Search NASA⌕ Search

SEARCH · Search NASA

Results for “grid code”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,603 records · Page 89

Calculated covariance matrices for fission product yields using BeoH

Fission product yields (FPY) are important for a variety of applications (reactor neutronics, spent fuel, dosimetry, radiochemistry, etc.) and are currently included in many of the evaluated libraries around the world. The FPYs in the current US evaluation, ENDF/B-VIII.0, are mainly based on the 1994 evaluation of England and Rider and have only had slight updates—such as the inclusion of a 2 MeV point for 239 Pu—since their development. Additionally, only mean values and uncertainties are included in the evaluation, not full correlations. Los Alamos National Laboratory, in collaboration with several other institutes, has been working on an updated evaluation for the FPYs of 239 Pu(n,f), 235 U(n,f), 238 U(n,f), and 252 Cf(sf) using the deterministic, Hauser-Feshbach, fission fragment decay code, BeoH. BeoH calculates the FPYs consistently with many other prompt and delayed fission observables, explicitly taking into account multi-chance fission and ensuring consistency between observables. In addition to providing updated means and uncertainties for the FPYs on a pointwise energy grid from thermal to 20 MeV, we calculate correlations between all FPYs at each incident energy and across incident energies. Here, we discuss the development of these covariance matrices, differences in the correlations between FPYs based on the parameters that are included in the model optimization, and correlations across incident energies for neutron-induced fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Full wave modeling of radio-frequency beams in tokamaks in the electron cyclotron frequency range

Simulation of full wave, without paraxial approximation, high-resolution solution of wave equations in frequency domain in the electron cyclotron resonance (ECR) frequency range for realistic Tokamak plasma parameters became possible by using recently formulated hybrid iterative algorithm [Svidzinski et al., Phys. Plasmas 25, 082509 (2018)] for numerically solving discretized wave equations. This approach combines time evolution and iterative relaxation techniques into iteration cycles. This algorithm is implemented in 2D code FullWave, solving wave equations in Tokamaks in cold and hot plasma models, and it has been tested in 3D full wave iterative RF beams simulation tool, which is presently being developed to model 3D ECRH RF beams in fusion devices using dynamic grid adaptation. The results of 2D full wave modeling, assuming specified toroidal mode number, of ECRH RF beams in DIII-D plasma, performed in the cold and hot plasma models for outboard and top launch scenarios using FullWave are presented. Nonlocal hot plasma response model, based on accurate numerical solution of linearized Vlasov equation, is used to model beam propagation and absorption in the 2nd electron cyclotron harmonic region. Demonstration of capability of the hybrid iterative algorithm to model ECRH RF beams in 3D is made by simulating a substantial part of realistic beam in DIII-D, launched from outboard side of the machine. All relevant physics of RF beam propagation, most of which is not captured in paraxial approximation, such as beam's divergence, interference between the X and O modes in the beam, X-O mode conversion, beam splitting into the X and O mode beams, transformation of beam's cross section, and absorption at the 2nd electron cyclotron harmonic, is captured in the simulations. A numerical technique to find an optimal beam polarization at the launcher to launch a nearly pure X or O mode beam in plasma is developed and tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This data record spans from 1981 to 2024 using data from NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18, -19 and S-NPP. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗

Model verification studies using accurate measurements of spin up

The reliability and accuracy of the numerical code for spin up flows in a cylinder by comparing the numerical results against high resolution laser Doppler velocimeter (LDV) measurements of the azimuthal flows were checked. A computer code to generate numerical solution for axisymmetric rotating fluid in a cylinder was obtained and amended for routine use at MSFC. The numerical simulations used the Navier-Stokes equations in axisymmetric form and employed finite difference techniques on both constant and variable grids. The numerical solutions are analyzed to gain further insight into the fundamental questions analyzed in rotating fluid dynamics.

Hyun, J. M.↗

An approximate Riemann solver for magnetohydrodynamics (that works in more than one dimension)

An approximate Riemann solver is developed for the governing equations of ideal magnetohydrodynamics (MHD). The Riemann solver has an eight-wave structure, where seven of the waves are those used in previous work on upwind schemes for MHD, and the eighth wave is related to the divergence of the magnetic field. The structure of the eighth wave is not immediately obvious from the governing equations as they are usually written, but arises from a modification of the equations that is presented in this paper. The addition of the eighth wave allows multidimensional MHD problems to be solved without the use of staggered grids or a projection scheme, one or the other of which was necessary in previous work on upwind schemes for MHD. A test problem made up of a shock tube with rotated initial conditions is solved to show that the two-dimensional code yields answers consistent with the one-dimensional methods developed previously.

