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NASA NTRS1979

The effect of nonuniform wind shear on the intensification and reflection of mountain waves

A study is made of the intensification and reflection of mountain waves when the shear of the basic wind profile is nonuniform. A two-layer atmospheric model is treated, and the wind profile in the troposphere is assumed to be parabolic. The Scorer parameter includes the wind profile curvature term, which may not be neglected if the Richardson number Ri is finite. When Ri is finite, the optimal phase difference across the troposphere for maximum surface velocity intensifications is found to be slightly greater than Pi. As Ri increases, the optimal phase difference decreases with Ri and approaches the limiting value Pi. This implies that waves approximately reverse phase between the surface and the tropopause for maximum wave intensifications in most physically realistic atmospheric situations. The concept of Eliassen and Palm concerning the additivity of the vertical wave energy fluxes is expanded (valid at least up to the parabolic wind profile), by which the upward and downward energy transporting modes are identified.

Hyun, J. M.↗

NASA NTRS2003

Thermal and Chemical Characterization of Composite Materials. MSFC Center Director's Discretionary Fund Final Report, Project No. ED36-18

The purpose of this research effort was to: (1) provide a concise and well-defined property profile of current and developing composite materials using thermal and chemical characterization techniques and (2) optimize analytical testing requirements of materials. This effort applied a diverse array of methodologies to ascertain composite material properties. Often, a single method of technique will provide useful, but nonetheless incomplete, information on material composition and/or behavior. To more completely understand and predict material properties, a broad-based analytical approach is required. By developing a database of information comprised of both thermal and chemical properties, material behavior under varying conditions may be better understood. THis is even more important in the aerospace community, where new composite materials and those in the development stage have little reference data. For example, Fourier transform infrared (FTIR) spectroscopy spectral databases available for identification of vapor phase spectra, such as those generated during experiments, generally refer to well-defined chemical compounds. Because this method renders a unique thermal decomposition spectral pattern, even larger, more diverse databases, such as those found in solid and liquid phase FTIR spectroscopy libraries, cannot be used. By combining this and other available methodologies, a database specifically for new materials and materials being developed at Marshall Space Flight Center can be generated . In addition, characterizing materials using this approach will be extremely useful in the verification of materials and identification of anomalies in NASA-wide investigations.

Stanley, D. C.↗

NASA NTRS2006

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

soil↗

NASA NTRSDate not supplied

Comparison Between DSMC and CFD for Hypersonic Planetary Entry Simulations

Hypersonic planetary entry flows span a wide range of Knudsen numbers between rarefied and continuum flows. While computational fluid dynamics (CFD) techniques cannot provide an accurate solution for flows in the rarefied regime, the direct simulation Monte Carlo (DSMC) method is capable of providing accurate solutions for flows in both in the rarefied and continuum regimes but becomes prohibitively expensive as the Knudsen number decreases. For the purpose of thermal protection systems (TPS) design and post-flight reconstruction, various selected points along an entry trajectory are often solved using hypersonic solvers. The quantities of interest that are obtained from that exercise are generally surface quantities, such as pressure, heat flux and enthalpy. Then, material response solvers are used to either design the heat shield to an optimal thickness based on a choice of material, or to provide in-depth heating profiles through the material at various select locations, and compare with flight instrumentation such as the ones that flew on NASA’s two most recent Mars missions, MSL and Mars2020. While most of the heating is generally experienced during the continuum part of the entry, the heating within the rarefied regime is significant for some atmospheres, and hence the flow solutions need to be computed using the DSMC method. Ensuring consistency between hypersonic CFD and the DSMC is crucial so that reliable surface quantities can be passed to material response solvers. Studies were performed to compare the two methods at various select locations, for both non-reacting argon flows as well reacting CO2/N2 flows. Preliminary conclusions show that, for non-reacting flows, the agreement between the two methods for surface heating is excellent (within expected uncertainties) for a freestream Knudsen number of 0.0006, and gets progressively worse as the Knudsen number increases to 0.06. Continuum breakdown analyses were performed and showed that, in general, the Gradient Length Local Knudsen number (KnGLL) from Boyd [1] and associated criteria (KnGLL > 0.05) can be accurately used to predict zones of breakdown in the flow, and associated errors for surface quantities. Furthermore, when studying reacting flow, our studies showed that while flow quantities are highly dependent on relaxation parameters and chemistry rates, it is possible to obtain a good agreement for surface heating, as long as the continuum breakdown in minimal (see Fig. 1). Finally, we studied the impact of the grid refinement on the surface quantities in DSMC.

