 Commercial Analysis Validation
This article discusses how it might be proved that a particular
numerical analysis is ‘correct’. This is called
analysis validation and can take many forms. Physical testing is
the most obvious and convincing means of showing that an analysis
is accurate. This is often not viable or costeffective however.
Other options are FE analyses of similar structures that have been
validated through testing, or independent calculations.
A Formal Procedure for Validation
The SAFESA documents mentioned in the last article
(NAFEMS Documents Ref. R0039
, R0040
, R0041
) introduce new definitions and concepts for validating numerical
structural analyses. Perhaps the most important concept is
distinguishing between uncertainties in the physical description of
the structure, and errors in the definition of the model created to
represent it. The analyst team will often have full responsibility
for the latter and perhaps some of the former.
The SAFESA approach breaks down the whole analysis process into
discrete steps, each one requiring validation. This takes the
concept of validation to another level. For example, several
sources of data all demonstrating that a mesh is suitably refined
do not, on their own, represent thorough validation. Instead,
validation should include information to show that errors have been
considered for each modelling assumption, decision or step in the
analysis process.
Validation in a Commercial Environment
Detailed model validation procedures as described in the SAFESA
documents are appropriate for safety-critical structures. But in
other applications, validation is at the discretion of the analysis
team and devising a suitable validation strategy for each project
can be difficult. Many analyses that consultancies carry out are
novel, where no previous validation from similar structures is
available. Despite the important requirement for it in these cases,
it can be a challenge to carry out appropriate validation under
commercial pressures, typically experienced by consultancy teams.
Consultancies’ clients often have a perception of analysis as
being 100% accurate, a view for which they cannot be blamed. In
giving the client what they want, it can be tempting to let this
view prevail and short-cut the validation process since it provides
no obvious improvement in the appearance of the analysis for the
client. This is a risky approach however. It is the job of the
analysis team to openlydiscuss with the client (or internal
customer) the errors, uncertainties and corresponding risks
associated with the full analysis process and, if a budget can be
obtained for so doing, attempt to quantify them. Perseverance may
be required here to portray validation as a benefit rather than an
inconvenience.
A Risk Based Approach to Analysis
An open discussion of risk can help recalcitrant clients see
analysis as a powerful but not an absolute process. If the level of
risk of an event occurring can be estimated, then a cost can be
associated with it. For example, consider a newly designed moulded
part where tooling rework is estimated to cost £50,000. We
can make a rough estimate of the risk of this occurring: based on
the success rate of the design team with similar past projects,
let’s say that the risk of structural problems occurring in
the part is 30%. With a good analysis supporting the design
process, the risk of the design being structurally inadequate can
be reduced to say, 10%. (That is the analysis is likely to be valid
in 90% of cases.) The risk reduction value of the analysis is
therefore 20% of £50,000, or £10,000. This is then a
limiting cost for an analysis of this part.
(As well as discussing structural analysis, this approach could
also apply to mould flow simulation, for example.) One digression
that springs from this is considering the reasons for an analysis
being incorrect. The risk of an analysis project drawing the wrong
conclusions is different to the risk of the analysis team being at
fault. Unfortunately, good professional conduct does not eliminate
all risk. The distinction made previously between uncertainty and
error may be useful here: errors may be considered the analysis
team’s direct responsibility whereas uncertainties are more
difficult to assign.
Analysis Validation to Reduce Risk
Risk assessment can also be applied to analysis validation.
Continuing with the previous example, a physical test and further
analyses to correlate with it could be carried out to improve
confidence in the model. If this improved confidence from 90% to
95%, then the risk reduction value of the validation would be 5% of
£50,000, or £2,500. So physical testing could not be
justified if it cost more than around £2,500 in this example.
In a risk assessment context, hand calculations, sensitivity tests
and independent checking procedures, are usually cost-effective
validation steps.
A difficulty with risk assessment generally is deciding on actual
risk levels – a 5% risk reduction due to physical testing is
not easily proven. Despite this, considering the approximate risk
associated with different stages of an analysis is a useful process
for an analyst. And when used merely to communicate the concept of
analysis risk to a client, accurate figures are not required of
course.
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