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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Computational Methods for Multi-Physics Simulation of Melting in Steelmaking

Iron and steel production accounts for approximately 8% of global carbon dioxide (CO) emissions. Pathways to decarbonize include replacing fossil fuels in iron ore reduction and electrifying other steelmaking processes. Iron pellets produced by hydrogen, called Hydrogen Direct Reduced Iron (HDRI), have property differences from those produced using conventional DRI processes. These differences may impact melting in electric arc furnaces (EAF) and other downstream processes. The physical properties of iron pellets vary significantly with temperature during heating, complicating predictions of their behavior. In this project, we seek to develop an integrated simulation, including the fluid flow and convective thermal transport around the pellet particle. We also examine conduction and phase changes within the particle as they impact the melting process. We use adaptive mesh refinement (AMR) to resolve both the changing size of the particle and the complex physics of the interaction between the pellet and the surrounding fluid. We base our simulations on the AMReX-incflo module, which allows large-scale Navier-Stokes simulation while resolving the changing particle size during melting. As we advance our numerical tools, we anticipate an improved understanding of the dynamics of HDRI melting, which will, in turn, accelerate the adoption of low-carbon technologies in the steelmaking industry.

AMReX↗
DOE OSTI2025

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Eavesdropping on the Decohering Environment: Quantum Darwinism, Amplification, and the Origin of Objective Classical Reality

“How much information about a system S can one extract from a fragment F of the environment E that decohered it?” is the central question of Quantum Darwinism. To date, most answers relied on the quantum mutual information of SF, or on the Holevo bound on the channel capacity of F to communicate the classical information encoded in S. Furthermore, these are reasonable upper bounds on what is really needed but much harder to calculate—the accessible information in the fragment F about S. We consider a model based on imperfect c-not gates where all the above can be computed, and discuss its implications for the emergence of objective classical reality. We find that all relevant quantities, such as the quantum mutual information as well as various bounds on the accessible information exhibit similar behavior. In the regime relevant for the emergence of objective classical reality this includes scaling independent of the quality of the imperfect c-not gates or the size of E, and even nearly independent of the initial state of S.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Logical memory address regions

Systems, apparatuses, and methods for implementing logical memory address regions in a computing system. The physical memory address space of a computing system may be partitioned into a plurality of logical memory address regions. Each logical memory address region may be dynamically configured at run-time to meet changing application needs of the system. Each logical memory address region may also be configured separately from the other logical memory address regions. Each logical memory address region may have associated parameters that identify region start address, region size, cell-level mode, physical-to-device mapping scheme, address masks, access permissions, wear-leveling data, encryption settings, and compression settings. These parameters may be stored in a table which may be used when processing memory access requests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Unique Methodologies for Nano/Micro Manufacturing Job Training Via Desktop Supercomputer Modeling and Simulation

This project establishes an initiative in high speed (Teraflop)/large-memory desktop supercomputing for modeling and simulation of dynamic processes important for energy and industrial applications. It provides a training ground for employment of current students in an emerging field with skills necessary to access the large supercomputing systems now present at DOE laboratories. It also provides a foundation for NIU faculty to quantum leap beyond their current small cluster facilities. The funding extends faculty and student capability to a new level of analytic skills with concomitant publication avenues. The components of the Hewlett Packard computer obtained by the DOE funds create a hybrid combination of a Graphics Processing System (12 GPU/Teraflops) and a Beowulf CPU system (144 CPU), the first expandable via the NIU GAEA system to ~60 Teraflops integrated with a 720 CPU Beowulf system. The software is based on access to the NVIDIA/CUDA library and the ability through MATLAB multiple licenses to create additional local programs. A number of existing programs are being transferred to the CPU Beowulf Cluster. Since the expertise necessary to create the parallel processing applications has recently been obtained at NIU, this effort for software development is in an early stage. The educational program has been initiated via formal tutorials and classroom curricula designed for the coming year. Specifically, the cost focus was on hardware acquisitions and appointment of graduate students for a wide range of applications in engineering, physics and computer science.

