digital twin - nafems...use case : calibration of the digital twin data collection and storage...

Digital TwinAn Engineers’ PerspectiveFatma Kocer – Altair – Engineering Analytics

© 2017 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.

Altair at a GlanceAltair’s Vision

5,000 Customer Installations Worldwide

Long heritage of solving some of the most challenging engineering problems


A digital replica of physical assets, processes and systems that can be used for various purposes

Digital Twin Definition

© 2017 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.© 2017 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.

FunctionalRequirements

System

Subassembly

Detailed Design

ReleaseCandidate

Integration

Unit

End of Life

Physical

Digital


• 1D models

• Fast Model Build• Multi-Model • Multi-Physics• Optimization

• Detailed Model Build• Test Coverage• Accurate Physics

In Service

Product Lifecycle and Digital Twins

• IoT Sensors • Monitoring• Maintenance• Warranty

ConceptFormulation

Product Release & Manufacturing

Feedback


Twins for Operations

Data-Based ModelsPhysics-Based 1D Models

Detect Predict

Operation

Simulation in Digital Twins

Concept Design

Physics-Based 1D Models

IdeateOptimize

Configuration

Twins for Manufacturing


PredictPrescribe

Process/Integration

Twins for Design


Predict - SimulatePrescribe - Optimize

Detailed Design




Detect Predict

Operation


Concept Design


IdeateOptimize

Configuration



PredictPrescribe

Process

Twins for Design



Detailed Design


Predict Remaining Useful Life on an Aircraft Engine

PHM08 Challenge - NASA Challenge DataPrognostics Center of Excellence Data Repositoryhttps://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/


Problem Statement

Engine 1

Engine 2

Engine 3

Engine 100

.

.

.

TUL = 192

TUL = 245

TUL = 135

TUL = 212

Engine 101

Engine 102

Engine 103

Engine n

.

.

.

RUL = ? given 31 cycles




Given 20k+ data of Find


Steps

1. Problem Formulation: • Define and compute Remaining Useful Life (RUL).

2. Data Analysis: • Review the data. • Eliminate constant values, review outliers, review relations.

3. Predictive Modelling : • Start from a simple model; then move on to more complex models.• Review diagnostics and pick the best predictive model.

4. Predict:• Use the predictive model to predict the next engine RUL.• Approximate the prediction.


Results

• FAST for Automated Predictive Modelling• Evaluate each engine in operation using FAST

Engine No.

CurrentCycle

Actual RUL (cycles)

Predicted RUL (cycles)

101 31 112 171102 49 98 139103 126 69 65104 106 82 81124 186 20 19125 48 145 160134 395 7 11


DIGITAL TWIN OF A RADAR SYSTEMLIVIO MARIANO, Technical Specialist, Math and Systems

THIERRY BERNARD, Sr Technical Specialist, MBD

ALTAIR ENGINEERING2018


TWINS for DESIGN

Mechanical Fluid ControlElectromagneticlow-frequency

Electromagnetichigh-frequency


TWINS for OPERATION

ControlControl

SENSOR

Thermal


IoT Platform

TWINS for OPERATION


USE CASE : MAINTENANCE RECOMMENDATION

Data collection and storage(current/historical)

Real-timeanalysis

FRICTION IS HIGH

Lubrication is contaminated. Schedule maintenance


USE CASE : MAINTENANCE RECOMMENDATION


Real-time analysis

ANOMALIES in SENSOR 21

Sensor 21 is the acceleration sensor in the antenna.

Check the antenna structural integrity


USE CASE : PERFORMANCE PREDICTION

Combined with external data, 1D models are run for performance predictions against future events such as extreme weather events.

Based on these predictions, feedback to the system are given such as optimized operation settings or suggested maintenance.

Data collection and storage(weather data)

Feedback to the system


USE CASE : PARAMETER UPDATE

Calculated Motor Torque

USE CASE : PARAMETER UPDATE

Virtual model does not match to physical model.

Automatically update the friction parameter values.

Update friction coefficients


USE CASE : CALIBRATION of the DIGITAL TWIN


Real-timeanalysis

INACCURATE DIGITAL TWIN

Virtual model no longer matches to physical model.

Use optimization to calibrate the model.

Optimization for calibration

Update the model


USE CASE : DESIGN FEEDBACK


Real-timeanalysis

Trends are found for each location, design.

Give feedback to design, maintenance.


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digital twin - nafems...use case : calibration of the digital twin data collection and storage...

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