Lecture 1

CE 5109 Computer Aided Design and

Analysis of Structures

Chapter 1 INTRODUCTION

1 General Remarks Computers have been widely used in structural

engineering for: Structural analysis Computer-aided design and drafting (CADD) Report preparation

Typical computer usage by an engineer: Word-processing Preparation of tender documents and engineering drawings Small and intermediate computations Analysis of structures Design work Data reduction and storage Software development Email Etc.

2 Historical Development

1. In the 1940s and 1950s, structural engineers were confronted with highly statically indeterminate systems: high-rise tall buildings and large aircraft structures.

2. In 1940, Hardy Cross proposed the moment distribution method, based on the relaxation concept, to solve large systems of indeterminate frame structures.

3. Since the 1950s, digital computers have been rapidly developed.

4. In 1954, Professor J. Argyris and S. Kelsey formulated the matrix method of structural analysis, which effectively utilizes digital computers.

5. In the 1950s, a group of structural engineers Turner, Clough, Martin and Topp at the Boeing Company also proposed the matrix formulation for structural analysis of airplanes.

6. Subsequently, a more general computer method—the finite element method—was developed for conducting structural analysis of a wide variety of structures.

The methods of structural analysis have been dramatically revolutionalized by the advance in digital computers and the demand in stringent design requirements of airplanes. A number of significant milestones are:

2 Historical Development

Advantages of Matrix Formulation: Convenient for computer programming. It is difficult to analyze a complicated structure by hand calculation

unless a great deal of simplification is made.

3 Computer Hardware and Software

Computers have evolved tremendously. The basic computer hardware has gone through several phase changes, from vacuum tubes to transistors, and then silicon chips. There are basically three classes of computers:

Personal Computers 486: 25-50 MHz 586/Pentium: 100-500 MHz Pentium 4: 3.6 GHz, Dual Core processors, Core i3, i5 and i7, First, second, third and fourth generation is etc.


Workstations (some obsolete now) Sun SPARC 20 HP Workstations Appollo DEC Stations IBM Risk 6000 DELL Systems Apple MAC systems etc.


Supercomputers Vector machines: Cray 90, IBM, Convex Parallel machines: CM-5, Intel Paragon, nCube, etc.

Current trend: PC clusters (parallel processing): Cluster: group of (e.g. 8) PCs connected by a very fast

network Can outperform workstations or supercomputers of equivalent

price

Operating systems: Oracle: Workstation, PC Linux: Workstation, PC MS Windows : Workstation, PC


Mathematical Software

Excel (small-scale matrix work / optimization, data storage & pre-processing, etc.)

MATLAB, MathCAD (general-purpose)

Computer Algebra Systems (CAS): Mathematica, Maple, Derive, etc. Handles numeric as well as symbolic work (e.g. matrix

inversion) Small-to-medium scale work (inversion of 100100 numerical

matrix on Mathematica: ~ 1 min.)

Many numerical schemes built-in (e.g. LUDecomposition, RowReduce)


Specialized Structural Analysis Software: ABAQUS, ADINA, ANSYS, ETABS, NASTRAN, SAP2000, etc.

SAP2000 Integrated software for structural analysis & design

(e.g. for bridges) Will be discussed in this class

ETABS Analysis, design and drafting of building systems Will be discussed in this class


ANSYS (Engineering analysis system) Special features of the package

Linear time history Nonlinear time history Sub-structuring Nonlinear transient dynamic

Types of analysis Linear elastic analysis Materially-nonlinear analysis Large deformation analysis Fracture mechanics

Element library Bar, beam, pipe, elbow and tee element Two-dimensional membrane element Three-dimensional solid element Two-dimensional bending element Shell element

4 node shell 8 node curved shell 16 node thick shell


NASTRAN – NASA (National Aerospace and Space Administration) Structural analysis Program Special features of the package

Direct and modal complex eigenvalue analysis Direct and modal transient analysis Aeroelastic response Aeroelastic flutter Sparse matrix solutions Generalized dynamic reduction Multi-level super-elements Automatic re-sequencing Automatic singularity suppression

Types of analysis Linear elastic analysis Material non-linearity and geometric non-linearity Complex eigenvalue analysis Response spectral analysis

Element library Truss and beam elements Two-dimensional inplane and bending elements Three-dimensional solid element Constraint elements (rigid and interpolating) Curved shell element


ADINA – MIT (Automatic Dynamic Incremental Non-linear Analysis) Special features of the package

Time integration Sub-structuring Solution to frequencies and mode shapes Mode superposition

Types of analysis Linear elastic analysis Materially-nonlinear analysis Large deformation formulation

Element library Truss and cable Two-dimensional solid and fluid element Three-dimensional solid and fluid element Two-node beam element Isoparametric beam element Three-node plate/shell element Isoparametric shell element


Computer Aided Drafting Systems: AutoCAD, MicroStation, I-DEAS (3-D modelling & FEM),

etc.

