Results for “Lookup table” — Page 4

NASA NTRSDate not supplied

A Comprehensive Forward Model for Spaceborne Radar Instruments

We present the development and validation of a comprehensive forward model designed to enhance remote sensing capabilities of spaceborne radar instruments. To overcome limitations in existing models, we integrated a Discrete Dipole Approximation (DDA) cloud scattering database into our Radiative Transfer Model (RTM), focusing on microwave frequencies. By simulating the optical properties of non-spherical frozen hydrometeors, the DDA technique effectively reduced discrepancies between simulated and observed values, surpassing traditional Mie tables. The evaluation of DDA lookup tables involved comparisons with a collocated dataset comprising short-term forecasts and satellite microwave data, providing evidence of their superiority. Additionally, we address the challenges of assimilating active radar measurements, which offer vertically resolved insights into clouds and precipitation. We explored the assimilation of spaceborne radar measurements in Numerical Weather Prediction (NWP) models by integrating a forward radar model, along with its adjoint and tangent linear, into the data assimilation system. Evaluation using CloudSat measurements demonstrated promising agreement between simulations and observations, particularly when the input hydrometeor profiles aligned with the measured reflectivity profiles, showcasing the potential of the developed forward radar model. Moreover, we discuss other challenges in radar measurement assimilation within NWP models, including potential observation errors and biases.

Isaac Moradi↗

NASA NTRS1997

Algorithm for Atmospheric and Glint Corrections of Satellite Measurements of Ocean Pigment

An algorithm is developed to correct satellite measurements of ocean color for atmospheric and surface reflection effects. The algorithm depends on taking the difference between measured and tabulated radiances for deriving water-leaving radiances. 'ne tabulated radiances are related to the measured radiance where the water-leaving radiance is negligible (670 nm). The tabulated radiances are calculated for rough surface reflection, polarization of the scattered light, and multiple scattering. The accuracy of the tables is discussed. The method is validated by simulating the effect of different wind speeds than that for which the lookup table is calculated, and aerosol models different from the maritime model for which the table is computed. The derived water-leaving radiances are accurate enough to compute the pigment concentration with an error of less than q 15% for wind speeds of 6 and 10 m/s and an urban atmosphere with aerosol optical thickness of 0.20 at lambda 443 nm and decreasing to 0.10 at lambda 670 nm. The pigment accuracy is less for wind speeds less than 6 m/s and is about 30% for a model with aeolian dust. On the other hand, in a preliminary comparison with coastal zone color scanner (CZCS) measurements this algorithm and the CZCS operational algorithm produced values of pigment concentration in one image that agreed closely.

Fraser, Robert S.↗

NASA NTRSDate not supplied

Impacts of aerosol size-dependent below-cloud scavenging on tropospheric aerosol in the NASA GEOS model

Wet deposition is the major sink for a suite of tropospheric aerosols, and thus largely affects the global distribution and lifetime of aerosols as well as the formation of clouds in the atmosphere. In this study, we implement the aerosol size-dependent below-cloud scavenging (BCS; washout) parameterization of Croft et al. (Atmos. Chem. Phys., 2009; hereafter referred to as C09) in the GOCART bulk aerosol scheme coupled with the NASA Goddard Earth Observing System (GEOS) model, and evaluate the simulated tropospheric aerosols against surface, airborne, and satellite observations. The current below-cloud scavenging in GOCART employs a first-order removal function with a constant scavenging coefficient that is independent of aerosol sizes and precipitation fluxes. The C09 BCS parameterization instead calculates aerosol below-cloud scavenging coefficients based on a size-dependent collision efficiency between aerosol particles and raindrops (or snow crystals). A look-up table of compiled collision efficiencies provides scavenging coefficients for sixty aerosol sizes and nine rain flux rates. We determine instantaneous coefficients according to the C09 BCS look-up table, precipitation fluxes, and a log-normal size distribution of aerosols. The implemented BCS parameterization tends to result in a large diversity of scavenging coefficient values with higher magnitudes, leading to more efficient scavenging. The model-simulated global mean tropospheric Pb-210 aerosol lifetime decreases from 7.4 days to 5.8 days. The separate consideration of rain and snow conditions in the scavenging coefficient lookup table leads to a bi-mode distribution of scavenging coefficients. These changes also cause increased mass fractions of smaller aerosols compared to the current simulation. We examine the impacts of the C09 BCS parameterization on the simulated aerosol vertical profiles, tropospheric lifetimes, and deposition fluxes through comparisons with NASA aircraft measurements (ATom), surface observations of aerosol concentrations (IMPROVE) and wet deposition fluxes (NADP and APQMP), and MODIS aerosol optical depth (AOD) retrievals.

