ANSYS http://www.ansys-blog.com Engineering Simulation Software Tue, 23 May 2017 13:11:30 +0000 en-US hourly 1 https://wordpress.org/?v=4.7.5 http://www.ansys-blog.com/wp-content/uploads/2015/09/cropped-blog-header-1-32x32.jpg ANSYS http://www.ansys-blog.com 32 32 34579800 CFD Time Transformation Delivers Accurate Turbomachinery Unsteady Transient Flows Faster Than Conventional Methods http://www.ansys-blog.com/turbomachinery-unsteady-transient-flows/ http://www.ansys-blog.com/turbomachinery-unsteady-transient-flows/#respond Tue, 23 May 2017 13:11:30 +0000 http://www.ansys-blog.com?p=18221&preview=true&preview_id=18221 Unsteady methods are becoming increasingly important in turbomachinery design and optimization because they model transient flows and performance more realistically. Unfortunately, using time-accurate CFD simulations to understand these unsteady flows in compressor stages can be computationally expensive. In recent years, ANSYS … Continue reading

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Unsteady methods are becoming increasingly important in turbomachinery design and optimization because they model transient flows and performance more realistically. Unfortunately, using time-accurate CFD simulations to understand these unsteady flows in compressor stages can be computationally expensive. In recent years, ANSYS has been working on methods for modelling the transient flows in turbomachinery stages that require as few as single-blade passages per row but with equivalent accuracy. As a result, engineers can drastically reduce computational time and memory resources by up to 10X.

Unsteady Flows in a Centrifugal Compressor transient flows

Centrifugal Compressor Stage geometry and CFD simulation images created
using the Time Transformation method

Our engineers have been collaborating with the team at GE Oil and Gas in Le Creusot, France to study Time Transformation (TT) — one of these methods. In a recent paper, they concluded that the Time Transformation method was able to accurately predict the transient flow behavior of unsteady flow in a centrifugal compressor stage equipped with a vaned diffuser and cavities. In comparison with the reference solution (TRS), the TT method experimental data showed a good agreement and the results correlated well. In addition, the TT method demonstrated a strong ability to improve run time and reduce memory requirements. You can learn more about ANSYS TT and other transient blade row methods in our on-demand webinar.

These GE and ANSYS researchers will be presenting the detailed results in a paper entitled Unsteady Flow in a Centrifugal Compressor Stage Equipped with a Vaned Diffuser and Cavities at the upcoming ASME Turbo Expo in June. If you will be in Charlotte, NC please plan to attend their presentation.

And don’t forget to visit ANSYS in booth number 701 at the Charlotte Convention Center. You can learn more about ANSYS is up to at the Turbo Expo here.

Finally, I want to give a big shout out to the authors: François Moyroud and Christophe Corneloup of GE and Mohand Younsi and Antoine Baldacci of ANSYS. Nice work! Learn more: Proceedings of ASME Turbo Expo 2017, GT2017, July 26-30, 2017, NC, USA

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Engineering a Hyperloop Pod with ANSYS http://www.ansys-blog.com/hyperloop-pod-ansys/ http://www.ansys-blog.com/hyperloop-pod-ansys/#respond Fri, 19 May 2017 12:45:19 +0000 http://www.ansys-blog.com/?p=18040 Since starting out as a segmented group of individuals passionate about high-speed technology, Berkeley Hyperloop (bLoop) has come a long way in our (roughly) two years of existence. What started as a vague mission to create a broader impact on … Continue reading

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Since starting out as a segmented group of individuals passionate about high-speed technology, Berkeley Hyperloop (bLoop) has come a long way in our (roughly) two years of existence. What started as a vague mission to create a broader impact on the future of transport is now a tangible team of engineers, designers, marketers, logisticians and everything in between and we have no plans of stopping now. Of course, we didn’t do it alone. We’d be remiss if we did not acknowledge the generous support of sponsors like ANSYS, sponsors that have helped us realize the dream of designing and bringing a functional Hyperloop pod to that only existed in our wildest dreams up until a few months ago.

berkeley hyperloop pod ansys

With ANSYS technology, bLoop has accomplished a great deal — from identifying structural efficiencies to helping solve intricate problems in braking and levitation, ANSYS’ support has indeed been indispensable throughout our journey.

