Giter Site home page Giter Site logo

droptest's Introduction

droptest

GitHub CRAN

An R package for simulating LOX drop testing.

Introduction:

Generates simulated data representing the LOX drop testing process (also known as impact testing). Drop testing is expensive, time consuming, and notoriously difficult to analyze. A simulated process allows for accelerated study of test behavior. Functions are provided to simulate trials, test series, and groups of test series. Functions for creating plots specific to this process are also included. Test attributes and criteria can be set arbitrarily.

Installation:

To get the current released version from CRAN:

install.packages("droptest")

To get the current development version from github:

# install.packages("devtools")
devtools::install_github("chadr/droptest")

Background information:

Drop testing -- sometimes called impact testing -- is used to evaluate if a material will interact with liquid oxygen (LOX). The material is exposed to the LOX and an impactor is dropped onto the sample. Each drop is a bernoulli trial where a reaction is a failure and a non-reaction is a success. The specified number of trials -- until failure -- completes one test.

While fundamentally a binomial process, drop testing -- performed by the military and NASA -- yields results that are difficult to analyze. Numerous tech briefs and standards have attempted to address the problem (see below for more information). Testing stops immediately once the failure condition is reached. If the failure condition occurs on drop one or two -- depending on the failure criteria -- then the test returns only one or two result values. Alternatively, if a material passes, or if the failure condition occurs on the last trial, then the test returns as many result values as trials.

Simulation can be used to examine the behavior of this test procedure.

Inspired by NASA Technical Note "Computer Simulation of Threshold Sensitivity Determinations" (NASA-TN-D-7663). Gayle (1974). https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19750004618.pdf

Definitions:

  • Trial: A simulated bernoulli trial that represents one drop of the impactor onto a material sample. Hence a trial is also referred to as a drop. Where q is the probability of failure. A reaction is recorded as a failure. Where p is the probability of success. A non-reaction is recorded as a success. Where p = 1 - q. See https://en.wikipedia.org/wiki/Bernoulli_trial

  • Drop Test: A collection of simulated trials (drops) generated with equal parameters (q, number of trials, failure criteria, etc). When the failure criteria is reached the test is immediately terminated and no more trials are completed. The sooner a test reaches the failure criteria the less total trials for that particular test. A test with no failures will always contain the maximum number of trials as defined in the function parameters.

  • Test Series: A collection of simulated drop tests. A group number can be attached to the drop tests in a test series (optional).

  • Groups: A collection of multiple simulated test series. Each batch of test series are identified with a group number. Within each group test parameters will be identical.

  • Trial Deviation: The average distance from q for the total percent of reactions (failures).

Applicable Standards:

Pass/Fail criteria and number of observations required have been defined in the following standards:

Note: This package is not constrained by any standard. Arbitrary test criteria and observations can be specified for maximum flexibility.

For more information on drop testing:

Note: This work is not endorsed by or affiliated with NASA. Released under MIT license.

droptest's People

Stargazers

 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.