- 2019-11-12 10:50:04
- Article ID: 722408
Deep Learning Expands Study of Nuclear Waste Remediation
-
A schematic of the physics-informed generative adversarial network used to estimate parameters and quantify uncertainty in the subsurface flow at the Hanford Site.
“In science we know the laws of physics and observation principles – mass, momentum, energy, etc.,” said George Karniadakis, professor of applied mathematics at Brown and co-author on the SC19 workshop paper. “The concept of physics-informed GANs is to encode prior information from the physics into the neural network. This allows you to go well beyond the training domain, which is very important in applications where the conditions can change.”
GANs have been applied to model human face appearance with remarkable accuracy, noted Prabhat, a co-author on the SC19 paper who leads the Data and Analytics Services team at Berkeley Lab’s National Energy Research Scientific Computing Center. “In science, Berkeley Lab has explored the application of vanilla GANs for creating synthetic universes and particle physics experiments; one of the open challenges thus far has been the incorporation of physical constraints into the predictions,” he said. “George and his group at Brown have pioneered the approach of incorporating physics into GANs and using them to synthesize data – in this case, subsurface flow fields.”
For this study, the researchers focused on the Hanford Site, established in 1943 as part of the Manhattan Project to produce plutonium for nuclear weapons and eventually home to the first full-scale plutonium production reactor in the world, eight other nuclear reactors, and five plutonium-processing complexes. When plutonium production ended in 1989, left behind were tens of millions of gallons of radioactive and chemical waste in large underground tanks and more than 100 square miles of contaminated groundwater resulting from the disposal of an estimated 450 billion gallons of liquids to soil disposal sites. So for the past 30 years the U.S. Department of Energy has been working with the Environmental Protection Agency and the Washington State Department of Ecology to clean up Hanford, which is located on 580 square miles (nearly 500,000 acres) in south-central Washington, whole parts of it adjacent to the Columbia River - the largest river in the Pacific Northwest and a critical thoroughfare for industry and wildlife.
To track the cleanup effort, workers have relied on drilling wells at the Hanford Site and placing sensors in those wells to collect data about geologic properties and groundwater flow and observe the progression of contaminants. Subsurface environments like the Hanford Site are very heterogeneous with varying in space properties, explained Alex Tartakovsky, a computational mathematician at PNNL and co-author on the SC19 paper. “Estimating the Hanford Site properties from data only would require more than a million measurements, and in practice we have maybe a thousand. The laws of physics help us compensate for the lack of data."
“The standard parameter estimation approach is to assume that the parameters can take many different forms, and then for each form you have to solve subsurface flow equations perhaps millions of times to determine parameters best fitting the observations,” Tartakovsky added. But for this study the research team took a different tack: using a physics-informed GAN and high performance computing to estimate parameters and quantify uncertainty in the subsurface flow.
For this early validation work, the researchers opted to use synthetic data - data generated by a computed model based on expert knowledge about the Hanford Site. This enabled them to create a virtual representation of the site that they could then manipulate as needed based on the parameters they were interested in measuring - primarily hydraulic conductivity and hydraulic head, both key to modeling the location of the contaminants. Future studies will incorporate real sensor data and real-world conditions.
“The initial purpose of this project was to estimate the accuracy of the methods, so we used synthetic data instead of real measurements,” Tartakovsky said. “This allowed us to estimate the performance of the physics-informed GANS as a function of the number of measurements.”
In training the GAN on the Summit supercomputer at the Oak Ridge Leadership Computing Facility OLCF, the team was able to achieve 1.2 exaflop peak and sustained performance – the first example of a large-scale GAN architecture applied to SPDEs. The geographic extent, spatial heterogeneity, and multiple correlation length scales of the Hanford Site required training the GAN model to thousands of dimensions, so the team developed a highly optimized implementation that scaled to 27,504 NVIDIA V100 Tensor Core GPUs and 4,584 nodes on Summit with a 93.1% scaling efficiency.
“Achieving such a massive scale and performance required full stack optimization and multiple strategies to extract maximum parallelism,” said Mike Houston, who leads the AI Systems team at NVIDIA. “At the chip level, we optimized the structure and design of the neural network to maximize Tensor Core utilization via cuDNN support in TensorFlow. At the node level, we used NCCL and NVLink for high-speed data exchange. And at the system level, we optimized Horovod and MPI not only to combine the data and models but to handle adversary parallel strategies. To maximize utilization of our GPUs, we had to shard the data and then distribute it to align with the parallelization technique.”
“This is a new high-water mark for GAN architectures,” Prabhat said. “We wanted to create an inexpensive surrogate for a very costly simulation, and what we were able to show here is that a physics-constrained GAN architecture can produce spatial fields consistent with our knowledge of physics. In addition, this exemplar project brought together experts from subsurface modeling, applied mathematics, deep learning, and HPC. As the DOE considers broader applications of deep learning - and, in particular, GANs - to simulation problems, I expect multiple research teams to be inspired by these results.”
