# Weibull plotting paper

In this paper, we focus on how a Q-Q plot can be augmented by intervals for all the points so that, if the population distribution is Weibull or exponential then all the points should fall inside the corresponding intervals simultaneously with probability $1-\alpha$. These simultaneous $1-\alpha$ probability…. View via Publisher.In this paper, we study three different models, each involving two Weibull distributions, to model failure data. We carry out a characterization of the plots on Weibull plotting paper (WPP). This allows one to decide on the appropriateness of a particular model formulation to model a given data set.Title: Weibull Plot Paper Author: x2x.xlear.com-2022-06-18T00:00:00+00:01 Subject: Weibull Plot Paper Keywords: weibull, plot, paper Created DateThe formula for the percent point function of the Weibull distribution is $$G(p) = (-\ln(1 - p))^{1/\gamma} \hspace{.3in} 0 \le p 1; \gamma > 0$$ The following is the plot of the Weibull percent point function with the same values of γ as the pdf plots above. Hazard Function The formula for the hazard function of the Weibull distribution isDownload Free Probability Plotting Papers to Create Your Own Graphs of Probability for the Weibull, Lognormal, Normal and Exponential Distributions Probability Plotting Papers This page provides free probability plotting papers for you to download in *.pdf format. The papers were created by ReliaSoft with the Weibull++ software.The Weibull distributions is immensely popular in reliability, because it includes distributions of decreasing, constant, and increasing failure rates. The main advantage of Weibull analysis is that its able to detect accurate failure rates with extremely small samples. The bathtub curve is widely used in reliability engineering.The Weibull distribution is very popular among engineers. One reason for this is that the Weibull cdf has a closed form which is not the case for the normal cdf Φ(x). Another reason for the popularity of the Weibull distribution among engineers may be that Weibull’s most famous paper, originally submitted to a statistics journal This video explains step-by-step procedure for probability plotting of failure data. Probability plotting is a technique used to determine whether given data...It is observed that the tensile strength B. Statistical Analysis of Tensile Data values of less than 750 MPa are highly reliable. For a more Figure 4 shows the two-parameter Weibull plot of ultimate certain assessment, let us consider 0.95 and 0.9 reliability tensile strength data. short 6 minute step by step tutorial for using excel to determine weibull modulus for test data.This page provides free probability plotting papers for you to download in *.pdf format. The papers were created by ReliaSoft with the Weibull++ software. In addition, this page provides access to the rank tables required for probability plotting. Probability Plotting Papers: Select the type of probability paper from the list below. kdist: K-Distribution and Weibull Paper. Density, distribution function, quantile function and random generation for the K-distribution. A plotting function that plots data on Weibull paper and another function to draw additional lines. See results from package in T Lamont-Smith (2018), submitted J. R. Stat. Soc.This page provides free probability plotting papers for you to download in *.pdf format. The papers were created by ReliaSoft with the Weibull++ software. In addition, this page provides access to the rank tables required for probability plotting. Probability Plotting Papers: Select the type of probability paper from the list below. The line at 6.6 metres per second marks the median wind speed. 50% of the time the wind is lower than the median and 50% of the time it is stronger than the median. The shape of the Weibull Distribution depends on a parameter called (helpfully) Shape. In Northern Europe and most other locations around the world the value of Shape is ... Years ago Reliability engineers used specially printed log-log (probability plot) graph paper to manually plot the failure ages and fit a regression line by eye, before reading off the parameters ...Weibull Analysis The Weibull distribution is one of the most commonly used distributions in Reliability Engineering because of the many shapes it attains for various values of β. Weibull analysis continues to gain in popularity for reliability work, particularly in the area of mechanical reliability, due to its inherent versatility. The ... Weibull Probability Plotting Paper 1, 2, 3 and 4 Cycles . Download (or view and print) Weibull paper in *.pdf format 1, 2, 3 and 4 cycle papers are in the same *.pdf document. Lognormal Probability Plotting Paper 1, 2, 3 and 4 Cycles. Download (or view and print) Lognormal paper in *.pdf format 1, 2, 3 and 4 cycle papers are in the same *.pdf ...A central component of Weibull analysis is the generation of Weibull plots. Relyence Weibull offers