Simulation-based Validation
Simulation-based Validation - Related Videos
01:29
Reliability and Validity
0 Views •
2020
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways. Unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. To illustrate this concept, consider a kitchen...
11:05
Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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Cited by 10 •
2016
The following paper presents a novel FE simulation technique (KBC-FE), which reduces computational cost by performing simulations on a cloud computing environment, through the application of individual modules. Moreover, it establishes a seamless collaborative network between world leading scientists, enabling the integration of cutting edge knowledge modules into FE simulations.
09:46
MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
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Cited by 48 •
2012
An efficient way to gain insight into how humans navigate themselves in three dimensions is described. The method takes advantage of a motion simulator capable of moving observers in ways unattainable by traditional simulators. Results confirm that movement in the horizontal plane is underestimated, while vertical movement is overestimated.
08:45
Study of Siphon Breaker Experiment and Simulation for a Research Reactor
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Cited by 2 •
2017
The siphon breaking phenomenon was investigated experimentally and a theoretical model was proposed. A simulation program based on the theoretical model was developed and the results of the simulation program were compared with experimental results. It was concluded that the results of the simulation program matched the experimental results well.
10:52
Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
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Cited by 13 •
2016
A protocol is presented for the characterization of the in-field pedestrian behavior and the simulation of the resulting structural response. Field-tests demonstrate that the in situ identified pacing rate and synchronization rate among the participants constitute an essential input for the simulation and verification of the human-induced loads.
FAQs
Validation becomes meaningful when the simulated response is compared with a defined reference, such as an engineering requirement, an experimental result, or observed real-world performance. Agreement supports confidence in the design or model, while disagreement identifies behavior that needs investigation. This comparison also makes the assessment traceable to a specific expected outcome.
Accurate assumptions, calibration, and independent verification provide complementary safeguards. Assumptions affect how operating conditions and system behavior are represented; calibration helps align the model with available evidence; and independent verification strengthens confidence that the computational implementation has been checked separately. Together, they reduce the risk of treating an unexamined model result as dependable engineering evidence.
Controlled inputs and selected operating conditions determine what the model actually tests. Engineers can examine behavior across operating ranges rather than relying on one scenario, then inspect outputs such as stress, temperature, motion, reliability, or overall system response. Choosing outputs that match the requirement helps reveal whether a design performs acceptably under the conditions being assessed.
A practical workflow starts by identifying the requirement or expected behavior, then using a computational model to reproduce the relevant operating conditions and apply controlled inputs. Engineers evaluate the resulting outputs, compare them with the chosen reference, and investigate discrepancies. Repeating this process across operating ranges can expose design flaws before physical deployment or prototype construction.
Simulation-based validation is especially useful early in development, when engineers need to test alternatives before committing to physical deployment or extensive prototype work. It can reveal potential flaws, evaluate performance over multiple operating ranges, and reduce development time and cost. The approach is therefore valuable when early computational assessment can guide later design and testing decisions.
In engineering, the results can support decisions about whether a design meets safety, performance, and regulatory requirements. The method can also organize evidence around measurable behaviors, including stress, temperature, motion, reliability, and system response. Its value depends on the credibility of the assumptions, calibration, and independent verification accompanying those results.