Characterization and analysis of the tensile and acoustic emission parameter distributions of single wool fibers

2020 ◽  
Vol 90 (21-22) ◽  
pp. 2454-2466
Author(s):  
Di Lu ◽  
Weidong Yu

Acoustic emission (AE) parameters of damaged material have discrete characteristics that are universally known. Such characteristics restrict wider use of AE analysis in materials such as textiles. In the present work, the best-fitted distribution models of AE signal energy are analyzed: amplitude, duration, tensile breaking strength, elongation, and specific work of wool fibers. The parameters of Weibull, normal, and log-normal distribution models are obtained by regression analysis. The chi-square, Kolmogorov–Smirnov, and maximum likelihood criterions are used to discriminate against the above models. The results show that the Weibull distribution is the best-fitted model for amplitude and elongation of wool. The best-fitted model for energy, strength, and specific work is the log-normal distribution. The differences between the cumulative distributions of the AE and tensile parameters are compared. It can be seen that strength also has a high correlation coefficient and a similarly cumulative distribution with energy and amplitude. Compared to amplitude, the relationship between energy and strength is supposed to be stronger.

2016 ◽  
Vol 18 (2) ◽  
pp. 139-148
Author(s):  
Togani Cahyadi Upomo ◽  
Rini Kusumawardani

Rainfall event is a stochastic process, so to explain and analyze this processes the probability theory and frequency analysisare used. There are four types of probability distributions.They are normal, log normal, log Pearson III and Gumbel. To find the best probabilities distribution, it will used goodness of fit test. The tests consist of chi-square and smirnov-kolmogorov. Results of the chi-square test for normal distribution, log normal and log Pearson III was 0.200, while for the Gumbel distribution was 2.333. Results of Smirnov Kolmogorov test for normal distribution D = 0.1554, log-normal distribution D = 0.1103, log Pearson III distribution D = 0.1177 and Gumbel distribution D = 0.095. All of the distribution can be accepted with a confidence level of 95%, but the best distribution is log normal distribution.Kejadian hujan merupakan proses stokastik, sehingga untuk keperluan analisa dan menjelaskan proses stokastik tersebut digunakan teori probabilitas dan analisa frekuensi. Terdapat empat jenis distribusi probabilitas yaitu distribusi normal, log normal, log pearson III dan gumbel. Untuk mencari distribusi probabilitas terbaik maka akan digunakan pengujian metode goodness of fit test. Pengujian tersebut meliputi uji chi-kuadrat dan uji smirnov kolmogorov. Hasil pengujian chi kuadrat untuk distribusi normal, log normal dan log pearson III adalah 0.200, sedangkan untuk distribusi gumbel 2.333. Hasil pengujian smirnov kolmogorov untuk distribusi normal dengan nilai D = 0.1554, distribusi log normal dengan nilai D = 0.1103, distribusi log pearson III dengan nilai D = 0.1177 dan distribusi gumbel dengan nilai D = 0.095. Seluruh distribusi dapat diterima dengan tingkat kepercayaan 95%, tetapi distribusi terbaik adalah distribusi log normal.


2020 ◽  
Vol 8 (1) ◽  
pp. 09-34
Author(s):  
Abou El-Makarim Aboueissa

The occurrence of censored data due to less than detectable measurements is a common problem with environmental data such as quality and quantity monitoring applications of water, soil, and air samples. The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. Over the past decades, various methods for comparing the parameters of two lognormal distributions in the presence censored data have been proposed. Some of them are differing in terms of how the statistic test adjust to accept or to reject the null hypothesis. As a model distribution of measured environmental and/or biomedical data, log-normal distribution is considered. Logmormal means can be compared either by confidence intervals or hypothesis testing procedures. In this article, a new test procedure for comparing the means of k (k >= 3) lognormal distributions in the presence of left-censored data is introduced and evaluated. Asymptotic chi-square test is used in the proposed test procedure. A simulation study was performed to examine the power and the size of the proposed test procedure introduced in this article utilizing a computer program written in the R language. We find  analytically that the considered test procedure is doing well through comparing the size and power of the statistic test.


2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.


Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 64
Author(s):  
Arnaud Millet

The mechanosensitivity of cells has recently been identified as a process that could greatly influence a cell’s fate. To understand the interaction between cells and their surrounding extracellular matrix, the characterization of the mechanical properties of natural polymeric gels is needed. Atomic force microscopy (AFM) is one of the leading tools used to characterize mechanically biological tissues. It appears that the elasticity (elastic modulus) values obtained by AFM presents a log-normal distribution. Despite its ubiquity, the log-normal distribution concerning the elastic modulus of biological tissues does not have a clear explanation. In this paper, we propose a physical mechanism based on the weak universality of critical exponents in the percolation process leading to gelation. Following this, we discuss the relevance of this model for mechanical signatures of biological tissues.


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