Dynamic Modeling and Simulation of Flexible Beam Finite Rotation with ANCF Method and FFR Method.
Han, Ling ; Liu, Ying ; Yang, Bin 等
Dynamic Modeling and Simulation of Flexible Beam Finite Rotation with ANCF Method and FFR Method.
1. Introduction
The earliest method discovered for dealing with flexible body
dynamic equations is the kineto-elasto-dynamic (KED) method [1-3]. This
method is based on assumptions of low speed and small displacement,
while the coupling terms of rigid-body motion and elastic motion in the
dynamic equations are neglected. The inertia characteristics of flexible
body rigid motion are loaded onto the flexible body itself in the form
of inertial forces. With the constant emergence of lightweight,
high-speed machinery, the disadvantages of the KED method have been
gradually exposed [4]. To describe the effect of elastic deformation of
the flexible body on its own large overall motion, Likins [5] proposed
the floating frame of reference (FFR). The FFR method decomposes the
configuration of the flexible body into two parts: the large overall
rigid motions of the floating coordinate system, and the elastic
deformation of the flexible body with respect to the floating coordinate
system. Although the selection of the floating coordinate system does
not affect the analysis results, the mass matrix obtained by this method
is a nonlinear function matrix of generalized coordinates, resulting in
inertial coupling between the rigid motion and elastic deformation of
the flexible body.
To simplify the mass matrix, Simo [6-9] suggested suppressing the
floating coordinate system and expressing the beam's dynamic
equations in the global coordinate system directly. In describing the
bending and shearing of the beam, Simo reserved the beam's
cross-section local coordinate system containing the cross-section angle
relative to the beam rigid configuration. Simo's approach
simplifies the expression of the kinetic energy of the beam compared to
the FFR method. The constant mass matrix can be obtained using variable
separation; however, the expressions of elastic potential energy and the
stiffness matrix become more complex.
At the end of the 20th century, Shabana and other scholars [10-14]
proposed the absolute nodal coordinate formulation (ANCF) method. This
method is similar to that proposed by Simo: the dynamic equations of the
beam are described in the global coordinate system; the cross-section
local coordinate system of the beam is used to describe bending,
shearing, and twisting; and the constant mass matrix can be obtained, so
the centrifugal force and Coriolis force are zero. The shortcomings of
these two methods are identical: the stiffness matrix becomes highly
complicated.
In contrast to Simo's method, in the ANCF approach, the
cross-section slopes at the nodes (instead of the cross-section angles)
become the beam's generalized coordinates. Therefore, the
rigid-body inertia of the beam can be described accurately, and the
constant mass matrix can be obtained without needing to perform variable
separation on generalized coordinates.
For the flexible body dynamic simulation, however, a simple mass
matrix and simple stiffness matrix cannot be obtained simultaneously.
The stiffness matrix obtained with the FFR method is relatively simple,
but the mass matrix is a nonlinear function matrix of the generalized
coordinates. If the floating coordinate system is suppressed and the
dynamic equations are expressed in the absolute coordinate system, then
the mass matrix can be reduced to a constant matrix, but the stiffness
matrix becomes highly nonlinear.
In this paper, based on assumptions of low speed and small
deformation, the ANCF method is considered a finite element
interpolation method. The interpolation matrices, mass matrix, and
stiffness matrix of the two-node beam element are extended to those of
the multi-node beam element, thereby improving calculation accuracy. The
ANCF method is combined with the FFR method (for convenience, the
combination of these two methods is termed the ANCF-FFR method). The
stiffness matrix, which does not include generalized coordinates, is
obtained along with the constant mass matrix. In the ANCF method, the
bending moment is a nonlinear function vector of the generalized
coordinates, so it is difficult to solve the system states directly. The
split-iteration method is used to solve the system states and Lagrange
multipliers. This algorithm guarantees a sufficiently accurate solution
and improves the computational efficiency substantially.
2. Modeling and solving methods for flexible beam finite rotation
To improve simulation accuracy, the expressions of the generalized
coordinates, interpolation matrices, mass matrix, stiffness matrix, and
generalized forces of the two-node beam are extended to those of the
multi-node beam. The FFR method is combined with the ANCF method to
obtain the stiffness matrix, which does not contain the generalized
coordinates. To enhance the efficiency of the simulation, the splitting
iteration method is used to solve both the static and dynamic equations.
