Question Everything

Avery 21 Tx

[materialsscienceandengineering]

Material called a mechanical neural network can learn and change its physical properties

A new type of material can learn and improve its ability to deal with unexpected forces thanks to a unique lattice structure with connections of variable stiffness, as described in a new paper by my colleagues and me.

The new material is a type of architected material, which gets its properties mainly from the geometry and specific traits of its design rather than what it is made out of. Take hook-and-loop fabric closures like Velcro, for example. It doesn’t matter whether it is made from cotton, plastic or any other substance. As long as one side is a fabric with stiff hooks and the other side has fluffy loops, the material will have the sticky properties of Velcro.

My colleagues and I based our new material’s architecture on that of an artificial neural network—layers of interconnected nodes that can learn to do tasks by changing how much importance, or weight, they place on each connection. We hypothesized that a mechanical lattice with physical nodes could be trained to take on certain mechanical properties by adjusting each connection’s rigidity.

Read more.

[jdm]

[moath1]

[florenctts]

[gzabu]

[malikthemartian]

[spacetalin]

[stiffspeed]

[92-n]

[stiffspeed]

[materialsscienceandengineering]

The stiffest porous lightweight materials ever

3D printing and other additive production techniques make it possible to manufacture materials with internal structures of previously unimaginable complexity. This is interesting for lightweight construction, too, as it enables the development of materials that have the highest possible share of interior voids (to make the materials as light as possible) but are simultaneously as robust as possible. Achieving this requires that the internal structures be intelligently organised for maximum efficiency.

A research team from ETH Zurich and MIT led by Dirk Mohr, Professor of Computational Modeling of Materials in Manufacturing, has developed and fabricated material architectures that are equally strong in all three dimensions, and that are simultaneously extremely stiff.

It is possible to determine mathematically just how stiff materials with internal voids can theoretically become; Mohr’s structures have been shown to come extremely close to this theoretical maximum stiffness. Put another way, it’s practically impossible to develop other material structures that are stiffer for the given weight.

Read more.

[materialsscienceandengineering]

Distortion of water droplet surface may increase the likelihood of the droplet freezing

Clouds are a big source of uncertainty in computer simulations used to study Earth systems. To reduce that uncertainty, researchers study the formation of ice in clouds. This formation influences precipitation rates, large-scale cloud motions, and cloud optical properties. This research helps to address a long-standing mystery. For more than 50 years, scientists wanted to know why water droplets will freeze at a higher temperature when they are impacted by a particle. It’s the pressure of the impact, according to new observations. A new study suggests the warmer freezing point is due to pressure changes resulting from the contact.

In most predictive models of cloud formation and growth, temperature is the most important variable, followed by the material properties of atmospheric particles, in determining whether or not a cloud is composed of water droplets or ice crystals. These new results imply that it may also be important to consider collisions, or dynamic properties, that influence the water surface.

Read more.

[stiffspeed]

[materialsworld]

Autonomous boats run errands

Week in Brief (23–27 May)

Credit: MIT/Courtesy of the researchers

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Lab in the Department of Urban Studies and Planning, USA, have designed a fleet of 3D-printed autonomous vessels for transporting goods and services around cities with lots of canals. 

The boats measure 4m by 2m and are equipped with a power supply, sensors, GPS, and microcontrollers. Environmental sensors can also be added allowing them to monitor city pollution levels and water quality. Their rectangular shape allows them move sideways and join together forming larger structures and platforms.

The long-term aim is for the boats to be able to function during the night, performing tasks such as delivering goods, reducing daytime traffic. CSAIL Director Daniela Rus commented, ‘Imagine shifting some of infrastructure services that usually take place during the day on the road — deliveries, garbage management, waste management — to the middle of the night, on the water, using a fleet of autonomous boats.’

To find out more visit, bit.ly/2J1AJnE

In other news:

– Drax power station, UK, will head a £400,000 carbon capture trial

– Biomaterials from multiple sources have been produced using a 3D printer

– McDonald’s shareholders vote not to monitor use of plastic straws

To find out more on materials science, packaging and engineering news, visit our website IOM3 at or follow us on Twitter @MaterialsWorld for regular news updates.

[comehereoften]

What happened to u???

I don't get on here much anymore. Just been grinding through school.

[fyphysica]

The Vapor Cone.

A vapor cone, also known as shock collar or shock egg, is a visible cloud of condensed water which can sometimes form around an object. A vapor cone is typically observed as an aircraft, or object, flying at Transonic speeds. ( slightly slower than the speed of sound) 

The Pressure - Temperature dependence.

As the aircraft approaches the speed of sound, the air pressure around the object drops, and thereby the air temperature drops. If the temperature drops below the dew point, water in the atmosphere condenses to form a cloud in the shape of the shockwave.

Red Bull Stratos and the Vapor Cone.

Remember that epic jump where Felix Baumgartner, as a part of the Red Bull Stratos project broke the sound barrier ( reached Mach 1.25 ) during his descent? But why weren’t vapor cones seen around Felix’s body? Or were they?

Vapor cones are formed only near the ground, where plenty of wet air persists. But when Felix broke the sound barrier, there was no wet air that surrounded him that would enable the formation of Vapor cones.

Have a Good day!

PC: twistedsifter

[fyphysica]

This is a Bonus post from the series. It‘s purpose is primarily to bring out the essence of pressure-temperature dependence that allows us visualize flow in a F1 car

[fyphysica]

Vortex Generators

So we now understand about boundary layers, flow separation, stalls, what causes them, how to detect and get out of one  (previous post).

One way to delay stalls is by inserting is a small angled plate  on the wing known as Vortex Generators. They impart a rotational/swirling motion to the flow of air on the surface of a wing.

Why do Vortex generators work?

Basically, creating a vortex over a surface allows you to delay boundary layer* separation.

The swirling/rotational motion of air prevents the separation of air from the wing earlier on. This increases the lift and/or also reduces drag.

Benefits of vortex generators

As you saw in the gif above the stallspeed when using VGs drastically reduces. This means that you can fly (and land safely) at low speeds without stalling.  

And it has also been shown that VGs reduce the noise generated by air inside the aircraft.

Some more benefits have been listed below (source) for the sake of completion:

● An added safety margin for low-speed flight   

● Improved low-speed handling characteristics

● Improved cross wind handling at low speeds 

● Increased safety margin in the event of an engine failure

● Reduced take-off distance, improving short field performance

Now this idea of forcibly generating vortices to increase lift and/or reduce drag finds application in some crazy places and we shall be looking at that in an upcoming post.

Good day!