Simulation Based Design - Lecture 2

Published 2016-08-18


Engineering Design Problem: When we design we would like to:

  • Improve product or process quality
  • Reduce life cycle costs
  • Reduce development lead times

This can happen during the initial design phase or sometime during the products life.

The design process starts by generating ideas - the functional performance of these ideas have to be verified.

There are two ways to verify an ideas functional performance:

  • Physical testing of a prototype or the final product or process.
  • Prediction of the performance of the product or process.

When to measure and when to simulate?
What is the best choice? Generally the answer depends on the system, its behaviour, and the required results.

As a general guideline: Simulate what is easy to simulate and measure what is easy to measure!

Generally it is better to simulate when:

  • Evaluating concepts - before prototypes - are available.
  • Many different or very long load cases have to be evaluated.
  • Required outputs are difficult or impossible to obtain.
  • Measurement will be very expensive (land mine tests).

Simulation Can Assist During:

Initial product development (no product or prototype is available)
Allows designer to:

  • Make well founded decisions early in product development process.
  • Test more ideas in shorter time.
  • Understand how product behaviour is affected by different factors.
  • Discover unexpected behaviour.
  • Be sure product fulfills demands.

Continual product Improvement (prototype or product is available)

  • Optimise design solutions for next product generation.
  • Estimate product sensitivity to changes in e.g. weather, wear, ageing.
  • Test dangerous situations.
  • Understand product behaviour and factors that affect the behaviour at controlled repeated conditions.

Analysis Paralysis?

Model definition might be according to Neelamkavil: "A model is a simplified representation of a system (or process or theory) intended to enhance our ability to understand, predict, and possibly control the behaviour of the system".

For testing or simulation one of two approaches can be taken:

  • Trail and error
    • This method is not well defined and can continue forever without providing any indication as to how close the design is to an optimal value.
  • Testing program e.g. DOE study
    • More structured approach that gives the designer much more insight into how the design behaves.

MBD Simulation Methodology

  1. Problem formulation
  2. Definition of idealized model
  3. Development of computer model
  4. Formulation of system equations
  5. Equation solving
  6. Results and post processing
  7. Evaluation and conclusion

1. Simulation Methodology: Problem formulation, describe:

  • Technical problem to be solved
  • Physical effects to include
  • Limitations of system
  • System components
  • Targets to achieve (force, torque, displacement..)


Design Example

  1. Load cases
  2. Bodies
  3. Inverse Dynamics
    • Ideal constraints
  4. Robust design
    • Model flexibility
  5. Forward Dynamics
  6. Model improvements
    • Door damper/closer
    • Automation

Design door

  • Size: 0.6x2.0x0.04 (from ergonomic data)
  • It must be comfortably operated by a standard human (see later for human force values).
  • Door mechanism must be designed for infinite life.
  • Design must be robust e.g. not fail under limit manufacturing tolerances Automation.

Door V2

  • Optimise door design
  • Door add-ons
    • Damper
    • Opening mechanism

1.Design Example: Load Cases

  • Own mass
  • Opening Forces
  • Extra accessories
  • Manufacturing tolerances
  • Misuse cases

door loadcases

2. MBD Simulation Methodology: Definition of idealized model

Collect relevant system data:

  • Parts
  • Component couplings (interactions between parts)

Model parameters

  • Mass, centers of gyration, damping, stiffness

Figure 6: Idealized Model

3. MBD Simulation Methodology: Development of computer model Driven by:

  • Access to information
  • Required results and accuracy
  • Allowed simplifications
  • Available resources (time and money)
  • Model complexity
    • Static, Quasi static, Dynamic
    • 1D ,2D or 3D computer model
  • Available modeling methods
    • Gravity
    • Rigid bodies
    • Ideal joints
    • Stiffness elements
    • Damping elements
    • General force components
    • Contact
    • Advanced elements (tyres, flexible bodies, ..)

Creating models in Adams/View

Location and Orientation

  1. Points (Parametric): Location only
  2. Markers: Location and orientation

Figure 7: Location and Orientation

Specifying Location and Orientation in Adams

Figure 8: Specify location and orientation

  • Location: specify in global or local coordinates
  • Orientation: specify in global or local coordinates
    • Along Axis: Z-axis along line of two points, arbitrary rotation.
    • In Plane: Z-axis along line of first two points, third point locates zx-plane.

