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At least 559 records · Page 31

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NASA NTRS1986

Optical techniques to feed and control GaAs MMIC modules for phased array antenna applications

A complex signal distribution system is required to feed and control GaAs monolithic microwave integrated circuits (MMICs) for phased array antenna applications above 20 GHz. Each MMIC module will require one or more RF lines, one or more bias voltage lines, and digital lines to provide a minimum of 10 bits of combined phase and gain control information. In a closely spaced array, the routing of these multiple lines presents difficult topology problems as well as a high probability of signal interference. To overcome GaAs MMIC phased array signal distribution problems optical fibers interconnected to monolithically integrated optical components with GaAs MMIC array elements are proposed as a solution. System architecture considerations using optical fibers are described. The analog and digital optical links to respectively feed and control MMIC elements are analyzed. It is concluded that a fiber optic network will reduce weight and complexity, and increase reliability and performance, but higher power will be required.

Bhasin, K. B.↗

NASA NTRS1988

Digital carrier demodulation for the DSN Advanced Receiver

The digital in-phase and quadrature (I and Q) carrier demodulation for the Deep Space Network's (DSN) Advanced Receiver is described and analyzed. The system provides coherent demodulation for a variety of modulation formats including Binary Phase Shift Keying (BPSK), BPSK with a carrier residual, Quadrature Phase Shift Keying (QPSK), Offset-QPSK (OQPSK), and Minimum Shift Keying (MSK). The focus is on the theory and hardware design of the halfband filters which are the integral part of the demodulator. The underlying theory of the filters is summarized, a breadboard hardware design is described, and a VLSI implementation is proposed which significantly decreases the hardware. A second important problem analyzed is DC-offset in the demodulator. This is a serious problem which translates into bias error in the residual carrier phase detector. The dynamic range of the complex mixer is analyzed using a probabilistic approach. It is deduced that the resulting static phase error is less than 0.2 deg when the ratio of carrier power to noise power in the demodulator input bandwidth is -72 dB or higher. Thus, the static phase error is negligible at a carrier power to noise spectral density of 0 dB-Hz for a 15 MHz bandwidth demodulator.

Sadr, R.↗

NASA NTRS1991

An analysis of the least-squares problem for the DSN systematic pointing error model

A systematic pointing error model is used to calibrate antennas in the Deep Space Network. The least squares problem is described and analyzed along with the solution methods used to determine the model's parameters. Specifically studied are the rank degeneracy problems resulting from beam pointing error measurement sets that incorporate inadequate sky coverage. A least squares parameter subset selection method is described and its applicability to the systematic error modeling process is demonstrated on Voyager 2 measurement distribution.

Alvarez, L. S.↗

NASA NTRS1992

Integrated numerical methods for hypersonic aircraft cooling systems analysis

Numerical methods have been developed for the analysis of hypersonic aircraft cooling systems. A general purpose finite difference thermal analysis code is used to determine areas which must be cooled. Complex cooling networks of series and parallel flow can be analyzed using a finite difference computer program. Both internal fluid flow and heat transfer are analyzed, because increased heat flow causes a decrease in the flow of the coolant. The steady state solution is a successive point iterative method. The transient analysis uses implicit forward-backward differencing. Several examples of the use of the program in studies of hypersonic aircraft and rockets are provided.

Petley, Dennis H.↗

NASA NTRS1999

Urban Heat Islands and Summertime Convective Thunderstorms in Atlanta: Three Case Studies

Data from both 27 sites in the Atlanta mesonet surface meteorological network and eight National Weather Service sites were analyzed for the period from 26 July to 3 August 1996. Analysis of the six precipitation events over the city during the period (each on a different day) showed that its urban heat island (UHI) induced a convergence zone that initiated three of the storms at different times of the day, i.e., 0630,0845, and 1445 EDT. Previous analysis has shown that New York City (NYC) effects summer daytime thunderstorm formation and/or movement. That study found that during nearly calm regional flow conditions the NYC UHI initiates convective activity. Moving thunderstorms, however, tended to bifurcate and to move around the city, due to its building barrier effect. The current Atlanta results thus agree with the NYC results with respect to thunderstorm initiation.

Bornstein, Robert↗

NASA NTRS2011

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Petrenko, Maksym↗

NASA NTRS2012

Evaluation of the Performance Characteristics of CGLSS II and U.S. NLDN Using Ground-Truth Dalta from Launch Complex 398, Kennedy Space Center, Florida

A new comprehensive lightning instrumentation system has been designed for Launch Complex 39B (LC39B) at the Kennedy Space Center, Florida. This new instrumentation system includes seven synchronized high-speed video cameras, current sensors installed on the nine downconductors of the new lightning protection system (LPS) for LC39B; four dH/dt, 3-axis measurement stations; and five dE/dt stations composed of two antennas each. The LPS received 8 direct lightning strikes (a total of 19 strokes) from March 31 through December 31 2011. The measured peak currents and locations are compared to those reported by the Cloud-to-Ground Lightning Surveillance System (CGLSS II) and the National Lightning Detection Network (NLDN). Results of comparison are presented and analyzed in this paper.

