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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5

C3PU:Real-Time Predictive Charge Control Software for Battery Management Systems (Code for Charge Control and Predictive Unit) [SWR-21-48]

C3PU sets up a model predictive control formulation for the optimal charging control of battery packs and can be deployed for real-time operation on an embedded microprocessor. C3PU uses electrochemical and thermal models of battery packs to predict the charging trajectories of the battery pack over a time horizon under different operating conditions. It then selects the optimal charging trajectory such that a pre-defined objective is minimized, which in the present state of the code is to minimize the charging duration of the battery pack. The optimal charging trajectory is obtained by solving an underlying mathematical problem. However, C3PU is flexible to incorporate other charging objectives. The underlying battery models can be swapped as well, as long as they follow certain mathematical properties. Mathematically, optimal control problems (in this case, optimally controlling the charging current of the battery pack) are computationally expensive. C3PU implements advanced numerical techniques, namely pseudo-spectral optimization, to reduce the computational burden of the underlying problem to solve. This allows for the problem to be solved in real-time in an embedded system. Once the optimal charging trajectory is computed over a time horizon, C3PU can package such data and send it out via appropriate communication protocols.

Mishra, Partha↗

Neutron (and other Particle) Transport at LANL: An Overview [Presentation]

For decades, Los Alamos National Laboratory has been at the forefront of neutron transport methods research and code development. One such code is PARTISN, the LANL parallel time-dependent discrete ordinate neutron transport code. In this presentation, we describe the various research efforts currently underway by the PARTISN and other code teams. Some examples of current research are a block automated mesh refinement scheme, the application of tensor trains to the discretized neutron transport equation, and GPU code porting. The block automated mesh refinement scheme uses cross section information to refine and coarsen the solution mesh to improve time to solution and reduce memory. The tensor train approach expresses discretized transport operators as tensor products of vectors and matrices to compress the size of linear systems being solved by transport codes. Rather than relying on matrix-free methods such as the transport sweep, we have access to an operator that can be inverted, reshaped, or manipulated algebraically. Finally, we describe how PARTISN is used, what problems we are looking to solve, and what the future holds for neutron transport at LANL. In addition to this, we briefly describe the various research efforts in other particle transport teams using both deterministic and Monte Carlo methods. In the presentation, we list possible opportunities for collaboration between the laboratory and faculty and students.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

MCNP® Code Version 6.3.1 Release Notes

The Monte Carlo N-Particle® (MCNP® ) code is a general-purpose, continuous-energy, generalized-geometry, time-dependent, radiation transport code developed by the MCNP development team. MCNP calculations provide predictive capabilities that can replace expensive or impossible-to-perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.1, follows the MCNP6.3.0 version. Since the release of MCNP6.3.0, a variety of bug fixes and code enhancements have been completed for MCNP6.3.1. A few new features have also been added to this release to support both ongoing research and the release of the latest ENDF/B-VIII.1 nuclear data library. The MCNP code, version 6.3.1, theory and user input information is documented in MCNP® Code Version 6.3.1 Theory & User Manual, the build guidance for various platforms is documented in MCNP® Code Version 6.3.1 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP® Code Version 6.3.1 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Finite-difference multiple fluid solution for source-driven rotation in highly magnetized linear plasma device

The rotation profile of a magnetized plasma cylinder composed of multiple fluids is investigated analytically, expanding on previous results. The analytic steady-state solution is used as a benchmark for a time-dependent multiple-fluid finite-difference code, MITNS: Multiple-Ion Transport Numerical Solver. Magnetic field evolution is taken into account, both analytically and numerically. Its details are shown to be of importance when particles are allowed out of the domain. MITNS reproduces the asymptotic expansion results for a small parameter $δ<<<1$. For $\sqrt{m_elm_i} ~ δ << 1$ , a slightly different regime, dominated by viscosity-induced transport of ions, is found numerically and analytically. Finally, this verification supports the use of this code for more complex time-dependent calculations in the future. Additionally, we derive the angular velocity profile of each species due to radial particle and charge fluxes of various strengths.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Survey of Multimaterial Treatments for Thermal Radiative Transfer