Kimball, Clyde↗
DOE OSTI2022

Fock-Space Schrieffer–Wolff Transformation: Classically-Assisted Rank-Reduced Quantum Phase Estimation Algorithm

We present an extension of many-body downfolding methods to reduce the resources required in the quantum phase estimation (QPE) algorithm. In this paper, we focus on the Schrieffer–Wolff (SW) transformation of the electronic Hamiltonians for molecular systems that provides significant simplifications of quantum circuits for simulations of quantum dynamics. We demonstrate that by employing Fock-space variants of the SW transformation (or rank-reducing similarity transformations (RRST)) one can significantly increase the locality of the qubit-mapped similarity-transformed Hamiltonians. The practical utilization of the SW-RRST formalism is associated with a series of approximations discussed in the manuscript. In particular, amplitudes that define RRST can be evaluated using conventional computers and then encoded on quantum computers. The SW-RRST QPE quantum algorithms can also be viewed as an extension of the standard state-specific coupled-cluster downfolding methods to provide a robust alternative to the traditional QPE algorithms to identify the ground and excited states for systems with various numbers of electrons using the same Fock-space representations of the downfolded Hamiltonian. The RRST formalism serves as a design principle for developing new classes of approximate schemes that reduce the complexity of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Simplex-stochastic collocation method with improved scalability

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Discrete Thermodynamics

Here, we consider the dependence of velocity probability distribution functions on the finite size of a thermodynamic system. We are motivated by applications to computational fluid dynamics, hence discrete thermodynamics. We then begin by describing a coarsening process that represents geometric renormalization. Then, based only on the requirements of conservation, we demonstrate that the pervasive assumption of local thermodynamic equilibrium is not form invariant. We develop a perturbative correction that restores form invariance to second-order in a small parameter associated with macroscopic gradients. Finally, we interpret the corrections in terms of unresolved kinetic energy and discuss the implications of our results both in theory and as applied to numerical simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

AMPX: A Modern cross section processing system for generating nuclear data libraries - 14619

Nuclear data libraries are essential for nuclear analysis code systems like SCALE. AMPX has been continuously developed since the early 1970's and is used to generate these data libraries for SCALE. Recently, Oak Ridge National Laboratory (ORNL) initiated a major modernization effort to position AMPX for continued development and deployment on modern computing platforms. An important step toward modernization has been to merge AMPX under the SCALE continuous integration (CI) development framework. As a result, AMPX is now developed under the SCALE software quality assurance plan, providing increased confidence in the quality of data libraries developed and deployed by AMPX. This merge allowed us to develop novel methods to generate self-shielding factors that combine SCALE's resonance self-shielding capabilities with the AMPX library-generation capabilities. AMPX processes Evaluated Nuclear Data Format (ENDF/B) files. The ENDF community is working to develop a more modern format that will replace the existing ENDF/B format. Due to strict space and memory requirements when AMPX was first developed, the original AMPX processing and reading of ENDF data were tightly integrated. On newer computer systems, this is no longer necessary. Now there is a separation between reading and processing which allows for simultaneous support of current and new ENDF formats. As a result, AMPX is positioned to adopt any new ENDF format when available. For end users, the modernization effort has resulted in improved processing capabilities for generating nuclear data libraries. The objective of the paper is to document the latest AMPX cross-section processing capabilities and provide the current status of the AMPX modernization effort. (authors)

42 ENGINEERING↗
NASA NTRS1996

Development of a Computer Architecture to Support the Optical Plume Anomaly Detection (OPAD) System

The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.

