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DOE OSTI2020

Interpenetrating Plasma Simulations

This project investigated multifluid models for simulating interpenetrating plasmas. These models solve the Euler equations for each plasma stream along with an appropriate model for electron dynamics. The project developed a novel code, Euclid, that simulates these models using high-order conservative spatial discretization methods and explicit and semi-implicit time integration methods. Euclid was used to solve several multifluid test cases representative of plasma dynamics in high-energy density physics experiments. Kinetic simulations of interpenetrating flows using the LOKI code revealed novel physical effects of the ion-ion streaming instability. A new multi-flow collision operator was developed for the LOKI code. A simple model of the ion-ion streaming instability was also developed. Several presentations were given on the project results; three journal articles have been published, one has been submitted, and two are planned.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

IC Report for project “Developing nonlinear laser-plasma instability models for high-fidelity, multi-physics simulation capability for ICF/HED” [Slides]

We’ve achieved our technical goals: (1) Perform large-scale kinetic simulations of SRS and CBET a range of plasma and laser conditions; (2) Develop a new $\delta f$-Gaussian-mixture algorithm to represent non-Maxwellian distribution functions from particle trapping and time-dependent plasma response; (3) Develop physics-based preliminary nonlinear LPI models for coupling to LRT/ Mazinisin and AMP; and (4) Begin implementation of LPI sub-grid models into Mazinisin.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2003

Alabama NASA EPSCoR Preparation Grant Program: Grant No. NCC5-391

The funded research projects under the Experimental Program to Stimulate Cooperative Research (EPSCoR) grant program and the student fellowship awards are summarized in this report. The projects include: 1) Crystallization of Dehydratase/DcoH: A Target in Lung Disease; 2) Measuring Velocity Profiles in Liquid Metals using an Ultrasonic Doppler Velocimeter; 3) Synthesis, Structure, and Properties of New Thermoelectric Materials; 4) Computational Determination of Structures and Reactivity of Phenol-Formaldehyde Resins; 5) Synthesis of Microbial Polyesters in the NASA Bioreactor; 6) Visualization of Flow-Fields in Magnetocombustion; 7) Synthesis of Fluorescent Saccharide Derivatives. The student fellowship awards include: 1) Distributed Fusion of Satellite Images; 2) Study of the Relationship between Urban Development, Local Climate, and Water Quality for the Atlanta, Georgia Metrop; 3) Computer Simulation of the Effectiveness of a Spring-Loaded Exercise Device.

Gregory, John C.↗

DOE OSTI2012

PROTOPLASMA - Proton-driven plasma-wakefield experiment at Fermilab: Stages and approach

Generation of TeV-scale electron beams using conventional RF technology appears expensive for building the next generation of colliders. Proton-driven plasma-wakefield acceleration of electrons promises an alternative route to generate TeV-scale electron beams using existing proton machines. PROTOPLASMA is the proposed R and D project at Fermilab that plans to use a proton beam driven plasma-wakefield to accelerate electrons. The project is planned in stages with the project's path guided by simulations. First, a 60-120 GeV proton beam will be injected into 1-2 meters of plasma to observe selfmodulation instability in the proton beam. Next, an injected 5 MeV electron beam will be accelerated by the plasma. In this paper, we report on the basic project plan and outline our staged approach. We report on first simulation results that show self-modulation of a proton bunch and discuss beam optics requirements and other limits.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Unraveling the Physics Associated with the Production of Extremely Dense Plasma States of Microscale Nanosecond-pulsed Discharges

