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At least 199 records · Page 11

A high-order adaptive algorithm for multispecies gaseous flows on mapped domains

We report a fourth-order accurate finite-volume method is developed and verified for solving strongly nonlinear, time-dependent, compressible, thermally perfect, and multispecies gaseous flows on mapped grids that are adaptively refined in space and time. The algorithm introduces a new scheme for numerical flux calculations in order to cope with the nonlinear, spatially and temporally varying thermodynamic and transport properties of the gaseous mixture. The fourth-order numerical error convergence and solution accuracy are verified using Couette flow, species mass diffusion bubble, and vortex convection and diffusion problem. The thermally perfect, multispecies functionality is validated using a one-dimensional shock tube and two-dimensional shock box problem. Results are obtained for the Mach reflection problem where a strong shock propagates in the multispecies gaseous flow along a ramp and are compared to the solution of the shock propagation in a single species, calorically perfect, gaseous flow over the same ramp. The validated algorithm is then applied to simulate a relatively complex flow configuration to examine the secondary flow mixing due to the double air jets along with the main inlet where a premixed fuel mixture flows in. Future investigations will focus on three-dimensional configurations.

42 ENGINEERING↗

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Reduced scale stripline platform to extend accessible pressures on the Z machine: Shockless compression of platinum to 650 GPa

Reaching astrophysically relevant high energy density (HED) material states in the laboratory is an ongoing effort at multiple experimental facilities. We have developed a new dynamic compression platform for the Z Pulsed Power Facility that allows for sample sizes 100s of [Formula: see text]m in thickness that accommodate multiple grains in order to fully capture bulk properties, such as material strength. A pair of experiments compressed platinum (Pt) to HED conditions and conventional inverse Lagrangian analysis as well as a recent Bayesian calibration technique were used to determine the principal isentrope to 650 GPa with density uncertainties of <2%. These low uncertainties are calculated for single sample experiments, presenting the possibility of even smaller experimental uncertainties with multiple samples the platform allows. Our new platform extends the accessible Pt ramp pressures achievable on the Z machine to over 80% of the pressure recently achieved using the National Ignition Facility planar Hohlraum platform. This new capability, the next generation evolution of the stripline platform, was made possible by advancements in both our understanding of the Z pulsed power driver and our overall magnetohydrodynamic modeling capabilities.

Porwitzky, Andrew↗

National Assessment of Energy Storage for Grid Balancing and Arbitrage: Phase 1, WECC

To examine the role that energy storage could play in mitigating the impacts of the stochastic variability of wind generation on regional grid operation, the Pacific Northwest National Laboratory (PNNL) examined a hypothetical 2020 grid scenario in which additional wind generation capacity is built to meet renewable portfolio standard targets in the Western Interconnection. PNNL developed a stochastic model for estimating the balancing requirements using historical wind statistics and forecasting error, a detailed engineering model to analyze the dispatch of energy storage and fast-ramping generation devices for estimating size requirements of energy storage and generation systems for meeting new balancing requirements, and financial models for estimating the life-cycle cost of storage and generation systems in addressing the future balancing requirements for sub-regions in the Western Interconnection. Evaluated technologies include combustion turbines, sodium sulfur (Na-S) batteries, lithium ion batteries, pumped-hydro energy storage, compressed air energy storage, flywheels, redox flow batteries, and demand response. Distinct power and energy capacity requirements were estimated for each technology option, and battery size was optimized to minimize costs. Modeling results indicate that in a future power grid with high-penetration of renewables, the most cost competitive technologies for meeting balancing requirements include Na-S batteries and flywheels.

energy storage↗

Optimizing on-ramp merging for connected and automated vehicles: A hierarchical approach using deep reinforcement learning and optimal control

On-ramp merging for Connected and Automated Vehicles (CAVs) presents significant challenges in dynamic traffic environments. Traditional methods and recent learning-based approaches often fail to simultaneously address decision-making complexity and execution precision under fluctuating conditions. This study introduces a novel hierarchical framework that combines: (1) a high-level Deep Reinforcement Learning (DRL) module that coordinates merging sequences through Virtual Traffic Signals (VTS) with Yield/Green phases and (2) a low-level optimal controller generating collision-free speed trajectories via pseudospectral convex optimization. A convolutional autoencoder compresses high-dimensional traffic states to enhance responsiveness. Extensive simulations demonstrate a 12.5% improvement in mainline throughput a 28% reduction in emergency braking events, and 31.66% lower fuel consumption compared to baseline methods. Furthermore, the framework’s effectiveness in coordinating CAV merges highlights its potential for real-world deployment. Future work will extend validation to multi-lane scenarios with mixed traffic and large-scale multiple merging points.

