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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Understanding the Flow Physics of Shock Boundary-Layer Interactions Using CFD and Numerical Analyses

Computational fluid dynamic (CFD) analyses of the University of Michigan (UM) Shock/Boundary-Layer Interaction (SBLI) experiments were performed as an extension of the CFD SBLI Workshop held at the 48th AIAA Aerospace Sciences Meeting in 2010. In particular, the UM Mach 2.75 Glass Tunnel with a semi-spanning 7.75deg wedge was analyzed in attempts to explore key physics pertinent to SBLI's, including thermodynamic and viscous boundary conditions as well as turbulence modeling. Most of the analyses were 3D CFD simulations using the OVERFLOW flow solver, with additional quasi-1D simulations performed with an in house MATLAB code interfacing with the NIST REFPROP code to explore perfect verses non-ideal air. A fundamental exploration pertaining to the effects of particle image velocimetry (PIV) on post-processing data is also shown. Results from the CFD simulations showed an improvement in agreement with experimental data with key contributions including adding a laminar zone upstream of the wedge and the necessity of mimicking PIV particle lag for comparisons. Results from the quasi-1D simulation showed that there was little difference between perfect and non-ideal air for the configuration presented.

Friedlander, David J.↗
DOE OSTI2017

Basic Energy Sciences Roundtable: Opportunities for Basic Research for Next-Generation Quantum Systems

For decades, scientists have predicted that devices based on “quantum phenomena” will be able to store and manipulate information to provide radical new approaches for computing, communication, and sensing. However, only recently have quantum phenomena been incorporated into technologies for next-generation computers, sensors, and detectors that demonstrate performance characteristics rivaling those of their conventional counterparts. These devices clearly demonstrate the enormous potential for future quantum-based technologies. The novel quantum device capabilities currently envisioned include enhanced resolution in imaging, sensors, and detectors; advanced cryptography for more secure communication; and significantly larger computational capabilities at speeds far greater than those possible in classical computing. However, realizing these advances requires a detailed understanding of how quantum systems (including quantum materials or assemblies of trapped ions and electrons) behave, accurate knowledge of how to integrate the components into complex systems, and precise control of the structures. In this context, creating and controlling quantum states within molecules and materials offer exciting scientific opportunities for fundamental research, as well as for enabling next-generation quantum-based technologies. Numerous questions remain, ranging from how quantum interactions may enable innovation through the creation of novel quantum systems, to how these new quantum technologies can advance our understanding of matter and chemistry at the most fundamental levels. To address these questions and identify priority research opportunities (PROs), the US Department of Energy (DOE) Office of Basic Energy Sciences (BES) convened a roundtable of experts in quantum materials and quantum systems encompassing the fields of physics, chemistry, materials synthesis science, device engineering, detector technology, and atomic-scale characterization techniques. This group of experimentalists and theorists met on October 30–31, 2017, to explore scientific research opportunities in this rapidly moving field, in which BES support can play a key role in advancing and utilizing quantum information science (QIS). The goals of this roundtable were to define the unique roles for BES in this active research field and to provide input on future research directions, forming the basis for a coordinated, long-term research effort that will enable major advances in quantum-based science and technology. BES is uniquely positioned to advance this field because of its long history of fundamental research support for both materials and chemical sciences, along with its construction and operation of world-class scientific user facilities. Fundamental research in this area is strongly coupled to DOE efforts in scientific computing, high-energy physics, and accelerator/detector research and related to activities in “Beyond Moore’s Law” computing, next-generation semiconductor materials, and exascale computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Direct imaging of shock wave splitting in diamond at Mbar pressure

Understanding the behavior of matter at extreme pressures of the order of a megabar (Mbar) is essential to gain insight into various physical phenomena at macroscales—the formation of planets, young stars, and the cores of super-Earths, and at microscales—damage to ceramic materials and high-pressure plastic transformation and phase transitions in solids. Under dynamic compression of solids up to Mbar pressures, even a solid with high strength exhibits plastic properties, causing the induced shock wave to split in two: an elastic precursor and a plastic shock wave. This phenomenon is described by theoretical models based on indirect measurements of material response. The advent of x-ray free-electron lasers (XFELs) has made it possible to use their ultrashort pulses for direct observations of the propagation of shock waves in solid materials by the method of phase-contrast radiography. However, there is still a lack of comprehensive data for verification of theoretical models of different solids. Here, we present the results of an experiment in which the evolution of the coupled elastic–plastic wave structure in diamond was directly observed and studied with submicrometer spatial resolution, using the unique capabilities of the x-ray free-electron laser (XFEL). The direct measurements allowed, for the first time, the fitting and validation of the 2D failure model for diamond in the range of several Mbar. Our experimental approach opens new possibilities for the direct verification and construction of equations of state of matter in the ultra-high-stress range, which are relevant to solving a variety of problems in high-energy-density physics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Quantitative Parameter Estimation, Model Selection, and Variable Selection in Battery Science

