Realistic material damage simulation using real-time Finite Element Analysis

Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2009

2009 Paper No. 9409 Page 1 of 9

Realistic material damage simulation using real-time Finite Element Analysis

Steven L. Griffith

Objective Interface Systems, Inc

Herndon, Virginia

[email protected]

ABSTRACT

The realistic modeling of material damage is a key component in the development of high fidelity virtual simulations.

Properly simulated battle damage provides invaluable feedback to the simulation user and produces emergent

scenarios and behaviors that more precisely reflect the real world. However, producing simulations that depict

objects that realistically deform and break as if they were made from real-world materials is labor-intensive and

expensive. Simulation developers have traditionally relied heavily on art swaps, or real-time substitutions of art

assets, to model the deformation and fracture of simulation objects; often with disappointing results. Even when

combined with rigid body physics systems, art swapping lacks the level of detail required to capture the complex

interaction of battle damage and the effect on the battlespace and the warfighter.

This paper will describe the use of an advanced, physics-based method to model and simulate material damage. This

simulation accounts for the material properties of an object (density, toughness, plasticity, dampening, etc.) and the

forces acting on the object. These variables are processed in real-time using advance finite element analysis (FEA)

and the object is rendered in a visually realistic deformed or fractured state. This method can be employed to model

virtually any solid material including concrete, glass, rubber, terrain, and vegetation. Furthermore, changing a

material’s behavior (e.g. replacing standard glass with bullet-resistant glass) is accomplished by simply modifying

the objects material properties rather than creating new simulation assets.

Simulating, rather than animating, materials in real-time allows simulation designers and developers to deploy

kinetically realistic simulations while reducing development time and cost.

ABOUT THE AUTHOR

Steve Griffith is the director of physical modeling and simulation at Objective Interface Systems. He has more than

20 years of engineering, business development, and management experience in the software industry.



Realistic material damage simulation using real-time Finite Element Analysis

Steven L. Griffith

Objective Interface Systems, Inc

Herndon, Virginia

[email protected]

INTRODUCTION

The realistic modeling of material damage is a key

component in the development of high fidelity virtual

simulations. However, many simulation developers

have been reluctant to incorporate this level of detail

into their development lifecycle. This reluctance is not

due to a lack of enthusiasm for realistic kinematics;

rather it is a reflection of the cost and complexity of

producing simulations that depict objects that

realistically deform and break as if they were made

from real-world materials.

Despite the challenges, it is imperative that simulation

developers strive to provide properly simulated battle

damage. This level of detail provides invaluable

feedback to the simulation user and produces emergent

scenarios and behaviors that more precisely reflect the

real world. In real-world warfare, the environment is

constantly changing—terrain craters, buildings

crumble, obstacles are eliminated and new ones are

created. If warfighters are to “train like they fight and

fight like they train,” the physical dynamics of the

battlefield need to be simulated with as much fidelity as

possible. Furthermore, today’s military demands that

warfighters are trained not only to overtake the enemy,

but to be aware of the political, economic, social, and

infrastructure implications of their actions. Realistic

training simulations depicting accurate battlefield

damage can help achieve the goal of building and

reinforcing this awareness.

Simulation developers have traditionally relied heavily

on art swaps, or real-time substitutions of art assets, to

model the deformation and fracture of simulation

objects; often with disappointing results. Even when

combined with rigid body physics systems, art

swapping requires the use of pre-defined geometry that

lacks the level of detail required to capture the complex

interaction of battle damage and the effects on the

battlespace and the warfighter.

This paper will describe the use of an advanced,

physics-based method to model and simulate material

damage. This simulation accounts for the material

properties of an object (density, toughness, plasticity,

dampening, etc.) and the forces acting on the object.

