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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 325 records · Page 18

AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations

We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.

17 WIND ENERGY↗

Error Control Techniques for Satellite and Space Communications

In this report, we present the results of our recent work on turbo coding in two formats. Appendix A includes the overheads of a talk that has been given at four different locations over the last eight months. This presentation has received much favorable comment from the research community and has resulted in the full-length paper included as Appendix B, 'A Distance Spectrum Interpretation of Turbo Codes'. Turbo codes use a parallel concatenation of rate 1/2 convolutional encoders combined with iterative maximum a posteriori probability (MAP) decoding to achieve a bit error rate (BER) of 10(exp -5) at a signal-to-noise ratio (SNR) of only 0.7 dB. The channel capacity for a rate 1/2 code with binary phase shift-keyed modulation on the AWGN (additive white Gaussian noise) channel is 0 dB, and thus the Turbo coding scheme comes within 0.7 DB of capacity at a BER of 10(exp -5).

Costello, Daniel J., Jr.↗

3D Electromagnetic Plasma Particle Simulations on the Intel Delta Parallel Computer

A three-dimensional electromagnetic PIC code has been developed on the 512 node Intel Touchstone Delta MIMD parallel computer. This code is based on the General Concurrent PIC algorithm which uses a domain decomposition to divide the computation among the processors. The 3D simulation domain can be partitioned into 1-, 2-, or 3-dimensional subdomains. Particles must be exchanged between processors as they move among the subdomains.

PIC↗

Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres

While most of traditional Earth-atmosphere satellite remote sensing relies on radiative transfer in the plane parallel geometry, effects of sphericity are important at high sun and view zenith angles. Broad understanding of these effects is limited and, contrary to the plane-parallel case, finding accurate numerical results to test spherical RT codes is not easy. This paper aims to partially fill in this gap. Using the full-spherical RT code MYSTIC (Monte Carlo), and the plane-parallel RT code VLIDORT (discrete ordinates) corrected for atmospheric sphericity in the single and multiple scattering, we reproduced with better accuracy and extended the benchmark results by Adams & Kattawar [1978].

spherical atmospheres↗

3D Material Response of the MSL Heatshield Using NuSil-Coated PICA

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performance for protecting probes during planetary entry. Data from the Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. A space-grade silicone-based coating commercially known as NuSil CV-1144-0 [3] was applied to the entire MSL heatshield, including the MEDLI plugs, to mitigate the spread of dust from PICA. Modeling the thermal response of PICA-NuSil (PICA-N) system is still an open challenge. Ground testing of PICA-N models exhibited surface temperature jumps of the order of 150 K due to oxide scale formation and sub-sequent NuSil burn-off. It is therefore critical to include a validated model for the material response of the coating in engineering codes. A test campaign has been conducted at the NASA’s Langley HyMETS [4] facility to screen the response of PICA-N and gather detailed data on its behavior [5]. A first model of PICA-N thermal response has been developed using the Hy-METS experiments [6]. The objective of this work is to analyze the material response of the latest PICA-N model compared to the engineering model used to simulate the entry of MSL. The environment and material response around the MSL aeroshell during Mars atmospheric entry is simulated using a collection of tools. The Direct Simulation Monte Carlo SPARTA code [7] is used in the rarefied regime, the Data Parallel Line Relaxation (DPLR) code [8] is used in the continuum regime and radiative heating conditions are provided by the Nonequilibrium air radiation (NEQAIR) code [9] to estimate the environmental conditions. The thermal response inside the material is computed using the Porous material Analysis Toolbox based on Open-FOAM (PATO) [10,11,12]. Thermodynamic and chemistry properties are estimated using the Mutation++ library [13]. The approach implemented in PATO as a first cut PICA-N thermal response model is outlined in Figure 1. While the recession is less than the coating thickness, the Surface mass and energy balance Boundary Condition (SBC) uses the NuSil B’ tables. Once the recession removes the coating, the usual PICA B’ tables are used for the SBC. The B’ tables are computed using an equilibrium solver implemented in Mutation++, given the temperature, pressure, blowing rate, composition of the pyrolysis and environment gases, and the condensed species at the surface. Preliminary results of the 3D material response of the MSL heat-shield at the peak heating (80 sec after Entry Interface) are shown in Figure 2. Current NASA’s mission to Mars, Mars 2020, used the spare heatshield of MSL for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the PATO high-fidelity material response capability was benchmarked against flight data from MEDLI. This effort represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes. This bench-marking is awaiting the final release of the MEDLI-2 data.

