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It is a numerical procedure that replaces a continuous problem by an equivalent discrete one.
The objective of this study is to present a numerical procedure that evaluates compressive strength and carbonation depth of high volume slag concrete.
So, it is immensely important to develop a numerical procedure that would appropriately treat general fuzzy linear systems and solve them.
Currently, we propose a numerical procedure that considers the changes in the luminance of sky elements to predict the interior daylight illuminance under the 15 CIE standard skies.
It is a numerical procedure that can be applied to obtain solutions to a variety of problems in engineering including steady, transient, linear, or nonlinear problems.
Obtained data were used as input parameters of a numerical procedure, that is able to estimate the effective stress intensity factor the sample actually experiences.
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The main purpose of this paper concerns the applicability of a particular numerical procedure that is an alternative to the finite element method (F.E.M).
The proposed method is based on a refined numerical procedure that combines advanced modelling of the steel rebar and computation of relationships between observed/monitored crack patterns and uncertainties affecting relevant structural parameters.
Artificial neural network (ANN) is an intelligent numerical procedure that includes three main steps.
We present a model and a simple-to-implement numerical procedure that obtains the normal detonation shock velocity (Dn)–curvature relationships for an explosive material with nonideal equation of state and an arbitrary reaction rate law.
The computations are based on an iterative, finite-volume numerical procedure that incorporates a single-domain enthalpy formulation for simulation of the phase change phenomenon.
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