This research is supported in part by the DOE’s Center for Physics Informed Learning Machines (PhILMs), a collaboration between PNNL and Sandia Laboratory, with academic partners at Brown University, Massachusetts Institute of Technology, Stanford University, and the University of California, Santa Barbara.
The paper, “Highly Scalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs,” will be presented at the SC19 Deep Learning on Supercomputers workshop. In addition to Karniadakis, Prabhat, Tartakovsky, and Houston, co-authors are Thorsten Kurth of NERSC, L. Yang of Brown University, David Barajas-Solano of PNNL, Sean Treichler and Joshua Romero of NVIDIA, and Keno Fischer and Valentin Churavy of Julia Computing.
NERSC and OLCF are DOE Office of Science user facilities.
MORE NEWS FROM
Lawrence Berkeley National Laboratory
comments 
commenting policy
Participating Labs
- DOE Office of Science
- Argonne National Laboratory
- Oak Ridge National Laboratory
- Pacific Northwest National Laboratory
- Iowa State University, Ames Laboratory
- Brookhaven National Laboratory
- Princeton Plasma Physics Laboratory
- Lawrence Berkeley National Laboratory
- Thomas Jefferson National Accelerator Facility
- Fermi National Accelerator Laboratory (Fermilab)
- SLAC National Accelerator Laboratory
Batten down the hatches: Preventing heat leaks to help create a star on Earth
PPPL physicists have identified a method by which instabilities can be tamed and heat can be prevented from leaking from fusion plasma, giving scientists a better grasp on how to optimize conditions for fusion in devices known as tokamaks.
Quenching Water Scarcity with a Good Pore
Researchers at UC San Diego and MIT linked theory and experiment to move closer to developing materials that address global water scarcity.
Simulations Attempt to Reconstruct One of the Most Explosive Events in the Universe: A Neutron Star Merger
A team led by scientists that included Berkeley Lab researchers has simulated the formation of a disc of matter, a giant burst of ejected matter, and the startup of energetic jets in the aftermath of a merger by two neutron stars.
Tiny Quantum Sensors Watch Materials Transform Under Pressure
Scientists at Berkeley Lab have developed a diamond anvil sensor that could lead to a new generation of smart, designer materials, as well as the synthesis of new chemical compounds, atomically fine-tuned by pressure.
Scientists harvest energy from light using bio-inspired artificial cells
By replicating biological machinery with non-biological components, scientists have created artificial cells that convert light into chemical energy.
Argonne's debt to 2019 Nobel Prize for lithium-ion battery
A roar of approval rang out at the U.S. Department of Energy's (DOE's) Argonne National Laboratory upon the announcement in October that John B. Goodenough, M. Stanley Whittingham and Akira Yoshino had won the 2019 Nobel Prize in Chemistry. On December 10th in Stockholm, they received this highly coveted prize for their major contributions to the invention of the lithium-ion battery, which is a long-standing major focus of research at Argonne.
Battery collaboration meeting discusses new pathways to recycle lithium-ion batteries
At a conference held by the ReCell Center, an advanced battery recycling collaboration based at Argonne, representatives from industry, government, and academia discussed innovative approaches for lithium-ion battery recycling.
New Function for Plant Enzyme Could Lead to Green Chemistry
Scientists at Brookhaven National Laboratory have discovered a new function in a plant enzyme that could inspire the design of new chemical catalysts. The enzyme catalyzes, or initiates, one of the cornerstone chemical reactions needed to synthesize a wide array of organic molecules, including those found in lubricants, cosmetics, and those used as raw materials for making plastics.
Freeze Frame: Scientists Capture Atomic-Scale Snapshots of Artificial Proteins
Scientists at Berkeley Lab are the first to use cryo-EM (cryogenic electron microscopy), a Nobel Prize-winning technique originally designed to image proteins in solution, to image atomic changes in a synthetic soft material.
Argonne Collaboration Shows Benefits of Better Corn Residue Management Strategies
Sustainable corn stover removal can maintain soil carbon stock, according a new Argonne-led study.
James Wilson Clark, PPPL's first deputy director for administrative operations, was a decorated World War II veteran, experienced federal administrator, and active member of the Princeton community
James W. Clark, PPPL's first deputy director for administrative operations, was a decorated World War II veteran with a long career in public service, who died Aug. 6. A memorial service in his honor will be held Dec. 21.
Department of Energy to Provide $24 Million in EPSCoR Grants for Energy-Related Research
The U.S. Department of Energy (DOE) announced a funding opportunity for up to $24 million for new grants under the Established Program to Stimulate Competitive Research (DOE EPSCoR).
