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Fracture mechanics. 1, Analysis of reliability and quality control /
This first book of a 3-volume set on Fracture Mechanics is mainly centered on the vast range of the laws of statistical distributions encountered in various scientific and technical fields. These laws are indispensable in understanding the probability behavior of components and mechanical structures...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London : John Wiley & Sons,
Hoboken, N.J. : ISTE Ltd ;
[2013?]
|
| Colección: | Mechanical engineering and solid mechanics series.
Fracture mechanics ; 1. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Grous, Ammar, |e author. | |
| 245 | 1 | 0 | |a Fracture mechanics. |n 1, |p Analysis of reliability and quality control / |c Ammar Grous. |
| 246 | 3 | 0 | |a Analysis of reliability and quality control |
| 264 | 1 | |a London : |b Hoboken, N.J. : |b ISTE Ltd ; |a John Wiley & Sons, |c [2013?] | |
| 264 | 4 | |c ©2013 | |
| 300 | |a 1 online resource (xii, 259 pages) : |b illustrations. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Mechanical engineering and solid mechanics series | |
| 490 | 1 | |a Fracture mechanics ; |v 1 | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |6 880-01 |a Title Page; Contents; Preface; Chapter 1. Elements of Analysis of Reliability and Quality Control; 1.1. Introduction; 1.1.1. The importance of true physical acceleration life models (accelerated tests = true acceleration or acceleration); 1.1.2. Expression for linear acceleration relationships; 1.2. Fundamental expression of the calculation of reliability; 1.3. Continuous uniform distribution; 1.3.1. Distribution function of probabilities (density of probability); 1.3.2. Distribution function; 1.4. Discrete uniform distribution (discrete U); 1.5. Triangular distribution. | |
| 505 | 8 | |a 1.5.1. Discrete triangular distribution version1.5.2. Continuous triangular law version; 1.5.3. Links with uniform distribution; 1.6. Beta distribution; 1.6.1. Function of probability density; 1.6.2. Distribution function of cumulative probability; 1.6.3. Estimation of the parameters (p, q) of the beta distribution; 1.6.4. Distribution associated with beta distribution; 1.7. Normal distribution; 1.7.1. Arithmetic mean; 1.7.2. Reliability; 1.7.3. Stabilization and normalization of variance error; 1.8. Log-normal distribution (Galton); 1.9. The Gumbel distribution. | |
| 505 | 8 | |a 1.9.1. Random variable according to the Gumbel distribution (CRV, E1 Maximum)1.9.2. Random variable according to the Gumbel distribution (CRV E1 Minimum); 1.10. The Frechet distribution (E2 Max); 1.11. The Weibull distribution (with three parameters); 1.12. The Weibull distribution (with two parameters); 1.12.1. Description and common formulae for the Weibull distribution and its derivatives; 1.12.2. Areas where the extreme value distribution model can be used; 1.12.3. Risk model; 1.12.4. Products of damage; 1.13. The Birnbaum-Saunders distribution. | |
| 520 | |a This first book of a 3-volume set on Fracture Mechanics is mainly centered on the vast range of the laws of statistical distributions encountered in various scientific and technical fields. These laws are indispensable in understanding the probability behavior of components and mechanical structures that are exploited in the other volumes of this series, which are dedicated to reliability and quality control. The author presents not only the laws of distribution of various models but also the tests of adequacy suited to confirm or counter the hypothesis of the law in question, namely t. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Reliability (Engineering) | |
| 650 | 0 | |a Quality control. | |
| 650 | 2 | |a Quality Control | |
| 650 | 6 | |a Fiabilité. | |
| 650 | 6 | |a Qualité |x Contrôle. | |
| 650 | 7 | |a quality control. |2 aat | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Quality Control. |2 bisacsh | |
| 650 | 7 | |a Quality control |2 fast | |
| 650 | 7 | |a Reliability (Engineering) |2 fast | |
| 758 | |i has work: |a Fracture mechanics 1 Analysis of reliability and quality control (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGvYt9vDQyFm7wvb7TCpmq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Grous, Ammar. |t Fracture mechanics. 1, Analysis of reliability and quality control. |d London : Hoboken, N.J. : ISTE ; Wiley, 2013 |z 9781848214408 |w (OCoLC)824602801 |
