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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Testing the optical components for the National Ignition Facility time-resolved soft x-ray opacity spectrometer (OpSpecTR)

Opacity measurements are being carried out at the Z-facility at Sandia National Laboratories and at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory. The current soft x-ray Opacity Spectrometer (OpSpec) used on the NIF uses two elliptically bent crystals in time-integrated mode on either an image plate or a film. Plans are under way to expand these opacity measurements into a mode of time-resolved detection, called OpSpecTR. Previously, considerations for the available hCMOS detector size and photometrics led to a crystal geometry redesign and the use of a grazing angle x-ray mirror. The mirror acts as a low-pass x-ray energy filter, reducing the contribution of higher energy x rays. The first tests of the mirror and the crystal for OpSpecTR are presented here. The size of the mirror reflection and the reflectivity is tested using a Manson x-ray source. The mirror coupled with the new elliptical crystal shape demonstrates OpSpecTR’s spectral coverage. Finally, the results from the x-ray optics performance testing are shown along with the intended design.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

High order explicit local time stepping methods for hyperbolic conservation laws

In this paper we present and analyze a general framework for constructing high order explicit local time stepping (LTS) methods for hyperbolic conservation laws. In particular, we consider the model problem discretized by Runge-Kutta discontinuous Galerkin (RK-DG) methods and design LTS algorithms based on the strong stability preserving Runge-Kutta (SSP-RK) schemes, that allow spatially variable time step sizes to be used for time integration in different regions of the computational domain. The proposed algorithms are of predictor-corrector type, in which the interface information along the time direction is first predicted based on the SSP-RK approximations and Taylor expansions, and then the fluxes over the region of the interface are corrected to conserve mass exactly at each time step. Following the proposed framework, we detail the corresponding LTS schemes with accuracy up to the fourth order, and prove their conservation property and nonlinear stability for the scalar conservation laws. Numerical experiments are also presented to demonstrate excellent performance of the proposed LTS algorithms.

58 GEOSCIENCES↗
DOE OSTI2026

Adaptive Control for Load-Following of Boiling Water Reactors Part I: Linear Systems and Fully-Observable Dynamics

Automation control is a key strategy to improve the economic competitiveness of nuclear power plants. Not only does it help reduce operational costs, but it also extends the value proposition of these plants to nontraditional markets, including unattended operations in remote villages and space. However, the dynamics of the operating environments of nuclear reactors are subject to changes over time, and there are no widely adopted methods to ensure that the automation strategy will remain effective over the extended durations required for these applications. Adaptive control is a discipline that offers the possibility to accommodate such changes online. However, it relies on mathematical assumptions that must be respected to ensure robustness and reliability. In this work, we derive an adaptive control formulation for linear systems in which all states are observable and apply it to an instance of load-follow operation for Boiling Water Reactors. We assumed uncertainty in two factors: the temperature coefficient and the control rod worth, both of which are affected over time by the evolution of the nuclear reactor core environment. With an arbitrary penalty factor of 5, we found that the mean absolute and integral time absolute errors can be reduced by more than 90%, underscoring the strength of adaptive control. To extend the application to more challenges, different uncertainties and load-follow trajectories, as well as new formulations that include non-linearity and partial observability, are currently being developed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Diagnosing low-mode (ℓ < 6) and mid-mode (6 ≤ ℓ ≤ 60) asymmetries in the post-stagnation phase of laser-direct-drive deuterium–tritium cryogenic implosions on OMEGA

Low- and mid-mode perturbations are possible candidates for performance limitations in cryogenic direct-drive implosions on the OMEGA laser at the Laboratory of Laser Energetics. Simulations with a 3D hydrocode demonstrated that hotspot imagers do not show evidence of the shell breakup in the dense fuel. However, these same simulations revealed that the low- and mid-mode perturbations in the dense fuel could be diagnosed more easily in the post-stagnation phase of the implosion by analyzing the peak in the x-ray emission limb at the coronal–fuel interface than before or at the stagnation phase. In experiments, the asymmetries are inferred from gated images of the x-ray emission of the implosion by using a 16-pinhole array imager filtered to record x-ray energies >800 eV and an x-ray framing camera with 40-ps time integration and 20-μm spatial resolution. Furthermore, a modal analysis is applied to the spatial distribution of the x-ray emission from deuterium and tritium cryogenic implosions on OMEGA recorded after the bang time to diagnose the low- and mid-mode asymmetries, and to study the effect that the beam-to-target ratio (Rb/Rt) has on the shell integrity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Benchmarking of X‐Ray Fluorescence Microscopy with Ion Beam Implanted Samples Showing Detection Sensitivity of Hundreds of Atoms