The research carried out on this grant aimed to study the properties of anomalously dense plasmas formed in so-called ”fast” discharges, such as high pressure narrow-gap nanosecond pulsed discharges and short pulse (nanosecond-scale) laser driven discharges. These fast discharges are receiving much attention as they now enable new applications in aerodynamics, combustion, biology, and medicine. The mechanisms that generate these high electron densities (ne > 10 19 cm −3 ) that encroach on warm dense matter regimes are not well understood. Such densities are orders of magnitude higher than those (≈ 10 15 cm −3 ) routinely seen in classical high-pressures (streamer) discharges. Furthermore, the dense plasmas are reported to be highly nonequilibrium, with T gas <<, T i << T e . These properties would place these discharges in a regime of near full ionization (Z ≥ 1) where there is inadequate electron screening and therefore strong ion coupling - physics that is not generally accounted for in simulations. In this project work, we seek to study these fast discharges, validate simulations with experiments at pressures as high as 10-50 bar, and augment plasma production to even higher levels of n e (> 10 20 cm −3 ) with second-stage picosecond laser heating. In parallel, we have studied the use of these fast discharges in reactive gases, unraveling mechanisms related to the fast discharge dissociation of CO 2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Final Report for Large Scale Laboratory Experiments on Kinetic Magnetic Reconnection

Magnetic reconnection plays a fundamental role in nearly all magnetized plasmas as it enables magnetic energy to be converted into high speed flows, and thermal energy. It allows the magnetic field lines to change topology in collisionless plasmas, and it thereby controls the spatial and temporal evolution of explosive phenomena such as solar flares, coronal mass ejections, and internal disruptions in fusion devices. Because of its strong impact on the plasma dynamics, understanding the physics of magnetic reconnection is one of the most important topics in plasma physics. New frontiers have now emerged in reconnection research with an emphasis on particle energization, reconnection with multiple X-lines in large systems, and the role of kinetic effects in collisionless reconnection. These research topics are closely linked and large scale computer simulations show that 3D effects are likely important to explain the detailed observations of reconnection in solar, interplanetary and magnetospheric plasmas. For experiments to remain relevant in this maturing field of research and help push forward the new frontiers, new devices are needed which access the regimes of large system size and low normalized collisionallity. To address this need, the project the new Terrestrial Reconnection EXperiment (TREX), which is spatially the largest dedicated reconnection experiment constructed to date. With the use of the 3m diameter spherical vacuum vessel of the Madison Plasma Dynamo Experiment (MPDX), the TREX is highly leveraged by earlier NSF investments. MPDX was constructed with funds from NSF's MRI program and is now being operated as a multi-investigator facility, which we name the Wisconsin Plasma Physics Laboratory (WiPPL). The project was carried out mainly by two UW-Madison graduate students, for reconnection in parameter regimes and configurations in TREX not attainable by previous experiments. The implementation of TREX within WiPPL renders the upgraded facility unique in its capabilities to extend the frontiers of experimental reconnection research, including access to reconnection in the collisionless regime at large system sizes and compatible with three-dimensional configurations. The theoretical teams in reconnection research have been given full access to the experimental results. Our experimental results havel allowed us to test existing theoretical models, provide resolution to controversy, and stimulate new understanding of magnetic reconnection. The WiPPAL, with its large basic plasma physics device, is largely operated by graduate and undergraduate students. It has proven an ideal facility for students to become immersed in state of the art research while learning the fundamental principles of plasma physics. The program has also proven effective in attracting new outstanding students into plasma physics and providing them with exciting learning experiences. While our research program and experimental results successfully compete with those of professional scientists at national labs, the most important legacy of our research is, perhaps, the broad training in experimental plasma physics of the large number of students affiliated with our program.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Extending the path for efficient extreme ultraviolet sources for advanced nanolithography

Developing efficient light sources for extreme ultraviolet (EUV) lithography is one of the most important problems of high volume manufacturing (HVM) of the next generation computer chips. Critical components of this technology are continued to face challenges in the demanding performance for HVM. Current investigations of EUV and beyond EUV (BEUV) community are focused on the dual-pulse laser produced plasma (LPP) using droplets of mass-limited targets. Two main objectives as well as challenges in the optimization of these light sources are related to enhancement of the conversion efficiency (CE) of the source and increase components lifetime of the collector optical system. These require significant experimental and computer simulation efforts. These requirements call for fine detail analysis of various plasma physics processes involved in laser target interactions and their effects on source optimization. We continued to enhance our comprehensive HEIGHTS simulation package and upgrade our CMUXE laboratories to study and optimize the efficiency of LPP sources. Integrated modeling and experimental research were done to both benchmark simulation results and to make projections and realistic predictions of the development path for powerful EUVL devices for HVM requirements. We continued the detail analysis of dual-pulse laser systems using various laser wavelengths and delay times between the two pulses. We showed that the efficiency of EUV sources can be improved utilizing the higher harmonics of Nd:YAG laser for the prepulse and the first harmonics for the main pulse, while still having lower efficiency than the combination involving CO{sub 2} laser in the range of parameters studied in this case. The differences in optimization process as well as in the source characteristics for two combinations of laser wavelengths were analyzed based on details of atomic and hydrodynamics processes during the evolving plasma plumes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Partnership for Edge Physics Simulation (EPSI)

