reach 200 times the temperatures of stored propellant, and pressures in the injector and combustion chamber are orders of magnitude greater than at the nozzle exit. In addition, phase change is omnipresent, with opportunities for vaporization as the liquid fuel or oxidizer cools the engine on its path to the combustion chamber, cavitation in the turbopumps or injectors, solidification as ice forms near the cold walls, and condensation at the nozzle outlet. These changes in phase can occur even before the combustion reactions convert the fuel and oxidizer into gas-phase products to propel the device. To accurately simulate liquid rocket combustors, you need to be able to capture the phase transitions and associated property changes under these extreme conditions.
CONVERGE 5 includes a real-fluid model (RFM) that can represent fluids with a realistic (i.e., non-ideal) equation of state. RFM imposes a phase equilibrium constraint on the transported species, so that the effective phase of any mixture realized in the model is a function only of the species concentrations, pressure, and temperature, as well as the equation of state. This approach differs from the volume of fluid approach, which requires either transporting the void fraction or representing the gas and liquid phases as separate transported quantities with an additional phase transition model. RFM can handle fluids across a broad range of the phase diagram, including supercritical areas, and it allows for multi-phase, multi-component treatment of mixtures governed by the vapor-liquid equilibrium associated with minimization of the Gibbs free energy. This method enables thermodynamically consistent treatment of mixtures and allows you to model multi-component processes, including absorption, separation, and gas dissolution. RFM also includes a blending feature that reduces the computational cost of multi-species cases, opening the door to realistic simulations of mixing and combustion in rocket engines.
Furthermore, CONVERGE 5 introduces the capability to use an enthalpy-pressure-based fluid property table, in addition to pressure-temperature tables. In the two-phase region of the phase diagram for pure species and some special cases of mixtures (e.g., azeotropic mixtures), pressure-temperature tabulation isn’t appropriate because those thermodynamic variables are not independent. Pressure and enthalpy, however, are independent, and using these properties, along with species mass fractions, allows you to determine the quantities and locations of liquid and vapor conditions at equilibrium. This enhancement allows for more accurate simulations of liquid rocket engines.
Additional improvements include increased stability for cases with high CFL numbers, which is important for the high Mach flows found in rocket nozzles and for external aerodynamics studies. For SAGE detailed chemistry combustion cases, the solver has been enhanced to allow for additional fuel and oxidizer species, including hydrogen peroxide and hydrazine. All of these improvements help to position CONVERGE at the forefront of rocket CFD.
Battery Systems
CONVERGE 5 contains a variety of new models and features that improve the accuracy and expand the capabilities of battery simulations.
The new solidification/melting model enables you to investigate novel cooling strategies involving phase-change materials (PCMs). PCMs, such as paraffin wax, can act as a temperature regulator, absorbing heat during the melting process and releasing heat during solidification. This passive cooling approach is lightweight, compact, and efficient, and the variety of PCMs available with different transition temperatures allows you to choose the best material for your battery’s thermal requirements. The solidification/melting model simulates the solid-liquid phase change using an enthalpy-porosity method. This approach can account for buoyancy effects and can be used with transient 3D conjugate heat transfer modeling to simulate PCM battery cooling.
The Lagrangian solid parcel wall film model is useful for modeling solid ejecta deposition and heat transfer during battery thermal runaway. With this approach, solid parcels vented from a faulty battery cell can stick to nearby surfaces and transfer heat to those solids. This model helps manufacturers investigate if battery cell venting is likely to contribute to thermal runaway propagation to adjacent cells.
CONVERGE 5 also includes a new detailed electrochemical modeling approach for lithium-ion batteries called the pseudo-2D (P2D) electrochemical model. This model takes into consideration the transport phenomena occurring in both the solid and the electrolyte phases and accounts for spatial variations. Compared to the Single Particle Model introduced in CONVERGE 4, the P2D model is more detailed, and thus more accurate, but also more computationally expensive. The range of electrochemical modeling options in CONVERGE allows you to balance speed and accuracy for your particular case.