Connected and automated vehicles↗

Development of a high current density, high temperature superconducting cable for pulsed magnets

Abstract A low AC loss Rare Earth Barium Copper Oxide (REBCO) cable, based on the VIPER cable technology has been developed by Commonwealth Fusion Systems for use in high field, REBCO based tokamaks. The new cable is composed of partitioned and transposed copper ‘petals’ shaped to fit together in a circular pattern with each petal containing a REBCO tape stack and insulated from each other to reduce AC losses. A stainless steel jacket adds mechanical robustness—also serving as a vessel for solder impregnation—while a tube runs through the middle for cooling purposes. Additionally, fiber optic sensors are placed under the tape stacks for quench detection. To qualify this design, a series of experiments were conducted as part of the SPARC tokamak Central Solenoid Model Coil program—to retire the risks associated with full scale, fast ramping, high flux HTS Central Solenoid (CS) and Poloidal Field (PF) coils for tokamak fusion power plants and net energy demonstrators. These risk study and risk reduction experiments include (1) AC loss measurement and model validation in the range of ~5 T/s, (2) an IxB electromagnetic loading of over 850 kN/m at the cable level and up to 300 kN/m at the stack level, (3) a transverse compression resilience of over 350 MPa, (4) manufacturability at tokamak relevant speeds and scales, (5) cable to cable joint performance, (6) fiber optic based quench detection speed, accuracy, and feasibility, and (7) overall winding pack integration and magnet assembly. The result is a cable technology, now referred to as PIT VIPER, with AC losses that measure fifteen times lower (at ~5 T/s) than its predecessor technology; a 2% or lower degradation of critical current (Ic) at high IxB electromagnetic loads; no detectable Ic degradation up to 570 MPa of transverse compression on the cable unit cell; end to end magnet manufacturing, consistently producing Ic values within 7% of the model prediction; cable to cable joint resistances at 20 K on the order of ~15 nΩ; and fast, functional quench detection capabilities that do not involve voltage taps. This cable technology will be tested comprehensively in a Central Solenoid Model Coil to prove its readiness for compact, high field tokamak operation.

Sanabria, Charlie (ORCID:0000000150175309)↗

EVALUATING THE COMPETITIVENESS OF ENERGY STORAGE FOR MITIGATING THE STOCHASTIC, VARIABLE ATTRIBUTES OF RENEWABLES ON THE GRID

Energy storage has recently attracted significant interest as an enabling technology for integrating stochastic, variable renewable power into the electric grid. To meet the renewable portfolio standards targets imposed by 29 U.S. states and the District of Columbia, electricity production from wind technology has increased significantly. At the same time, wind turbines, like many renewables, produce power in a manner that is stochastic, variable, and non-dispatchable. These attributes introduce challenges to generation scheduling and the provision of ancillary services. To study the impacts of the stochastic variability of wind on regional grid operation and the role that energy storage could play to mitigate these impacts, Pacific Northwest National Laboratory (PNNL) has developed a series of linked, complex techno-economic-environmental models to address these key questions: a. What are the future expanded balancing requirements necessary to accommodate enhanced wind turbine capacity, so as to meet the renewable portfolio standards in 2020? Specific analyses are conducted for the four North American Electric Reliability Corporation (NERC) western sub-regions. b. What are the most cost-effective technological solutions for providing either fast ramping generation or energy storage to serve these balancing requirements? PNNL applied a stochastic approach to assess the future, expanded balancing requirements for the four western sub-regions with high wind penetration in 2020. The estimated balancing requirements are quantified for four sub-regions: Arizona-New Mexico-Nevada (AZNMNV), California-Mexico (CAMC), Northwest Power Pool (NWPP), and Rocky Mountain Power Pool (RMPP). Model results indicate that the new balancing requirements will span a spectrum of frequencies, from minute-to-minute variability (intra-hour balancing) to those indicating cycles over several hours (inter-hour balancing). The sharp ramp rates in the intra-hour balancing are of significant concern to grid operators. Consequently, this study focuses on analyzing the intra-hour balancing needs. A detailed, life-cycle cost (LCC) modeling effort was used to assess the cost competitiveness of different technologies to address the future, intra-hour balancing requirements. Technological solutions considered include combustion turbines, sodium sulfur (NaS) batteries, lithium ion (Li-ion) batteries, pumped-hydro energy storage (PHES), compressed air energy storage (CAES), flywheels, redox flow batteries, and demand response (DR). Hybrid concepts are also evaluated. For each technology, distinct power and energy capacity requirements are estimated. LCC results indicate that the most cost competitive technologies include electrochemical energy storage and Na-S and Li-Ion. This finding is consistent among the four sub-regions and is generally applicable to other regions.

