Computational Fluid Analysis
Computational Fluid Analysis which is done during CFD consulting in our Singapore office at BroadTech Engineering involves replacing Partial differential equations (PDE) systems with a set of Algebraic equations which is solvable mathematically using computer CFD simulation software.
These Partial differential equations (PDE) are governing mathematical equations which represent physics laws for conservation of Mass, Momentum, and Energy.
Computational Fluid Dynamics (CFD)
Computational Fluid Dynamics (CFD) is a highly interdisciplinary area of engineering which lies at the intersection of Physics, Applied mathematics, and Computer science.
It allows CFD companies to provide a Qualitative (and sometimes Quantitative) simulation of fluid flow patterns.
Th enables Simulation Engineers, Green building consultants, ESD consultant and Scientists to execute Fluid dynamic analysis using ‘numerical experiments’ (i.e. computer simulations) in a ‘virtual flow environment’ to accurately predict engineering design performance, Optimize and Improve Design performance, and Validate product Fluid Dynamic behavior as early as possible in the engineering development process.
Featured Computational Fluid Analysis Case Studies
Automating Transmission CFD results and Linking them to a 1-D Hydraulic System Model
CFD Analysis to Reduce the Side-loads on Spool Valves.
Advantages of Computational Fluid Dynamics (CFD)
Our CFD consulting services (IL: CFD consulting services) at BroadTech Engineering gives an engineering insight into fluid flow pattern behaviors that are difficult, costly or impossible to recreate and analyze using conventional testing methods.
CFD simulation software offers many advantages such as
1. Cheaper Cost
Lower cost of testing and validation of new engineering designs by eliminating the need for expensive physical destructive testing of prototypes.
It also removes the need for the use of actual physical Test Equipment which is logistically difficult and costly to transport.
This allows for a larger number of test simulation studies to be conducted and provides a larger quantity of data points and time instants
The Flexibility option to offer an easy & fast modification of test parameters makes it possible to save prototype testing time by having the capability to conduct a parallel, Multiple-purposed model design validation testing on virtually any test configuration.
This is in contrast to Conventional single-purposed Physical testing which is usually Slow, Sequential.
3. Comprehensive & Realistic Test Input Parameters
Can Simulate for All Operating Environmental Conditions
Computational Fluid Analysis carried out by a CFD software offers an Accurate Quantitative prediction of fluid flow behavior which takes into account all the required input parameters.
Accurate Mathematical model
Simulation in a virtual time and space environment allows the creation of a Mathematical model which is High resolution and Full Scale (instead of Scale-down models in physical testing)
We Help Our Clients Gain Valuable Insights to Optimize and Improve Product Performance, Reliability, and Efficiency.
1. Powerful ANSYS FEA Simulation Software Tools
2. FEA Consultants with Extensive Research & Professional Experience
3. FEA projects Completed in a Timely and Cost-effective Manner
4. Proven Track Record
6. Full Knowledge Transfer
Call Us for a Free Consultation
Discover what Computational Fluid Analysis can do for your company today by calling us today at +6581822236 for a no obligation discussion of your needs.
If you have any queries our knowledgeable and friendly consultants will be glad to Assist and understand more about your simulation needs and requirements
Alternatively, for quote request, simply email us your technical specifications & requirements to firstname.lastname@example.org
What is Fluid Flow
Fluid flows can be classified into either the following flow conditions/types
Fluid Flow is happening all around us
It is a physical phenomenon that we encountered in the natural environment in our everyday life.
Applications of Computational Fluid Dynamics (CFD)
Numerical simulations of fluid flow (will) enable
• Designers and engineers of vehicles to improve the Aerodynamic performance characteristics
Computational Fluid Dynamics (CFD) Process
CFD is performed out by means of using the following methods
1. Mathematical Model
Mathematical modeling of fluid analysis problem to be resolved expressed based on Partial differential equations (PDE) eg. IBVP = PDE + IC + BC
2. Discretization Process
The Discretization process involves having the PDE system mathematically converted into a set of algebraic equations. Numerical analysis techniques using discretization includes
1. Mesh Generation
This involves breaking down of the model into Nodes elements and Time instants.
The Cell elements can be either Structured or unstructured, Triangular or Quadrilateral.
• Adaptive refinement of Mesh element size in Flow regions of interest
• CAD tools + grid generators (Delaunay, advancing front)
2. Space Discretization
This is the approximation of spatial derivatives using coupled ODE/DAE systems
3. Time Discretization
Time discretization is the approximation of temporal derivatives base on Algebraic system Ax = b
3. Iterative Solution Solving Approach/Strategy
The coupled nonlinear algebraic equations must be solved iteratively
• Outer iterations
The coefficients of the discrete problem are updated using the solution values from the previous iteration so as to
• Inner iterations
The resulting sequence of linear subproblems is typically solved by an iterative method (conjugate gradients, multigrid) because direct solvers (Gaussian elimination) are prohibitively expensive
• Convergence criteria
It is necessary to check the residuals, relative solution changes and other indicators to make sure that the iterations converge.
As a rule, the algebraic systems to be solved are very large (millions of unknowns) but sparse, i.e., most of the matrix coefficients are equal to zero.
4. CFD Simulation Software
Involves implementation of CFD Computer Fluid dynamics simulation (IL: Fluid dynamics simulation) software code tools (Iterative solvers, Discrete function values, Pre- and postprocessing utilities) and Computer hardware to solve mathematical formulations
The computation time taken for a CFD flow simulation depend on
5. Post-processing Visualization, Analysis of data
The human (simulation analyst) component input involved in this CFD simulation analysis involves defining the problems & inspection.
Post-processing of the CFD simulation results involves interpretation of the computed flow field to extract the desired data. This calls for experience and good judgment.
This involves the calculation of Derived quantities (such as Streamfunction, vorticity) and Integral parameters (lift, drag, total mass)
Visualization involves representation of numeric data as visual images
Through the use of Statistical tools, the simulation data is Systematically Analyzed to Validate the CFD mathematical model
Here you can create the content that will be used within the module.
Limitations of Computational Fluid Analysis Testing Methods
As a practice, CFD does not completely replace the actual measurements completely but the amount of experimentation and the overall cost can be significantly reduced.
The results of a CFD simulation are never meant to be a 100% representation as
1. Approximate Discretization Process
The data of the input parameter may contain/involve a certain degree of approximation or imprecision due to the discretization process. This can result in possible Errors due to Modeling, Discretization, Flow disturbances caused by probes.
2. Limitations of mathematical modeling
The mathematical model of the analysis problem at hand may be insufficient.
The underlying assumptions mathematical model can also affect the quality of the simulation results
3. Constraints of Computer Processing Power
Accuracy and Speed of the simulation results is constrained by the pre-existing computing power available