The new 3D short-circuit model couples with the electric potential solver and allows users to model internal short-circuit events caused by a foreign object, such as a nail, penetrating a battery cell. Nail penetration tests are commonly performed during battery development to evaluate the risk of thermal runaway. With this model, you can simulate that test to virtually evaluate the safety of your battery pack, helping to save time and money by conducting fewer experimental tests.
Another new feature in CONVERGE allows you to conduct flammability and autoignition risk analysis. This feature enables quick risk analysis for flammable volumes and self-ignition risk during battery venting of combustible products. In this approach, you generate 0D chemical equilibrium and 0D tabulated kinetics of ignition tables using CONVERGE’s chemistry tools. You can then run your 3D battery venting simulation without the need for a 3D combustion model to rapidly obtain insight into the location of flammable mixtures and the risk that those mixtures will ignite.
Fuel Cells
CONVERGE 5 includes several new electrochemistry and multi-phase flow modeling approaches that enable accurate simulations of fuel cells.
The coupled electric potential solver can provide high-fidelity results for fuel cell simulations. The electric potential solver predicts current and associated heat transfer by solving the full partial differential equations for the ion and electron fields using source terms from the Butler Volmer equations.
An alternative approach to the electric potential solver is the lumped electrochemistry model, currently implemented as a user-defined function (UDF). This simplified 0D approach solves the electric potential balance equation at the cathode catalyst and can provide faster turnaround time for fuel cell simulations.
The multi-phase flow in the fuel cell can be solved using various approaches based on your simulation requirements for fidelity versus runtime. The highest fidelity approach is to use the multi-phase drift flux model for porous media, which solves for the transport of the gas and liquid species and accounts for the different permeabilities of the phases in the porous media. For cases where we don’t need to consider the effects of the porous media, we can conduct a regular species-based volume of fluid (VOF) simulation. In CONVERGE 5, we introduced a new pseudo-multi-phase model in which the liquid water is represented by a gas with the same properties as water vapor. While this method is lower fidelity than the other approaches, it can significantly accelerate fuel cell simulations, enabling a faster exploration of the design space.
These various approaches can be used in different combinations to achieve the accuracy and efficiency needed for your simulation studies.
Electric Motors
There are several new updates that help users manage complex electric motor geometries and streamline the process of setting up conjugate heat transfer (CHT) simulations of motor cooling.
CONVERGE Studio features an option that will automatically generate CHT interfaces when you import a CAD geometry. The import CAD functionality can also automatically create boundary names, define regions, and group CAD components based on the CAD assembly. This feature can significantly reduce the time it takes to set up electric motor cooling simulations.
CONVERGE Studio 5 also includes a new CAD Editor module. This module allows you to modify and manipulate CAD geometries directly in CONVERGE Studio before triangulating the surface. In the CAD Editor, you can manage the names of bodies, regions, and boundaries; perform uniting, deleting, extraction, and extrusion operations; patch holes; transform the geometry; and generate and validate your surface mesh. Especially for complex geometries like electric motors, the CAD Editor makes it easy to clean up and prepare your geometry to ensure a high-quality triangulation for your CFD simulations.
In addition to the CAD-related enhancements, CONVERGE 5 includes a new species sub-cycling option for VOF multi-phase simulations, which is useful for liquid-cooled motors. Species sub-cycling is an acceleration method that allows you to solve species density and species transport equations at a low CFL number, while using a higher CFL value for other equations. This technique accelerates the simulation while allowing you to maintain a sharp interface between phases.
Internal Combustion Engines
Conducting accurate CFD simulations of internal combustion engines requires a surrogate fuel blend that captures the behavior of the real-world fuel. CONVERGE’s surrogate blender tool allows you to create a multi-component surrogate fuel by optimizing the mass fractions of user-defined fuel components to match prescribed property targets, such as distillation range, viscosity, and octane number. The octane number represents a fuel’s ability to resist knock, a phenomenon that can cause pressure fluctuations in the cylinder and potentially damage engine components. In previous versions of CONVERGE, the surrogate blender tool relied on correlations to determine a surrogate fuel’s octane rating. However, the octane number obtained from the correlations did not necessarily match the octane number derived from the chemical mechanisms used in the 3D CFD simulations, which could lead to unexpected knocking behavior.
