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NASA NTRSDate not supplied

Application of Tisserand's Criterion and the Lidov-Kozai Effect to STORM's Trajectory Design

The Solar-Terrestrial Observer for the Response of the Magnetosphere (STORM) concept recently completed its Phase A design funded by NASA's Heliophysics Medium-class Explorers program. The mission design required a lunar gravity assist to insert the single spacecraft into a 30-Earth-radii circular geocentric science orbit inclined 90 degrees to the ecliptic. STORM's trajectory design leveraged several interesting gravitational effects from third bodies. This paper describes our application of Tisserand's criterion for finding feasible transfers and lunar gravity assist trajectories, and the Lidov-Kozai effect to design a maneuver-free science orbit optimization and decommissioning strategy.

tisserand criterion↗

DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation among the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗

DOE OSTI2018

Direct construction of optimized stellarator shapes. Part 1. Theory in cylindrical coordinates

The confinement of the guiding-centre trajectories in a stellarator is determined by the variation of the magnetic field strength $B$ in Boozer coordinates $(r,\unicode[STIX]{x1D703},\unicode[STIX]{x1D711})$ , but $B(r,\unicode[STIX]{x1D703},\unicode[STIX]{x1D711})$ depends on the flux surface shape in a complicated way. Here we derive equations relating $B(r,\unicode[STIX]{x1D703},\unicode[STIX]{x1D711})$ in Boozer coordinates and the rotational transform to the shape of flux surfaces in cylindrical coordinates, using an expansion in distance from the magnetic axis. A related expansion was done by Garren and Boozer ( Phys. Fluids B, vol. 3, 1991 a , 2805) based on the Frenet–Serret frame, which can be discontinuous anywhere the magnetic axis is straight, a situation that occurs in the interesting case of omnigenity with poloidally closed $B$ contours. Our calculation in contrast does not use the Frenet–Serret frame. The transformation between the Garren–Boozer approach and cylindrical coordinates is derived, and the two approaches are shown to be equivalent if the axis curvature does not vanish. The expressions derived here help enable optimized plasma shapes to be constructed that can be provided as input to VMEC and other stellarator codes, or to generate initial configurations for conventional stellarator optimization.

Physics↗

NASA NTRS1984

Approximate solutions to minimax optimal control problems for aeroassisted orbital transfer

The maneuver considered in the present investigation involves the coplanar transfer of a spacecraft from a high earth orbit (HEO) to a low earth orbit (LEO). HEO can be a geosynchronous earth orbit (GEO). The basic concept utilized involves the hybrid combination of propulsive maneuvers in space and aerodynamic maneuvers in the sensible atmosphere. The considered type of flight is also called synergetic space flight. With respect to the atmospheric part of the maneuver, trajectory control is achieved by means of lift modulation. The Bolza problem of optimal control is stated, and the first-order optimality conditions for this problem are given. The one-arc approach, the two-arc approach, and the three-subarc approach are discussed. Attention is given to the Chebyshev problem of optimal control, details concerning aeroassisted orbital transfer (AOT), AOT optimization problems, and numerical experiments.

Miele, A.↗

DOE OSTI2018

Mass, momentum, and energy transfer in supersonic aerosol deposition processes

Aerosol deposition (AD) can lead to the formation of dense coatings via deposition of particles from a gas flow; in AD the aerosol is passed through a converging-diverging nozzle, facilitating inertial particle impaction on a desired substrate at supersonic particle velocities. Unique from thermal spray methods, AD can be applied near room temperature and unique from cold spray, in AD the aerosol is typically at atmospheric pressure upstream of the nozzle. Though AD has been successfully demonstrated previously, a number of aspects related to particle motion in AD systems remain poorly understood. In this work, we simulated compressible flow field profiles and particle trajectories for typical AD working conditions for a slit type converging-diverging nozzle with a planar substrate. In examining the fluid flow profile, we show that the velocity and pressure profiles, as well as the shock structure are sensitive to the upstream and downstream operating pressures of the nozzle. These ultimately affect particle impaction speed. Importantly, in AD, the particle drag regime is dynamic; both particle Knudsen numbers and Mach numbers can vary by orders of magnitude. To aid particle trajectory simulations, we trained a neural network to predict the drag force on the particles based on existing experimental data, theoretical limits, and new direct simulation Monte Carlo (DMSC) results. The neural network based drag law, which depends upon both Mach and Knudsen numbers, shows better agreement with the DSMC simulation data than pre-existing correlations. With it, particle trajectory simulation results reveal that for a given particle density, there exists an optimal particle diameter to maximize particle impaction speed. We also find that in AD particles undergo size dependent inertial focusing, i.e. there is a particular particle diameter where the particle deposition linewidth is minimized. Particles smaller than this diameter are underfocused, and particles larger than this are overfocused, and hence have larger deposition linewidths in both cases. Using trajectory simulations, we additionally develop a framework that can be used to evaluate the position-dependent mass, momentum and kinetic energy fluxes to the deposition substrate for any aerosol size distribution function upstream the nozzle. It is shown for typical aerosol concentrations achievable in the laboratory, the kinetic energy flux can approach a magnitude normally observed in convective heat transfer with phase change, hence translational kinetic energy to thermal energy transfer in AD is likely the key contributor to the formation of dense coatings.