Starting with optimizing our aero profile, ANSYS CFD software allowed us to quell concerns about pod aerodynamics. By designing our pod with a Von Karman profile to minimize drag at speeds up to 250 miles per hour (the maximum speed before an air compressor becomes useful), we have been able to push our pod’s engineering capabilities to new heights. By running parametric sweeps of levitation and braking for airgap and velocity, we have been able to calculate and experimentally measure the forces generated by our NdFeB Halbach arrays.

Lastly, by generating a surface fit of our levitation sims, we have been able to compare and match experimental data to our expectations from simulation, thus increasing the accuracy of our design decisions. After presenting these results at the ANSYS Innovation Conference last fall, we received invaluable feedback that allowed us to improve our work. However, our design/build efforts are far from complete.

bLoop Berkeley hyperloop ansys composite prepost

In the near future, we plan on running more advanced simulations for our carbon fiber structures in ANSYS Composite PrePost to perform modal analysis and simulate loading on bonded subcomponents. We also plan to develop more innovative braking systems that could enable deceleration from speeds of up to 760mph. Gradually, we plan to completely redefine the way our pod is engineered and to compete at the SpaceX Hyperloop Competition in 2018. We are also expanding our team through the next few months to bring these ideas to life and engineer a powerful, sustainable pod.

Berkeley Hyperloop team

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Digital Twin of a Motor and Pump System – Second Edition http://www.ansys-blog.com/digital-twin-motor-pump-system/ http://www.ansys-blog.com/digital-twin-motor-pump-system/#respond Thu, 18 May 2017 15:01:56 +0000 http://www.ansys-blog.com/?p=18332 About a year ago, my colleague, Eric Bantegnie, wrote a blog that described how we, along with our partners PTC, NI and HPE, had created a digital twin of a pump and one of its valves. We showcased this at … Continue reading

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About a year ago, my colleague, Eric Bantegnie, wrote a blog that described how we, along with our partners PTC, NI and HPE, had created a digital twin of a pump and one of its valves. We showcased this at PTC LiveWorx. I’m happy to announce that work continues with our partners on a new and expanded version of the digital twin of this pump and its valves to its motor and electric drive.

Why is this exciting and important? This enhanced digital twin demonstrates a multi-domain system including fluids, electromechanical, electromagnetics and thermal  aspects, coupled with a user friendly Human Machine Interface (HMI),  to solve a challenging problem that faces motor designers and operators — determining, monitoring and maintaining the optimal temperature at which to operate the motor and its components on a consistent basis. Why does this matter? Every 10 degree Celsius increase in operating temperature of the motor and components over their optimum temperatures decreases the life of the motor by half!

But how can an operator determine if the motor is consistently running at its optimum temperature and not overheating? Often there are no sensors on the motor to provide information about the temperature of the motor. Operators can guess at what temperature the motor is by monitoring the input power, current and voltage, but this is an imprecise method.   When motors are deployed in the field, even if there are sensors measuring temperature, they are costly to operate and data is frequently inaccurate or delayed.

Determining Motor Temperature

A digital twin can provide answers to this important question, extending the life of the motor by ensuring the motor temperature is within the desirable range while the pump operates at around its best efficiency point. How does this work?  Flow and pressure have an impact on the operation of the motor and the temperature at which it operates. The physical pump is connected to the motor driven by the electrical controller. With the digital twin, only two inputs from two sensors that indicate the opening position of the two flow valves controlling flow rate through the pump, are needed to simulate the entire system — allowing us to gain useful insights into the operating conditions of the pump and motor. By utilizing virtual sensors embedded in simulation models, the need for physical sensors can be drastically reduced. With the digital twin and the information from the two sensors on the pump, we are able to determine the temperatures of the motor in addition to the current, flow rate and pressure at various locations at all times.   

Building and Connecting the Digital Twin

In order to create the simulation models necessary to build the digital twin and determine the operating temperature of the motor, a system-level, multi-physics approach that combines fluids, electromechanical, electromagnetics and thermal simulations is necessary. Remember that the pump is connected to the motor and the motor is driven by a controller.