Mata, C. T.↗

NASA NTRS2016

Elevated Aerosol Layers and Their Radiative Impact over Kanpur During Monsoon Onset Period

Accurate information about aerosol vertical distribution is needed to reduce uncertainties in aerosol radiative forcing and its effect on atmospheric dynamics. The present study deals with synergistic analyses of aerosol vertical distribution and aerosol optical depth (AOD) with meteorological variables using multisatellite and ground-based remote sensors over Kanpur in central Indo-Gangetic Plain (IGP). Micro-Pulse Lidar Network-derived aerosol vertical extinction (sigma) profiles are analyzed to quantify the interannual and daytime variations during monsoon onset period (May-June) for 2009-2011. The mean aerosol profile is broadly categorized into two layers viz., a surface layer (SL) extending up to 1.5 km (where sigma decreased exponentially with height) and an elevated aerosol layer (EAL) extending between 1.5 and 5.5 km. The increase in total columnar aerosol loading is associated with relatively higher increase in contribution from EAL loading than that from SL. The mean contributions of EALs are about 60%, 51%, and 50% to total columnar AOD during 2009, 2010, and 2011, respectively. We observe distinct parabolic EALs during early morning and late evening but uniformly mixed EALs during midday. The interannual and daytime variations of EALs are mainly influenced by long-range transport and convective capacity of the local emissions, respectively. Radiative flux analysis shows that clear-sky incoming solar radiation at surface is reduced with increase in AOD, which indicates significant cooling at surface. Collocated analysis of atmospheric temperature and aerosol loading reveals that increase in AOD not only resulted in surface dimming but also reduced the temperature (approximately 2-3 C) of lower troposphere (below 3 km altitude). Radiative transfer simulations indicate that the reduction of incoming solar radiation at surface is mainly due to increased absorption by EALs (with increase in total AOD). The observed cooling in lower troposphere in high aerosol loading scenario could be understood as a dynamical feedback of EAL-induced stratification of lower troposphere. Further, the observed radiative effect of EALs increases the stability of the lower troposphere, which could modulate the large-scale atmospheric dynamics during monsoon onset period. These findings encourage follow-up studies on the implication of EALs to the Indian summer monsoon dynamics using numerical models.

aerosol vertical distribution↗

NASA NTRS2020

Bhutan Water Resources Tech Paper: Comparing Precipitation, Temperature, and Phenology Data Trends in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Himalayan countries, including Bhutan, have become vulnerable to warming trends which result in increasing temperature and variable rainfall and snowfall. By combining phenological and meteorological data, Earth observation platforms and sensors were used to assess trends in precipitation, temperature, and vegetation phenology in Bhutan from 1996 through 2017. This project studied precipitation using Climate Hazards Center Infrared Precipitation with Station data, analyzed temperature using the Famine Early Warning System Network Land Data Assimilation System, incorporated elevation data from the Shuttle Radar Topography Mission, and assessed vegetation phenology using Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) to evaluate climate variability and its effects on Bhutan. In situ temperature and precipitation data were also collected from the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) project and Bhutan’s National Center for Hydrology and Meterology. Modeled and in situ data showed similar trends in precipitation and temperature for the Thimpu, Chhukha, and Gasa regions. Aqua and Terra MODIS phenology data were variable from year to year. However, the data suggested a late onset of spring green up. Partners at the Bhutan Foundation and locally in Bhutan can use this information to better understand and monitor climate variability and replicate these methods for future analysis.

Kinley Dorji↗

NASA NTRS2020

Bhutan Water Resources Project Summary - Comparing Precipitation, Temperature, and Phenology Data Trends in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

DEVELOP Project Summary↗

NASA NTRS2024

Summarizing Multiple Aspects of Triple Collocation Analysis in a Single Diagram

With the ongoing expansion of global observation networks, it is expected that we shall routinely analyze records of geophysical variables such as temperature from multiple collocated instruments. Validating datasets in this situation is not a trivial task because every observing system has its own bias and noise. Triple collocation is a general statistical framework to estimate the error characteristics in three or more observational-based datasets. In a triple colocation analysis, several metrics are routinely reported but traditional multiple-panel plots are not the most effective way to display information. A new formula of error variance is derived for connecting the key terms in the triple collocation theory. A diagram based on this formula is devised to facilitate triple collocation analysis of any data from observations, as illustrated using three aerosol optical depth datasets from the recent Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). An observational-based skill score is also derived to evaluate the quality of three datasets by taking into account both error variance and correlation coefficient. Several applications are discussed and sample plotting routines are provided.

triple collocation↗

DOE OSTI2021

Full-field imaging learning machine (FILM)

A method of determining dynamic properties of a structure (linear or nonlinear) includes receiving spatio-temporal inputs, generating mode shapes and modal components corresponding to the spatio-temporal inputs using a trained deep complexity coding artificial neural network, and subsequently generating the dynamic properties by analyzing each modal component using a trained learning machine. A computing system for non-contact determination of dynamic properties of a structure includes a camera, a processor, and a memory including computer-executable instructions. When the instructions are executed, the system is caused to receive spatio-temporal image data, decompose the spatio-temporal image data into constituent manifold components using an autoencoder, and analyze the constituent manifold components using a trained learning machine to determine the dynamic properties.

