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NASA NTRS2015

NASA's Meteoroid Environments Office's Response to Three Significant Bolide Events Over North America

Being the only U.S. Government entity charged with monitoring the meteor environment, the Meteoroid Environment Office has deployed a network of all sky and wide field meteor cameras, along with the appropriate software tools to quickly analyze data from these systems. However, the coverage of this network is still quite limited, forcing the incorporation of data from other cameras posted to the internet in analyzing many of the fireballs reported by the public and media. A procedure has been developed that determines the analysis process for a given fireball event based on the types and amount of data available. The differences between these analysis process will be explained and outlined by looking at three bolide events, all of which were large enough to produce meteorites. The first example is an ideal event - a bright meteor that occurred over NASA's All Sky Camera Network on August 2, 2014. With clear video of the event from various angles, a high-accuracy trajectory, beginning and end heights, orbit and approximate brightness/size of the event are able to be found very quickly using custom software. The bolide had the potential to have dropped meteorites, so dark flight analysis and modeling was performed, allowing potential fall locations to be mapped as a function of meteorite mass. The second case study was a bright bolide that occurred November 3, 2014 over West Virginia. This was just north of the NASA southeastern all-sky network, and just south of the Ohio-Pennsylvania network. This case study showcases the MEO's ability to use social media and various internet sources to locate videos of the event from obscure sources (including the Washington Monument) for anything that will permit a determination of a basic trajectory and fireball light curve The third case study will highlight the ability to use doppler weather radar in helping locate meteorites, which enable a definitive classification of the impactor. The input data and analysis steps differ for each case study, but the goals remain the same - a trajectory, orbit, and mass estimate for the bolide within hours of the event, and, for events with a high probability of producing meteorites, a location of the strewn field within a day.

Blaauw, Rhiannon C.↗
NASA NTRS2015

Odyssey Mars Orbiter - Thirteen Years of On-Orbit Navigation

The Odyssey spacecraft has been in Mars orbit since October 24, 2001 and has nearly completed 61,490 orbits. Navigation operational objectives include the following: Control the local mean solar time for science observations; for most of the mission, this varied from 3:45 pm to 5:20 pm. Currently, an orbit trim maneuver planned for November 10, 2015 will place Odyssey at 6:45 pm/6:45 am at equator crossings in order to observe early morning ground frost, fog and clouds. Initially, Odyssey was late by 42 minutes for an over-flight of the critical seven minutes of Phoenix's entry, descent and landing (EDL). Odyssey was successfully positioned for this over-flight using the Delta V from angular momentum desaturations (AMD). Similar results for the Mars Science Laboratory's EDL and Comet Siding Spring's minimum risk location will be presented. Odyssey has and continues to relay significant quantities of rover data. Navigation successfully models frequent AMD Delta Vs in order to generate accurate sixty-day trajectory predictions; a typical timing error is 25 seconds after 60 days. However, unexpected events, such as safe-mode entries with their larger and more frequent thrusting, severely impact that trajectory accuracy. Impacted trajectories can have timing errors ranging from a few minutes to ten-to-fifteen minutes after sixty-days. Other analyses (briefly stated) include: a) the offset of the orbital ground track pattern after an initial cycle of 30 days or 362 orbits and b) an operations environment of continuous thrusting if/when one of the three remaining reaction wheels fails.