In addition to the electromechanical model of the motor, we created a thermal Reduced Order Model (ROM) of the motor with the inputs to the motor being the voltage and current, and the output being the temperature. This requires first an electromagnetic simulation of the components within the motor to calculate the heat sources within the motor itself. Then, these results are passed to a CFD simulation to determine the cooling aspects. In the above process, two ROMs are created, the first one for motor electromagnetics and the second one for cooling, enabling quick predictions of both the transient and future steady state temperatures of the components of the motor.

system-level model of the digital twinThe system-level model of the digital twin
incorporates multiple physics and an HMI. (click image to enlarge)

Once the as-designed digital twin is ready, we can connect it to the physical pump and gather sensor data to determine the operating conditions of the pump and the motor and make adjustments as needed to maintain optimum motor temperature. But, we can do even more than this. When we disconnect the digital twin from the physical asset, we can use ANSYS simulation and HMI to test different scenarios and operating conditions of the digital pump and motor. By digitally manipulating the valves on the pump, we can immediately see how these changes affect the flow, discharge and suction pressures, current, and temperature of the motor’s rotor cage and the bearings inside the motor. This allows the pump operator to perform what if scenario testing, putting the digital version of the motor-pump through its paces to find optimal operating conditions for both the motor and pump, and perform corrective actions.

Normal Condition

Overheat Condition

Predicting the Future With Digital Twins

The digital twin allows the operator to determine the future state of the motor components’ temperatures too. This is extremely useful information that cannot be determined without the use of a digital twin. Due to the thermal mass of the motor components, it takes time for their temperature to change. For example, if the motor is in an environment with high ambient temperature or in an overload condition, the operator may not know that there will be a temperature spike on the motor components until it actually happens some time later, if there are temperature sensors on the motor. If there are no temperature sensors on the motor, the operator would never receive this information. By being able to predict the results of certain changes in the ambient temperature, pump, fluid or flow and how they will affect the temperature of the motor and its components immediately, the operator can take corrective action early, helping to preserve the life span of the motor and its components. The digital twin enables all of this.

If you are going to be at PTC LiveWorx, swing by Booth 345. We’ll be demonstrating a real life motor-pump digital twin in our booth. Also, learn more about how we are partnering with PTC to enable digital twins and how simulation can solve the challenges of ever increasing digitalization. We’ll be presenting on this topic at the show.

And learn more about how we are powering simulation-based digital twins in the most recent edition of ANSYS Advantage magazine.

 

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Why Digitalization Needs Physics-Based Simulation http://www.ansys-blog.com/digitalization-needs-physics-based-simulation/ http://www.ansys-blog.com/digitalization-needs-physics-based-simulation/#comments Wed, 17 May 2017 13:48:05 +0000 http://www.ansys-blog.com?p=18284&preview=true&preview_id=18284 Digitalization, digital transformation, and digital twins have become key business initiatives at many companies. The goal of these initiatives ultimately is to accelerate revenue and profitability growth by speeding innovation, improving productivity, and increasing reliability across the enterprise. Industry leaders know … Continue reading

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Digitalization, digital transformation, and digital twins have become key business initiatives at many companies. The goal of these initiatives ultimately is to accelerate revenue and profitability growth by speeding innovation, improving productivity, and increasing reliability across the enterprise. Industry leaders know that revenue and profitability both suffer when their product fails to meet design objectives, underperforms the competition or does not meet customer expectations. When your product fails, your customer is unhappy, your re-design costs will be higher than planned, your reputation may be damaged, or worse, you may go out of business.

Given the complexity of today’s products, how can companies be sure that they will deliver the most reliable and innovative products to the market? Moreover, how can they leverage their product superiority to deliver additional value to their customer and more profitability for their business?

The answer to these questions includes physics-based modeling and simulation.

Digitalization in R&D – Smart Product Design

In a Wall Street Journal article titled, “Silicon Valley Stumbles in World Beyond Software”, Jack Nicas gives excellent examples of product prototypes that failed when deployed in the real-world. He notes that Google scrapped and redesigned a drone delivery project when it was discovered that the drone often toppled during takeoffs and landings due to wind. Chris Anderson, CEO of 3D Robotics, a supplier to Google, is quoted as saying, “It was a dumb thing about physics”! The article explains that, “In software, programmers can control their environment. The physical world is messy and unpredictable.”

That is a credible statement. Bad things happen when you neglect physics.

Physics-based engineering simulation can and is playing an important role in smart product development and testing today. Unlike building an actual prototype, physics-based modeling and simulation tools allow you to not only predict what will happen, but why it will happen. It gives you the insights you need to make the correct choices. In other words, simulation can help you choose between good ideas and bad ones, speeding you on your way to success in your digitalization journey.