42 ENGINEERING↗

NASA NTRS1985

Energy management of three-dimensional minimum-time intercept

A real-time computer algorithm to control and optimize aircraft flight profiles is described and applied to a three-dimensional minimum-time intercept mission. The proposed scheme has roots in two well known techniques: singular perturbations and neighboring-optimal guidance. Use of singular-perturbation ideas is made in terms of the assumed trajectory-family structure. A heading/energy family of prestored point-mass-model state-Euler solutions is used as the baseline in this scheme. The next step is to generate a near-optimal guidance law that will transfer the aircraft to the vicinity of this reference family. The control commands fed to the autopilot (bank angle and load factor) consist of the reference controls plus correction terms which are linear combinations of the altitude and path-angle deviations from reference values, weighted by a set of precalculated gains. In this respect the proposed scheme resembles neighboring-optimal guidance. However, in contrast to the neighboring-optimal guidance scheme, the reference control and state variables as well as the feedback gains are stored as functions of energy and heading in the present approach. Some numerical results comparing open-loop optimal and approximate feedback solutions are presented.

Kelley, H. J.↗

NASA NTRS2022

Stability Analysis of Streaks Induced by Optimized Vortex Generators

Numerical computations are performed to investigate the potential for transition control in an axisymmetric boundary layer via fully realizable, streamwise stationary streaks induced by an azimuthally periodic array of surface mounted vortex generators (VGs). Previous work has shown that suitable streaks of this type can significantly reduce the growth of Mack’s second mode instabilities, but large streak amplitudes can make the flow susceptible to previously absent streak instabilities that can become the leading cause of transition. Here, we use the adjoint capabilities of the SU2 flow solver to optimize the VG shape to maximize the reduction in the growth of second-mode disturbances while also preventing the streak amplitudes from reaching large enough values to precipitate an earlier onset of transition via streak instabilities. The geometry and the freestream flow conditions are selected to match a relevant trajectory lo-cation from the HIFiRE-1 flight experiment. Results show that the optimized VGs can increase the mean streak amplitude by 117% with respect to a manually developed baseline design. The stability of this optimized basic state is analyzed via the plane-marching parabolized stability equations, predicting a fully laminar flow over the entire cone, or equivalently, yielding transition delay of 130% versus the 17% for the baseline VGs.

Boundary layer transition↗

NASA NTRS2022

Stability Analysis of Streaks Induced By Optimized Vortex Generators

Boundary layer transition↗

DOE OSTI2017

Dual-Polarity Ion Trap Mass Spectrometry: Dynamic Monitoring and Controlling Gas-phase Ion–Ion Reactions

A dual-polarity linear ion trap (LIT) mass spectrometer was developed in this study, and the method for simultaneously controlling and detecting cations and anions was proposed and realized in the LIT. With the application of an additional dipolar DC field on the ejection electrodes of an LIT, dual-polarity mass spectra could be obtained, which include both the mass-to-charge (m/z) ratio and charge polarity information of an ion. Compared with conventional method, the ion ejection and detection efficiency could also be improved by about one-fold. Furthermore, ion–ion reactions within the LIT could be dynamically controlled and monitored by manipulating the distributions of ions with opposite charge polarities. This method was then used to control and study the reaction kinetics of ion–ion reactions, including electron transfer dissociation (ETD) and charge inversion reactions. A dual-polarity collision-induced dissociation (CID) experiment was proposed and performed to enhance the sequence coverage of a peptide ion. Ion trajectory simulations were also carried out for concept validation and system optimization. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Reduced-order modeling on a near-term quantum computer