These variables are processed in real-time using

advanced finite element analysis (FEA) and the object

is rendered in a visually realistic deformed or fractured

state. This method can be employed to model virtually

any solid material including concrete, glass, rubber,

terrain, and vegetation. Furthermore, changing a

material’s behavior (e.g. replacing standard glass with

bullet-resistant glass) is accomplished by simply

modifying the object’s material properties rather than

creating new simulation assets. Finally, the paper will

discuss Digital Molecular Matter (DMM), a COTS

software implementation of real-time FEA developed

by Pixelux Entertainment and subsequently adapted for

military simulation application and released as

DMMfx. Figure 1 shows a tank breaking through some

wooden fences in a simulation using DMMfx.

Figure 1. Simulated Tank Breaking Through an

FEA Simulated Fence.

WHY REALISM MATTERS

A growing number of researchers are finding a

substantial synergy between interactive storytelling and

training. Rather than simply reciting facts, figures, or

procedures; storytelling builds context around critical

information and allows the student to more quickly



internalize knowledge (Mantovani, 2001). As

interactive media has become ubiquitous, visual effects

have taken on a big role in today’s digital storytelling.

Especially for the younger generations, computer

games, interactivity, immersion in synthetic scenarios,

are as normal and accessible as other media like

internet, television, radio or books. (Ponder, et al,

2003). It follows; therefore, the efficacy of a simulation

is influenced greatly by how immersive and realistic it

is.

Today’s 3D graphics technology is capable of

rendering visually stunning scenes. Off the shelf,

however, the technology does little to provide greater

kinetic realism. Kinetic realism should be considered

just as important, if not more important, than visual

realism – especially in military simulations.

Human perception is highly tuned to movement, and so

kinetic fidelity is a major visual cue in providing

immersive simulations. Because visual fidelity has

seen so much advancement over the past 10 years, it

has served to exasperate the problem of a lack of

kinetic fidelity. In the field of animation, it is well

understood how important it is for the visual fidelity to

be less convincing than the kinetic fidelity in order to

provide a convincing element of animation. Pixar, in

fact, has kept their cartoonish style chiefly because

their lighting models are so good that bumping the

visual fidelity up to its true potential would cause them

a problem of having to increase the kinetic fidelity of

their animations up to a level not possible with manual

animation.

The advent of Rigid Body Dynamics (RBD) has

improved the situation, but physics engines do not

provide an accurate portrayal of materials reacting to

high-energy forces such as munitions (Mann, et al,

2008).

The Problem with Art Swapping

Simulation developers have traditionally relied heavily

on art swaps, or real-time substitutions of art assets, to

show the deformation and fracture of simulation

objects. When a projectile strikes a brick wall, artwork

of wall fragments are swapped in and keyframe

animated to show the wall crumbling. The result is a

wall that always breaks the same way regardless of the

direction and force of the projectile. To create this

effect, artists have to draw hundreds of individual

frames to show the slightest bit of motion or movement.

This approach limits an object’s behaviors while

greatly increasing the effort and time required to

develop the simulation. A breaking pane of glass, for

example, will break the same way if struck by a bullet

or struck by a rock. Should a simulation require a

change of material, such as the addition of bullet-

resistant glass, new art assets need to be created and

scripted to depict the new behavior. The time required

to produce art swaps to depict kinetic effects drives up

the cost of simulation development and can make the

cost of updating an existing simulation prohibitive.

Many simulation developers combine RBD systems

with art swapping in an effort to improve kinetic

fidelity and generate emergent behaviors. This

approach has several disadvantages.

Unconstrained emergent behaviors tend to produce

unintended consequences and side effects, especially as

the number of interactions between objects increases.

Developers need to be able to constrain emergent

behavior depending on the training objective.

Simulations for manual skills training that require a

great deal of practice may require little or no emergent

behavior that might interfere with the repetitive nature

of the procedure being learned. Simulations that build

psychological skills, such as decision making, can

benefit from having a large range of emergent

behaviors that render the simulation game play less

predictable (Ponder, et al, 2003).

Additionally, RBD combined with art swapping does

not consider the consequences of secondary effects in

complex kinematic scenarios. When a bomb explodes

near a vehicle, pieces of the vehicle may then become

projectiles that may, in turn, damage other nearby

materials. Simulating this type of complex interaction

quickly becomes impractical with rigid body systems

because they do not allow for the deformation and

fracture of materials.