And while the modern world is intensely focused on the opportunities presented by electrification, we should remember that structural mechanics, fluid-dynamics, and electronics are all governed by natural laws of physics. Therefore, to overcome the challenges of designing smart products, engineering simulation needs to include multiple physics to fully characterize and understand the behavior of the product in the real world, or risk failure. The short video below provides an example of how physics-based simulation helps engineers design better products for the digital world.

Digitalization in Operations – Digital Twins

According to Dr. Irving Wladawsky-Berger, Chairman Emiritus IBM Academy of Technology, digital twins are bringing physical and digital worlds closer together. Dr. Wladawsky-Berger notes that digital twins are quickly becoming an integral part of the industrial economy. General Electric and PTC have been on the forefront of this trend, launching the Predix and ThingWorx platforms to speed the development of industrial Internet applications.

“Companies can use digital twins to detect and isolate faults, perform diagnostics and troubleshooting, recommend corrective action, determine the ideal maintenance schedule, optimize asset operation, and generate insights to improve the next generation of the product.” – Chris MacDonald, Sr. Director, Analytics GTM Strategy & Business Development, PTC

General Electric has deployed over 660K digital twins — an amazing accomplishment. This number will surely grow quickly in the coming years. Ganesh Bell, chief digital officer of software and analytics at GE Power and Water says that “the digital twin is not a generic model. It’s a collection of actual physics-based models reflecting the exact operating conditions, such as lifing, performance and failure modes, in the real world.”

Digital twins can reduce equipment down time by 30 percent – General Electric

In the most recent issue of the ANSYS Advantage magazine, Ajei Gopal, President and CEO of ANSYS, shares that “simulation is the only way to fully realize the tremendous value contained within the digital twin”.

digitalization digital twin - mind of a machine - GE

Courtesy General Electric

To implement a digital twin for an asset, you begin with its physics-based model, Since many organizations are already using physics-based models to create their products, they can additionally employ them to simulate the product’s field performance in real-time using the same sensor information that the physical asset is experiencing. This real-time simulation with real-world data can enable real-time analytics, delivering better business outcomes through efficiency gains and reduction in unplanned downtime. Black & Decker, which manufactures power tools, has improved labor utilization by 12 percent and increased throughput by 10 percent. This digital twin of a pump illustrates how 3D physics simulation, connected to the ThingWorx platform, can be used to improve product reliability and asset up-time.

Digitalization across Industries

To be sure, the application of digital twins spans multiple industries. Thierry Marchal, Industry Director for Healthcare at ANSYS, says that someday you will have your own digital twin! He notes that virtual model of ourselves will allow us to “fine tune treatments and predict the behavior of our own body to optimize our health”. This technology will help reduce healthcare cost, improve quality of service, and make it easier to access healthcare information and services.

digitalization digital twin healthcare

Join me and my ANSYS colleagues on May 22-25 at the LiveWorx17 Technology Conference in Boston to learn more about digitalization and digital twins. We will demonstrate a working digital twin and show how physics-based simulation is critical for your digitalization initiative.

 

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Enabling Digital Exploration with ANSYS 18.1 http://www.ansys-blog.com/digital-exploration-ansys-18-1/ http://www.ansys-blog.com/digital-exploration-ansys-18-1/#respond Tue, 16 May 2017 22:40:15 +0000 http://www.ansys-blog.com/?p=18350 Digital exploration has never been more vital to long-term business success than it is today. The product design space is exploding, driven by increasingly smarter devices, advanced materials, and next-generation manufacturing technologies like 3-D printing and mass customization. At the … Continue reading

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Digital exploration has never been more vital to long-term business success than it is today. The product design space is exploding, driven by increasingly smarter devices, advanced materials, and next-generation manufacturing technologies like 3-D printing and mass customization. At the same time sustainability and cost put pressure on identifying and eliminating unnecessary safety margins, while still ensuring long-term product strength and durability. Design engineers have an unprecedented opportunity to innovate and explore product designs, but also orders of magnitude more complexity to manage.

Engineering simulation gives product developers the necessary insight to understand the impact of design choices, evaluate what-if questions, and tame the growing complexity. And when used upfront in the process to digitally explore larger design spaces than ever before. However, for all engineers to benefit from simulation we must continue to make it easier to use.

The powerful combination of ANSYS SpaceClaim and ANSYS AIM in ANSYS 18.1 highlights the ability for entire design teams, not just simulation specialists, to explore new design opportunities enabled by the latest manufacturing techniques. Through upfront simulation they can confidently understand the impact on product performance. Let me give just two examples in this blog.

