ASME V&V 10 pdf free download

ASME V&V 10-2019 pdf free download.Standard for Verification and Validation in Computational Solid Mechanics.
Program managers need assurance that computational models of engineered systems are sufficiently accurate to support programmatic decisions. This Standard provides the technical community — engineers, scientists, and program managers — with guidelines for assessing the credibility of computational solid mechanics (CSM) models.
Verification and validation (V&V) are the processes by which evidence is gathered to determine the accuracy of the computer model for specified conditions. These accuracy results, along with uncertainty quantification (tJQJ, contribute to the determination of the credibility of the model for the conditions of its intended use.
Professional organizations differ En their definitions of V&V. The American Society of Mechanical Engineers (ASME) V&V 10 Subcommittee on Verification and Validation in Computational Solid Mechanics has chosen definitions consistent with those published by the Department of Defense (DoD) (ref. (1J) and by the American Institute of Aeronautics and Astronautics (AIAA) (ref. [21). Verification assesses the numerical accuracy of a computational model regardless of the physics being modeled. Both code verification (addressing errors in the software and numerical algorithms) and calculation verification (estimating the numerical errors due to under-resolved discrete representations of the mathematical model) are addressed. Validation assesses the degree to which the computational model is an accurate representation of the physics being modeled. It Is based on comparisons between numerical simulations and relevant experimental results. Validation is essential in assessing the predictive capability of the model in the physical realm of interest, and it must address uncertainties that arise from both experimental and computational procedures.
As shown In Figure 2.3-1. the general V&V process begins with a statement of the intended use of the model and pertinent information about the system being modeled so that the relevant physics are included in both the model and the experiments performed to validate the model. Modelingand experimental activities are guided by the response quantities of interest and the accuracy requirements for the intended use. Experimental outputs intended for validation for component-level to system-level tests should, whenever possible, be provided to modelers only after verification and the numerical simulations for those outputs have been performed.
Ideally, the V&V process for a particular application ends with acceptable agreement between model predictions and experimental outputs, after the uncertainties in both have been taken into account. If the agreement between model and experiment is not acceptable, an assessment should be performed to determine why agreement was not met and, potentially, the processes of V&V repeated by updating the model and performing additional experiments. Successful completion of the validation process, demonstrated by satisfactory agreement between simulation and experiment, means that the model adequately reproduces the experimental measurements that have been obtained.
Once the validation process is successfully completed, the model should be assessed to determine if its predictive capability, including relevant uncertainties, is adequate for conditions where no experimental data arc available. Since most models are developed for use where experimental data are not available, predictive capability must address a much wider range of uncertainties than validation. This Standard introduces the concept of predictive capability but does not go into detail because of the early stage of development of this field.
Finally, it is important to document all V&V activities. In addition to preserving the compiled evidence ol V&V, documentation records the justifications for important decisions such as selecting primary response quantities and setting accuracy requirements. Documentation thereby supports the primary objective of V&V: to build confidence in the predictive capability of computational models.
The guidance provided herein will enable managers and practitioners of V&V to better assess and enhance the credibility oICSM models. Upon reading about the process described in this Standard and illustrated in ASM E V&V 10.1-2012, engineers may be left with the sense that the real-world constraints of the engineering environment (i.e., schedule and budget) do not allow for sufficient project scope to complete the V&V process to a satisfactory level of rigor. Users of this Standard are nonetheless encouraged to provide a V&V foundation for their engineering calculations and Identify any associated uncertainties and risks.ASME V&V 10 pdf download.