arbitrage↗

WE-Validate: An Open-Source Framework For Wind Power Validation

Grid operators rely on historical weather time series at existing and planned wind power plants to make informed decisions when planning for a future power grid with very high penetration of renewable power. While synthetic wind power time series have been developed based on historical weather models, their validation with actual power production data remains complex due to variations in modeling practices and methodologies. This paper introduces the WE-Validate framework, originally designed for wind speed validation and now enhanced for wind power validation with a graphical user interface to support users with minimal programming experience. Validation of wind power with WE-Validate is based on robust metrics consisting of RMSE, centered RMSE, average bias, average percent bias, mean absolute error, mean absolute percent error, cross correlation, and calculation of ramping magnitude, rate, and duration. This paper showcases WE-Validate with validation of synthetically derived power for a wind plant in Washington state for one month in 2018. Validation of the synthetic power from two comparison data sets compared with observations shows both comparison series have strong correlation with observed across weekly and monthly aggregations while suffering from persistent negative bias. The suite of metrics within WE-Validate facilitates immediate insight into the utility of the comparison data sets through compression across multiple axes. This user-friendly, open-source tool can be extended beyond wind power, making it a valuable resource for system planners and operators in different domains.

Moncheur de Rieudotte, Malcolm P.↗

THESEUS: A techno-economic design, integration and downselection framework for energy storage

Optimal selection of energy storage technologies is critical to ensure reliable integration of intermittent and often uncertain renewable energy in electricity grids. The consideration of a diverse set of energy storage technologies is required for a more sustainable deployment of energy storage. We present THESEUS (TecHno-Economic framework for Systematic Energy storage Utilization and downSelection), which is a comprehensive framework for the optimal selection, design and operation of energy storage systems. THESEUS includes rigorous models of major energy storage technologies at different maturity levels, such as thermal storage using phase-change materials or molten salt, cryogenic storage, mechanical storage in the form of compressed air and pumped hydro storage, chemical storage using hydrogen, and electrochemical storage in the form of lithium-ion, sodium sulfur and vanadium flow batteries. An illustrative case study on state-wide prospective energy storage shows that storage integration with fossil power plants could reduce the cost of meeting the grid energy demand by 20%, with mechanical storage as the best suited technology. Although high-temperature thermal storage has low storage efficiency, it is optimal for integration with renewable energy plants. In addition, Li-ion batteries are optimal for high ramping but low storage duration requirements. Furthermore, such insights can enable the deployment of both existing and emerging energy storage technologies to facilitate a smooth transition to a clean energy future.

25 ENERGY STORAGE↗

Turbulent Acceleration of Interstellar Pickup Ions at the Heliospheric Termination Shock Forms the Global ENA Spectrum

The heliospheric energetic neutral atom spectrum observed by the Interstellar Boundary Explorer (IBEX) reveals that the heliosheath proton distribution is consistent with a power law. The origin of the spectrum is likely from interstellar pickup ions (PUIs) accelerated at the heliospheric termination shock (HTS). We present an explanation of the proton spectrum origin using a test particle simulation of PUIs accelerated at the HTS. PUIs experience preferential heating by the motional electric field in the shock foot, but do not develop a power-law tail without the presence of turbulence at wavenumbers (k) close to the PUI gyroradius scale (R g ). Voyager 2 observations of the magnetic field downstream of the HTS indicate a moderate amount of turbulence at kR g ≅ 1, (δB /B 0 ) 2 @ 0.01, which we find to be sufficient for producing a downstream suprathermal PUI tail but not at intensities observed by IBEX. Within the shock ramp, however, Voyager observed the turbulence power at much smaller scales to be nearly 100 times stronger, suggesting the possibility of strong turbulence at the PUI gyroradius scale. We show that a proton distribution can develop a power law downstream of the HTS consistent with IBEX observations if (δB /B 0 ) 2 ≳ 0.1 at kR g ≅ 1 in the shock foot. Shock drift acceleration of PUIs by the motional electric field is aided by interactions with turbulence upstream of the shock overshoot. Steepening of the IBEX proton spectrum in directions farther from the heliospheric nose suggests the HTS compression ratio and/or turbulence power weakens near the heliotail.

