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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

A study of IMRT planning parameters on planning efficiency, delivery efficiency, and plan quality

Purpose: To improve planning and delivery efficiency of head and neck IMRT without compromising planning quality through the evaluation of inverse planning parameters.Methods: Eleven head and neck patients with pre-existing IMRT treatment plans were selected for this retrospective study. The Pinnacle treatment planning system (TPS) was used to compute new treatment plans for each patient by varying the individual or the combined parameters of dose/fluence grid resolution, minimum MU per segment, and minimum segment area. Forty-five plans per patient were generated with the following variations: 4 dose/fluence grid resolution plans, 12 minimum segment area plans, 9 minimum MU plans, and 20 combined minimum segment area/minimum MU plans. Each plan was evaluated and compared to others based on dose volume histograms (DVHs) (i.e., plan quality), planning time, and delivery time. To evaluate delivery efficiency, a model was developed that estimated the delivery time of a treatment plan, and validated through measurements on an Elekta Synergy linear accelerator. Results: The uncertainty (i.e., variation) of the dose-volume index due to dose calculation grid variation was as high as 8.2% (5.5 Gy in absolute dose) for planning target volumes (PTVs) and 13.3% (2.1 Gy in absolute dose) for planning at risk volumes (PRVs). Comparison results of dose distributions indicated that smaller volumes were more susceptible to uncertainties. The grid resolution of a 4 mm dose grid with a 2 mm fluence grid was recommended, since it can reduce the final dose calculation time by 63% compared to the accepted standard (2 mm dose grid with a 2 mm fluence grid resolution) while maintaining a similar level of dose-volume index variation. Threshold values that maintained adequate plan quality (DVH results of the PTVs and PRVs remained satisfied for their dose objectives) were 5 cm{sup 2} for minimum segment area and 5 MU for minimum MU. As the minimum MU parameter was increased, the number of segments and delivery time were decreased. Increasing the minimum segment area parameter decreased the plan MU, but had less of an effect on the number of segments and delivery time. Our delivery time model predicted delivery time to within 1.8%. Conclusions: Increasing the dose grid while maintaining a small fluence grid allows for improved planning efficiency without compromising plan quality. Delivery efficiency can be improved by increasing the minimum MU, but not the minimum segment area. However, increasing the respective minimum MU and/or the minimum segment area to any value greater than 5 MU and 5 cm{sup 2} is not recommended because it degrades plan quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Game Theory for Proactive Dynamic Defense and Attack Mitigation in Cyber-Physical Systems

While there has been a great deal of security research focused on preventing attacks, there has been less work on how one should balance security and resilience investments. In this work we developed and evaluated models that captured both explicit defenses and other mitigations that reduce the impact of attacks. We examined these issues both in more broadly applicable general Stackelberg models and in more specific network and power grid settings. Finally, we compared these solutions to existing work in terms of both solution quality and computational overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Algorithm to calculate off-plane magnetic field from an on-plane field map

An algorithm is presented to calculate the field components [B x (x,y,z), B y (x,y,z), B z (x,y,z)] of the magnetic field at a point (x,y,z) in space, from the knowledge of the components [B x (x,y = 0,z), B y (x,y = 0,z), B z (x,y = 0,z)] on a ”reference plane”, which is normal to the y-axis at y=0. The algorithm, which is a general one and is not restricted to fields with mid-plane symmetry is based on the Taylor series expansion of the magnetic field components at any point in space in terms of the distance (y) of the point from the reference plane. The coefficients of the Taylor series expansion are expressed in terms of the on-plane field components and their partial derivatives with respect to spatial coordinates (x,z). The field components are usually generated from magnetic field measurements on a rectangular grid on the plane. The required partial derivatives of the field components on the plane can be computed with two methods; numerically, or by fitting a polynomial function to the experimentally measured values of the field components and subsequently take the required partial derivatives of the polynomial function. Each of these two method which calculates the partial derivatives of the field components on the plane, is applied to calculate the off-plane field components of the magnetic field generated by a modified Halbach magnet [1] of inner radius of 4.4 cm and it is found that each method provides accurate results with a relative error <1% deviation from the ”ideal” fields if the y distance of the point from the reference plane is smaller than 2 cm. This algorithm is part of the RAYTRACE computer code [2] and has been applied [3] on a dipole magnet with median plane symmetry.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Gaussian Process Emulators for Volcanic Ash Dispersion Model Tephra2