We propose to develop advanced simulation codes, based upon an extreme parallelism, first principles kinetic approach, to address the challenges associated with the edge region of magnetically confined plasmas. This work is relevant to both existing magnetic fusion facilities and essential for next-generation burning plasma experiments, such as ITER where success is critically dependent upon H-mode operation achieving an edge pedestal of sufficient height for good core plasma performance without producing deleterious large scale edge localized instabilities. The plasma edge presents a well-known set of multi-physics, multi-scale problems involving complex 3D magnetic geometry. Perhaps the greatest computational challenge is the lack of scale separation – temporal scales for drift waves, Alfven waves, ELM dynamics for example have strong overlap. Similar overlap occurs on the spatial scales for the ion poloidal gyro-radius, drift wave and pedestal width. The traditional approach of separating fusion problems into weakly interacting spatial or temporal domains clearly breaks down in the edge. A full kinetic model (full-f model) must be solved to understand and predict the edge physics including non-equilibrium thermodynamic issues arising from the magnetic topology (the open field lines producing a spatially sensitive velocity hole), plasma wall interactions, neutral and atomic physics. The plan here is to model these phenomena within a comprehensive first principles set of equations without the need for the insurmountable multiple-codes coupling issues by building on the XGC1 code developed under the SciDAC Proto-FSP Center for Plasma Edge Simulation (CPES). This proposal includes the critical participants in the XGC1 development. We propose enhancing the capability of XGC1 by including all the important turbulence physics contained in kinetic ion and electron electromagnetic dynamics, by extending the PIC technology to incorporate several positive features found in the Eulerian grid technology, combining the coarse grained XGC0 code into it with a multiscale projective time integration technique to be developed in the project for experimental time scale simulation of the edge multi-physics, and by implementing modern computational technologies to move forward with the extreme scale heterogeneous hardware/software platform development. Ultra-fast edge localized instabilities, involving compressional Alven modes, will be studied using a proper MHD or two-fluid codes employing kinetic closure information from XGC. The proposed research integrates the most important physical processes on overlapping temporal and spatial scales, to study (i) transitions and thresholds for enhanced confinement regimes, (ii) the predictive understanding of the edge pedestal formation, structure and dynamics, (iii) the effect of the edge plasma on the core confinement, (iv) the physics of Edge Localized Modes and their suppression or mitigation via external control techniques, and (v) the heat load on the material wall. Our approach will implement physical models that are valid in their relevant collisionality regimes for current experiments and future burning plasma devices. Comparisons with experimental data will be made at multiple levels including characterization of turbulence dynamics, flux-gradient responses in the energy, particle and momentum channels, and observations of global phenomena such as L-H transitions, momentum generation, ELM dynamics, ELM-free regimes and the tokamak density limit. The proposal team has established strong connections, through joint membership, with other organizations that will be critical for success. These include FASTMath, SUPER and QUEST Institutes respectively for meshing tools and solvers; code performance tuning and uncertainty quantification as well as a proposed Data Management and Visualization Institute.. We will also be teaming with ongoing fusion SciDAC’s: CSWPI for RF-edge plasmas interactions; CEMM for the M3D MHD simulations and with PEPSC for incorporation of energetic particle physics. Finally, the team includes representatives from each of the major U.S. experimental facilities who will coordinate the validation program and the development of synthetic diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