Katsinis, Constantine↗
DOE OSTI2013

MC21 analysis of the MIT PWR benchmark: Hot zero power results

MC21 Monte Carlo results have been compared with hot zero power measurements from an operating pressurized water reactor (PWR), as specified in a new full core PWR performance benchmark from the MIT Computational Reactor Physics Group. Included in the comparisons are axially integrated full core detector measurements, axial detector profiles, control rod bank worths, and temperature coefficients. Power depressions from grid spacers are seen clearly in the MC21 results. Application of Coarse Mesh Finite Difference (CMFD) acceleration within MC21 has been accomplished, resulting in a significant reduction of inactive batches necessary to converge the fission source. CMFD acceleration has also been shown to work seamlessly with the Uniform Fission Site (UFS) variance reduction method. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2008

Current Computational Challenges for CMC Processes, Properties, and Structures

In comparison to current state-of-the-art metallic alloys, ceramic matrix composites (CMC) offer a variety of performance advantages, such as higher temperature capability (greater than the approx.2100 F capability for best metallic alloys), lower density (approx.30-50% metal density), and lower thermal expansion. In comparison to other competing high-temperature materials, CMC are also capable of providing significantly better static and dynamic toughness than un-reinforced monolithic ceramics and significantly better environmental resistance than carbon-fiber reinforced composites. Because of these advantages, NASA, the Air Force, and other U.S. government agencies and industries are currently seeking to implement these advanced materials into hot-section components of gas turbine engines for both propulsion and power generation. For applications such as these, CMC are expected to result in many important performance benefits, such as reduced component cooling air requirements, simpler component design, reduced weight, improved fuel efficiency, reduced emissions, higher blade frequencies, reduced blade clearances, and higher thrust. Although much progress has been made recently in the development of CMC constituent materials and fabrication processes, major challenges still remain for implementation of these advanced composite materials into viable engine components. The objective of this presentation is to briefly review some of those challenges that are generally related to the need to develop physics-based computational approaches to allow CMC fabricators and designers to model (1) CMC processes for fiber architecture formation and matrix infiltration, (2) CMC properties of high technical interest such as multidirectional creep, thermal conductivity, matrix cracking stress, damage accumulation, and degradation effects in aggressive environments, and (3) CMC component life times when all of these effects are interacting in a complex stress and service environment. To put these computational issues in perspective, the various modeling needs within these three areas are briefly discussed in terms of their technical importance and their key controlling mechanistic factors as we know them today. Emphasis is placed primarily on the SiC/SiC ceramic composite system because of its higher temperature capability and enhanced development within the CMC industry. A brief summary is then presented concerning on-going property studies aimed at addressing these CMC modeling needs within NASA in terms of their computational approaches and recent important results. Finally an overview perspective is presented on those key areas where further CMC computational studies are needed today to enhance the viability of CMC structural components for high-temperature applications.

DiCarlo, James↗
DOE OSTI2019

MPF X-Ray Module Setup for 2018

The Mobile Plutonium Facility (MPF) is a portable module design facility that can be deployed anywhere in the world for the safe recovery, packaging, and shipment of a nations legacy, or excess plutonium stockpile. All of the modules of MPF have specific purposes for operating in a mission if one were to ever come up. For my past four internships here at SRNL I have been working on the support of the X-Ray module for MPF. This year I installed new equipment I had purchased last year for the X-Ray Module and made sure the module was mission ready for the chance that the team deploys in the future for plutonium recovery. Using digital radiography (DR) and computed tomography (CT) provides the MPF team the ability to verify the contents of containers that would be holding material. This also ensures the safety of the team members in the glovebox facilities by verifying that there are no sharps, liquids, or other items that may harm the workers or glovebox operations when working with radioactive material. X-Ray imaging can also pick up low density objects like plastic bags and tape. Note how the DR image hides the puncture in the inner can while the CT image shows the damage. New DR and CT computers with upgraded software, New imaging panel, NOVO Portable X-Ray System. Because of the new upgrades to the X-Ray module system containers can be scanned and evaluated quicker than before. With the last system the 3D model reconstruction alone would take anywhere from 10-12 minutes, now with the new system that time has been brought down to just shy of 1 minute 30 seconds. The new portable system also can 1,2 or 4 images of an object and stitch them together into a mosaic for scanning of larger containers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Quantum fluctuation theorem for error diagnostics in quantum annealers

