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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Estimating the Value of Nuclear Integrated Hydrogen Production and the Dependency of Electricity and Hydrogen Markets on Natural Gas

Producing low carbon Hydrogen at a competitive price is one of the challenges to hydrogen being part of the solution to reach net-zero emission targets set by the U.S. DOE by 2050. With projected near-term improvements in technology, hydrogen production via solid oxide electrolysis cell (SOEC) / high-temperature steam electrolysis (HTSE) integrated with existing light water reactor (LWR) Nuclear Power Plants (NPP-HTSE) can produce carbon-free hydrogen competitively. In the near term, a 10-year production tax credit (PTC) found in the Inflation Reduction Act (IRA) has been passed, which will catalyze the development and improvement of hydrogen production technology to be competitive. The “1-1-1” target set by the U.S. DOE is to reduce the cost of carbon-free hydrogen by 80% to $1 per kilogram in 1 decade. Several models are available to analyze the profitability, opportunity, and technical capability of NPP-HTSE systems. In order of complexity from most complex to least complex some of these models include: RAVEN/HERON, process models using Aspen HYSYS and capital expense estimations using Aspen Process Economic Analyzer (APEA) and levelized cost of hydrogen (LCOH) calculation using the H2A model (Hydrogen Analysis Model), and custom spread sheets built by the interested party. Though some of the more advanced existing models provide detailed analysis to complex grid integrated problems, they also can take considerable time to setup and run. These advanced models are well suited to complex grid integrated analysis and the consideration of flexibility and variability of regulated and de-regulated electricity price and advanced estimation of capital and operating expenses and heat and material balances.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2004

Probabilistic Residual Strength Model Developed for Life Prediction of Ceramic Matrix Composites

For the next generation of reusable launch vehicles, NASA is investigating introducing ceramic matrix composites (CMCs) in place of current superalloys for structural propulsion applications (e.g., nozzles, vanes, combustors, and heat exchangers). The higher use temperatures of CMCs will reduce vehicle weight by eliminating and/or reducing cooling system requirements. The increased strength-to-weight ratio of CMCs relative to superalloys further enhances their weight savings potential. However, in order to provide safe designs for components made of these new materials, a comprehensive life prediction methodology for CMC structures needs to be developed. A robust methodology for lifing composite structures has yet to be adopted by the engineering community. Current industry design practice continues to utilize deterministic empirically based models borrowed from metals design for predicting material life capabilities. The deterministic nature of these models inadequately addresses the stochastic character of brittle composites, and their empirical reliance makes predictions beyond the experimental test conditions a risky extrapolation. A team of engineers at the NASA Glenn Research Center has been developing a new life prediction engineering model. The Probabilistic Residual Strength (PRS) model uses the residual strength of the composite as its damage metric. Expected life and material strength are both considered probabilistically to account for the observed stochastic material response. Extensive experimental testing has been carried out on C/SiC (a candidate aerospace CMC material system) in a controlled 1000 ppm O2/argon environment at elevated temperatures of 800 and 1200 C. The test matrix was established to allow observation of the material behavior, characterization of the model, and validation of the model's predictive capabilities. Sample results of the validation study are illustrated in the graphs.

Thomas, David J.↗
NASA NTRS1998

Refraction of Sound Emitted Near Solid Boundaries from a Sheared Jet

A mathematical model is developed to describe the sound emitted from an arbitrary point within a turbulent flow near solid boundaries. A unidirectional, transversely sheared mean flow is assumed, and the cross-section of the cold jet is of arbitrary shape. The analysis begins with Lilley's formulation of aerodynamic noise and, depending upon the specific model of turbulence used, leads via Fourier analysis to an expression for the spectral density of the intensity of the far-field sound emitted from a unit volume of turbulence. The expressions require solution of a reduced Green's function of Lilley's equation as well as certain moving axis velocity correlations of the turbulence. Integration over the entire flow field is required in order to predict the sound emitted by the complete flow. Calculations are presented for sound emitted from a plugflow jet exiting a semi-infinite flat duct. Polar plots of the far-field directivity show the dependence upon frequency and source position within the duct. Certain model problems are suggested to investigate the effect of duct termination, duct geometry, and mean flow shear upon the far-field sound.