It is necessary to predict volcanic ash deposition since falling ash is harmful to human activities. Because simulators built for this purpose are computationally expensive, it is popular to use statistical emulators for geophysical hazard analyses, where a large number of simulations are required. Gaussian stochastic process emulators are able to approximate expensive simulations in an accurate and efficient way. Using a relatively small number of simulation runs, a well-trained emulator can accurately predict simulation outputs at massive new input points in a few seconds. Under different explosive eruption conditions, we constructed Gaussian stochastic process emulators for Tephra2, a simulation tool for estimating the accumulation of volcanic ash over a region. Historical wind records are used as input wind data, without assuming a Gaussian wind speed profile or common wind direction among elevations. While there are several inputs for Tephra2, we use no more than three physically motivated variables as emulator inputs to reduce the computational cost of emulations. The emulator outputs predict the mass of tephra per unit area at 50281 grid points around a predetermined vent location.

58 GEOSCIENCES↗
DOE OSTI2025

High sensitivity of simulated fog properties to parameterized aerosol activation in case studies from ParisFog

Aerosols influence fog properties such as visibility and lifetime by affecting fog droplet number concentrations (N d ). Numerical weather prediction (NWP) models often represent aerosol–fog interactions using highly simplified approaches. Incorporating prognostic size-resolved aerosol microphysics from climate models could allow them to simulate N d and aerosol–fog interactions without incurring excessive computational expense. However, microphysics code designed for coarse spatial resolution may struggle with sub-kilometer-scale grid spacings. Here, we test the ability of the UK Met Office Unified Model to simulate aerosol and fog properties during case studies from the ParisFog field campaign in 2011. We examine the sensitivity of fog properties to variations in N d caused by modifications to simulated aerosol activation. Our model, with a 500 m horizontal resolution and interactive aerosol and cloud microphysics, significantly underpredicts N d , although it only slightly underestimates the cloud condensation nuclei concentration. With an updated version of the Abdul-Razzak and Ghan (2000) activation scheme, we produce N d that are more consistent with those predicted by a cloud parcel model under fog-like conditions. We activate droplets only by adiabatic cooling. We incorporate more realistic hygroscopicities for sulfate and organic aerosols and explore the sensitivity of simulated N d to unresolved updrafts. We find that both N d and simulated fog liquid water content are very sensitive to the updated activation scheme but remain less affected by the update to hygroscopicities. Our improvements offer insights into the physical processes regulating N d in stable conditions, potentially laying foundations for improved operational fog forecasts that incorporate interactive aerosol simulations or aerosol climatologies.

Ghosh, Pratapaditya [Carnegie Mellon University, P↗
DOE OSTI2016

Revised Extended Grid Library

The Revised Eolus Grid Library (REGL) is a mesh-tracking library that was developed for use with the MCNP6TM computer code so that (radiation) particles can track on an unstructured mesh. The unstructured mesh is a finite element representation of any geometric solid model created with a state-of-the-art CAE/CAD tool. The mesh-tracking library is written using modern Fortran and programming standards; the library is Fortran 2003 compliant. The library was created with a defined application programmer interface (API) so that it could easily integrate with other particle tracking/transport codes. The library does not handle parallel processing via the message passing interface (mpi), but has been used successfully where the host code handles the mpi calls. The library is thread-safe and supports the OpenMP paradigm. As a library, all features are available through the API and overall a tight coupling between it and the host code is required. Features of the library are summarized with the following list: Can accommodate first and second order 4, 5, and 6-sided polyhedra; any combination of element types may appear in a single geometry model; parts may not contain tetrahedra mixed with other element types; pentahedra and hexahedra can be together in the same part; robust handling of overlaps and gaps; tracks element-to-element to produce path length results at the element level; finds element numbers for a given mesh location; finds intersection points on element faces for the particle tracks; produce a data file for post processing results analysis; reads Abaqus .inp input (ASCII) files to obtain information for the global mesh-model; supports parallel input processing via mpi; and support parallel particle transport by both mpi and OpenMP.

