Sentence examples for models when used from inspiring English sources

These findings give insight into the scalability of discrete element models when used for the simulation of concrete material.

This finding may account for the shortcomings of random-walk (scale-finite) models when used to predict large-scale movement and search patterns by extrapolating from observations made at small scales.

Despite being computationally efficient, the semi-empirical and empirical models, when used under conditions that lie outside the calibration data set, exhibit up to 71% error in capacity loss prediction.

The developed statistical models, when used in conjunction with existing thermodynamic information, make it possible to estimate the chemical composition of the matrix and the types of, and semi-quantitatively the amounts of, boraides, carbides and boro-carbide precipitates.

Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context.

The case studies demonstrate the importance of adjusting for weather and production between the pre- and post-retrofit periods, how plant-wide savings can be disaggregated to evaluate the effectiveness of individual retrofits, how the method can identify the time-dependence of savings, and limitations of engineering models when used to estimate future savings.

The obtained results indicated that the mutation score has been significantly improved for all models when using the novel fitness function.

It may take days or weeks to obtain the final maps and to visually evaluate the prediction models when using a desktop workstation.

Following on from our previous work in Part I, this part II paper introduces three new permeability models when using aqueous solutions as feed.

While improving the correspondence of the models when using the "coarse-grain" statistic, the additional information does not lead to quite as substantial an overall agreement between the models when the "fine-grain" statistics are compared.

As can be observed in the Table, the M5P algorithm generating a regression tree produced the best model when using the first type of descriptor set, whilst Bagging produced the best models when using the other two types of descriptor sets.