Dill, Loren H.↗
DOE OSTI2020

LA17-V-InverseRadTransportProblem-PD2Kb. Final Project Report

In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2013

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.↗
NASA NTRS2015

Reducing the Effect of Transducer Mount Induced Noise on Aeroacoustic Wind Tunnel Testing Data with a New Transducer Mount Design

Characterization of launch vehicle unsteady aerodynamics is a field best studied through experimentation, which is often carried out in the form of large scale wind tunnel testing. Measurement of the fluctuating pressures induced by the boundary layer noise is customarily made with miniature pressure transducers installed into a model of the vehicle of interest. Literature shows that noise level increases between two to five decibels (dB referenced to 20 micropascal) can be induced when the transducer surface is not mounted perfectly flush with the model outer surface. To reduce this artificially induced noise, special transducer holders have been used for aeroacoustic wind tunnel testing by NASA. This holder is a sleeve into which the transducer fits, with a cap that allows it to be mounted in a recessed hole in the model. A single hole in the holder allows the transport of the tunnel medium so the transducer can discriminate the fluctuating pressure due to the turbulent boundary layer noise. The holder is first dry fitted into the model and any difference in height between the holder and the model surface can be sanded flush. The holder is then removed from the model, the transducer glued inside the holder, and the holder replaced in the model, secured also with glue, thus eliminating the problem of noise level increases due to lack of flushness. In order to work with this holder design, special transducers have been ordered with their standard screen removed and the diaphragm moved as close to the top of the casing as possible to minimize any cavity volume. Although this greatly reduces induced noise due to the transducers being out of flush, the holders can also induce a cavity resonance that is usually at a very high frequency. This noise is termed transducer mount induced noise (XMIN). The peak of the mode can vary with the cavity depth, boundary layer noise that can excite the mode, tunnel flow medium, and the build of the transducers. Because the boundary layer flow interaction with the microphone holder seems to have some effect on the cavity resonance response, the NASA/Marshall Space Flight Center (MSFC) aeroacoustic team postulated that changing the design of the holder might reduce the cavity resonance response. An experiment was performed at the MSFC Trisonic Wind Tunnel comparing a new holder design with the traditional MSFC holder. The new holder design is intended to mimic the Kulite Semiconductors, Inc. B-screen, where the single hole of the traditional MSFC holder is replaced by a series of ten 0.007 inch diameter holes. This particular design serves to protect the transducer diaphragm as in the manufacturer's B-screen, but also increases the frequency of the XMIN such that it is not apparent in the data collected from aeroacoustic wind tunnel tests. MSFC compared the two holder designs by installing two transducers in standard holders on one side of a ten inch long ten degree cone, and two transducers in B-screen holders on the opposite side for a series of runs at different conditions. Over 11-13 February, 2013, the model was run at Mach numbers between 0.80 and 1.96 at angles of attack at 0 deg, plus or minus 1 deg, plus or minus 2 deg, plus or minus 4 deg, and plus or minus 8 deg. Model roll attitudes at 0 deg, 90 deg, and 180 deg were tested to isolate potential tunnel bias. This paper presents results from the test showing that the proposed holder design significantly reduces the influence of XMIN on measured fluctuating pressure levels.

Herron, A. J.↗
NASA NTRS1994

The energetics of Titan's ionosphere

We have developed a comprehensive model to study the dynamics and energetics of the ionosphere of Titan. We solved the one-dimensional, time-dependent, coupled continuity and momentum equations for several ion species, together with single ion and electron energy equations, in order to calculate density, velocity, and temperature profiles. Calculations were carried out for several cases corresponding to different local times and configurations of the Titan-Saturn system. In our model the effects of horizontal magnetic fields were assumed to be negligible, except for their effect on reducing the electron and ion thermal conductivities and inhibiting vertical transport in the subram region. The ionospheric density peak was found to be at an altitude of about 1100 km, in accordance with earlier model calculations. The ionosphere is chemically controlled below an altitude of about 1500 km. Above this level, ion densities differ significantly from their chemical equilibrium values due to strong upward ion velocities. Heat is deposited in a narrow region around the ionospheric peak, resulting in temperature profiles increasing sharply and reaching nearly constant values of 800-1000 deg K for electrons and 300 deg K for ions in the topside, assuming conditions appropriate for the wake region. In the subram region magnetic correction factors make the electron heat conductivities negligible, resulting in electron temperatures increasing strongly with altitude and reaching values in the order of 5000 deg K at our upper boundary located at 2200 km. Ion chemical heating is found to play an important role in shaping the ion energy balance in Titan's ionosphere.

Roboz, A.↗
DOE OSTI2023

Electronic structure, magnetic properties, spin orientation, and doping effect in Mn 3 Si 2 Te 6