Abstract Single impurities in insulators are now often used for quantum sensors and single photon sources, while nanoscale semiconductor doping features are being constructed for electrical contacts in quantum technology devices, implying that new methods for sensitive, non‐destructive imaging of single‐ or few‐atom structures are needed. X‐ray fluorescence (XRF) can provide nanoscale imaging with chemical specificity, and features comprising as few as 100 000 atoms have been detected without any need for specialized or destructive sample preparation. Presently, the ultimate limits of sensitivity of XRF are unknown – here, gallium dopants in silicon are investigated using a high brilliance, synchrotron source collimated to a small spot. It is demonstrated that with a single‐pixel integration time of 1 s, the sensitivity is sufficient to identify a single isolated feature of only 3000 Ga impurities (a mass of just 350 zg). With increased integration (25 s), 650 impurities can be detected. The results are quantified using a calibration sample consisting of precisely controlled numbers of implanted atoms in nanometer‐sized structures. The results show that such features can now be mapped quantitatively when calibration samples are used, and suggest that, in the near future, planned upgrades to XRF facilities might achieve single‐atom sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rethinking materials simulations: Blending direct numerical simulations with neural operators

Abstract Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of the underlying evolution equations, the nature of multiscale spatiotemporal interactions, and the need to reach long-time integration. We develop a method that blends direct numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism to enable accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this hybrid framework on simulations of microstructure evolution via the phase-field method. Such simulations exhibit high spatial gradients and the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with large speed-up compared to DNS depending on the hybrid strategy utilized. This methodology is generalizable to a broad range of materials simulations, from solid mechanics to fluid dynamics, geophysics, climate, and more.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Charged particle diagnostics for inertial confinement fusion and high-energy-density physics experiments

MeV-range ions generated in inertial confinement fusion (ICF) and high-energy-density physics experiments carry a wealth of information, including fusion reaction yield, rate, and spatial emission profile; implosion areal density; electron temperature and mix; and electric and magnetic fields. Here, the principles of how this information is obtained from data and the charged particle diagnostic suite currently available at the major US ICF facilities for making the measurements are reviewed. Time-integrating instruments using image plate, radiochromic film, and/or CR-39 detectors in different configurations for ion counting, spectroscopy, or emission profile measurements are described, along with time-resolving detectors using chemical vapor deposited diamonds coupled to oscilloscopes or scintillators coupled to streak cameras for measuring the timing of ion emission. A brief description of charged-particle radiography setups for probing subject plasma experiments is also given. The goal of the paper is to provide the reader with a broad overview of available capabilities, with reference to resources where more detailed information can be found.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Data-driven time-scale separation of ODE right-hand sides using dynamic mode decomposition and time delay embedding

Multi-physics simulation often involves multiple different scales. The ARKODE ODE solver package in the SUNDIALS library addresses multi-scale problems with a multi-rate time-integrator that can work with a right-hand side that has fast scale and slow scale components. In this report, we use dynamic mode decomposition and time delay embedding to extract the fast and slow components of the right-hand sides of a simple ODE from data. We then use the extracted components to solve the ODE with ARKODE. Finally, to move towards a real-world use case, we attempt to extract fast and slow scale dynamics from synthetic seismic modeling data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

From ETROC to VTROC

The Endcap Timing ReadOut Chip (ETROC) is designed to process LGAD signals with time resolution down to about 40-50ps per hit, to reach 30-35ps per track with two detector layers. The ETROC2 is the first full size (16x16) prototype design and is fully compatible with the final chip specifications in terms of functionality. The ETROC2 has been extensively tested recently. In this talk, the testing results of the ETROC2 will be presented first, including performance study using charge injection, laser and beam, as well as TID testing and wafer probe testing to study the yield. In addition, future challenges of precision position and timing ASIC design will be discussed, based on what we have learned from the ETROC development, and how the challenges could be addressed in the VTROC, Vertically integrated Timing ReadOut chip (funded as SBIR phase 2) for precision position and timing detector R&D.

Liu, Ted↗
DOE OSTI2026

Detector Interface for Streaming, Control, and Open-source integration (DISCO) v1.0.0

This suite consists of a multi-package ecosystem featuring detector emulators, EPICS areaDetector drivers, and remote server frameworks designed for the Advanced Light Source (ALS). Engineered for high-bandwidth devices—including VFCCD, Timepix3, Timepix4, and related pixel detectors—the software simulates hardware, wraps vendor SDKs into remote-callable servers, and integrates with open-source control systems. Key Capabilities: Distributed SDK Architecture: Server packages wrap hardware-specific SDKs, allowing areaDetector drivers to execute remote framework calls. This isolates proprietary libraries from the EPICS IOC, enhancing stability and enabling distributed computing across beamline networks. Device Support: Custom drivers for VFCCD, the Timepix family, and similar sensors optimize the data path from hardware control to high-speed transport. Full-Stack Emulation: Sophisticated emulator packages allow end-to-end pipeline testing and software development without requiring physical hardware or beam time. Integrated Workflows: Supports high-bandwidth streaming for real-time analysis and robust, metadata-rich file-based workflows (e.g., HDF5/NeXus). By standardizing interfaces across heterogeneous hardware, this suite reduces technical debt. It provides the ALS with a scalable, open-source solution to manage massive data rates within a unified control environment.