Powell, Kenneth G.↗

Investigation of Advanced Counterrotation Blade Configuration Concepts for High Speed Turboprop Systems. Task 8: Cooling Flow/heat Transfer Analysis

The focus of this task was to validate the ADPAC code for heat transfer calculations. To accomplish this goal, the ADPAC code was modified to allow for a Cartesian coordinate system capability and to add boundary conditions to handle spanwise periodicity and transpiration boundaries. The primary validation case was the film cooled C3X vane. The cooling hole modeling included both a porous region and grid in each discrete hold. Predictions for these models as well as smooth wall compared well with the experimental data.

Hall, Edward J.↗

Convective Heat Transfer in the Reusable Solid Rocket Motor of the Space Transportation System

This simulation involved a two-dimensional axisymmetric model of a full motor initial grain of the Reusable Solid Rocket Motor (RSRM) of the Space Transportation System (STS). It was conducted with CFD (computational fluid dynamics) commercial code FLUENT. This analysis was performed to: a) maintain continuity with most related previous analyses, b) serve as a non-vectored baseline for any three-dimensional vectored nozzles, c) provide a relatively simple application and checkout for various CFD solution schemes, grid sensitivity studies, turbulence modeling and heat transfer, and d) calculate nozzle convective heat transfer coefficients. The accuracy of the present results and the selection of the numerical schemes and turbulence models were based on matching the rocket ballistic predictions of mass flow rate, head end pressure, vacuum thrust and specific impulse, and measured chamber pressure drop. Matching these ballistic predictions was found to be good. This study was limited to convective heat transfer and the results compared favorably with existing theory. On the other hand, qualitative comparison with backed-out data of the ratio of the convective heat transfer coefficient to the specific heat at constant pressure was made in a relative manner. This backed-out data was devised to match nozzle erosion that was a result of heat transfer (convective, radiative and conductive), chemical (transpirating), and mechanical (shear and particle impingement forces) effects combined.

Ahmad, Rashid A.↗

LSPRAY-II: A Lagrangian Spray Module

LSPRAY-II is a Lagrangian spray solver developed for application with parallel computing and unstructured grids. It is designed to be massively parallel and could easily be coupled with any existing gas-phase flow and/or Monte Carlo Probability Density Function (PDF) solvers. The solver accommodates the use of an unstructured mesh with mixed elements of either triangular, quadrilateral, and/or tetrahedral type for the gas flow grid representation. It is mainly designed to predict the flow, thermal and transport properties of a rapidly vaporizing spray because of its importance in aerospace application. The manual provides the user with an understanding of various models involved in the spray formulation, its code structure and solution algorithm, and various other issues related to parallelization and its coupling with other solvers. With the development of LSPRAY-II, we have advanced the state-of-the-art in spray computations in several important ways.

Raju, M. S.↗

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗

LSPRAY-III: A Lagrangian Spray Module

LSPRAY-III is a Lagrangian spray solver developed for application with parallel computing and unstructured grids. It is designed to be massively parallel and could easily be coupled with any existing gas-phase flow and/or Monte Carlo Probability Density Function (PDF) solvers. The solver accommodates the use of an unstructured mesh with mixed elements of either triangular, quadrilateral, and/or tetrahedral type for the gas flow grid representation. It is mainly designed to predict the flow, thermal and transport properties of a rapidly vaporizing spray because of its importance in aerospace application. The manual provides the user with an understanding of various models involved in the spray formulation, its code structure and solution algorithm, and various other issues related to parallelization and its coupling with other solvers. With the development of LSPRAY-III, we have advanced the state-of-the-art in spray computations in several important ways.

Raju, M. S.↗

FUN3D Airload Predictions for the Full-Scale UH-60A Airloads Rotor in a Wind Tunnel

An unsteady Reynolds-Averaged Navier-Stokes solver for unstructured grids, FUN3D, is used to compute the rotor performance and airloads of the UH-60A Airloads Rotor in the National Full-Scale Aerodynamic Complex (NFAC) 40- by 80-foot Wind Tunnel. The flow solver is loosely coupled to a rotorcraft comprehensive code, CAMRAD-II, to account for trim and aeroelastic deflections. Computations are made for the 1-g level flight speed-sweep test conditions with the airloads rotor installed on the NFAC Large Rotor Test Apparatus (LRTA) and in the 40- by 80-ft wind tunnel to determine the influence of the test stand and wind-tunnel walls on the rotor performance and airloads. Detailed comparisons are made between the results of the CFD/CSD simulations and the wind tunnel measurements. The computed trends in solidity-weighted propulsive force and power coefficient match the experimental trends over the range of advance ratios and are comparable to previously published results. Rotor performance and sectional airloads show little sensitivity to the modeling of the wind-tunnel walls, which indicates that the rotor shaft-angle correction adequately compensates for the wall influence up to an advance ratio of 0.37. Sensitivity of the rotor performance and sectional airloads to the modeling of the rotor with the LRTA body/hub increases with advance ratio. The inclusion of the LRTA in the simulation slightly improves the comparison of rotor propulsive force between the computation and wind tunnel data but does not resolve the difference in the rotor power predictions at mu = 0.37. Despite a more precise knowledge of the rotor trim loads and flight condition, the level of comparison between the computed and measured sectional airloads/pressures at an advance ratio of 0.37 is comparable to the results previously published for the high-speed flight test condition.

