Name
Abstract | ||
|---|---|---|
The construction of structures subjected to impact was traditionally carried out empirically, relying on real impact tests.
The need for design tools to simulate this process triggered the development in recent years of a large number of models of
different types. Taking into account the difficulties of these methods, poor precision and high computational cost, a neural
network for the classification of the result of impacts on steel armours was designed. Furthermore, the numerical simulation
method was used to obtain a set of input patterns to probe the capacity of themodel development. In the problem tackled with,
the available data for the network designed include, the geometrical parameters of the solids involved — radius and length
of the projectile, thickness of the steel armour — and the impact velocity, while the response of the system is the prediction
about the plate perforation.
|
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-90-481-2311-7_32 | World Congress on Engineering (Selected Papers) |
Keywords | Field | DocType |
impacts classificationmultilayer perceptronoptimizationneural networksimulation,multilayer perceptron | Multilayer perceptron,Artificial intelligence,Engineering,Artificial neural network,Machine learning | Conference |
Citations | PageRank | References |
3 | 0.38 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ángel García-crespo | 1 | 553 | 38.57 |
| Belén Ruíz-mezcua | 2 | 66 | 9.88 |
| Israel Gonzàles-carrasco | 3 | 7 | 1.50 |
| José Luis López Cuadrado | 4 | 24 | 4.20 |