February 5, 2016 — Brian Wood, Technical Writer, Technical Communications and Strategy Group
“What are the odds?” This phrase is often tossed around to point out seemingly coincidental occurrences, and it’s normally intended as a rhetorical question. Most people won’t even wager a guess; they know that the implied answer is usually “very slim.”
However, I always find myself fascinated by this question. I like to think about the events leading up to a situation and what sorts of unseen mechanisms might be at work. I interpret the question as a challenge, an exciting topic worthy of discussion. In some cases the odds may seem incalculable—and I’ll admit it’s not always easy. However, a quick investigation of the surrounding mathematics can give you a lot of insight. Hopefully after reading this post, you’ll have a better answer the next time someone asks, “What are the odds?”
February 3, 2016 — Bernat Espigulé-Pons, Consultant, Technical Communications and Strategy Group
When I hear about something like January’s United States blizzard, I remember the day I was hit by the discovery of an infinitely large family of Koch-like snowflakes.
The Koch snowflake (shown below) is a popular mathematical curve and one of the earliest fractal curves to have been described. It’s easy to understand because you can construct it by starting with a regular hexagon, removing the inner third of each side, building an equilateral triangle at the location where the side was removed, and then repeating the process indefinitely:
If you isolate the hexagon’s lower side in the process above you’ll get the Koch curve, described in a 1904 paper by Helge von Koch (1870–1924). It has a long history that goes back way before the age of computer graphics. See, for example, this handmade drawing by the French mathematician Paul Lévy (1886–1971):
January 28, 2016 — Stephen Wolfram
Six and a half years ago we put Wolfram|Alpha and the sophisticated computational knowledge it delivers out free on the web for anyone in the world to use. Now we’re launching the Wolfram Open Cloud to let anyone in the world use the Wolfram Language—and do sophisticated knowledge-based programming—free on the web.
It’s been very satisfying to see how successfully Wolfram|Alpha has democratized computational knowledge and how its effects have grown over the years. Now I want to do the same thing with knowledge-based programming—through the Wolfram Open Cloud.
Last week we released Wolfram Programming Lab as an environment for people to learn knowledge-based programming with the Wolfram Language. Today I’m pleased to announce that we’re making Wolfram Programming Lab available for free use on the web in the Wolfram Open Cloud.
January 19, 2016 — Stephen Wolfram
I’m excited today to be able to announce the launch of Wolfram Programming Lab—an environment for anyone to learn programming and computational thinking through the Wolfram Language. You can run Wolfram Programming Lab through a web browser, as well as natively on desktop systems (Mac, Windows, Linux).
January 18, 2016 — Håkan Wettergren, Applications Engineer, SystemModeler (MathCore)
Wolfram SystemModeler is a tool for multidomain analysis. One area with many multidomain applications is hydraulics: fluid power systems. Fluid power is one of three main methods of transmitting power. The other two are mechanical transmission, via gears and shafts, and electrical transmission, via wires. In SystemModeler, all three can be used at the same time without any restrictions or simplification.
This blog describes how the SystemModeler hydraulic library can be used in education, but the focus is not only on the hydraulic part. The idea is also to show how to build up an interesting, real application where hydraulics play an essential role. In the model it is then possible to study the effects of filter locations, choose valves, adjust settings, study different oil grades, etc. This post may also give ideas to hydraulic engineers used to working with conventional software as to what more can be done with SystemModeler compared to the standard software.
January 12, 2016 — Jenna Giuffrida, Content Administrator, Technical Communications and Strategy Group
As this new year begins and the books keep rolling in, we are happy to share with you an exciting new selection of texts featuring Wolfram technologies. If you’re looking for a New Year’s resolution for 2016, why not consider learning how to use Mathematica or the Wolfram Language? In this post are several books for beginners in English, German, and Japanese, as well as more advanced books for those who are looking to sharpen their skills.
January 7, 2016 — Devendra Kapadia, Mathematica Algorithm R&D
Partial differential equations (PDEs) play a vital role in mathematics and its applications. They can be used to model real-world phenomena such as the vibrations of a stretched string, the flow of heat in a bar, or the change in values of financial options. My aim in writing this post is to give you a brief glimpse into the fascinating world of PDEs using the improvements for boundary value problems in DSolve and the new DEigensystem function in Version 10.3 of the Wolfram Language.
The history of PDEs goes back to the works of famous eighteenth-century mathematicians such as Euler, d’Alembert, and Laplace, but the development of this field has continued unabated during the last three centuries. I have, therefore, chosen examples of both classical as well as modern PDEs in order to give you a taste of this vast and beautiful subject.
December 30, 2015 — Håkan Wettergren, Applications Engineer, SystemModeler (MathCore)
In 1869, Rankine extended Euler and Bernoulli’s century-old theory of lateral vibrations of bars to an understanding of rotating machinery that is out of balance. Classical dynamics had a new branch: rotor dynamics. Machine vibration caused by imbalance is one of the main characteristics of machinery in rotation.
All structures have natural frequencies. The critical speed of a rotating machine occurs when the rotational speed matches one of these natural frequencies, often the lowest. Until the end of the nineteenth century the primary way of improving performance, increasing the maximum speed at which a machine rotates without an unacceptable level of vibration, was to increase the lowest critical speed: rotors became stiffer and stiffer. In 1889, the famous Swedish engineer Gustaf de Laval pursued the opposite strategy: he ran a machine faster than the critical speed, finding that at speeds above the critical threshold, vibration decreased. The trick was to accelerate fast through the critical speed. Thirty years later in 1929, the American Henry Jeffcott wrote the equation for a similar system, a simple shaft supported at its ends. Such a rotor is now called the de Laval rotor or Jeffcott rotor and is the standard rotor model used in most basic equations describing various phenomena.
December 23, 2015 — Kathryn Cramer, Technical Communications and Strategy Group
With some impressive new features, new forums, and many new members, Wolfram Community has had a great year. As we approach the end of 2015, we wanted to share a few highlights from the last few months’ excellent posts on the Wolfram Community site.
Interested in drones? Check out these posts.
Connecting ROS to the Wolfram Language, Or Controlling a Parrot ArDrone 2.0 from Mathematica, by Loris Gliner, a student in aeronautical engineering.
Loris Gliner used his time in the Wolfram mentorship program to work out how to connect the Wolfram Language to the Linux Robot Operating System. He includes code examples and a video showing the flight of a Parrot ArDrone 2.0 controlled via the Wolfram Language.
December 18, 2015 — Eila Stiegler, Quality Analysis Manager, Wolfram|Alpha Quality Analysis
It has been quite a while since I graduated from college in Germany with a degree in mathematics. Of course, I have plenty of memories of long study nights, difficult homework assignments, and a general lack of a social life. But I also vividly remember having to take programming classes. I had done my best to avoid these for as long as I could. But when they became part of my curriculum, I could not continue ignoring them. Not being a native English speaker, I was not just dealing with the concept of programming, which was completely abstract to me—I also had to find my way around function names always given in English. Though I struggled in those classes, I successfully graduated, and years later am now part of a project that would have helped me tremendously back then: the Wolfram Language Worldwide Translations Project.
The Wolfram Language Worldwide Translations Project provides any non-English-speaking programming novice with an effortless way into the Wolfram Language. It aims to introduce the Wolfram Language while at the same time addressing any lack of English language skills.