Aerosols↗

NASA NTRSDate not supplied

Surface and Atmospheric Shortwave Radiative Fluxes From ISCCP Data and Fu-Liou Algorithm at Higher Spatial and Vertical Resolution

NASA/GEWEX Surface Radiation Budget (SRB) has provided surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology data as the primary input. Release 4.0 came out in 2019, with data from July 1983 through June 2017, and improved validation stats relative to Release 3.0 (Stackhouse et al., 2012). Release 4.0 used the newly reprocessed ISCCP H data set. The shortwave algorithm for versions 3 and 4 has been based on the Pinker and Laszlo (1992) algorithm, which relies on the satellite-measured shortwave radiance to produce a TOA albedo. This background TOA albedo is made utilizing the background clear-sky visible radiance (called clear-sky composite radiance in the ISCCP data) and applying narrowband-to-broadband angular distribution models. Using a climatological aerosol assumption, the surface albedo is estimated using radiative transfer based (i.e., Fu/Liou radiative transfer model; Fu and Liou, 1993) look-up tables. Using this surface albedo and an instantaneous TOA albedo, the look-up tables are used to adjust both the aerosol optical depth (for clear sky) and cloud optical depth (for cloudy sky) for each scene. These properties and look up tables are then used to generate surface fluxes. While this has worked well to provide useful fluxes, it has occasionally resulted in inaccurate direct and diffuse surface SW fluxes due to the overreliance on aerosol optical depth. With increased computational power and storage now available, a more direct approach is now possible. Here we present a different approach for a future high resolution SRB Release 5.0. We replace the Pinker-Laszlo lookup table approach with a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). In addition to being a proven radiation code, Fu-Liou allows the calculation of fluxes at different atmospheric levels and spectral bands, which will provide more insight into the surface radiation budget, its variability and attribution. It is expected that horizontal resolution will increase to at least 0.5°x0.5° from the current 1°x1°. Here we demonstrate a preliminary look at the next SRB, and show comparisons with the current release.

Earth Radiation Budget↗

NASA NTRS2005

Status of the MODIS Level 1B Algorithms and Calibration Tables

The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites, launched in December 1999 and May 2002, respectively. The MODIS Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the MODIS L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the MODIS collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.

MODIS LEVEL 1B ALGORITHMS↗

NASA NTRS1999

Control of a Thrust Alignment Table for Modeling the Coning Dynamics of a Spinning Spacecraft with a Follower Force

This document presents a system controlling the motion of a spherical air bearing used in the modeling of spacecraft dynamics and controls in a laboratory environment. The system is part of the Spinning Rocket Simulator (SRS), used to simulate the coning of spacecraft during a thrusting stage. The reaction force at the spherical air bearing supporting the spacecraft model must coincide with the thrust axis of the model for proper simulation. Therefore, the bearing is translated in a circular path to introduce a centrifugal force. This horizontal force along with the gravitational reaction force at the bearing combines to simulate the direction of the spacecraft's thrust force. The control system receives attitude information from the spacecraft model via a laser beam embedded in the model that impinges on a photosensitive array. The non-linear system is controlled using high-speed lookup tables and digital techniques. A vector-controlled motor and a stepper motor are given the necessary signals to accurately control the turntable and platform supporting the air bearing. Preliminary performance data is presented. Mechanical elements of the table and platform are described in detail. A wireless (RF) data path for all devices on the spacecraft model to an off-table command computer is also described.

Halsmer, Dominic↗

NASA NTRS2010

MMIC Amplifiers and Wafer Probes for 350 to 500 GHz

A wireless avionics interface exploits the constrained nature of data networks in flight systems to use a lightweight routing method. This simplified routing means that a processor is not required, and the logic can be implemented as an intellectual property (IP) core in a field-programmable gate array (FPGA). The FPGA can be shared with the flight subsystem application. In addition, the router is aware of redundant subsystems, and can be configured to provide hot standby support as part of the interface. This simplifies implementation of flight applications requiring hot stand - by support. When a valid inbound packet is received from the network, the destination node address is inspected to determine whether the packet is to be processed by this node. Each node has routing tables for the next neighbor node to guide the packet to the destination node. If it is to be processed, the final packet destination is inspected to determine whether the packet is to be forwarded to another node, or routed locally. If the packet is local, it is sent to an Applications Data Interface (ADI), which is attached to a local flight application. Under this scheme, an interface can support many applications in a subsystem supporting a high level of subsystem integration. If the packet is to be forwarded to another node, it is sent to the outbound packet router. The outbound packet router receives packets from an ADI or a packet to be forwarded. It then uses a lookup table to determine the next destination for the packet. Upon detecting a remote subsystem failure, the routing table can be updated to autonomously bypass the failed subsystem.

