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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Structural load prediction methods for space payloads

The state of the art in structural loads prediction procedures for spacecraft is summarized. Three categories of prediction techniques delineated by cost, complexity, comprehensiveness, accuracy, and applications are outlined. The lowest cost method has been used for earth resources, communications, and weather satellites, the medium cost method for sun-synchronous orbits and the large space telescope, and the most expensive for planetary missions, comet rendezvous, and out-of-ecliptic orbits, all assuming Shuttle launch. The lowest cost method involves a mass-acceleration curve. A shock spectra technique predicts a least upper bound for loads. A recovered transient method analyzes the interface acceleration of two connected launch vehicles. The most accurate method devised thus far is a transient analysis of the total launch vehicle/payload dynamic system.

Wada, B. K.↗
DOE OSTI2020

DPM: A deep learning PDE augmentation method with application to large-eddy simulation

A framework is introduced that leverages known physics to reduce overfitting in machine learning for scientific applications. The partial differential equation (PDE) that expresses the physics is augmented with a neural network that uses available data to learn a description of the corresponding unknown or unrepresented physics. Training within this combined system corrects for missing, unknown, or erroneously represented physics, including discretization errors associated with the PDE's numerical solution. For optimization of the network within the PDE, an adjoint PDE is solved to provide high-dimensional gradients, and a stochastic adjoint method (SAM) further accelerates training. Additionally, the approach is demonstrated for large-eddy simulation (LES) of turbulence. High-fidelity direct numerical simulations (DNS) of decaying isotropic turbulence provide the training data used to learn sub-filter-scale closures for the filtered Navier–Stokes equations. Out-of-sample comparisons show that the deep learning PDE method outperforms widely-used models, even for filter sizes so large that they become qualitatively incorrect. It also significantly outperforms the same neural network when a priori trained based on simple data mismatch, not accounting for the full PDE. Measures of discretization errors, which are well-known to be consequential in LES, point to the importance of the unified training formulation's design, which without modification corrects for them. For comparable accuracy, simulation runtime is significantly reduced. A relaxation of the typical discrete enforcement of the divergence-free constraint in the solver is also successful, instead allowing the DPM to approximately enforce incompressibility physics. Since the training loss function is not restricted to correspond directly to the closure to be learned, training can incorporate diverse data, including experimental data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs

The fully electromagnetic particle-in-cell code WarpX is being developed by a team of the U.S. DOE Exascale Computing Project (with additional non-U.S. collaborators on part of the code) to enable the modeling of chains of tens to hundreds of plasma accelerator stages on exascale supercomputers, for future collider designs. The code is combining the latest algorithmic advances (e.g., Lorentz boosted frame and pseudo-spectral Maxwell solvers) with mesh refinement and runs on the latest computer processing unit and graphical processing unit (GPU) architectures. In this paper, we summarize the strategy that was adopted to port WarpX to GPUs, report on the weak parallel scaling of the pseudo-spectral electromagnetic solver, and then present solutions for decreasing the time spent in data exchanges from guard regions between subdomains. In Sec. IV, we demonstrate the simulations of a chain of three consecutive multi-GeV laser-driven plasma accelerator stages.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Plasma gradient effect on direct laser acceleration

The transfer of a high-intensity laser pulse energy to a high-energy electron beam via the direct laser acceleration mechanism is shown to be significantly enhanced through control of the plasma density gradient. Experiments performed using the OMEGA EP facility's high-intensity beams altered the plasma density and gradients by changing the Mach number and the angle of the gas-jet nozzle to the laser axis. When a long density gradient at the rear of the target is used, the total high-energy electron number measured was enhanced by 4.5 times compared to a shorter rear gradient. Complementary two-dimensional simulations, which follow the laser field evolution and the corresponding electron dynamics, strongly support the key trends observed in the experiment. The effect is twofold, the long density gradient provides the longest acceleration distance while it minimizes the formation of the sheath field as the electron beam exits into the vacuum. This study shows the importance of tailoring the plasma density.

Laser plasma interactions↗
NASA NTRS1987

An L-U implicit multigrid algorithm for the three-dimensional Euler equations

An LU implicit multigrid scheme is developed for the calculation of three-dimensional transonic flow through rotating cascades. This numerical method solves the unsteady Euler equations of gas dynamics in a finite-volume form. The implicit scheme makes it possible to take a much larger time step than is normally permitted in most explicit schemes, while the multigrid method is incorporated to accelerate the convergence rate for steady state calculations. Using this method, computational storage requirements are comparable to those of explicit schemes, while operation counts are considerably less than those found in the more widely-used ADI schemes.

