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We have developed a new methodology for forward analysis of retrogressive hydration (rehydration) reactions by an improved thermodynamic forward modeling technique based on a differential thermodynamic approach (Gibbs' method).
In order to alleviate this problem, this paper proposed HMEM as a new acoustic modeling technique based on maximum entropy modeling approach.
We present here a stochastic modeling technique, based on a 3D coupled flow and transport groundwater model, to assess the risk of salinization in a multi-layered coastal aquifer, under model parameter uncertainty.
We use a modeling technique based on influence diagrams able to integrate different uncertainty levels (on dependencies) in a unique model.
The modeling technique, based on the averaging method, is illustrated in thermal design and optimization of a microstructure.
The technique applied here uses a Geographic Information System GISS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem.
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We also present new streamline modeling techniques based on the new tangent vector blending techniques.
Fundamental research is undertaken by using virtual prototyping modeling techniques based on the finite element method.
Theoretical investigation is accomplished by using virtual prototyping modeling techniques based on the finite element method.
Existing techniques can be classified as statistical, physical and time series modeling techniques based on the forecasting models they used [1].
To deduce a 2-D flow map by merging and spatially interpolating LOSV values, several modeling techniques based on the LOSV observation were developed in past studies.
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