Samoska, Lorene A.↗

NASA NTRS2010

Interface Supports Lightweight Subsystem Routing for Flight Applications

A wireless avionics interface exploits the constrained nature of data networks in flight systems to use a lightweight routing method. This simplified routing means that a processor is not required, and the logic can be implemented as an intellectual property (IP) core in a field-programmable gate array (FPGA). The FPGA can be shared with the flight subsystem application. In addition, the router is aware of redundant subsystems, and can be configured to provide hot standby support as part of the interface. This simplifies implementation of flight applications requiring hot stand - by support. When a valid inbound packet is received from the network, the destination node address is inspected to determine whether the packet is to be processed by this node. Each node has routing tables for the next neighbor node to guide the packet to the destination node. If it is to be processed, the final packet destination is inspected to determine whether the packet is to be forwarded to another node, or routed locally. If the packet is local, it is sent to an Applications Data Interface (ADI), which is attached to a local flight application. Under this scheme, an interface can support many applications in a subsystem supporting a high level of subsystem integration. If the packet is to be forwarded to another node, it is sent to the outbound packet router. The outbound packet router receives packets from an ADI or a packet to be forwarded. It then uses a lookup table to determine the next destination for the packet. Upon detecting a remote subsystem failure, the routing table can be updated to autonomously bypass the failed subsystem.

Lux, James P.↗

NASA NTRS2018

JPSS-1 VIIRS Solar Diffuser Witness Sample BRF Calibration Using a Table-Top Goniometer at NASA GSFC

In support of the prelaunch calibration of the Joint Polar Satellite System-1 (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS), the Bidirectional Reflectance Factor (BRF) and Bidirectional Reflectance Distribution Function (BRDF) of a VIIRS solar diffuser (SD) witness sample were determined using the table-top goniometer (TTG) located in the NASA GSFC Diffuser Calibration Laboratory (DCL). The BRF of the sample was measured for VIIRS bands in the reflected solar wavelength region from 410 nm to 2250 nm. The new TTG was developed to extend the laboratory’s BRF and BRDF measurement capability to wavelengths from 1600 to 2250 nm and specifically for the VIIRS M11 band centered at 2250 nm. We show the new features and capabilities of the new scatterometer and present the BRF and BRDF results for the incident/scatter test configuration of 0°/45° and for a set of angles representing of the VIIRS on-orbit solar diffuser calibration. The BRF and BRDF results of the SD witness were used to assist in finalizing the set of BRF values of J1 VIIRS SD to be used on-orbit. Comparison of the BRF results between the JPSS-1 VIIRS SD witness sample and the flight SD panel was made by varying different sample clocking orientations and by analyzing the ratio of BRF to total hemispherical reflectance in effort to minimize the uncertainty of the extrapolated flight BRF value at 2250 nm. Furthermore, differences between the prelaunch BRF results and those used in the VIIRS on-orbit BRF lookup table were examined to improve the VIIRS BRF calibration for future missions.

Zeng, Jinan↗

NASA NTRS2018

JPSS-1 VIIRS Solar Diffuser Witness Sample BRF Calibration Using a Table-Top Goniometer at NASA GSFC

In support of the prelaunch calibration of the Joint Polar Satellite System-1 (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS), the Bidirectional Reflectance Factor (BRF) and Bidirectional Reflectance Distribution Function (BRDF) of a VIIRS solar diffuser (SD) witness sample were determined using the table-top goniometer (TTG) located in the NASA GSFC Diffuser Calibration Laboratory (DCL). The BRF of the sample was measured for VIIRS bands in the reflected solar wavelength region from 410 nm to 2250 nm. The new TTG was developed to extend the laboratory’s BRF and BRDF measurement capability to wavelengths from 1600 to 2250 nm and specifically for the VIIRS M11 band centered at 2250 nm. We show the new features and capabilities of the new scatterometer and present the BRF and BRDF results for the incident/scatter test configuration of 0°/45° and for a set of angles representing of the VIIRS on-orbit solar diffuser calibration. The BRF and BRDF results of the SD witness were used to assist in finalizing the set of BRF values of J1 VIIRS SD to be used on-orbit. Comparison of the BRF results between the JPSS-1 VIIRS SD witness sample and the flight SD panel was made by varying different sample clocking orientations and by analyzing the ratio of BRF to total hemispherical reflectance in effort to minimize the uncertainty of the extrapolated flight BRF value at 2250 nm. Furthermore, differences between the prelaunch BRF results and those used in the VIIRS on-orbit BRF lookup table were examined to improve the VIIRS BRF calibration for future missions.