Arbitrary Lagrangian-Eulerian methods are a popular choice for hydrodynamic modeling in radiation (rad-hydro) simulations. Because these methods involve a relaxation step that moves the mesh relative to material boundaries, multimaterial spatial zones are generally present. Accurate treatments of these zones are needed to resolve various physical phenomena of interest for inertial confinement fusion applications. However, these codes are often paired with single-material, deterministic thermal radiative transfer (TRT) codes that are oblivious to the material compositions of each zone. These single-material TRT codes can only accept homogenized material properties (opacities, specific heats, etc.) from the hydrodynamic code and output homogenized solutions. After each TRT time step, the multimaterial hydrodynamic code must dehomogenize the quantities computed by the TRT package in order to update subzonal material temperatures. The process by which hydrodynamic codes perform this dehomogenization has not been well documented in previous literature, and the methods can vary significantly from code to code. The purpose of this paper is to document, study, and compare existing techniques used for rad-hydro simulations as well as present a new method with potentially promising results. We summarize several methods and give comparisons on infinite-medium problems as well a finite-medium problem for two of the methods.

42 ENGINEERING↗

Multigrid reduction in time with Richardson extrapolation

The advent of exascale computing will leave many users with access to more computational resources than they can simultaneously use, e.g., billion-way parallelism. In particular, this is true for time-dependent simulations that limit parallelism to the spatial domain. One method to add parallelism in time to existing simulation codes and thus take advantage of ever larger compute resources is Multigrid Reduction in Time (MGRIT). The goal is to achieve a smaller time-to-solution through parallelism in time. In this paper, MGRIT is enhanced with Richardson extrapolation in a cost-efficient way to produce a parallel-in-time method with improved accuracy. Overall, this leads to a large improvement in the accuracy per computational cost of MGRIT.

97 MATHEMATICS AND COMPUTING↗

Code for paper "Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces"

New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.

Grosskopf, Michael↗

Developments in SRW Code and Sirepo Framework Supporting Simulation of Time-Dependent Coherent X-ray Scattering Experiments

Physical optics simulations for beamlines and experiments are essential for the effective use of synchrotron light source facilities such as NSLS-II at BNL. The SRW software package supports such source-to-detector simulations for coherent X-ray scattering and imaging experiments through its Python interface and Sirepo browser-based graphical user interface. This allows one to define custom sample models, assess the feasibility of an experiment, and estimate most appropriate beamline settings before using valuable beamtime. We discuss the recent use of general-purpose GPU resources and coherent mode decomposition algorithms in SRW to accelerate physical optics simulations with partially coherent X-rays. To illustrate these new capabilities, we describe simulations of typical time series of partially coherent scattering images used in X-ray Photon Correlation Spectroscopy (XPCS) experiments; aiming to characterize the nanoscale dynamics of a disordered sample, representing a solution of nanoparticles undergoing Brownian diffusion.

36 MATERIALS SCIENCE↗

Simulations of divertor plasmas with inverse sheaths

The effect of strong electron emission from material surfaces has been proposed to form an “inverse sheath”: a region with a positive potential relative to the near-wall plasma which prevents the flow of ions to the wall [M. D. Campanell, “Negative plasma potential relative to electronemitting surfaces,” Phys. Rev. E. 88, 033103 (2013); M. D. Campanell and M. V. Umansky, “Strongly emitting surfaces unable to float below plasma potential,” Phys. Rev. Lett. 116, 1–5 (2016); M. D. Campanell and G. R. Johnson, “Thermionic cooling of the target plasma to a sub-ev temperature,” Phys. Rev. Lett. 122, 1–5 (2019)]. We assess the viability of this regime in a tokamak device using the 2D edge plasma transport code UEDGE [T. Rognlien et al ., “A fully implicit, time dependent 2-D fluid code for modeling tokamak edge plasmas,” J. Nucl. Mater. 196–198, 347–351 (1992)]. Since the UEDGE code does not consider the sheath region directly, we apply boundary conditions at the divertor targets which emulate the physics of both “standard” and “inverse” sheath regimes [R. Masline et al ., “Influence of the inverse sheath on divertor plasma performance in tokamak edge plasma simulations,” Contrib. Plasma Phys. 60, e201900097 (2020)]. Using these boundary conditions, we perform scoping studies to assess plasma parameters near the target by varying the density at the core-edge interface. We observe a smooth transition in the resultant profiles of plasma parameters for the standard sheath, and a bifurcation across the simulation set for plasmas with an inverse sheath. The cause of this bifurcation is assessed by performing the parameter scan both with and without impurity radiation; we observe that the bifurcation persists in both cases, indicating that this bifurcation is caused by plasma recombination.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi v