The layered material Mn 3 Si 2 Te 6 , with alternating stacking honeycomb and triangular layers, is attracting considerable attention due to its rich physical properties. Here, in this study, using density functional theory and classical Monte Carlo (MC) methods, we systematically study this system with the 3d 5 electronic configuration. Near the Fermi level, the states are mainly contributed by Te 5p orbitals hybridized with Mn 3d orbitals, resembling a charge-transfer system. Furthermore, the spin orientations of the ferrimagnetic (FiM) ground state display different conductive behaviors when along the ab plane or out-of-plane directions: insulating vs metallic states. The energy difference between the FiM [110] insulating and FiM [001] metallic phases is very small (~0.71 meV/Mn) . Changing the angle θ of spin orientation from in-plane to out-of-plane directions, the band gaps of this system are gradually reduced, leading to an insulator-metal transition, resulting in an enhanced electrical conductivity, related to the colossal angular magnetoresistance (MR) effect. Although the three main magnetic couplings were found to be antiferromagnetic, overall the ground state is FiM. In addition, we also constructed the magnetic phase diagram using the classical XY spin model studied with the MC method. Three magnetic phases were obtained, including antiferromagnetic order, noncollinear spin patterns, and FiM order. Moreover, we also investigated the Se and Ge doping into the Mn 3 Si 2 Te 6 system: the FiM state has the lowest energy among the magnetic candidates for both Se- and Ge-doped cases. The magnetic anisotropy energy (MAE) decreases in the Se-doped case because the Mn orbital moment is reduced as the doping x increases. Due to the small spin-orbit-coupling effect of Se, the insulator-metal transition caused by the spin orientation disappears in the Se-doped case, resulting in an insulating phase in the FiM [001] phase. This causes a reduced colossal angular MR. However, both the MAE and the band gap of the Ge-doped case do not change much with increasing doping x . Our results for Mn 3 Si 2 Te 6 could provide guidance to experimentalists and theorists working on this system or related materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1998

Simulation of Ultra-Small MOSFETs Using a 2-D Quantum-Corrected Drift-Diffusion Model

The continued down-scaling of electronic devices, in particular the commercially dominant MOSFET, will force a fundamental change in the process of new electronics technology development in the next five to ten years. The cost of developing new technology generations is soaring along with the price of new fabrication facilities, even as competitive pressure intensifies to bring this new technology to market faster than ever before. To reduce cost and time to market, device simulation must become a more fundamental, indeed dominant, part of the technology development cycle. In order to produce these benefits, simulation accuracy must improve markedly. At the same time, device physics will become more complex, with the rapid increase in various small-geometry and quantum effects. This work describes both an approach to device simulator development and a physical model which advance the effort to meet the tremendous electronic device simulation challenge described above. The device simulation approach is to specify the physical model at a high level to a general-purpose (but highly efficient) partial differential equation solver (in this case PROPHET, developed by Lucent Technologies), which then simulates the model in 1-D, 2-D, or 3-D for a specified device and test regime. This approach allows for the rapid investigation of a wide range of device models and effects, which is certainly essential for device simulation to catch up with, and then stay ahead of, electronic device technology of the present and future. The physical device model used in this work is the density-gradient (DG) quantum correction to the drift-diffusion model [Ancona, Phys. Rev. B 35(5), 7959 (1987)]. This model adds tunneling and quantum smoothing of carrier density profiles to the drift-diffusion model. We used the DG model in 1-D and 2-D (for the first time) to simulate both bipolar and unipolar devices. Simulations of heavily-doped, short-base diodes indicated that the DG quantum corrections do not have a large effect on the IN characteristics of electronic devices without heteroj unction s. On the other hand, ultra-small MOSFETs certainly exhibit important quantum effects that the DG model will include: quantum repulsion of the inversion and gate charges from the oxide interfaces, and quantum tunneling through thin gate oxides. We present initial results of 2-D DG simulations of ultra-small MOSFETs. Subtle but important issues involving the specification of the model, boundary conditions, and interface constraints for DG simulation of MOSFETs will also be illuminated.

Biegal, Bryan A.↗
DOE OSTI2020

Sparse thermal data for cellular automata modeling of grain structure in additive manufacturing

Grain growth in the wake of the melt pool formed during alloy-based additive manufacturing (AM) is complex and multifaceted, depending on parameters governing heat transport, fluid flow, and solidification itself. Cellular automata (CA) models have proven effective in providing computationally efficient and physically sound predictions of grain structure for several AM problems, but their efficiency is tied to the performance of heat transport models. CA models use only a small portion of the problem's temperature data (near the moving melt pool boundary), and much of the CA calculations do not affect the final result due to re-melting of material. Coupling of and communication between heat transport and solidification models, and eliminating operations irrelevant towards final grain structure prediction, will be necessary for using these methods for efficient simulation of large parts. In this work, we introduce a procedure of decoupling the CA from temperature field simulation, using files of relevant temperature data written by the heat transport model. This approach is validated against the standard coupling approach using data obtained through the computational fluid dynamics software OpenFOAM. Negligible differences are seen in grain size, volume, and texture distributions for multilayer simulation of test problems, while the quantity of temperature data for these test problems was reduced by four orders of magnitude (from 100s of GB to 10s of MB) and the code performance sped up by a factor of around 50. Furthermore, variability in microstructure as a function of cell size, substrate, time step, and nucleation parameters is studied, and it is found that cell sizes less than or equal to 1.67 μm and sufficiently small time steps yield Αstatistically equivalent microstructures. Finally, a potential use case for this CA approach—the layer-wise convergence in grain structure starting from extremes in initial grain size—is examined. This approach's ability to simulate expected trends in nucleation and epitaxial grain growth for large regions of microstructure, simulated independently of heat transport models themselves, should prove useful for investigation of various microstructure uncertainties and prediction of part-scale experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling protected species distributions and habitats to inform siting and management of pioneering ocean industries: A case study for Gulf of Mexico aquaculture