79 ASTRONOMY AND ASTROPHYSICS↗

Application of linear multiple model predictive control (MMPC) framework towards dynamic maximazation of oxygen yield in an elevated-pressure air separation unit

In a typical air separation unit (ASU) utilizing either a simple gaseous oxygen (GOX) cycle or a pumped liquid oxygen (PLOX) cycle, the flowrate of liquid nitrogen (LN2) stream connecting high-pressure and low-pressure ASU columns plays an important role in the total oxygen yield. It has been observed that this yield reaches a maximum at a certain optimal flowrate of LN2 stream. At nominal full-load operation, the flowrate of LN2 stream is maintained near this optimum value, whereas at part-load conditions this flowrate is typically modified in proportion with the load-change (oxygen demand) through a ratio/feed-forward controller. Due to nonlinearity in the entire ASU process, the ratio-modified LN2 flowrate does not guarantee an optimal oxygen yield at part-load conditions. This is further exacerbated when process disturbances in form of “cold-box” heat-leaks enter the system. To address this problem of dynamically maximizing the oxygen yield while the ASU undergoes a load-change and/or a process disturbance, a multiple model predictive control (MMPC) algorithm is proposed. This approach has been used in previous studies to handle large ramp-rates of oxygen demand posed by the gasifier in an IGCC plant. In this study, the proposed algorithm uses linear step-response “blackbox” models surrounding the operating points corresponding to maximum oxygen yield points at different loads. It has been shown that at any operating point of the ASU, the MMPC algorithm, through model-weight calculation based on plant measurements, naturally and continuously selects the dominant model(s) corresponding to the current plant state, while making control-move decisions that approach the maximum oxygen yield point. This dynamically facilitates less energy consumption in form of compressed feed-air compared to a simple ratio control during load-swings. In addition, since a linear optimization problem is solved at each time step, the approach involves much less computational cost compared to a firstprinciple based nonlinear MPC. Introduction

97 MATHEMATICS AND COMPUTING↗

Storage Field Development Plan: One Earth Energy

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, and operational plans, and costs associated with the proposed One Earth Sequestration Carbon Capture and Storage (OES-CCS) site in McLean County, Illinois, near Gibson City. The proposed storage complex, known as the Mt. Simon Storage Complex, comprises the Cambrian Mt. Simon Sandstone reservoir and the primary seal, the Cambrian Eau Claire Formation. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Ordovician St. Peter Sandstone. Geologic characterization of the Mt. Simon Storage Complex at the OES-CCS site was performed by the Illinois Storage Corridor CarbonSAFE Phase III project, which also prepared and submitted three UIC Class VI applications to construct three injection wells; the permit applications were submitted and are in the federal EPA review process. A characterization well, OEE #1, was drilled to collect site-specific data. These data were analyzed and used to develop the UIC Class VI applications. The OEE #1 well will be converted to an in-zone monitoring (IZM) well for the injection phase. The proposed buildout for the OES-CCS site includes (1) three injection wells (OES #1, OES #2, and OES #3), (2) two IZM wells, (3) two above confining zone (ACZ) monitoring wells, one of which will be used to monitor the lowermost USDW, (4) capture and compression facilities, and (5) transportation facilities, i.e., pipelines. A pre-operational testing program was proposed in the Class VI permit application and will be employed at the site pending approval. Additional pre-injection (baseline), syn-injection, and post-injection monitoring and site care procedures will be followed by OES to ensure that injection activities are protective of human health and the environment. Injection is scheduled to begin in 2025, distributed across the three injection wells in accordance with the permit operating conditions. One Earth Sequestration intends to inject up to 90 million tonnes of CO 2 over a period of approximately 20 years. Injection will begin at approximately 0.5 million tonnes of CO 2 annually and ramp up to a maximum of 4.5 million tonnes annually. Daily injection rates are expected to range from 1,400 to 1,500 tonnes per day initially and reach a maximum of approximately 4,225 tonnes per day, depending on site geology and injectivity at each injection well location, and CO 2 availability. The costs associated with the OES-CCS project include pre-operational costs (e. g. additional seismic data acquisition and well drilling), capture and transportation facility and equipment costs, predicted field operating expenditures (OpEx), and decommissioning and post-injection site care (PISC) costs. The risks associated with project activities, such as site construction, injection operations, and verification of secure storage were evaluated, and mitigation strategies proposed to alleviate those risks.