One example of this is exploring the opportunities opened up by additive manufacturing, that enables the creation of highly stable lightweight structures that cannot be produced using conventional production processes. ANSYS SpaceClaim 18.1 significantly simplifies the creation of such parts, and complex light-weighting can be achieved in a single operation using one of over a dozen pre-defined infill patterns.  Designers can now also quickly verify that parts are suitable for manufacture, and SpaceClaim’s pre-print checks will highlight areas of insufficient thickness, cavities that can trap print materials, and overhangs that may be in need of additional support during the print process.

In the example below, 50% material reduction is achieved using hexagonal infill in a support bracket. Subsequent analysis in ANSYS AIM took a matter of minutes and verified acceptable stresses and comparable deformation under a 1-ton load (deformation visually exaggerated for effect), validating that the light-weighted part would perform as required.

ansys 18.1 ANSYS AIM

ANSYS 18.1 release

As previously highlighted, customization is a powerful enabler to realizing upfront simulation, by providing tools focused on specific design goals, while embedding expert, simulation-based knowledge in a streamlined process. ANSYS 18.1 makes these customization possibilities pervasive from initial geometry modeling down to final results evaluation, through powerful new scripting capabilities in SpaceClaim and the new ‘Guide Me’ custom applications in AIM.

In the example below, a few lines of script and SpaceClaim’s script publishing tool allow any user to extend the user interface to automate any set of tasks that is common in their workflow — in this case automatically removing all holes and bodies below a certain tolerance. (Stay tuned for our upcoming blog that takes an even more in depth look at the power of scripting in ANSYS 18.1.)

ANSYS SpaceClaim ANSYS AIM customization

SpaceClaim and AIM customization allows easy exposure of new tools and automation, without the need for complex programming.

These two examples only scratch the surface of how ANSYS 18.1 continues to make engineering simulation accessible to a much broader audience and enables massive upfront digital exploration. With growing product complexity and around 80% of the costs locked in at the early design stage, the potential of enabling every design engineer to use simulation is one of the largest opportunities for innovation today.

And since ANSYS SpaceClaim and ANSYS AIM build on the same foundation as the flagship ANSYS products used by experts across the world, there is no longer a compromise between easy to use and accurate simulation. I encourage you to check out the complete coverage available on the ANSYS 18.1 launch page.

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How to Make Smart Digital Twins http://www.ansys-blog.com/smart-digital-twins/ http://www.ansys-blog.com/smart-digital-twins/#respond Mon, 15 May 2017 16:47:04 +0000 http://www.ansys-blog.com/?p=18325 Digital twins continue to grow in importance. Here in Germany, engineers at many companies, including Bosch and Daimler, are dealing with complex applications and the challenge to improve the product performance to come up with an optimized and robust virtual … Continue reading

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digital twins dynardoDigital twins continue to grow in importance. Here in Germany, engineers at many companies, including Bosch and Daimler, are dealing with complex applications and the challenge to improve the product performance to come up with an optimized and robust virtual design. They need to determine and evaluate the robustness of virtual prototypes, considering scattering effects, which is difficult or not even possible in hardware tests. Software is used to accurately and rapidly generate proper samples and the resulting understanding saves them a lot of time and money in prototyping so they can stay competitive.

High-performance computing (HPC) and Product Lifecycle Management (PLM) tools are enabling these companies generate and store big data to such an extent that the creation and calibration of virtual system models has become possible. Once created, a digital twin can simulate the product performance at almost real-time operating status. With the resulting diagnoses and prognosis, the performance and reliability of products can be much better understood, controlled and optimized.

For example, engineers can use software to consider measured scatter of various input data in their virtual designs. Then real world data measurements can be input into the digital twin to almost instantly predict the performance and quality of the product.

Using these simulation-based virtual system models, these companies are looking at opportunities for optimization and control of such systems. These tools would enable engineers to speed up the decision-making process, enhance traceability and improve existing Quality Management Systems (QMS) in place. By using these virtual system models to analyze the causes and effects in the operating state, it is also possible to develop intelligent maintenance systems. Digital twins are becoming important components for competitive product development.

Post-processing tools enable full interactive data mining. This is supported through a variety of charts and tables which capture complex statistical evaluations in an easily understandable and presentable way. This capability builds another bridge between the world of hardware data and the world of simulation.

