#Annie Kritcher

[yesilhaber]

Nükleer füzyonun geleceği

Güneş ve yıldızları güçlendiren aynı nükleer reaksiyonu kullanarak dünyayı aydınlatma umudu: Fransa’daki Uluslararası Termonükleer Deneysel Reaktör (ITER) ve ABD’deki Ulusal Ateşleme Tesisi’nin (NIF) başarıları. Fransa’nın güneyinde, bilim dünyasının en parlak zekaları, dünyanın en büyük ve en iddialı bilim deneyini gerçekleştirmek için bir araya geliyor. ITER projesi, nükleer füzyonu endüstriyel…

[blockgeni]

The week before its successful experiment on December 5, Lawrence Livermore National Laboratory's machine-learning models foresaw the historic achievement of fusion ignition. The design team for the National Ignition Facility sent the experimental plan to the Cognitive Simulation (CogSim) machine-learning team for analysis, and it discovered that the fusion reactions that resulted would probably produce more energy than was required to initiate the process, leading to ignition. Three football field-sized LLNL's laser-based inertial confinement fusion research device fired 192 laser beams, delivering 2.05 megajoules of ultraviolet energy to a nearly round diamond fuel capsule, sparking 3.15 megajoules of fusion ignition for the first time in a laboratory during the most recent experiment. Having nuclear testing banned strengthens American energy independence and national security, and CogSim machine-learning models helped make sure the experiment didn't fall into the same traps it did the year before. LLNL Director Kim Budil stated during a press conference at the Department of Energy on Tuesday that last week their pre-shot predictions, improved by machine learning and the wealth of data they have collected, indicated that they had a better than 50% chance of exceeding the target gain of 1. The NIF design team develops designs that will achieve the extreme conditions necessary for fusion ignition by comparing them to complex plasma physics simulations and analytical models against experimental data gathered over 60 years. The most recent experiment reached temperatures of 150 million degrees and pressures two times greater than those of the Sun. Thousands of machine-learning simulations of an experimental design could be run in the lead-up using CogSim. According to Annie Kritcher, principal designer, they have made quite a bit of progress in our machine-learning models to kind of tie together their complex radiation hydrodynamics simulations of the experimental data and learning. However, the NIF experiment on August 8, 2021 crossed the ignition threshold, and the experiment in September opened the door for a new laser capability. For the most recent experiment, the design team utilized conventional techniques and limited machine learning to prediction-making. The design team used improved models to increase the symmetry of the implosion by transferring more energy between laser beams in the second half and adjusting the first half of the pulse in order to thicken the fuel capsule for this experiment in order to increase the burn rate and increase the margin of success. Although she referred to capsule defects—which are more difficult to model and predict—as the experiment's "main driver" of performance, Kritcher credited those changes for the experiment's success. Although the diamond capsule is 100 times smoother than a mirror, defects must be seen, measured, and counted using X-ray tomography, creating a large amount of data that software can now help analyze. Future experiments should perform better because the robust capsule used in the most recent experiment was not the best choice, according to Michael Stadermann, program manager for Target Fabrication. The NIF is a scientific demonstration facility, not an optimized one. Firing the laser required an additional 300 megajoules of energy to be drawn from the power grid. Director of the LLNL Weapons, Physics, and Design program Mark Herrmann stated, "The laser wasn't designed to be efficient." The laser was created to provide us with the maximum amount of energy to enable these extraordinary circumstances. The NIF has been around for more than 20 years, and some of its technology is from the 1980s. Federal officials are confident that the United States can achieve President Biden's goal of a commercial fusion reactor within the decade thanks to new laser architectures, target fabrication techniques, materials, computation and simulations, and machine learning.

In a public-private partnership centered on fusion pilot power plant designs, DOE invested $50 million in September, but Budil claimed that without "concerted effort and investment" on the technology side, such a plant is probably still four decades away. Last year, the private sector spent $3 billion on fusion research, and DOE is working with the White House Office of Science and Technology Policy to develop a plan for commercial fusion that would produce zero-carbon energy for use in heavy industry, cars, homes, and other buildings. To its credit, the Biden administration put forth the largest R&D budget in American history, and recent investments made it possible for LLNL's most recent accomplishment. According to OSTP Director Arati Prabhakar, she thinks this is an amazing example of the power of America's research and development enterprise. Source link

[sciencespies]

Can a slew of nuclear fusion start-ups deliver unlimited clean energy?

https://sciencespies.com/physics/can-a-slew-of-nuclear-fusion-start-ups-deliver-unlimited-clean-energy/

Can a slew of nuclear fusion start-ups deliver unlimited clean energy?

We have been trying to harness the reaction that powers the stars for decades, and now private firms are promising commercial fusion within a decade. Is there any reason to believe them this time?