Martz, Roger L.↗
DOE OSTI2017

A stable and accurate partitioned algorithm for conjugate heat transfer

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in a implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems together with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode the- ory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized- Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and dif- fusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. Lastly, the CHAMP scheme is also developed for general curvilinear grids and CHT ex- amples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Prevalence and scalable control of localized networks

The ability to control network dynamics is essential for ensuring desirable functionality of many technological, biological, and social systems. Such systems often consist of a large number of network elements, and controlling large-scale networks remains challenging because the computation and communication requirements increase prohibitively fast with network size. Here, we introduce a notion of network locality that can be exploited to make the control of networks scalable, even when the dynamics are nonlinear. We show that network locality is captured by an information metric and is almost universally observed across real and model networks. In localized networks, the optimal control actions and system responses are both shown to be necessarily concentrated in small neighborhoods induced by the information metric. This allows us to develop localized algorithms for determining network controllability and optimizing the placement of driver nodes. This also allows us to develop a localized algorithm for designing local feedback controllers that approach the performance of the corresponding best global controllers, while incurring a computational cost orders-of-magnitude lower. Here, we validate the locality, performance, and efficiency of the algorithms in Kuramoto oscillator networks, as well as three large empirical networks: synchronization dynamics in the Eastern US power grid, epidemic spreading mediated by the global air-transportation network, and Alzheimer’s disease dynamics in a human brain network. Taken together, our results establish that large networks can be controlled with computation and communication costs comparable to those for small networks.

42 ENGINEERING↗
DOE OSTI2020

Moment preserving constrained resampling with applications to particle-in-cell methods

The Moment Preserving Constrained Resampling (MPCR) algorithm for particle resampling is introduced and applied to particle-in-cell (PIC) methods to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. The general algorithm partitions the system space into smaller subsets and resamples the distribution within each subset. Further, the algorithm is designed to conserve any number of particle and grid moments with a high degree of accuracy (i.e. machine accuracy). The effectiveness of MPCR is demonstrated with several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. Finally, the computational cost of MPCR is negligible compared to the cost of particle evolution in PIC methods, and the tests demonstrate that periodic particle resampling yields a significant improvement in the accuracy and stability of the results.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Quantum computation of SU(2) lattice gauge theory with continuous variables

We present a quantum computational framework for pure SU(2) lattice gauge theory, using continuous variables instead of discrete qubits to represent the infinite-dimensional Hilbert space of the gauge fields. We consider a ladder as well as a two-dimensional grid of plaquettes, detailing the use of gauge fixing to reduce the degrees of freedom and simplify the Hamiltonian. We demonstrate how system dynamics, ground states, and energy gaps can be computed using the continuous-variable approach to quantum computing. Our results indicate that it is feasible to study non-Abelian gauge theories with continuous variables, providing new avenues for understanding the real-time dynamics of quantum field theories.

Gauge Symmetry↗
DOE OSTI2017

Importance of turbulence-chemistry interactions at low temperature engine conditions

The role of turbulence-chemistry interaction in autoignition and flame stabilization is investigated for spray flames at low temperature combustion (LTC) conditions by performing high-fidelity three-dimensional computational fluid dynamics (CFD) simulations. A recently developed Tabulated Flamelet Model (TFM) is coupled with a large eddy simulation (LES) framework and validated across a range of Engine Combustion Network (ECN) ambient temperature conditions for n-dodecane fuel. High resolution grids with 0.0625 mm minimum cell size and 25 million total cell count are implemented using adaptive mesh refinement over the spray and combustion regions. Simulations with these grids and multiple LES realizations, with a 103 species n-dodecane mechanism show good agreement with experimental data for all the ambient conditions investigated. This modeling approach with the computational cost advantage of tabulated chemistry is then extended towards understanding the auto-ignition and flame stabilization at an ambient temperature of 750 K. These low temperature conditions lead to substantially higher ignition delays and flame liftoff lengths, and significantly leaner combustion compared to conventional high temperature diesel combustion. These conditions also require the simulations to span significantly larger temporal and spatial dimensions thereby increasing the computational cost. The TFM approach is able to capture autoignition and flame liftoff length at the low temperature conditions. Significant differences with respect to mixing, species formation and flame stabilization are observed under low temperature compared to conventional diesel combustion. At higher ambient temperatures, formation of formaldehyde is observed in the rich region (phi > 1) followed by the formation of OH in the stoichiometric regions. Under low temperature conditions, formaldehyde is observed to form at leaner regions followed by the onset of OH formation in significantly lean regions of the flame. Qualitative differences between species formation and transient flame development for the high and low temperature conditions are presented. The two stage ignition process is further investigated by studying the species formation in mixture fraction space by solving 1D flamelet equations for different scalar dissipation rates and homogeneous reactor assumption. Results show that scalar dissipation causes these radicals to diffuse within the mixture fraction space. As a result, this significantly enhances ignition and plays a dominant role at such low temperature conditions which cannot be captured by the homogeneous reaction assumption based model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Permanent Magnet Synchronous Condenser for Wind Power Plant Grid Connection Support: Preprint