SAND2024-01302O NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi is a neuromorphic script that generates a random walk simulation of a discrete-time Markov Chain for the Loihi neuromorphic hardware. The code was used to produce the paper "Neuromorphic scaling advantages for energy-efficient random walk computations" by Smith et al., 2021. It was published in Nature Electronics. The software provides code for implementing the discrete time Markov chain random walks on Intel's Loihi Neuromorphic platform. In addition, it provides an example problem through a mini app.

Aimone, James↗

The LISE package: solvers for static and time-dependent superfluid local density approximation equations in three dimensions

Nuclear implementation of the density functional theory (DFT) is at present the only microscopic framework applicable to the whole nuclear landscape. The extension of DFT to superfluid systems in the spirit of the Kohn-Sham approach, the superfluid local density approximation (SLDA) and its extension to time-dependent situations, time-dependent superfluid local density ap- proximation (TDSLDA), have been extensively used to describe various static and dynamical problems in nuclear physics, neutron star crust, and cold atom systems. In this paper, we present the codes that solve the static and time-dependent SLDA equations in three-dimensional coordinate space without any symmetry restriction. These codes are fully parallelized with the message passing interface (MPI) library and take advantage of graphic processing units (GPU) for accelerating execution. The dynamic codes have checkpoint/restart capabilities and for initial conditions one can use any generalized Slater determinant type of wave function. The code can describe a large number of physical problems: nuclear fission, collisions of heavy ions, the interaction of quantized vor- tices with nuclei in the nuclear star crust, excitation of superfluid fermion systems by time dependent external fields, quantum shock waves, domain wall generation and propagation, the dynamics of the Anderson-Bogoliubov-Higgs mode, dynamics of fragmented condensates, vortex rings dynamics, generation and dynamics of quantized vortices, their crossing and recombinations and the incipient phases of quantum turbulence.

Jin, Shi↗

A Novel Partitioned Approach for Reduced Order Model—Finite Element Model (ROM-FEM) and ROM-ROM Coupling

Partitioned methods allow one to build a simulation capability for coupled problems by reusing existing single-component codes. In so doing, partitioned methods can shorten code development and validation times for multiphysics and multiscale applications. In this work, we consider a scenario in which one or more of the “codes” being coupled are projection-based reduced order models (ROMs), introduced to lower the computational cost associated with a particular component. We simulate this scenario by considering a model interface problem that is discretized independently on two non-overlapping subdomains. Here we then formulate a partitioned scheme for this problem that allows the coupling between a ROM “code” for one of the subdomains with a finite element model (FEM) or ROM “code” for the other subdomain. The ROM “codes” are constructed by performing proper orthogonal decomposition (POD) on a snapshot ensemble to obtain a low-dimensional reduced order basis, followed by a Galerkin projection onto this basis. The ROM and/or FEM “codes” on each subdomain are then coupled using a Lagrange multiplier representing the interface flux. To partition the resulting monolithic problem, we first eliminate the flux through a dual Schur complement. Application of an explicit time integration scheme to the transformed monolithic problem decouples the subdomain equations, allowing their independent solution for the next time step. We show numerical results that demonstrate the proposed method’s efficacy in achieving both ROM-FEM and ROM-ROM coupling.

de Castro, Amy↗

Sparsified Time-dependent PDEs FNO (STFNO) v1.0.0

STFNO (Sparsified Time-dependent PDEs FNO code) is an extension of the popular Fourier Neural Operator (FNO) architecture to the solution of coupled systems of time-dependent partial differential equations. STFNO leverages the sparsified dependencies on the field quantities based on the semi-discretiezed form of the PDEs, enabling significant reduction in the number of model parameters. STFNO has been extensively tested on two fusion simulation codes, NIMROD and GTC, and can be easily tailored to other systems of PDEs.