2.1. Generalized coordinates, interpolation matrix, and mass matrix
Fig. 1 displays the schematic diagram of the global coordinate
system and the local coordinate system based on the ANCF method. For
convenience, the number of nodes on the neutral axis of the beam is set
to 4. The global coordinate system is (O, [r.sub.1], [r.sub.2],
[r.sub.3]), and the local coordinate system is ([A.sub.1], x, y, z). The
original point of the local coordinate system is located at the
beam's neutral axis endpoint, [A.sub.1]; the coordinate x is the
arc length coordinate of the beam neutral axis; [A.sub.1]y is the axis
along the height direction of the beam cross-section; and [A.sub.1]z is
the axis along the width direction of the beam cross-section.
Let the mass density of the rectangular beam be [rho], the height
of the cross-section be h, and the width of the cross-section be w. The
four nodes on the beam's neutral axis are [A.sub.1], [A.sub.2],
[A.sub.3], [A.sub.4], which divide the beam into three elements. The
length of the neutral axis of the ith element is [L.sub.i] (i=1, 2, 3).
The generalized coordinates of each node are defined as:
[mathematical expression not reproducible] (1)
r = [([r.sub.1], [r.sub.2], [r.sub.3]).sup.T], i = 1, 2, 3, 4.
The generalized coordinates of the beam can be expressed as:
[mathematical expression not reproducible] (2)
set
[mathematical expression not reproducible] (3)
and the scale functions are:
[f.sub.L](a,b,c) = 2[a.sup.3]-3[a.sup.2]+1; [f.sub.xL](a, b ,c) = a
- 2[a.sup.2]+[a.sup.3]; [f.sub.yL](a,b,c) = b - b * a; [f.sub.zL](a,b,c)
= c - c * a. (4)
[f.sub.R](a,b,c) = 3[a.sup.2]-2[a.sup.3]; [f.sub.xR] (a, b, c ) =
[a.sup.3]-[a.sup.2]; [f.sub.yR](a,b,c) = b-a; [f.sub.zR](a,b,c) = c-a.
(5)
The interpolation functions of the ith element are defined as:
S[L.sub.i] = [f.sub.L]([[xi].sub.i] ,[[eta].sub.i],[[zeta].sub.i]);
SL[x.sub.i] = [L.sub.i]*[f.sub.xL]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]); SL[y.sub.i]= h*[f.sub.yL]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]); SL[z.sub.i]= w *
[f.sub.zL]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]); i=1, 2, 3.
S[R.sub.i +1] =
[f.sub.R]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]); SR[x.sub.i +1]
=[L.sub.i]*[f.sub.xR]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]);
SR[y.sub.i +1] =h*[f.sub.yR]([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]);
R[z.sub.i +1]= w*[f.sub.zR] ([[xi].sub.i],[[eta].sub.i],[[zeta].sub.i]);
(7) i=1, 2, 3.
Define matrices:
S[L.sub.i] = [[SLi * I SLxi * I SLyi * I SLzi * I].sub.3 x 12]; i =
1, 2, 3; SRj = [[S[R.sub.i] * I SR[x.sub.i] * I SRyi * I SR[z.sub.i] *
I].sub.3 x 12]; j = 2, 3, 4; (8)
where: I is the 3-order identity matrix. The interpolation matrix
of the beam elements between two adjacent nodes [A.sub.i] , [A.sub.i +1]
can be expressed as:
[S.sub.1] = [[S[L.sub.1] S[R.sub.2] [0.sub.3x12]
[0.sub.3x12]].sub.3x48]; [S.sub.2] = [[[0.sub.3x12] S[L.sub.2]
S[R.sub.3] [0.sub.3x12]].sub.3x48]; [S.sub.3] = [[[0.sub.3x12]
[0.sub.3x12] S[L.sub.3] S[R.sub.4]].sub.3x48]; (9)
The symbol 0 means the zero matrix, and the elements of [S.sub.i]
(i= 1, 2, 3) are the functions of x, y, z. Let P be an arbitrary point
on the beam element between nodes Ai and [A.sub.i +1]. The position
vector of P in the global coordinate system can be expressed as follows:
r[|.sub.P] =Si(x,y,z)[|.sub.P]-e ; i=1, 2, 3. (10)
Then, the kinetic energy of the beam is:
[mathematical expression not reproducible] (11)
and the mass matrix of the beam is:
[mathematical expression not reproducible] (12)
where: M is a symmetric positive definite constant matrix.