A synchronous condenser (SC) using a permanent magnet synchronous generator (PMSG) is proposed for providing necessary reactive power to a wind power plant to support its connection to a weak grid. A PMSG has the advantage of higher efficiency and reliability. Because of its lack of a field winding, a PMSG is typically controlled by a full-power converter, which can be costly. In the proposed system, the reactive power of the SC is controlled by a serially connected compensator operating in a closed-loop configuration. The compensator also damps the PMSG's tendency to oscillate. The compensator's VA rating is only a fraction of the rating of the SC and the PMSG. In this initial investigation, the proposed scheme is shown to be effective by computer simulations.

17 WIND ENERGY↗
DOE OSTI2014

Accurate small and wide angle x-ray scattering profiles from atomic models of proteins and nucleic acids

A new method is introduced to compute X-ray solution scattering profiles from atomic models of macromolecules. The three-dimensional version of the Reference Interaction Site Model (RISM) from liquid-state statistical mechanics is employed to compute the solvent distribution around the solute, including both water and ions. X-ray scattering profiles are computed from this distribution together with the solute geometry. We describe an efficient procedure for performing this calculation employing a Lebedev grid for the angular averaging. The intensity profiles (which involve no adjustable parameters) match experiment and molecular dynamics simulations up to wide angle for two proteins (lysozyme and myoglobin) in water, as well as the small-angle profiles for a dozen biomolecules taken from the BioIsis.net database. The RISM model is especially well-suited for studies of nucleic acids in salt solution. Use of fiber-diffraction models for the structure of duplex DNA in solution yields close agreement with the observed scattering profiles in both the small and wide angle scattering (SAXS and WAXS) regimes. In addition, computed profiles of anomalous SAXS signals (for Rb{sup +} and Sr{sup 2+}) emphasize the ionic contribution to scattering and are in reasonable agreement with experiment. In cases where an absolute calibration of the experimental data at q = 0 is available, one can extract a count of the excess number of waters and ions; computed values depend on the closure that is assumed in the solution of the Ornstein–Zernike equations, with results from the Kovalenko–Hirata closure being closest to experiment for the cases studied here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Computing the Properties of Hadrons, Nuclei, and Nuclear Matter from Quantum Chromodynamics, UNC-CH Final Report.

This is the final technical report for the UNC-CH component of a SciDAC3 project. This project served to coordinate the software development effort which the nuclear physics lattice QCD community is developing to ensure that lattice calculations can make optimal use of forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The project developed and optimized simulation software for lattice QCD calculations on leadership class computers and on GPUaccelerated heterogeneous architectures. The participating team at multiple instritutions improved and extended software libraries (Chroma, CPS, MILC, QLUA, QPhiX, QDP++, QDP-jit) by providing interfaces for heterogeneous computing environments and through the optimization of gauge field evolution algorithms and sparse matrix inverters. The former includes the development of new multi-time scale integrators and the latter focused on the development of new multi-grid and domain decomposition inverters for several QCD fermion discretization schemes. The sub-project at the University of North Carolina worked towards the development a domain specific language for lattice QCD computations with the express purpose of generating code with uncompromised performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Surrogate approximation of the Grad–Shafranov free boundary problem via stochastic collocation on sparse grids

