First Look at Flight in 2025

A First Look at Flight in 2025

01.13.11

 

Artist's concept of an aircraft that could enter service in 2025 from the team led by Northrop Grumman. Credit: NASA/Northrop Grumman
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Artist's concept of an aircraft that could enter service in 2025 from the team led by The Boeing Company. Image credit: NASA/The Boeing Company
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Artist's concept of an aircraft that could enter service in 2025 from the team led by Lockheed Martin. Image credit: NASA/Lockheed Martin
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In late 2010, NASA awarded contracts to three teams — Lockheed Martin, Northrop Grumman, The Boeing Company — to study advanced concept designs for aircraft that could take to the skies in the year 2025.

At the time of the award, the team gave NASA a sneak peek of the particular design they plan to pursue.

Each design looks very different, but all final designs have to meet NASA's goals for less noise, cleaner exhaust and lower fuel consumption. Each aircraft has to be able to do all of those things at the same time, which requires a complex dance of tradeoffs between all of the new advanced technologies that will be on these vehicles.

The proposed aircraft will also have to operate safely in a more modernized air traffic management system.

And each design has to fly up to 85 percent of the speed of sound; cover a range of approximately 7,000 miles; and carry between 50,000 and 100,000 pounds of payload, either passengers or cargo.

For the rest of this year, each team will be exploring, testing, simulating, keeping and discarding innovations and technologies to make their design a winner.

How different will the final designs look from these initial glimpses?

Check back and see.

›  Read About Aircraft Designs for 2035

 

THE GREAT ENERGY CHALLENGE BY NATIONAL GEOGRAPHIC

http://environment.nationalgeographic.com/environment/energy/great-energy-challenge/global-footprints/

Impregnating plastics with carbon dioxide

Everyone has heard that carbon dioxide is responsible for global warming. But the gas also has some positive characteristics. Researchers are now impregnating plastics with compressed CO2 in a process that could lead to new applications ranging from colored contact lenses to bacteria-resistant door handles.

CO2 is more than just a waste product. In fact, it has a variety of uses: the chemical industry makes use of this colorless gas to produce urea, methanol and salicylic acid. Urea is a fertilizer, methanol is a fuel additive, and salicylic acid is an ingredient in aspirin.
Researchers at the Fraunhofer Institute for Environmental, Safety and Energy Technology UMSICHT in Oberhausen are pursuing a new idea by testing how carbon dioxide can be used to impregnate plastics. At a temperature of 30.1 degrees Celsius and a pressure of 73.8 bar, CO2 goes into a supercritical state that gives the gas solvent-like properties. In this state, it can be introduced into polymers, or act as a “carrier” in which dyes, additives, medical compounds and other substances can be dissolved. “We pump liquid carbon dioxide into a high-pressure container with the plastic components that are to be impregnated, then steadily increase the temperature and the pressure until the gas reaches the supercritical state. When that state is reached, we increase the pressure further. At 170 bar, pigment in powder form dissolves completely in the CO2 and then diffuses with the gas into the plastic. The whole process only takes a few minutes. When the container is opened, the gas escapes through the surface of the polymer but the pigment stays behind and cannot subsequently be wiped off,” explains Dipl.-Ing. Manfred Renner, a scientist at Fraunhofer UMSICHT.
In tests, the researchers have even managed to impregnate polycarbonate with nanoparticles that give it antibacterial properties. E-coli bacteria, placed on the plastic’s surface in the institute’s own high-pressure laboratory, were killed off completely – a useful function that could be applied to door handles impregnated with the same nanoparticles. Tests conducted with silica and with the anti-inflammatory active pharmaceutical ingredient flurbiprofen were also successful. “Our process is suitable for impregnating partially crystalline and amorphous polymers such as nylon, TPE, TPU, PP and polycarbonate,” states Renner, “but it cannot be applied to crystalline polymers.”
The process holds enormous potential, as carbon dioxide is non-flammable, non-toxic and inexpensive. Whilst it shows solvent-like properties, it does not have the same harmful effects on health and on the environment as the solvents that are used in paints, for example. Painted surfaces are also easily damaged and are not scratch-resistant. Conventional processes for impregnating plastics and giving them new functions have numerous drawbacks. Injection molding, for instance, does not permit the introduction of heat-sensitive substances such as fire retardants or UV stabilizers. Many dyes change color; purple turns black. “Our method allows us to customize high-value plastic components and lifestyle products such as mobile phone shells. The best about it is that the color, additive or active ingredient is introduced into layers near the surface at temperatures far below the material’s melting point, in an environ mentally friendly manner that does away with the need for aggressive solvents ,” says Renner. The process could, for example, be used to dye contact lenses – and lenses could even be enriched with pharmaceutical compounds that would then be slowly released to the eye throughout the day, representing an alternative to repeated applications of eye drops for the treatment of glaucoma. According to the scientist, this new impregnation method is suitable for a broad range of new applications.

extension of note 1 (fuzzy logoc)

getting into fuzzy world:





What do ya mean fuzzy ??!!
Before illustrating the mechanisms which make fuzzy logic machines work, it is important to realize what fuzzy logic actually is. Fuzzy logic is a superset of conventional(Boolean) logic that has been extended to handle the concept of partial truth- truth values between "completely true" and "completely false". As its name suggests, it is the logic underlying modes of reasoning which are approximate rather than exact. The importance of fuzzy logic derives from the fact that most modes of human reasoning and especially common sense reasoning are approximate in nature.
The essential characteristics of fuzzy logic as founded by Zader Lotfi are as follows.