trajectory accuracy↗
NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During early conceptual design of complex systems, speed and accuracy are often at odds with one another. While many characteristics of the design are fluctuating rapidly during this phase there is nonetheless a need to acquire accurate data from which to down-select designs as these decisions will have a large impact upon program life-cycle cost. Therefore enabling the conceptual designer to produce accurate data in a timely manner is tantamount to program viability. For conceptual design of launch vehicles, trajectory analysis and optimization is a large hurdle. Tools such as the industry standard Program to Optimize Simulated Trajectories (POST) have traditionally required an expert in the loop for setting up inputs, running the program, and analyzing the output. The solution space for trajectory analysis is in general non-linear and multi-modal requiring an experienced analyst to weed out sub-optimal designs in pursuit of the global optimum. While an experienced analyst presented with a vehicle similar to one which they have already worked on can likely produce optimal performance figures in a timely manner, as soon as the "experienced" or "similar" adjectives are invalid the process can become lengthy. In addition, an experienced analyst working on a similar vehicle may go into the analysis with preconceived ideas about what the vehicle's trajectory should look like which can result in sub-optimal performance being recorded. Thus, in any case but the ideal either time or accuracy can be sacrificed. In the authors' previous work a tool called multiPOST was created which captures the heuristics of a human analyst over the process of executing trajectory analysis with POST. However without the instincts of a human in the loop, this method relied upon Monte Carlo simulation to find successful trajectories. Overall the method has mixed results, and in the context of optimizing multiple vehicles it is inefficient in comparison to the method presented POST's internal optimizer functions like any other gradient-based optimizer. It has a specified variable to optimize whose value is represented as optval, a set of dependent constraints to meet with associated forms and tolerances whose value is represented as p2, and a set of independent variables known as the u-vector to modify in pursuit of optimality. Each of these quantities are calculated or manipulated at a certain phase within the trajectory. The optimizer is further constrained by the requirement that the input u-vector must result in a trajectory which proceeds through each of the prescribed events in the input file. For example, if the input u-vector causes the vehicle to crash before it can achieve the orbital parameters required for a parking orbit, then the run will fail without engaging the optimizer, and a p2 value of exactly zero is returned. This poses a problem, as this "non-connecting" region of the u-vector space is far larger than the "connecting" region which returns a non-zero value of p2 and can be worked on by the internal optimizer. Finding this connecting region and more specifically the global optimum within this region has traditionally required the use of an expert analyst.

Dees, Patrick D.↗
NASA NTRS2016

Cassini Maneuver Experience Through the Last Icy Satellite Targeted Flybys of the Mission

The Cassini spacecraft will reach its spectacular end-of-mission in September 2017, after having spent a successful twenty years in space gathering invaluable scientific data about Saturn, its rings, and moons. Cassini has flown the most complex gravity-assist trajectory ever designed, which requires frequent maneuvering to achieve the desired targets. After so many years in operation the propellant is starting to dwindle, making it of paramount importance that the maneuvers be designed to prioritize preserving propellant. This paper highlights the strategies for 50 planned maneuvers during twelve Titan flybys and the last Dione and Enceladus flybys of the mission.

Hernandez, Sonia↗
NASA NTRS2021

A Machine Learning Approach to Predict Aircraft Landing Times using Mediated Predictions from Existing Systems

We developed a novel approach for predicting the landing time of airborne flights in real-time operations. The first step predicts a landing time by using mediation rules to select from among physics-based predictions (relying on the expected flight trajectory) already available in real time in the Federal Aviation Administration System Wide Information Management system data feeds. The second step uses a machine learning model built upon the mediated predictions. The model is trained to predict the error in the mediated prediction, using features describing the current state of an airborne flight. These features are calculated in real time from a relatively small number of data elements that are readily available for airborne flights. Initial results based on five months of data at six large airports demonstrate that incorporating a machine learning model on top of the mediated physics-based prediction can lead to substantial additional improvements in prediction quality.

Machine learning↗
NASA NTRS2021

A Machine Learning Approach to Predict Aircraft Landing Times using Mediated Predictions from Existing Systems

We developed a novel approach for predicting the landing time of airborne flights in real-time operations. The first step predicts a landing time by using mediation rules to select from among physics-based predictions (relying on the expected flight trajectory) already available in real time in the Federal Aviation Administration System Wide Information Management system data feeds. The second step uses a machine learning model built upon the mediated predictions. The model is trained to predict the error in the mediated prediction, using features describing the current state of an airborne flight. These features are calculated in real time from a relatively small number of data elements that are readily available for airborne flights. Initial results based on five months of data at six large airports demonstrate that incorporating a machine learning model on top of the mediated physics-based prediction can lead to substantial additional improvements in prediction quality.