| 830 | 0 | |a Mechanical engineering and solid mechanics series. | |
| 830 | 0 | |a Fracture mechanics ; |v 1. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=3058885 |z Texto completo |
| 880 | 0 | 0 | |6 505-01/(S |g Machine generated contents note: |g ch. 1 |t Elements of Analysis of Reliability and Quality Control -- |g 1.1. |t Introduction -- |g 1.1.1. |t importance of true physical acceleration life models (accelerated tests = true acceleration or acceleration) -- |g 1.1.2. |t Expression for linear acceleration relationships -- |g 1.2. |t Fundamental expression of the calculation of reliability -- |g 1.3. |t Continuous uniform distribution -- |g 1.3.1. |t Distribution function of probabilities (density of probability) -- |g 1.3.2. |t Distribution function -- |g 1.4. |t Discrete uniform distribution (discrete U) -- |g 1.5. |t Triangular distribution -- |g 1.5.1. |t Discrete triangular distribution version -- |g 1.5.2. |t Continuous triangular law version -- |g 1.5.3. |t Links with uniform distribution -- |g 1.6. |t Beta distribution -- |g 1.6.1. |t Function of probability density -- |g 1.6.2. |t Distribution function of cumulative probability -- |g 1.6.3. |t Estimation of the parameters (p, q) of the beta distribution -- |g 1.6.4. |t Distribution associated with beta distribution -- |g 1.7. |t Normal distribution -- |g 1.7.1. |t Arithmetic mean -- |g 1.7.2. |t Reliability -- |g 1.7.3. |t Stabilization and normalization of variance error -- |g 1.8. |t Log-normal distribution (Galton) -- |g 1.9. |t Gumbel distribution -- |g 1.9.1. |t Random variable according to the Gumbel distribution (CRV, E1 Maximum) -- |g 1.9.2. |t Random variable according to the Gumbel distribution (CRV E1 Minimum) -- |g 1.10. |t Frechet distribution (E2 Max) -- |g 1.11. |t Weibull distribution (with three parameters) -- |g 1.12. |t Weibull distribution (with two parameters) -- |g 1.12.1. |t Description and common formulae for the Weibull distribution and its derivatives -- |g 1.12.2. |t Areas where the extreme value distribution model can be used -- |g 1.12.3. |t Risk model -- |g 1.12.4. |t Products of damage -- |g 1.13. |t Birnbaum-Saunders distribution -- |g 1.13.1. |t Derivation and use of the Birnbaum-Saunders model -- |g 1.14. |t Cauchy distribution -- |g 1.14.1. |t Probability density function -- |g 1.14.2. |t Risk function -- |g 1.14.3. |t Cumulative risk function -- |g 1.14.4. |t Survival function (reliability) -- |g 1.14.5. |t Inverse survival function -- |g 1.15. |t Rayleigh distribution -- |g 1.16. |t Rice distribution (from the Rayleigh distribution) -- |g 1.17. |t Tukey-lambda distribution -- |g 1.18. |t Student's (t) distribution -- |g 1.18.1. |t t-Student's inverse cumulative function law (T) -- |g 1.19. |t Chi-square distribution law (Χ2) -- |g 1.19.1. |t Probability distribution function of chi-square law (Χ2) -- |g 1.19.2. |t Probability distribution function of chi-square law (Χ2) -- |g 1.20. |t Exponential distribution -- |g 1.20.1. |t Example of applying mechanics to component lifespan -- |g 1.21. |t Double exponential distribution (Laplace) -- |g 1.21.1. |t Estimation of the parameters -- |g 1.21.2. |t Probability density function -- |g 1.21.3. |t Cumulated distribution probability function -- |g 1.22. |t Bernoulli distribution -- |g 1.23. |t Binomial distribution -- |g 1.24. |t Polynomial distribution -- |g 1.25. |t Geometrical distribution -- |g 1.25.1. |t Hypergeometric distribution (the Pascal distribution) versus binomial distribution -- |g 1.26. |t Hypergeometric distribution (the Pascal distribution) -- |g 1.27. |t Poisson distribution -- |g 1.28. |t Gamma distribution -- |g 1.29. |t Inverse gamma distribution -- |g 1.30. |t Distribution function (inverse gamma distribution probability density) -- |g 1.31. |t Erlang distribution (characteristic of gamma distribution, Γ) -- |g 1.32. |t Logistic distribution -- |g 1.33. |t Log-logistic distribution -- |g 1.33.1. |t Mathematical-statistical characteristics of log-logistic distribution -- |g 1.33.2. |t Moment properties -- |g 1.34. |t Fisher distribution (F-distribution or