If you would like to learn more about how to apply these methods to help you deliver your product promise, you are invited to our conference. There you can hear engineers from BOSCH, Daimler and other companies who revolutionized their simulation process with these techniques and learn how you can apply CAE-based sensitivity analyses, optimizations and robustness evaluations with ANSYS optiSLang. The 14th Weimar Optimization and Stochastic Days 2017 will take place on June 1-2 offering focused information in practical training and interdisciplinary lectures.

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How To Optimize Your Industrial Operations With Digital Twins http://www.ansys-blog.com/industrial-operations-digital-twins/ http://www.ansys-blog.com/industrial-operations-digital-twins/#respond Wed, 10 May 2017 13:42:24 +0000 http://www.ansys-blog.com?p=18055&preview=true&preview_id=18055 The first issue of ANSYS Advantage for 2017 focuses on a revolutionary disruptive technology that you may just be starting to hear about: the digital twin. At the most basic level, a digital twin is a 3-D digital model of … Continue reading

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The first issue of ANSYS Advantage for 2017 focuses on a revolutionary disruptive technology that you may just be starting to hear about: the digital twin. At the most basic level, a digital twin is a 3-D digital model of an operating physical system. The physical system can be a jet engine, a power generator, a pipeline, a locomotive or an entire industrial plant. Someday, you will most likely have your own digital twin — a virtual copy of yourself — that will allow you and your doctor to predict the behavior of your body to fine tune treatments and optimize your health.

ANSYS Advantage Digital Twins issue

At the recent Minds + Machines conference, I learned that GE has deployed over 550,000 digital twins — an amazing accomplishment. I heard their VP of Software Research, Colin Parris, succinctly explain what a digital twin is and why we need it: “A digital twin is a living model that drives business outcomes.” I also heard GE Chairman and CEO, Jeff Immelt, synthesize how to implement a digital twin: Physics + Analytics = Digital Twins.

Discover how ANSYS is working with companies like GE and PTC, to leverage simulation as a key component of the digital twin, and how our companies complement each other’s strengths so any business can get the most out of digital twin technology.

In the leadoff editorial, ANSYS President and CEO Ajei Gopal makes the case that “Simulation is the only way to fully realize the tremendous value contained within the digital twin.” He describes how digital twins enable you to optimize the operations of your current product in its real-world setting, while also building a valuable database to improve the design of the next generation of your product. Eric Bantegnie, VP of Systems Engineering Business at ANSYS, examines best practices for realizing the digital twin vision.

Digital Twins

Chris MacDonald, Senior Director of ThingWorx Analytics at PTC, reveals how they used their ThingWorx platform along with ANSYS solutions to create a digital twin of a Flowserve industrial pump. GE Digital Chief Marketing Officer John Magee talks about how GE focuses on the Industrial Internet, as opposed to the wider Internet of Things, to target the digital twin market with their Predix software platform.

Beyond digital twins, this issue of ANSYS Advantage also contains articles describing Jet Towers Wi-Fi towerhow Siemens Mobility uses simulation to precisely control the temperature in passenger railway coaches for the comfort of the passengers; how Jet Towers of Santiago, Brazil, simulates the design of modular Wi-Fi towers that can be installed in one-fifth the time of traditional towers; and how startup PHAZR uses electromagnetic simulation solutions to develop a unique 5G millimeter wave system that is 128 times faster and has 1,024 times more capacity compared to 4G LTE.

This is just a sample of the full scope of this issue. I hope these articles encourage you to investigate where digital twins may fit into your company’s plans to “drive business outcomes.” Read ANSYS Advantage online today.

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The Next Generation of Aircraft is Different from Anything You’ve Seen Before http://www.ansys-blog.com/design-next-generation-aircraft/ http://www.ansys-blog.com/design-next-generation-aircraft/#comments Tue, 09 May 2017 14:35:55 +0000 http://www.ansys-blog.com/?p=18086 A few weeks ago I got a very close look at a F-35, and was able to talk a bit with one of the test pilots. “This is not an aircraft,” he told me. It’s more a kind of spaceship.” I believe … Continue reading

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A few weeks ago I got a very close look at a F-35, and was able to talk a bit with one of the test pilots. “This is not an aircraft,” he told me. It’s more a kind of spaceship.” I believe he is right. This is not an aircraft, at least not the kind of aircraft we are used to.