To address this, we developed an approach to determine the octane number directly from the chemical kinetics during the surrogate blender optimization process using CONVERGE’s 0D chemistry tools. This approach ensures that the octane ratings used by the surrogate blender are consistent with the kinetic mechanism. However, with this approach, the optimization time is strongly dependent on the size of the mechanism. A single optimization requires running hundreds of 0D reactor cases sequentially, which can add up quickly for large mechanisms. To overcome this limitation, you can calculate RON and MON values using CONVERGE’s 0D chemistry tools for a random sample of fuel surrogates before starting the fuel blender optimization process. These cases can be run in parallel, so given sufficient computational resources, the runtime can be reduced to the time it takes to run a single case. During the fuel blender optimization process, you can then use a regression method to obtain the RON and MON values for each test case based on the pre-calculated values, which are then averaged to find the octane number.
While 3D CFD simulations have proven to be effective at predicting knock magnitude and location, they can be expensive because of the small time-steps needed to capture the propagating pressure waves. CONVERGE 5 offers an alternative approach: the Livengood-Wu autoignition model, which predicts engine knock based on average in-cylinder parameters. This model allows you to use a much higher Mach CFL number, which significantly reduces runtime for knock simulations.
CONVERGE 5 also offers expanded capabilities for modeling hydrogen engines. In previous versions of CONVERGE, the thickened flame model (TFM) was available for use with large eddy simulation (LES) modeling. In CONVERGE 5, TFM can now also be used with Reynolds-Averaged Navier-Stokes (RANS) simulations. For hydrogen combustion, where the flame thickness is very thin, this feature allows you to track the flame front at a much lower computational cost.
Furthermore, CONVERGE 5 introduces a preliminary Lagrangian modeling framework for gas-phase parcels, adding to the established options for liquid and solid parcels. CONVERGE considers spherical gas “droplets” as the basis for gas parcel modeling. These gaseous spheres are treated as compressible, meaning their density depends on pressure and temperature, and their radius may vary even if the parcel mass does not change. CONVERGE 5 includes several sub-models for gas parcels, including drag, turbulent dispersion, heat transfer, and consolidation models. The gas parcels option is useful for modeling hydrogen direct injection.
Aftertreatment Systems
CONVERGE 5 contains a variety of new and enhanced features for modeling aftertreatment systems.
The spray database approach is an acceleration scheme that can be coupled with the fixed flow feature to further speed up simulations with sprays, such as in a urea/SCR system. When this approach is activated, the spray parcel’s properties will be recorded at the time instances right before they hit the wall. During subsequent cycles, the recorded spray parcels will be sequentially emitted at the same impingement locations instead of being emitted from the injector. The spray-wall interactions are still evaluated to determine the outcomes of the parcels, e.g., filming, splashing, or rebounding. Users have the option to delete any splashed or rebounded parcels after the impingement. Because these parcels are not tracked all the way from the injector to the wall, the simulation time-step is not limited by the spray parcel movement. When coupled with fixed flow, the spray database approach significantly speeds up simulations of aftertreatment systems and film deposition.
For accurate predictions of the location and quantity of urea deposits, CONVERGE offers a urea deposit growth model. This model has been improved in CONVERGE 5 so that it now considers a transitional temperature range for the solidification of urea, centered on the urea critical temperature, which the solver uses to determine whether or not the urea will solidify. In addition, the improved model accounts for the decomposition of already solidified urea deposits on the wall. This model can be coupled with the MORPH feature, which will deform the boundary based on the predicted urea deposit growth. This allows the simulation to accurately capture the impact of solid deposits on the surrounding flow in the system.
CONVERGE 5 includes several other features that are useful for aftertreatment simulations. The split surface chemistry solver in version 5 improves predictions for three-way catalysts, lean NOx traps, and other surface chemistry cases. The Friedrich-Wegener model can simulate film separation over a sharp corner based on a force balance of inertial, surface tension, and gravitational forces. Finally, the deposit risk model is an empirical model that predicts the risk of urea deposit formation—an efficient alternative to simulating urea growth deposits directly.
