Houston, TX June 20, ANSYS, Inc. June 21, 2012

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1 Houston, TX June 20,

2 Confidence by Design Houston June 20, 2012 Mike Smocer Vice President, Central U.S. and Canada 2

Oil and Gas Industry Statistics Global ANSYS Oil and Gas Customer Base All super major IOCs All oil and gas engineering service companies 50 of global top 100 oil and gas companies* Design and

3 Oil and Gas Industry Statistics Global ANSYS Oil and Gas Customer Base All super major IOCs All oil and gas engineering service companies 50 of global top 100 oil and gas companies* Design and analysis of all oil/gas equipment Over 100+ different applications areas *By revenue Platform for technology evaluation/development How do we manage risk? We calculate it up front in simulation stages at both system and component levels. Scott Parent Vice President of Technology at Baker Hughes, 3

4 Today s Mission The Confidence by Design workshops are designed to help you realize your product promise. The agenda is designed to teach you how to leverage ANSYS tools to ensure that your designs will work the first time, before any prototypes are built and tested. 4

5 Our Strategy Simulation-Driven Product Development Fluids Dynamics Structural Mechanics Explicit Dynamics Low-Frequency Electromagnetics High-Frequency Electromagnetics Thermal Mechanics Acoustics Complete Systems Simulated Environments Multiphysics Span Organizational and Geographic Silos Share Engineering Insights Democratize Simulation Better Click to edit Decisions Master text Faster styles 5 Process Automation Enable Best Practices Focus on Engineering

Smart Products Today, product performance is

Courtesy Baker Hughes What if there was a unified

6 Smart Products Today, product performance is evaluated at the component level. Systems integration occurs at the lab, not on the computer. Courtesy Baker Hughes What if there was a unified environment that enabled simulation of the complete systems while addressing all relevant components and physics? 6

7 Smart Products 7

8 Robust Design Today, design evaluations are done repeatedly (tediously), one physics at a time, to find an acceptable design. Initial Design Single Design Parametric Simulation Probabilistic Optimization Goal-Driven Optimization Using systems modeling with ANSYS tools enables T-Rex to ensure design robustness of an in-line sled [ILS]. Courtesy T-Rex Engineering & Construction Final Design Source: ANSYS Advantage Magazine 2012 What if you could quickly and accurately evaluate multiple designs, at the component and system levels, to pinpoint the best design both for performance and reliability? 8

9 Amplifying Engineering Today, analyses are mostly set up and performed by a few experts. ANSYS Design change cost Design change cost Design change cost Development phase What if there was a simulation solution that was powerful enough for experts but easy to use and customizable for novices, without compromising on speed, accuracy and scope? 9

10 Scalable and Cost-Effective IT Solutions Today, simulation tools are deployed on desktops and sometimes on private, high-performance clusters. What if you could deploy simulation across private or public clouds and manage them remotely from a desktop, or even a smart phone or tablet? 10

11 Open Collaboration Platform Today, simulations are done by few at a few sites. What if simulation collaboration were limitless (across all departments, geographies and complete systems)? 11

12 Conference Guideposts Smart Products Robust Design Amplify Engineering Scalable and Cost Effective IT Solutions Open Collaboration Platform 12

13 Morning Agenda 13

14 Multi-track Agenda 14

15 Access to these presentations 15

16 Follow us on Social Media 16

17 Confidence by Design -Houston Companies Represented ~ 90 Attendees Pre-registered ~

18 Confidence by Design Anirudh M. Technical Services ANSYS Inc. 18

19 Agenda Key initiatives that are changing the simulation landscape (yours, ours) Smart Products Robust Design Amplify Engineering Scalable and Cost Effective IT Solutions Open Collaboration Platform 19

20 Key Initiatives Which Business drivers & Technology trends will have the greatest impact/influence on Process / Product Development Workflow Process Optimization / Product Performance Evaluation Implications for ANSYS product strategy Priority, Future vision / path to adoption 20