visually impactful plotting capabilities. You can select from a variety of plot types, and include confidence bounds if you prefer. You can customize the plots to suit your needs and generate output reports in a variety of formats.The model can be considered as another useful 3-parameter generalization of the Weibull distribution. An advantage of the model is that the model parameters can be estimated easily based on a Weibull probability paper (WPP) plot that serves as a tool for model identification. Model characterization based on the WPP plot is studied.Dec 22, 2015 · Contents. The mixed Weibull distribution (also known as a multimodal Weibull) is used to model data that do not fall on a straight line on a Weibull probability plot. Data of this type, particularly if the data points follow an S-shape on the probability plot, may be indicative of more than one failure mode at work in the population of failure ... Figure 2 - Chart of Weibull distribution by beta parameter. Worksheet Functions. Excel Function: Excel provides the following function in support of the Weibull distribution where α and β are the parameters in Definition 1. WEIBULL.DIST(x, β, α, cum) = the pdf of the Weibull distribution f(x) when cum = FALSE and the cdf F(x) when cum = TRUEI am trying right now to recreate this graph of the exponential probability paper in python.. In order to do it, I have to linearize the CDF function as: x = a*g(Fx(x)) + b and then plot x vs g(Fx(x)).. This image shows the parameters for different distributionsThe Weibull distribution is very popular among engineers. One reason for this is that the Weibull cdf has a closed form which is not the case for the normal cdf Φ(x). Another reason for the popularity of the Weibull distribution among engineers may be that Weibull's most famous paper, originally submitted to a statistics journalthrough the origin. If the Weibull model is appropriate, the LLS curve should be approximately linear. Since there are more than one stratum, the LLS plot may also be used to check the proportional hazards model assumption. Under this assumption, the LLS curves should be approximately parallel across strata. Get Free Weibull Plot Paper equipment reliability data for risk-based decisions. Focusing on the process industries, it provides the protocol and techniques to collect and organize high quality plant performance, maintenance, and repair data from your ownMany types of Weibull plotting paper have scales that allow one to read the slope of the line directly, rather than having to calculate it based on "rise over run." By drawing a line parallel to the best-fit model line through the slope scale, we can see that the estimate for for this data set is approximately 1.4. Weibull Analysis The Weibull distribution is one of the most commonly used distributions in Reliability Engineering because of the many shapes it attains for various values of β. Weibull analysis continues to gain in popularity for reliability work, particularly in the area of mechanical reliability, due to its inherent versatility. The ... Section 5 outlines the steps to incorporate the failure times of the operational level into the ALT analysis. Section 6 presents the conclusions. Finally, the paper ends with the references in section 7. 2. Problem statement. Since a Weibull demonstration test plan is performed without failures, the Weibull parameters b and h could not be ... A reduced new modiﬁed Weibull distribution SaadJ.Almalki SchoolofMathematics,UniversityofManchester,ManchesterM139PL,UK Abstract In this paper, we propose a reduced version of the new modiﬁed Weibull (NMW) distribution due to Almalki and Yuan  in order to avoid some estimation problems. The number of parametersin the NMW distribution is ... In this paper, we shall formulate a quantile regression model considering a parametrization of the unit-Weibull distribution in terms of the τth quantile. By reparameterizing the unit-Weibull distribution in terms of its quantile function, one gets the interpretation of its location parameter as being the τ th quantile of the distribution. The Weibull CDF plot is on a log-log set of scales. The horizontal axis is time (could be cycles, operating or calendar time, etc.). The vertical access is the probability of failure, from near zero to 1, often we use 0.01 to 0.99 indicating a 1% to 99% chance of failure. ... Actually, "Weibull paper" uses a log transformation for time and ...Assuming that X is a random variable which has a cumulative distribution function F x (x). The probability that X is less than equal to a given event x p is given as: F x (x) = P (X≤x p) = p. The probability that this event will be exceeded is then equal to 1-p and the percent exceedance is denoted as 100 (1-p).Define the frequency curve plotting points: Point 1 = ẍ - s @ non-exceedance probability = 0.1587 Point 2 = ẍ + s @ non-exceedance probability = 0.8413 4. Note that 0.8413 and 0.1587 represent the probabilities that the