Two generations, face to face

Courtesy G.P. Torriani

This 5th generation of fighters still has a lot of detractors who believe that the cost of this aircraft was excessive. They went so far as to ask Boeing to price out a comparable F-18 Super Hornet. The press played up the angle that, in a simulation of a dogfight, the prototype of the mighty F-35 was badly beaten by a 40-year-old F-16 Falcon.

This made me think about an old story… but before I get into that, let me introduce myself and tell you why I talk so much about aircraft. I was recently appointed as the Global Aerospace & Defense Industry Director at ANSYS, a position that lets me follow two of my biggest passions: aerospace and technology. I have spent the last 18 years of my life advising companies about how to develop their strategic thinking around emerging technologies in product engineering, rapid prototyping, additive manufacturing and, of course, engineering simulation.

But my first passion is aeronautics. When I was a child I lived close to an Air Force base. They had old F-104 Starfighters, and every time they scrambled into the sky, I rushed to the window to see the long tail of the afterburners as they got smaller and smaller. Years later I joined the Italian Air Force and started my military pilot training. Though my career took a different path, I still fly regularly to this day and I try to learn as much as I can about aerospace.

Now let’s go back to our story.

Would you believe me if I told you that the old F-104 was able to outperform the new, super-maneuverable F-16? The F-104 is a small aircraft with almost no wings and a small tail. Its radar signature is pretty small — too small to be detected by the first version of the F-16’s radar. During the first combat exercises, the F-104 pilots were able to avoid detection by the radar on the F-16 and surprise the F-16 pilots, who were looking for enemies on their green screens and were flying high (and were therefore visible to the F-104 pilots) so they could use their radar.

After suffering these first ’embarrassing’ defeats, the F-16 pilots started to look for EMI emissions to localize the F-104s, but the F-104 pilots countered this move by switching off their IFF and radios to stay invisible. In this way, the F-104s maintained a very good winning ratio versus the F-16s, until the airborne warning and control system (AWACS) came onto the scene. The AWACS’ integration of different sources of sensors and information for detecting the F-104s made the F-16s unbeatable.

The new generation of fighters
So how does this apply to the F-35? In both cases (F-35 versus F-16, and F-16 versus F-104), the new, superior technology was initially beaten by the older technology. These unexpected outcomes happened because the newer technology was not equipped with the full operating capabilities it would ultimately have. The F-35 was not designed with dogfights in mind. As I said at the beginning of this article, the F35 is not (just) a fighter aircraft. It is a piece of an incredibly complex puzzle that is well described by the “Air Force Future Operating Concepts” document, whose central idea is that “In 2035, Air Forces will leverage operational agility as a way to adapt swiftly to any situation or enemy action. Operational agility is the ability to rapidly generate — and shift among — multiple solutions for a given challenge,” and it requires an unprecedented situational awareness for the pilot and their command centers.

We are shifting the priorities from air superiority, air reconnaissance and coordination of air defense to a more multi-domain command and control that includes global integrated ISR, rapid mobility and adaptive response. In this scenario, information is vital. What the Air Force is expecting from the F-35 is much, much more than to win in a dogfight against an opponent. They are expecting the F-35 to be a piece of a vast network, able to collect information, elaborate scenarios, use artificial intelligence to create awareness and suggest options, and respond quickly to any threat. In this environment, every aircraft is a sensor, a node of a network, and can receive, send and evaluate information.

Let’s discuss how to design them at the ANSYS Pacific Northwest Innovation Conference in Seattle

Of course, this shift from individual aircraft to aircraft systems is creating a number of challenges in aircraft design. Engineering simulation will play an increasingly bigger role in solving these challenges as the complexity of these systems increases. I’ll talk about some of these challenges in defense and commercial aviation, together with some other great speakers, at the ANSYS Pacific Northwest Innovation Conference on May 23rd in Seattle. Please join us to catch up on the latest aerospace developments and learn how simulation can help you meet the demands of this quickly changing market. You can find more information and register today.

I look forward to meeting you in person in Seattle.
If you can’t be there, please connect with me through LinkedIn or Twitter.