21 Key initiatives Smart Products Robust Design Amplify Engineering Scalable and Cost Effective IT Solutions Open Collaboration Platform 21

22 1: Systems / Smart Products Products are Increasingly Instrumented and Interconnected More electronics System of systems ANSYS # 1 Depth & Breadth of Solutions Your Partner to Enable Systems Approach to Simulation 22 Shift from single to system innovation Crash Sensors; ESP, Sunroof, Seat controls

physics environments - Connecting different

there was a unified environment that enabled

23 Systems Complexity - evaluate product performance at the full system level Key Challenges Today Effective management (Configurations, reps, model size) Different physics environments - Connecting different physics still cumbersome High-fidelity (3-D) simulations and reduced-order models simulations can t be connected easily What if there was a unified environment that enabled simulation of the complete systems while addressing all relevant components and physics? 23

Systems Approach to Simulation - More Than Just 3-D MARKET

SYSTEMS SIMULATION IP KNOWLEDGE BASE IN SERVICE SYSTEMS VALIDATION

Fidelity DEVELOPMENT Original Source - Prof. Steven D.

24 Systems Approach to Simulation - More Than Just 3-D MARKET ANALYSIS FEASIBILITY OPERATIONS UPGRADES Low Fidelity REQUIREMENTS SYSTEMS SIMULATION IP KNOWLEDGE BASE IN SERVICE SYSTEMS VALIDATION SUB-SYSTEMS SUB-SYSTEMS TEST DETAILED PHYSICAL COMPONENT TEST High Fidelity DEVELOPMENT Original Source - Prof. Steven D. Eppinger (MIT) Control System Embedded Software Click to edit Master text styles 24

25 Systems Multiphysics today in WB Systems Drag-and-drop multiphysics Automated data transfer and solution mapping 25

2: Robust Design Methods Building in Product Reliability Water Level

Click to edit Master text styles Variations in operating conditions,

26 2: Robust Design Methods Building in Product Reliability Water Level Auxiliary Power Reliability Confidence isn t achieved through the sum of all component validations. Safety of Operation Core Temperature Reactor Containment Reliability 26 Click to edit Master text styles Variations in operating conditions, manufacturing processes and material properties create uncertainty in the overall success of a product design. Aids in screening of new product ideas

The Path to Robust Design Optimization Algorithms Robust Design Probabilistic Algorithms 27 Single Physics Solution Accuracy, robustness, speed Multiphysics Solution Integration Platform What if

27 The Path to Robust Design Optimization Algorithms Robust Design Probabilistic Algorithms 27 Single Physics Solution Accuracy, robustness, speed Multiphysics Solution Integration Platform What if Study Parametric Platform Design Exploration DOE, Response Surfaces, Correlation, Sensitivity, etc. Key Enablers/Dependencies - User Experience - IT Scalability & Licensing - Data Management - Process Automation

Robust Design Key Challenges Today Determining the

processes are needed for a full system level study

Optimization Goal-Driven Optimization Parametric

multiple designs with a set of easy to use process

28 Robust Design Key Challenges Today Determining the right parameters over a large number of combinations of design and environmental factors. Computational costs & Licensing Specialized tools and processes are needed for a full system level study Not easy across domains Single Design Probabilistic Optimization Goal-Driven Optimization Parametric Simulation What if you could accurately evaluate multiple designs with a set of easy to use process automation & optimization tools while addressing the bottlenecks with IT and big data. 28

29 Workbench Platform Parametric Studies Robust Design Parameters defined in the applications; managed at the project level Rapid what-if studies 29

30 Workbench Platform, Integrated Optimization Robust Design Drive parametric simulation with ANSYS DesignXplorer Easily advance from one-off simulation to DOE and optimization studies Gain dramatically more design insight with little additional engineering time 30

31 3: Amplifying Engineering New Simulation Users, More Productive Users Pervasiveness of CAE Front Loading Intense pressure Do more with less New product development initiatives call for improved methodologies and tools Human Capital and Consistency challenges Amplify Existing Engineers Productivity and Scope Democratize Simulation to the Engineering Masses Click to edit Master text styles 31

requires complex coding and deployment is not easy What if there was a solution set that was powerful enough for