Near term quantum hardware promises unprecedented computational advantage. Crucial in its development is the characterization and minimization of computational errors. We introduce the use of the quantum fluctuation theorem to benchmark the accuracy of quantum annealers. This versatile tool provides simple means to determine whether the quantum dynamics are unital, unitary, and adiabatic, or whether the system is prone to thermal noise. Our proposal is experimentally tested on two generations of the D-Wave machine, which illustrates the sensitivity of the fluctuation theorem to the smallest aberrations from ideal annealing. In addition, for the optimally operating D-Wave machine, our experiment provides the first experimental verification of the integral fluctuation in an interacting, many-body quantum system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2003

In Search of the Physics: The Interplay of Experiment and Computation in Slat Aeroacoustics

The synergistic use of experiments and numerical simulations can uncover the underlying physics of airframe noise sources. We focus on the high-lift noise component associated with a leading-edge slat; flap side-edge noise is discussed in a companion paper by Streett et al. (2003). The present paper provides an overview of how slat noise was split into subcomponents and analyzed with carefully planned complementary experimental and numerical tests. We consider both tonal and broadband aspects of slat noise. The predicted far-field noise spectra are shown to be in good qualitative (and, to lesser extent, good quantitative agreement) with acoustic array measurements. Although some questions remain unanswered, the success of current airframe noise studies provides ample promise that remaining technical issues can be successfully addressed in the near future.

Khorrami, Mehdi R.↗
DOE OSTI2024

Respecting causality for training physics-informed neural networks

While the popularity of physics-informed neural networks (PINNs) is steadily rising, to this date PINNs have not been successful in simulating dynamical systems whose solution exhibits multi-scale, chaotic or turbulent behavior. In this work we attribute this shortcoming to the inability of existing PINNs formulations to respect the spatio-temporal causal structure that is inherent to the evolution of physical systems. We argue that this is a fundamental limitation and a key source of error that can ultimately steer PINN models to converge towards erroneous solutions. We address this pathology by proposing a simple re-formulation of PINNs loss functions that can explicitly account for physical causality during model training. We demonstrate that this simple modification alone is enough to introduce significant accuracy improvements, as well as a practical quantitative mechanism for assessing the convergence of a PINNs model. Here we provide state-of-the-art numerical results across a series of benchmarks for which existing PINNs formulations fail, including the chaotic Lorenz system, the Kuramoto–Sivashinsky equation in the chaotic regime, and the Navier–Stokes equations. To the best of our knowledge, this is the first time that PINNs have been successful in simulating such systems, introducing new opportunities for their applicability to problems of industrial complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Learning physics-based reduced-order models from data using nonlinear manifolds

Here we present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed approach is driven by embeddings of low-order polynomial form. A projection onto the nonlinear manifold reveals the algebraic structure of the reduced-space system that governs the problem of interest. The matrix operators of the reduced-order model are then inferred from the data using operator inference. Numerical experiments on a number of nonlinear problems demonstrate the generalizability of the methodology and the increase in accuracy that can be obtained over reduced-order modeling methods that employ a linear subspace approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Supo Thermal Model Development II

This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the report, Supo Thermal Model Development1, by Cynthia Buechler. The goal for this report is to estimate the natural convection heat transfer coefficient (HTC) of the system using the CFD results and to compare those results to remaining past operational data. Also, the correlation for determining radiolytic gas bubble size is reevaluated using the larger simulation sample size. The background, solution vessel geometry, mesh, material properties, and boundary conditions are developed in the same manner as the previous report. Although, the material properties and boundary conditions are determined using the appropriate experiment results for each individual power level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