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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower (DIVERS-H)

U.S. hydropower plants face potential threats from shrinking water supply, rising demands, and warmer stream temperatures from various causes. Power plant owners, operators, and regulators require new tools to take advantage of and interpret the diverse range of scientific data being produced by both observational methods (for example, satellite, radar, stream gauges) and computer modeling methods that evaluate and predict how earth's dynamic systems (atmosphere, oceans, land surface, and sea ice) are changing and interacting. Combining datasets such as these with AI-based analyses introduces a novel decision support system to help users anticipate and address potential impacts on power generation stations. This new technology has been named DIVERS-H for "Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower." In Phase I, technical feasibility was established with the development and demonstration of all the new technologies that are required. Most notably, DIVERS-H will use new artificial intelligence (AI) methods to capture the complex dynamics of water availability, demand, and environmental changes. In addition, new data management software was developed, and a prototype user interface was implemented as the precursor to a full scale decision support system. With technical research complete, the project focus now shifts to development of a commercial software product to provide users with actionable insight into water availability and the risk/resilience of critical systems at their locations of interest. Although DIVER-H was originally conceived as a tool for hydroelectric power applications, the same underlying technology can be readily applied to other water-consuming systems including coal, natural gas, oil, and nuclear power plants.

Chaudhary, Aashish [Kitware, Inc., Clifton Park, N↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be difficult to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Automatic flight phase classification will enhance efficiencies of ATM/ATC-like architectures for AAM/UAM. Classifying the main flight phases (takeoff, climb, cruise, descent, and landing) provides insight to ensure safe operations, provide situational awareness of the NAS, and monitor flights in case there are any emergencies. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight for flight phase classification by leveraging distributed sensing concepts.

distributed sensing↗
NASA NTRS1999

The Design and Operation of TMI, a Mechanically-Scanning, Multi-Frequency Microwave Radiometer for the Tropical Rainfall Measurements Mission

The Tropical Rainfall Measurement Mission (TRMM), a joint mission between the U.S. NASA and the Japans NASDA (National Space Development Agency), was successfully launched in November of 1997. On board of the TRMM satellite are two major microwave sensors, a real-aperture radar operating at 13.8 GHz, called the Precipitation Radar (PR), and a microwave radiometer system called TRMM Microwave Imager (TMI). The TMI contains five frequencies, ranging from 10.7 to 85 GHz, is designed to cover a wide dynamic range of rain intensities. The TMI measures the rain from the emission properties while the PR's measurement is based on the scattering of the hydrometeor. The two instruments aboard the same platform provide a complementary and synergistic measurement of precipitation. This paper will focus primarily on the TMI. The advent of microwave sensor technology in recent years, the addition of a new frequency (at 10.7 GHz), as well as the mission design, have enabled the TMI to be a superior instrument for the precipitation measurement. We will provide a description of the instrument together with some of its the design rationales and practical hardware implementation. We will also show the performance of TMI aboard the TRMM and some examples of its data.

Shiue, James C.↗
NASA NTRS1997

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗
NASA NTRS1995

Microwave Imaging and Holographic Diagnostic to Antennas in Cylindrical Near-Field Measurement

In this paper, the issues pertaining to microwave imaging and holographic diagnostic to antennas in cylindrical near-field measurements are addressed. The theoretical approach is based on expanding the work in [1] and [2] where a cylindrical wave expansion of the field on a cylindrical near-field surface is given. The sampling probe is modeled by its equivalent aperture current (idealized circular aperture) and incorporated into the near-field to far-field transformation. The method of steepest decent is applied to obtain the far-field. In its implementation, however, one could specify directly the angular spectrum at which the far-field is desired to be calculated without resorting to interpolation. The microwave imaging and holographic diagnostic is based on back projection where a plane wave expansion of the far-field is obtained. This approach necessitates the knowledge of the far-field at exact angular spectrum resulting from application of 2-D FFT. Hence, we were able to construct simply the near-field on a plane not necessarily on the aperture plane of the test antenna but also on planes perpendicular to the aperture plane [3]. And a 3-D high resolution and high precision antenna imaging of the test antenna is obtained from cylindrical near-field simulated measurements. In addition microwave holographic diagnostic of large NASA scatterometer radar antenna obtained from measured near-field on a cylindrical surface will be given if time permits.