Application Areas: Design of tall building and bridges Offshore platforms Aircraft and jet engine design Nuclear power plant design etc.

4 Computer Methods vs. Classical Methods

Both the computer and classical methods are established from the fundamental principles in mechanics, i.e.

Force equilibrium or energy balance of a structure. Compatibility in deformation. Consistent with support conditions.

The classical methods may consist of the following:

• Slope-deflection method• Moment distribution• Virtual displacements• Unit load method• Castigliano’s theorem• Energy theorems, etc.

The computer methods are actually formulated on the basis of the energy principle with the following characteristics:• The least amount of

approximations is involved.• For complex structures, the

method involves the solution of large systems of linear equations.

• The method gives multiple results, e.g. deflections of all joints, member forces.

• Computer does the routine calculations.

4 Computer Methods vs. Classical Methods

Scope of the Course: Structures: beam, continuous beam, plane truss, space

truss, plane frame, space frame, grid, etc. Materials: linearly elastic Deformation: small Analysis: static and dynamic Support conditions: arbitrary

Expectation from the Course:1. Basic theory behind the computer methods of structural analysis

2. How to model a structure for computer analysis

3. How to form the stiffness and mass matrices by hand calculation

4. How to form the loading in matrix form

5. How to use mathematical software to assist in (1) – (4)

6. How to solve practical problems using a structural software

5 Flexibility and Stiffness Concepts

Fig. 1.1 An Elastic Spring

Fig. 1.1 An Elastic Spring

We consider a linear spring, a one-degree of freedom system, as shown in Fig. 1.1. Let the spring constant be k N/m while the spring is subjected to a force f. The corresponding displacement is designated by d.

We have the following relationship

k · d = f (1)

The physical meaning of k, the spring constant, is the amount of force required to stretch the spring by a unit displacement. The inverse relation of Eq.(1) is

d = F · f (2)

where F is called the flexibility coefficient of the spring, it is also the amount of displacement induced by a unit force.


Let the deflection and rotation of the tip be denoted by D and q, respectively. To find D and q, we may consider the force and moment applied to the beam separately.

Effects of force P:

(3)

where EI is the bending rigidity of the beam.

Effects of Moment M:

(4)

We consider next a cantilever beam subjected to a force P and a moment M at the tip as shown in Fig. 1.2.

Fig. 1.2 A Cantilever Beam Deflected by End Force and Moment

EI

PL

EI

PLPP 2

,3

23

EI

ML

EI

MLMM ,

2

2


EI

ML

EI

PLMP 23

23

EI

ML

EI

PLMP

2

2

M

P

EILEIL

EILEIL

/2/

2/3/2

23

The defection and rotation due to both P and M applied to the beam simultaneously, then, can be obtained by using the principle of superposition, i.e.

(5)and

(6)The above equations can be rearranged in the form similar to Eq.(2),

(7)We may also express the above relationship in matrix notation

D =F · F (8)


where D is the “displacement vector”; F is the “flexibility matrix” of the beam; F is the “force vector”. The inverse of Eq.(8) gives

KD = F (9)

where K = F -1 is the stiffness matrix of the beam, namely

K =

LEILEI

LEILEI

/4/6

/6/122

23

(10)

This matrix inversion can be performed efficiently on Mathematica as shown :

Note that both the flexibility and stiffness matrices are symmetric, and this property is related to Maxwell and Betti’s law, or the reciprocal theorem.