Machine learning↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

SU-D-18C-01: A Novel 4D-MRI Technology Based On K-Space Retrospective Sorting

Purpose: Current 4D-MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D-MRI based on k-space retrospective sorting. Methods: An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k-space data for 4D-MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) and image acquisition starting-phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k-space data, with respiratory signal and acquisition time for each k-space data line recorded simultaneously. K-space data was re-sorted based on respiratory phases. To evaluate 4D-MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross-correlation coefficient(CC) are calculated. Finally, phase-sharing sliding window technique was applied to investigate the feasibility of generating ultra-fast 4D-MRI. Result: Cp increased with NR(Cp=100*[1-exp(-0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely-proportional to Lb (r=0.97), but independent of other factors. 4D-MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image-based sorting 4D-MRI. Ultra-fast 4D-MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase-sharing sliding window technique. Conclusions: A novel 4D-MRI technology based on k-space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D-MRI technique for many radiation therapy applications. NIH (1R21CA165384-01A1)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Diagnosing heterogeneous dynamics in single-molecule/particle trajectories with multiscale wavelets

In this study, we describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large data sets generated in single-molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistically adaptive universal thresholding, whose advantage is to avoid a single arbitrary threshold that might conceal individual variability across populations. How to implement this multiscale method is described, focusing on local confined diffusion separated by transient transport periods or hopping events, with three specific examples: in cell biology, biotechnology, and glassy colloid dynamics. The discussion is generalized within the framework of continuous time random walk. This computationally efficient method can run routinely on hundreds of millions of data points analyzed within an hour on a desktop personal computer.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Simulations of Hayabusa2 Atmospheric Entry and Comparisons with Data from the Imaging Campaign

Results from flow and radiation simulations for the Hayabusa2 Sample Return Capsule (SRC) along its best-estimated trajectory (BET) are presented. Flow fields are first computed at several points along the best-estimated trajectory for a freestream consisting of N2, O2, Ar, CO2, and H2O; the last three are trace species in Earth’s atmosphere. The thermal response of an assumed ablative material is estimated and flow fields are recomputed at each time point with modified surface temperature distributions. The spectral radiance, from the combination of an aeroheated capsule and the high-temperature shock layer around it, is computed on an imaging plane for a given view angle and slant range at each time point. The radiance is transported through the intervening atmosphere between the Hayabusa2 SRC and the observing aircraft and upon integration over solid angle representing the field of view of the instruments converted to a spectral irradiance. The spectral irradiance is convolved with the instrument function to obtain results that can be directly compared with measurement. Fair to good comparisons with measurements required shifting the time coordinate of measurements by 7.5 s. The disagreement between prediction and measurement is substantial after about 72.5 s along the BET. Additional computations seem to support the idea of flow transition over the capsule.

Atmospheric entry↗
NASA NTRSDate not supplied

Simulations of Hayabusa2 Atmospheric Entry and Comparisons with Data from the Imaging Campaign

Results from flow and radiation simulations for the Hayabusa2 Sample Return Capsule (SRC) along its best-estimated trajectory (BET) are presented. Flow fields are first computed at several points along the best-estimated trajectory for a freestream consisting of N2, O2, Ar, CO2, and H2O; the last three are trace species in Earth’s atmosphere. The thermal response of an assumed ablative material is estimated and flow fields are recomputed at each time point with modified surface temperature distributions. The spectral radiance, from the combination of an aeroheated capsule and the high-temperature shock layer around it, is computed on an imaging plane for a given view angle and slant range at each time point. The radiance is transported through the intervening atmosphere between the Hayabusa2 SRC and the observing aircraft and upon integration over solid angle representing the field of view of the instruments converted to a spectral irradiance. The spectral irradiance is convolved with the instrument function to obtain results that can be directly compared with measurement. Fair to good comparisons with measurements required shifting the time coordinate of measurements by 7.5 s. The disagreement between prediction and measurement is substantial after about 72.5 s along the BET. Additional computations seem to support the idea of flow transition over the capsule.