Numerical physics-based models are useful in understanding battery performance and devel- oping optimal battery design architectures. Data science developments have enabled software algorithms to perform data analysis and decision making that traditionally could only be per- formed by technical experts. Traditional workflows of model development - manual parameter estimation through visual comparison of simulations to experimental observations, and model discrimination through expert intuition - are time-consuming, and difficult to justify. This paper compares the conclusions derived from computationally scalable algorithms to conclu- sions developed by expert researchers. This paper illustrates how data science techniques, such as cross-validation and lasso regression, can be used to augment physics-based simulations to perform data analysis such as parameter estimation, model selection, variable selection, and model-guided design of experiment. The validation of these algorithms is that they produce results similar to those of the expert modeler. The algorithms outlined are well-established and the approaches are general, so can be applied to a variety of battery chemistries and architectures. The conclusions reached using these approaches are in agreement with expert analysis (literature results), were reached with minimal human intervention, and provide quantitative justification. By minimizing the amount of expert time, and providing rigorous quantitative justifications, these methods may accelerate battery development.

25 ENERGY STORAGE↗
DOE OSTI2015

Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-­L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-­bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-­4 weeks of an FTE split amongst two staff scientists and one post-­doc. The DEM simulations emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-­particles square by 10-­particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Future computing platforms for science in a power constrained era

Power consumption will be a key constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics (HEP). This makes performance-per-watt a crucial metric for selecting cost-efficient computing solutions. For this paper, we have done a wide survey of current and emerging architectures becoming available on the market including x86-64 variants, ARMv7 32-bit, ARMv8 64-bit, Many-Core and GPU solutions, as well as newer System-on-Chip (SoC) solutions. We compare performance and energy efficiency using an evolving set of standardized HEP-related benchmarks and power measurement techniques we have been developing. In conclusion, we evaluate the potential for use of such computing solutions in the context of DHTC systems, such as the Worldwide LHC Computing Grid (WLCG).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

Proceedings of RIKEN BNL Research Center Workshop, Volume 113: Thermal Radiation Workshop

The RIKEN BNL Research Center (RBRC) was established in April 1997 at Brookhaven National Laboratory. It is funded by the "Rikagaku Kenkyusho" (RIKEN, The Institute of Physical and Chemical Research) of Japan. The Memorandum of Understanding between RIKEN and BNL, initiated in 1997, has been renewed in 2002, 2007 and again in 2012. The Center is dedicated to the study of strong interactions, including spin physics, lattice QCD, and RHIC physics through the nurturing of a new generation of young physicists. The RBRC has both a theory and experimental component. The RBRC Theory Group and the RBRC Experimental Group consists of a total of 25-30 researchers. Positions include the following: full time RBRC Fellow, half-time RHIC Physics Fellow, and full-time post doctoral Research Associate. The RHIC Physics Fellows hold joint appointments with RBRC and other institutions and have tenure track positions at their respective universities or BNL. To date, RBRC has over 95 graduates (Fellows and Post- docs) of which approximately 40 theorists and 20 experimenters have already attained tenure positions at major institutions worldwide. Beginning in 2001 a new RIKEN Spin Program (RSP) category was implemented at RBRC. These appointments are joint positions of RBRC and RIKEN and include the following positions in theory and experiment: RSP Researchers, RSP Research Associates, and Young Researchers, who are mentored by senior RBRC Scientists. A number of RIKEN Jr. Research Associates and Visiting Scientists also contribute to the physics program at the Center. RBRC has an active workshop program on strong interaction physics with each workshop focused on a specific physics problem. In most cases all the talks are made available on the RBRC website. In addition, highlights to each speaker’s presentation are collected to form proceedings which can therefore be made available within a short time after the workshop. To date there are over one hundred proceeding volumes available. A 10 teraflops RBRC QCDOC computer funded by RIKEN, Japan, was unveiled at a dedication ceremony at BNL on May 26, 2005. This supercomputer was designed and built by individuals from Columbia University, IBM, BNL, RBRC, and the University of Edinburgh, with the U.S. D.O.E. Office of Science providing infrastructure support at BNL. Physics results were reported at the RBRC QCDOC Symposium following the dedication. QCDSP, a 0.6 teraflops parallel processor, dedicated to lattice QCD, was begun at the Center on February 19, 1998, was completed on August 28, 1998, and was decommissioned in 2006. It was awarded the Gordon Bell Prize for price performance in 1998. QCDOC was decommissioned in May 2012. The next generation computer in this sequence, QCDCQ (600 Teraflops), is currently operational and is expected to produce many more interesting discoveries in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Proceedings of RIKEN BNL Research Center Workshop: The Physics of p ↑ +A Collisions at RHIC