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine [Slides]

In this work we present a novel deep learning-based downscaling method, using generative adversarial networks (GANs), for generating high-resolution wind resource data from ECMWF Reanalysis v5 data (ERA5). We show that by training a GAN model on ERA5, as opposed to coarsened high-resolution data, we achieve results that are competitive with conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. All GANs are trained on data sampled from CONUS, selected to provide a diverse sampling of terrain conditions, and validated on observational data along with data held out from training. This cross-validation shows low error and high correlations with observations and excellent agreement with hold out data across physical distributions. Our approach is finally used to downscale 30km hourly ERA5 to 2-km 5-minute wind data, for January 2000 through December 2023, at multiple hub heights, over Ukraine, Moldova, and part of Romania. Comparisons against observational data from Meteorological Assimilation Data Ingest System (MADIS) and multiple wind farms show the same level of performance as for CONUS validation. This 24 year data record is the first member of the "super resolution for renewable energy resource data with wind from reanalysis data" dataset (Sup3rWind).

17 WIND ENERGY↗
DOE OSTI2024

Optimization of Membrane-based Carbon Capture using Dimensional Analysis, CFD and Process System Engineering

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibil-ity and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability.To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2020

Concrete Structure Health Monitoring Using Vibro-acoustic Testing and Machine Learning

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

High speed turboprops for executive aircraft, potential and recent test results

Four high speed propeller models were designed and tested in an 8x6 foot wind tunnel in order to evaluate the potential of advanced propeller technology. Results from these tests show that the combination of: increased blade number, aerodynamically integrated propeller/nacelles, reduced blade thickness, spinner area ruling, and blade sweep are important in achieving high propeller efficiency at the high cruise speeds.

Mikkelson, D. C.↗
NASA NTRS1987

Summary of paper: Area navigation implementation for a microcomputer-based Loran-C receiver

The development of an area navigation program and the implementation of this software on a microcomputer-based Loran-C receiver to provide high-quality, practical area navigation information for general aviation are described. This software provides range and bearing angle to a selected waypoint, cross-track error, course deviation indication (CDI), ground speed, and estimated time of arrival at the waypoint. The range/bearing calculation, using an elliptical Earth model, provides very good accuracy; the error does not exceed more than -.012 nm (range) or 0.09 degree (bearing) for a maximum range to 530 nm. The alpha-beta filtering is applied in order to reduce the random noise on Loran-C raw data and in the ground speed calculation. Due to alpha-beta filtering, the ground speed calculation has good stability for constant or low-accelerative flight. The execution time of this software is approximately 0.2 second. Flight testing was done with a prototype Loran-C front-end receiver, with the Loran-C area navigation software demonstrating the ability to provide navigation for the pilot to any point in the Loran-C coverage area in true area navigation fashion without line-of-sight and range restriction typical of VOR area navigation.

Oguri, Fujiko↗
NASA NTRS1987

Simplified solution for a class of fading memory filters

A fading memory filter is a least squares estimator (LSE) that applies an exponentially decaying weight to past measurements. When compared with a standard Kalman filter, its key advantages are asymptotic stability and reduced sensitivity to modeling errors. This paper derives a simple solution for a class of fading memory filters, resulting in a reduction in computational complexity. Steady state filter solutions are obtained for second- and third-order filters used in a global positioning system (GPS) receiver for high dynamic vehicles.

Statman, Joseph I.↗
NASA NTRS1989

Flutter suppression control law synthesis for the Active Flexible Wing model

The Active Flexible Wing Project is a collaborative effort between the NASA Langley Research Center and Rockwell International. The objectives are the validation of methodologies associated with mathematical modeling, flutter suppression control law development and digital implementation of the control system for application to flexible aircraft. A flutter suppression control law synthesis for this project is described. The state-space mathematical model used for the synthesis included ten flexible modes, four control surface modes and rational function approximation of the doublet-lattice unsteady aerodynamics. The design steps involved developing the full-order optimal control laws, reducing the order of the control law, and optimizing the reduced-order control law in both the continuous and the discrete domains to minimize stochastic response. System robustness was improved using singular value constraints. An 8th order robust control law was designed to increase the symmetric flutter dynamic pressure by 100 percent. Preliminary results are provided and experiences gained are discussed.

Mukhopadhyay, Vivek↗