Finally, RBD is a very limited way of representing the

physical properties of an object. Simulation developers

using RBD have only 10 variables at their disposal to

describe very complex materials: 3 rotations, 3

translations, mass, inertia, dampening, and coefficient

of restitution (bounciness).

Training simulation developers are facing an

increasingly sophisticated audience that is demanding

more immersive and realistic synthetic environments

that capture their attention and engage them with

visually impressive digital storytelling. To do this, we

need a new approach that provides greater control and

freedom to define and render the kinetic behavior of

simulation objects. These behaviors can no longer be

scripted and animated, they need to be simulated.



The logical evolution of virtual simulation is the

accurate modeling of the kinetic properties of physical

materials. One of the most promising approaches to

kinetic fidelity is to utilize FEA in real time. FEA has

been a proven method to analyze the effects of force on

solid materials in less than real-time simulations for

over fifty years. Using today’s CPUs and GPUs, it is

possible to implement a real-time FEA physics engine

to create a material physics simulator that renders

objects in a virtual world that behave as if they were

made from real-world materials.

A BRIEF HISTORY OF FINITE ELEMENT

ANALYSIS

Finite Element Analysis as discussed here (also referred

to as the Finite Element Method) was first developed in

1943 by Richard Courant. While analyzing problems

involving vibration, Courant proposed breaking a

continuous material into triangular regions to simplify

the approximation of the properties of a material

(Courant 1943). In the mid 1950s a group of engineers

from academia and the Boeing Airplane Company

published an article in the Journal of Aeronautical

Sciences analyzing the stiffness of wing design by

dividing the wing structure into triangular segments. It

is about this time that the term finite element method

was coined (Turner, et al, 1956).

Offline FEA simulations have been used in the

manufacturing industry for many years. FEA

simulations are used to test and refine designs before

the prototype phase of production – reducing the

number of prototypes required, improving time-to-

market and reducing costs (Figure 2).

Figure 2. Visual Representation of FEA Simulation

of an Automobile Crash.

Advances in FEA continued throughout the second half

of the 20th century, paralleling advances in computer

technology. In 1964, a review of NASA's structural

dynamics research determined that the various research

centers were duplicating there efforts to develop

structural analysis software. The review recommended

that a single generic software program should be used

instead. A cooperative project was started to develop

this software and created a specification that outlined

the capabilities for the software (MacNeal, 1972).

A contract was awarded to Computer Sciences

Corporation (CSC) to develop the software. The name

of the program is an acronym formed from NAsa

STRuctural ANalysis. The NASTRAN system was

released to NASA in 1968.

By the early 1970s, FEA was being applied to solve a

wide variety of engineering problems in aerospace,

automotive, and civil engineering (Strange, et al, 1973).

However, FEA required tremendous computing power

and was limited to the most high priority projects.

During the 1980s and 1990s the application of FEA

expanded into the areas of electromagnetics, fluid

dynamics, and thermal dynamics (Strang, 1973). As

the number of problems addressed by FEA increased,

so did the demand on computing power.

By the year 2000 the groundwork was laid for FEA in

the simulation and gaming environment with Dr. James

O’Brien’s seminal work on graphically modeling and

animating the realistic behavior of materials that

fracture and deformation under stress (O’Brien, et al,

1999). At the time of O’Brien’s original writings, the

time required to render the shattering of his example

subject, a teapot, was almost an entire day. In just a few

years, technological advances would reduce that time

from hours to seconds.

FINITE ELEMENT ANALYSIS CORE

CONCEPTS

We will recall from mathematics that a differential

equation states how a rate of change in a single

independent variable is related to other variables and

that partial differential equations are a type of

differential equation involving multiple independent

variables. Partial differential equations are the most

common mathematical description of physical systems.

They are used to solve problems such as those

involving mechanics, thermodynamics, fluid dynamics,

and elasticity.

