JTCG/AS Interlaboratory Ballistic Test Program

Chang, Albert L.; Bodt, Barry A.

doi:10.21236/ada335629

Cited by 4 publications

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“…Two more promising possible models for fitting data of the type given in the curve in figure 1 are the cdf mixture model (CDFMM) (Bodt and Chang, 1997), a parametric method model procedure, and local llogr, a nonparametric method.…”

Section: Possible Modelsmentioning

confidence: 99%

“…Experimenters use variants of the Up and Down strategy (Dixon and Mood, 1948), the Robbins-Monro (Robbins and Monro, 1951), or other sequential designs to gather observations, and the maximum likelihood estimate (MLE) for the mean (V 50 ) is formed with a logistic or normal response function. An interlaboratory study of V50 estimation revealed widely varying estimates for some penetrator-armor matches (Chang and Bodt, 1997). Initially, the blame was thought to lie with varying test procedures among experimental testing sites.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Nonmonotonic Dose-Response Curves

Nottingham¹,

Birch²,

Bodt³

2001

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A number of procedures have been used to analyze nonmonotonic binary data to predict the probability of response. Some classical procedures are the Up and Down strategy the Robbins-Monro procedure, and other sequential optimization designs. Recently, nonparametric procedures such as kernel regression and local linear regression have been applied to this type of data. It is well known that kernel regression has problems fitting the data near the boundaries, and a drawback with local linear regression is that it may be too linear when fitting data from a curvilinear function. This report introduces a procedure called local logistic regression, which fits a logistic regression function at each of the data points. United States Army projectile data are used in an example that supports the use of local logistic regression for analyzing nonmonotonic binary data for certain response curves. Properties of local logistic regression are presented along with simulation results that indicate some of the strengths of the procedure. 11

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Section: Possible Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling Nonmonotonic Dose-Response Curves

Nottingham¹,

Birch²,

Bodt³

2001

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Local logisitic regression an application to army penetration data

Nottingham¹,

Birch

Bodt

2000

Journal of Statistical Computation and Simulation

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Performance Metrics for Composite Integral Armor

Fink

2000

Journal of Thermoplastic Composite Materials

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Future combat systems necessarily focus on lightweight, highly mobile and transportable armored vehicles. Lightweight composite integral armor systems are being developed to meet these needs. The goal of this paper is to centrally document the myriad design requirements for composite integral armors that serve multifunctional roles including ballistic, structural, shock, electromagnetic, and fire protection. Structural and ballistic performance requirements as well as manufacturing and life-cycle performance issues of integral armor are presented. Specific areas addressed include high-strain-rate testing and modeling, ballistic testing and modeling, low-cycle fatigue, damage tolerance, repair, reduced-step processing, through-thickness reinforcement, energy dissipation and rate-dependent failure mechanisms, and non-linear mechanics.

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JTCG/AS Interlaboratory Ballistic Test Program

Cited by 4 publications

References 1 publication

Modeling Nonmonotonic Dose-Response Curves

Modeling Nonmonotonic Dose-Response Curves

Local logisitic regression an application to army penetration data

Performance Metrics for Composite Integral Armor

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