Figure 10: In plane

Figure 9: Along axis

2. Design Example: Bodies

Figure 11: Clock pendulumPart vs Geometry

  • Good for concept evaluation
      • Pendulum with out link

  • Next step after acceptable results create CAD
      • Pendulum with link

Parts In AdamsFigure 13: Modify part

  • All Parts (except ground part) has:
    • Initial position and orientation
    • Part mass & inertia
      • Mass and inertia reference
    • Initial velocities
    • Degrees of freedom
      • Governed by laws of mechanics

Figure 12: Modify body

Moment of Inertia Experiment


  • Blue -> Solid Cylinder
  • Green -> Hollow cylinder
  • Brown -> Solid Sphere
  • Red -> Hollow Sphere
  • Rolling radius of all participants equal
  • Mass for all participants are equal
  • All participants roll without slipping

Constraint equations in Adams

  • Constraints are represented as algebraic equations in Adams/Solver.
  • These equations describe the relationship between two markers.
  • Joint parameters, referred to as I and J markers, define the location, orientation, and the connecting parts:
    • First marker, I, is fixed to the first part.
    • Second marker, J, is fixed to the second part.

Figure 14: Constraints

Figure 15: Constraint example

Ideal Constraints in Adams

Figure 15b: Ideal constraints

Joint Primitives in Adams

Figure 16: Joint primitives

5. MBD Simulation Methodology: Equation solving

  • Parameters:
  • Solver type
    • Stiff methods (Implicit backwards difference formulations)
    • Non stiff methods (Explicit forwards difference formulations)
  • Step size
  • Error
  • Simulation duration

6. MBD Simulation Methodology: Results and post processing

  • Problem dependent
  • Available tools
    • Time domain plots
    • Frequency domain plots
    • Animations
    • Data export

3. Design Example: Inverse Dynamics

Solve kinematic equations but calculate forces required to do so.
Use motions

  • Joint motion
  • Point motion

Measures: Your Virtual instrumentation

  • Predefined measures
    • Object
    • Point-to-Point
    • Included angle
    • Orientation
    • Range
  • User defined
    • Adams/view Computed
    • Adams/Solver function

Figure 18: Measure

7. MBD Simulation Methodology: Evaluation and conclusion

Compare system behaviour with initial problem formulation

  • Problem solved: continue to next step in development process
  • Problem not solved: Find what is wrong, update and iterate MBS procedure.
    • Unsatisfactory design
    • Model does not exhibit required behaviour

Evaluate certainty of results

  • Assumptions
  • Numerical approximation

Results Discussion

  • Measures in local coordinate systems
  • Redundant constraints: BAD! Why?
    • Indeterminate structure
    • Alternate constraint configuration

Figure 19: Results

4. Design Example: Robust Design

  • Manufacturing tolerance simulation
    Rotate hinge 0.1deg

Figure 20: Robust design



  • Forces for physicists:14431850
    • Gravitation
    • Weak force
    • Strong force
    • Electromagnetic force
  • Forces for engineers:
    • Body forces
      • Gravity
      • Electromagnetic forces
    • Aerodynamic forces
      • Buoyancy
      • Lift
      • Drag
      • Thrust
    • Contact or normal forces
    • Friction forces
    • Damping forces
    • Compliant forces (elastic)
    • Applied forces (push, pull, torque)
    • Fictions forces
      • Coriolis force
      • Centrifugal force


Adds linear flexibility

Figure 21: Bushing

Flexibility: Where should the flexibility be added?

Figure 22: Flexibility


Figure 23: Results



  • Model not over constrained anymore.
  • Forces increase with increasing angle of bottom joint.
  • Forces increase when distance between joints reduce but effect of tolerance reduces?

Figure 25: Discussion

5. Design Example: Forward Dynamics

Can a human open the door?

Figure 26: Human forces to open door

Applied Forces:

Figure 27: Applied forces

Figure 27: Applied forces

  • Single Component Force
  • Single Component Torque
  • Torque Vector
  • Force Vector
  • General Force

Must select, components, run time direction, and action and reaction bodies.

6. Design Example: Model Improvements

  • Improve constraint model
    • Add play
    • Torque vs axial reaction forces
  • Add some way of stopping the door when it is open and closed
    • Sensor
    • Stop torque
    • Point to plane contact
  • Load prediction for finite element calculation
  • Add door damper to automatically close door

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