Statistical Analysis of Breakdown Voltages in Virgin and Aged LDPE Using Johnson SB and Weibull Distribution

2016 ◽  
Vol 818 ◽  
pp. 58-62
Author(s):  
Nurul A. Bani ◽  
Zulkurnain Abdul-Malek ◽  
Hussein Ahmad
Keyword(s):  
Statistical Analysis ◽  
Weibull Distribution ◽  
Density Function ◽  
Polymeric Material ◽  
High Voltage ◽  
Goodness Of Fit ◽  
Engineering Application ◽  
Statistical Parameters ◽  
Insulating Material ◽  
High Voltage Engineering

Polymeric material such as low density polyethylene (LDPE) has been used for decades as insulating material. Any polymeric material will experience degradation after prolonged application of high electrical stresses. Deeper understanding of the long term electrical degradation of the insulating material is necessary to predict the life of high voltage cable. Electroluminescence method (EL) is used to detect the breakdown voltages of thin film LDPE. This method utilizes a Peltier cooled electron multiplying charge coupled device (EMCCD) camera to detect the breakdown of the sample. Statistical distribution of the AC breakdown voltages of 100μm virgin and aged LDPE has been analysed. Comparison for the best fitted distribution was made for Weibull distribution and Johnson SB distribution using Anderson-Darling (A2) goodness-of-fit and Kolmogorov-Smirnov (D) goodness-of-fit (GOF). Johnson SB is rarely used in high voltage engineering application. The probability density function (PDF) and the cumulative density function (CDF) for both distributions are defined in this article. The statistical parameters used are estimated based on Maximum Likelihood Estimation (MLE) for both distributions. Based on the statistical analysis, it is observed that Johnson SB provide better fitting than Weibull distribution with lower fitting error and that 3-parameter Weibull is much better fitting than 2-parameter Weibull distribution for most cases. It is also found that the median breakdown voltage of LDPE samples decreases with increasing aging temperature.

STATISTICAL ANALYSIS FOR TERENGGANU FORWARD SCATTER RADAR SEASIDE CLUTTER

2016 ◽  
Vol 78 (5-7) ◽  
Author(s):  
Nor Najwa Ismail ◽  
Nur Emileen Abd Rashid ◽  
Zuhani Ismail Khan
Keyword(s):  
Statistical Analysis ◽  
Weibull Distribution ◽  
High Frequency ◽  
Goodness Of Fit ◽  
Distribution Model ◽  
Logistic Distribution ◽  
Distribution Models ◽  
Very High Frequency ◽  
Forward Scatter ◽  
Scatter Radar

The statistical analysis for Terengganu, Malaysia seaside clutter is presented in this paper. The measured clutter data were collected using a prototype of forward scatter radar (FSR) micro-sensor network with very high frequency (VHF) and ultra-high frequency (UHF) bands. Four categories of clutter strength were recorded during the measurements, which are low, medium, strong and very strong clutter. The classes were divided according to the wind speed occurred during the measurements period. The analysis is to determine the best-fit distribution model for the measured clutter data. Four types of distribution models are used in this analysis, which are Weibull, Gamma, Log-Logistic and Log-Normal distribution. One of the goodness of fit (GOF) tests called root mean square error (RMSE) is used to prove which distribution is a better fit to the probability distribution of the measured clutter data. The obtained results show that for 64 MHz with all clutter level strength, Weibull distribution provides better fit and records the lowest RMSE. Weibull distribution also fits best to the clutter data for low clutter of 151 MHz. However, for the rest of clutter level strength for 151 MHz, Gamma distribution is the best-fitted model with lowest RMSE values. Log-Logistic distribution proves to be the best fitted model to all clutter level strength of clutter data for 434 MHz with smallest RMSE values.

scholarly journals Aluminum current collector for high voltage Li-ion battery. Part I: A benchmark study with statistical analysis