Atmospheric entry↗
DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗
DOE OSTI2016

Effects of downscaled high-resolution meteorological data on the PSCF identification of emission sources

The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizes (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Assimilation of Stratospheric Meteorological and Constituent Observations: A Review

This talk reviews the assimilation of meteorological and constituent observations of the stratosphere. The first efforts to assimilate observations into stratospheric models were during the early 1980s, and a number of research studies followed during the next decade. Since the launch of the Upper Atmospheric Research Satellite (UARS) in 1991, model-assimilated data sets of the stratospheric meteorological state have been routinely available. These assimilated data sets were critical in bringing together observations from the different instruments on UARS as well as linking UARS observations to measurements from other platforms. Using trajectory-mapping techniques, meteorological assimilation analyses are, now, widely used in the analysis of constituent observations and have increased the level of quantitative study of stratospheric chemistry and transport. During the 1990s the use of winds and temperatures from assimilated data sets became standard for offline chemistry and transport modeling. variability in middle latitudes. The transport experiments, however, reveal a set of shortcomings that become obvious as systematic errors are integrated over time. Generally, the tropics are not well represented, mixing between the tropics and middle latitudes is overestimated, and the residual circulation is not accurate. These shortcomings reveal underlying fundamental challenges related to bias and noise. Current studies using model simulation and data assimilation in controlled experimentation are highlighting the issues that must be addressed if assimilated data sets are to be convincingly used to study interannual variability and decadal change. observations. The primary focus has been on stratospheric ozone, but there are efforts that investigate a suite of reactive chemical constituents. Recent progress in ozone assimilation shows the potential of assimilation to contribute to the validation of ozone observations and, ultimately, the retrieval of ozone profiles from space-based radiance measurements. Assimilated data sets provide accurate analyses of synoptic and planetary Scale At the same time, stratospheric assimilation is evolving to include constituent

Rood, Richard B.↗
NASA NTRS1974

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 14

Tests were conducted in wind tunnels during April and May 1973, on a 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 degrees to +8 degrees. The isolated orbiter was tested at angles of attack from -15 degrees to +40 degrees and angles of sideslip from -10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data were obtained for upper and lower wing surfaces and left and right vertical tail surfaces.

Spangler, R. H.↗
NASA NTRS2012

Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments

Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.

Lee, Paul U.↗
DOE OSTI2019

Quantum Regge trajectories and the Virasoro analytic bootstrap

Every conformal field theory (CFT) above two dimensions contains an infinite set of Regge trajectories of local operators which, at large spin, asymptote to “double-twist” composites with vanishing anomalous dimension. In two dimensions, due to the existence of local conformal symmetry, this and other central results of the conformal bootstrap do not apply. We incorporate exact stress tensor dynamics into the CFT 2 analytic bootstrap, and extract several implications for AdS 3 quantum gravity. Our main tool is the Virasoro fusion kernel, which we newly analyze and interpret in the bootstrap context. The contribution to double-twist data from the Virasoro vacuum module defines a “Virasoro Mean Field Theory” (VMFT); its spectrum includes a finite number of discrete Regge trajectories, whose dimensions obey a simple formula exact in the central charge c and external operator dimensions. We then show that VMFT provides a baseline for large spin universality in two dimensions: in every unitary compact CFT 2 with c > 1 and a twist gap above the vacuum, the double-twist data approaches that of VMFT at large spin ℓ. Corrections to the large spin spectrum from individual non-vacuum primaries are exponentially small in √ℓ for fixed c. We analyze our results in various large c limits. Further applications include a derivation of the late-time behavior of Virasoro blocks at generic c; a refined understanding and new derivation of heavy-light blocks; and the determination of the cross-channel limit of generic Virasoro blocks. We deduce non-perturbative results about the bound state spectrum and dynamics of quantum gravity in AdS 3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