University of Kentucky Grant Seeks to Turn Coal Into Carbon Fiber
UK's Center for Applied Energy Research (CAER) has received a $1.8 million U.S. Department of Energy (DOE) grant to transform coal tar pitch into high-value carbon fiber for use in aircraft, automobiles, sporting goods and other high-performance materials.
Six Berkeley Lab Scientists Named AAAS Fellows
Six scientists from the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have been named Fellows of the American Association for the Advancement of Science (AAAS).
PPPL is recognized for being green
The U.S. Department of Energy's Princeton Plasma Physics Laboratory was recognized by the U.S. Environmental Protection Agency for its green practices in reducing waste, energy, and water, and transportation, and for green purchasing and electronics recycling.
Dmitri Zakharov Recognized with the 2019 Chuck Fiori Award
The award honors Dmitri Zakharov's contributions to environmental transmission electron microscopy at Brookhaven Lab's Center for Functional Nanomaterials.
Two Argonne projects earn Secretary of Energy Honor Awards
With this year's Nobel Prize in Chemistry awarded for the development of lithium-ion batteries, directors of the Joint Center for Energy Storage Research share perspectives on the future of energy storage.
Argonne teams up with Altair to manage use of upcoming Aurora supercomputer
Argonne National Laboratory and Altair, a global technology company, have created a new scheduling system that will be employed on the Aurora supercomputer.
University of Maryland, Baltimore County wins DOE's 2019 CyberForce Competition(tm)
After a long suspenseful day, University of Maryland, Baltimore County earned the top spot as national winner of the U.S. Department of Energy's CyberForce Competition.
In its 15th year, INCITE advances open science with supercomputer grants to 47 projects
The U.S. Department of Energy's Office of Science announced allocations of supercomputer access to 47 science projects for 2020--awarding 60 percent of the available time on some of the nation's most powerful supercomputers, with the ultimate goal of accelerating discovery and innovation. In 2020, 14 projects will run on Theta and 39 projects on Summit, where six of these projects will receive an allocation on both systems.
Harvesting Energy from Light using Bio-inspired Artificial Cells
Scientists designed and connected two different artificial cells to each other to produce molecules called ATP (adenosine triphosphate).
Engineering Living Scaffolds for Building Materials
Bone and mollusk shells are composite systems that combine living cells and inorganic components. This allows them to regenerate and change structure while also being very strong and durable. Borrowing from this amazing complexity, researchers have been exploring a new class of materials called engineered living materials (ELMs).
Excavating Quantum Information Buried in Noise
Researchers developed two new methods to assess and remove error in how scientists measure quantum systems. By reducing quantum "noise" - uncertainty inherent to quantum processes - these new methods improve accuracy and precision.
How Electrons Move in a Catastrophe
Lanthanum strontium manganite (LSMO) is a widely applicable material, from magnetic tunnel junctions to solid oxide fuel cells. However, when it gets thin, its behavior changes for the worse. The reason why was not known. Now, using two theoretical methods, a team determined what happens.
When Ions and Molecules Cluster
How an ion behaves when isolated within an analytical instrument can differ from how it behaves in the environment. Now, Xue-Bin Wang at Pacific Northwest National Laboratory devised a way to bring ions and molecules together in clusters to better discover their properties and predict their behavior.
Tune in to Tetrahedral Superstructures
Shape affects how the particles fit together and, in turn, the resulting material. For the first time, a team observed the self-assembly of nanoparticles with tetrahedral shapes.
Tracing Interstellar Dust Back to the Solar System's Formation
This study is the first to confirm dust particles pre-dating the formation of our solar system. Further study of these materials will enable a deeper understanding of the processes that formed and have since altered them.
Investigating Materials that Can Go the Distance in Fusion Reactors
Future fusion reactors will require materials that can withstand extreme operating conditions, including being bombarded by high-energy neutrons at high temperatures. Scientists recently irradiated titanium diboride (TiB2) in the High Flux Isotope Reactor (HFIR) to better understand the effects of fusion neutrons on performance.
Better 3-D Imaging of Tumors in the Breast with Less Radiation
In breast cancer screening, an imaging technique based on nuclear medicine is currently being used as a successful secondary screening tool alongside mammography to improve the accuracy of the diagnosis. Now, a team is hoping to improve this imaging technique.
Microbes are Metabolic Specialists
Scientists can use genetic information to measure if microbes in the environment can perform specific ecological roles. Researchers recently analyzed the genomes of over 6,000 microbial species.