Finite Element Analysis is a mathematical technique for

approximating solutions of partial differential

equations. The approach is to render the partial



differential equation into an approximation of ordinary

differential equations that are more easily solved. The

result, and the key feature of FEA in simulations, is the

discretization of a continuous object into a mesh of

finite triangular constituent elements.

FEA is a good choice for solving partial differential

equations involving complex objects, such as vehicles

or buildings, which undergo change (such as collisions

with obstacles or projectiles). It is also useful when a

variable level of precision is desired. For instance,

when ordinance detonates in a simulated street near a

building, it is possible to increase the accuracy of the

simulation in more critical areas (such as a storefront)

and reduce the precision in areas facing away from the

street. This approach offers the opportunity to tune the

performance of the simulation to achieve an optimal

result.

FEA provides thousands of degrees of freedom

Creating simulation objects in a FEA-capable

environment starts with a detailed, artist-created surface

mesh. This mesh is then used as the basis for the

creation of a tetrahedral cage (tet cage) or shell, of

points around the surface mesh (Figure 3).

Figure 3. Detailed Surface Mesh (left) and a Lower

Resolution Tetrahedral Cage (right).

The tet cage encapsulates the visible surface mesh and

is usually less detailed. The tet cage is in turn used to

create a “tet mesh”—a tetrahedral tessellation of the

volume bounded by the tet cage (Figure 4). If the

object is breakable, the tet mesh has to be clipped

against the surface mesh and have internal faces added

to tetrahedral boundaries, which will be visible when

the object breaks. The tet mesh represents the pre-

calculated fracture points of the solid object.

Figure 4. Tetrahedral mesh for a simple object. In

(a), only the external faces of the tetrahedra are

drawn; in (b) the internal structure is shown

(O’Brien 1999)

Calculations are then applied to these elements to

create a visualization where objects bend and twist and

reveal the distribution of stresses and displacements.

The degree to which the forces are distributed through

the material are determined by the material properties

assigned to the object at design time or at run time.

Utilizing a real-time FEA solver allows for vastly more

realistic representations of a simulated material.

Armed with FEA in real-time, simulation developers

have thousands of degrees of freedom in describing

how each discrete element can move and interact with

the simulation environment. Moreover, the properties

of these elements can be set to accurately behave like

real-life materials. Wood doesn't simply break apart

along a predetermined seam every time – instead it

splinters into countless pieces from the exact point of

impact, also taking into account the amount of sheer

force exerted. Likewise, concrete crumbles; metal

bends, deforms, and tears; and glass shatters

realistically. The result is kinetic fidelity never before

seen in real-time simulations. Using FEA, stresses

applied to an object as a whole are interpreted as

stresses to the individual elements. The result is a more

granular and realistic view of how an object reacts to

stress.

What is more, art objects developed with an FEA mesh

are created once, and their fracture and deformation

behavior is determined by their material properties and

rendered in real time – eliminating the need for art

swapping.

Objects in real time FEA simulations can realistically

react to forces according to their physical properties

whether big, small, dense, thin, floppy or rigid – FEA

causes it to react appropriately. For example, an aerial

refueling hose-and-drogue can react to air turbulence



just as easily as a stone wall can be made to crumble.

Any solid substance imaginable can be simulated.

The user experience is enhanced because objects can

now react in entirely new ways each time the user

engages in the simulation. So when a tank fires a

projectile at a building at different angles, the building

will crumble differently each time. These emergent

behaviors can reinforce decision training and deliver a

realistic user experience that will keep trainees

engaged.

Material Adjustment

While the FEA equation solver does the heavy lifting,

the most valuable asset within a material physics

simulation engine are the material properties variables.

The material properties of an object are assigned at

design time, but are not hard coded into the object so

that it is possible to change the properties of an object

without having to re-create the object itself. For

example, you may decide to up-armor a vehicle which

would include adding ballistic-resistant glass. In fact,

you can adjust material properties at run-time to reflect

changes in the environment. For example, the

properties of a steel beam can be altered to simulate

softening and deformation due to heat from fire.

Likewise, a rubber refueling hose can become more

rigid and even shatter as the ambient temperature drops

in a simulation scene. These properties can also be

manipulated to allowing the user to create effects

visualize “what if” scenarios within the simulation

itself.