6 Symbols and NotationsIn this section, we will list the definitions of frequently used symbols and notations. Note that bold-faced letters such as D or F represent either vectors or matrices.

sNormal stress

t Shear stress

e Normal strain

g Shear strain

d Deflection

q Angle or rotation

E Young’s modulus

A Cross sectional area

I Bending moment of inertia

J Polar moment of inertia

Notations:x A position vector (or coordinate vector of a point)

k Member stiffness matrix

F Member flexibility matrix

d Joint displacements of a member

f Joint force vector of a member

K Structural stiffness matrix

D Structural nodal displacement vector

F Structural nodal force vector

B Matrix relating nodal displacements to element strains

N Matrix of shape functions

Note: In the above, notations with no overbar represent quantities defined in the “global” coordinate system, whereas (¯) indicates the quantity is defined in a “local” (or member) coordinate system. These terms will be made clear in the subsequent chapters.

Symbols:

7 Solution of Linear Equations

We consider a system of linear equations of the form

Ax = b (1)

where A is an neqneq non-singular matrix with constant coefficients, x and b are neq1 vectors with x being the unknown. Matrix formulation of structural problems often leads to a large system of such simultaneous equations. Efficient ways of solving such equations have been the major concern of numerical analysts.

Nowadays, for problems are not too large (say, a matrix of size 2020), we may simply use a spreadsheet or even a calculator to invert (1) for a direct solution x = A-1b. For example, the following Excel commands (to be entered with Ctrl-Shift-Enter) can be helpful:

• To multiply matrices and vectors: MMULT• To transpose a matrix: TRANSPOSE• To invert a matrix: MINVERSE• To obtain the determinant of a matrix: MDETERM• To retrieve the (r, c) component of a matrix M: INDEX(M,r,c)

It is a good practice to name arrays for convenient selection You may press Ctrl-* to select a matrix


An example for matrix inversion on a spreadsheet is as follows:


To tackle problems of a large size, traditionally there has been basically two different solution approaches: direct and iterative methods. The direct methods successively decouple the simultaneous equations so that the unknowns can be readily calculated. Most are some kind of variation of the Gaussian elimination method, such as the Cholesky and Gauss-Jordan methods.

Iterative methods give approximate solutions that can be improved by successive iterations. They usually consume less memory than direct methods, but the solution convergence and accuracy are difficult to control. Therefore, direct methods are most preferred.

In solving the linear system of simultaneous equations arising in structural analysis, the following special characteristics can be utilized in coding:

• The matrices are usually symmetric and positive definite (xTAx > 0 for all nonzero x).

• The matrices are often sparse (avoids multiplications by 0’s and 1’s).

8 Gaussian EliminationThe basic idea of Gauss elimination is to suitably combine the rows of Eq.(1) to transform the coefficient matrix into upper triangular form. This is called a forward reduction process. Then, the resulting equations become sufficiently uncoupled. All unknowns x can be found by back-substitution, starting from the last row. To illustrate this procedure, we consider a 4×4 matrix equation with 4 unknowns:

8 Gaussian EliminationSummary of Procedures:We considered the above simple example for illustration of the Gauss elimination procedures. In reality, the number of equations in Eq. (1) can be fairly large. Then, Gauss elimination may be used in two phases as follows.

Phase 1: Forward ReductionEq.(1) is reduced into upper triangular form

Ux = c

Where

Phase 2: Back-Substitution to determine xComputer algorithms for forward reduction and back-substitution are given in the Appendix.

9 Cholesky DecompositionFor a large system of linear equations, the Cholesky decomposition is often a

preferred and efficient direct method. We consider the equation of the formAx = b (4)

Fact: if A is symmetric and positive definite, then A can be decomposed into two parts as

A = LU (5)

where • L is a lower triangular square matrix (i.e. all 0’s above the diagonal),• U is an upper triangular square matrix (i.e all 0’s below the diagonal), and• L = UT

Substituting (5) into (4), we haveLUx = b (6)

In the above, we defineUx = y (7)

So we haveLy = b (8)

Obviously, we can efficiently solve for y from Eq.(8) using forward-substitution, then x can be readily determined from Eq.(7) using back-substitution.

9 Cholesky DecompositionThe detailed procedures for obtaining L and U are given in the Appendix.

Nowadays, such algorithms are well implemented on various mathematical software packages such as Mathematica and MatLab. You may utilize the CholeskyDecomposition command, which is built into Mathematica’s linear algebra package, as shown in the following:

AppendixI. Computer algorithm for forward reduction:

II. Computer algorithm for back-substitution:

AppendixIII. Computer algorithm for LU decomposition: