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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Commissioning the DIRC Detector and Searching for Axion-like Particles at GlueX

This thesis centers around problems in the study of the strong nuclear force. The GlueX DIRC, a Cherenkov radiation-based detector, was proposed to upgrade the particle identification capability of the GlueX experiment, which aims to perform quantitative tests of Quantum Chromodynamics in the nonperturbative regime by searching for and studying hybrid mesons. This thesis describes the construction, commissioning, reconstruction, and calibration of the GlueX DIRC detector. Originally proposed to solve the strong CP problem, axions and axion-like particles are hypothetical pseudoscalar particles found in many proposed extensions to the Standard Model of particle physics. This thesis presents a search for photoproduction of axion-like particles using data in photon-proton interactions collected by the GlueX experiment at Jefferson Laboratory in the $\gamma\gamma$ and $\pi^+\pi^-\pi^0$ final states of the axion-like particles. In addition, the Monte Carlo modeling of the strong interaction at low energies leads to challenges known as the event generator tuning problem. This thesis presents a novel approach to the Monte Carlo event generator tuning problem using Bayesian optimization.

Yang, Yunjie↗
DOE OSTI2025

Identifying Urban Pluvial Frequency Flooding Hotspots Using the Topographic Control Index and Remote Sensing Radar Images for Early Warning Systems

Identifying areas that frequently experience post-rainfall ponding is essential for effective flood mitigation and planning. This study integrates Sentinel-1 radar imagery and the Topographic Control Index (TCI) to identify 378 flood-prone urban depressions in Beaumont, Texas. Out of 159 major rainfall events, only six had Sentinel-1 radar imagery acquired within six hours of peak rainfall, and these were used to generate the flood frequency map; the ground-based flood sensor data were used to verify that these selected events corresponded to actual peak rainfall and to validate radar-detected water pixels. Validation results showed 100% precision, 70.87% recall, an F1-score of 82.95%, and 71.32% overall accuracy. Approximately 84% of medium-to-high TCI depressions overlapped with Beaumont’s two-year inundation map, confirming a strong relationship between TCI and observed flooding. A total of 124 depressions retained significant water, and after excluding 25 engineered detention ponds, 99 natural depressions remained flood vulnerable. Among these, 74 depressions with medium or high TCI were identified as the highest-priority nuisance flooding hotspots. The results demonstrate that combining TCI with radar imagery provides a reliable and cost-effective approach for identifying areas prone to frequent urban ponding. This framework supports practical decision-making for drainage improvements, hotspot identification, and early-warning system development in urban flood-prone regions.

Sentinel-1 radar imagery↗
DOE OSTI2025

Introduction, Investigation, and Experimental Validation of a Novel Passive Neutron Spectrometer

Unfolding neutron energy spectra are instrumental for determining personal health effects and calculating dose received. This area of study is heavily researched, and Lawrence Livermore National Laboratory (LLNL) is investigating a passive neutron spectrometer for the purpose of acquiring the information needed to determine personnel dose in the event of a criticality accident. A part of this investigation is presented in this article through the examination of four experimental detector responses (DRs). These four DRs were acquired in the presence of 252 Cf, AmBe, GODIVA, and National Ignition Facility (NIF) neutron sources. An algorithm developed at LLNL was used to unfold the neutron fluence from each of the four DRs, and subsequently, fluence-to-dose conversion factors provided by the American National Standards Institute were used to calculate dose. Additionally, a multistep unfolding process was developed and employed to calculate the effects of both direct (from the source) and indirect (from room return) neutrons. The average error when unfolding the direct DR was less than 8%. The dose from 252 Cf was predicted with only 8% error. The multistep approach allowed for the identification of the low-energy neutrons in the 252 Cf, AmBe, and NIF DRs.

Nuclear Criticality Safety Program (NCSP)↗
NASA NTRS2011

Ion Composition of Titan's Ionosphere Observed During T9 Magnetotail Crossing

In a recent paper, Sittler et al., (2010) presented new results on the T9 encounter by the Cassini spacecraft when it passed through Titan s induced magnetotail. Two crossings were observed, but the first crossing, event 1, is thought to be out flowing ionosphere plasma. T9 is ideal for CAPS IMS probing of the ionosphere, since the ion densities at the higher altitudes of the T9 flyby approx. 10,000 km, allows measurements to be made down to 1 eV without saturating its detectors. Sittler et al., (2010) reported possible detection of NH4+ ions, but favored the detection of CH5+ and C2H5+ ions. In this report we investigate both the medium mass resolution (straight through (ST)) and high mass resolution (linear electric field (LEF)) composition data from the Cassini Plasma Spectrometer (CAPS) Ion Mass Spectrometer (IMS). We present a more in depth analysis of the composition data and make comparisons with ionospheric models including nitrogen chemistry such as that by Vuitton et al. (2007). The LEF data does not support NH4+ identification, but favors a CH5+ and C2H5+ identification, but also molecular ions C2N+ and CH2NH2+ are chemically allowed possibilities.

Sittler, Edward↗
NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, 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 will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed 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 l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗
NASA NTRS2006

A Burst and Simultaneous Short-Term Pulsed Flux Enhancement From The Magnetar Candidate 1E 1048.1-5937

We report on the 2004 June 29 X-ray burst detected from the direction of the AXP 1E 1048.1-5937 using the RXTE. We find a simultaneous increase of approx. 3.5 times the quiescent value in the 2-10 keV pulsed flux of 1E 1048.1-5937 during the tail of the burst, which identifies the AXP as the burst s origin. The burst was overall very similar to the two others reported from the direction of this source in 2001. The unambiguous identification of 1E 1048.1-5937 as the burster here confirms that it was the origin of the 2001 bursts as well. The epoch of the burst peak was very close to the arrival time of 1E 1048.1-5937 s pulse peak. The burst exhibited significant spectral evolution, with the trend going from hard to soft. Although the average spectrum of the burst was comparable in hardness (Lambda approx. 1.6) to those,of the 2001 bursts, the peak of this burst was much harder (Lambda approx. 0.3). During the 11 days following the burst, the AXP was observed further with RXTE, XMM-Newton, and Chandra. Pre- and post-burst observations revealed no change in the total flux or spectrum of the quiescent emission. Comparing all three bursts detected thus far from this source, we find that this event was the most fluent (>3.3 x 10(exp-8 ergs/sq cm) in the 2-20 keV band), had the highest peak flux (59+/-9 x 10(exp -10)ergs/s/sq cm) in the 2-20 keV band), and had the longest duration (>699 s). The long duration of the burst difFerentiates it from SGR bursts, which have typical durations of approx.0.1 s. Bursts that occur preferentially at pulse maximum, have fast rises, and long X-tails containing the majority of the total burst energy have been seen uniquely from AXPs. The marked differences between AXP and SGRs bursts may provide new clues to help understand the physical differences between these objects.

Gavriil, Fotis P.↗
NASA NTRS2018

Planetary Candidates from K2 Campaign 16

Given that Campaign 16 of the K2 mission is one of just two K2 campaigns observed so far in "forward-facing" mode, which enables immediate follow-up observations from the ground, we present a catalog of interesting targets identified through photometry alone. Our catalog includes 30 high-quality planet candidates (showing no signs of being non-planetary in nature), 48 more ambiguous events that may be either planets or false positives, 164 eclipsing binaries, and 231 other regularly periodic variable sources. We have released light curves for all targets in C16 and have also released system parameters and transit vetting plots for all interesting candidates identified in this paper. Of particular interest is a candidate planet orbiting the bright F dwarf HD 73344 (V = 6.9, K = 5.6) with an orbital period of 15 days. If confirmed, this object would correspond to a 2.56 +/- 0.18 R⊕ planet and would likely be a favorable target for radial velocity characterization. This paper is intended as a rapid release of planet candidates, eclipsing binaries, and other interesting periodic variables to maximize the scientific yield of this campaign, and as a test run for the upcoming TESS mission, whose frequent data releases call for similarly rapid candidate identification and efficient follow up.

bright F dwarf↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
NASA NTRS1991

Design, building, and testing of the postlanding systems for the assured crew return vehicle

The design, building, and testing of the postlanding support systems for a water-landing Assured Crew Return Vehicle (ACRV) are presented. One ACRV will be permanently docked to Space Station Freedom, fulfilling NASA's commitment to Assured Crew Return Capability in the event of an accident or illness. The configuration of the ACRV is based on an Apollo Command Module (ACM) derivative. The 1990-1991 effort concentrated on the design, building, and testing of a one-fifth scale model of the egress and stabilization systems. The objective was to determine the feasibility of (1) stabilizing the ACM out of the range of motions that cause seasickness and (2) the safe and rapid removal of a sick or injured crew member from the ACRV. The development of the ACRV postlanding systems model was performed at the University of Central Florida with guidance from the Kennedy Space Center ACRV program managers. Emphasis was placed on four major areas. First was design and construction of a one-fifth scale model of the ACM derivative to accommodate the egress and stabilization systems for testing. Second was the identification of a water test facility suitable for testing the model in all possible configurations. Third was the construction of the rapid egress mechanism designed in the previous academic year for incorporation into the ACRV model. The fourth area was construction and motion response testing of the attitude ring and underwater parachute systems.

Hosterman, Kenneth C.↗
NASA NTRS2015

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

MODIS VIIRS↗
NASA NTRS2015

The Archaeology of Little Wood Creek: New Chronometric Evidence

This study reports on the establishment of viable dates for several major cultural components at the Little Wood Creek site on the upper Hudson in Fort Edward, New York. The original excavation in the mid-1980s (Grossman et al. 1990) resulted in the identification of two major periods of occupation, a deeply buried Transitional period sequence of living floors, and closer to the surface, and separated by circa five feet of sterile alluvium, a series of Late Woodland period pits and features. Both are overlain by the discovery of the southern bastion of Revolutionary War-era Fort Edward. Ambiguities in the original bulk radiocarbon dating of the site left it in chronological limbo with widely divergent determinations for both prehistoric occupation periods. New AMS dates from 10 samples, four Transitional period and six Late Woodland period assays, both refined the absolute chronology of the site complex and clarified several major issues in the cultural and environmental history of the region. Together, these two sets of dates, combined with recent high resolution environmental sequences, provide sufficient resolution to correlate the newly defined periods of occupation with major events in the pollen and climate record of eastern New York State.

chronology↗
NASA NTRS2001

Supernova 1998bw In ESO 184-G82

Over the wavelength range 390-750 nm, we measure intrinsic linear polarization of 0.53 +/- 0.08 percent at position angle 49 +/- 3 deg, after correcting for Galactic interstellar polarization using the star HD 184100, which has polarization of 0.75 +/- 0.01 percent at p.a. 176.5 +/- 2.5 deg. This measured interstellar polarization is consistent with the Galactic extinction in this direction, estimated to be E(B-V) = 0.059 from IRAS maps, or E(B-V) = 0.079 from 21-cm H I. Interstellar polarization in the host galaxy ESO 184-G82 is expected to be negligible based on the relative absence of Na I D absorption at z = 0.00841 +/- 0.00005, the redshift of the environment of the supernova from narrow H II region emission lines in its spectrum. Polarization appears highest in between emission features in the total flux spectrum, which strengthens the interpretation of the polarization as intrinsic to the supernova. This modest polarization is less than that of some type-II supernovae, but greater than that of type-Ia supernovae, which are generally unpolarized. This supports the interpretation of SN 1998bw, a peculiar type-Ic supernova, as a core-collapse event in which the observed polarization is due to moderate asymmetry in either the photosphere of the ejecta or an overlying scattering envelope. However, this result does not strongly constrain arguments about whether some supernovae emit gamma-ray bursts, since such emission may come from a mildly relativistic shock associated with the radio emission and above the optical photosphere, without any requirements on beaming or orientation." A. V. Filippenko, University of California at Berkeley, comments on the total flux spectrum obtained above: "The spectrum most closely resembles those of the peculiar SN 1997ef, but perhaps evolving more slowly. It is not typical of type-Ic supernovae; indeed, the spectrum does not match any of the known spectral classes, but perhaps 'peculiar type Ic' is the best choice at this time. The object appears to be starting a transition to the nebular phase, but identifications of the broad emission features are uncertain. The feature at 650 nm is probably [Fe III], as is the one at 455 nm (perhaps with some contribution from Mg I]). That at 590 nm may be a mixture of [Co III] and Na D. The strongest feature, at 545 nm, may consist of Fe, Co, and Ti lines."

Kay, L. E.↗
NASA NTRS2021

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗
DOE OSTI2024

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗
NASA NTRS2010

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

Rohloff, Kurt↗
NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗
NASA NTRS1992

Development of a residual acceleration data reduction and dissemination plan

A major obstacle in evaluating the residual acceleration environment in an orbiting space laboratory is the amount of data collected during a given mission: gigabytes of data will be available as SAMS units begin to fly regularly. Investigators taking advantage of the reduced gravity conditions of space should not be overwhelmed by the accelerometer data which describe these conditions. We are therefore developing a data reduction and analysis plan that will allow principal investigators of low-g experiments to create experiment-specific residual acceleration data bases for post-flight analysis. The basic aspects of the plan can also be used to characterize the acceleration environment of earth orbiting laboratories. Our development of the reduction plan is based on the following program of research: the identification of experiment sensitivities by order of magnitude estimates and numerical modelling; evaluation of various signal processing techniques appropriate for the reduction, supplementation, and dissemination of residual acceleration data; and testing and implementation of the plan on existing acceleration data bases. The orientation of the residual acceleration vector with respect to some set of coordinate axes is important for experiments with known directional sensitivity. Orientation information can be obtained from the evaluation of direction cosines. Fourier analysis is commonly used to transform time history data into the frequency domain. Common spectral representations are the amplitude spectrum which gives the average of the components of the time series at each frequency and the power spectral density which indicates the power or energy present in the series per unit frequency interval. The data reduction and analysis scheme developed involves a two tiered structure to: (1) identify experiment characteristics and mission events that can be used to limit the amount of accelerator data an investigator should be interested in; and (2) process the data in a way that will be meaningful to the experiment objectives. A general outline of the plan is given.

Rogers, Melissa J. B.↗
NASA NTRS1998

Deterministic Reconfigurable Control Design for the X-33 Vehicle

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. Four reconfigurable control design methods were investigated for the X-33 vehicle: Redistributed Pseudo-Inverse, General Constrained Optimization, Automated Failure Dependent Gain Schedule, and an Off-line Nonlinear General Constrained Optimization. The Off-line Nonlinear General Constrained Optimization approach was chosen for implementation on the X-33. Two example failures are shown, a right outboard elevon jam at 25 deg. at a Mach 3 entry condition, and a left rudder jam at 30 degrees. Note however, that reconfigurable control laws have been designed for the entire flight envelope. Comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

Wagner, Elaine A.↗