32 Amplifying Engineering Key Challenges Today Simulation tools & process are often too complex for designers and not customized for their tasks Expert analysts spend too much time on tedious & repetitive tasks Automation requires complex coding and deployment is not easy What if there was a solution set that was powerful enough for experts but easy to use, customizable and deployable for novices, without compromising on speed, accuracy and scope? 32

33 Workbench Platform Automation and Re-use Amplify Engineering Illustration: Change the geometry Update the project Entire project updates in batch mode 33

34 Workbench Platform, Open, Customizable, Extensible Amplify Engineering Journaling and scripting for process automation Application Customization Toolkit for applicationlevel customization Workbench SDK for integration of external tools ANSYS EKM for web-based simulation templates 34

Up Front Analysis Drives Productivity Amplify Engineering Business Initiative: Analysis Led Design Cummins Analysis Led Design (ALD) strategy is a corporate-wide initiative to change

ALD can shorten product development time by getting designs right the first time.

35 Up Front Analysis Drives Productivity Amplify Engineering Business Initiative: Analysis Led Design Cummins Analysis Led Design (ALD) strategy is a corporate-wide initiative to change the prevalent test-first culture Significant benefits include: shorter development time, lower costs and improved products. ALD can shorten product development time by getting designs right the first time. The idea is to place simplified analysis tools in the hands of our designers so they can make more intelligent decisions. Preliminary screening is done early, allowing for domain experts to spend more time on those design enhancements that are shown to hold the greatest promise. 35 Francois Ntone Senior Technical Advisor, CEFD Cummins, Inc.

ANSYS Academic Program Amplify Engineering Presence Academic products used at 2,400 institutions in 79

Research use of ANSYS helps tackle next-generation industry challenges Software Technology Academic

curriculum, Cornell is producing students who can go into industry with a strong foundation in the

36 ANSYS Academic Program Amplify Engineering Presence Academic products used at 2,400 institutions in 79 countries worldwide Value to Industry Students trained in ANSYS join industry with experience in simulation Research use of ANSYS helps tackle next-generation industry challenges Software Technology Academic partnerships ensure our product technology leadership 36 By embedding ANSYS technology in our engineering curriculum, Cornell is producing students who can go into industry with a strong foundation in the application of advanced simulation. Dr. Rajesh Bhaskaran Cornell University ANSYS Academic Program Professor Rajesh Bhaskaran Cornell University

4: Cost-Effective and Scalable IT Critical

computing Efficient centralized infrastructure

s Laptop is Yesterday s supercomputer IT is the

therefore we have a strategic focus on the IT

37 4: Cost-Effective and Scalable IT Critical Enabler & Trends Scale-up of high performance computing Efficient centralized infrastructure (Cloud) Collaboration hubs with, remote, secure and scalable data access Support for platforms(mobile) WEIGHT PROCESSING POWER Today s Laptop is Yesterday s supercomputer IT is the engine that enables the growth of simulation and therefore we have a strategic focus on the IT environment Source: Web ON DEVICE ON DEMAND ON APPLICATION ON PLATFORM 37

of private or public clouds Remote access, job monitoring, Remote visualization What if you could deploy

38 Cost-Effective and Scalable IT Global Distributed workforce Key Challenges Today Licensing and installation are complex Data Issues - efficiency, collaboration, data security and IP management On demand Capacity- Limited use of private or public clouds Remote access, job monitoring, Remote visualization What if you could deploy simulation across private or public clouds and manage them remotely from a desktop, or even a smart phone or tablet? 38

5: Collaboration& Data/Knowledge Management NUMBER OF SIMULATIONS DATA & COMPLEXITY Network

Growth Linear Robust Design & Parametric Studies Exponential Component Subsystem System

edit Master text styles What if we build a non intrusive system that brings CAE collaboration