Yang, Yongchao↗

DOE OSTI2022

A numerical approach for detecting switch-like bistability in mass action chemical reaction networks with conservation laws

Theoretical analysis of signaling pathways can provide a substantial amount of insight into their function. One particular area of research considers signaling pathways capable of assuming two or more stable states given the same amount of signaling ligand. This phenomenon of bistability can give rise to switch-like behavior, a mechanism that governs cellular decision making. Investigation of whether or not a signaling pathway can confer bistability and switch-like behavior, without knowledge of specific kinetic rate constant values, is a mathematically challenging problem. Recently a technique based on optimization has been introduced, which is capable of finding example parameter values that confer switch-like behavior for a given pathway. Although this approach has made it possible to analyze moderately sized pathways, it is limited to reaction networks that presume a uniterminal structure. It is this limited structure we address by developing a general technique that applies to any mass action reaction network with conservation laws. In this paper we developed a generalized method for detecting switch-like bistable behavior in any mass action reaction network with conservation laws. The method involves (1) construction of a constrained optimization problem using the determinant of the Jacobian of the underlying rate equations, (2) minimization of the objective function to search for conditions resulting in a zero eigenvalue, (3) computation of a confidence level that describes if the global minimum has been found and (4) evaluation of optimization values, using either numerical continuation or directly simulating the ODE system, to verify that a bistability region exists. The generalized method has been tested on three motifs known to be capable of bistability. We have developed a variation of an optimization-based method for the discovery of bistability, which is not limited to uniterminal chemical reaction networks. Successful completion of the method provides an S-shaped bifurcation diagram, which indicates that the network acts as a bistable switch for the given optimization parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1978

Creation of lumped parameter thermal model by the use of finite elements

In the finite difference technique, the thermal network is represented by an analogous electrical network. The development of this network model, which is used to describe a physical system, often requires tedious and mental data preparation and checkout by the analyst which can be greatly reduced through the use of the computer programs to develop automatically the mathematical model and associated input data and graphically display the analytical model to facilitate model verification. Three separate programs are involved which are linked through common mass storage files and data card formats. These programs are SPAR, CINGEN and GEOMPLT, and are used to (1) develop thermal models for the MITAS II thermal analyzer program; (2) produce geometry plots of the thermal network; and (3) produce temperature distribution and time history plots.

Source record↗

NASA NTRS2001

Hyperspectral Image Classification using a Self-Organizing Map

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Martinez, P.↗

DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

MicroPulse DIAL (MPD) – a diode-laser-based lidar architecture for quantitative atmospheric profiling

Abstract. Continuous water vapor and temperature profiles are critically needed for improved understanding of the lower atmosphere and potential advances in weather forecasting skill. Ground-based, national-scale profiling networks are part of a suite of instruments to provide such observations; however, the technological method must be cost-effective and quantitative. We have been developing an active remote sensing technology based on a diode-laser-based lidar technology to address this observational need. Narrowband, high-spectral-fidelity diode lasers enable accurate and calibration-free measurements requiring a minimal set of assumptions based on direct absorption (Beer–Lambert law) and a ratio of two signals. These well-proven quantitative methods are known as differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL). This diode-laser-based architecture, characterized by less powerful laser transmitters than those historically used for atmospheric studies, can be made eye-safe and robust. Nevertheless, it also requires solar background suppression techniques such as narrow-field-of-view receivers with an ultra-narrow bandpass to observe individual photons backscattered from the atmosphere. We discuss this diode-laser-based lidar architecture's latest generation and analyze how it addresses a national-scale profiling network's need to provide continuous thermodynamic observations. The work presented focuses on general architecture changes that pertain to both the water vapor and the temperature profiling capabilities of the MicroPulse DIAL (MPD). However, the specific subcomponent testing and instrument validation presented are for the water vapor measurements only. A fiber-coupled seed laser transmitter optimization is performed and shown to meet all of the requirements for the DIAL technique. Further improvements – such as a fiber-coupled near-range receiver, the ability to perform quality control via automatic receiver scanning, advanced multi-channel scalar capabilities, and advanced processing techniques – are discussed. These new developments increase narrowband DIAL technology readiness and are shown to allow higher-quality water vapor measurements closer to the surface via preliminary intercomparisons within the MPD network itself and with radiosondes.

Spuler, Scott M.↗