Mahl, Johannes [Lawrence Berkeley National Laborat↗
DOE OSTI2021

A scalable exponential-DG approach for nonlinear conservation laws: With application to Burger and Euler equations

In this work, we propose an Exponential DG framework for partial differential equations. We decompose 7 governing equations into linear and nonlinear parts to which we apply the discontinuous Galerkin 8 (DG) spatial discretization. In particular, we construct the linear part using Jacobian that effectively 9 capture stiff characteristics in the system. The former is integrated analytically, whereas the latter 10 is approximated. This approach i) is stable with a large Courant number (Cr > 1); ii) supports 11 high-order solutions both in time and space; iii) is computationally favorable compared to IMEX 12 DG methods with no preconditioner; iv) becomes comparable to explicit RKDG methods on uniform 13 mesh and beneficial on non-uniform grid for Euler equations; v) is scalable in a modern massively 14 parallel computing architecture due to its explicit nature of exponential time integrators and com15 pact communication stencil of DG method. Numerical results demonstrate the performance of our 16 proposed methods through various examples. We also discuss the stability and convergence analysis 17 for our exponential DG scheme in the context of Burgers equation.

42 ENGINEERING↗
DOE OSTI2022

Phased plan for the implementation of the time-resolving magnetic recoil spectrometer on the National Ignition Facility (NIF)

The time-resolving magnetic recoil spectrometer (MRSt) is a transformative diagnostic that will be used to measure the time-resolved neutron spectrum from an inertial confinement fusion implosion at the National Ignition Facility (NIF). It uses a CD foil on the outside of the hohlraum to convert fusion neutrons to recoil deuterons. An ion-optical system positioned outside the NIF target chamber energy-disperses and focuses forward-scattered deuterons. A pulse-dilation drift tube (PDDT) subsequently dilates, un-skews, and detects the signal. While the foil and ion-optical system have been designed, the PDDT requires more development before it can be implemented. Therefore, a phased plan is presented that first uses the foil and ion-optical systems with detectors that can be implemented immediately—namely CR-39 and hDISC streak cameras. These detectors will allow the MRSt to be commissioned in an intermediate stage and begin collecting data on a reduced timescale, while the PDDT is developed in parallel. A CR-39 detector will be used in phase 1 for the measurement of the time-integrated neutron spectra with excellent energy-resolution, necessary for the energy calibration of the system. Streak cameras will be used in phase 2 for measurement of the time-resolved spectrum with limited spectral coverage, which is sufficient to diagnose the time-resolved ion temperature. Simulations are presented that predict the performance of the streak camera detector, indicating that it will achieve excellent burn history measurements at current yields, and good time-resolved ion-temperature measurements at yields above 3 × 10 17 . The PDDT will be used for optimal efficiency and resolution in phase 3.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO 2 v7.3

We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO 2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO 2 transport processes within the MPAS-CO 2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO 2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO 2 observations to surface CO 2 fluxes and the initial atmospheric CO 2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO 2 observations, namely the tower-based in situ CO 2 mixing ratio and satellite-derived column-averaged CO 2 mixing ratio (X CO 2 ). A comparison between the sensitivity to surface flux calculated by the MPAS-CO 2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for X CO 2 , might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO 2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO 2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO 2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO 2 TL and adjoint models, and their integration into the MPAS-CO 2 system, establish the possibility of using MPAS's unique features in atmospheric CO 2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Orthogonal Recursive Bisection (ORB) Based Time Advancement Algorithm for CFD-DEM Solvers