Yokota, Jeffrey W.↗
NASA NTRS1991

A general multiblock Euler code for propulsion integration. Volume 1: Theory document

A general multiblock Euler solver was developed for the analysis of flow fields over geometrically complex configurations either in free air or in a wind tunnel. In this approach, the external space around a complex configuration was divided into a number of topologically simple blocks, so that surface-fitted grids and an efficient flow solution algorithm could be easily applied in each block. The computational grid in each block is generated using a combination of algebraic and elliptic methods. A grid generation/flow solver interface program was developed to facilitate the establishment of block-to-block relations and the boundary conditions for each block. The flow solver utilizes a finite volume formulation and an explicit time stepping scheme to solve the Euler equations. A multiblock version of the multigrid method was developed to accelerate the convergence of the calculations. The generality of the method was demonstrated through the analysis of two complex configurations at various flow conditions. Results were compared to available test data. Two accompanying volumes, user manuals for the preparation of multi-block grids (vol. 2) and for the Euler flow solver (vol. 3), provide information on input data format and program execution.

Chen, H. C.↗
NASA NTRS1990

Vibration environment - Acceleration mapping strategy and microgravity requirements for Spacelab and Space Station

In order to define the acceleration requirements for future Shuttle and Space Station Freedom payloads, methods and hardware characterizing accelerations on microgravity experiment carriers are discussed. The different aspects of the acceleration environment and the acceptable disturbance levels are identified. The space acceleration measurement system features an adjustable bandwidth, wide dynamic range, data storage, and ability to be easily reconfigured and is expected to fly on the Spacelab Life Sciences-1. The acceleration characterization and analysis project describes the Shuttle acceleration environment and disturbance mechanisms, and facilitates the implementation of the microgravity research program.

Martin, Gary L.↗
NASA NTRS1978

Accelerated/abbreviated test methods for predicting life of solar cell encapsulants to Jet Propulsion Laboratory California Institute of Technology for the encapsulation task of the low-cost solar array project

An important principle is that encapsulants should be tested in a total array system allowing realistic interaction of components. Therefore, micromodule test specimens were fabricated with a variety of encapsulants, substrates, and types of circuitry. One common failure mode was corrosion of circuitry and solar cell metallization due to moisture penetration. Another was darkening and/or opacification of encapsulant. A test program plan was proposed. It includes multicondition accelerated exposure. Another method was hyperaccelerated photochemical exposure using a solar concentrator. It simulates 20 year of sunlight exposure in a short period of one to two weeks. The study was beneficial in identifying some cost effective encapsulants and array designs.

Kolyer, J. M.↗
NASA NTRS1992

Debris and micrometeorite impact measurements in the laboratory

A method was developed to simulate space debris in the laboratory. This method, which is an outgrowth of research in inertial confinement fusion (ICF), uses laser ablation to accelerate material. Using this method, single 60 micron aluminum spheres were accelerated to 15 km/sec and larger 500 micron aluminum spheres were accelerated to 2 km/sec. Also, many small (less than 10 micron diameter) irregularly shaped particles were accelerated to speeds of 100 km/sec.

Resnick, J.↗
NASA NTRS1983

Parallel solution of finite element equations

The paper examines several parallel processing solution algorithms for finite element equations arising in linear equilibrium problems. Two basic groups of algorithms, direct and iterative, are investigated with respect to a number of parallel computer architectures and associated selection criteria. The direct algorithms include: LR-Gauss, Crout, Cholesky, Cyclic Reduction and WZ-factorization. The iterative methods examined are: Accelerated Gauss-Seidel, Surrogate Stiffness, Jacobi, Series Expansion, and Energy Monte Carlo. For real-time applications, where the object is to minimize the execution time, Cyclic Reduction appears to be best suited. This assumes a computer with an unlimited number of parallel processors. However, for computers with a limited number of parallel processors that must be used efficiently, both Gauss factorization and Jacobi-like iterative methods rank favorably.

Salama, M.↗
NASA NTRS1988

Predicted and measured strain responses of isotropic panels to base excitation

The accuracy of classical linear theory for predicting acceleration and strain for cantilevered and Clamped-Free-Clamped-Free (C-F-C-F) panels excited through the base is studied. Aluminum, steel and titanium plates of various dimensions and thicknessess were vibration tested, using a broadband random signal applied through a shaker mounting fixture. The strains were measured at 9 locations on the cantilevered panels and at 5 locations on the C-F-C-F panels. Predictions were based on the Ritz method. The measured accelerations of the base were input to the analysis for the forcing function. Comparisons between predicted and measured strain acceleration spectra were within an average error of 20 percent for both the cantilevered and C-F-C-F panels.