• In fuzzy logic, exact reasoning is viewed as a limiting case of approximate reasoning.
• In fuzzy logic everything is a matter of degree.
• Any logical system can be fuzzified
• In fuzzy logic, knowledge is interpreted as a collection of elastic or, equivalently , fuzzy constraint on a collection of variables
• Inference is viewed as a process of propagation of elastic constraints.

The third statement hence, define Boolean logic as a subset of Fuzzy logic. Fuzzy Sets
Fuzzy Set Theory was formalised by Professor Lofti Zadeh at the University of California in 1965. What Zadeh proposed is very much a paradigm shift that first gained acceptance in the Far East and its successful application has ensured its adoption around the world.
A paradigm is a set of rules and regulations which defines boundaries and tells us what to do to be successful in solving problems within these boundaries. For example the use of transistors instead of vacuum tubes is a paradigm shift - likewise the development of Fuzzy Set Theory from conventional bivalent set theory is a paradigm shift.
Bivalent Set Theory can be somewhat limiting if we wish to describe a 'humanistic' problem mathematically. For example, Fig 1 below illustrates bivalent sets to characterise the temperature of a room.


The most obvious limiting feature of bivalent sets that can be seen clearly from the diagram is that they are mutually exclusive - it is not possible to have membership of more than one set ( opinion would widely vary as to whether 50 degrees Fahrenheit is 'cold' or 'cool' hence the expert knowledge we need to define our system is mathematically at odds with the humanistic world). Clearly, it is not accurate to define a transiton from a quantity such as 'warm' to 'hot' by the application of one degree Fahrenheit of heat. In the real world a smooth (unnoticeable) drift from warm to hot would occur. This natural phenomenon can be described more accurately by Fuzzy Set Theory. Fig.2 below shows how fuzzy sets quantifying the same information can describe this natural drift.


The whole concept can be illustrated with this example. Let's talk about people and "youthness". In this case the set S (the universe of discourse) is the set of people. A fuzzy subset YOUNG is also defined, which answers the question "to what degree is person x young?" To each person in the universe of discourse, we have to assign a degree of membership in the fuzzy subset YOUNG. The easiest way to do this is with a membership function based on the person's age. young(x) = { 1, if age(x) <= 20,

(30-age(x))/10, if 20 < age(x) <= 30,

0, if age(x) > 30 }

A graph of this looks like:


Given this definition, here are some example values:

Person    Age    degree of youth
--------------------------------------
Johan     10        1.00 
Edwin     21        0.90
Parthiban 25        0.50
Arosha    26        0.40
Chin Wei  28        0.20
Rajkumar  83        0.00 

So given this definition, we'd say that the degree of truth of the statement "Parthiban is YOUNG" is 0.50. Note: Membership functions almost never have as simple a shape as age(x). They will at least tend to be triangles pointing up, and they can be much more complex than that. Furthermore, membership functions so far is discussed as if they always are based on a single criterion, but this isn't always the case, although it is the most common case. One could, for example, want to have the membership function for YOUNG depend on both a person's age and their height (Arosha's short for his age). This is perfectly legitimate, and occasionally used in practice. It's referred to as a two-dimensional membership function. It's also possible to have even more criteria, or to have the membership function depend on elements from two completely different universes of discourse.

Fuzzy Set Operations.

Union

The membership function of the Union of two fuzzy sets A and B with membership functions and respectively is defined as the maximum of the two individual membership functions. This is called the maximum criterion. The Union operation in Fuzzy set theory is the equivalent of the OR operation in Boolean algebra.

Intersection

The membership function of the Intersection of two fuzzy sets A and B with membership functions and respectively is defined as the minimum of the two individual membership functions. This is called the minimum criterion. The Intersection operation in Fuzzy set theory is the equivalent of the AND operation in Boolean algebra.

Complement

The membership function of the Complement of a Fuzzy set A with membership function is defined as the negation of the specified membership function. This is caleed the negation criterion.

The Complement operation in Fuzzy set theory is the equivalent of the NOT operation in Boolean algebra.
The following rules which are common in classical set theory also apply to Fuzzy set theory.

De Morgans law

,

Associativity

Commutativity

Distributivity

Glossary

Universe of Discourse

The Universe of Discourse is the range of all possible values for an input to a fuzzy system.