2021 ◽  
Vol 126 ◽  
pp. 107013
Author(s):  
Chloé Bizot ◽  
Marie-Anne Blin ◽  
Pierre Guichard ◽  
Jonathan Hamon ◽  
Vincent Fernandez ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
High Voltage ◽  
Current Collector ◽  
Li Ion Battery ◽  
Benchmark Study ◽  
Li Ion

scholarly journals Extended perfusion protocol for MS lesion quantification

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 520-530
Author(s):  
Eleftherios Kontopodis ◽  
Kostas Marias ◽  
Georgios C. Manikis ◽  
Katerina Nikiforaki ◽  
Maria Venianaki ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Magnetic Resonance ◽  
Goodness Of Fit ◽  
Accurate Determination ◽  
Acquisition Time ◽  
Minimal Extension ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Demyelinating Lesions ◽  
Mri Protocol

AbstractThis study aims to examine a time-extended dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocol and report a comparative study with three different pharmacokinetic (PK) models, for accurate determination of subtle blood–brain barrier (BBB) disruption in patients with multiple sclerosis (MS). This time-extended DCE-MRI perfusion protocol, called Snaps, was applied on 24 active demyelinating lesions of 12 MS patients. Statistical analysis was performed for both protocols through three different PK models. The Snaps protocol achieved triple the window time of perfusion observation by extending the magnetic resonance acquisition time by less than 2 min on average for all patients. In addition, the statistical analysis in terms of adj-R2 goodness of fit demonstrated that the Snaps protocol outperformed the conventional DCE-MRI protocol by detecting 49% more pixels on average. The exclusive pixels identified from the Snaps protocol lie in the low ktrans range, potentially reflecting areas with subtle BBB disruption. Finally, the extended Tofts model was found to have the highest fitting accuracy for both analyzed protocols. The previously proposed time-extended DCE protocol, called Snaps, provides additional temporal perfusion information at the expense of a minimal extension of the conventional DCE acquisition time.

RADIOCARBON IN MEXICO: FROM PROPORTIONAL COUNTERS TO AMS

Radiocarbon ◽  
2021 ◽  
pp. 1-7
Author(s):  
Corina Solís ◽  
Efraín Chávez ◽  
Arcadio Huerta ◽  
María Esther Ortiz ◽  
Alberto Alcántara ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Sample Preparation ◽  
High Voltage ◽  
Accelerator Mass Spectrometry ◽  
Science And Technology ◽  
National Council ◽  
University Of Arizona ◽  
Technological Developments ◽  
High Voltage Engineering ◽  
The University

ABSTRACT Augusto Moreno is credited with establishing the first radiocarbon (14C) laboratory in Mexico in the 1950s, however, 14C measurement with the accelerator mass spectrometry (AMS) technique was not achieved in our country until 2003. Douglas Donahue from the University of Arizona, a pioneer in using AMS for 14C dating, participated in that experiment; then, the idea of establishing a 14C AMS laboratory evolved into a feasible project. This was finally reached in 2013, thanks to the technological developments in AMS and sample preparation with automated equipment, and the backing and support of the National Autonomous University of Mexico and the National Council for Science and Technology. The Mexican AMS Laboratory, LEMA, with a compact 1 MV system from High Voltage Engineering Europa, and its sample preparation laboratories with IonPlus automated graphitization equipment, is now a reality.

scholarly journals Finsler Geometry for Two-Parameter Weibull Distribution Function

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Emrah Dokur ◽  
Salim Ceyhan ◽  
Mehmet Kurban
Keyword(s):  
Probability Density Function ◽  
Weibull Distribution ◽  
Probability Density ◽  
Density Function ◽  
Finsler Space ◽  
Finsler Geometry ◽  
Cumulative Probability ◽  
Two Dimensional ◽  
Energy Potential ◽  
Two Parameter

To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two-dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two-parameter Weibull probability density function which has shape (k) and scale (c) parameters in two-dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two-parameter Weibull probability density function, especially used for determination of wind energy potential of a region.

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