Analysis of Flexure Strength Data of Ceramics

1983 ◽  
Vol 105 (3) ◽  
pp. 219-223 ◽  
Author(s):  
S. G. Seshadri ◽  
M. Srinivasan
Keyword(s):  
Strength Distribution ◽  
Service Performance ◽  
Parameter Estimates ◽  
Reliability Data ◽  
Flexure Strength ◽  
Statistical Strength ◽  
Strength Data ◽  
Weibull Parameters ◽  
Surface Flaws ◽  
Test Population

A method to obtain the two and three Weibull parameters from the statistical strength distribution of ceramics, when either surface flaws or volumetric flaws govern fracture, is outlined. The advantages of obtaining confidence in the parameter estimates are given realizing the flaw severity variations within a test population. The inadequacy of testing a very limited number of specimens to gather reliability data to assess service performance is discussed.

Some Stochastic Mechanical Design Applications

1992 ◽  
Vol 114 (1) ◽  
pp. 42-47 ◽  
Author(s):  
C. R. Mischke
Keyword(s):  
Mechanical Design ◽  
Stochastic Methods ◽  
Strength Data ◽  
Weibull Parameters ◽  
The Third ◽  
Active Constraints ◽  
Stochastic Problems ◽  
Property Data ◽  
Machine Elements ◽  
Machinery Design

This is the third paper in a series relating to stochastic methods in mechanical design. The two previous ones were entitled, “Some Property Data and Corresponding Weibull Parameters for Stochastic Mechanical Design,” and “Fitting Weibull Strength Data and Applying it to Stochastic Mechanical Design.” They presented the groundwork for addressing stochastic problems in machinery design to a reliability goal when strength data are sparse. The purpose of this paper is to utilize procedures for estimating reliability of machine elements when yielding, fracture, or distortion are the limiting or active constraints.

Some Property Data and Corresponding Weibull Parameters for Stochastic Mechanical Design

1992 ◽  
Vol 114 (1) ◽  
pp. 29-34 ◽  
Author(s):  
C. R. Mischke
Keyword(s):  
Goodness Of Fit ◽  
Mechanical Design ◽  
Stochastic Methods ◽  
Published Data ◽  
Short Supply ◽  
Strength Data ◽  
Weibull Parameters ◽  
Property Data ◽  
Strength Distributions

This is the first paper in a series of three relating to stochastic methods in mechanical design. The others are entitled, “Fitting Weibull Strength Data and Applying it to Stochastic Mechanical Design,” and “Some Stochastic Mechanical Design Applications.” The purpose of this paper is to present some Weibull parameters of strength distributions that were deduced from published histographic data. Stochastic materials data are in short supply; yet a closer look shows a surprising amount available. However, the published data may need to be interpreted and personal tests reduced. This paper shows histographic data that was converted to three-parameter Weibull distributional fits with relevant goodness-of-fit information displayed.

Testing Weibull as a viable statistical strength distribution for Nacre

2021 ◽  
Vol 158 ◽  
pp. 103855
Author(s):  
Arunachalam Muthukaruppan ◽  
Manoj Pandey ◽  
Amirtham Rajagopal
Keyword(s):  
Strength Distribution ◽  
Statistical Strength

scholarly journals Is Weibull distribution the most appropriate statistical strength distribution for brittle materials?

2009 ◽  
Vol 35 (1) ◽  
pp. 237-246 ◽  
Author(s):  
Bikramjit Basu ◽  
Devesh Tiwari ◽  
Debasis Kundu ◽  
Rajesh Prasad
Keyword(s):  
Weibull Distribution ◽  
Brittle Materials ◽  
Strength Distribution ◽  
Statistical Strength

scholarly journals Fracture Statistics for Inorganically-Bound Core Materials

Materials ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2306 ◽  
Author(s):  
Philipp Lechner ◽  
Jens Stahl ◽  
Florian Ettemeyer ◽  
Benjamin Himmel ◽  
Bianca Tananau-Blumenschein ◽  
...  
Keyword(s):  
Distribution Function ◽  
Fracture Stress ◽  
Brittle Materials ◽  
Weibull Model ◽  
Strength Distribution ◽  
Fracture Characteristics ◽  
Weibull Parameters ◽  
Four Point Bending ◽  
Volume Dependence ◽  
Bending Fracture

In this article, we study the fracture characteristics of inorganically-bound foundry cores. It will be shown that the fracture stress of inorganic cores follows Weibull’s strength distribution function for brittle materials. Using three-point and four-point-bending experiments, the volume dependence of the bending fracture stress is analyzed and a Weibull model fitted. Furthermore, the fracture stress of arbitrary bending experiments can be calculated based on the Weibull parameters found.