Fuzzy Set

A Fuzzy Set is any set that allows its members to have different grades of membership (membership function) in the interval [0,1].

Support

The Support of a fuzzy set F is the crisp set of all points in the Universe of Discourse U such that the membership function of F is non-zero.

Crossover point

The Crossover point of a fuzzy set is the element in U at which its membership function is 0.5.

Fuzzy Singleton

A Fuzzy singleton is a fuzzy set whose support is a single point in U with a membership function of one.

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forbs magazine has released (The World's Most Expensive Cars) lets have a quick look

http://www.forbes.com/2010/12/15/bugatti-rolls-royce-ferarri-business-autos-most-expensive-cars_slide_2.html

AT&T DONT TEXT WHILE DRIVING CAMPAIGN

FROM FRANKFURT AUTO SHOW

If you're going to make it in the exotic supercar business, it helps to have two things: a substantial lineup and an F1 team. The Ferrari case, first of all, goes without saying. McLaren has the latter covered, and is in the process of kicking the former into high gear. Spyker bought its own F1 team, and though it subsequently sold it, look at the Dutch automaker now: they own Saab. Lotus is following the same path with not one, but two F1 teams, and an aggressive model rollout plan. Now Marussia looks poised to follow the same path.

The exotic Russian automaker recently bought into the Virgin Racing team, so they've got one aspect covered. All they'll need now is a big ambitious model lineup. Cue the latest news.

According to the rumormill, Marussia Motors is planning on rolling out seven new products at the Frankfurt Motor Show in the fall. Included in the reported plans are a coupe, SUV, sedan and a city car. If this is all sounding familiar, look no further than Lotus, which set a new precedent with five new concepts at the Paris Motor Show this past autumn.

Along with the new vehicles, Marussia is reportedly hard at work expanding its distribution base, with new showrooms planned for London and Monaco, penetration into the American market in the works and factories slated to open in Germany and Belgium. The plans are nothing if not ambitious, but in this market, that could be exactly what the Doctor Zhivago ordered.(POST FROM AUTO BLOG).

FUZZY LOGIC

HAVE YOU EVER COME ACROSS THE TERM (FUZZY) OR (FUZZY LOGIC) OR EVER WONDER WHO INTRODUCE THIS TERM  INITIALLY.
Fuzzy logic has rapidly become one of the most successful of today's technologies for developing sophisticated control systems. The reason for which is very simple. Fuzzy logic addresses such applications perfectly as it resembles human decision making with an ability to generate precise solutions from certain or approximate information. It fills an important gap in engineering design methods left vacant by purely mathematical approaches (e.g. linear control design), and purely logic-based approaches (e.g. expert systems) in system design.fuzzy logic was discovered. Lotfi A. Zadeh, a professor of UC Berkeley in California, soon to be known as the founder of fuzzy logic observed that conventional computer logic was incapable of manipulating data representing subjective or vague human ideas such as "an atractive person" or "pretty hot". Fuzzy logic, hence was designed to allow computers to determine the distinctions among data with shades of gray, similar to the process of human reasoning. In 1965, Zadeh published his seminal work "Fuzzy Sets" which described the mathematics of fuzzy set theory, and by extension fuzzy logic. This theory proposed making the membership function (or the values False and True) operate over the range of real numbers [0.0, 1.0]. Fuzzy logic was now introduced to the world.
Although, the technology was introduced in the United States, the scientist and researchers there, ignored it mainly because of its unconventional name. They refused to take something which sounded so child-like seriously. Some mathematicians argued that fuzzy logic was merely probability in disguise. Only stubborn scientists or ones who worked in discrete continued researching it.
While the US and certain parts of Europe ignored it, fuzzy logic was excepted with open arms in Japan, China and most Oriental countries. It may be suprising to some that the world's largest number of fuzzy researchers are in China with over 10,000 scientists. Japan, though currently positioned at the leading edge of fuzzy studies falls second in manpower, followed by Europe and the USA. Hence, it can be said that the popularity of fuzzy logic in the Orient reflects the fact that Oriental thinking more easily accepts the concept of "fuzziness". And because of this, the US, by some estimates, trail Japan by at least ten years in this forefront of modern technology.

The new benchmark for automatic car transmissions

ZF has developed a new automatic transmission for cars with eight speeds that can achieve 11% fuel savings. The priority aim in development, however, was not the maximum number of gears, but minimum consumption. ZF engineers had set the bar high to produce a new benchmark for automatic car transmissions. The second generation of the ZF 6HP 6-speed transmission, that entered production only in 2006, defines standards that are hard to top: reaction times faster than human perception, direct engine linkage by early-stage torque converter lock-up and intelligent, adaptive control software, that almost reads the driver's intentions from his foot. But the new transmission is capable of even more - it saves (even more) fuel. It also guarantees ultimate driving enjoyment, as well as the variability needed to be able to use future technologies.