Designers of next-generation prosthetic devices and exoskeletons (or orthotics) are faced with the high cost and time requirements of prototyping — a process that can take years and has no way of pretesting candidate designs. One wrong choice (i.e., a spring that’s too stiff, a motor that lacks power or is too heavy, etc.) and you’re back to the drawing board — older and only a little wiser.
Clinicians face a different, but related problem: how to determine the right device for each patient. Today’s options range from those offering basic support to those with high-tech composites and embedded microprocessors but, unfortunately, there is no simple and objective way to compare these options. Clinicians make their best estimate based on their training, experience and knowledge of the patient; the patient then tries the recommended device, and everyone hopes for the best. If the device isn’t a good fit, options for modification or replacement can be limited.
Over the last couple of years, more and more companies are wrestling with the same question: “Shall I continue to invest in on-premise hardware or switch to cloud computing?” I usually respond: “Well, it depends. …” Because it depends on their business, use cases, infrastructure and other factors, I advise them to carefully consider eight important questions.
How connected are you to the amazing new technology surrounding you? With all the smart connected products that are being developed and deployed today, we can all be connected to our environment as never before. If you are the owner of smart home technology, you may be enjoying the benefits of voice-activated lighting, security and robotic vacuuming. Perhaps you own an Amazon Echo or a Google Home device that makes your life easier and more fun by answering questions you call out in any room of the house, or plays the music you want to hear at your command — no typing required! Maybe you have a personal health monitoring device that you wear on your wrist to count the number of steps you take or measure your hours of sleep and/or heart rate — all of which can be uploaded to a computer to keep track of your health goals.
It is well-known that in the middle of a cycling peloton you ride “sheltered from wind” and, therefore, experience less air resistance. But how much less has never been thoroughly investigated. Earlier research with small groups of riders has shown that riders in the middle of the pack encounter 50 to 70 percent of the air resistance experienced by an individual rider. And this number has been extrapolated to the whole peloton. However, professional riders and coaches suggest that when you’re well-embedded in the belly of the peloton you “sometimes hardly have to pedal,” so the air resistance must actually be much lower.
My teams at Eindhoven University of Technology in the Netherlands and KU Leuven in Belgium, in close collaboration with ANSYS and supercomputer company Cray, found that in the middle of a peloton, racing cyclists experience just 5 to 10 percent of the air resistance they face when cycling alone. This is about 10 times less than was previously estimated, and was demonstrated by computer simulations and wind tunnel research on a peloton of 121 cyclists. Both methods, performed independently, produced the same results, which can explain why so few escapes in road cycle races are successful: The assumptions contained in the calculation models that race teams use to determine their strategies are incorrect.
Generally, the size and cost of electric machines (motors or generators) are more closely related to the machines’ torque rating than to their power rating. Thus, if two machines are rated for the same power at different speeds, the higher-speed machine will be smaller and less expensive than the lower-speed machine. Therefore, it is common to use gearing to reduce the machine size and cost in many systems. Mechanical gearing, however, introduces acoustic noise, maintenance requirements and reliability concerns into the system. On the plus side, magnetic gears can perform the same function as mechanical gears, transferring power between low-speed, high-torque rotation and high-speed, low-torque rotation, without relying on mechanical contact for this power transfer. This non-contact operation allows magnetic gears to avoid some of the issues associated with mechanical gears, and reduce the size and cost of an electric machine, especially in applications where minimal maintenance and high reliability are important (e.g., wind turbines and electric vehicles).
Additionally, by integrating the magnetic gear with the electric machine, the system size and cost can be further reduced. The Advanced Electrical Machines & Power Electronics Lab (EMPE) at Texas A&M University invented a configuration that places an axial flux machine in the bore of an axial flux magnetic gear to produce a very compact device capable of producing very high torques at low speeds.