Spotlight
Barbara Garcia: A first-generation college student spends summer doing research at PPPL
Princeton Plasma Physics Laboratory
Argonne organization's scholarship fund blazes STEM pathway
Argonne National Laboratory
Brookhaven Lab, Suffolk Girl Scouts Launch Patch Program
Brookhaven National Laboratory
From an acoustic levitator to a "Neutron Bloodhound" robot, hands-on research inspires PPPL's summer interns
Princeton Plasma Physics Laboratory
Brookhaven Lab Celebrates the Bright Future of its 2019 Interns
Brookhaven National Laboratory
PPPL apprenticeship program offers young people chance to earn while they learn high-tech careers
Princeton Plasma Physics Laboratory
JSA Awards Graduate Fellowships for Research at Jefferson Lab
Thomas Jefferson National Accelerator Facility
ILSAMP Symposium showcases benefits for diverse students, STEM pipeline
Argonne National Laboratory
Integrating Scientific Computing into Science Curricula
Brookhaven National Laboratory
Students from Minnesota and Massachusetts Win DOE's 29th National Science Bowl(r)
Department of Energy, Office of Science
DOE's Science Graduate Student Research Program Selects 70 Students to Pursue Research at DOE Laboratories
Department of Energy, Office of Science
Young Women's Conference in STEM seeks to change the statistics one girl at a time
Princeton Plasma Physics Laboratory
Students team with Argonne scientists and engineers to learn about STEM careers
Argonne National Laboratory
Lynbrook High wins 2019 SLAC Regional Science Bowl competition
SLAC National Accelerator Laboratory
Equipping the next generation for a technological revolution
Argonne National Laboratory
Chemistry intern inspired by Argonne's real-world science
Argonne National Laboratory
Argonne intern streamlines the beamline
Argonne National Laboratory
Research on Light-Matter Interaction Could Lead to Improved Electronic and Optoelectronic Devices
Rensselaer Polytechnic Institute (RPI)
Innovating Our Energy Future
Oregon State University, College of Engineering
Physics graduate student takes her thesis research to a Department of Energy national lab
University of Alabama at Birmingham
"Model" students enjoy Argonne campus life
Argonne National Laboratory
Writing Code for a More Skilled and Diverse STEM Workforce
Brookhaven National Laboratory
New graduate student summer school launches at Princeton Plasma Physics Laboratory
Princeton Plasma Physics Laboratory
The Gridlock State
California State University (CSU) Chancellor's Office
Meet Jasmine Hatcher and Trishelle Copeland-Johnson
Brookhaven National Laboratory
Argonne hosts Modeling, Experimentation and Validation Summer School
Argonne National Laboratory
Undergraduate Students Extoll Benefits of National Laboratory Research Internships in Fusion and Plasma Science
Princeton Plasma Physics Laboratory
Students affected by Hurricane Maria bring their research to SLAC
SLAC National Accelerator Laboratory
Brookhaven Lab Pays Tribute to 2018 Summer Interns
Brookhaven National Laboratory
CSUMB Selected to Host Architecture at Zero Competition in 2019
California State University, Monterey Bay
From Hurricane Katrina Victim to Presidential Awardee: A SUNO Professor's Award-Winning Mentoring Efforts
Brookhaven National Laboratory
Department of Energy Invests $64 Million in Advanced Nuclear Technology
Rensselaer Polytechnic Institute (RPI)
Professor Miao Yu Named the Priti and Mukesh Chatter '82 Career Development Professor
Rensselaer Polytechnic Institute (RPI)
2018 RHIC & AGS Annual Users' Meeting: 'Illuminating the QCD Landscape'
Brookhaven National Laboratory
High-School Students Studying Carbon-Based Nanomaterials for Cancer Drug Delivery Visit Brookhaven Lab's Nanocenter
Brookhaven National Laboratory
Argonne welcomes The Martian author Andy Weir
Argonne National Laboratory
UW Professor and Clean Energy Institute Director Daniel Schwartz Wins Highest U.S. Award for STEM Mentors
University of Washington
Creating STEM Knowledge and Innovations to Solve Global Issues Like Water, Food, and Energy
Illinois Mathematics and Science Academy (IMSA)
Professor Emily Liu Receives $1.8 Million DoE Award for Solar Power Systems Research
Rensselaer Polytechnic Institute (RPI)
Celebrating 40 years of empowerment in science
Argonne National Laboratory
Introducing Graduate Students Across the Globe to Photon Science
Brookhaven National Laboratory
Students from Massachusetts and Washington Win DOE's 28th National Science Bowl(r)
Department of Energy, Office of Science
Q&A: Al Ashley Reflects on His Efforts to Diversify SLAC and Beyond
SLAC National Accelerator Laboratory
Insights on Innovation in Energy, Humanitarian Aid Highlight UVA Darden's Net Impact Week
University of Virginia Darden School of Business
Ivy League Graduate, Writer and Activist with Dyslexia Visits CSUCI to Reframe the Concept of Learning Disabilities
California State University, Channel Islands
Photographer Adam Nadel Selected as Fermilab's New Artist-in-Residence for 2018
Fermi National Accelerator Laboratory (Fermilab)
Showing results
0-4 Of 2215