39 5: Collaboration& Data/Knowledge Management NUMBER OF SIMULATIONS DATA & COMPLEXITY Network Speed Computer Speed Hardware Parallel Computing SIMULATION COSTS Traditional Growth Linear Robust Design & Parametric Studies Exponential Component Subsystem System MULTIPHYSICS, ROBUST DESIGN & SYSTEMS APPROACH WILL CALL FOR BETTER IP MANAGEMENT Click to edit Master text styles What if we build a non intrusive system that brings CAE collaboration for systematic management of simulation data and its associated processes of creating, organizing and reusing.

40 Explosion of CAE Data Tera/Peta Mega Bytes Kilo Bytes Search Model Build Runs Results/Reports Archival Test - Co-relation 40

41 EKM: Engineering Knowledge Management Strategic Intent: Get the right CAE data to the right people at the right time 41

ANSYS EKM Solution Business Initiatives (Current) Knowledge

Teams (Local & Distributed) Best Practices Capture - Human

Protection Business Initiatives (Road Map Focus) Collaborative

(Cloud) Library Data Management Infrastructure Regression

Organizing KNOWLEDGE INFORMATION Client Server Architecture

Team/Workgroup Client Server Architecture Distributed

42 ANSYS EKM Solution Business Initiatives (Current) Knowledge Management Retain & Reuse Simulation Collaboration Integrate Teams (Local & Distributed) Best Practices Capture - Human Capital Challenges, Simulation Consistency CAE Compliance - IP Protection Business Initiatives (Road Map Focus) Collaborative Multiphysics Systems Engineering HPC and Remote Simulation (Cloud) Library Data Management Infrastructure Regression Validation Decision Making Synthesizing Analyzing Summarizing Organizing KNOWLEDGE INFORMATION Client Server Architecture Single Repository Click to edit Master text styles Team/Workgroup Client Server Architecture Distributed Repositories Distributed Teams Collecting DATA 42 Individual Single User Access Individual Repository Scalable Solution

43 Value Drivers APPLICATION CLASSES WITH GREATEST VALUE Broadly Recognized Evolving Nascent Emerging Challenge to Adopt Lowest Moderate Highest Optimization Incremental Analytics CAD Integration Error Estimation and Control Adapt Gaming Technology Multisensory Feedback Advanced Materials Modeling Significant Transformational Impact on Design Success Simulation Data Management Multiphysics Simulation Systems Simulation MEMS/Nano Simulation Stochastic Simulation Complexity Analysis Source: NAFEMS 43 National Agency for Finite Element Methods and Standards

44 Next A Journey through these initiatives in the context of the Offshore Exploration and Operations Smart Products Robust Design Amplify Engineering Scalable and Cost Effective IT Solutions Open Collaboration Platform 44

45 System Simulation for Subsea Applications Scott Stanton Technical Director Ryan Magargle Lead Application Engineer 45

46 Subsea Power Distribution Click to edit Master text styles 46 Framo Engineering

47 Voice of Customers Use Cases List of Features Define Specifications Functional Representation and Models Component Click Selection to edit Master text styles and Sub-System Simulation 47

48 CAD Physics Based Solvers Embedded* Click to edit Master text styles 48

49 Virtual Prototyping Subassembly integration ROM Co-Simulation Software integration Click to edit Master text styles 49

50 Subsea Power Distribution: Engineering Challenges Components: Rating and Sizing Power, Efficiency and Reliability Size and weight of power converters must be appropriate for intended application: E.g. Mobile ROV applications vs. fixed seafloor equipment System level decision: Choosing operating frequencies and voltages levels for distribution Click to edit Master text styles

51 Subsea Power Distribution: Engineering Challenges Systems need to operate dependably within their rated lifetimes System level decision: Materials, dimensions, and electronic controls designed to minimize excess wear from steady state, transient, and fault conditions. Cable losses and overvoltage Transient startup inrush Short and open circuit events Click to edit Master text styles

TWT TWT TWT Subsea Power Distribution: Simulation Solutions Represent subsea network components with models SIMPARAM1 U3 Simplorer1 FML3 FML_INIT1 EQU ICA: id:=2/3*(cos(phiel)*wm1.

