Good discussion...👍

An 'acceptable' error needs to be defined in the context of your application.

Additionally, if your model accurately reproduces reality on one observable (ie. has low error with respect to the experimentally-measured parameter), it doesn't necessarily mean it reproduces reality (with low error) on other observables.

The consequence of error is also relevant; if the model is in error but is known to be conservative, this might be acceptable.

Thanks for all

Ahmed, It usually depends on the type of the problem. However, the range accepted by industry is about 5%. Keep in mind that the definition of the error and range that is accepted depends strongly on what you are trying to accomplish as well as the the actual experimental data value.

In complex scenarios, we even accept the CFD results if it mimics the trend of the data and provides a good understanding of the physics of the problem. Once again, when i review CFD or generally simulation studies, i have the 5% rule of thumb to accept the simulation results.

Many thanks Saeed for your answer

Good discussion...👍

Thanks

Thanks for your answer

It all depends on the case you are simulating and comparing it with experimental results.

(1) all the known simple as well complex systems/applications /phenomenon validation are available for comparison in earlier published work then the Journal/reviewer/academic community expects similar kind of matching results within 5% or even lesser deviations

(2) If you are trying for less explored concept through simulation or the case with many assumptions for simplifications, then larger deviation to some extent are also acceptable to Journal/reviewer/academic community

(3) Even for the same case, use of 2d or 3d may deviate your results

(4) One needs to look out assumptions made in CFD and actual experimental boundary conditions

(5) To my personal experience, deviations occur mainly from bad mesh and model physics and initial/boundary conditions

Many thanks Ravindra

The experimental measurements’ accuracy originated from two major sources: human error and equipment error. The equipment error (systematic error) is measurable, and its sources can be found. However, it is very difficult to find the source of human error, which is also known as random error. To prevent human error in the experiments, the measurements were repeated and their average was considered the final amount. Also, the numerical model owns some systematic errors.

Thanks Hamed

eDeAs per the industry standards, anywhere between 3 to 5% is acceptable. In some cases depending on the complexity of the problem and the models used up to 5 to 10% is also acceptable.

But you have to consider the accuracy of the experimental results, source of the data, and the technique used to measure the data. Because in some cases your CFD may give accurate results when compared to the experimental uncertainties (human and instrument error).