Microwave Imaging Holographic↗
NASA NTRS2003

Design of an L-band Microwave Radiometer with Active Mitigation of Interference

Radio frequency interference (RFI) impairs L-band radiometry outside the protected 20 MHz frequency band around 1413 MHz. However, bandwidths of 100 MHz or more are desired for certain remote sensing applications as well as certain astronomy applications. Because much of the RFI in this band is from radars with pulse lengths on the order of microseconds, traditional radiometers (i.e., those which directly measure total power or power spectral density integrated over time scales of milliseconds or greater) are poorly-suited to this task. Simply reducing integration time and discarding contaminated outputs may not be a practical answer due to the wide variety of modulations and pulse lengths observed in L-band RFI signals, the dynamic and complex nature of the associated propagation channels, and the logistical effort associated with post-measurement data editing. This motivates the design and development of radiometers capable of coherent sampling and adaptive, real-time mitigation of interference. Such a radiometer will be described in this presentation. This design is capable of coherently-sampling up to 100 MHz bandwidth at L-band. RFI mitigation is implemented in FPGA components so that real-time suppression is achieved. The system currently uses a cascade of basic time- and frequency-domain detection and blanking techniques; more advanced algorithms are under consideration. The modular FPGA-based architecture provides other benefits, such as the ability to implement extremely stable digital filters and the ability to reconfigure the system "on the fly". An overview of the basic design along with on-the-air results from an initial implementation will be provided in the presentation. Related L-band RFI surveys will be described to illustrate the relevance of this approach in a variety of operating conditions.

Hampson, G. A.↗
NASA NTRS2003

Design of an L-band Microwave Radiometer with Active Mitigation of Interference

Radio frequency interference (RFI) impairs L-band radiometry outside the protected 20 MHz frequency band around 1413 MHz. However, bandwidths of 100 MHz or more are desired for certain remote sensing applications as well as certain astronomy applications. Because much of the RFI in this band is from radars with pulse lengths on the order of microseconds, traditional radiometers (i.e., those which directly measure total power or power spectral density integrated over time scales of milliseconds or greater) are poorly-suited to this task. Simply reducing integration time and discarding contaminated outputs may not be a practical answer due to the wide variety of modulations and pulse lengths observed in L-band RFI signals, the dynamic and complex nature of the associated propagation channels, and the logistical effort associated with post-measurement data editing. This motivates the design and development of radiometers capable of coherent sampling and adaptive, real-time mitigation of interference. Such a radiometer will be described in this presentation. This design is capable of coherently-sampling up to 100 MHz bandwidth at L-band. RFI mitigation is implemented in FPGA components so that real-time suppression is achieved. The system currently uses a cascade of basic time- and frequency- domain detection and blanking techniques; more advanced algorithms are un- der consideration. The modular FPGA-based architecture provides other benefits, such as the ability to implement extremely stable digital filters and the ability to reconfigure the system "on the fly". An overview of the basic design along with on-the-air results from an initial implementation will be provided in the presentation. Related L-band RFI surveys will be described to illustrate the relevance of this approach in a variety of operating conditions.

Ellingson, S. W.↗
DOE OSTI2020

A New Method for Ice-Ice Aggregation in the Adaptive Habit Model

In this paper, a novel methodology for modeling ice-ice aggregation is presented. This methodology combines a modified hydrodynamic collection algorithm with bulk aggregate characteristic information from an offline simulator that collects ice particles, namely, the Ice Particle and Aggregate Simulator, and has been implemented into the Adaptive Habit Microphysics scheme in the Weather Research and Forecasting Model. Aggregates, or snow, are formed via collection of cloud ice particles, where initial ice characteristics and the resulting geometry determine aggregate characteristics. Upon implementation, idealized squall-line simulations are performed to examine the new methodology in comparison with commonly used bulk microphysics schemes. It is found that the adaptive habit aggregation parameterization develops snow and reduces ice mass and number concentrations compared to other schemes. The development of aggregates through the new methodology cascades into other interesting effects, including enhancements in ice and snow growth, as well as homogeneous freezing. Further microphysical analyses reveal varying sensitivities, where snow processes are most sensitive to the new parameterization, followed by ice, then cloud, rain, and graupel processes. Further, the new scheme results in enhancements in surface precipitation due to the persistence of snow at lower altitudes. This persistence is a result of shape-dependent melting and sublimation, increasing the residence time. Moreover, these low-level enhancements are reflected in increases in radar reflectivity at the surface and its spatial distribution. Finally, the ability to predict snow shape and density allows for the simulation of polarimetric radar quantities, resulting in signature enhancements compared to schemes that do not consider spatial and temporal variations in snow shape and density.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Flying SATS Higher Volume Operations: Training, Lessons Learned, and Pilots' Experiences