Lee-Rausch, Elizabeth M.↗

Jitter Controller Software

Sinusoidal jitter is produced by simply modulating a clock frequency sinusoidally with a given frequency and amplitude. But this can be expressed as phase jitter, frequency jitter, or cycle-to-cycle jitter, rms or peak, absolute units, or normalized to the base clock frequency. Jitter using other waveforms requires calculating and downloading these waveforms to an arbitrary waveform generator, and helping the user manage relationships among phase jitter crest factor, frequency jitter crest factor, and cycle-to-cycle jitter (CCJ) crest factor. Software was developed for managing these relationships, automatically configuring the generator, and saving test results documentation. Tighter management of clock jitter and jitter sensitivity is required by new codes that further extend the already high performance of space communication links, completely correcting symbol error rates higher than 10 percent, and therefore typically requiring demodulation and symbol synchronization hardware to operating at signal-to-noise ratios of less than one. To accomplish this, greater demands are also made on transmitter performance, and measurement techniques are needed to confirm performance. It was discovered early that sinusoidal jitter can be stepped on a grid such that one can connect points by constant phase jitter, constant frequency jitter, or constant cycle-cycle jitter. The tool automates adherence to a grid while also allowing adjustments off-grid. Also, the jitter can be set by the user on any dimension and the others are calculated. The calculations are all recorded, allowing the data to be rapidly plotted or re-plotted against different interpretations just by changing pointers to columns. A key advantage is taking data on a carefully controlled grid, which allowed a single data set to be post-analyzed many different ways. Another innovation was building a software tool to provide very tight coupling between the generator and the recorded data product, and the operator's worksheet. Together, these allowed the operator to sweep the jitter stimulus quickly along any of three dimensions and focus on the response of the system under test (response was jitter transfer ratio, or performance degradation to the symbol or codeword error rate). Additionally, managing multi-tone and noise waveforms automated a tedious manual process, and provided almost instantaneous decision- making control over test flow. The code was written in LabVIEW, and calls Agilent instrument drivers to write to the generator hardware.

Lansdowne, Chatwin↗

HANA - A three-dimensional Navier-Stokes code for chemically reacting flows

A recently developed computer program for analyzing chemically reacting flows is described. The program uses a diagonal implicit algorithm to solve the equations of viscous flow for a gas in thermochemical nonequilibrium. The diagonal scheme eliminates the expense of inverting large block matrices that arise when species conservation equations are introduced. The program uses multiple zones of grids patched together and includes a k-epsilon turbulence model. Solutions are presented for hypersonic flows of air, hypersonic flows of Martian atmospheric gases, combusting flows of hydrogen/air mixtures, and combusting flows of methane/air mixtures.

Imlay, Scott T.↗

Algebraic grid generation with control points

The control-point form (CPF) formulation is an algebraically defined class of coordinate transformations by means of which the interior form of the coordinates can be manipulated in the local fashion, and any boundary can be either specified or manipulated in a similar manner. Currently, the most intense activity involving CPF is with such graphic interactive codes as TurboI and TurboT, for which detailed illustrative examples are given; these have furnished experience on whose basis future interactive strategies can be developed.

Eiseman, Peter R.↗

Characterizing peak electricity demand for U.S. households: an assessment of end-use loads and demand factors

