title: Effects of stress rate and calculation method on subcritical crack growth parameters deduced from constant stress-rate flexural testing.
abstract: OBJECTIVE
  To more efficiently determine the subcritical crack growth (SCG) parameters of dental ceramics, the effects of stressing rate and choice of statistical regression model on estimates of SCG parameters were assessed.
  
  
  METHODS
  Two dental ceramic materials, a veneering material having a single critical flaw population (S) and a framework material having partially concurrent flaw populations (PC), were analyzed using constant stress-rate testing, or "dynamic fatigue", with a variety of testing protocols. For each material, 150 rectangular beam specimens were prepared and tested in four-point flexure according to ISO6872 and ASTM1368. A full-factorial study was conducted on the following factors: material, stress rate assumed vs. calculated, number of stress rates, and statistical regression method.
  
  
  RESULTS
  The proportion of specimens for which the statistical models over-estimated reliability was not significantly different based on regression method for Material S (P = 0.96, power = 94%) and was significantly different based on regression method for Material PC (P < 0.001). The standard method resulted in SCG parameters, n and l nB, of 35.9 and -11.1 MPa(2)s for Material S and 12.4 and 9.61 MPa(2)s for Material PC, respectively.
  
  
  CONCLUSIONS
  The method of calculation that uses only the median strength value at each stress rate provided the most robust SCG parameter estimates. Using only two stress rates resulted in fatigue parameters comparable to those estimated using four stress rates having the same range. The stress rate of each specimen can be assumed to be the target stress rate with negligible difference in SCG parameter estimates.
authors.affiliation: Department of Biomedical Materials Science, University of Mississippi Medical Center, 2500 North State Street, Room D528, Jackson, MS 39216-4505, USA.
authors.forename: Jason A
authors.initials: JA
authors.lastname: Griggs
authors.forename: Samer M
authors.initials: SM
authors.lastname: Alaqeel
authors.forename: Yunlong
authors.initials: Y
authors.lastname: Zhang
authors.forename: Amp W
authors.initials: AW
authors.lastname: Miller
authors.forename: Zhuo
authors.initials: Z
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D000537:Aluminum Oxide / Q000737:chemistry; D000538:Aluminum Silicates / Q000737:chemistry; D003776:Dental Porcelain / Q000737:chemistry*; D003799:Dental Stress Analysis / Q000706:statistics & numerical data; D003801:Dental Veneers; D005544:Forecasting; D005898:Glass / Q000737:chemistry; D006801:Humans; D008422:Materials Testing / Q000706:statistics & numerical data; D018583:Pliability; D017680:Potassium Compounds / Q000737:chemistry; D012044:Regression Analysis; D013314:Stress, Mechanical; D013499:Surface Properties; D015040:Zirconium / Q000737:chemistry
chemical_list: D000538:Aluminum Silicates; C485633:In-Ceram Zirconia; D017680:Potassium Compounds; C483027:vitadur alpha; D003776:Dental Porcelain; C016447:feldspar; D015040:Zirconium; D000537:Aluminum Oxide; C028541:zirconium oxide