Physics 19 October 2022

By Thomas Lewton

Fusion involves heating a charged gas called a plasma to temperatures approaching 200 million degrees Celsius

David Parker/Science photo library

IN MARCH 1951, the president of Argentina, Juan Perón, announced the results of a secretive project on Huemul Island in northern Patagonia. His scientists had achieved nuclear fusion, he said, harnessing the reaction that powers the sun to herald a future in which energy would be sold in “half-litre bottles, like milk”. But things soon turned sour when researchers returned from Huemul to report that the whole thing was an expensive, embarrassing fraud.

The Huemul hoax was an extreme case. Arguably, though, it set a pattern for the long quest to harness star power for virtually limitless clean energy here on Earth: audacious claims followed by disappointment, rinse and repeat. It explains the tiresome persistence of the old joke that fusion has always been 30 years away, and always will be.

Yet here we are again. In the past year alone, private fusion firms have received more investment than in the entire history of this enterprise. “The feeling among investors is that fusion will happen,” says Melanie Windridge, a fusion scientist and founder of Fusion Energy Insights, a membership organisation for the energy industry. Some companies are even promising commercial fusion reactors in a decade. “Progress is happening very rapidly,” says Annie Kritcher at Lawrence Livermore National Laboratory (LLNL) in California. “As you get closer and closer, things start to take off.”

What is hard to discern, however, is whether recent advances at big, state-funded fusion projects, together with new technologies and reactor designs …

#Physics

[blockgeni]

The week before its successful experiment on December 5, Lawrence Livermore National Laboratory's machine-learning models foresaw the historic achievement of fusion ignition. The design team for the National Ignition Facility sent the experimental plan to the Cognitive Simulation (CogSim) machine-learning team for analysis, and it discovered that the fusion reactions that resulted would probably produce more energy than was required to initiate the process, leading to ignition. Three football field-sized LLNL's laser-based inertial confinement fusion research device fired 192 laser beams, delivering 2.05 megajoules of ultraviolet energy to a nearly round diamond fuel capsule, sparking 3.15 megajoules of fusion ignition for the first time in a laboratory during the most recent experiment. Having nuclear testing banned strengthens American energy independence and national security, and CogSim machine-learning models helped make sure the experiment didn't fall into the same traps it did the year before. LLNL Director Kim Budil stated during a press conference at the Department of Energy on Tuesday that last week their pre-shot predictions, improved by machine learning and the wealth of data they have collected, indicated that they had a better than 50% chance of exceeding the target gain of 1. The NIF design team develops designs that will achieve the extreme conditions necessary for fusion ignition by comparing them to complex plasma physics simulations and analytical models against experimental data gathered over 60 years. The most recent experiment reached temperatures of 150 million degrees and pressures two times greater than those of the Sun. Thousands of machine-learning simulations of an experimental design could be run in the lead-up using CogSim. According to Annie Kritcher, principal designer, they have made quite a bit of progress in our machine-learning models to kind of tie together their complex radiation hydrodynamics simulations of the experimental data and learning. However, the NIF experiment on August 8, 2021 crossed the ignition threshold, and the experiment in September opened the door for a new laser capability. For the most recent experiment, the design team utilized conventional techniques and limited machine learning to prediction-making. The design team used improved models to increase the symmetry of the implosion by transferring more energy between laser beams in the second half and adjusting the first half of the pulse in order to thicken the fuel capsule for this experiment in order to increase the burn rate and increase the margin of success. Although she referred to capsule defects—which are more difficult to model and predict—as the experiment's "main driver" of performance, Kritcher credited those changes for the experiment's success. Although the diamond capsule is 100 times smoother than a mirror, defects must be seen, measured, and counted using X-ray tomography, creating a large amount of data that software can now help analyze. Future experiments should perform better because the robust capsule used in the most recent experiment was not the best choice, according to Michael Stadermann, program manager for Target Fabrication. The NIF is a scientific demonstration facility, not an optimized one. Firing the laser required an additional 300 megajoules of energy to be drawn from the power grid. Director of the LLNL Weapons, Physics, and Design program Mark Herrmann stated, "The laser wasn't designed to be efficient." The laser was created to provide us with the maximum amount of energy to enable these extraordinary circumstances. The NIF has been around for more than 20 years, and some of its technology is from the 1980s. Federal officials are confident that the United States can achieve President Biden's goal of a commercial fusion reactor within the decade thanks to new laser architectures, target fabrication techniques, materials, computation and simulations, and machine learning.

In a public-private partnership centered on fusion pilot power plant designs, DOE invested $50 million in September, but Budil claimed that without "concerted effort and investment" on the technology side, such a plant is probably still four decades away. Last year, the private sector spent $3 billion on fusion research, and DOE is working with the White House Office of Science and Technology Policy to develop a plan for commercial fusion that would produce zero-carbon energy for use in heavy industry, cars, homes, and other buildings. To its credit, the Biden administration put forth the largest R&D budget in American history, and recent investments made it possible for LLNL's most recent accomplishment. According to OSTP Director Arati Prabhakar, she thinks this is an amazing example of the power of America's research and development enterprise. Source link

[sciencespies]

In a lab on Earth, scientists just replicated pressures found on white dwarf stars

https://sciencespies.com/physics/in-a-lab-on-earth-scientists-just-replicated-pressures-found-on-white-dwarf-stars/

In a lab on Earth, scientists just replicated pressures found on white dwarf stars

For the first time, pressure over 100 times that found in Earth’s core has been generated in a lab, setting a new record.