2.2. Strain energy and stiffness matrix
The generalized displacement produced by elastic deformation at
point P on the ith (i=1, 2, 3) beam element can be expressed as:
u[|.sub.P]=[S.sub.i](x, y, z)[|.sub.P]-(e - [e.sub.0]); i = 1, 2,
3. (13)
where: [e.sub.0] is the generalized coordinate vector of the beam
in its rigid configuration. The deformation gradient of P is:
[mathematical expression not reproducible] (14)
where:
[mathematical expression not reproducible] (15)
Given low-speed and small-deformation assumptions and the FFR
method, the ANCF local coordinate system can be considered the float
coordinate system in the FFR method, i.e.,
[mathematical expression not reproducible] (16)
where: [[psi].sub.1], [[psi].sub.2], [[psi].sub.3] represent the
Caldan angles. The Cauchy strain tensor of point P is:
[mathematical expression not reproducible] (16)
and its vector form is:
[mathematical expression not reproducible] (17)
The elastic matrix Q is:
where: E is the elastic modulus and [mu] is the Poisson's
ratio. To eliminate the Poisson locking phenomenon, we set [mu]=0; thus,
the elastic matrix Q can be expressed as:
Q = diag(E E E E/2 E/2 E/2). (18)
The elastic strain energy of the ith beam element is:
[mathematical expression not reproducible] (19)
The elastic strain energy of the beam is:
[mathematical expression not reproducible] (19)
[mathematical expression not reproducible] (20)
Based on the assumptions of low speed and small deformation,
geometric nonlinearity is ignored, and the tangent stiffness matrix of
the beam can be approximated as:
[mathematical expression not reproducible] (21)
where: K is a symmetric positive semi-definite matrix that does not
include the generalized coordinates.
In summary, for low-speed, small-deformation problems, we can
combine the ANCF method and FFR method to obtain the constant mass
matrix and stiffness matrix, which does not include the generalized
coordinates.
2.3. Gravity
The virtual displacement by gravity at point P on the element
between two adjacent nodes [A.sub.i], [A.sub.i+1] is set to [delta]e,
and then the virtual work done by gravity at point P is:
[mathematical expression not reproducible] (22)
where: g denotes gravitational acceleration. From that, we can
obtain:
[mathematical expression not reproducible] (23)
where: V is the beam volume. The gravity on the beam element
between [A.sub.i], [A.sub.i +1] is :
[mathematical expression not reproducible] (24)
and the overall gravity of the beam is:
[mathematical expression not reproducible] (25)
2.4. Bending moment
As shown in Fig. 2, a bending moment [M.sub.B] is placed at the
cross-section of point [A.sub.2], its magnitude is M.
The virtual work of the bending moment [M.sub.B] is:
[mathematical expression not reproducible] (26)
From [15-16], the rotation angle [theta] of the cross-section
satisfies the following:
[mathematical expression not reproducible] (27)
so
[mathematical expression not reproducible] (28)
and the bending moment [M.sub.B] can be expressed as:
[mathematical expression not reproducible] (29)
2.4. Boundary conditions
Let the beam rotate anticlockwise around the O[r.sub.3] axis. A
constant bending moment vector [M.sub.B] is placed at the cross-section
of point [A.sub.2]. We set the boundary conditions in the rotating
process as follows:
a. At point [A.sub.1], the vector [mathematical expression not
reproducible] is parallel with the vector [([r.sub.1], [r.sub.2],
[r.sub.3]).sup.T.sub.A1]:
[[PI].sub.1] (t) = [e.sub.1] (t) * [e.sub.8] (t) - [e.sub.2] (t) *
[e.sub.7] (t) = 0; (30)
b. The distance between point [A.sub.1] and O(0, 0, 0) is a
constant:
[[PI].sub.2] (t) = [e.sub.1.sup.2] (t) + [e.sub.2.sup.2] (t) +
[e.sub.3.sup.2] (t) [equivalent to] [H.sup.2]; (31)
c. The coordinate [r.sub.3] of point A1 is zero:
[[PI].sub.3](t) = [e.sub.3](t) [equivalent to] 0; (32)
d. The coordinate [partial derivative][r.sub.3]/[partial
derivative]y of point A1 is zero:
[[PI].sub.4](t) = [e.sub.9](t ) [equivalent to] 0; (33)
e. Let the angle displacement function [phi](t) is a known
function. The coordinate [r.sub.1] of point [A.sub.2] satisfies:
[mathematical expression not reproducible] (34)
f. The coordinate [r.sub.2] of point [A.sub.2] satisfies:
[mathematical expression not reproducible] (35)
g. The coordinate [r.sub.3] of point A2 is zero.