Pumps and Compressors
Due to their complex moving geometries, sealing is an important feature for modeling pumps and compressors in CONVERGE. The sealing capabilities in CONVERGE 5 have been enhanced to improve stability and performance, which has also simplified the setup process for sealing cases. There are two main scenarios in which you might incorporate sealing into your pump and compressor simulations. First, you may wish to remove tiny gaps from the simulation domain that are created by two moving boundaries coming into close proximity with one another. This scenario is common in rotary devices, such as screw and vane compressors. The second scenario arises if the device you’re modeling contains a watertight seal, and you wish to replicate that seal in your simulation. Flexible impeller pumps and progressive cavity pumps are two examples where this scenario might occur.
The Under-Relaxation Steady (URS) solver has also been enhanced in version 5 to improve stability and achieve faster convergence. Steady-state simulations are useful for fast predictions of global metrics in centrifugal pumps. Studying these metrics for various speeds and operating conditions provides valuable insight to help you optimize the performance of the pump.
Another solver enhancement allows users to employ pressure-enthalpy tables for determining fluid properties. This enhancement allows for more accurate simulations of pumps and compressors operating with supercritical fluids and/or in two-phase regimes. This feature enables you to study applications such as supercritical CO2 compressors and wet compression, which are used in the air conditioning and refrigeration industries.
CONVERGE’s fluid-structure interaction (FSI) modeling capabilities have also been expanded in version 5 with the addition of the FSI membrane model. The membrane model can simulate the deformation of thin-walled structures in response to fluid flow, and it can be used in conjunction with other FSI modeling techniques. This is beneficial for simulations of diaphragm pumps, in which you can use the membrane model for the diaphragm and apply CONVERGE’s rigid FSI modeling to capture the motion of the valves.
Furthermore, CONVERGE 5 includes a new 1D flow solver, which can be used to efficiently model flows in long pipes or channels. With this new feature, you can conduct coupled 1D-3D simulations by applying the 1D solver in a portion of the domain and the 3D flow solver in another. This coupled approach can help speed up simulations of pumps and compressors with extensive upstream/downstream piping, allowing you to obtain accurate boundary conditions at the pipe entrances without needing to model the pipes in 3D.
Wind Energy
Modeling wind farms provides crucial insights into how wake effects from upstream turbines affect the efficiency and power of downstream turbines, which allows engineers to optimize the layout. Due to the size of the domain and the number of turbines involved, however, wind farm simulations can be very computationally expensive. CONVERGE 5 includes a new actuator-disk model (ADM), which is a highly efficient rotor model that can substantially reduce the cost of wind farm simulations. ADM represents the rotor as a disk and adds body forces to the CFD cells around the disk such that a prescribed total thrust and torque are applied to the fluid. ADM can be used on a coarse grid, which helps to further reduce the cost of the simulations while still capturing the essential flow dynamics of the wind turbine wakes.
Another enhancement in version 5 is the addition of an isotropic turbulence initialization method for LES models. This feature perturbs the initial resolved velocity field throughout the computational domain to mimic the turbulence spectrum. LES modeling is widely used for wind turbine simulations, especially for studies focused on the interaction between atmospheric turbulence and wake structures, and this new perturbation method increases the efficiency of these simulations by stimulating the generation of turbulence.
CONVERGE 5 also introduces flow profiles for gas-phase and compressible multi-phase VOF cases. The gas-phase flow profile, which is important for atmospheric boundary layer simulations, generates expected mean wind profiles following either the log law or power law as the inflow and initial conditions. Together with the turbulence perturbation method, this feature is critical for wind energy and civil engineering projects. The VOF flow profile is useful for handling compressible gas in marine environments, such as offshore wind turbines, gas leakage from seabeds, cavitation of boat propellers, compressed air inside oscillating water columns, and more.