09 BIOMASS FUELS↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Marine Hydrokinetic Tidal Turbine

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset is part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with other energy technologies. This dataset contains inputs and outputs from simulations of a floating marine hydrokinetic turbine over approximately half a tidal cycle (~6.6 hours). Inflow conditions were derived from field measurements in Alaska’s Cook Inlet and represent a tidal environment in which the current speed ramps from near 0 m/s to a peak of 3 m/s and back. The original acoustic doppler current profiler dataset is publicly available on the Marine and Hydrokinetic Data Repository. In a full tidal cycle, the flow reverses and the rotor would reorient; this reversal was not modeled. In the Cook Inlet campaign , turbulence intensity was similar in both directions. Two inflow cases are included. In the first case, labeled “raw” in the files, the measured current time series was used directly in the InflowWind module of OpenFAST. Speed and direction were applied as a function of time and elevation, uniformly in the horizontal direction. With full spatial coherence, this approach captures high turbulent variability and results in pronounced power fluctuations, so it is considered a conservative, near-worst-case representation of loading. In the second case, labeled “average” in the files, a 30-minute moving average was applied to extract the slowly varying mean speed. The residual fluctuations about this mean were used to generate spatially varying, full-field turbulence inputs with TurbSim, giving a more physically realistic representation of the inflow across the rotor disk. Two random realizations were used to produce distinct inflow conditions for two OpenFAST simulations representing a two-turbine array. The same turbulence intensity is applied across the full time series, producing larger fluctuations at the start and end, where the mean speed is low. The second case is the more appropriate framework for performance and power assessment but overpredicts turbulence at lower flow speeds and underpredicts it at higher speeds. As the floating platform moves and the rotor changes its x-position, Taylor’s frozen turbulence hypothesis used by InflowWind assumes a constant rather than a time-varying mean velocity, introducing some inaccuracy in the velocity plane sampling. The turbine modeled is the 500-kW Reference Model 1, a horizontal-axis two-bladed hydrokinetic turbine on a four-column floating semisubmersible substructure . Simulations were performed using OpenFAST v4.1 with the Reference Open Source Controller (ROSCO) v2.10. All input files required to reproduce the simulations are included. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel . This unit supports up to 2.5 MW, but NLR has only a single 1.25-MW stack. The datasets report hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. The system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operating current of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The simulated tidal turbine time series data was translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz. Each zip file represents a single tidal electrolysis experiment and is named: {technology}_{inflow method}_{number of 500 kW tidal turbines connected} For instance, “tidal-500kW-RM1_average_2.zip” is a 6-hour experiment using the 500-kW tidal reference model, scaled by 2x (1-MW) to better match the electrolyzer maximum of 1.25MW, fed with the 30-minute moving average current case. Each zip folder contains the following files: A .csv file of raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. A .csv file combines all tidal profiles as "combined_tidal_experiments.csv." A separate experiment, “characterization_200.zip,” shows the MC250 electrolyzer steady-state response with 30-minute load steps over 5 hours and is accessible with this entry.

08 HYDROGEN↗

Optimization of Isentropic Compression Loads on Current-Adder Pulsed Power Accelerator Architectures

The Thor pulsed power generator is being developed at Sandia National Laboratories. The design consists of up to 288 decoupled and transit time isolated capacitor-switch units, called “bricks”, that can be individually triggered to achieve a high degree of pulse tailoring for magnetically-driven isentropic compression experiments (ICE). The connecting transmission lines are impedance matched to the bricks, allowing the capacitor energy to be efficiently delivered to an ICE strip-line load with peak pressures of over 100 GPa. Thor will drive experiments to explore equation of state, material strength, and phase transition properties of a wide variety of materials. We present an optimization process for producing tailored current pulses, a requirement for many material studies, on the Thor generator. This technique, which is unique to the novel “current-adder” architecture used by Thor, entirely avoids the iterative use of complex circuit models to converge to the desired electrical pulse. We describe the optimization procedure for the Thor design and show results for various materials of interest. Also, we discuss the extension of these concepts to the megajoule-class Neptune machine design. Given this design, we are able to design shockless ramp-driven experiments in the 1 TPa range of material pressure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Interpreting dynamic-compression experiments to uncover the time dependence of freezing: Application to gallium