Earlier this year we kicked off the ANSYS Discovery Live Engineering Design Competition on the heels of the Discovery Live technology preview. Judging by the feedback and participation, it was a tremendous success. Many users shared stories of their simulation-aided design innovations and spoke of the knowledge they acquired from simulation — without the need for supercomputing. Initially, we selected three winners; in this blog, we wish to shine a spotlight on our first-place winner, Ninsight’s Michael Stadler. Continue reading →
The drone segment is among the fastest growing in the aerospace industry. Although initially focused on military applications, the segment is now rapidly expanding into the commercial realm. According to Statista, the sector’s 2015 value was already $127 billion and growing.
In this increasingly competitive market, the company that comes up with the best drone designs wins, and the battle is on for performance (endurance, payload, cameras/sensors/antennas) and safety (reliability, robustness, bug-free control code). Because drone producers need to keep development costs as low as possible, while innovating faster in an arena full of inexperienced players, it shouldn’t be a surprise that simulation is playing a major role.
Back in February, we announced a new multiphase capability in ANSYS Fluent that speeds up accurate spray simulations using a unique hybrid volume of fluid (VOF) to discrete phase model (DPM) method. You can learn more in a blog written by my colleague Muhammad Sami. We recently ran a webinar on this new capability that garnered great interest. In the past, spray simulations required substantial computing resources to complete with accuracy. This VOF-to-DPM capability requires much less computing time, making it practical to solve a much wider range of problems, including those involving wider length scales. For these problems the focus is to transition large-scale spherical structures in a VOF field to droplets in a Lagrangian field. This helps in optimizing computational resources without compromising the accuracy.
While this approach is great for modeling sprays, there are other problems that start with particles and end with continuous fluids. For example, a spray of droplets impinging on a wall and forming a film or rain falling on a pond. Now we have developed a Fluent user-defined function (UDF) that converts Lagrangian droplets back to a liquid phase in the Eulerian VOF model. Intelligence has been added to the DPM-to-VOF transition algorithm that ensures the transition happens close to the wall or liquid-gas interface, thereby dynamically refining the area occupied by the chosen parcel before conversion and converting only the parcels that are going to hit the wall or liquid-gas interface.
New model speeds simulations, as shown for spray impinging on a wall. The DPM model tracks the droplets until they merge, when they are then tracked by the VOF model.Continue reading →
The aerospace industry is challenged to design more fuel-efficient, quieter and safer aircraft in the face of increasing pressure to reduce operational cost, increase production rates of aircraft and explore new concepts of air mobility. At the same time, global defense spending is increasing as organizations innovate to maintain or establish technological leadership, in pursuit of weapon systems that can be upgraded quickly and often to keep their operational capabilities and lethality intact. The new space race has begun: New companies and nations are challenging the historic dominance of a small number of government-funded agencies, opening the way for commercial exploitation of space and making it a viable solution for more players.
All sectors of the aerospace and defense (A&D) industry are confronting a demand for innovation that is accelerating at a pace never seen before. The ability to seize the opportunities from the disruptive forces of emerging technologies, materials and business models is critical for all organizations — newcomers and established leaders — not only to prosper, but also to survive in the industry.
I spend a lot of my time visiting our commercial and academic customers around the world, and we are talking more and more about how to speed up initiatives based on autonomy, electrification, connectivity, digital twins, new materials and additive manufacturing. Continue reading →
At IIT (Illinois Institute of Technology) Motorsports, we had a challenge. Our student team of 30-plus motivated engineers wanted our Formula car to go fast, but we also needed to create a great amount of downforce so that the car sticks to the racetrack and can perform high-speed turns. The problem is that increasing the downforce increases the drag. The solution is to fit the car with a drag reduction system (DRS) in the style of Formula One cars, in which parts of the rear wing (the second and third elements, in our design) will be rotated about their quarter chord point to an angle of attack at which they generate less downforce. This reduces drag when the car is moving in a straight line while allowing activated by control systems based on driver action rather than direct driver inputs. The CFD simulation images depict the ON and OFF settings for the system.
Rear wing ADRS OFF: The wings create an increased downforce that allow the driver to perform high-speed turns safely.
Rear wing ADRS ON: The wing positions create minimum drag and allow the driver to go as fast as possible.