Developments in aviation, including new surveillance technologies and quicker, more economical small aircraft, have been identified as driving factors in a potential expansion of the use of non-towered, non-radar airports. The Small Aircraft Transportation System (SATS) project has developed the Higher Volume Operations (HVO) concept that enables pilots to safely arrive and depart these airports in instrument conditions at an increased rate as compared to today's procedures. This is achieved by transferring some traffic management tasks to centralized, ground-based automation, while assigning others to participating pilots aided by on-board tools. This paper describes strategies and lessons learned while training pilots to fly these innovative operations. Pilot approaches to using the experimental displays and dynamic altering systems during training are discussed. Potential operational benefits as well as pit-falls and frustrations expressed by subjects while learning to fly these new procedures are presented. Generally, pilots were comfortable with the procedures and the training process, and expressed interest in its near-term implementation.

Conway, Sheila↗
NASA NTRS2012

Multi-pixel high-resolution three-dimensional imaging radar

A three-dimensional imaging radar operating at high frequency e.g., 670 GHz radar using low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform, is disclosed that operates with a multiplexed beam to obtain range information simultaneously on multiple pixels of a target. A source transmit beam may be divided by a hybrid coupler into multiple transmit beams multiplexed together and directed to be reflected off a target and return as a single receive beam which is demultiplexed and processed to reveal range information of separate pixels of the target associated with each transmit beam simultaneously. The multiple transmit beams may be developed with appropriate optics to be temporally and spatially differentiated before being directed to the target. Temporal differentiation corresponds to a different intermediate frequencies separating the range information of the multiple pixels. Collinear transmit beams having differentiated polarizations may also be implemented.

Cooper, Ken B.↗
NASA NTRS2011

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Njoku, Eni↗
NASA NTRS2012

3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer

Determining the Z-R relationship (where Z is the radar reflectivity factor and R is rainfall rate) from disdrometer data has been and is a common goal of cloud physicists and radar meteorology researchers. The usefulness of this quantity has traditionally been limited since radar represents a volume measurement, while a disdrometer corresponds to a point measurement. To solve that problem, a 3D-DSD (drop-size distribution) method of determining an equivalent 3D Z-R was developed at the University of Central Florida and tested at the Kennedy Space Center, FL. Unfortunately, that method required a minimum of three disdrometers clustered together within a microscale network (.1-km separation). Since most commercial disdrometers used by the radar meteorology/cloud physics community are high-cost instruments, three disdrometers located within a microscale area is generally not a practical strategy due to the limitations of these kinds of research budgets. A relatively simple modification to the 3D-DSD algorithm provides an estimate of the 3D-DSD and therefore, a 3D Z-R measurement using a single disdrometer. The basis of the horizontal extrapolation is mass conservation of a drop size increment, employing the mass conservation equation. For vertical extrapolation, convolution of a drop size increment using raindrop terminal velocity is used. Together, these two independent extrapolation techniques provide a complete 3DDSD estimate in a volume around and above a single disdrometer. The estimation error is lowest along a vertical plane intersecting the disdrometer position in the direction of wind advection. This work demonstrates that multiple sensors are not required for successful implementation of the 3D interpolation/extrapolation algorithm. This is a great benefit since it is seldom that multiple sensors in the required spatial arrangement are available for this type of analysis. The original software (developed at the University of Central Florida, 1998.- 2000) has also been modified to read standardized disdrometer data format (Joss-Waldvogel format). Other modifications to the software involve accounting for vertical ambient wind motion, as well as evaporation of the raindrop during its flight time.

Lane, John↗
DOE OSTI2022

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be challenging to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Aircraft typically have the following flight phases: takeoff, climb, cruise, descent, and landing. Classifying these flight phases provides insight into ensuring safe operations, providing situational awareness of the NAS, and monitoring flights in emergencies. Automatic flight phase classification will enhance the efficiencies of ATM/ATC-like architectures for AAM/UAM, especially since numerous aircraft will be flying in highly dense urban environments. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight into flight phase classification by leveraging distributed sensing concepts. Simulation results and post-processed flight test results demonstrate the utility of HME for automatic and robust flight phase classification for real-time AAM operations.

distributed sensing↗
NASA NTRS1994

Experiments with the Mesoscale Atmospheric Simulation System (MASS) using the synthetic relative humidity

