simcenter - the art of the possible - siemens plm …€¦ · simcenter - the art of the possible...
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Simcenter - The Art of the PossiblePaul Weal - Sr. Business Developer, Siemens PLM
Realize innovation.Unrestricted © Siemens AG 2016
Unrestricted © Siemens AG 2016
16.05.2016Page 2 Siemens PLM Software
The Art of the Possible
We drive innovations
Virtual sensing
Model Predictive
Control
Testing
productivity with
Cloud / IoT
Convergent
modeling
Big Data
AnalyticsComposites
design
Topology
optimization
Parameter
management
Real-time
simulation
Test-1D-3D
Enabling Systems
Driven Performance
Verification
Synchronous
technology
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Optimal Trajectory Planning for
Driver Assistance System
How to extend a driver’s limited viewing
horizon using digital map data?
How to anticipate for dangerously
high velocity when entering a turn?
How to achieve fuel efficient driving?
Driver Support Using Model Predictive Control
Addressing New Challenges in Controls Engineering…
Similar to human driving
Dynamic constraints
Input constraints
2. Control Objective
Smooth trajectory
Time-optimal driving
Safe vehicle cornering
3. Dynamic Trajectory Optimization
Find the optimal trajectory over a receding horizon
Online optimization
Visually inform the driver about reference path
and vehicle velocity
1. Model for Prediction
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“Virtual Sensing” – Combined Use of Test and Simulation
Example: Body Force Estimation applied to Driving Performance
Wheel Angles
Speed/Position
Strain/ Accel. …
Sensor data
Cornering
Forces
At Body
Connections
Virtual sensor
Measurement update
∆ (Measured value - predicted )
Kalman Filter based on Simulation (Real-time)
Input maneuver
Objective evaluation of driving
performance by estimating body
cornering forces at suspension
to body connection points using
Test - 1D/3D modeling
Tires
Road
Chassis/body
Su
sp
en
sio
n
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Real-time Simulation – 1D, 3D and Combined
Enabling Human in the Loop (Simulators) and Frontloading Controls Engineering
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Convergent Modeling Technology
Revolutionize the way product shapes are developed
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Enabling Systems Driven Performance Verification
MBSE in Enterprise Systems Engineering Processes
System Architecture Modeling
Model
elements
Sim.
Architecture
Sim. I/O
realize
specify
Reusable Assets
Models
Specify, Trace and Configure
Realize, Implement, Validate and Verify
instantiate
ICE
E-motor
rshaft_1
Battery
elect_1_2
rshaft_1
Gearb
ox
Chassis
rshaft_1
elect_1_1
rshaft_1
rshaft_1
Multi-Domain Simulation Architecture
Sim.
Conf.
Configured Multi-Domain Simulation
Simulate and Validate
specify
behavior
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Taking Advantage of IoT and Data Analytics
In support of testing productivity
Multi-physics data acquisition
on real-life test item
with LMS SCADAS XS
Measurement data from Cloud
as input for simulation model
- Model validation
- Result calculations
- Model as virtual sensor
Cloud-enabled
remote monitoring of full
measurement data, including
processing
Cloud-enabled remote
measurement status
tracking via mobile
device
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Data mining and processing on
large sets of automotive
measurement data
Providing answers to
engineering questions about
vehicle usage during driving conditions
Big Data Analytics
Processing of On-road Fuel Economy, Durability, Vehicle Usage, …
Generating Engineering insight from Vehicle Usage Data
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Central Europe China USA Central Europe China USA
B-Type C-Type
Relative Time v=0
Relative Time XSystemEngineOff var 1
Relative Time XSystemEngineOff var 2
On-road driving –
fleet information
CAN
Sensor
…
Data taken during
realistic driving
conditions
Machine Learning &
Statistical processing
on large data
quantities
Data mining services delivered by Siemens STS services
Engineering
Insight
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Teamcenter Simulation
Parameter Management
“We use the Teamcenter simulation process management solution to close the loop
with the tools that are used.”Marc Solomon, PLM Chief Engineer and Engineering Systems Architect, ULA
Highly specialized disciplines
Hundreds of tools
Historically document centric
Goal: Minimize handoff cost and error to/from analysis and
design tools
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Topology Optimization
Innovative workflows to speed engineering
Challenge
Efficient and complete
process for designing,
simulating and optimizing
lightweight parts
Optimized models using different parameters
Define functional features on optimized result
1. Define CAD features as
functional requirements for
the optimization – bosses,
holes, keep out/in’s etc
2. Define multiple load cases
and single objective
3. Set resolution
4. Result is returned as a
Convergent CAD model
ready for:
• further modeling work
• use as design guidance
for re-modeling
• being sent straight to the
3D Printer
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Synchronous Technology
Leverage geometry from any source for faster CAE analysis
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Leveraging the value of composites with LMS Samtech Samcef
Airbus Group Innovations
Realizing technological excellence and breakthroughs in aircraft composite design
• Facilitated the engineering and
analysis of complex composite
structures
• Used improved understanding of
composites to increase lead over
competitors
• Enhanced ability to perform
composite damage analysis
“Thanks to the implementation into LMS Samcef of advanced composite material laws
developed in collaboration with LMT Cachan and LMA Marseille, Airbus Group gained much
deeper physical insights, thus extending the gap with its competitors by positioning itself as
the first and leading research department able to offer such advanced expertise."
Didier Guedra-Desgeroges, Vice-President and Head of the Technical Capabilities Center
• Identify delamination and damage in composite structures
• Use nonlinear analysis to determine adequate safety margins
Correlation between LMS Samtech Samcef
and test resultsDamage on a composite helicopter blade