Quantum computing is an advancing area of research in which computer hardware and algorithms are developed to take advantage of quantum mechanical phenomena. In recent studies, quantum algorithms have shown promise in solving linear systems of equations as well as systems of linear ordinary differential equations (ODEs) and partial differential equations (PDEs). Reducedorder modeling (ROM) algorithms for studying fluid dynamics have shown success in identifying linear operators that can describe flowfields, where dynamic mode decomposition (DMD) is a particularly useful method in which a linear operator is identified from data. In this work, DMD is reformulated as an optimization problem to propagate the state of the linearized dynamical system on a quantum computer. This reformulation was chosen as a means of facilitating implementation on a near-term quantum computer. Quadratic unconstrained binary optimization (QUBO), a technique for optimizing quadratic polynomials in binary variables, allows for quantum annealing algorithms to be applied. A quantum circuit model (quantum approximation optimization algorithm, QAOA) is utilized to obtain predictions of the state trajectories. Results are shown for the quantum-ROM predictions for flow over a 2D cylinder at Re = 220 and flow over a NACA0009 airfoil at Re = 500 and α = 15°. The quantum-ROM predictions are found to depend on the number of bits utilized for a fixed point representation and the truncation level of the DMD model. Comparisons with DMD predictions from a classical computer algorithm are made, as well as an analysis of the computational complexity and prospects for future, more fault-tolerant quantum computers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Local Electric Field Effects on Water Dissociation in Bipolar Membranes Studied Using Core–Shell Catalysts

The local electric field strength is thought to affect the rate of water dissociation (WD) in bipolar membranes (BPMs) at the catalyst–nanoparticle surfaces. Here, we study core–shell nanoparticles, where the core is metallic, semiconducting, or insulating, to understand this effect. The nanoparticle cores were coated with a WD catalyst layer (TiO2 or HfO2) via atomic layer deposition (ALD), and the morphology was imaged with transmission electron microscopy. Irrespective of the core material, these core–shell catalysts displayed comparable WD overpotentials at optimal mass loading, despite the hypothesized differences in the electric field strength across the catalyst particle suggested by continuum electrostatic simulations. Substantial atomic interdiffusion between the core and shell was ruled out by X-ray absorption spectroscopy, X-ray photoelectron spectroscopy, and diffuse reflectance optical measurements. However, the optimal mass loading of catalyst was roughly 1 order of magnitude higher for the conductive and high dielectric core materials than for the low dielectric insulating cores. These findings are consistent with the hypothesis that electric field screening within the core material focuses the electric field drop between particles such that larger film thicknesses can be tolerated. Collectively, these data support the idea that it is the local electric field at the molecular level that controls proton-transfer rates and that the metal core/dielectric-shell constructs introduced here modulate that field. Further materials and synthetic design may enable optimization of the electric field strength across the proton-transfer trajectory at the material surface.

Sarma, Prasad V↗

DOE OSTI2021

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1970

Trajectory design for a Solar-Electric- Propulsion Mars high-data rate orbiter

Solar electric propulsion Mars high data rate orbiter trajectory design and analysis, including landing site selection and spacecraft parameters optimization

Sauer, C. G., Jr.↗

NASA NTRS1999

Human Mars Mission: Launch Window from Earth Orbit

The determination of orbital window characteristics is of major importance in the analysis of human interplanetary missions and systems. The orbital launch window characteristics are directly involved in the selection of mission trajectories, the development of orbit operational concepts, and the design of orbital launch systems. The orbital launch window problem arises because of the dynamic nature of the relative geometry between outgoing (departure) asymptote of the hyperbolic escape trajectory and the earth parking orbit. The orientation of the escape hyperbola asymptotic relative to the earth is a function of time. The required hyperbola energy level also varies with time. In addition, the inertial orientation of the parking orbit is a function of time because of the perturbations caused by the Earth's oblateness. Thus, a coplanar injection onto the escape hyperbola can be made only at a point in time when the outgoing escape asymptote is contained by the plane of parking orbit. Even though this condition may be planned as a nominal situation, it will not generally represent the more probable injection geometry. The general case of an escape injection maneuver performed at a time other than the coplanar time will involve both a path angle and plane change and, therefore, a delta V penalty. Usually, because of the delta V penalty the actual departure injection window is smaller in duration than that determined by energy requirement alone. This report contains the formulation, characteristics, and test cases for five different launch window modes for Earth orbit. These modes are: 1) One impulsive maneuver from a Highly Elliptical Orbit (HEO); 2) Two impulsive maneuvers from a Highly Elliptical Orbit (HEO); 3) One impulsive maneuver from a Low Earth Orbit (LEO); 4) Two impulsive maneuvers form LEO; and 5) Three impulsive maneuvers form LEO. The formulation of these five different launch window modes provides a rapid means of generating realistic parametric data for space exploration studies. Also the formulation provides vector and geometrical data sufficient for use as a good starting point in detail trajectory analysis based on calculus of variations, steepest descent, or parameter optimization program techniques.

