InterPenet

Probabilistic evaluation of penetration of plate

Shinsuke Sakai

Emeritus Professor, The University of Tokyo, Japan
Visiting Professor, Yokohama National University, Japan

Overview

For the risk evaluation of penetration caused by flying objects onto steel plates, the assessment of penetration probability is required. For the evaluation of penetration probability of flying objects on plates, Limit State Function Method (LSFM) is applied. Representative 11 penetration formulas are included. If you want to know the details of this package, refer to the following paper.

S.Sakai and T. Kumagai,"Application of Limit State Function Method To Statistical Analysis of Ballistic Penetration", Proceedings of the 17th Hypervelocity Impatct Symbosium HVIS2024, Sept.9-13,2024,Tsukuba,Japan

Installation

You can install the package via pip:

pip install InterPenet

Operation check

The following describes the method for checking when applying to penetration analysis using BRL formula. To execute this program, you need th input file 'BRL.pkl'. The 'BRL.pkl' is given in the site.

from InterPenet import InterPenet as ip
bb=ip.Base()
bb.CalcPenet('BRL.pkl')

If the following output is obtained, it is working correctly.

Validation [['v_bl', 'satisfied'], ['Limp/d', 'satisfied'], ['b/d', 'satisfied'], ['Lsh/d', 'satisfied'], ['Su', 'not satisfied']]
*** Probabilistic analysis ***
[ BRL Formula ]
variable= ['b', 'd', 'm', 'v', 'Me']
beta= -0.5571767489022684
Alpha= [ 0.06413751  0.06413751 -0.0427838  -0.9006759   0.42275907]
Pf= 0.7112966629840962
*** Analysis of Balistic Limit Velocity ***
Vbl= 102.34312241793276
File= BRL.pkl

If you want to get the output as a dictionary, do it like this.

from InterPenet import InterPenet as ip
bb=ip.Base()
dd=bb.CalcPenet2Df('BRL.pkl')
dd

The output will be displayed as follows.

{'Formula': 'BRL Formula',
 'Validation': [['v_bl', 'satisfied'],
  ['Limp/d', 'satisfied'],
  ['b/d', 'satisfied'],
  ['Lsh/d', 'satisfied'],
  ['Su', 'not satisfied']],
 'variable': ['b', 'd', 'm', 'v', 'Me'],
 'g_value': -7.422565340273962,
 'beta': -0.5571767489022684,
 'Alpha': array([ 0.06413751,  0.06413751, -0.0427838 , -0.9006759 ,  0.42275907]),
 'Pf': np.float64(0.7112966629840962),
 'Vbl': 102.34312241793276,
 'File': 'BRL.pkl'}