This study is intended to examine the impact of the synthetic relative humidity on the model simulation of mesoscale convective storm environment. The synthetic relative humidity is derived from the National Weather Services surface observations, and non-conventional sources including aircraft, radar, and satellite observations. The latter sources provide the mesoscale data of very high spatial and temporal resolution. The synthetic humidity data is used to complement the National Weather Services rawinsonde observations. It is believed that a realistic representation of initial moisture field in a mesoscale model is critical for the model simulation of thunderstorm development, and the formation of non-convective clouds as well as their effects on the surface energy budget. The impact will be investigated based on a real-data case study using the mesoscale atmospheric simulation system developed by Mesoscale Environmental Simulations Operations, Inc. The mesoscale atmospheric simulation system consists of objective analysis and initialization codes, and the coarse-mesh and fine-mesh dynamic prediction models. Both models are a three dimensional, primitive equation model containing the essential moist physics for simulating and forecasting mesoscale convective processes in the atmosphere. The modeling system is currently implemented at the Applied Meteorology Unit, Kennedy Space Center. Two procedures involving the synthetic relative humidity to define the model initial moisture fields are considered. It is proposed to perform several short-range (approximately 6 hours) comparative coarse-mesh simulation experiments with and without the synthetic data. They are aimed at revealing the model sensitivities should allow us both to refine the specification of the observational requirements, and to develop more accurate and efficient objective analysis schemes. The goal is to advance the MASS (Mesoscal Atmospheric Simulation System) modeling expertise so that the model output can provide reliable guidance for thunderstorm forecasting.

Chang, Chia-Bo↗
NASA NTRS1996

Verification and implementation of microburst day potential index (MDPI) and wind INDEX (WINDEX) forecasting tools at Cape Canaveral Air Station

This report details the research, development, utility, verification and transition on wet microburst forecasting and detection the Applied Meteorology Unit (AMU) did in support of ground and launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS). The unforecasted wind event on 16 August 1994 of 33.5 ms-1 (65 knots) at the Shuttle Landing Facility raised the issue of wet microburst detection and forecasting. The AMU researched and analyzed the downburst wind event and determined it was a wet microburst event. A program was developed for operational use on the Meteorological Interactive Data Display System (MIDDS) weather system to analyze, compute and display Theta(epsilon) profiles, the microburst day potential index (MDPI), and wind index (WINDEX) maximum wind gust value. Key microburst nowcasting signatures using the WSR-88D data were highlighted. Verification of the data sets indicated that the MDPI has good potential in alerting the duty forecaster to the potential of wet microburst and the WINDEX values computed from the hourly surface data do have potential in showing a trend for the maximum gust potential. WINDEX should help in filling in the temporal hole between the MDPI on the last Cape Canaveral rawinsonde and the nowcasting radar data tools.

Wheeler, Mark↗
NASA NTRS2010

A 311-GHz Fundamental Oscillator Using InP HBT Technology

This oscillator uses a single-emitter 0.3- m InP heterojunction bipolar transistor (HBT) device with maximum frequency of oscillation (fmax) greater than 500 GHz. Due to high conductor and substrate losses at submillimeterwave frequencies, a primary challenge is to efficiently use the intrinsic device gain. This was done by using a suitable transmission-line media and circuit topology. The passive components of the oscillator are realized in a twometal process with benzocyclobutene (BCB) used as the primary transmission line dielectric. The circuit was designed using microstrip transmission lines. The oscillator is implemented in a common-base topology due to its inherent instability, and the design includes an on-chip resonator, outputmatching circuitry, and an injection-locking port, the port being used to demonstrate the injection-locking prin ciple. A free-running frequency of 311.6 GHz has been measured by down-converting the signal. Ad di tionally, injection locking has been successfully demonstrated with up to 17.8 dB of injection-locking gain. The injection-locking reference signal is generated using a 2 20 GHz frequency synthesizer, followed by a doubler, active tripler, a W-band amplifier, and then a passive tripler. Therefore, the source frequency is multiplied 18 times to obtain a signal above 300 GHz that can be used to injection lock the oscillator. Measurement shows that injection locking has improved the phase noise of the oscillator and can be also used for synchronizing a series of oscillators. A signal conductor is implemented near the BCP -InP interface and the topside of the BCB layer is fully metallized as a signal ground. Because the fields are primarily constrained in the lower permittivity BCB region, this type of transmission line is referred to as an inverted microstrip. In addition, both common-emitter and commonbase circuits were investigated to determine optimum topology for oscillator design. The common -base topology required smaller amount of feedback than the common-emitter design, therefore preserving device gain, and was chosen for the oscillator design. The submillimeter-wave region offers several advantages for sensors and communication systems, such as high resolution and all-weather imaging due to the short-wavelength, and improved communication speeds by access to greater frequency bandwidth. This oscillator circuit is a prototype of the first HBT oscillator operating above 300 GHz. Additional development is necessary to increase the output power of the circuit for radar and imaging applications.

Gaier, Todd↗
NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