scholarly journals Understanding the effect of surface flaws on the strength distribution of brittle single crystals

2018 ◽  
Vol 101 (12) ◽  
pp. 5705-5716 ◽  
Author(s):  
Manuel Gruber ◽  
Alexander Leitner ◽  
Irina Kraleva ◽  
Daniel Kiener ◽  
Peter Supancic ◽  
...  
Keyword(s):  
Single Crystals ◽  
Strength Distribution ◽  
Surface Flaws ◽  
Effect Of Surface

The Effect of Elevated Temperature Exposure of Composites on the Strength Distribution of the Reinforcing Fibers

1994 ◽  
Vol 350 ◽  
Author(s):  
M. L. Gambone ◽  
F. E. Wawner
Keyword(s):  
Elevated Temperature ◽  
Fiber Strength ◽  
Strength Distribution ◽  
Surface Flaw ◽  
Heat Treated ◽  
Weibull Statistical Analysis ◽  
Surface Flaws ◽  
The Matrix ◽  
Temperature Exposure ◽  
The Relationship

AbstractUnidirectionally-reinforced Timetal® 21S composite specimens were subjected to elevated temperature heat treatments. The SiC fibers were then chemically extracted from the matrix, and their tensile strengths were measured at room temperature. A Weibull statistical analysis of fiber strength distribution was performed to compare the Weibull parameters of fibers from the as-consolidated and heat-treated composites. Fractographic analysis of the tested fibers was used to identify the flaws which caused failure in each condition. Surface flaws were found to initiate low strength failures in all conditions, and the number of surface initiated failures increased with an increase in severity of heat-treatment. A relationship between the fiber/matrix chemical reaction and surface flaw development is demonstrated. A fracture mechanics analysis that explains the relationship between surface flaw size, fiber fracture toughness, and the measured tensile strengths is suggested.

Sem Examinations of Glass Knives

1970 ◽  
Vol 28 ◽  
pp. 282-283
Author(s):  
J. Temple Black
Keyword(s):  
Plastic Deformation ◽  
Tensile Loading ◽  
Resultant Force ◽  
Stress Concentrations ◽  
Edge Chipping ◽  
Surface Flaws ◽  
Edge Defects ◽  
Microscopic Surface

There are two types of edge defects common to glass knives as typically prepared for microtomy purposes: 1) striations and 2) edge chipping. The former is a function of the free breaking process while edge chipping results from usage or bumping of the edge. Because glass has no well defined planes in its structure, it should be highly resistant to plastic deformation of any sort, including tensile loading. In practice, prevention of microscopic surface flaws is impossible. The surface flaws produce stress concentrations so that tensile strengths in glass are typically 10-20 kpsi and vary only slightly with composition. If glass can be kept in compression, wherein failure is literally unknown (1), it will remain intact for long periods of time. Forces acting on the tool in microtomy produce a resultant force that acts to keep the edge in compression.

Glass Knife Geometry as Seen by the SEM

1971 ◽  
Vol 29 ◽  
pp. 454-455
Author(s):  
J. Temple Black
Keyword(s):  
Low Cost ◽  
Amorphous Material ◽  
Stress Concentrations ◽  
Basic Tool ◽  
Tool Materials ◽  
Optical Inspection ◽  
Surface Flaws ◽  
Slip Planes ◽  
Glass Knife ◽  
Diamond Knife

In ultramicrotomy, the two basic tool materials are glass and diamond. Glass because of its low cost and ease of manufacture of the knife itself is still widely used despite the superiority of diamond knives in many applications. Both kinds of knives produce plastic deformation in the microtomed section due to the nature of the cutting process and microscopic chips in the edge of the knife. Because glass has no well defined slip planes in its structure (it's an amorphous material), it is very strong and essentially never fails in compression. However, surface flaws produce stress concentrations which reduce the strength of glass to 10,000 to 20,000 psi from its theoretical or flaw free values of 1 to 2 million psi. While the microchips in the edge of the glass or diamond knife are generally too small to be observed in the SEM, the second common type of defect can be identified. This is the striations (also termed the check marks or feathers) which are always present over the entire edge of a glass knife regardless of whether or not they are visable under optical inspection. These steps in the cutting edge can be observed in the SEM by proper preparation of carefully broken knives and orientation of the knife, with respect to the scanning beam.

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