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Designing the Hyperloop Dream: A Collaborative Design-to-Manufacturing Journey by a Team of 50+ Students with Autodesk Fusion

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Description

Considering the imminent climate crisis, we need to reduce our emissions drastically. However, at the same time, the mobility sector is steadily growing. One solution can be the Hyperloop, promising shorter travel times than air passenger travel with fewer emissions. mu-zero HYPERLOOP is a team of 50+ passionate students from the Karlsruhe Institute of Technology (KIT) with a mission to contribute to a sustainable future of transportation. Each year, we design and build a Hyperloop Pod using Autodesk Fusion software, and ultimately compete very successfully against other teams at the European Hyperloop Week (EHW). This session will explore how we use Fusion to design and manage a complex project with 25,000+ components and collaborate with 50+ team members. Learn how to use Fusion as a comprehensive platform for concept sketching, simulation, generative design, and the handling of large assemblies and streamlined manufacturing workflows.

Key Learnings

  • Learn how we develop and optimize product generations, manage large and complex models, and get better each year.
  • Learn the key ideas behind the Hyperloop Pod development, and hear about our journey from concept to manufactured reality.
  • Learn about the benefits of the Autodesk Fusion platform for student engineering teams and effective onboarding of new team members.

Speaker

  • Johannes Anton Mootz
    Johannes is a mechanical engineer who graduated from the Karlsruhe Institute of Technology in Germany and is currently a PhD candidate in San Diego. He is the former lead structural engineer of the mu-zero Hyperloop team, a student club dedicated to developing the future of mobility. His work contributed to the development of the award-winning prototype showcased at the European Hyperloop Week.
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Transcript

JOHANNES MOOTZ: Welcome to my presentation, Designing the Hyperloop Dream, a collaborative design-to-manufacturing journey by a team of 50-plus students with Autodesk Fusion. I'm Johannes Mootz, your host for today. I'm a former team lead from the mu-zero Hyperloop team from Karlsruhe, Germany. I'm a mechanical engineer, and currently I'm doing my PhD in San Diego.

Let's start with today's learning objectives. Number one, learn the key ideas behind the Hyperloop Pod development and hear about our journey from concept to manufactured reality. Two, learn how we develop and optimize product generations, manage large and complex models, and get better each year. And three, learn about the benefits of the Autodesk Fusion platform for student engineering teams and effective onboarding of new team members.

So before we start, I want to give you a sneak peek about today's topic.

[INCREASING SUSPENSE SOUND]

[MUSIC PLAYING]

So I hope you enjoyed this teaser about our project. And you've heard probably some key words like the Hyperloop technology or Athena. And I would like to cover those in my presentation. But first, let's start with the Hyperloop technology in general. So what's the concept of a Hyperloop?

Hyperloop is a transport vehicle that floats through an airless, near-vacuum tube close to the speed of sound. It's so fast because it minimizes the friction via magnetic levitation. And it minimizes the drag via low-pressure tubes. Overall, it can be a highly efficient system with the potential of integrating renewable energy sources.

And as you can see in the figure on the right-hand side, the energy need per passenger and kilometer traveled is significantly lower than for cars or airplanes. It's about the same for trains, just with the difference that Hyperloop is three times faster.

And you might ask, why do we want to do that? What's our vision? First, we want to address the climate crisis by pioneering the future of sustainable mobility. As we know, the climate crisis is one of the most urgent problems we have to solve. And we as a student club want to contribute to that goal.

The second point is we want to link global cities through innovative transportation solutions. There's a high volume of passenger transport, especially between big cities, which is often carried out by short-haul flights. And they contribute to a lot of the CO2 emissions. And the third goal is, we want to enable high-speed travel with maximum efficiency. So there's a need to travel fast. And we want to make it just convenient and safe and reliable.

Next, I would like to introduce you to the team, to all the amazing people that have made it possible. As I said before, we are a student club from Germany. We are called mu-zero Hyperloop. Mu-zero is quite a technical name. It refers to zero-friction coefficient of the mu. And here, we try to achieve that with our Hyperloop prototype. We have members from four different universities in Southwest Germany. And our headquarter is in Karlsruhe.

Here are some stats about mu-zero Hyperloop. Currently, we have 63 students from 11 field of studies, mostly from engineering. We have members from 20 nationalities. And we share one common vision, which is creating the future of mobility. Our organization is divided into two big divisions, technology and operations, each consisting of teams.

On the technology side, there are seven teams, such as structure and packaging, propulsion, aerodynamics, levitation and guidance, software, electronics, and track. And they basically deal with all the technical aspects of the prototype development. And on the operations side, we have four teams-- marketing, finance, event management, and sponsoring. And they keep the business running.

Next, I would like to give my team a chance to introduce themselves.

[MUSIC PLAYING]

ADAM FAWZY: Being a part of mu-zero is a learning experience.

