# Shock Response Spectrum

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The following tutorial gives further information: [http://www.vibrationdata.com/tutorials2/srs_intr.pdf srs_intr.pdf] | The following tutorial gives further information: [http://www.vibrationdata.com/tutorials2/srs_intr.pdf srs_intr.pdf] | ||

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'''Utility''' | '''Utility''' |

## Revision as of 16:00, 23 July 2011

**Introduction**

Mechanical shock pulses are often analyzed in terms of shock response spectra (SRS). The shock response spectrum assumes that the shock pulse is applied as a common base input to an array of independent single-degree-of-freedom systems. The shock response spectrum gives the peak response of each system with respect to the natural frequency. Damping is typically fixed at a constant value, such as 5%, which is equivalent to an amplification factor of Q=10.

The following tutorial gives further information: srs_intr.pdf

**Utility**

The scripts on this page require the utility module tompy.py

**Arbitrary Base Input**

The SRS for an an arbitrary base input can be calculated via a digital recursive filtering relationship, which models the convolution integral.

The filtering relationship can be implemented in Python by importing the lfilter function from scipy.

*from scipy.signal import lfilter*

A script for doing this is given at: srs.py

A version for calculating and plotting the SRS in tripartite format is given at: srs_tripartite.py

**Half-sine Pulse**

The response of an SDOF system to a half-sine base input can be calculated via a Laplace transform which yields a closed-form solution, as shown in sbase.pdf

A script is given at: half_sine_base.py

Note that the peak response may occur either during or after the half-sine pulse depending on the pulse duration, natural frequency, and damping ratio.

**Terminal Sawtooth Pulse**

The response of an SDOF system to a terminal sawtooth base input can also be calculated via a Laplace transform. terminal_sawtooth.pdf

A script is given at: terminal_sawtooth_base.py

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