an observation is 1 SD away (either side, or z =1 and z =-1) from the mean of a standard normal distribution.Weibull plotting position. The Weibull plotting position for the r th ranked (from largest to smallest) datum from a sample of size n is the quotient. It is recommended for use when the form of the underlying distribution is unknown and when unbiased exceedance probabilities are desired. See plotting position, probability paper.Weibull's Derivation n n − = − P P 1 (1 ) x x Let's define a cdf for each link meaning the link will fail at a load X less than or equal to x as P(X≤x)=F(x) Call P n the probability that a chain will fail under a load of x If the chain does not fail, it's because all n links did not fail If the n link strengths are probabilistically independent Weibull, W., 1951,"A Statistical ...This Weibull plotting is facilitated by Weibull probability paper with a log 10-transformed abscissa with untransformed labels and a transformed ordinate scale given by w(p) = log 10 [−log e (1−p)] with labels in terms of p. Sometimes this scale is labeled in percent ( i.e., in terms of 100p%). R-Squared is also known as the coefficient of determination. To estimate the parameters of the Weibull distribution using probability plotting, follow these steps: Enter the data using one of the data entry grids, or connect to a database. Select the "Parameter Estimation" Select "Weibull" Select "Probability Plot"To open a PDF file in your browser, click the filename. Download (or view and print) Weibull paper in *.pdf format 1, 2, 3 and 4 cycle papers are in the same *.pdf document. Lognormal Probability Plotting Paper 1, 2, 3 and 4 Cycles. weibull probability plot › Verified 1 days ago › Url: weibull.com Go Now › Get more: Weibull probability ... a parametric approach (Weibull or lognormal estimation). In the rest of this chapter, when we refer to survival analysis, you can freely substitute ‘reliability’ for ‘survival.’ The two terms refer to the same type of analysis. We will give a brief introduction to the subject in this section. For a complete account of survival analysis, we Weibull plot. The fit of a Weibull distribution to data can be visually assessed using a Weibull plot. The Weibull plot is a plot of the empirical cumulative distribution function ^ of data on special axes in a type of Q-Q plot. The axes are ? (? (^ ())) versus ? (). The reason for this change of variables is the cumulative distributionWeibull plotting position. The Weibull plotting position for the r th ranked (from largest to smallest) datum from a sample of size n is the quotient. It is recommended for use when the form of the underlying distribution is unknown and when unbiased exceedance probabilities are desired. See plotting position, probability paper.Years ago Reliability engineers used specially printed log-log (probability plot) graph paper to manually plot the failure ages and fit a regression line by eye, before reading off the parameters ...It is observed that the tensile strength B. Statistical Analysis of Tensile Data values of less than 750 MPa are highly reliable. For a more Figure 4 shows the two-parameter Weibull plot of ultimate certain assessment, let us consider 0.95 and 0.9 reliability tensile strength data. Weibull analysis of tensile strength data is routinely performed to determine the quality of optical fiber. A typical Weibull analysis includes setting up an experiment, testing the samples, plotting and interpreting the data, and performing a statistical analysis. One typical plot that is often included in the analysis is the Weibull probability plot in which the data are plotted as points on ...Define the frequency curve plotting points: Point 1 = ẍ - s @ non-exceedance probability = 0.1587 Point 2 = ẍ + s @ non-exceedance probability = 0.8413 4. Note that 0.8413 and 0.1587 represent the probabilities that the an observation is 1 SD away (either side, or z =1 and z =-1) from the mean of a standard normal distribution.Weibull plot. The fit of a Weibull distribution to data can be visually assessed using a Weibull plot. The Weibull plot is a plot of the empirical cumulative distribution function ^ of data on special axes in a type of Q-Q plot. The axes are ? (? (^ ())) versus ? (). The reason for this change of variables is the cumulative distributionWeibull Analysis The Weibull distribution is one of the most commonly used distributions in Reliability Engineering because of the many shapes it attains for various values of β. Weibull analysis continues to gain in popularity for reliability work, particularly in the area of mechanical reliability, due to its inherent versatility. The ... Weibull plot. The fit of a Weibull distribution to data can be visually assessed using a Weibull plot. The Weibull plot is a plot of the empirical cumulative distribution function ^ of data on special axes in a type of Q-Q plot. The axes are ? (? (^ ())) versus ? (). The reason for this change of variables is the