Aerospace↗

User-Defined Data Distributions in High-Level Programming Languages

One of the characteristic features of today s high performance computing systems is a physically distributed memory. Efficient management of locality is essential for meeting key performance requirements for these architectures. The standard technique for dealing with this issue has involved the extension of traditional sequential programming languages with explicit message passing, in the context of a processor-centric view of parallel computation. This has resulted in complex and error-prone assembly-style codes in which algorithms and communication are inextricably interwoven. This paper presents a high-level approach to the design and implementation of data distributions. Our work is motivated by the need to improve the current parallel programming methodology by introducing a paradigm supporting the development of efficient and reusable parallel code. This approach is currently being implemented in the context of a new programming language called Chapel, which is designed in the HPCS project Cascade.

physically distributed memory↗

Implementation of a Mesh refinement algorithm into the quasi-static PIC code QuickPIC

Plasma-based acceleration (PBA) has emerged as a promising candidate for the accelerator technology used to build a future linear collider and/or an advanced light source. In PBA, a trailing or witness particle beam is accelerated in the plasma wave wakefield (WF) created by a laser or particle beam driver. The WF is often nonlinear and involves the crossing of plasma particle trajectories in real space and thus particle-in-cell methods are used. The distance over which the drive beam evolves is several orders of magnitude larger than the wake wavelength. This large disparity in length scales is amenable to the quasi-static approach. Three-dimensional (3D), quasi-static (QS), particle-in-cell (PIC) codes, e.g., QuickPIC, have been shown to provide high fidelity simulation capability with 2-4 orders of magnitude speedup over 3D fully explicit PIC codes. In PBA, the witness beam needs to be matched to the focusing forces of the WF to reduce the emittance growth. In some linear collider designs, the matched spot size of the witness beam can be 2 to 3 orders of magnitude smaller than the spot size (and wavelength) of the wakefield. Such an additional disparity in length scales is ideal for mesh refinement where the WF within the witness beam is described on a finer mesh than the rest of the WF. A mesh refinement scheme is described that has been implemented into the 3D QS PIC code, QuickPIC. Very fine (high) resolution is used in a small spatial region that includes the witness beam and progressively coarser resolutions in the rest of the simulation domain. A fast multigrid Poisson solver has been implemented for the field solve on the refined meshes and a Fast Fourier Transform (FFT) based Poisson solver is used for the coarse mesh. The code has been parallelized with both MPI and OpenMP, and the parallel scalability has also been improved by using pipelining. A preliminary adaptive mesh refinement technique is described to optimize the computational time for simulations with an evolving witness beam size. Several test problems are used to verify that the mesh refinement algorithm provides accurate results. Additionally, the results are benchmarked against highly resolved simulations exhibiting near-azimuthal symmetry, performed using QPAD—a novel hybrid QS PIC code that uses a PIC description in the coordinates (r, ct – z) and a gridless description in the azimuthal angle, Φ.

Linear collider↗

Simulation of Hypervelocity Impact on Aluminum-Nextel-Kevlar Orbital Debris Shields

An improved hybrid particle-finite element method has been developed for hypervelocity impact simulation. The method combines the general contact-impact capabilities of particle codes with the true Lagrangian kinematics of large strain finite element formulations. Unlike some alternative schemes which couple Lagrangian finite element models with smooth particle hydrodynamics, the present formulation makes no use of slidelines or penalty forces. The method has been implemented in a parallel, three dimensional computer code. Simulations of three dimensional orbital debris impact problems using this parallel hybrid particle-finite element code, show good agreement with experiment and good speedup in parallel computation. The simulations included single and multi-plate shields as well as aluminum and composite shielding materials. at an impact velocity of eleven kilometers per second.