University of Tennessee, Knoxville (UTK) contribution to: Deciphering the role of mixed-material deposition and temperature on lithium-coated PFCs in NSTX-U high-performance plasmas: Collaborative UIUC & UTK Proposal (Final Report)

This report describes the final product of model development to decipher the role of mixed material deposition and temperature on lithium-coated PFCs in NSTX-U. The computational modeling approach used to address these specific questions involved a pragmatic multiscale materials modeling framework, with the use of reaction-diffusion based continuum simulations, through modifications to the SDTrimSP code. This pragmatic modeling was supplemented with a few, select parametric ab-initio and molecular dynamics simulations, to investigate the effect of lithium and mixed lithium-carbon-refractory metal chemistry and surface morphology and chemistry on erosion yields and deuterium uptake, including the role of temperature and boronization. The main progress of the project was to develop the major framework and structure of the model, although validated application of the model was limited as a result of the unplanned shutdown and outage of NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

Reduced Variance for Material Sources in Implicit Monte Carlo

Implicit Monte Carlo (IMC), a time-implicit method due to Fleck and Cummings, is used for simulating supernovae and inertial confinement fusion (ICF) systems where x-rays tightly and nonlinearly interact with hot material. The IMC algorithm represents absorption and emission within a timestep as an effective scatter. Similarly, the IMC time-implicitness splits off a portion of a material source directly into the radiation field. We have found that some of our variance reduction and particle management schemes will allow large variances in the presence of small, but important, material sources, as in the case of ICF hot electron preheat sources. We propose a modification of our implementation of the IMC method in the Jayenne IMC Project. Instead of battling the sampling issues associated with a small source, we bypass the IMC implicitness altogether and simply deterministically update the material state with the material source if the temperature of the spatial cell is below a user-specified cutoff. We describe the modified method and present results on a test problem that show the elimination of variance for small sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

New proposed ITER divertor design using carbon insert on tungsten to mitigate ELMs and secondary radiation effects on nearby components

Abstract Building a successful device for the magnetic fusion energy production is a great challenge. ITER is an international project of the tokamak based magnetic fusion design being developed for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. A key obstacle to a successful magnetic fusion energy production is however, the performance during abnormal events including plasma disruptions and edge-localized modes (ELMs). A credible reactor design must tolerate at least a few of these transient events without serious consequences such as melting of the structure. This paper investigates and compares the performance of the current ITER tokamak design during two types of transient events, i.e., ELMs occurring at normal operation and disruptions during abnormal operation. We simulated the divertor components response using our integrated 3D HEIGHTS package. The simulations include self-consistent modeling of the interaction of the released core plasma particles with the initial solid divertor material, energy deposition processes, vaporization of divertor material, secondary plasma formation and MHD evolution, incident core particles collisions and scattering from this dense secondary plasma, photon radiation of secondary plasma, and the resulting heat loads on nearby components. Our simulations showed that using a small carbon insert around the strike point can significantly reduce the overall expected damage on the tungsten dome structure, reflector plates, and prevent tungsten vaporization and its potential core plasma contamination.

47 OTHER INSTRUMENTATION↗

DOE OSTI2013

Global Field Aligned Mesh and Gyrokinetic Field Solver in a Tokamak Edge Geometry (Final Technical Report)

This project was a collaboration between researchers at the California Institute of Technology and the University of California, Irvine to investigate the utility of a global field-aligned mesh and gyrokinetic field solver for simulations of the tokamak plasma edge region. Mesh generation software from UC Irvine was tested with specific tokamak edge magnetic geometry scenarios and the quality of the meshes and the solutions to the gyrokinetic Poisson equation were evaluated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Non-disruptive error field measurement in DIII-D low safety factor plasmas and projection to ITER