ALEXANDER GABALLA: I believe in mu-zero, that we are not selling a product, but we're trying to reach out a vision. We are promoting the idea of a global new system of transportation that might revolutionize everything that we've known so far.

FELIPE NARANJO: To me, mu-zero is learning about design, industry, leadership, but most important, teamwork.

[MUSIC PLAYING]

STINA WALLER: I believe that working at mu-zero has taught me and will teach everyone a lot about how to work in a team, how to become better engineers as well. And I think in that way, we can kind of shape the future of transport.

[MUSIC PLAYING]

TIA HAMMOUD: Working in mu-zero has really helped me create a more well-rounded experience in my university life because being in this team has really allowed me to see first-hand everything I've been learning so far.

ANA BAKALOVA: Through my time in mu-zero, I have been able to learn how to be a dedicated team member. And I think that will be quite beneficial to my future career path.

SAIF HASHEM: It actually gives you the chance to go for it, to skip all the bureaucracy, to just build, build the prototype of the future.

[MUSIC PLAYING]

ADAM FAWZY: The coordination of the whole team this season, in my opinion, is simply beautiful. We have 63 students from 20 different nationalities. And it is honestly the perfect environment for technology that is so out of the box like Hyperloop technologies.

[MUSIC PLAYING]

AHMAD KHEIR: Part of the vision for the season is to create new markets for technologies that already exist so that we work together with different companies on ameliorating the Hyperloop technology in general. Each of our division had its own goal. And we worked all together with sponsors, the team, and we achieved like the product that you can see in front of you.

STINA WALLER: My team, structure and packaging, is responsible for four main things-- the frame, brakes, wheels, and lastly, the LIM harness.

BENEDICT BASCHANG: So the main task of the electronics team is, of course, providing power to every system.

IZAK KANTER: Our team is responsible for making the pod move with a linear induction motor.

FELIPE NARANJO: The main goal of the guidance team is to achieve a precise positioning of the pod along the track.

TIM MAIER: Our responsibility this season is to build a track that's safe and reliable for the other divisions.

KARL SASSIE: The software team is responsible for all of the embedded components. A very big focus this year was also put on the control panel with some very nice data visualization.

AHMAD KHEIR: Students are usually looking for places to discover things about themselves and to open up opportunities. And I think this year is the right place for that. So make sure to sign up and join our vision.

[MUSIC PLAYING]

JOHANNES MOOTZ: So this was the members of our current season. But mu-zero started earlier than that. Our start was in the year 2021, when mu-zero was founded. In the very first year, we were able to build a prototype. And that could propel, which was pretty amazing given the short time. In the second season, we changed our system to a high-voltage system. And that allowed us to achieve speeds up to 120 kilometers per hour.

In the third season, we improved our system by implementing a stable levitation system. And it worked so well, it could handle a lot of different loads and was still a stable system. So what's left? you might ask. What's our goal? So in our last season, we wanted to integrate all of our knowledge we gained in the previous years into one fully functional prototype. And now, I would like to show you how we did that.

Each year looks kind of similar in our student club. We start with a concept phase in the fall. Then we have a design phase in the winter, going to a manufacturing phase in spring, and then ending in the implementation phase in summer. In phase one, the concept phase, most importantly, we define our goals before each season.

So as I said before, we wanted to integrate all of the subsystems. And precisely, we wanted to achieve a true contactless maglev. A maglev is a magnetic levitation train. Our second goal was to implement wireless power transfer so we were completely independent off battery power. And the third goal was to design a long, modular track to have a good distance to drive tests. Some key activities of this phase were the cabin weekend where we all came together and brainstormed over initial drafts. But we also had a lot of fun.

Phase two is the design phase where we improved our ideas to CAD models. We also made the necessary calculations for the loads. And we validated our designs with FEA simulations. This is usually the busiest phase for all the teams, especially the engineering teams. And we put in a lot of effort and work.

Phase three is the manufacturing phase. In this phase, we either collaborate with industry for manufacturing large or milled components, as you can see in the picture. But we also have our in-house production of smaller parts, including 3D printing. In this phase, usually the first challenges emerge since initial design flaws reveal and make us to come to quick solutions and decide what to make from our mistakes.

In the last phase, we assemble all the components to one prototype. We perform tests to ensure functionality and safety. And we prepare for the European Hyperloop Week, which is the competition that took place in Zurich, Switzerland in this year.

So European Hyperloop Week-- what's that? It's an annual event. And as I said, it took place in Switzerland at Zurich this year. It features a competition between over 26 teams from around the world. And the goal is to produce the best Hyperloop pod. But that's not the biggest goal. It actually is much more about collaboration and networking with the other teams. For example, it's amazing to see how teams collaborate with each other and help each other out, for example, when there is a tool missing and some material missing.