52 TWT TWT TWT Subsea Power Distribution: Simulation Solutions Represent subsea network components with models SIMPARAM1 U3 Simplorer1 FML3 FML_INIT1 EQU ICA: id:=2/3*(cos(phiel)*wm1.i + cos(phiel - 2*pi/3)*WM2.I + cos(phiel - 4*pi/3)*WM3.I) iq:=2/3*(sin(phiel)*wm1.i + sin(phiel - 2*pi/3)*WM2.I + sin(phiel - 4*pi/3)*WM3.I) Controller THREE_PHASE1 3PHAS A * sin (2 * pi * f * t + PHI + phi_u) PHI = 0 ~ PHI = -120 ~ PHI = -240 ~ 600V 36kV 6000V B6U1 + soft-starter VSI_3ph_avg TWT1 R1 0 soft-starter W TWT2 SM_ROT1 F B6U VM1 D1 D3 D5 + V WM1 VSI3ph_A1 WM3 D2 D4 D6 0 TWT3 + WM2 FM_ROT1 MASS_ROT1 + A N B ROT1 Click to W edit Master text styles C ROT W w 0 T T VM_ROT1 F_ROT1 V V V V V V Topside Power Generator Step-Up Cable Cable Umbilical Step-Down Power Rectifier Converter Inverter Booster Booster Pump ANSYS, Inc. Transformer June 21, 2012 Transformer Pump

53 Subsea Power Distribution: Simulation Solutions FEA/Numerical Models Cable Electric Machine (Booster Pump) Analytical Models Transformers Behavioral Models Inverter Electronic Drive Controller Click to edit Master text styles 53

54 Subsea Power Distribution: Simulation Solutions Use models to evaluate critical system behavior Determine component voltages from system response Examine transients from startup-conditions Verify electronic controller operation during faults and startup Click to edit Master text styles 54

55 Topside Power: Analytical Representation Click to edit Master text styles 55

56 Cable Umbilical: FEA/Numerical Methods System simulation calculates conductor voltages based on environmental conditions FEA automatically generates models for system Click to edit Master text styles 56

57 Cable Umbilical: FEA/Numerical Methods Verify Material Breakdown for Reliability Map worst case voltage to FEM field simulation Observe electric field intensity for breakdown Voltage [kv] Core Phase Voltages Curve Info ANSOFT PhaseA NexximTransient PhaseB NexximTransient PhaseC NexximTransient Time [ms] Click to edit Master text styles 57

58 Power Converter: Analytical Representation Click to edit Master text styles 58

59 Booster Pump: Analytical Models Full Customization Evaluate machine performance over wide ranges of operation in seconds Click to edit Master text styles Larger gap Longer length Smaller diameter 59

60 Booster Pump: FEA/Numerical Models Automatically Generate System and 3D FEM Models for Simulation Model for System 3D FEM Model Electrical Mechanical Click to edit Master text styles 60

61 Electric Drive Controller Implement control algorithms in a natural way prior to hardware implementation Digital Analog Click to edit Master text styles 61

TWT TWT TWT Bringing it all Together Validate Components Behavior with Rapid Full System Simulation 7000.00 Pump Startup Speed ANSOF 6000.00 Pump Speed [rpm] 4500.00 3000.00 1500.00 0.00 0.00 2.50 5.

