Application of a validation strategy to Darcy's experiment

Davis, Paul A.; Olague, N.E.; Goodrich, Michael T.

doi:10.1016/0309-1708(92)90022-t

Cited by 24 publications

(14 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several researchers [1][2][3][4][5] had verified that Darcy's law is valid only for low flow rates where pressure drop is linearly proportional to the flow rate. When velocity increases, the influence of inertia and turbulence becomes more significant and the pressure drop displays a parabolic trend with velocity.…”

Section: Introductionmentioning

confidence: 99%

The effect of microstructure on the permeability of metallic foams

Medraj

Baril²,

Loya

et al. 2007

J Mater Sci

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

The effect of microstructure on the permeability of metallic foams

Medraj

Baril²,

Loya

et al. 2007

J Mater Sci

View full text Add to dashboard Cite

“…If γ increases as a function of the lag distance, then the model is unacceptable, as there are systematic errors in the predictions. In support of this semivariogram analysis, Davis et al (1992) state .".. the semivariogram analysis, while not flawless, has proved to be the most robust in terms of finding false models as invalid and true models as not invalid.…”

Section: E3 Analysis Of the Spatial Structure Of Residualsmentioning

confidence: 68%

“…Davis and Goodrich (1990) and Davis et al (1992) propose that a model is invalid if the measurement residuals are correlated. Their criteria of acceptance are based on the change in the variance of the residuals as a function of the spatial lag or separation distance between measurement points.…”

Section: E3 Analysis Of the Spatial Structure Of Residualsmentioning

confidence: 99%

A Validation Process for the Groundwater Flow and Transport Model of the Faultless Nuclear Test at Central Nevada Test Area

Hassan¹

2003

View full text Add to dashboard Cite

EXECUTIVE SUMMARYMany sites of groundwater contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This has created a need for tools and approaches that can be used to build confidence in model predictions and make it apparent to regulators, policy makers, and the public that these models are sufficient for decision making. This confidence building is a long-term iterative process and it is this process that should be termed "model validation." Model validation is a process not an end result. That is, the process of model validation cannot always assure acceptable prediction or quality of the model. Rather, it provides safeguard against faulty models or inadequately developed and tested models. Therefore, development of a systematic approach for evaluating and validating subsurface predictive models and guiding field activities for data collection and long-term monitoring is strongly needed. This report presents a review of model validation studies that pertain to groundwater flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general in nature, but the focus of the discussion is on site-specific, predictive groundwater models that are used for making decisions regarding remediation activities and site closure. An attempt is made to compile most of the published studies on groundwater model validation and assemble what has been proposed or used for validating subsurface models. The aim is to provide a reasonable starting point to aid the development of the validation plan for the groundwater flow and transport model of the Faultless nuclear test conducted at the Central Nevada Test Area (CNTA).The review of previous studies on model validation shows that there does not exist a set of specific procedures and tests that can be easily adapted and applied to determine the validity of site-specific groundwater models. This is true for both deterministic and stochastic models, with the latter posing a more difficult and challenging problem when it comes to validation. This report then proposes a general validation approach for the CNTA model, which addresses some of the important issues recognized in previous validation studies, conferences, and symposia as crucial to the process. The proposed approach links model building, model calibration, model predictions, data collection, model evaluations, and model validation in an iterative loop. The approach focuses on use of collected validation data to reduce model uncertainty and narrow the range of possible outcomes of stochastic numerical models. It accounts for the stochastic nature of the numerical CNTA model, which used Monte Carlo simulation approach. The proposed methodology relies on the premise that absolute validity is not even a theoretical possibility and is not a regulatory requirement. Rather, it highlights the importance of testing as many aspect...

show abstract

“…Bastiaanssen et al, 1994;Moran et aI., 1994;Goodrich et al, 1994). In this sense, the development of such conceptualisations is dependent on inference from data rather than theory (noting that this is also true for the theory we have available now except that the inferences were made at small scales (and long ago) and even then are only approximations to the data, see Davis et al, 1992, for a discussion of Darcy's law in this context).…”

Section: The Future Of Distributed Modelling: On the Value Of Datamentioning

confidence: 95%