Ratios | Dimensionless numbers
In materials science and solid mechanics, Poisson's ratio (nu) is a measure of the Poisson effect, the deformation (expansion or contraction) of a material in directions perpendicular to the specific direction of loading. The value of Poisson's ratio is the negative of the ratio of transverse strain to axial strain. For small values of these changes, is the amount of transversal elongation divided by the amount of axial compression. Most materials have Poisson's ratio values ranging between 0.0 and 0.5. For soft materials, such as rubber, where the bulk modulus is much higher than the shear modulus, Poisson's ratio is near 0.5. For open-cell polymer foams, Poisson's ratio is near zero, since the cells tend to collapse in compression. Many typical solids have Poisson's ratios in the range of 0.2–0.3. The ratio is named after the French mathematician and physicist Siméon Poisson. (Wikipedia).
Short Introduction to the Poisson Distribution
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From playlist Statistics
Statistics: Intro to the Poisson Distribution and Probabilities on the TI-84
This video defines a Poisson distribution and then shows how to find Poisson distribution probabilities on the TI-84.
From playlist Geometric Probability Distribution
When you strain a material along one axis, you often see corresponding strain perpendicular to the load direction. A material under tension gets thinner, for example. The ratio of these two strains is defined as Poisson's ratio. Most materials are between 0.25-0.35 with some exceptions. Is
From playlist Materials Sciences 101 - Introduction to Materials Science & Engineering 2020
Statistics - 5.3 The Poisson Distribution
The Poisson distribution is used when we know a mean number of successes to expect in a given interval. We will learn what values we need to know and how to calculate the results for probabilities of exactly one value or for cumulative values. Power Point: https://bellevueuniversity-my
From playlist Applied Statistics (Entire Course)
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This video explains how to determine a Poisson distribution probability by hand using a formula. http://mathispower4u.com
From playlist Geometric Probability Distribution
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From playlist Probability Distributions
The Mean, Standard Deviation, and Variance of the Poisson Distribution
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From playlist Statistics
Probability of Exactly 15 Births using the Poisson Distribution
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From playlist Statistics
In this video I take a detailed look at Poisson's ratio, a really important material property which helps describe how a material will deform under loading. --- If you would like to support the channel, please consider becoming a Patron - https://www.patreon.com/efficientengineer. This w
From playlist Understanding Material Properties
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Tutorial worked example problem of how to convert from a stress and changes in length to Elastic modulus to Poisson's ratio to Shear modulus and eventually to a shear stress. *subscribe to help me grow this channel and comment below with a suggested new mse problem to solve*
From playlist MSE example problems tutorial
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From playlist Mathematics Research Center
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Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 If Y, K, and Nu are the values of Young’s modulus, bulk modulus, and modulus of rigidity of any material respectfully. Choose the cor
From playlist JEE (MAIN) PHYSICS MECHANICS
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This statistics video tutorial provides a basic introduction into the poisson distribution. It explains how to identify the mean with a changing time interval in order to calculate the probability of an event occurring. My Website: https://www.video-tutor.net Patreon Donations: https:/
From playlist Statistics
Relationship between the shear and axial strain is demonstrated. Lectures for Mechanics of Solids and Structures course at Olin College.
From playlist Lectures for mechanics of solids and structures
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From playlist Materialism Podcast
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From playlist Strings 2015 conference
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From playlist Lectures for mechanics of solids and structures
The Poisson is a classic distribution used in operational risk. It often fits (describes) random variables over time intervals. For example, it might try to characterize the number of low severity, high frequency (HFLS) loss events over a month or a year. It is a discrete function that con
From playlist Statistics: Distributions
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From playlist Introduction to Materials Science and Engineering Fall 2018