Zeng, Jinan↗

DOE OSTI2024

A taxonomy of automatic differentiation pitfalls

Automatic differentiation is a popular technique for computing derivatives of computer programs. While automatic differentiation has been successfully used in countless engineering, science, and machine learning applications, it can sometimes nevertheless produce surprising results. In this paper, we categorize problematic usages of automatic differentiation, and illustrate each category with examples such as chaos, time-averages, discretizations, fixed-point loops, lookup tables, linear solvers, and probabilistic programs, in the hope that readers may more easily avoid or detect such pitfalls. We also review debugging techniques and their effectiveness in these situations.

Autodiff↗

DOE OSTI2025

Predicting critical heat flux with uncertainty quantification and domain generalization using conditional variational autoencoders and deep neural networks

Deep generative models (DGMs) can generate synthetic data samples that closely resemble the original dataset, addressing data scarcity. In this work, we developed a conditional variational autoencoder (CVAE) to augment critical heat flux (CHF) data used for the 2006 Groeneveld lookup table. To compare with traditional methods, a fine-tuned deep neural network (DNN) regression model was evaluated on the same dataset. Both models achieved small mean absolute relative errors, with the CVAE showing more favorable results. Uncertainty quantification (UQ) was performed using repeated CVAE sampling and DNN ensembling. The DNN ensemble improved performance over the baseline, while the CVAE maintained consistent results with less variability and higher confidence. Both models achieved small errors inside and outside the training domain, with slightly larger errors outside. Altogether, the CVAE performed better than the DNN in predicting CHF and exhibited better uncertainty behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Fast estimation of reaction rates in spherical and non-spherical porous catalysts

Here we present a methodology for modeling multi-step reaction rates in porous catalyst particles for use in CFD-DEM and two fluid models. Single-step effectiveness factors based on a Thiele modulus, while useful, cannot accurately capture the cascading reaction systems common in high temperature vapor-phase chemical reactors like fluidized catalytic cracking units and catalytic biomass fast pyrolysis systems. Instead, multi-step effectiveness vectors derived from steady-state solutions to the governing reaction-diffusion equations are needed. Solutions for various catalyst shapes are presented, including spheres, cylinders, and prisms. Computational challenges inherent in repeated evaluation of reaction rates with diffusion limitations are discussed, and an efficient implementation based on pre-computed lookup tables is proposed and demonstrated on a simulation of a fluidized bed reactor. Open-source code is provided for the compilation of reaction rate tables for use in ODE, DEM, and two-fluid models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗

DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Assessment of flamelet/progress variable methods for supersonic combustion

Tabulated chemistry models, including the flamelet/progress variable approach, have been successfully used for a variety of turbulent flame simulations. The progress variable describes the progress of reactions in a system and parameterizes a lookup table of thermochemical variables. This approach reduces the cost of simulations, transporting only one scalar (progress variable) instead of the many species mass fractions required for detailed chemistry. Originally developed for low Mach number flame simulations, recent works have focused on extensions of this approach to compressible flames, supersonic combustion, and detonations, with applications such as scramjet combustors and rotating detonation engines. Unlike low Mach simulations, compressible flow simulations require solving the energy transport equation, which is coupled to the equation of state. This leads to additional modeling challenges regarding the thermodynamics and its impact on the chemistry. The validity of modeling assumptions, for example the relationship between energy and temperature, also varies with the combustion regime. The present work provides a detailed assessment of the existing strategies for chemistry tabulation for compressible/supersonic combustion, including detonations. A priori analysis indicates that approximations which are reasonable for weakly compressible flames may break down for shock-induced combustion. Furthermore, the analysis identifies specific assumptions and approximations that do not hold for detonations, emphasizing that care must be taken when applying tabulated chemistry models outside their intended combustion regimes.

Detonations↗

DOE OSTI2021

Proof-of-concept of a reinforcement learning framework for wind farm energy capture maximization in time-varying wind

Here, we present a proof-of-concept distributed reinforcement learning framework for wind farm energy capture maximization. The algorithm we propose uses Q-Learning in a wake-delayed wind farm environment and considers time-varying, though not yet fully turbulent, wind inflow conditions. These algorithm modifications are used to create the Gradient Approximation with Reinforcement Learning and Incremental Comparison (GARLIC) framework for optimizing wind farm energy capture in time-varying conditions, which is then compared to the FLOw Redirection and Induction in Steady State (FLORIS) static lookup table wind farm controller baseline.

17 WIND ENERGY↗

DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