The time integration of the granular phase in coupled computational fluid dynamics (CFD) – discrete element method (DEM) simulations presents a unique computational challenge brought about by the large variations in particle collisional time scales. Particles in the dilute regions of the computational domain can be advanced with large time steps while dense regions require much smaller time increments. However, the time step size in most solvers is globally set as the limit for accuracy and stability imposed by the collisions and is typically orders of magnitude less than that required away from collisions. This work addresses this precise issue and provides a strategy to avoid the use of a global conservative small time step size for the entire set of particles.A novel time stepping algorithm for CFD-DEM solvers using a partitioning approach using orthogonal recursive bisection (ORB) that allows for variable time steps among particles is described and its computational performance is compared against baseline explicit methods, typically used in several CFD-DEM solvers. ORB has advantages of being relatively quick and easy to update incrementally and has the required heuristic behavior (i.e., it will split the region in half with a cluster on each side) when groups of particles are well separated (clustered). The algorithm presented in this work uses a local time stepping approach to resolve collisional time scales for subsets of particles that are present at the leaves of the ORB, thereby resulting in substantial reduction of computational cost. The parallel implementation of this method where a ``knapsack” algorithm is used in tandem with ORB for effective load-balancing is also presented, where a best possible partitioning is obtained based on number of particles and local time-stepping costs. The algorithm is tested against benchmark problems with varying particle distributions that include fluidized bed and riser flow scenarios. Preliminary results indicate that the approach is 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.

adaptive timestepping↗
DOE OSTI2023

Simulation of Reverse Osmosis Membrane Compaction Using Material Point Method

Reverse Osmosis (RO) is a promising technology to address the impending water-crisis in the upcoming decades. RO at high salinities and high pressures is challenging due to membrane compaction that changes its porosity and permeability. In this study, we present a simulation methodology for membrane structural mechanics to understand pore size distribution and permeability variations under high pressure. We use the material point method (MPM), that solves the solid mechanics equations in a Lagrangian framework. MPM provides many features that make it well-suited for simulating mesoporous membranes. The Lagrangian framework allows for large deformations, easy integration of constitutive models and direct import of complex geometries as particles. The spatial discretization in our MPM solver is achieved using linear or cubic-spline shape functions while the time integration is carried out using the explicit Euler method. A series of images containing detailed pore structures obtained from X-ray tomography is first converted to a collection of material points. Compressive loads are applied to the top layer of the membrane to simulate the application of pressure. The membrane deformation and pore size distribution before and after load application are reported and compared with the experimental measurements. The presentation discusses the numerical methods used, the performance of the solver on high-performance computing machines, and the results of membrane compact in detail.

compaction↗
DOE OSTI2022

Verification of MOOSE/Bison's Heat Conduction Solver Using Combined Spatiotemporal Convergence Analysis

Bison is a computational physics code that uses the finite element method to model the thermo-mechanical response of nuclear fuel. Since Bison is used to inform high-consequence decisions, it is important that its computational results are reliable and predictive. One important step in assessing the reliability and predictive capabilities of a simulation tool is the verification process, which quantifies numerical errors in a discrete solution relative to the exact solution of the mathematical model. One step in the verification process—called code verification—ensures that the implemented numerical algorithm is a faithful representation of the underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. In this paper, the code verification process is applied to spatiotemporal heat conduction problems in Bison. Simultaneous refinement of the discretization in space and time is employed to reveal any potential mistakes in the numerical algorithms for the interactions between the spatial and temporal components of the solution. For each verification problem, the correct spatial and temporal order of accuracy is demonstrated for both first- and second-order accurate finite elements and a variety of time-integration schemes. Furthermore, these results provide strong evidence that the Bison numerical algorithm for solving spatiotemporal problems reliably represents the underlying mathematical model in MOOSE. The selected test problems can also be used in other simulation tools that numerically solve for conduction or diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

On the convergence of statistics in simulations of stationary incompressible turbulent flows

When reporting statistics from simulations of statistically stationary chaotic phenomenon, it is important to verify that the simulations are time-converged. This condition is connected with the statistical error or number of digits with which statistics can be reliably reported. In this work we consider numerical experiments of low Reynolds number incompressible homogeneous and isotropic turbulence as a model problem to investigate statistical convergence over finite simulation times. Specifically, we investigate the time integration requirements that allow meaningful reporting of the statistical error associated with finiteness of the temporal domain. We address two key questions: (1) How long should a simulation be performed in terms of large eddy time, and (2) How should the simulation time be divided among temporal windows over which a quantity of interest is estimated so that its statistical error could be reliably reported? We find that reliable reporting of statistical errors requires simulations on the order of 10 4 large eddy times, which is orders of magnitude longer than typically performed. Additionally, data post-processing should employ windows of at least ten times the large eddy time scale, with the most robust computation of statistical error of the mean requiring window sizes of an additional factor of ten. For practical simulations, we demonstrate that it is possible to estimate the statistical error within a factor of two under a less stringent condition in which a minimum of four windows with size at least ten large eddy times are used. In conclusion, our observations for homogeneous isotropic turbulence are also shown to hold in turbulent channel flow.

42 ENGINEERING↗