 

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ANSYS HPC: On to a Million Cores! http://www.ansys-blog.com/hpc/ http://www.ansys-blog.com/hpc/#comments Thu, 04 May 2017 18:41:14 +0000 http://www.ansys-blog.com?p=18249&preview=true&preview_id=18249 ANSYS CFD is on the verge of a second renaissance in high-performance computing (HPC). The first, spanning more than a decade, has seen tremendous leaps in both the depth and breadth of HPC capabilities. Depth (or heights, rather) in the … Continue reading

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ANSYS CFD is on the verge of a second renaissance in high-performance computing (HPC). The first, spanning more than a decade, has seen tremendous leaps in both the depth and breadth of HPC capabilities. Depth (or heights, rather) in the size of the scalable clusters — first 1000s, then 10K, and recently 100K core counts — and breadth of coverage across solvers, physics, post-processing, even file I/O, covered the gamut of high-performance simulations. The trend, in fact, is exponential, as evident in this chart, and spans many years of ANSYS Fluent software releases. While there are other impressive scientific scalability demonstrations, ANSYS Fluent set the standard for industrial HPC CFD simulations.

Meanwhile, things have been both heating up and cooling down in the world of HPC. Larger scale-out systems and faster interconnects have pushed usable core counts higher, while cooler and more energy efficient processors, vector architectures, GPGPUs, consolidation in the cloud, etc., led the way to more diverse and sustainable HPC hardware ecosystems.

Modern and upcoming HPC systems present a truly mixed bag of performance and efficiency choices that require careful re-tuning of software components. From hybrid programming for shared/distributed clusters dawned the era of heterogeneous computation including accelerators such as GPGPUs and Intel Xeon Phi, and associated parallel patterns and programming languages. Continuing to enhance scalability and throughput in this new computational environment in order to meet the increasing demands of industry to support their simulation-driven product development processes is the challenge of the coming years.

Would ANSYS Fluent, in spite of the new trends, inexorably push to a million CPU cores by 2020 as the chart predicts? The sheer scale — a million cores — seems hard to imagine, yet is only 3 years away! There are certainly cross-winds this time and only time will tell. But, in HPC, it will be sooner than we’d expect, so are you ready to harness the power of HPC simulation?

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The Great Mobility Revolution – Planes, Trains and Automobiles http://www.ansys-blog.com/mobility-revolution/ http://www.ansys-blog.com/mobility-revolution/#comments Tue, 02 May 2017 13:29:54 +0000 http://www.ansys-blog.com?p=18205&preview=true&preview_id=18205 For most of human history, our mode of mobility was feet — our own feet, or those of some domesticated animal. Whenever we wanted to go somewhere, we walked or used horses. These quadrupeds remained the dominant mode of inter-city … Continue reading

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For most of human history, our mode of mobility was feet — our own feet, or those of some domesticated animal. Whenever we wanted to go somewhere, we walked or used horses. These quadrupeds remained the dominant mode of inter-city and intra-city transport for over two thousand years. Then in the mid-nineteenth century, the mode of inter-city transport changed over from horses to railways. Another half a century later the horse also disappeared from cities and towns as intra-city transport was taken over by automobiles. In the mid-twentieth century airplanes became the dominant mode of inter-city travel in North America, with railways continuing in addition to airplanes in Europe and Asia.

And that’s where we are today — stuck with trains, planes and automobiles for nearly a century. But not for long.

As Ford’s CEO, Mark Fields, recently said,

“We are on the cusp of a mobility revolution.”

And it is not going to be anything short of a great mobility revolution. We can expect to see a total transportation transformation. Intra-city transport is set to be revolutionized by autonomous vehicles and ride-sharing and may be even drone flying-cars, and inter-city travel by innovations such as the hyperloop.

If I have to pick one legendary figure who personifies this great mobility revolution, hands-down it would be Elon Musk. His combination of visionary audacity and grit to persevere through incredible odds, is a once-in-a-generation phenomenon. And when that force has trained its eyes on the mobility industry that has remained in an evolutionary rut for nearly a century, a great transformation is all but inevitable.

At last week’s TED 2017 —The Future You conference, Elon Musk sat down with TED’s Head Curator, Chris Anderson, and talked at length about his entire arsenal of revolutionary projects from Tesla to SpaceX to Hyperloop and to the latest The Boring Company. Not only is he revolutionizing intra-city and inter-city travel, but also inter-planetary travel. He has plans to build a rocket that can carry the equivalent of a fully loaded 747 jumbo-jet as its payload, all the way to Mars, with the aim of establishing a human population of 1 million on Mars within Musk’s lifetime. Now that is audacious! And absolutely, incredibly, exciting!

Watch Musk’s full talk here. And get ready for the great mobility revolution!

For information on how ANSYS is helping to drive the mobility revolution (pun intended), please check out our whitepaper Fast-Tracking Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles Development with Simulation.

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