Using the highest-energy laser system in the world, physicists briefly subjected solid hydrocarbon samples to pressures up to 450 megabars, meaning 450 million times Earth’s atmospheric pressure at sea level.

That’s equivalent to the pressures found in the carbon-dominated envelopes of a rare type of white dwarf star – some of the densest objects in the known Universe. It could help us to better understand the effect those pressures have on changes in the stars’ brightness.

Most of the stars in the Universe will end their lives as a white dwarf, including our Sun. As they reach the end of their main-sequence, hydrogen-fusing days, they’ll puff out into red giants, eventually ejecting most of their material out into space as the core collapses into a white dwarf – a ‘dead’ star no longer able to support fusion.

White dwarfs are dense. They can be up to around 1.5 times the mass of the Sun, packed into a sphere the size of Earth. Only something called electron degeneracy pressure keeps the star from collapsing under its own gravity.

At around 100 megabars of pressure, electrons are stripped from their atomic nuclei – and, because identical electrons can’t occupy the same space, these electrons supply the outward pressure that keeps the star from collapsing.

This pressure doesn’t just influence how compressible the material is, it also decreases the opacity of the plasma ionised by the loss of electrons. And the links between these properties are described by the material’s equations of state, which also can be used to calculate such properties as the temperature profile and rate of cooling.

There are, however, some disagreements in equation of state (EOS) models for extreme pressures; for white dwarf stars, the EOS models along what is known as the shock Hugoniot – the curve that plots the increase in pressure and density under compression – can vary by 10 percent.

This can be a problem when trying to understand the fundamental properties of the Universe, because white dwarf stars should be quite predictable. Although they shine, the light is only from residual heat, not fusion, and their cooling rate can therefore be used as a sort of clock to confirm the age of the Universe, for instance, and the ages of the stars around them.

So this is what the research team is trying to resolve, using the laser system at the Lawrence Livermore National Laboratory’s National Ignition Facility (NIF).

“White dwarf stars provide important tests of stellar physics models, but EOS models at these extreme conditions are largely untested,” said physicist Annie Kritcher of the Lawrence Livermore National Laboratory.

“NIF can duplicate conditions ranging from the cores of planets and brown dwarfs to those in the centre of the Sun. We’re also able in NIF experiments to deduce the opacity along the shock Hugoniot. This is a necessary component in studies of stellar structure and evolution.”

The experimental set-up consisted of a small, solid, one-millimetre hydrocarbon (plastic) bead inside a hollow gold cylinder about the size of a pencil eraser called a hohlraum. This was then irradiated with 1.1 million joules of ultraviolet light delivered by the lasers, which created a uniform X-ray bath heating the plastic sphere to nearly 3.5 million Kelvin.

The outer layer of the bead was destroyed through ablation, which created a spherical ablation shockwave travelling up to 220 kilometres per second that converged spherically, resulting in increasing pressure as it propagated through the bead.

By the way, all this happened extraordinarily quickly – the shockwave took just 9 nanoseconds to traverse the entire sample – but, using X-ray radiography, the research team was able to record the shock Hugoniot, measuring pressures of 100 megabars on the outside of the bead to 450 megabars by the time it reached the middle.

The pressure inside Earth’s core is 3.6 megabars. And, previously, the highest pressure achieved in this kind of controlled experiment was 60 megabars.

The pressure generated in their experiment, the team said, is consistent with the carbon envelope – the convection region surrounding the core – seen in what are known as “hot DQ” white dwarfs. These are relatively rare; unlike ordinary white dwarfs, whose atmospheres are composed primarily of hydrogen and helium, hot DQs have primarily carbon atmospheres, and they’re unusually hot and bright.

Some of them also pulsate as they spin, resulting in brightness variations. To understand these pulsations and model them, we need an accurate understanding of how the matter in the star behaves under pressure.

In addition to X-ray radiography, the physicists used X-ray Thomson scattering to measure the electron temperature and degree of ionisation in the sample. It, too, turned up hot DQ.

“We measured a reduction in opacity at high pressures, which is associated with a significant ionisation of the carbon inner shell,” Kritcher said.

“This pressure range along the Hugoniot corresponds to the conditions in the carbon envelope of white dwarf stars. Our data agree with equation-of-state models that include the detailed electronic shell structure.”

What this means is that the ionisation ultimately makes the material more compressible than models that don’t have electronic shells. This places new constraints on the compressibility and opacity of the carbon envelope in hot DQs, which in turn can contribute to a better understanding of their properties and evolution. All this, from a lab experiment on our own planet. 

The research has been published in Nature.

#Physics