DSMC↗

NASA NTRSDate not supplied

Comparison Between DSMC and CFD for Hypersonic Planetary Entry Simulations

Hypersonic planetary entry flows span a wide range of Knudsen numbers between rarefied and continuum flows. While computational fluid dynamics (CFD) techniques cannot provide an accurate solution for flows in the rarefied regime, the direct simulation Monte Carlo (DSMC) method is capable of providing accurate solutions for flows in both in the rarefied and continuum regimes but becomes prohibitively expensive as the Knudsen number decreases. For the purpose of thermal protection systems (TPS) design and post-flight reconstruction, various selected points along an entry trajectory are often solved using hypersonic solvers. The quantities of interest that are obtained from that exercise are generally surface quantities, such as pressure, heat flux and enthalpy. Then, material response solvers are used to either design the heat shield to an optimal thickness based on a choice of material, or to provide in-depth heating profiles through the material at various select locations, and compare with flight instrumentation such as the ones that flew on NASA’s two most recent Mars missions, MSL and Mars2020. While most of the heating is generally experienced during the continuum part of the entry, the heating within the rarefied regime is significant for some atmospheres, and hence the flow solutions need to be computed using the DSMC method. Ensuring consistency between hypersonic CFD and the DSMC is crucial so that reliable surface quantities can be passed to material response solvers. Studies were performed to compare the two methods at various select locations, for both non-reacting argon flows as well reacting CO2/N2 flows. Preliminary conclusions show that, for non-reacting flows, the agreement between the two methods for surface heating is excellent (within expected uncertainties) for a freestream Knudsen number of 0.0006, and gets progressively worse as the Knudsen number increases to 0.06. Continuum breakdown analyses were performed and showed that, in general, the Gradient Length Local Knudsen number (KnGLL) from Boyd and associated criterion (KnGLL > 0.05) seems conservative in predicting zones of breakdown in the flow, and associated errors for surface quantities. Updated criteria of KnGLL = 2.0 and 0.5 appear to be more appropriate for surface and flow quantities, respectively. Furthermore, when studying reacting flows, our studies showed that while flow quantities are highly dependent on relaxation parameters and chemistry rates, it is possible to obtain a good agreement for surface heating, as long as the continuum breakdown is minimal.

DSMC↗

DOE OSTI2023

Engineered current-density profile diode laser

The present technology can be used to control the current injection profile in the longitudinal direction of a high-power diode laser in order to optimize current densities as a function of position in the cavity to promote higher reliable output power and increase the electrical to optical conversion efficiency of the device beyond the level which can be achieved without application of this technique. This approach can be utilized, e.g., in the fabrication of semiconductor laser chips to improve the output power and wall plug efficiency for applications requiring improved performance operation.

Leisher, Paul O.↗

DOE OSTI2024

Prototyping of a Rotary Triboelectric Nanogenerator for Power at Sea

Increasing at-sea power generation by Triboelectric Nanogenerator (TENG) energy harvesters towards the order of 1-Watt will create significant opportunities to power ocean observation buoys and distributed sensor nodes by extending mission time and increasing sensor payload. Of the many possible configurations of harvesting wave energy with TENGs, we document the rationale for choosing and developing a rotary TENG that operates by the freestanding mode. The rotary TENG prototype consists of two plates, a rotor and a stator, to take advantage of the various mechanisms of converting wave action into rotational motion. We have constructed a testing apparatus that allows us to vary several key parameters of the device: distance between rotor and stator, triboelectric material, rotational speed, number of electrodes and output load impedance. Preliminary results show that when driven at a constant 500 rpm, we can achieve a power density of 0.7 W/m3. A variable speed motor drives the rotor, which can be driven using a velocity profile informed by the equivalent to the output from a wave energy converter (WEC). The optimized rotational TENG can be stacked and driven by a single shaft, increasing the energy density of the device. The output of such a TENG could be used to power devices in the ocean at a low cost and high durability.

electrostatic generator↗

DOE OSTI2024

Engineered current-density profile diode laser

Leisher, Paul O.↗

DOE OSTI2025

Improved Representations of Longwave Surface Emissivity to Reduce Surface and Atmospheric Heating Biases in Earth System Models

Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.