Rahman, Mustafa [Lawrence Berkeley National Labora↗

Real-time time-dependent density functional theory in Quantum Espresso and related codes

A set of subroutines that interact with an existing computer program, Quantum Espresso (QE), that takes a set of electronic orbitals from QE and propagates them forward in time in response to a number of perturbations. These perturbations include the motion of ions and a wide spectrum of applied electromagnetic fields (e.g., static magnetic fields, slowly-varying electric fields, x-rays, etc.). From the time evolution of the electronic orbitals comes time-varying values of physical observables like the electronic charge and current densities and atomic forces. These are further post-processed to yield properties of interest like stopping powers, conductivities, and the dynamic structure factor. The electronic orbitals are described in a plane wave basis and the equations of motion are carried out using a unitary or approximately unitary time propagation algorithm. Related work will include subroutines for interfacing this capability, as well as others that already exist within QE, with a fork of QE that is more extensible and modular.SAND2019-12611 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Baczewski, Andrew↗

Orthogonal spatial coding with stimulated parametric down-conversion

Orthogonal optical coding is widely used in classical multi-user communication networks. Using the phase conjugation property of stimulated parametric down-conversion, we extend the current time-domain orthogonal optical coding scheme to the spatial domain to encode and decode image information. In this process, the idler beam inherits the complex conjugate of the field information encoded in the seed beam. An encoding phase mask introduced onto the input seed beam blurs the image transferred to the idler. The original image is restored by passing the coded transferred image through a corrective phase mask placed in the momentum space of the idler beam. We expect that this scheme can also inspire new techniques in secure image transmission, aberration cancellation, and frequency conversion imaging.

Xu, Yang↗

Update to the Microcontroller Benchmark for Radiation Testing

LANL developed a benchmark of software code for radiation testing of microprocessors several years ago, and it was published under an open-source license on GitHub. Publishing the software is necessary for other researchers to adopt and implement this benchmark for radiation testing of other microprocessors to standardize test practices so that test data can be compared across different microprocessors. The original codes have been used several times by other organizations to test a wide range of microcontrollers and microprocessors. After several years of research, LANL is ready to update the benchmark. Changes include: 1. Addition of new codes that allow common software codes to be tested, 2. Addition of new codes that instrument more microprocessor circuitry, 3. Addition of input patterns that allow for a more compressive understanding of how the memory layout affects the sensitivity to radiation-induced faults and better use of automated test pattern generation standards, and 4. Modification of current codes for faster and more resilient detection, reporting and correction of radiation-induced faults. These codes have been tested by LANL researchers over the last few years, which has been published in the open literature. As the code base for the new benchmarks are stable, it is time to release the update to the GitHub repository, where the original codes were released.

Quinn, Heather↗

Keras2c: A library for converting Keras neural networks to real-time compatible C

With the growth of machine learning models and neural networks in measurement and control systems comes the need to deploy these models in a way that is compatible with existing systems. Existing options for deploying neural networks either introduce very high latency, require expensive and time consuming work to integrate into existing code bases, or only support a very limited subset of model types. We have therefore developed a new method called Keras2c, which is a simple library for converting Keras/TensorFlow neural network models into real-time compatible C code. It supports a wide range of Keras layers and model types including multidimensional convolutions, recurrent layers, multi-input/output models, and shared layers. Keras2c re-implements the core components of Keras/TensorFlow required for predictive forward passes through neural networks in pure C, relying only on standard library functions considered safe for real-time use. The core functionality consists of ~ 1500 lines of code, making it lightweight and easy to integrate into existing codebases. Keras2c has been successfully tested in experiments and is currently in use on the plasma control system at the DIII-D National Fusion Facility at General Atomics in San Diego.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