The RIKEN BNL Research Center (RBRC) was established in April 1997 at Brookhaven National Laboratory. It is funded by the "Rikagaku Kenkyusho" (RIKEN, The Institute of Physical and Chemical Research) of Japan. The Memorandum of Understanding between RIKEN and BNL, initiated in 1997, has been renewed in 2002, 2007 and again in 2012. The Center is dedicated to the study of strong interactions, including spin physics, lattice QCD, and RHIC physics through the nurturing of a new generation of young physicists. The RBRC has both a theory and experimental component. The RBRC Theory Group and the RBRC Experimental Group consists of a total of 25-30 researchers. Positions include the following: full time RBRC Fellow, half-time RHIC Physics Fellow, and full-time postdoctoral Research Associate. The RHIC Physics Fellows hold joint appointments with RBRC and other institutions and have tenure track positions at their respective universities or BNL. To date, RBRC has over 95 graduates (Fellows and Post- docs) of which approximately 40 theorists and 20 experimenters have already attained tenure positions at major institutions worldwide. Beginning in 2001 a new RIKEN Spin Program (RSP) category was implemented at RBRC. These appointments are joint positions of RBRC and RIKEN and include the following positions in theory and experiment: RSP Researchers, RSP Research Associates, and Young Researchers, who are mentored by senior RBRC Scientists. A number of RIKEN Jr. Research Associates and Visiting Scientists also contribute to the physics program at the Center. RBRC has an active workshop program on strong interaction physics with each workshop focused on a specific physics problem. In most cases all the talks are made available on the RBRC website. In addition, highlights to each speaker’s presentation are collected to form proceedings which can therefore be made available within a short time after the workshop. To date there are over one hundred proceeding volumes available. A 10 teraflops RBRC QCDOC computer funded by RIKEN, Japan, was unveiled at a dedication ceremony at BNL on May 26, 2005. This supercomputer was designed and built by individuals from Columbia University, IBM, BNL, RBRC, and the University of Edinburgh, with the U.S. D.O.E. Office of Science providing infrastructure support at BNL. Physics results were reported at the RBRC QCDOC Symposium following the dedication. QCDSP, a 0.6 teraflops parallel processor, dedicated to lattice QCD, was begun at the Center on February 19, 1998, was completed on August 28, 1998, and was decommissioned in 2006. It was awarded the Gordon Bell Prize for price performance in 1998. QCDOC was decommissioned in May 2012. The next generation computer in this sequence, QCDCQ (600 Teraflops), is currently operational and is expected to produce many more interesting discoveries in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2018

Quantum Machine Learning

Quantum computing promises an unprecedented ability to solve intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. The Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center is the space agency's primary facility for conducting research and development in quantum information sciences. QuAIL conducts fundamental research in quantum physics but also explores how best to exploit and apply this disruptive technology to enable NASA missions in aeronautics, Earth and space sciences, and space exploration. At the same time, machine learning has become a major focus in computer science and captured the imagination of the public as a panacea to myriad big data problems. In this talk, we will discuss how classical machine learning can take advantage of quantum computing to significantly improve its effectiveness. Although we illustrate this concept on a quantum annealer, other quantum platforms could be used as well. If explored fully and implemented efficiently, quantum machine learning could greatly accelerate a wide range of tasks leading to new technologies and discoveries that will significantly change the way we solve real-world problems.

Biswas, Rupak↗
DOE OSTI2017

Ferroelectric symmetry-protected multibit memory cell

Here, the tunability of electrical polarization in ferroelectrics is instrumental to their applications in information-storage devices. The existing ferroelectric memory cells are based on the two-level storage capacity with the standard binary logics. However, the latter have reached its fundamental limitations. Here we propose ferroelectric multibit cells (FMBC) utilizing the ability of multiaxial ferroelectric materials to pin the polarization at a sequence of the multistable states. Employing the catastrophe theory principles we show that these states are symmetry-protected against the information loss and thus realize novel topologically-controlled access memory (TAM). Our findings enable developing a platform for the emergent many-valued non-Boolean information technology and target challenges posed by needs of quantum and neuromorphic computing.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Majorana Superconducting Qubit

