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Category: sustainability – Page 174

Built Robotics has introduced an autonomous pile driving robot that will help build utility-scale solar farms in a faster, safer, more cost-effective way, and make solar viable in even the most remote locations. Called the RPD 35, or Robotic Pile Driver 35, the robot can survey the site, determine the distribution of piles, drive piles, and inspect them at a rate of up to 300 piles per day with a two-person crew. Traditional methods today typically can complete around 100 piles per day using manual labor.

The RPD 35 was unveiled today at CONEXPO-CON/AGG in Las Vegas, the largest construction trade show in North America and held every three years.

The 2022 Inflation Reduction Act “Building a Clean Energy Economy” section includes a goal to install 950 million solar panels by 2030. With solar farms requiring tens of thousands of 12-to 16-foot-long piles installed eight feet deep with less than an inch tolerance, piles are a critical component of meeting that target.

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Elon Musk’s Boring Company is doubling down on its Vegas bet, with a proposal that would expand its underground transport system to 65 miles of tunnels below the streets of Sin City.

The proposed network map, which was recently filed with the city of Las Vegas and not previously reported, depicts dozens of tunnels criss-crossing the city to reach more casinos, retail zones, the University of Nevada Las Vegas campus and, for the first time, even residential areas. The proposed transit system is comprised of 69 stations and 65 miles of tunnels, according to planning documents, plus an unknown number of Tesla vehicles.

If successful, a Loop station would be located within a few blocks of almost anywhere in central Las Vegas. Five stations would serve the University of Nevada; and Allegiant Stadium — home to the Raiders NFL team — would get extra links to the west of the city. Harry Reid International Airport would have several stations surrounding it, although none actually serving the passenger terminal.

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One of the oldest tools in computational physics — a 200-year-old mathematical technique known as Fourier analysis — can reveal crucial information about how a form of artificial intelligence called a deep neural network learns to perform tasks involving complex physics like climate and turbulence modeling, according to a new study.

The discovery by mechanical engineering researchers at Rice University is described in an open-access study published in the journal PNAS Nexus, a sister publication of the Proceedings of the National Academy of Sciences.

“This is the first rigorous framework to explain and guide the use of deep neural networks for complex dynamical systems such as climate,” said study corresponding author Pedram Hassanzadeh. “It could substantially accelerate the use of scientific deep learning in climate science, and lead to much more reliable climate change projections.”

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A biological method that produces metal nanoclusters using the electroactive bacterium Geobacter sulfurreducens could provide a cheap and sustainable solution to high-performance catalyst synthesis for various applications such as water splitting.

Metal nanoclusters contain fewer than one hundred atoms and are much smaller than nanoparticles. They have unique electronic properties but also feature numerous active sites available for catalysis on their surface. There are several synthetic methods for making nanoclusters, but most require multiple steps involving and harsh temperature and pressure conditions.

Biological methods are expected to deliver ecofriendly alternatives to conventional chemical synthesis. Yet, to date, they have only led to large nanoparticles in a wide range of sizes. “We found a way to control the size of the nanoclusters,” says Rodrigo Jimenez-Sandoval, a Ph.D. candidate in Pascal Saikaly’s group at KAUST.

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The Swiss startup’s pilot project will focus on the Western public rail system and cost around $437,240.

European startup Sun-Ways has devised a mechanical device to deploy removable solar panels along railway tracks.

This innovation could be implemented on half of the railway lines across the globe, according to the Swizerland-based energy startup.

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A system of robots that harvest and transport crops on their own without human assistance has been developed for use in agricultural facilities such as smart farms.

The research team under Choi Tae-yong, principal researcher at the AI Robot Research Division’s Department of Robotics and Mechatronics of the Korea Institute of Machinery and Materials, an institution under the jurisdiction of the Ministry of Science and ICT, has developed a multiple-robot system for harvesting crops.

This technology can be used to help at agricultural sites where there is a noticeable shortage of manpower by harvesting crops through an automated system. This system also includes robots that use autonomous driving technology to then transport the harvested crops to loading docks.

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“The goal is for community groups or individual citizens anywhere to be able to measure local air pollution.”

As per an estimation by WHO, air pollution causes around 4 million annual premature deaths all over the globe. Considering this issue, an MIT research team launched an open-source version of an economical, mobile pollution detector through which individuals can track the air-quality more broadly.

The detector, named Flatburn, can be fabricated through 3D printing or by ordering cheap parts. The researchers have now conducted tests and calibrated the detector concerning existing ultra-modern machines and are making people aware of how to assemble, use, and interpret the data.

Flatburn is an open-source, mobile pollution detector from the MIT Senseable City Lab intended to let people measure air quality cheaply.

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