Many different numeric models have been created to address a variety of hydraulic and hydrologic engineering applications. Each utilizes formulations and numeric methods to represent processes such as contaminant transport, coastal circulation, and watershed runoff. Although one process may be adequately represented by a model, this does not guarantee that another process will be represented even if that process is similar. For example, a model that computes subcritical flow does not necessarily compute supercritical flow. Selecting an appropriate numeric model for a situation is a prerequisite to obtaining accurate results. Current policies and resources do not provide adequate guidance in the model selection process. Available resources range from approved lists to guidelines for performing calculations to technical documentation of candidate numeric models. Many of these resources are available only from the developers of the numeric models. They focus on strengths with little or no mention of weaknesses or limitations. For this reason, engineers must make a selection based on publicity and/or familiarity rather than capability, often resulting in inappropriate application, frustration, and/or incorrect results. A comprehensive selection tool to aid engineers needs to test model capabilities by comparing model output with analytical solutions, laboratory tests, and physical case studies. The first step in building such a tool involves gathering and categorizing robust data the can be used for such model comparisons. A repository has been designed for this purpose, created, and made available to the engineering community. This repository can be found at http://verification.aquaveo.com. This allows engineers and regulators to store studies with assigned characteristics, as well as search and access studies based on a desired set of characteristics. Studies with characteristics similar to a desired project can help identify appropriate numeric models.
College and Department
Ira A. Fulton College of Engineering and Technology; Civil and Environmental Engineering
BYU ScholarsArchive Citation
Hollingsworth, Jason Michael, "Foundational Data Repository for Numeric Engine Validation" (2008). Theses and Dissertations. 1560.
numeric model, numeric engine, verification, validation, data repository, selection