Fahrenthold, Eric P.↗

Implementation of a partitioned algorithm for simulation of large CSI problems

The implementation of a partitioned numerical algorithm for determining the dynamic response of coupled structure/controller/estimator finite-dimensional systems is reviewed. The partitioned approach leads to a set of coupled first and second-order linear differential equations which are numerically integrated with extrapolation and implicit step methods. The present software implementation, ACSIS, utilizes parallel processing techniques at various levels to optimize performance on a shared-memory concurrent/vector processing system. A general procedure for the design of controller and filter gains is also implemented, which utilizes the vibration characteristics of the structure to be solved. Also presented are: example problems; a user's guide to the software; the procedures and algorithm scripts; a stability analysis for the algorithm; and the source code for the parallel implementation.

Alvin, Kenneth F.↗

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗

CPU timing routines for a CONVEX C220 computer system

The timing routines available on the CONVEX C220 computer system in the Structural Mechanics Division (SMD) at NASA Langley Research Center are examined. The function of the timing routines, the use of the timing routines in sequential, parallel, and vector code, and the interpretation of the results from the timing routines with respect to the CONVEX model of computing are described. The timing routines available on the SMD CONVEX fall into two groups. The first group includes standard timing routines generally available with UNIX 4.3 BSD operating systems, while the second group includes routines unique to the SMD CONVEX. The standard timing routines described in this report are /bin/csh time,/bin/time, etime, and ctime. The routines unique to the SMD CONVEX are getinfo, second, cputime, toc, and a parallel profiling package made up of palprof, palinit, and palsum.

Bynum, Mary Ann↗

Towards improved speed and accuracy of laser powder bed fusion simulations via multiscale spatial representations

Due to the growing popularity of laser powder bed fusion (LPBF) as a metal additive manufacturing technique, there is a strong need to be able to accurately predict build outcomes. Full fidelity simulations of this process are not feasible due to the vast range of length and time scales inherent to it. While part-scale codes for simulating residual stress and distortion have shown reasonable predictive capability, they often neglect many aspects of the process occurring over smaller length/time scales, and thus are unable to capture effects of process parameter adjustments or the behavior of fine features. One way of capturing aspects at more refined length scales is through the use of adaptive mesh refinement (AMR). AMR allows for the process to be simulated at scales approaching the physical spatial dimensions without drastically increasing the total degrees of freedom in the simulation. This manuscript describes the implementation of an AMR algorithm within a multiphysics, parallelized finite element code, and its application to the LPBF problem. In this work, part-scale examples are provided where the use of AMR has allowed for higher fidelity thermal and thermomechanical simulations, as compared to experimental measurements. Results from these higher resolution simulations show that while AMR is a necessary component for increased accuracy in a computationally efficient manner, other improvements are also necessary, including handling of the multiple time scales inherent to the problem and the need for improved AM-specific material models.

42 ENGINEERING↗

Multiphysics analysis system for heat pipe cooled micro-reactors employing PRAGMA-OpenFOAM-ANLHTP

A multiphysics analysis system for neutronics/thermo-mechanical/heat-pipe analysis of heat pipe cooled micro-reactors was developed using the PRAGMA code as the neutronics engine. PRAGMA, which used to be a GPU-based continuous-energy MC code for power reactor applications, now has an extended geometry package to handle geometries with unstructured meshes generated by the ANSYS Design-Modeler and Meshing. The NVIDIA ray tracing engine OptiX was exploited for efficient neutron transport on unstructured geometry. On the multiphysics side, the open-source CFD tool OpenFOAM and one-dimensional heat pipe analysis code ANLHTP were adopted. The manager-worker system based on the MPI dynamic process management (DPM) model enables efficient coupling of codes employing different parallelization schemes. With all the features, the multiphysics analysis of the one-sixth symmetrical MegaPower 2D core was performed and it demonstrated the benefit of the tight integration of the three-way coupling system and one-to-one geometry coupling strategy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization

In this work, we present DFT-FE 1.0, building on DFT-FE 0.6 [Comput. Phys. Commun. 246, 106853 (2020)], to conduct fast and accurate large-scale density functional theory (DFT) calculations (reaching ~ 100,000 electrons) on both many-core CPU and hybrid CPU-GPU computing architectures. This work involves improvements in the real-space formulation—via an improved treatment of the electrostatic interactions that substantially enhances the computational efficiency—as well high-performance computing aspects, including the GPU acceleration of all the key compute kernels in DFT-FE. We demonstrate the accuracy by comparing the ground-state energies, ionic forces and cell stresses on a wide-range of benchmark systems against those obtained from widely used DFT codes. Further, we demonstrate the numerical efficiency of our implementation, which yields ~ 20× CPU-GPU speed-up by using GPU acceleration on hybrid CPU-GPU nodes. Notably, owing to the parallel-scaling of the GPU implementation, we obtain wall-times of 80–140 seconds for full ground-state calculations, with stringent accuracy, on benchmark systems containing ~ 6, 000 – 15,000 electrons.

pseudopotential↗

Self-Consistent Relativistic Electron Scattering using the Sherlock Scattering Model for X-ray Diagnostics

We present on a new, self-consistent, arbitrary-temperature Romberg integration scheme for modeling electron scattering in materials in a LANL Lagrangian Shock Hydro (LSH) code. Electron beam-target interactions are fundamental to a wide range of scientific and technological applications. When high-energy electron beams hit their target, they may scatter, deposit energy, or ionize the source. These processes govern the behavior and outcomes in nanotechnology manufacturing, electron microscopy, and modern X-ray diagnostics. Simulating these interactions is essential for interpreting experimental results, predicting material responses, and designing efficient tools and experiments. At Los Alamos, this is done using a LSH code, which is a multi-dimension, multi-material, massively parallel, multi-physics code used to simulate applications from asteroid impacts to electron beam interactions. By effectively and efficiently modeling the way that electrons scatter from the beam we can bolster these simulations and more accurately predict experimental outcomes. The model currently implemented in the LSH of interest is based on work by Papp and does not self-consistently preserve momentum in the slightly relativistic regime; here we adopt a model proposed by Braams and Karney and implement a Romberg integration scheme to compute the diffusion tensor. In this paper we will provide background on the Braams-Karney diffusion tensor as well as the Romberg integration scheme we employed to numerically solve for it. We will show that our integration scheme is accurate in solving for the set of scalar potentials used to re-express the diffusion tensor in differential form, and in solving for the diffusion coefficients in the larger LSH code. By using this diffusion tensor rather than the existing Papp one, and numerically integrating it with a Romberg method, we produce much more accurate, self-consistent results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The BLAZE language: A parallel language for scientific programming

A Pascal-like scientific programming language, Blaze, is described. Blaze contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus Blaze should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with onceptually sequential control flow. A central goal in the design of Blaze is portability across a broad range of parallel architectures. The multiple levels of parallelism present in Blaze code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of Blaze are described and shows how this language would be used in typical scientific programming.

Mehrotra, P.↗

The BLAZE language - A parallel language for scientific programming

A Pascal-like scientific programming language, BLAZE, is described. BLAZE contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus BLAZE should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with conceptually sequential control flow. A central goal in the design of BLAZE is portability across a broad range of parallel architectures. The multiple levels of parallelism present in BLAZE code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of BLAZE are described and it is shown how this language would be used in typical scientific programming.

Mehrotra, Piyush↗

The MAVRIC-Shift Sequence in SCALE for Radiation Transport and Shielding Calculations with Automated Variance Reduction and Parallel Computing

A new MAVRIC-Shift sequence has been implemented and tested within the SCALE Code System to provide parallel computing capabilities for radiation transport and shielding analysis with automated variance reduction. This new sequence provides the most widely used capabilities of the MAVRIC sequence and also features the highly scalable Shift Monte Carlo solver, thus enabling faster time-to-solution when run on multiple cores. This report provides a summary of the theory of variance reduction approaches in MAVRIC and the integration of Shift into the MAVRIC sequence of SCALE. Similarities and differences in methodologies between the traditional MAVRIC sequence and the new MAVRIC-Shift sequence are discussed. Validation cases are presented with models of radiation shielding experiments and verification is provided with a series of practical application cases of interest to the US Nuclear Regulatory Commission, the sponsors of this work, including spent nuclear fuel transportation and storage systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