Using pulsed-power magnetic field sources to compress gallium to gigapascal pressures on nanosecond timescales, we report here experiments on shockless dynamic compression of a liquid metal. Time-resolved velocimetry data reveal signatures of rapid freezing from a metastable liquid state, and we demonstrate that the kinetics of this nonequilibrium solidification can be accurately simulated with a computational modeling framework we have developed in previous studies, where classical nucleation theory is coupled with hydrodynamics. Notably, velocity traces in some of our experiments show evidence of a phase transition, while others do not, even though other types of evidence suggest that solidification may be occurring in all of them. We explain how predictions made by our models regarding the presence or absence of these phase-transition signatures motivated additional experiments that later confirmed the theoretical predictions. Our analysis shows that due to the rapid, quasi-isentropic nature of the loading path, our experiments were able to compress liquid gallium to metastable states that are undercooled below the equilibrium melt temperature by more than 300 K and exhibit pressures that approach five times the equilibrium melt pressure. The understanding gained in this study should form the basis for future dynamic-compression experiments aimed at interrogating melt curves at high pressures.

gallium↗

Estimates of Ta strength at ultrahigh pressures and strain rates using thin-film graded-density impactors

In this paper, we present results from an experimental technique used to estimate the strength of Ta at extreme pressures (150 GPa) and strain rates (10 7 s -1 ). A graded-density impactor (GDI) was fabricated using sputter deposition to produce an approximately 40-μm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched with a 2-stage light gas gun, and shock-ramp-release velocity profiles were measured over timescales of ~10 ns. Results are presented for the direct impact of the film onto LiF windows, which allows for a dynamic characterization of the GDI, as well as from impact onto thin (~40μm) sputtered Ta samples backed by a LiF window. The measurements were coupled with mesoscale numerical simulations to infer the strength of Ta, and the results agree well with other high-pressure platforms, particularly when strain-rate, microstructural, and thermodynamic-path differences are considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Results from Plasma Wakefield Experiments at FACET

We report initial results of the Plasma Wakefield Acceleration (PWFA) Experiments performed at FACET - Facility for Advanced aCcelertor Experimental Tests at SLAC National Accelerator Laboratory. At FACET a 23 GeV electron beam with 1.8 x 10{sup 10} electrons is compressed to 20 {mu}m longitudinally and focused down to 10 {mu}m x 10 {mu}m transverse spot size for user driven experiments. Construction of the FACET facility completed in May 2011 with a first run of user assisted commissioning throughout the summer. The first PWFA experiments will use single electron bunches combined with a high density lithium plasma to produce accelerating gradients > 10 GeV/m benchmarking the FACET beam and the newly installed experimental hardware. Future plans for further study of plasma wakefield acceleration will be reviewed. The experimental hardware and operation of the plasma heat-pipe oven have been successfully commissioned. Plasma wakefield acceleration was not observed because the electron bunch density was insufficient to ionize the lithium vapor. The remaining commissioning time in summer 2011 will be dedicated to delivering the FACET design parameters for the experimental programs which will begin in early 2012. PWFA experiments require the shorter bunches and smaller transverse sizes to create the plasma and drive large amplitude wakefields. Low emittance and high energy will minimize head erosion which was found to be a limiting factor in acceleration distance and energy gain. We will run the PWFA experiments with the design single bunch conditions in early 2012. Future PWFA experiments at FACET are discussed in [5][6] and include drive and witness bunch production for high energy beam manipulation, ramped bunch to optimize tranformer ratio, field-ionized cesium plasma, preionized plasmas, positron acceleration, etc.. We will install a notch collimator for two-bunch operation as well as new beam diagnostics such as the X-band TCAV [7] to resolve the two bunches. With these new instruments and desired beam parameters in place next year, we will be able to complete the studies of plasma wakefield acceleration in the next few years.

43 PARTICLE ACCELERATORS↗

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