Oil & Gas
Automating your CFD workflow can help increase efficiency and productivity by reducing the time spent on routine/repetitive tasks and allowing you to evaluate more geometries and design iterations. Using the custom panel feature in CONVERGE Studio, you can customize your case setup inputs and fully automate the case setup process. Custom panels can be created for any application where automation is beneficial, as demonstrated by the custom panel we developed specifically for drill bit simulations. Through this custom panel, you can automatically configure boundary names and types, assign boundary conditions, define solver settings, specify the meshing strategy, and fully automate your post-processing analysis. Your simulation workflow is simplified to importing your CAD geometry, performing any necessary geometry cleanup operations using built-in tools, and defining a limited set of user inputs in the custom panel. The case will then be set up automatically, and all that’s left to do is run your simulation.
In addition to the custom panels, CONVERGE 5 introduces the capability to couple erosion modeling with the MORPH feature, which moves the surface triangles to deform the surface in accordance with the erosion rate. This new capability also accounts for the effect of the surface deformation on the future erosion rate, increasing the accuracy of erosion simulations. This feature is useful for many applications in the oil & gas industry, including studying erosion on valve seats, impeller blades, drill bits, pipelines, and other drilling and transport equipment.
Gas Turbines
Gas turbine engines are characterized by complex interactions between combustion, turbulence, sprays, heat transfer, and a variety of other physical phenomena. To effectively model these complex systems, you need high-fidelity physical models, accurate chemistry, and finer meshes. At Convergent Science, we are continuing to improve and refine our modeling capabilities, including enhancements to our RANS and LES turbulence models in CONVERGE 5. In addition, we continue to lead the Computational Chemistry Consortium (C3), which aims to develop comprehensive and accurate chemical mechanisms. Recent work has focused on improving and incorporating chemistry for alternative fuels such hydrogen and ammonia. New chemical mechanisms are released periodically to the public to ensure widespread access to the advanced tools developed as part of the C3 consortium. We continue to enhance the mechanism extraction, reduction, and optimization tools in CONVERGE to help users translate the comprehensive detailed chemical mechanisms into smaller mechanisms ideal for CFD simulations. Furthermore, we are continuously advancing our steady-state combustion models to enable our clients to run faster gas turbine simulations.
In addition to accurate physical models, access to advanced high-performance computing (HPC) resources is critical for large gas turbine simulations. We continue to develop our cloud computing platform, CONVERGE Horizon, which provides easy and affordable access to top-tier computing hardware. We routinely add new and updated hardware options to the platform to ensure our users are getting access to the latest and greatest resources available. In addition, we continuously test and optimize CONVERGE to scale efficiently on thousands of cores, so you can take advantage of HPC to speed up your simulations.
Biomedical
To realistically simulate blood flow throughout the circulatory system, you need to capture the deformation of flexible blood vessels, which reduces the pressure required to move the fluid. The FSI membrane model in CONVERGE 5 can simulate the deformation of thin-walled structures in response to fluid flow. When using this model, CONVERGE treats the surface triangles comprising the membrane as a finite element mesh. The solver applies a linear elastic model to calculate the membrane deformation in three dimensions according to local fluid forces and specified material properties.
In addition to the membrane model, CONVERGE offers the ability to couple with the Abaqus FEA solver for more complex deformation studies in which hyperelastic or anisotropic material models may be required for tissue or for medical devices using composites. With this approach, CONVERGE calculates the fluid forces and passes them to Abaqus at each time-step. The Abaqus solver uses those forces to calculate the deformation of the solid through an FEA approach, then transfers the surface deformation data back to CONVERGE. This coupled approach enables accurate studies of cases such as valve leaflet deformation, aneurysm growth, thrombosis breakdown, stent deployment, and many others.
GPU Solver
GPUs have recently gained significant interest in the CFD community because of their potential to speed up CFD simulations. CONVERGE 5 features a new limited GPU solver for transient, incompressible, cold flow simulations. The GPU solver uses a SYCL framework, which enables the solver to run on GPUs from any vendor. In our studies so far, one NVIDIA A100 GPU provides over a 2x speedup compared to 128 AMD Milan cores. While the initial GPU solver implementation is limited, more features and functionalities will be added in future releases.