cumulative distributionThe half-normal plot with simulated envelope for the Cox-Snell residuals - risk management cost effectiveness data. Table 7. ... In the paper herein, the unit-Weibull distribution was considered as an alternative to the Kumaraswamy distribution. For this purpose, the proposed model was reparameterized in terms of its quantiles. ...Figure 2 - Chart of Weibull distribution by beta parameter. Worksheet Functions. Excel Function: Excel provides the following function in support of the Weibull distribution where α and β are the parameters in Definition 1. WEIBULL.DIST(x, β, α, cum) = the pdf of the Weibull distribution f(x) when cum = FALSE and the cdf F(x) when cum = TRUEthe weibull plot is inspected to determine how well the failure data fit a straight line. sometimes the failure points do not fall along a straight line on the weibull plot, and modification of the simple weibull approach is required. the data are trying to tell us something in these cases. weibull illustrated this concept in his 1951 paper. …Weibull Plot 4/12/2014Webinar for ASQ Reliability Division 9 Rectification of Weibull distribution If we plot the right hand side vs. log failure time, then we have a straight line The slope is the shape parameter The intercept at t=1 is Characteristic life When the right hand side equals to 0, t=characteristic life F(t)=1-1/e=0.63 At the ...Figure 1 - Fitting a Weibull distribution via regression. First, we sort the data (e.g. by using the Real Statistics array formula =QSORT (B4:B15)) in column C. Now the x values in the regression are the values of LN (x), i.e. the values in column D. To get the y values, first, we calculate the estimated values of F(x) by placing the formula ...Hi, I want to create Weibull paper in Excel. The problem is the labelling at the Y-axis. I want to label probabilities (between 0.1 and 99.9%), but want to plot the transformed logaritmic data; calculated out of the probability via ln(ln(1/(1-p))) X P (probabiliy, label) Y (transformed data; to2.2 Weibull Probability Plotting A distribution's probability plotting paper is constructed by linear the cumulative density function (CDF) or unreliability function of the distribution. Once this has occurred, the scales for the x- and y-axis of the distribution's plotting paper can be constructed. Generates a probability plot on Weibull scaled probability paper so that the CDF of the distribution appears linear. This function can be used to show Weibull_2P or Weibull_3P distributions. Parameters: failures ( array, list) - The failure data. Must have at least 2 elements. right_censored ( array, list, optional) - The right censored data.Weibull analysis is performed by first defining a data set, or a set of data points that represent your life data. This data can be in many forms, from a simple list of failure times, to information that includes quantities, failures, operating intervals, and more. The data is then evaluated to determine a best fit distribution, or the curve ...Title: Weibull Plot Paper Author: x2x.xlear.com-2022-06-18T00:00:00+00:01 Subject: Weibull Plot Paper Keywords: weibull, plot, paper Created DateThe Weibull distribution is very popular among engineers. One reason for this is that the Weibull cdf has a closed form which is not the case for the normal cdf Φ(x). Another reason for the popularity of the Weibull distribution among engineers may be that Weibull's most famous paper, originally submitted to a statistics journalAbout Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features Press Copyright Contact us Creators ...A central component of Weibull analysis is the generation of Weibull plots. Relyence Weibull offers visually impactful plotting capabilities. You can select from a variety of plot types, and include confidence bounds if you prefer. You can customize the plots to suit your needs and generate output reports in a variety of formats. Many types of Weibull plotting paper have scales that allow one to read the slope of the line directly, rather than having to calculate it based on "rise over run." By drawing a line parallel to the best-fit model line through the slope scale, we can see that the estimate for for this data set is approximately 1.4. this weibull plotting is facilitated by weibull probability paper with a log10-transformed abscissawith untransformed labels and a transformed ordinate scale given byw(p) = log10[−loge(1−p)]with labels in terms ofp. sometimes this scale is labeled in percent ( i.e., in terms of 100p%).three blank specimens of such weibull probability paper are …short 6 minute step by step tutorial for using excel to determine weibull modulus for test data.Title: Weibull Plot Paper Author: hex.arista.com-2022-06-15T00:00:00+00:01 Subject: Weibull Plot Paper Keywords: weibull, plot, paper Created DateTitle: Lognormal Probability Plotting Paper, Generated by ReliaSoft's Weibull++ Software Author: ReliaSoft Corporation Created Date: Thursday, December 