Lyle, Karen H.↗
DOE OSTI2020

Quantitative Determination of Biomass-derived Renewable Carbon in Fuels from Coprocessing of Bio-oils in Refinery Using a Stable Carbon Isotopic Approach

Increasing renewable carbon incorporation into conventional fuels through coprocessing with vacuum gas oil (VGO, a petroleum refining feedstock) is a critical step in biofuels development, scaling-up, adoption and associated GHG reduction. Optimization of the co-processing parameters maximizes incorporation of the renewable carbon in the fuel products. Quantitative determination of the renewable carbon content in the co-processed products provides direct evaluation of the parameters. The co-processing bio-oil with VGO through hydrocracking (HC) or fluid catalytic cracking (FCC) system resulted in carbon isotopic fractionation that prevented the direct use of the isotope mixing model for quantifying the renewable carbon. Here, we report an algorithm of using a stable carbon isotope approach to quantify the renewable carbon content in co-processing biofuel products through high-precision ?13C analysis. A controlled experiment carried out by blending a fossil diesel (-29.013‰) with a bio-diesel (-30.099‰) at various blending levels up to 98.0/2.0 wt% is presented and has demonstrated the applicability of this approach. The carbon isotope fractionation factors for the bio-oil co-processing were obtained by using a 14C-derived isotope-mixing model. The ?13C method was tested by co-processing 13C-labeled bio-crude and natural woody biomass-derived fast pyrolysis (FP) and catalytic fast pyrolysis (CFP) bio-oils with VGO. The results were verified by 14C accelerator mass spectrometry (AMS) method (ASTM-D6866) and compared with the yield mass balance (YMB) method. Strong agreement between d13C and 14C AMS methods demonstrated the applicability of the ?13C method to quantify renewable carbon content in co-processing fuel products and guide the co-processing optimization

Li, Zhenghua↗
DOE OSTI2024

cppTPSA/pyTPSA: a C++/Python package for truncated power series algebra

The truncated power series algebra (TPSA), also referred to as differential algebra (DA), is a well-established and widely used method in particle accelerator physics and astronomy. The most straightforward usage of TPSA/DA is to calculate the Taylor expansion of a given function at a specific point up to order ?. In recent years, as the application of TPSA/TA has been extended to other fields, a reusable implementation of TPSA/DA as a modern C++ library or other high level programming language like Python has become desirable. The cppTPSA package implements TPSA/DA in C++11 and provides developers a convenient library with which to build advanced TPSA/DA-based methods. A Python 3 library, pyTPSA, has also been developed based on the C++ lib.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Progress Update on the In Situ Load Retention Aging Vessel

To improve upon our conventional thermally accelerated aging study methods which require periodic interruption of aging to perform load testing in an Instron machine, a new aging system is being developed to: (1) automate/facilitate data acquisition/analysis, (2) improve data quality, and (3) enable uninterrupted aging conditions (compression, temperature, atmosphere) which represents the service condition. In FY24, a thermal aging vessel instrumented with load cells was fabricated and tested. That unit demonstrated the primary function of the vessel: to continuously monitor the in situ load retention of up to three compressed polymer coupons undergoing thermally accelerated aging under nitrogen. A secondary objective, not realized in the unit due to inadequate sealing, was to enable a single initial nitrogen backfill (as opposed to a continuous purge) and gas sampling of the vessel headspace during thermal aging. Heating of the vessel was achieved using a custom heater jacket.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accelerator Physics at NSLS-II: Research Accomplishments in 2022

NSLS-II accelerator physicists are working on scientific support of the NSLS-II operations and start-up of the accelerator systems including Storage Ring, Injector, beam diagnostics, and top-off injection; improvement of beam stability and orbit feedbacks; commissioning of a superconducting wiggler for the HEX beamline; development of a new operation mode for time-resolved experiments. The routine lattice characterization is continued to keep tracking the machine, the storage ring lattice model including strong coupling is developed, and seasonal variations of the ring circumference are studied. The collaboration with the EIC project is ongoing. In the frameworks of three LDRD projects, the physicists are working on the lattice development, studies of collective effects, and specifications of alignment and stability for the NSLS-II accelerator upgrade; novel methods of lattice design and optimization; studies of free-electron laser options; ultrafast electron diffraction and microscopy. Research accomplishments achieved in 2022, are summarized in this report.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