Young, Archie↗

NASA NTRS2001

Human Exploration Missions Study Launch Window from Earth Orbit

The determination of orbital launch window characteristics is of major importance in the analysis of human interplanetary missions and systems. The orbital launch window characteristics are directly involved in the selection of mission trajectories, the development of orbit operational concepts, and the design of orbital launch systems. The orbital launch window problem arises because of the dynamic nature of the relative geometry between outgoing (departure) asymptote of the hyperbolic escape trajectory and the earth parking orbit. The orientation of the escape hyperbola asymptotic relative to earth is a function of time. The required hyperbola energy level also varies with time. In addition, the inertial orientation of the parking orbit is a function of time because of the perturbations caused by the Earth's oblateness. Thus, a coplanar injection onto the escape hyperbola can be made only at a point in time when the outgoing escape asymptote is contained by the plane of parking orbit. Even though this condition may be planned as a nominal situation, it will not generally represent the more probable injection geometry. The general case of an escape injection maneuver performed at a time other than the coplanar time will involve both a path angle and plane change and, therefore, a Delta(V) penalty. Usually, because of the Delta(V) penalty the actual departure injection window is smaller in duration than that determined by energy requirement alone. This report contains the formulation, characteristics, and test cases for five different launch window modes for Earth orbit. These modes are: (1) One impulsive maneuver from a Low Earth Orbit (LEO), (2) Two impulsive maneuvers from LEO, (3) Three impulsive maneuvers from LEO, (4) One impulsive maneuvers from a Highly Elliptical Orbit (HEO), (5) Two impulsive maneuvers from a Highly Elliptical Orbit (HEO) The formulation of these five different launch window modes provides a rapid means of generating realistic parametric data for space exploration studies. Also the formulation provides vector and geometrical data sufficient for use as a good starting point in detail trajectory analysis based on calculus of variations, steepest descent, or parameter optimization program techniques.

Young, Archie↗

NASA NTRS2010

The Applied Meteorology Unit: Nineteen Years Successfully Transitioning Research into Operations for America's Space Program

The Applied Meteorology Unit (AMU) provides technology transition and technique development to improve operational weather support to the Space Shuttle and the entire American space program. The AMU is funded and managed by NASA and operated by a contractor that provides five meteorologists with a diverse mix of advanced degrees, operational experience, and associated skills including data processing, statistics, and the development of graphical user interfaces. The AMU's primary customers are the U.S. Air Force 45th Weather Squadron at Patrick Air Force Base, the National Weather Service Spaceflight Meteorology Group at NASA Johnson Space Center, and the National Weather Service Melbourne FL Forecast Office. The AMU has transitioned research into operations for nineteen years and worked on a wide range of topics, including new forecasting techniques for lightning probability, synoptic peak winds,.convective winds, and summer severe weather; satellite tools to predict anvil cloud trajectories and evaluate camera line of sight for Space Shuttle launch; optimized radar scan strategies; evaluated and implemented local numerical models; evaluated weather sensors; and many more. The AMU has completed 113 projects with 5 more scheduled to be completed by the end of 2010. During this rich history, the AMU and its customers have learned many lessons on how to effectively transition research into operations. Some of these lessons learned include collocating with the operational customer and periodically visiting geographically separated customers, operator submitted projects, consensus tasking process, use of operator primary advocates for each project, customer AMU liaisons with experience in both operations and research, flexibility in adapting the project plan based on lessons learned during the project, and incorporating training and other transition assistance into the project plans. Operator involvement has been critical to the AMU's remarkable success and many awards from NASA, the National Weather Association, and two citations from the Navy's Center of Excellence for Best Manufacturing Practices. This paper will present the AMU's proven methods and explain how they may be applied by other organizations to effectively transition research into operations.

Madura, John T.↗

NASA NTRS2015

Safety Related Considerations in Autonomy

In this talk I will describe NASA strategy and research efforts to provide safety assurance for increasingly autonomous systems used in aviation. In the near future, autonomy will play an important role in civil aviation, and its applications will range from vehicles and platforms (UAVs, transport-class, including supersonic to hypersonic, aircraft) to airspace operations, or health management systems. This infusion of autonomy is driven by a need for optimizing airspace operations to accommodate increasing traffic density (e.g., adaptive trajectory-based operations, autonomous tugs, close parallel runways, and dynamic separation assurance), reducing operation costs to ensure that US operators can compete with emergent countries, and enabling new business models (e.g., fire fighting, UAS-based package delivery and precise aerial photography). In essence virtually every component of the National Airspace System will become increasingly autonomous. Yet we need to do so in a safe manner and have techniques and processes in place to ensure the safety of the public. This talk describes NASA plans to address this problem

Air Traffic Management↗