And now, I have some impressions for you from this year's Hyperloop Week. So the most important day of the week is the demonstration day, where all the teams present their prototype to the public. Here you can see our prototype, our test bench, and see some audience standing around. Now, we had a pretty good prototype, so we won some awards in the end. I will come to that later. But we also had a lot of fun as a team and could celebrate the completion of one year of hard work afterwards. So that's all about us, our team.

And now I want to speak about how it was made possible. As you can imagine, building a Hyperloop is not cheap, of course. We do that all as volunteers, but material and production costs are still pretty high. So we are dependent on sponsors. And we are very glad that we have Autodesk as a sponsor for years right now. Without them, it wouldn't be possible to build what we are building.

But it's not only financial contributions that help us. We have also the chance to partner with Autodesk on the Hanover Messe in Germany, which is an industry fair. And it was a great opportunity for us to get more traction and attention, speak with other potential sponsors, get inspired by the latest technology advancements, and so on.

Another way to help us is workshops, such as the workshop for Fusion we got through all of this. It's very important for us to get new members a solid start into the program, especially since engineering students from Karlsruhe will learn on another CAD platform. But Fusion is actually a pretty good tool because it's easy to learn for us, and there's a steep learning curve. That covers the software side.

We also have a hardware side, which is manufacturing support. Here, we collaborate with local manufacturing companies around Karlsruhe. And they help us to build the large parts we can't do on our own. And if you have-- or if you take a look at it more abstractly, what we actually do is design product generations. So we just do what companies do, just on a smaller scale and as a student club.

But that also means we face similar challenges. For example, one is the management of over 30,000 components in one model. And the next challenge is a very volatile environment with over 80% fluctuation rate each year because we have a lot of members who are just there for one year, then leave. And we have to onboard a lot of other members in a fraction of the time.

So how can we keep the knowledge we've gained and pass it to the next team? To tackle that challenge, we have developed a strategy, which is based on three areas. The first one is the onboarding phase. It's super important when the new team is coming in that they are mentored by the corresponding member or team lead from the year before. That way we can make sure that the knowledge is transferred to the next generation.

The second step is, as I mentioned earlier, the workshops, for example, the Fusion workshop. It's an essential tool for us to get professional with the tools we are using. And the third point is Fusion itself. We have created a folder structure within Fusion that keeps all our information stored in an ordered manner and helps others and other teams to see what we've done and to get a better idea what the previous years looked like.

I would like to show you what we did. So the structure of our Fusion organization stays the same for every team. But we integrated two different phases, which are aligning with the concept and the design phase. In the concept phase, we create many ideas and learn Fusion, get the skills to operate Fusion, and have a first understanding.

And then we draw a line through a concept freeze and start with the design phase. And in that phase, we start over again. So we're not using the maybe mistakenly wrong-made models from the first phase. But we try to get a fresh start and make sure that the initial design flaws are way less.

Working with Fusion does not only help us with our product generation management, we exploit it in a lot of other different ways, such as FEA to the topology optimization. We are using the generative design a lot. As I said before, we are working on very large assemblies with over 30,000 parts. And we're working with over 40 people on one model at the same time.

Now I would like to get more into detail about our prototype, how it operates and what's the science behind, and how could that be better visualized by another video.

[MUSIC PLAYING]

NARRATOR: Prepare to witness the dawn of a new era in transportation with mu-zero's season-four Hyperloop pod prototype. Join us in exploring the marvels of mu-zero's groundbreaking Hyperloop pod prototype, where every component is meticulously designed to redefine the future of transportation.

Our shell, made out of natural fibers, enhances efficiency by minimizing drag and meeting structural needs for higher speeds. At the heart of our innovation lies a precisely designed rigid frame made up of several key components surrounded by dampeners to minimize vibrations. The chassis, a symphony of precision engineering, where ribs, bridges, and base plates converge to ensure unparalleled strength and safety.

Our minimalist emergency brake subsystem crafted from laser-cut aluminum and precision milled blocks ensures simplicity without compromising effectiveness. The wheels, versatile and robust, effortlessly handle transportation duties while doubling as a fail-safe mechanism during emergencies. Our LIM harness is precisely crafted with premium materials, seamlessly integrating with the double-sided linear induction motor for unwavering stability. It generates thrust through a moving magnetic field interacting with an aluminum secondary.

The modular levitation and lateral guidance systems are powered by the precision of electromagnetic suspension that ensure the efficiency of the system. Six modular levitation units maintain a consistent levitation, offering flexibility with detachable connections. The modular guidance system is the cornerstone of the pod safety for precise lateral positioning along the track. A closed-loop liquid cooling mechanism is employed to maintain the modular levitation units and the double-sided linear induction motor within its specified temperature range.

Our wireless power transfer system, the Movitrans developed by SEW, fuels our Hyperloop with sustainable energy, propelling us into a greener future. But that's not all. Our 20-meter track, engineered for scalability, opens doors to a world where Hyperloop travel knows no bounds. Join us on this journey into the future.

