Automation of Engineering Design Aids using Neural Networks Siripong Malasri and Jittapong Malasri...

Automation of Engineering Design Aids using Neural Networks

Siripong Malasri and Jittapong Malasri

Christian Brothers University

Kriangsiri MalasriGeorgia Tech

MAESC ’05 – May 13, 2005

Presentation Overview

• Introduction• Artificial Neural Networks• The Stress Concentration Problem• Software Development

Data preparation Network training and validation Standalone application development

• Conclusions and Future Work

Introduction

• Traditional design aids Look-up tables Graphical plots

• Shortcomings Inaccurate interpolation/extrapolation Difficult to smoothly integrate with

computer applications

Neural Networks• Have been used to recognize patterns

and project trends in data• Backpropagation model – can be trained

to generate desired input-output relationships

Stress Concentration (1)

• Objective Calculate the peak stress in a notched beam

cross-section subject to a bending moment

• Possible approaches Finite-element analysis Experimental procedures Determine a stress concentration factor

from a design aid

Stress Concentration (2)

• Stress concentration factor, C Function of the ratios a/h2 and h1/h2

• Peak stress at notch: M = bending moment applied I = cross-sectional moment of inertia c = distance from N.A.

I

McC

Software – Data Preparation• Training data obtained from a published

graphical design aid

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

0.00 0.05 0.10 0.15 0.20 0.25 0.30

a / h2

C

h1 / h2 = 2

h1 / h2 = 1.5

h1 / h2 = 1.1

• Inputs: a/h2 , h1/h2• Output: C• 46 training pairs,

15 calibration pairs, 15 validation pairs

Software – Network Training

• NeuroShell 2 software• Backpropagation network with 2 input neurons,

8 hidden neurons, and 1 output neuron• Excellent results from trained network

Software – Standalone Program

• Interface developed in Visual Basic

• Network code generated from NeuroShell 2

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

0.00 0.05 0.10 0.15 0.20 0.25 0.30

a / h2

C

h1 / h2 = 2

h1 / h2 = 1.5

h1 / h2 = 1.1

Conclusions and Future Work

• Excellent network estimates of the stress concentration factor for this particular application

• Standalone executable is portable to any Windows computer

• Future work: comprehensive stress analysis program with a variety of cross-sections