In magnetic confinement fusion devices, the equilibrium configuration of a plasma is determined by the balance between the hydrostatic pressure in the fluid and the magnetic forces generated by an array of external coils and the plasma itself. The location of the plasma is not known a priori and must be obtained as the solution to a free boundary problem. The partial differential equation that determines the behavior of the combined magnetic field depends on a set of physical parameters (location of the coils, intensity of the electric currents going through them, magnetic permeability, etc.) that are subject to uncertainty and variability. The confinement region is in turn a function of these stochastic parameters as well. In this work, we consider variations on the current intensities running through the external coils as the dominant source of uncertainty. This leads to a parameter space of dimension equal to the number of coils in the reactor. With the aid of a surrogate function built on a sparse grid in parameter space, a Monte Carlo strategy is used to explore the effect that stochasticity in the parameters has on important features of the plasma boundary such as the location of the x-point, the strike points, and shaping attributes such as triangularity and elongation. Furthermore, the use of the surrogate function reduces the time required for the Monte Carlo simulations by factors that range between 7 and over 30.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Near-continuum, hypersonic oxygen flow over a double cone simulated by direct simulation Monte Carlo informed from quantum chemistry

A large-scale, fully resolved direct simulation Monte Carlo (DSMC) computation of a non-equilibrium, reactive flow of pure oxygen over a double cone is presented. Under the simulated near-continuum conditions, the computational demands are shown to be significant because of the wide range of length scales that must be resolved. Therefore, robust grid adaption capabilities and efficient parallelization of the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code that is utilized in this work are essential. The thermochemical and transport collision models were selected for efficiency and simplicity. First-principles data, obtained from the highly accurate direct molecular simulation method, were used to inform the collision models’ parameters. Importantly, because SPARTA implements molecular collision models using collision-specific energies, the resulting macroscopic relaxation rates were evaluated a posteriori via zero-dimensional heat bath simulations. The comparisons of surface properties, namely heat flux and pressure, show very close agreement with previous computational fluid dynamics (CFD) results. Differences with the measurements were found to be similar to the CFD simulations. The unresolved discrepancy with the measurements could be due to inconsistent free stream conditions with the actual experimental data or missing physical phenomena altogether, for example atomic and molecular oxygen electronically excited states, three-dimensional effects, or more complex gas–surface interactions. As shown in this work, the advantages of obtaining a DSMC particle solution for these flows reside in the method's ability to be directly informed from first principles and to seamlessly describe internal energy non-equilibrium for all modes. With the advent of exascale computing and beyond, particle methods will be an increasingly important tool to verify the validity of physical assumptions in reduced-order models via fully resolved, experimental-scale simulations, down to the level of molecular-level distributions.

Mechanics↗
DOE OSTI2026

Addressing Rising Energy Demand Through Innovation

The U.S. is facing a significant increase in energy demand, driven by AI advancements, the rapid expansion of data centers, manufacturing and industrial growth, and the electrification of transportation and buildings. Buildings alone account for approximately 75% of U.S. electricity consumption and 40% of total energy use. To address these challenges, NLR leverages its state-of-the-art research facilities, advanced energy modeling, hardware-in-the-loop emulation, and real-world demonstrations to provide data-driven insights that de-risk emerging energy solutions, increase efficiency and demand flexibility, optimize grid controls, and identify vulnerabilities to enhance energy security. This presentation will highlight our research ecosystem and its role in supporting a more reliable, affordable, and adaptive energy infrastructure in the face of accelerating demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

A paraboloid fitting technique for calculating curvature from piecewise-linear interface reconstructions on 3D unstructured meshes

In this work, we present a novel method for calculating interface curvature on 3D unstructured meshes from piecewise-linear interface reconstructions typically generated in the volume of fluid method. Interface curvature is a necessary quantity to calculate in order to model surface tension driven flow. Curvature needs only to be computed in cells containing an interface. The approach requires a stencil containing only neighbors sharing a node with a target cell, and calculates curvature from a least-squares paraboloid fit to the interface reconstructions. This involves solving a 6 × 6 symmetric linear system in each mixed cell. We present verification tests where we calculate the curvature of a sphere, an ellipsoid, and a sinusoid in a 3D domain on regular Cartesian meshes, distorted hex meshes, and tetrahedral meshes. Lastly, for both regular and unstructured meshes, we find in all cases the paraboloid fitting method for curvature to converge between first and second order with grid refinement.

97 MATHEMATICS AND COMPUTING↗