62 TWT TWT TWT Bringing it all Together Validate Components Behavior with Rapid Full System Simulation Pump Startup Speed ANSOF Pump Speed [rpm] Time [s] U3 SIMPARAM1 Simplorer1 FML3 FML_INIT1 EQU ICA: id:=2/3*(cos(phiel)*wm1.i + cos(phiel - 2*pi/3)*WM2.I + cos(phiel - 4*pi/3)*WM3.I) iq:=2/3*(sin(phiel)*wm1.i + sin(phiel - 2*pi/3)*WM2.I + sin(phiel - 4*pi/3)*WM3.I) Controller THREE_PHASE1 3PHAS A * sin (2 * pi * f * t + PHI + phi_u) PHI = 0 ~ PHI = -120 ~ PHI = -240 ~ 600V 36kV 6000V B6U1 + soft-starter VSI_3ph_avg TWT1 R1 0 soft-starter W TWT2 B6U 0 0 VM1 D1 D3 D5 + V WM1 VSI3ph_A1 0 + WM2 FM_ROT1 Click to edit Master text MASS_ROT1 styles + A N B ROT1 W C ROT2 T SM_ROT1 F WM3 0 0 F_ROT1 0 TWT3 D2 D4 D6 + W + w T VM_ROT V V V V V V Generator Step-Up 2012 ANSYS, Inc. June 21, Transformer 2012 Cable Step-Down Transformer Rectifier Inverter Booster Pump

Subsea Power Distribution Examples: Direct Electrical Pipe Heating Engineering Challenges Generate sufficient electrical heat to prevent wax

http://www.tekna.no/ikbviewer/content/745664/deh-basic%20technology.

63 Subsea Power Distribution Examples: Direct Electrical Pipe Heating Engineering Challenges Generate sufficient electrical heat to prevent wax and hydrate formation Wire harness topology efficiencies Sizing power source for pipe load current requirements 63 SINTEF Energy Research Options to prevent clogging Raising temperature Requires extra power cabling Requires topside power Adding Click chemicals to edit Master text styles Requires transport Requires extra processing Environmentally sensitive

for 85W/m pipe heating Efficiency measures ratio of useful loss in

current 49% Efficient 1014A flowline current 37% Efficient Click to

64 Subsea Power Distribution Examples: Direct Electrical Pipe Heating FEM field simulation determines cabling efficiency Examples compared for 85W/m pipe heating Efficiency measures ratio of useful loss in pipe to total loss 593A flowline current 55% Efficient 1200A flowline current 49% Efficient 1014A flowline current 37% Efficient Click to edit Master text styles Pipe in Pipe Open Loop (DEH) Induction 64 Efficiency

65 Coupled Solution ANSYS Offers an Integrated Electromagnetic + CFD Solution Click to edit Master text styles 65

Subsea Power Distribution Examples: Direct Electrical Pipe Heating THREE_PHASE1 DEH Cable 3PHAS A * sin (2 * pi * f * t + PHI + phi_u) ~ PHI = 0 TWT R3 ~ PHI = -120 TWT R4 C3

66 Subsea Power Distribution Examples: Direct Electrical Pipe Heating THREE_PHASE1 DEH Cable 3PHAS A * sin (2 * pi * f * t + PHI + phi_u) ~ PHI = 0 TWT R3 ~ PHI = -120 TWT R4 C3 cable_copper_acable_copper_b ~ PHI = -240 TWT 0 R5 L3 C2 0 Optimize compensation capacitor 1.00 Power Factor ANSOFT 0.80 FEM simulation of cable PWR_Probe1.PFE Automatically search and size capacitor for 0.9 PF Time [ms] 66

-240 TWT 0 R5 L3 0 Complex cable geometry electrical parasitics are extracted and dynamically

67 Subsea Power Distribution Examples: Powerline cabling THREE_PHASE1 3PHAS A * sin (2 * pi * f * t + PHI + phi_u) ~ PHI = 0 TWT R3 ~ PHI = -120 TWT R4 C3 cable_copper_acable_copper_b C2 ~ PHI = -240 TWT 0 R5 L3 0 Complex cable geometry electrical parasitics are extracted and dynamically linked to the System Simulator Increased cable lengths see greater signal delay and oscillation. 67

68 Summary System simulation enables robust hierarchical modeling Automation available at all levels Reusable analytical, extracted, or co-simulated models enables efficient and robust designs 68

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