[[PI].sub.7](t ) = [e.sub.15](t) [equivalent to] 0. (36)
Fig. 3 is the schematic diagram of finite rotation boundary
conditions of the beam.
2.5. Solution of initial states
The static equilibrium equation of the system at the moment of t=0
can be expressed as:
[mathematical expression not reproducible] (37)
where: [e.sub.0] is the rigid configuration of the beam, [lambda]
is the vector of the Lagrange multipliers, and [[PI].sub.e] is defined
as:
[[PI].sub.e]=([partial derivative][[PI].sub.j]/[partial
derivative][e.sub.i]) (38)
For the expression of generalized force vector:
[F.sub.Gen](e) = G + M + [[PI].sub.e] * [lambda] + K * [e.sub.0],
(39)
contains the nonlinear terms of the generalized coordinates and the
coupling terms between the generalized coordinates and Lagrange
multipliers, it is difficult to solve the system states directly. The
split-iteration algorithm is thus used to solve Equation (37).
For convenience, assume the following conventions: Let [N.sub.1]
and [N.sub.2] be two sets such that:
[N.sub.1] ={1, 2, 3, 9, 13, 14, 15}; [N.sub.1] [union] [N.sub.2]
={1, 2, 3, ..., 48}; (40) [N.sub.1] [intersection] [N.sub.2]=0.
Set matrix A = [([a.sub.ij]).sub.s x t], vector [mathematical
expression not reproducible] is the submatrix of A,
v([[OMEGA].sub.1],...,[[OMEGA].sub.l]) is the subvector of v:
[mathematical expression not reproducible] (41)
[mathematical expression not reproducible] (42)
Using the above agreements, we set:
[mathematical expression not reproducible] (43)
[mathematical expression not reproducible] (44)
[mathematical expression not reproducible] (45)
[mathematical expression not reproducible] (46)
[mathematical expression not reproducible] (47)
[mathematical expression not reproducible] (48)
[mathematical expression not reproducible] (49)
[mathematical expression not reproducible] (50)
where: [K.sup.R.sub.R] and [K.sup.D.sub.D] are invertible matrices.
Equation (37) can be expressed as:
[mathematical expression not reproducible] (51)
set
[mathematical expression not reproducible] (52)
where: [K.sup.R.sub.R1] and [K.sup.R.sub.R2] satisfy:
[K.sup.R.sub.R1] + [K.sup.R.sub.R2]= [K.sup.R.sub.R], (53)
so
[mathematical expression not reproducible] (54)
The first equation of (51) can be written as:
[mathematical expression not reproducible] (55)
and we can get the iterative algorithm:
[mathematical expression not reproducible] (56)
Equation (58) is convergent when p[epsilon][0,1). If the elastic
modulus of the material is sufficiently large, then the fast convergence
rate can be obtained when p=0.
Because the generalized force vector [F.sub.R] is a nonlinear
function vector of [e.sub.R] and [lambda], the right side of Equation
(56) should be simplified before each iteration. For small deformation
problems, expanding the right side of (56) to the 2nd-order Taylor
series at [e.sub.D]=[e.sub.Dr], [lambda]=0 before each iteration can
ensure sufficient accuracy of the solution, where [e.sub.Dr] is:
Finally, [e.sub.R] converges to the 2nd-order Taylor series of
[e.sub.D] and [lambda].:
[e.sub.R] = [e.sub.R] ([e.sub.D], [lambda]). (57)
After that, the constraint Eqs: (30)-(36) and the second equation
in (51) should be linearized to the 1st-order Taylor series at
[e.sub.D]=[e.sub.Dr], [lambda]=0, and combined with Equation (57),
[e.sub.R], [e.sub.D] and [lambda] can be solved quickly.
2.6. Solution of dynamic equations
The dynamic equations of the beam can be expressed as:
[mathematical expression not reproducible] (58)
Let the damping matrix C = 0, and Equation (58) can be solved with
the Newmark method:
[mathematical expression not reproducible] (59)
[mathematical expression not reproducible] (60)
[mathematical expression not reproducible] (61)
where: [beta] =0.25, [gamma]=0.5. After rearranging Eqs. (59)-(61),
we can get:
[mathematical expression not reproducible] (62)
Eq. (62) can be solved using the method described in Section 2.6.