Material adjustments can also be used to fine-tune an

object. Watching a brick wall slightly bend before it

crumbles provides a familiar visual cue that can

enhance decision training. Changes in the material

properties and the deformation of simulation objects

can be used as feedback to the simulator’s sound

system so that the creaking sound of a wooden door can

be heard before it cracks open.

The material properties of objects in a real-time FEA

simulation are exactly the same as what you might

expect to find in a materials science textbook (Table 1).

Material properties may be determined by standardized

test methods. Many such test methods have been

documented by their respective user communities and

published by ASTM International.

Using real-time FEA technology, simulation developers

can vastly improve the visual and kinetic fidelity of

their simulations while reducing asset creation time and

cost. Simulations no longer need be scripted scenarios,

and time-to-deployment is exponentially faster.

Table 1. Common Material Properties Used in FEA

Material Property Description

Young’s modulus Denotes the elasticity (flexibility)

of a material. It is the ratio of

stress (the force on a material)

over strain (deformation of the

material)

Young’s

Dampening

The material’s capacity to

dissipate the energy

Young’s Creep Change in Young’s Modulus as a

material deforms

Poisson’s Ratio Specifies the amount of volume

preservation a material has when

subjected to stress

Poisson’s

Damping

Affects the velocity at which

something changes shape

Density Specifies how much a material

weighs per unit volume

Toughness Denotes the strength of a material

(how breakable something is)

Toughness Creep Change in Toughness as a

material deforms

Plastic Yield Determines how much something

has to deform before it will no

longer return to it’s original shape

Maximum Yield Limits how much a material may

deform. If you strain a material

more than this than the material

will not deform any more

Plastic Creep Determines how quickly

deformation occurs

Friction Controls how slippery a material

is



IMPLEMENTATION OF FINITE ELEMENT

ANALYSIS IN SIMULATIONS

Real-time Finite Element Analysis has been deployed

in a new technology called Digital Molecular Matter

(DMM). DMM technology is implemented as a real-

time engine subsystem that runs independently of the

primary simulation engine; it also includes the tools

required to convert ordinary meshes created by artists

into finite element volumetric meshes.

A key advantage of DMM is the ability to add FEA

effects to both new objects as they are created or to

existing objects for enhanced capability. With minimal

effort, simulation developers can leverage their existing

investments by adding DMM capability to legacy

simulations.

Based on James O’Brien’s original work, DMM was

developed and brought to market by Pixelux

Entertainment for the gaming industry. DMM attracted

the attention of LucasArts, who wanted to deliver state-

of-the art gameplay technology and take their video

games to the next level of realism and reduce

production costs. In late 2005, Pixelux began working

in partnership with LucasArts to develop and refine

DMM into an artist-friendly technology that could

deliver the promise of real-time finite element physics.

DMM is used extensively in their newly released video

game “Star Wars: The Force Unleashed.”

Pixelux subsequently partnered with Objective

Interface Systems (OIS) to adapt DMM to the military

and aerospace simulation market. The resulting

product, DMMfx, was introduced at I/ITSEC 2007 and

represents a way to provide realistic deformation and

fracture in real-time within military simulations. Wood

breaks like wood, metal bends and tears like metal, and

glass shatters like glass. DMM achieves this capability

by modeling the stress within a scene through finite

element representations of the art assets in simulation.

Greatly desired damage features such as buckling,

collateral effects, tearing and fracture can now occur in

completely expected ways (Figure 5), providing

simulations with the unpredictability and realism

necessary to ensure their effectiveness. Virtually any

solid object can be modeled and simulated including

architectural elements, terrain, and vegetation.

Figure 5. A Shaped Charge and a Steel Plate

Modeled as DMM objects before (top) and After

Detonation.