Previous experiments in DIII-D (Paz-Soldan et al 2022 Nucl. Fusion 62 126007) introduced a method to identify intrinsic error fields (EFs) in tokamaks with minimal disruption risk by promptly healing driven magnetic islands during the conventional 'compass scan'. This paper presents recent experimental and numerical advancements in extending this approach to low q 95 plasmas, and projects its applicability to ITER. Non-disruptive EF measurement is achieved at q 95 = 4.5 and 3.9 without any initial EF correction (EFC) by reducing the time between the occurrence of the locked mode (LM) and control action to 10 ms and increasing the density 50%–100%. However, 50% correction of the intrinsic EF is required to achieve island healing at q 95 = 3.2 with 10 ms delay for the control action. Nonlinear two-fluid modeling with the TM1 code reproduces the DIII-D experimental observations, indicating that promptly turning off the 3D coil current reduces both magnetic island width and electromagnetic force, while raising the density increases plasma viscosity, facilitating magnetic island healing. The simulations show that for scenarios with q 95 = 3.2, lowering the control action time to 5 ms will lead to island healing without EFC. TM1 simulations are extended to future ITER scenarios with 5 MA and 7.5 MA plasma currents, predicting the dependence of required density rise on action time and EF amplitude. These simulations indicate that, benefiting from the much longer resistive time, island healing can be successfully achieved in ITER when taking control action 100–500 ms after a LM occurrence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2011

Science and Technology Review December 2011

This month's issue has the following articles: (1) High-Performance Computing for Energy Innovation - Commentary by Tomas Diaz de la Rubia; (2) Simulating the Next Generation of Energy Technologies - Projects using high-performance computing demonstrate Livermore's computational horsepower and improve the quality of energy solutions and the speed of deployment; (3) ARC Comes into Focus - The Advanced Radiographic Capability, a petawatt-class laser, can penetrate dense objects to reveal material dynamics during National Ignition Facility experiments; (4) A New Method to Track Viral Evolution - A sensitive technique developed at the Laboratory can identify virus mutations that may jump from host to host; and (5) Data for Defense: New Software Finds It Fast - Department of Defense warfighters and planners are using Livermore software systems to extract pertinent information from massive amounts of data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Climate Nowcasting

The climate is changing so rapidly that climatologies based on historical statistics cannot reliably capture the current risk of extreme weather events hazardous to society. Decision relevant projections of weather extreme probability over the next 10–15 years are needed to enable adaptation and resilience in the face of this evolving risk. Current weather forecasts/predictions and long-term climate projections for decades into the future are inadequate for providing this information to stakeholders that need it, targeting forecast horizons either too short or too far into the future. We argue that a new approach is needed: climate nowcasting. Climate nowcasting would focus on user-inspired extreme metrics over the next 10–15 year time frame, targeting specific impacts and locations down to a local scale, by engaging with stakeholders to understand their needs and provide information in a format relevant for decision making. Importantly, climate nowcasting will not consist of a single approach or data set, involving rather data fusion from different sources of information: simulations, observations and data driven methods, likely through different weights depending on the metric of interest. Predictions must be accompanied by serious engagement with stakeholders facing climate risks, and clearly present uncertainties and limitations of any prediction. Such a vision is very different from how typical climate or weather forecasts are applied today.