3. Numerical example
Set the length of the rectangular section beam as 7.791m. The
position of each node on the beam is shown in Figure 3.the width of the
cross-section as w=0.1m, the height of the cross-section as h=0.1m, the
elastic modulus as E=2.1 x [10.sup.11]Pa, the mass density as
[rho]=7850kg/[m.sup.3], and Poisson's ratio as [mu]=03. The
boundary conditions are described in Section 2.5, and O[A.sub.1]
satisfies the following:
||O[A.sub.1]|| [equivalent to] H= 0.295m. (63)
The lump mass m is fixed at the endpoint of the beam. The constant
bending moment [M.sub.B] is loaded at the cross-section of node
[A.sub.2], and:
||[M.sub.B]|| = 1000Nm. (64)
The beam angular displacement function[phi](t) satisfies:
[mathematical expression not reproducible] (65)
Figs. 4 and 5 denote the static deflection of the end-point of the
neutral axis of the beam obtained by the ANCF-FFR method and ABAQUS
simulation when the lump mass m = 0 kg and m = 50 kg, respectively. The
angles between the beam rigid configuration and the O[r.sub.1] axis are
set at 0 degrees, 15 degrees, 30 degrees, 45 degrees, 60 degrees,
respectively. When using the ANCF-FFR method, the numbers of nodes on
the neutral axis of the beam are 4, 10, 16, 22, and 28, respectively. In
the ABAQUS software, the beam model is divided into 4192 2nd-order
hexahedral elements. The charts and tables indicate that when the number
of nodes on the neutral axis of the beam is small, the results obtained
by the ANCF-FFR are quite different than those in the ABAQUS simulation.
As the number of nodes increases, the ANCF-FFR results tend to be
consistent with those of ABAQUS. When the number of nodes in ANCF
reaches 28, the relative error of the two methods is less than 1%, a
satisfactorily accurate proportion for engineering machinery such as
cranes and aerial work platforms.
Let the initial state of the beam be the horizontal static
equilibrium state. Figs. 6 and 11 display the dynamic deflections of the
beam during the starting stage, luffing stage, braking stage, and
steady-state vibrating stage obtained by the ANCF-FFR method and ABAQUS
software when the lump mass m = 0 kg and m = 50 kg, respectively. Figs.
7-10 and Figs. 12-15 are the local charts of every stage when m = 0 kg
and m = 50 kg, respectively. From the starting stage to the steady-state
vibrating stage after braking, the results of the 4-node beam clearly
deviate from other results. The results of the 10-node beam agree well
with the ABAQUS simulation results during the starting stage, but
subsequent phase errors increase significantly over time during the
luffing stage and the steady--state vibrating stage. The 16-node results
show good pre-braking performance. In the steady-state vibrating stage,
however, the phase errors between the 16-node results and the ABAQUS
results are slightly larger. The 22-node and 28-node results are almost
completely aligned with the ABAQUS simulation results. Of course, an
increase in accuracy requires an increase in computing time.
4. Conclusions
1. Based on the assumptions of low speed and small deformation, the
constant mass matrix and stiffness matrix without generalized
coordinates of the multi-node beam are obtained by combining the ANCF
and FFR methods; the calculation process is simplified, and the solution
accuracy is improved.
2. By using the split-iteration method, the generalized coordinates
not included in the constraint equations are iteratively expanded as a
2nd-order Taylor series of the Lagrange multipliers and the generalized
coordinates contained in the constraint equations, and the constraint
equations themselves, are linearized to a 1st-order Taylor series at the
rigid configuration of the generalized coordinates, after which the
system states and Lagrange multipliers can be solved quickly. The
simulation results demonstrate that for small-deformation problems, the
low-order Taylor approximation of the generalized displacement at the
rigid configuration can significantly improve the solution speed and
ensure sufficient solution accuracy.
Acknowledgements
The financial supports from the Natural Science Foundation of
Jiangsu Province, China (Grant No. BK20161522), Six Talent Peaks Project
in Jiangsu Province, China (Grant No. JXQC-023), the State Laboratory of
Advanced Design and Manufacturing for Vehicle Body (Grant No. 31415008)
and Chinese Postdoctoral Science Foundation (Grant No. 2015M572243).
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Ling HAN (*), Ying LIU (**), Bin YANG (***), Yueqin ZHANG (****)
(*) Nanjing Forestry University, Nanjing 210037, China, E-mail:
[email protected]
(**) Nanjing Forestry University, Nanjing 210037, China, E-mail:
[email protected]
(***) Nanjing Institute of Technology, Nanjing, 211167, China,
Email:
[email protected]
(****) Nanjing University of Aeronautics and Astronautics, Nanjing,
210016, E-mail:
[email protected]
http://dx.doi.org/10.5755/j01.mech.24.5.20358
Received May 01, 2018
Accepted October 18, 2018
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