Creating DMM Assets

Creating breakable/deformable assets for use with

DMM starts by creating a watertight, non-self

intersecting poly mesh and then turning that mesh into a

DMM Object. The result is a tetrahedral mesh assigned

with default physical materials that will be controlled

by the DMM simulator. DMM provides command line

tools to perform the conversion. These tools are also

implemented as plug-ins for Autodesk’s Maya and 3DS

Max modeling applications. In the examples below,

Autodesk Maya is used.

The next step is to define the material properties of the

object. When the object is created, it is assigned a

default material, or a material which can be selected

from a library that includes glass, concrete, brick, wood

and many others. Figure 6 shows the dialog box used to

modify material properties at design time.



Figure 6. Design time material property

adjustments. Min Iter, Max Iter, Split Limit and

Relative Error are used to control and optimize the

amount of time consumed by the simulator.

At this point, other modifications can be made that will

affect the object’s behavior. Forces can be applied,

objects can be “glued” using a spring/dampener force,

and selected regions of objects can be made “passive”

so they are not processed by the simulation. The

simulation can now be run and the object will behave

according to it’s properties and the forces acting on it—

including gravity which is adjustable and turned on by

default.

Making a surface mesh breakable clips it with the Tet

Mesh (Figure 7). The fracture geometry is very angular

and straight. This is fine for crystalline materials but

not for things made of other materials like wood or

bricks.

Figure 7. Glass cube shattering after fall

These types of objects can be forced to break on pre-

defined boundaries by attaching an additional “splinter”

cage to the object. A block wall, for example will

fracture at the mortar joints (Figure 8).

Figure 8. Block wall fracturing at mortar joints

Figure 9, below, is a visible representation of how the

DMM object creation and simulation inputs and

outputs relate together.

Figure 9. DMM Mesh Preparation and Simulation.



Once the DMM scene is complete the simulation is run

in the modeling environment and behaviors are fine-

tuned to produce the desired results. The scene is then

exported to be run within a game engine. DMM is

implemented as static library the is ready to link into

your simulation.

CLOSING REMARKS

Although physics-based modeling is not by any means

a new field, recent advances in hardware and software

now make it possible and cost-effective to deploy

virtual simulations that utilized verifiable, real-time

FEA physics modeling to improve kinetic fidelity.

This improved fidelity has important training

implications, especially in the area of decision training.

Furthermore, as younger generations enter the services

with a history of video game play, virtual training

simulations will have to deliver a user experience that

rivals that of the gaming world in order to keep them

engaged.

Finally, simulation rather than animating material

damage can save hundreds, even thousands of hours of

modeling time. In today’s dynamic, asymmetric warfare

environment high-fidelity simulations, deployed

rapidly, will allow our troops to “Train to Fight” and

“Fight to Win.

ACKNOWLEDGEMENTS

The author would like to thank Eric Parker, Vik Sohal,

and Olivier Basille or Pixelux Entertainment for their

assistance with this paper.

REFERENCES

Bimber, O. (2009) Visual Effects and Beyond.

Computer, Vol. 42, no. 7, July 2009

Courant, R. (1943). Variational Methods for the

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MacNeal, R., (1972), The NASTRAN Theoretical

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Mann, J., Lyons, J., del la Cruz, H. (2008) Using Real-

time Physics to Enhance Game Based Effects.

Interservice/Industry Training, Simulation, and

Education Conference (I/ITSEC) 2008

Mantovani, F., VR learning: Potential and Challenges

for the Use of 3D Environments in Education and

Training, Chapter 12 in Towards Cyber-Psychology:

Mind, Cognitions and Society in the Internet Age,

Amsterdam, IOS Press, © 2001, 2002, 2003.

O’Brien, J., Bargteil, A., Hodgins, J., (2002). Graphical

Modeling and Animation of Ductile Fracture, ACM

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Ponder, M., Herbelin, B., Molet, T., Schertenlieb, S.,

Ulicny, B., Papagiannakis, G., Magnenat-Thalmann,

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Strang, G., Fix, G. (1973). An Analysis of the Finite

Element Method. Englewood Cliffs: Prentice-Hall.

O’Brien, J. (2000). Graphical Modeling and

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Documents

Realistic material damage simulation using real-time Finite Element Analysis