Manzo, L. [Department of Earth System Science Univ↗

DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System

Frequency control from photovoltaic (PV) power plants has great potential to address the frequency response challenge of the power system with high penetrations of renewable generation. Using model-based approaches to determine the optimal PV headroom reserve, however, requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic 1-day operation profile of the WECC system and demonstrates a savings of more than 40% PV headroom compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

frequency control↗

DOE OSTI2021

Solar Field Layout and Aimpoint Strategy Optimization

The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.

14 SOLAR ENERGY↗

NASA NTRS1984

Optimal quasi-static shape control for large aerospace antennae

In this paper, an on-line control approach which will adjust the steady-state shape of a large antenna arbitarily close to any achievable desired profile is proposed. The method makes use of distributed parameter system theory and allows refocusing using a limited number of control actuators and sensors. The controller gains are calculated by approximating the solution to an infinite-dimensional optimal quasi-static control problem. A very general convergence result for such quasi-static controllers is proved and applied to the antenna controller to show convergence, using any Galerkin (finite-element) approximation method.

Balas, M. J.↗

NASA NTRS1997

PROFILE: Airfoil Geometry Manipulation and Display

This report provides user information for program PROFILE, an aerodynamics design utility for plotting, tabulating, and manipulating airfoil profiles. A dozen main functions are available. The theory and implementation details for two of the more complex options are also presented. These are the REFINE option, for smoothing curvature in selected regions while retaining or seeking some specified thickness ratio, and the OPTIMIZE option, which seeks a specified curvature distribution. Use of programs QPLOT and BPLOT is also described, since all of the plots provided by PROFILE (airfoil coordinates, curvature distributions, pressure distributions)) are achieved via the general-purpose QPLOT utility. BPLOT illustrates (again, via QPLOT) the shape functions used by two of PROFILE's options. These three utilities should be distributed as one package. They were designed and implemented for the Applied Aerodynamics Branch at NASA Ames Research Center, Moffett Field, California. They are all written in FORTRAN 77 and run on DEC and SGI systems under OpenVMS and IRIX.

Collins, Leslie↗

DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

A convergence metric for counting statistics in time-resolved small angle neutron scattering

Here, this work introduces a model-independent, dimensionless metric for predicting optimal measurement duration in time-resolved small-angle neutron scattering using early-time data. Built on a Gaussian process regression framework, the method reconstructs scattering profiles with quantified uncertainty, even from sparse or noisy measurements. Demonstrated on the EQ-SANS instrument at the Spallation Neutron Source, the approach generalizes to general SANS instruments with a two-dimensional detector. A key result is the discovery of a dimensionless convergence metric revealing a universal power-law scaling in profile evolution across soft matter systems. When time is normalized by a system-specific characteristic time t*, the variation in inferred profiles collapses onto a single curve with an exponent between −2 and −1. This trend emerges within the first ten time steps, enabling early prediction of measurement sufficiency. The method supports real-time experimental optimization and is especially valuable for maximizing efficiency in low-flux environments such as compact accelerator-based neutron sources.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗

NASA NTRS1986

PROFILE user's guide

User information for program PROFILE, an aerodynamics design utility for refining, plotting, and tabulating airfoil profiles is provided. The theory and implementation details for two of the more complex options are also presented. These are the REFINE option, for smoothing curvature in selected regions while retaining or seeking some specified thickness ratio, and the OPTIMIZE option, which seeks a specified curvature distribution. REFINE uses linear techniques to manipulate ordinates via the central difference approximation to second derivatives, while OPTIMIZE works directly with curvature using nonlinear least squares techniques. Use of programs QPLOT and BPLOT is also described, since all of the plots provided by PROFILE (airfoil coordinates, curvature distributions) are achieved via the general purpose QPLOT utility. BPLOT illustrates (again, via QPLOT) the shape functions used by two of PROFILE's options. The programs were designed and implemented for the Applied Aerodynamics Branch at NASA Ames Research Center, Moffett Field, California, and written in FORTRAN and run on a VAX-11/780 under VMS.

Collins, L.↗

NASA NTRS2014

Mass and Volume Optimization of Space Flight Medical Kits

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Monte Carlo Method↗