Gettelman, Andrew↗

DOE OSTI2020

Simulations of Laser Experiments to Study the Origin of Cosmic Magnetic Fields

Magnetic fields are ubiquitous in the universe; however, their origin is not fully understood. Cosmologists and astrophysicists have proposed a variety of ways in which small seed magnetic fields could be created. It is widely thought that the much larger values of the cosmic magnetic fields that we observe are a result of the amplification of these seed fields by the nonlinear turbulent dynamo mechanism. Such a mechanism had not yet been demonstrated in a controlled laboratory environment. We conceived experiments designed to demonstrate and study the nonlinear turbulent dynamo mechanism in the laboratory. These experiments characterize the distribution of turbulent energy among the velocity, magnetic field, and density fluctuations, providing a comprehensive picture of the energy cascade in a magnetized, turbulent plasma. The experiments build on the pathfinder experiments we have conducted on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and the OMEGA laser at Laboratory for Laser Energetics at Rochester. They utilize the high-intensity lasers at the Omega Laser Facility, the National Ignition Facility (NIF) at LLNL and the Laser Megajoule (LMJ) Facility in France – the largest laser facilities in the world. The goal of this project was to design and model the highly demanding experiments through simulation campaigns using FLASH, a highly capable radiation-MHD code we have developed, and large-scale 3D simulations on the Mira supercomputer at ANL. The simulations were vital to ensuring the experiments achieve the strong turbulence and large magnetic Reynolds numbers required for the nonlinear turbulent dynamo mechanism to operate. The simulations were also critical to determining when to fire the diagnostics, since the experiments last tens of nanoseconds but the signals of the strongly amplified magnetic fields last only a few nanoseconds. Finally, high-fidelity, validated FLASH simulations were crucial to interpreting the results of the experiments. By combining theory, experiments, and simulations, we were able to succeed in demonstrating and characterizing the nonlinear turbulent dynamo mechanism. The effort leveraged (1) the emergence of the Flash Center for Computational Science as a leader in numerical modeling of academic High Energy Density Physics (HEDP) experiments; (2) the FLASH code, which has been developed by the Flash Center and is a leadership-class, multi- physics, publicly available community code that has been applied successfully in many laser-driven experiments; (3) the expertise acquired through pathfinder experiments we performed on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and on the Omega laser facility; (4) the experience we have gained in designing and interpreting these experiments using validated simulations done with FLASH; and (5) the close collaborations we have established with outstanding experimental groups in the US and abroad. The broader impacts of the project are two-fold: (1) the work furthered the transformation of the academic community’s ability to design and analyze HEDP experiments at large laser facilities that is happening through the availability of FLASH and its widespread adoption by the academic community – a community that previously had had limited access to open and validated hydro/MHD simulation tools for HEDP experiments; and (2) the work trained young scientists to design and interpret HEDP experiments using validated simulations – a critical national need.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Final Scientific/Technical Report: Correlations and Fluctuations in Weakly Collisional Plasma

Plasma is a state of matter that exhibits a very rich range of phenomena. To begin with, plasma is both electrical and mechanical - bringing together theories of particle motion and the electromagnetic field. Furthermore, and especially important for this project, a weakly-collisional plasma, such as is found in high-temperature (fusion energy) experiments on earth and the majority of contexts in space and astrophysics, has many moving parts. For example, sitting in earth’s atmosphere we are immersed in a mechanical wave field (sound), a possibly turbulent fluid motion (wind), and an electromagnetic vector wave field with two polarizations (light). This is already enough to produce a rich range of possibilities. In plasma, the electromagnetic field is coupled to the mechanical motion of the medium because it is ionized. Furthermore, a weakly-collisional plasma supports an infinite number of mechanically independent fluids. Thus, plasmas support an infinite number of independent electromechanical waves. Much has been done to describe plasmas with "reduced models" of various kinds. The goal of this project was to both explore the validity of reduced plasma models that are in use, and to propose and validate new models of plasma motion. The primary means to his end was laboratory experiments employing both electrical probes and laser spectroscopy. Laser spectroscopy enables many techniques which can separate the spectrum of independent fluid motions in the ion phase-space. The choice was to focus on low frequency electrostatic waves because the electron motion is relatively simple, the experiments can be on a spatial scale of a few meters, and all the relevant parameters can be measured with a few lasers systems. No study of this kind had previously been undertaken for the study of plasmas. The validation of theories required that the experimental descriptions be compared with theory and simulation in detail. It was found that even multi-fluid theories leave out a large part of the complexity of plasma motion. Reduced descriptions were found to fail under most circumstances. A new technique was developed that enabled a measurement of the phase-space resolved ion correlation function for the first time. The wide range of plasma dynamics possible became clear through this technique. It was found that collisionless (Vlasov) theory has a large field of application even when the plasma is weakly-collisional. A new approach, the kinetic wave expansion, was proposed, tested and found to be very useful for describing electrostatic ion waves. This project demonstrated a new way of looking at the "degrees-of-freedom" of plasmas and provided significant validation tests of fluid and kinetic plasma descriptions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