Understanding household peak electricity demand is critical to evaluate the technical need for electrical infrastructure upgrades. This study characterizes peak loads for existing and new equipment using metered data from a convenience sample of 11,940 U.S. dwellings from four sources, including 911 from two sources with end-use metering. After standardized data cleaning and labeling, we derived descriptive statistics for key metrics, such as maximum demand and demand factors, and developed predictive models relating 60- to 15-min demand for the National Electrical Code (NEC). Mean 15-min maximum demand was 9.7 kW (median 9.0 kW; IQR 7.0–11.5 kW, 95% CI 9.6–9.8 kW), indicating spare capacity in 98% of homes with hypothetical 100 A panels. Maximum demand increased with floor area and number of high-demand loads. Dwelling maximum demand was driven by higher-power, longer-duration heating appliances and vehicle charging, while most user-operated appliances contributed little. Demand factors are used to account for how most devices contribute less than their rated power to maximum demand. Existing load mean demand factors (28%; median 10%; IQR 0–58%; CI 28–29%) were higher than those for new loads (21%; median 7%; IQR 0–35%; CI 20–21%), because new loads changed the timing and magnitude of maximum demand. New high-demand loads had higher than average demand factors (40–60%). Whole dwelling demand factors support the NEC's 40% assumption, but they challenge its conservative 100% treatment of new HVAC. We propose a data-driven 50% demand factor for new equipment, which would align with metered data, improve affordability, and modernize electrical codes.

Appliances↗

Aeroelasticity Benchmark Assessment: Subsonic Fixed Wing Program

The fundamental technical challenge in computational aeroelasticity is the accurate prediction of unsteady aerodynamic phenomena and the effect on the aeroelastic response of a vehicle. Currently, a benchmarking standard for use in validating the accuracy of computational aeroelasticity codes does not exist. Many aeroelastic data sets have been obtained in wind-tunnel and flight testing throughout the world; however, none have been globally presented or accepted as an ideal data set. There are numerous reasons for this. One reason is that often, such aeroelastic data sets focus on the aeroelastic phenomena alone (flutter, for example) and do not contain associated information such as unsteady pressures and time-correlated structural dynamic deflections. Other available data sets focus solely on the unsteady pressures and do not address the aeroelastic phenomena. Other discrepancies can include omission of relevant data, such as flutter frequency and / or the acquisition of only qualitative deflection data. In addition to these content deficiencies, all of the available data sets present both experimental and computational technical challenges. Experimental issues include facility influences, nonlinearities beyond those being modeled, and data processing. From the computational perspective, technical challenges include modeling geometric complexities, coupling between the flow and the structure, grid issues, and boundary conditions. The Aeroelasticity Benchmark Assessment task seeks to examine the existing potential experimental data sets and ultimately choose the one that is viewed as the most suitable for computational benchmarking. An initial computational evaluation of that configuration will then be performed using the Langley-developed computational fluid dynamics (CFD) software FUN3D1 as part of its code validation process. In addition to the benchmarking activity, this task also includes an examination of future research directions. Researchers within the Aeroelasticity Branch will examine other experimental efforts within the Subsonic Fixed Wing (SFW) program (such as testing of the NASA Common Research Model (CRM)) and other NASA programs and assess aeroelasticity issues and research topics.

Florance, Jennifer P.↗

Overshadow PLC to Detect Remote Control-Logic Injection Attacks

Programmable logic controllers (PLCs) in industrial control systems (ICS) are vulnerable to remote control logic injection attacks. Attackers target the control logic of a PLC to manipulate the behavior of a physical process such as nuclear plants, power grids, and gas pipelines. Control logic attacks have been studied extensively in the literature, including hiding the transfer of a control logic over the network from both packet header-based signatures, and deep packet inspection. For instance, these attacks transfer a control logic code as data, into small fragments (one-byte per packet), that are further padded with noise data. To detect control logic in ICS network traffic, this paper presents Shade, a novel shadow memory technique that observes the network traffic to maintain a local copy of the current state of a PLC memory. To analyze the memory contents, Shade employs a classification algorithm with 42 unique features categorized into five types at different semantic levels of a control logic code, such as number of rungs, number of consecutive decompiled instructions, and n-grams. We then evaluate Shade against control logic injection attacks on two PLCs, Modicon M221 and MicroLogix 1400 from two ICS vendors, Schneider electric and Allen-Bradley, respectively. The evaluation results show that Shade can detect an attack instance (i.e., identifying at least one attack packet during the transfer of a malicious control logic) accurately without any false alarms.

Yoo, Hyunguk↗

FDTD: Solving 1+1D delay PDE in parallel

We present a proof of concept for solving a 1+1D complex-valued, delay partial differential equation (PDE) that emerges in the study of waveguide quantum electrodynamics (QED) by adapting the finite-difference time-domain (FDTD) method. The delay term is spatially non-local, rendering conventional approaches such as the method of lines inapplicable. Here, we show that by properly designing the grid and by supplying the (partial) exact solution as the boundary condition, the delay PDE can be numerically solved. In addition, we demonstrate that while the delay imposes strong data dependency, multi-thread parallelization can nevertheless be applied to such a problem. Our code provides a numerically exact solution to the time-dependent multi-photon scattering problem in waveguide QED.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