09, 1999 12:51:08 PM1.1 The Two-Parameter Weibull Distribution There are many applications for the Weibull distribution in statistics. Although it was rst identi ed by Fr echet in 1927, it is named after Waalobi Weibull and is a cousin to both the Fr echet and Gumbel distributions. Waalobi Weibull was the rst to promote the usefulnessWeibull plotting position. The Weibull plotting position for the r th ranked (from largest to smallest) datum from a sample of size n is the quotient. It is recommended for use when the form of the underlying distribution is unknown and when unbiased exceedance probabilities are desired. See plotting position, probability paper.The Weibull distribution is defined by three parameters: shape, scale, and threshold. The shape parameter refers to the shape of the Weibull curve: 3 approximates a normal curve, while a low value like the 1.69 in the graph above produces a right-skewed curve. A high shape value for shape, like 10, will result in a left-skewed Weibull curve. To open a PDF file in your browser, click the filename. Download (or view and print) Weibull paper in *.pdf format 1, 2, 3 and 4 cycle papers are in the same *.pdf document. Lognormal Probability Plotting Paper 1, 2, 3 and 4 Cycles. weibull probability plot › Verified 1 days ago › Url: weibull.com Go Now › Get more: Weibull probability ... Weibull's Derivation n n − = − P P 1 (1 ) x x Let's define a cdf for each link meaning the link will fail at a load X less than or equal to x as P(X≤x)=F(x) Call P n the probability that a chain will fail under a load of x If the chain does not fail, it's because all n links did not fail If the n link strengths are probabilistically independent Weibull, W., 1951,"A Statistical ...Weibull analysis of tensile strength data is routinely performed to determine the quality of optical fiber. A typical Weibull analysis includes setting up an experiment, testing the samples, plotting and interpreting the data, and performing a statistical analysis. One typical plot that is often included in the analysis is the Weibull probability plot in which the data are plotted as points on ...A plot of y versus x is called the Weibull probability plot (WPP). The data are ranked (i.e., rearranged so the earliest failure or suspension is listed first and the oldest failure or suspension is last), plotted on Weibull probability paper (WPP). One of the main tasks when plotting WPP is calculating the y-values that correspond F (t) values.in this paper. The rest of the paper is organized as follows. In Section II, we review the related work on differential privacy and privacy-preserving survival analysis. In Section III, we for-mally introduce the parametric model with Weibull distribution and derive the system of equations used to estimate Weibull’s parameters. To open a PDF file in your browser, click the filename. Download (or view and print) Weibull paper in *.pdf format 1, 2, 3 and 4 cycle papers are in the same *.pdf document. Lognormal Probability Plotting Paper 1, 2, 3 and 4 Cycles. weibull probability plot › Verified 1 days ago › Url: weibull.com Go Now › Get more: Weibull probability ... plot the points on Weibull paper, approximate a line, determine the slope and characteristic life; maximum likelihood estimate (MLE) In general, if only a small number of data points are available, then the approximation using Weibull paper or its equivalent will generate good results. If there is a relatively large body of data available, then ...In this paper, we shall formulate a quantile regression model considering a parametrization of the unit-Weibull distribution in terms of the τth quantile. By reparameterizing the unit-Weibull distribution in terms of its quantile function, one gets the interpretation of its location parameter as being the τ th quantile of the distribution. Exponential Probability Plotting Paper Weibull.com is a service of ReliaSoft Corporation, www.ReliaSoft.com Reliability, R(t) Title: Exponential Probability Plotting Paper, Generated by ReliaSoft's Weibull++ Software Author: ReliaSoft Corporation Created Date:This image is what I need to graph, it is called "Weibull probability plotting paper" Is there a way in ggplot2 or within the survival package (or anything other that base R graphics) to create this plot? From there, I can overlay the points. Please keep in mind the graphics I create in the end will need to be compatible with Shiny. Thank you.Hi, I want to create Weibull paper in Excel. The problem is the labelling at the Y-axis. I want to label probabilities (between 0.1 and 99.9%), but want to plot the transformed logaritmic data; calculated out of the probability via ln(ln(1/(1-p))) X P (probabiliy, label) Y (transformed data; toThe model can be considered as another useful 3-parameter generalization of the Weibull distribution. An advantage of the model is that the model parameters can be estimated easily based on a Weibull probability paper (WPP) plot that serves as