UpFront Engineering Simulation
8020 Engineering Ltd
Aston Court, Kingsmead Business Park Frederick Place, High Wycombe, HP11 1LA United
Kingdom
‘The 80:20 Criteria for the SUCCESSFUL Implementation of CFD/CAE within the Design
Process…’
… 8020 Engineering Limited Download PDF
Version
The Pareto Principle or 80:20 rule states that for many events eighty per cent of
the effects come from twenty percent of the causes. For example, in economics the
richest twenty percent of the population earns eighty percent of the overall income.
In the product development world eighty per cent of the product performance or project
success is often dictated within the first twenty per cent of the development life-cycle.
However, to what extent can this also applied to the Computer Aided Engineering
(CAE) world? Is eighty per cent of the business value delivered associated with
only twenty per cent of the resources deployed, or time spent using simulation technology?
If this is the case, perhaps it is time for engineering companies to consider what
are the obstacles preventing successful implementation of CAE tools within their
design process? From our experience, when a product development group is looking
to realize the benefits of computational simulation, there are seven areas of the
implementation that need detailed assessment. We refer to these as the ’80:20 Criteria
for SUCCESS’: -
- Suitability of CAD models. Current marketing surrounding the integration of CAE
within CAD/PLM systems tends to encourage companies to assume they can take any production
CAD model and instantly run a computational simulation (CFD or FEA). However, even
when this is possible, it is not necessarily a very efficient way of running a CFD/FEA
model. The computational mesh automatically produced can be over dense in areas that
are of little significance to the physics with the consequence that the solutions
take too long to run without any gain in accuracy. One solution to this is to de-feature
the CAD model, however, this can often require many hours of work and may require
the simulation engineer to learn the full complexities of the company CAD system.
In some cases it may be simpler to start again from scratch with a concept version
of the geometry, in the company CAD system or elsewhere.
- Development Process Change. In some companies the design resources available to
use the simulation technology may prefer ‘more traditional build and test’ development
methods, and therefore may lack a real desire to make optimum use of the computational
simulation facility. The concept of simulation driven design is that CFD/FEA models
are run frequently during the early stages of the design process so that any potential
issues are resolved before the design is too costly to change. This is more effective
if users believe in these process benefits and the specific technology available
to them and feel simulation is part of their process rather than just some final
verification step. On the other side to this management themselves may not allocate
enough ‘upfront’ time or resources within specific project plans so more ‘Traditional’
processes and project metric systems are maintained.
- Operating Environments and Material Properties. Knowing how to represent reality
within a computer simulation should not be underestimated. Unless the definition
of the boundary conditions match the real life situation then there is a risk that
results obtained won’t be useful. Equally material properties need to be known or,
if not, then adequate assumptions made so as not to affect the validity of the predicted
results. Electronics enclosures for example are very sensitive to material property
conduction paths. Flows through valves can be very sensitive to the pressure conditions
applied. For example an incorrect operating condition can cause choke or cavitation
to be predicted making the results not valid.
- Experimental Test and Verification. Confidence in simulation results is often required
before CFD/FEA is really accepted as part of the design process. Verification of
a CFD tool is often performed by comparison of test data with the simulation results.
However, if they don’t match the CFD tool is often blamed and the whole concept of
using simulation thrown out. In these situations it’s important to make sure that
the test data is challenged in terms of calibration, sampling method, apparatus used
and validity of comparison between what has been tested and the simulation model
before drawing any conclusions.
- Appropriate Computer Resources. The computer resources required for a given application
may be prohibitively expensive to purchase and maintain with respect to the Return
on Investment (ROI) that will be realised. For example if every design iteration
for a pump model requires a full transient CFD simulation at enough points to define
the operating curve, something more than a standard CAD workstation computer is needed.
You may need a modern High Performance (HPC) cluster in order to turn round one
design iteration in anything significantly less than a week. Or if a given model
requires a very large computational mesh (e.g. 2-3 million+ cells) to provide meaningful
results, such as a Wind Turbine, then again a standard workstation may not be up
to the task.
- The Phenomena of Fluid Dynamics. Some application’s physics may have some unusual
Fluid Dynamics phenomena occurring. Design focused CFD tools are developed to make
life easy for the majority of users who are running the most common types of applications
(The 80:20 rule applies here as well – twenty per cent of the what is possible with
CFD tends to cover eighty per cent of the potential flow and thermal design applications).
However, this can mean that when there is something unusual about the physics of
the application, even though it may look like it is within a design focused CFD tool
capability, the user may find it difficult to get relevant results from the models
or is required to delve deep into the background of the software to find a technique
that does produce reasonable results. An example of this is an external aerodynamic
model where the user needs to closely control the mesh around the working surfaces
and may also need to change many of the default settings on the turbulence model.
- CFD and Complex Physics. Some Fluid Flow applications can be so complex that only
high end CFD tools, developed for the full-time analyst or educational establishments,
are appropriate. These applications, such as flows with chemical reactions/combustion,
multi-phase fluids or free surface flows, are normally way beyond the capabilities
of design focused CFD tools. This may be because they do not fit within the 80:20
principle mentioned within Criteria 6 above and therefore the software vendor has
decided that they are not economical to develop. Other complex physics capabilities
may be left out because they require the knowledge of an engineer who has a PhD in
numerical methods just to understand the required input (and/or output). This can
mean that some companies are left to justify recruiting the services of a CFD expert,
with the cost of the appropriate high end tool, to address that particular application.
CONCLUSIONS
With all these potential obstacles in the path of a successful implementation of
a design focused CFD/CAE strategy, is it still worth the investment of time and money?
Our opinion is “YES, ABSOLUTELY” because once the technology is SUCCESSFULLY implemented
significant prototype cost savings and quality improvements become a standard part
of the design process. The important point is to recognise what potential implementation
barriers exist early-on and make sure there are plans in place to overcome the issues
as they occur.
Of the seven criteria mentioned above the first four are best addressed through planned
training and adequate education. Both formal training courses and one to one mentoring
with experienced engineers are recommended. By ‘experienced engineers’ we mean those
who have seen many other companies go through a SUCCESSFUL design based implementation
process many times before. Only these engineers will have the knowledge to understand
what is happening when simulation results do not exactly match experimental data.
If computer resources are identified as a potential issue then partnering with an
organization which can provide access to fast high performance computing clusters
is an answer, to overcome bottlenecks or to assess how essential better computer
resources are on a permanent basis.
Unusual Fluid Dynamics or Complex Physics are best addressed by also partnering with
an organization that is able to offer design focused solutions whilst providing access
to advanced high-end consultancy services. Many companies find this very economical,
particularly if their unusual or more difficult applications are only a small part
of the potential benefit CFD will bring to their design, research and development
efforts.