Optimum adhesive thickness in structural adhesives joints using statistical techniques base on Weibull distribution

The geometrical factors defining an adhesive joint are of great importance as its design greatly conditions the performance of the bonding. One of the most relevant geometrical factors is the thickness of the adhesive as it decisively influences the mechanical properties of the bonding and has a clear economic impact on the manufacturing processes or long runs. The traditional mechanical joints (riveting, welding, etc.) are characterised by a predictable performance, and are very reliable in service conditions. Thus, structural adhesive joints will only be selected in industrial applications demanding mechanical requirements and adverse environmental conditions if the suitable reliability (the same or higher than the mechanical joints) is guaranteed. For this purpose, the objective of this paper is to analyse the influence of the adhesive thickness on the mechanical behaviour of the joint and, by means of a statistical analysis based on Weibull distribution, propose the optimum thickness for the adhesive combining the best mechanical performance and high reliability. This procedure, which is applicable without a great deal of difficulty to other joints and adhesives, provides a general use for a more reliable use of adhesive bondings and, therefore, for a better and wider use in the industrial manufacturing processes.

Improved estimation of Weibull Parameters considering unreliability uncertainties

We propose a linear regression method for estimating Weibull parameters from life tests. The method uses stochastic models of the unreliability at each failure instant. As a result, a heteroscedastic regression problem arises that is solved by weighted least squares minimization. The main feature of our method is an innovative s-normalization of the failure data models, to obtain analytic expressions of centers and weights for the regression. The method has been Monte Carlo contrasted with Benard?s approximation, and Maximum Likelihood Estimation; and it has the highest global scores for its robustness, and performance.

Fracture strength of drilled wafers: study of the stress concentration factor and determination of the weibull distribution of the fracture stress

In the photovoltaic field, the back contact solar cells technology has appeared as an alternative to the traditional silicon modules. This new type of cells places both positive and negative contacts on the back side of the cells maximizing the exposed surface to the light and making easier the interconnection of the cells in the module. The Emitter Wrap-Through solar cell structure presents thousands of tiny holes to wrap the emitter from the front surface to the rear surface. These holes are made in a first step over the silicon wafers by means of a laser drilling process. This step is quite harmful from a mechanical point of view since holes act as stress concentrators leading to a reduction in the strength of these wafers. This paper presents the results of the strength characterization of drilled wafers. The study is carried out testing the samples with the ring on ring device. Finite Element models are developed to simulate the tests. The stress concentration factor of the drilled wafers under this load conditions is determined from the FE analysis. Moreover, the material strength is characterized fitting the fracture stress of the samples to a three-parameter Weibull cumulative distribution function. The parameters obtained are compared with the ones obtained in the analysis of a set of samples without holes to validate the method employed for the study of the strength of silicon drilled wafers.

Conditional Confidence Interval for the Scale Parameter of a Weibull Distribution

2000 Mathematics Subject Classification: 62F25, 62F03.

Bayesian Prediction of Weibull Distribution Based on Fixed and Random Sample Size

2000 Mathematics Subject Classification: 62E16, 65C05, 65C20.

Bayesian and Frequentist Two-Sample Predictions of the Inverse Weibull Model Based on Generalized Order Statistics

2000 Mathematics Subject Classification: 62E16,62F15, 62H12, 62M20.

Caracterização analítica e geométrica da metodologia geral de determinação de distribuições de Weibull para o regime eólico e suas aplicações

O regime eólico de uma região pode ser descrito por distribuição de frequências que fornecem informações e características extremamente necessárias para uma possível implantação de sistemas eólicos de captação de energia na região e consequentes aplicações no meio rural em regiões afastadas. Estas características, tais como a velocidade média anual, a variância das velocidades registradas e a densidade da potência eólica média horária, podem ser obtidas pela frequência de ocorrências de determinada velocidade, que por sua vez deve ser estudada através de expressões analíticas. A função analítica mais adequada para distribuições eólicas é a função de densidade de Weibull, que pode ser determinada por métodos numéricos e regressões lineares. O objetivo deste trabalho é caracterizar analítica e geometricamente todos os procedimentos metodológicos necessários para a realização de uma caracterização completa do regime eólico de uma região e suas aplicações na região de Botucatu - SP, visando a determinar o potencial energético para implementação de turbinas eólicas. Assim, foi possível estabelecer teoremas relacionados com a forma de caracterização do regime eólico, estabelecendo a metodologia concisa analiticamente para a definição dos parâmetros eólicos de qualquer região a ser estudada. Para o desenvolvimento desta pesquisa, utilizou-se um anemômetro da CAMPBELL.

Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Modified Steels for Cold-Forming U-Bolts Used In Leaf Springs Systems

In this work, a low alloy steel and a fabrication process were developed to produce U-Bolts for commercial vehicles. Thus, initially five types of no-heat treated steel were developed with different additions of chrome, nickel, and silicon to produce strain hardening effect during cold-forming processing of the U-Bolts, assuring the required mechanical properties. The new materials exhibited a fine perlite and ferrite microstructure due to aluminum and vanadium additions, well known as grain size refiners. The mechanical properties were evaluated in a servo-hydraulic test machine system-MTS 810 according to ASTM A370-03; E739 and E08m-00 standards. The microstructure and fractography analyses of the cold-formed steels were performed by using optical and scanning electronic microscope techniques. To evaluate the performance of the steels and the production process, fatigue tests were carried out under load control (tensile-tensile), R = 0.1 and f = 30 Hz. The Weibull statistic methodology was used for the analysis of the fatigue results. At the end of this work the 0.21% chrome content steel, Alloy 2, presented the best fatigue performance.

Mechanical properties and cytotoxicity of 3Y-TZP bioceramics reinforced with Al(2)O(3) particles

The influence of Al(2)O(3) addition and sintering parameters on the mechanical properties and cytotoxicity of tetragonal ZrO(2)-3 mol% Y(2)O(3) ceramics was evaluated. Samples containing 0, 10, 20 and 30 wt.% of Al(2)O(3) particles were prepared by cold uniaxial pressing (80 MPa) and sintered in air at 1500, 1550 and 1600 degrees C for 120 min. The effects of the sintering conditions on the microstructure were analyzed by X-ray diffraction analysis and scanning electron microscopy. Hardness and fracture toughness were determined by the Vickers indentation method and the mechanical resistance by four-point bending tests. As a preliminary biological evaluation, ""in vitro"" cytotoxicity tests were realized to determine the cytotoxic level of the ZrO(2)-Al(2)O(3) composites, using the neutral red uptake method with NCTC clones L929 from the American Type Culture Collection (ATCC) bank. Fully dense ceramic materials were obtained with a hardness ranging between 1340 HV and 1585 HV, depending on the amount of Al(2)O(3) in the ZrO(2) matrix. On the other hand, no significant influence of the Al(2)O(3) addition on fracture toughness was observed, exhibiting values near 8 MPa m(1/2) for all compositions and sintering conditions studied. The non-cytotoxic behavior, the elevated fracture toughness, the good bending strength (sigma(f) = 690 MPa) and the elevated Weibull`s modulus (m = 11) exhibited by the material, show that these ceramic composites are highly suitable biomaterials for dental implant applications. (C) 2008 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.