a tool for model identification. Model characterization based on the WPP plot is studied.The standard Weibull model with Eta and Beta parameters, also known as the Extreme Value Type III Lower distribution. Addition of a t0 (time shift) parameter to the standard Eta and Beta parameters to account for a failure free period (positive t0) or prior deterioration (negative t0).Download Free Probability Plotting Papers to Create Your Own Graphs of Probability for the Weibull, Lognormal, Normal and Exponential Distributions Probability Plotting Papers This page provides free probability plotting papers for you to download in *.pdf format. The papers were created by ReliaSoft with the Weibull++ software.Title: Weibull Plot Paper Author: x2x.xlear.com-2022-06-18T00:00:00+00:01 Subject: Weibull Plot Paper Keywords: weibull, plot, paper Created DateThe Weibull distribution is defined by three parameters: shape, scale, and threshold. The shape parameter refers to the shape of the Weibull curve: 3 approximates a normal curve, while a low value like the 1.69 in the graph above produces a right-skewed curve. A high shape value for shape, like 10, will result in a left-skewed Weibull curve. Weibull plotting paper. Mathpages - Weibull Analysis; Using Excel for Weibull Analysis This article from the Quality Digest describes how to use MS Excel to analyse lifetest data with the Weibull statistical distribution. Although Excel doesn't have an inverse Weibull function, this article shows how to use Excel to solve for critical values ... Many types of Weibull plotting paper have scales that allow one to read the slope of the line directly, rather than having to calculate it based on "rise over run." By drawing a line parallel to the best-fit model line through the slope scale, we can see that the estimate for for this data set is approximately 1.4.Weibull Plot Purpose: Graphical Check To See If Data Come From a Population That Would Be Fit by a Weibull Distribution The Weibull plot ( Nelson 1982 ) is a graphical technique for determining if a data set comes from a population that would logically be fit by a 2-parameter Weibull distribution (the location is assumed to be zero).This image is what I need to graph, it is called "Weibull probability plotting paper" Is there a way in ggplot2 or within the survival package (or anything other that base R graphics) to create this plot? From there, I can overlay the points. Please keep in mind the graphics I create in the end will need to be compatible with Shiny. Thank you.Python - Weibull Minimum Distribution in Statistics. scipy.stats.weibull_min () is a Weibull minimum continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution.Assuming that X is a random variable which has a cumulative distribution function F x (x). The probability that X is less than equal to a given event x p is given as: F x (x) = P (X≤x p) = p. The probability that this event will be exceeded is then equal to 1-p and the percent exceedance is denoted as 100 (1-p).It is observed that the tensile strength B. Statistical Analysis of Tensile Data values of less than 750 MPa are highly reliable. For a more Figure 4 shows the two-parameter Weibull plot of ultimate certain assessment, let us consider 0.95 and 0.9 reliability tensile strength data. Visualisation and validation of weibull models; A new diagnostic methodology. Authors: David Nevell. Assystem. Assystem. View Profile, Wes Fulton ... Section 5 outlines the steps to incorporate the failure times of the operational level into the ALT analysis. Section 6 presents the conclusions. Finally, the paper ends with the references in section 7. 2. Problem statement. Since a Weibull demonstration test plan is performed without failures, the Weibull parameters b and h could not be ... Weibull parameter estimates are easily read o from the Weibull plot. The use of Weibull plotting is introduced rst in the context of complete samples and then ex-tended to two common forms of censoring: type I or multiple censoring and type II censoring. Two blank Weibull plotting templates are provided, one for a two cycle log 10 The Weibull plot ( Nelson 1982 ) is a graphical technique for determining if a data set comes from a population that would logically be fit by a 2-parameter Weibull distribution (the location is assumed to be zero). 2.2 Weibull Probability Plotting A distribution's probability plotting paper is constructed by linear the cumulative density function (CDF) or unreliability function of the distribution. Once this has occurred, the scales for the x- and y-axis of the distribution's plotting paper can be constructed. The line at 6.6 metres per second marks the median wind speed. 50% of the time the wind is lower than the median and 50% of the time it is stronger than the median. The shape of the Weibull Distribution depends on a parameter called (helpfully) Shape. In Northern Europe and most other locations around the world the value of Shape is ... 10l_2ttl