Machine Learning for Rapid Optimization
Coupling machine learning (ML) techniques with CFD opens the door to rapid optimization studies that can help manufacturers accelerate the development of new technologies and find unprecedented performance gains in established technologies. To extend this powerful capability to our users, we integrated a new ML tool into CONVERGE Studio (first available in version 4.1.0). This tool takes you through the entire optimization process, starting with setting up a design of experiments (DoE) study. You can run the DoE on your local cluster or take advantage of our cloud computing platform, CONVERGE Horizon, to run your cases in the cloud on high-performance hardware. Next, the results of the DoE are used to train an ML meta model, which the ML tool optimizes to rapidly predict the proposed optimum. The final step is to run the predicted best case in CONVERGE to confirm the results. Rapid optimization is just one use for ML in CFD—more functionalities, such as reduced order modeling and uncertainty quantification, are under active development.
CAD Editor
The ability to directly modify a CAD geometry in a CFD pre-processing software provides a valuable opportunity for CFD engineers to refine their geometry and create a high-quality surface mesh tailored for their CFD simulation. CONVERGE 5 introduces the CAD Editor, a new module in CONVERGE Studio that contains a variety of tools for manipulating and modifying CAD geometries.
When you import your geometry into the CAD Editor, regions and boundaries are automatically created based upon the CAD file. You can then rename and group the boundaries as needed for your case. The CAD Editor includes a variety of geometry transformation options, including tools for performing uniting, deleting, extracting, and extrusion operations. You can also use the tools to patch holes in the geometry and create and extrude wire bodies. Finally, you can generate a surface mesh—including adding custom meshes to certain parts of the geometry—and validate the mesh before transferring the geometry to the CONVERGE Studio Case Setup module.
Sealing
Sealing in CONVERGE mimics the physical seals in your system by dynamically eliminating gaps between boundaries. It can also be used to remove small gaps in the domain that might otherwise require a highly refined mesh and small time-steps to resolve, allowing for a more efficient simulation. The sealing capabilities in CONVERGE 5 have been significantly improved to enhance stability and performance. The enhanced stability also translates to easier case setup. Seals can now be added without worrying about the number or alignment of vertices or the relative orientation of the surfaces. In addition, a number of flags have been added to make diagnosing seal configuration errors easier.
CONVERGE 5 also introduces the ability to directly resolve intersections between surfaces. This option is more intuitive and flexible than sealing, but it can lead to unphysical results if not used properly. General intersection handling can be particularly useful for cases with FSI contact modeling, allowing the solver to tolerate intersections if they occur.
Furthermore, CONVERGE 5 includes the ability to resolve intersections between polygons in the same plane, which is beneficial for cases such as gear simulations, in which the top and bottom surfaces of a pair of gears often meet in the same plane. Version 5 also includes an option to remove tiny volumes which may be artificially created by the surface discretization errors of intersecting surfaces.
Under-Relaxation Steady Solver
CONVERGE 4 introduced a new Under-Relaxation Steady (URS) solver, which offers a number of benefits for steady-state simulations. Instead of using time marching to reach steady state, as the pseudo-transient solver does, the URS solver uses under-relaxation in place of the transient term. With this scheme, the residuals often converge much faster, significantly reducing runtime. In CONVERGE 5, the URS solver has been enhanced for improved stability and faster convergence. Depending on the case, the URS solver is anywhere from 2–20 times faster than the pseudo-transient solver.
1D Solver
Flows in long pipes or channels can be approximated as one-dimensional. CONVERGE 5 introduces a new 1D flow solver, which is useful for parametric studies and validation studies, enabling users to gain insight into the relevant physics of a simulation with a simple setup and quick runtimes. The 1D solver can also be coupled with the 3D flow solver, enabling users to implement the 1D solver in one portion of the domain and the 3D flow solver in another portion. This coupled approach enables efficient component and system-level simulations, such as modeling the pipes upstream of an engine with the 1D solver to generate boundary conditions for a 3D engine cylinder simulation or modeling cooling pipes in a battery pack with the 1D flow solver for a 3D CHT simulation.
Looking for Converge 4?
Click here for information on the models and features introduced in CONVERGE 4.