In this paper, we propose a platform for universal quantum computation that uses conventional $s$-wave superconducting leads to address a topological qubit stored in spatially separated Majorana bound states in a multiterminal topological superconductor island. Both the manipulation and readout of this “Majorana superconducting qubit” are realized by tunnel couplings between Majorana bound states and the superconducting leads. The ability of turning on and off tunnel couplings on demand by local gates enables individual qubit addressability while avoiding cross-talk errors. By combining the scalability of superconducting qubit and the robustness of topological qubits, the Majorana superconducting qubit may provide a promising and realistic route towards quantum computation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Self-Induced Curvature in an Internally Loaded Peridynamic Fiber

A straight fiber with nonlocal forces that are independent of bond strain is considered. These internal loads can either stabilize or destabilize the straight configuration. Transverse waves with long wavelength have unstable dispersion properties for certain combinations of nonlocal kernels and internal loads. When these unstable waves occur, deformation of the straight fiber into a circular arc can lower its potential energy in equilibrium. The equilibrium value of the radius of curvature is computed explicitly.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Methods and algorithms for computer synthesis of holographic elements to obtain a complex impulse response of optical information processing systems based on modern spatial light modulators

The possibilities of designing optical devices for data processing and imaging based on the manipulation of coherent light beams by means of spatial light modulators (SLMs) are investigated. A review of commercially available SLMs is presented and the limitations of their complex modulation characteristics are analysed. The main problem of using present-day SLMs is the lack of the ability to modulate directly all states within a unit circle in the complex plane. In this regard, the characteristics of current methods for the synthesis of holographic elements are described that implement a given complex impulse response of the optical system and are optimal for using SLMs with purely amplitude, purely phase, and hybrid amplitude – phase modulation. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Lessons from the COVID Era and Visions for the Future

In December 2020, the U.S. Department of Energy Office of Science convened a virtual Roundtable of its 27 operating scientific user facilities to discuss facility challenges and lessons learned during the COVID-19 pandemic as well as facility responses, best practices, and innovations that could be adopted going forward. Roundtable participants included facility staff, users, and user executive committee chairs. This report summarizes their discussions, which encompassed topics such as user research and facility operations in virtual and physically distanced contexts; user training and engagement; computation, data, and network resources; and crosscutting issues.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗
DOE OSTI2023

A dynamic variational multiscale method on unstructured meshes for stationary transport problems

Here, this paper presents a variational multiscale (VMS) based finite element method where the stabilization parameter is computed dynamically. The current dynamic procedure takes in a general structure/form of the stabilization parameter with unknown coefficients and computes them dynamically in a local fashion resulting in a dynamic VMS-based finite element method. Thus, a static stabilization parameter with pre-defined coefficients is not needed. A variational Germano identity (VGI) based local procedure suitable for unstructured meshes is developed to perform the dynamic computation in a local fashion. The local VGI based procedure is applied for each interior vertex in the mesh and unknown coefficients are first determined locally at each vertex, and subsequently, for each element a maximum value is taken over the vertices of the element. To make the current procedure practical, a coarser secondary solution is constructed from the primary coarse-scale solution, which is done locally over a patch of elements around each interior vertex. Further, averaging steps are employed to make the local dynamic procedure robust. Currently, the new dynamic VMS formulation is applied to steady problems governed by the advection-diffusion and incompressible Navier-Stokes equations in both 1D and 2D to demonstrate its efficacy and effectiveness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Mechanisms of Flame Stabilization and Blowout in a Reacting Turbulent Hydrogen Jet in Cross-Flow

The mechanisms contributing to flame stabilization and blowout in a nitrogen-diluted hydrogen transverse jet in a turbulent boundary layer cross-flow (JICF) are investigated using three-dimensional direct numerical simulation (DNS) with detailed chemistry. Non-reacting JICF DNS were performed to understand the relative magnitude and physical location of low velocity regions on the leeward side of the fuel jet where a flame can potentially anchor. As the injection angle is reduced from 90{sup o} to 70{sup o}, the low velocity region was found to diminish significantly, both in terms of physical extent and magnitude, and hence, its ability to provide favorable conditions for flame anchoring and stabilization are greatly reduced. In the reacting JICF DNS a stable flame is observed for 90{sup o} injection angle and, on average, the flame root is in the vicinity of low velocity magnitude and stoichiometric mixture. When the injection angle is smoothly transitioned to 75{sup o} a transient flame blowout is observed. Ensemble averaged quantities on the flame base reveal two phases of the blowout characterized by a kinematic imbalance between flame propagation speed and flow normal velocity. In the first phase dominant flow structures repeatedly draw the flame base closer to the jet centerline resulting in richer-than-stoichiometric mixtures and high velocity magnitudes. In the second phase, in spite of low velocity magnitudes and a return to stoichiometry, due to jet bending and flame alignment normal to the cross-flow, the flow velocity normal to the flame base increases dramatically perpetuating the blowout.

08 HYDROGEN↗