This work identifies the influence of strain rate, temperature, plastic strain, and microstructure on the strain rate sensitivity of automotive sheet steel grades in crash conditions. The strain rate sensitivity m has been determined by means of dynamic tensile tests in the strain rate range 10 À3 -200 s À1 and in the temperature range 233-373 K. The dynamic flow curves have been tested by means of servohydraulic tensile testing. The strain rate sensitivity decreases with increasing plastic strain due to a gradual exhausting of work hardening potential combined with adiabatic softening effects. The strain rate sensitivity is improved with decreasing temperature and increasing strain rate, according to the thermally activated deformation mechanism. The m-value is reduced with increasing strength level, this decrease being most pronounced for steels with a yield strength below 400 MPa. Solid solution alloying with manganese, silicon, and especially phosphorous elements lowers the strain rate sensitivity significantly. Second phase hardening with bainite and martensite as the second constituent in a ferritic matrix reduces the strain rate sensitivity of automotive sheet steels. A statistical modeling is proposed to correlate the m-value with the corresponding quasistatic tensile flow stress.

The present investigation deals with the influence of pre-straining with or without bake hardening on the strain rate sensitivity of automotive sheet steels in typical crash conditions. The strain rate sensitivity m has been determined by means of dynamic tensile tests in the strain rate range 0.005-1000 s À1 and in the temperature range 233-373K. A bake hardening heat treatment at 170 8C for 20 min without pre-straining does not influence the m-value in comparison to the base material condition. A small pre-straining near plane strain condition, as commonly found in outer door panels, or a 10% uniaxial, plane strain and biaxial pre-straining, as typically used in formed automotive crash components, without bake hardening does not affect the m-value of sheet steels in comparison to the base material condition. Uniaxial 2% to 10% pre-straining, longitudinal or transverse to rolling direction with subsequent bake hardening, does not clearly change the m-value in comparison to the base material condition either. Small differences in the strain rate sensitivity behaviour are rather attributed to experimental scattering without real physical background.

The dynamic behavior of AISI 301LN2B (EN 1.4318) metastable austenitic steel grade has been investigated at 296 K by means of servohydraulic tensile and split Hopkinson bar testing in the strain rate range 0.005–1000 s−1. As delivered, as well as 10% uniaxial, biaxial, and plane strain pre‐strained conditions, without subsequent heat treatment have been tested. A negative strain rate sensitivity is observed in the low strain rate range between 10−4 and 1–10 s−1. Pre‐straining reduces the magnitude of the adiabatic tensile strength softening, especially in the plane strain condition with higher triaxility. The thermal activation related dynamic flow stress increase is not dependent on pre‐straining. The γ → α′ induced additional flow stress increase, however, is highly strain rate and pre‐straining sensitive. The amount of pre‐straining determines the overall ductility at fracture, and therefore the adiabatic temperature increase. The pre‐straining stress state influences the amount of α′‐martensite formed before dynamic testing, and consequently the maximum intensity of the TRIP induced flow stress increase by subsequent dynamic testing.

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Fisher information about multiple parameters in a progressively Type-II censored sample is discussed. A representation of the Fisher information matrix in terms of the hazard rate of the baseline distribution is established which can be used for efficient computation of the Fisher information. This expression generalizes a result of Zheng and Park [On the Fisher information in multiply censored and progressively censored data, Comm. Statist. Theory Methods 33 (2004), pp. 1821-1835 for Fisher information about a single parameter. The result is applied to identify A-and D-optimal censoring plans in a progressively Type-II censored experiment. For illustration, extreme value, normal, and Lomax distributions are considered.