Lifeboat Foundation

Circa 2017

A brief history of Polywell progress is recounted. The present PIC simulation explains why the most recent Polywell fusion reactor failed to produce fusion energy. Synchronized variations of multiple parameters would require DC power supplies, not available in historic model testing. Even with DC power, the simulation showed that the trapping of cold electrons would ruin plasma stability during start-up. A theoretical solution to this trapping problem was found in Russian literature describing diocotron-pumping of electrons out of a plasma trap at Kharkov Institute. In Polywell, diocotron-pumping required matching the depth of the potential-well to the electron-beam current falling on a special aperture installed in one of the electromagnets. With diocotron-pumping the reactor was simulated to reach steady-state, maximum-power operation in a few milliseconds of simulated time. These improvements, validated in simulating small-scale DD reactors, were scaled up by a factor of 30 to simulate a large, net-power reactor burning p + ¹¹ B fuel. Power-balance was estimated from a textbook formula for fusion power density by numerically integrating the power density. Unity power-balance required the size of the p + ¹¹ B reactor to be somewhat larger than ITER.

https://youtube.com/watch?v=FxlGPz4kyZw

The China Electricity Council (CEC) ratified and published a set of national standards for electric vehicle wireless charging, which will be based on the magnetic resonance technology developed and patented by WiTricity, a wireless power transfer specialist based in Massachusetts.

Lack of standardization was always a major obstacle for the popularization of the wireless charging, but it seems that in the near future the industry will finally introduce a general solution for all EVs — not only in China, but also globally.

Continue reading “China To Introduce EV Wireless Charging Standard Based On WiTricity Technology” »

If you really have the need for speed, you could get it on the ground. But if you’re looking more for stuff that can break the sound barrier many times over, you should consider looking up. That’s the hint casually dropped by aeronautic manufacturer Lockheed Martin, which has mulled over revisiting the idea of a hypersonic revamp. In this case, they’re reportedly looking at an upgrade of the old SR-71 “Blackbird” that first took to the air nearly 60 years ago.

Lockheed Martin’s Skunk Works department has been making noises about a revival of the legendary bomber, a jet that was capable of flying up to Mach 3. That’s slightly more than 3,700 mph, about one and a half times speedier than the .220 Swift, reportedly the fastest bullet ever produced.

But the Skunk Work’s brain trust claims the SR-72 might even double the speed of its predecessor. That’s a tricky proposition considering the plane’s air intake would be brutal at those speeds, like trying to start a campfire in gale-force winds.

Lockheed Martin’s Advanced Development Programs, known as Skunk Works, has demonstrated an artificial intelligence-powered intelligence, surveillance and reconnaissance (ISR) pod autonomously searching out and confirming a target.

The demonstration was conducted at Edwards Air Force Base in California using an ISR pod mounted on a Lockheed Martin F-16 fighter, says the company on 8 May. The demonstration was conducted in Air Force Test Pilot School.

Harold White left NASA in December to join a new nonprofit focused on building the technologies to bring humans to the outer solar system and beyond.

The U.S. Navy is teaming up with DARPA to develop autonomous, robotic ships that are completely human free. The NOMARS (No Mariners Required Ship) concept, if successful, would be a huge leap over current unmanned surface vessel development efforts. The result could be a warship able to do the tedious, dangerous, and dirty jobs all by itself, keeping human-crewed ships safe from harm—and boredom.

The Navy, struggling to grow the fleet on a flat defense budget, is making a big push into unmanned surface vessels, or USVs. The Navy plans to build ten Large Unmanned Surface Vehicle ships, 200 to 300 foot long vessels displacing 2,000 tons, in five years. LUSV would act as a scout, sailing ahead of the fleet to detect threats early, or floating magazine, carrying a large load of missiles. LUSV would ideally be autonomous, or optionally manned with a small crew.

“The world is currently rightly focused on tackling the global health emergency,” Mark Wright, science director of the U.K. branch of the World Wildlife Fund, told The Guardian. “However, this new research reinforces that, after we are through this extremely difficult time, we will need renewed ambitious action to address the climate and nature crisis.”

More on the environment: Doomsday Report Author: Earth’s Leaders Have Failed

Up next__elon musk says he’ll be working on the tesla assembly line today.

Of the seven patterns of AI that represent the ways in which AI is being implemented, one of the most common is the recognition pattern. The main idea of the recognition pattern of AI is that we’re using machine learning and cognitive technology to help identify and categorize unstructured data into specific classifications. This unstructured data could be images, video, text, or even quantitative data. The power of this pattern is that we’re enabling machines to do the thing that our brains seem to do so easily: identify what we’re perceiving in the real world around us.

The recognition pattern is notable in that it was primarily the attempts to solve image recognition challenges that brought about heightened interest in deep learning approaches to AI, and helped to kick off this latest wave of AI investment and interest. The recognition pattern however is broader than just image recognition In fact, we can use machine learning to recognize and understand images, sound, handwriting, items, face, and gestures. The objective of this pattern is to have machines recognize and understand unstructured data. This pattern of AI is such a huge component of AI solutions because of its wide variety of applications.

The difference between structured and unstructured data is that structured data is already labelled and easy to interpret. However unstructured data is where most entities struggle. Up to 90% of an organization’s data is unstructured data. It becomes necessary for businesses to be able to understand and interpret this data and that’s where AI steps in. Whereas we can use existing query technology and informatics systems to gather analytic value from structured data, it is almost impossible to use those approaches with unstructured data. This is what makes machine learning such a potent tool when applied to these classes of problems.

Add another giant bug to the list of things Washington state is working to handle right now.

Earlier this week, scientists said they had spotted Asian giant hornets in the state — and it’s still unknown how they got there.

Now there’s another threat: a non-native gypsy moth.