Fisher-Snedecor) -- |g 1.35. |t Analysis of component lifespan (or survival) -- |g 1.36. |t Partial conclusion of Chapter 1 -- |g 1.37. |t Bibliography -- |g ch. 2 |t Estimates, Testing Adjustments and Testing the Adequacy of Statistical Distributions -- |g 2.1. |t Introduction to assessment and statistical tests -- |g 2.1.1. |t Estimation of parameters of a distribution -- |g 2.1.2. |t Estimation by confidence interval -- |g 2.1.3. |t Properties of an estimator with and without bias -- |g 2.2. |t Method of moments -- |g 2.3. |t Method of maximum likelihood -- |g 2.3.1. |t Estimation of maximum likelihood -- |g 2.3.2. |t Probability equation of reliability-censored data -- |g 2.3.3. |t Punctual estimation of exponential law -- |g 2.3.4. |t Estimation of the Weibull distribution -- |g 2.3.5. |t Punctual estimation of normal distribution -- |g 2.4. |t Moving least-squares method -- |g 2.4.1. |t General criterion: the LSC -- |g 2.4.2. |t Examples of nonlinear models -- |g 2.4.3. |t Example of a more complex process -- |g 2.5. |t Conformity tests: adjustment and adequacy tests -- |g 2.5.1. |t Model of the hypothesis test for adequacy and adjustment -- |g 2.5.2. |t Kolmogorov-Smirnov Test (KS 1930 and 1936) -- |g 2.5.3. |t Simulated test (1st application) -- |g 2.5.4. |t Simulated test (2nd application) -- |g 2.5.5. |t Example 1 -- |g 2.5.6. |t Example 2 (Weibull or not) -- |g 2.5.7. |t Cramer-Von Mises (CVM) test -- |g 2.5.8. |t Anderson-Darling test -- |g 2.5.9. |t Shapiro-Wilk test of normality -- |g 2.5.10. |t Adequacy test of chi-square (Χ2) -- |g 2.6. |t Accelerated testing method -- |g 2.6.1. |t Multi-censored tests -- |g 2.6.2. |t Example of the exponential model -- |g 2.6.3. |t Example of the Weibull model -- |g 2.6.4. |t Example for the log-normal model -- |g 2.6.5. |t Example of the extreme value distribution model (E-MIN) -- |g 2.6.6. |t Example of the study on the Weibull distribution -- |g 2.6.7. |t Example of the BOX-COX model -- |g 2.7. |t Trend tests -- |g 2.7.1. |t unilateral test -- |g 2.7.2. |t military handbook test (from the US Army) -- |g 2.7.3. |t Laplace test -- |g 2.7.4. |t Homogenous Poisson Process (HPP) -- |g 2.8. |t Duane model power law -- |g 2.9. |t Chi-Square test for the correlation quantity -- |g 2.9.1. |t Estimations and Χ2 test to determine the confidence interval -- |g 2.9.2. |t t_test of normal mean -- |g 2.9.3. |t Standard error of the estimated difference, s -- |g 2.10. |t Chebyshev's inequality -- |g 2.11. |t Estimation of parameters -- |g 2.12. |t Gaussian distribution: estimation and confidence interval -- |g 2.12.1. |t Confidence interval estimation for a Gauss distribution -- |g 2.12.2. |t Reading to help the statistical values tabulated -- |g 2.12.3. |t Calculations to help the statistical formulae appropriate to normal distribution -- |g 2.12.4. |t Estimation of the Gaussian mean of unknown variance -- |g 2.13. |t Kaplan-Meier estimator -- |g 2.13.1. |t Empirical model using the Kaplan-Meier approach -- |g 2.13.2. |t General expression of the KM estimator -- |g 2.13.3. |t Application of the ordinary and modified Kaplan-Meier estimator -- |g 2.14. |t Case study of an interpolation using the bi-dimensional spline function -- |g 2.15. |t Conclusion -- |g 2.16. |t Bibliography -- |g ch. 3 |t Modeling Uncertainty -- |g 3.1. |t Introduction to errors and uncertainty -- |g 3.2. |t Definition of uncertainties and errors as in the ISO norm -- |g 3.3. |t Definition of errors and uncertainty in metrology -- |g 3.3.1. |t Difference between error and uncertainty -- |g 3.4. |t Global error and its uncertainty -- |g 3.5. |t Definitions of simplified equations of measurement uncertainty -- |g 3.5.1. |t Expansion factor k and range of relative uncertainty -- |g 3.5.2. |t Determination of type A and B uncertainties according to GUM -- |g 3.6. |t Principal of uncertainty calculations of type A and type B -- |g 3.6.1. |t Standard and expanded uncertainties -- |g 3.6.2. |t Components of type A and type B uncertainties -- |g 3.6.3. |t Error on repeated measurements: composed uncertainty -- |g 3.7. |t Study of the basics with the help of the GUMic software package: quasi-linear model -- |g 3.8. |t Conclusion -- |g 3.9. |t Bibliography. |
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