FEA Isoparametric Quadrilaterals Part 3: Gauss Quadrature for Integration of the Stiffness Matrix
This video continues from part 1 ( • FEA Isoparametric Quadrilaterals Part 1: J... ) and part 2 ( • FEA Isoparametric Quadrilaterals Part 2: T... ) to investigate how to integrate the stiffness matrix for linear 4-node isoparametric quadrilateral elements in finite element analysis (FEA). This video shows how Gauss quadrature can be used to transform the integration of [K] into summation of the integrand within [K] evaluated at four distinct locations called Gauss points, integration points, and/or sampling points. 0:00 Introduction and review of the elemental stiffness matrix equation 1:05 Why direct integration of the stiffness matrix would be difficult 2:02 Introduction to Gauss quadrature 3:57 Table of sampling points for Gauss quadrature (also called Gauss points or integration points) 5:14 Gauss quadrature example with one variable (1D) 6:40 Gauss quadrature example with two variables (2D) 8:45 Gauss quadrature applied to the elemental stiffness matrix equation for 4-node linear isoparametric quadrilateral 10:20 Reflection questions Suggested answers to the reflection questions 1.) The main advantage of Gauss quadrature is that it changes the integral of a polynomial into summation of that polynomial integrated at distinct locations (called Gauss points, integration points, or sampling points) 2.) Gauss quadrature works most easily on the interval between -1 and 1 although there are techniques for it to work over other interval ranges. Gauss quadrature will give the exact integral result for polynomials of order k as long as the polynomial is evaluated at a sufficient number of Gauss integration points, n. The order of the polynomial, k must be less than or equal to 2n-1 for exact representation. If less Gauss points are used, then it will give an approximate representation (this is done sometimes in FEA for reduced integration). 3.) n = 2 is sufficient in each direction for integrating the 4-node linear isoparametric element because each component of the integrand matrix equation (transpose[B]*[C]*[B]*|J|) would at most be a cubic polynomial in either xi or eta directions (k = 3 = 2n-1). 4.) The four Gauss integration points are located at: xi = -1/sqrt(3), eta = -1/sqrt(3) xi = 1/sqrt(3), eta = -1/sqrt(3) xi = 1/sqrt(3), eta = 1/sqrt(3) xi = -1/sqrt(3), eta = 1/sqrt(3)

FEA Isoparametric Quadrilaterals Part 2: The Strain-Displacement Matrix

FEA Isoparametric Quadrilaterals Part 1: Jacobian matrix and natural coordinates

45) NCB 06( ಒಂದಕ್ಕೆ ಸಮನಾದದ್ದು ಉದಾಹರಣೆಗಳಿಗೂ ಉತ್ತರಿಸಿರಿ

Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra

Why The Russian Accent Terrifies Everyone

Excelling in Calculus and Physics

Rayleigh-Ritz Method

How reading changes the way your brain works - BBC World Service

What is Jacobian? | The right way of thinking derivatives and integrals

Electrons Don't Actually Orbit Like This

The Big Picture of Linear Algebra

Deep Work Music | Focus Music for Productivity & Concentration | Ambient Study Background

FEA Isoparametric Quadrilaterals Part 4: Evaluating Stress Results

What's The Difference Between Matrices And Tensors?

The Insane Genius of a Formula 1 Gearbox

🚗 BYD : The biggest SCAM of the car industry ?

Conan O’Brien Delivers the Commencement Address | Harvard Commencement 2026

Give Me 30 min, I will make Linear Algebra Click Forever