[MUSIC PLAYING]

JOHANNES MOOTZ: So just to wrap things up, here's another visualization of our path. Most importantly, we have the levitation and the guidance units that helps us to levitate and stay in track. But we also have a cooling system that prevents the magnets from overheating.

We have super capacitors that store the energy we need. We have a converter box for the wireless power-transfer system. We have electronic boxes where all the control is stored in. And we have emergency brakes in case the power is shut down and we have to come to a quick stop. That might have been a lot of information. And don't worry, I will cover all the different topics in the next slides.

Let's start with the structural frame. It's the base of the prototype, and it incorporates mounting points for all the other components and connects them. Most importantly, it's the structural integrity we want to achieve. So that means the frame should not break or bend under different loads. This is prevented by doing FEA simulations and run them iteratively over many times and make sure that it doesn't break or bend in any circumstance.

But it's all about the durability. It's all about light weight. So that's where Fusion topology optimization comes in. As you can see, at some parts, there's no material. And that's the parts where the part doesn't need a material fill to support its structural integrity under the loads.

It's of high importance that we maintain high tolerances at all times. And that was the reason that we decided to use waterjet-cut sheet aluminum, and we welded them together with high-precision laser welding. The track is the infrastructure the part needs to operate. It has interfaces for the levitation, the guidance, the wheels, and the LIM. The LIM is the Linear Induction Motor.

The interfaces are just steel rails and aluminum rails for the LIM, and they are made of a cost-effective structural steel because we wanted to have a long track. We also used a lot of 3D-printed components because they're cheap. And we used standardized screws to make it easier to assemble the track each time. The track is also designed for a scalable design and an easy adjustment for potential other pod geometries.

The aerodynamic shell is designed for velocities up to three meters per second, which is not that much. But we will increase in the future with longer tracks. But of course, we did computational fluid dynamics analysis here to ensure that it's aerodynamic and it's both functional and aesthetic.

Of course, if we are in a vacuum tube, which is our final goal, then the aerodynamic component isn't that important. But until then, we are testing on field with air around. The shell is fabricated with natural fibers for an environmental-friendly approach.

So the heart of our prototype consists of the propulsion unit, which is a double-sided linear induction motor. It has two stators and one rotor, like a usual electric motor, just that they are configurated in a linear way. So the resulting force is a translation force. It's capable of delivering one meter per square second acceleration, 300 newtons thrust, and speeds up to 15 kilometers per hour, with just three kilowatts of power. It's designed in a way that it can be scaled up and be applied to larger systems.

The levitation and guidance system consists of electromagnets. So electromagnets are just magnets that are powered with current. And by controlling the current, you can control the force the magnets have. The system is based on an attraction-based levitation. So it's pulling itself toward the track up rather than repelling from the floor. And it's equipped with six magnetic levitation units. And they are customized electromagnets.

We also have four guidance units. They help us to stay in track, stay centered, and not leave the track on the side. The magnets, they have an adjustable current control that maintains a six-millimeter air gap to the track independently of the load.

Coming to electronics-- to control all of the motors and magnets, we have eight printed circuit boards for the control. We also replaced the heavy batteries with lightweight supercapacitors. They have the advantage that they can deliver the power way faster than the usual batteries. And we are utilizing the Movitrans contactless energy system by SEW. And that enables us an uninterrupted operation, which is theoretically driving forever.

That was a small technical demonstration. And now I'd like to emphasize what we have learned on our journey. First, our efforts have not been unrecognized. We won several awards at the European Hyperloop Week. If I may pinpoint one highlight, which is second place in the complete pod category, and this year it's a newly invented category. And we can proudly say that we were the second-best student team in the world. But of course, we are aiming to attack the first place in the next competition.

But it's not only about the competition. It's much more because we can learn so much as being a team and getting to solve the problems together. It's also an amazing opportunity to actually get the hands dirty and apply the university knowledge to a real project.

And you can learn to grow as a team member but also as an individual by learning to be creative and learn to analyze the system. And most importantly, we actually can contribute with passion to the goal of creating the future of mobility and have a positive impact on the environment.

So where's all that fancy Hyperloop idea heading? In general, as I said before, it's an idea to travel super fast. It has the potential to reach speeds over 1,000 kilometers per hour, which is about 620 miles per hour. And that can be done with zero direct emission. However, there are some challenges, such as high infrastructure costs and safety standards, all problems that can be solved and tackled. And we are working on that in our upcoming generations.

There's a new program that has been launched in Europe, which is the Hyperloop Development Program. It's a partnership that is dedicated to develop the Hyperloop as upscaled mode of high-speed transportation. And now all what is left to say is, let's create the future together. Thank you for all your attention. Goodbye.

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We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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