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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
NASA NTRS2026

A Missed Thrust Framework for Low-Thrust Spiral Trajectories to the NRHO

A framework is developed by which end-to-end optimization of many-revolution low-thrust spiral trajectories can be completed in the presence of missed thrust events. This framework is applied to the Lunar Transit trajectory by which the initial capability of NASA’s Gateway lunar space station will be delivered to a Near Rectilinear Halo Orbit. This low-thrust mission consists of three subphases, each designed according to the specific objectives and dynamical regimes encountered as the mission progresses from a medium Earth insertion orbit to cislunar space. The presented framework accounts for the unique considerations demanded by each mission phase and incorporates appropriate capabilities into a novel mission analysis tool. This methodology enables large scale and reliable analyses of missed thrust events across the end-to-end Lunar Transit to verify the robustness of flight trajectories across the full range of considered launch dates.

missed thrust↗
NASA NTRSDate not supplied

Responses of Microbes to Modeled Space Radiation

The built environment of spaceships is host to a microbial community that affects crew and craft alike. While the static composition of this community has been characterized and its temporal dynamics examined, the mechanisms controlling its make-up and evolutionary trajectory are not understood. Systematic analyses of microbial diversity show consistent patterns in community composition and function. Understanding these patterns' ecological origins remains a significant challenge, as it requires connecting processes at varying temporal and spatial scales. However, it is clear that the state and trajectories of microbial communities are in-part determined by their physical environment. In this regard, the spaceflight environment includes numerous interacting factors that differentiate it from Earth environments, including an altered atmospheric composition, reduced gravity (and thus altered fluid dynamics), and increased ionizing radiation. These factors impart selective pressures on microbial communities that affect their evolutionary trajectories and thus the risks and benefits these communities represent to crew and craft. The radiation environment of space leads to chronic exposure to low doses and is difficult to mimic on Earth. Thus, little is known about how microbial communities in spacecraft will respond and evolve. Therefore, given the limitations of existing studies, we aim to empirically determine how exposure to low doses of ionizing radiation for thousands of cell divisions affects rates of mutation accumulation in bacteria and the trajectory of their evolution. In this way, we will provide a critical set of data for designing safe and robust space missions. Here we discuss our progress towards this aim, including the construction of exposure facilities, our culturing and analysis approach, and preliminary data.

radiation↗
NASA NTRSDate not supplied

Angles-Only Robust Trajectory Optimization for NRHO Rendezvous

This study demonstrates a robust trajectory optimization approach for rendezvous and proximity operations with angles-only navigation measurements. Often, sensors that directly measure relative range and velocity require communication or coordination between the chaser and target vehicle and can have limiting pointing accuracy, mass, or power requirements compared to angle measurement sensors. Thus, the capability to perform a rendezvous with only angle measurements can be advantageous for vehicle design and to improve robustness to failures. However, the well studied limitation of angles-only navigation in measuring range results in large uncertainties in the navigation system that must be reduced with chaser vehicle thrust maneuvers to induce observability in range for the navigation filter. This analysis presents a trajectory optimization problem for a lunar ascent rendezvous during a crewed lunar mission in a Near-Rectilinear Halo Orbit (NRHO) that is limited to only angle measurements. The objective of this study is to show that an angles-only rendezvous is feasible in an NRHO and to present the sensitivity to an assortment of constraints generated from a systematic optimization process using linear covariance analysis and particle swarm optimization. Linearized NRHO dynamics and linearized relative targeting are applied to use linear covariance analysis to determine the expected delta-v and trajectory dispersions due to initial state uncertainty, sensor errors, maneuver execution errors, and unmodeled dynamics. The delta-v and trajectory dispersions are passed into a particle swarm optimization algorithm to find the optimized maneuver profile that minimizes fuel use while satisfying constraints such as free drift and underburn to 3-sigma certainty. The trajectory constraints including time available, desired final uncertainty, and initial uncertainty are varied to ascertain sensitivity and desirable engineering trades.

Linear Covariance Analysis↗
NASA NTRSDate not supplied

Aerocapture Trajectory Design for Uranus Orbiter

Introduction: The recently released National Academies Planetary Science and Astrobiology Decadal Survey 2023-2032 [1] identified the Ice Giants as the top priority science destination. While the survey acknowledged the potential for either a Uranus Orbiter and Probe (UOP) mission or a Neptune-Triton Odyssey mission, it ultimately identified the former as the highest priority new flagship mission. UOP missions calls for a launch window of opportunity between 2031-2038 with 12-15 year interplanetary cruise time along with a fully-propulsive Uranus Orbit Insertion burn on the order of a few km/s. However, a mission to Uranus with the same science payload could utilize aerocapture for orbit insertion to achieve both a significant reduction in the interplanetary cruise time and reduction in propulsive burn costs. Why Aerocapture: Aerocapture is a promising propellant and time-saving orbital insertion technique for planetary destinations with an atmosphere. Although not flight-proven, previous aerocapture systems studies in the literature have demonstrated both the validity and robustness of the technique at various planetary destinations. With respect to the Ice Giant planets, Neptune has seen more of the analysis in the literature. For science missions at Neptune, aerocapture can enable 1.4 times more delivered mass to orbit than an all-propulsive mission for the same launch vehicle while reducing interplanetary cruise times by more than 3 years [2] Additionally with modern guidance and control, Neptune aerocapture with blunt-body aeroshells is realizable [3][4]. There are limited papers in the literature investigating Uranus aerocapture with those available providing a preliminary feasibility assessment [5]. Consequently, the two-year funded NASA Space Technology Mission Directorate (STMD)-funded project, titled Aerocapture System as an Enabling Technology for Ice Giants Missions, aims to mature the analysis and technology state of Uranus aerocapture. Trajectory Design: This paper presents the current state of the trajectory design in support of the new aerocapture project. The project design philosophy is inspired from recent Neptune aerocapture studies, which employed modern guidance and control, in the sense that blunt-body aeroshells are analyzed. An assessment of the theoretical flight path angle corridor width is conducted for a range of ballistic coefficients and lift-to-drag ratios for both Space Launch System and Falcon Heavy Launch Vehicle interplanetary trajectory solutions. The results from the corridor width assessment provide an assessment of the aerocapture design-space and qualitative metrics on trajectory design considerations. The Program to Optimize Simulated Trajectories II (POST2) is utilized to run Monte Carlo simulations of Uranus aerocapture three-degree-of-freedom bank angle modulated trajectories using a closed-loop numerical-predictor corrector guidance algorithm. UranusGRAM 2021 is utilized as the atmospheric model [6]. A Uranus-developed aerodatabase, originally derived from Mars Science Laboratory (MSL), is utilized to provide vehicle aerodynamics over a wide range of hypersonic flow regimes. A MSL-derived 70 deg 4.5m diameter sphere-cone aeroshell that houses the UOP payload mass is assumed. Robustness testing and performance analysis is conducted, including the assessment of entry state errors, atmosphere density variations, and aerodynamic dispersions. Post-aerocapture Delta-V and aerothermal statistics are formulated into propellant mass and TPS requirements. The results presented in the paper will demonstrate the trajectory viability of Uranus aerocapture. Preliminary Results: Preliminary trajectory design results indicates successful Uranus aerocapture with a blunt-body aeroshell housing the same payload mass as the UOP mission from an Earth-to-Uranus interplanetary trajectory arriving in less than 7 years. From this interplanetary trajectory, aerocapture provides an orbit insertion Delta-V capability of 6.9 km/s requiring less than 300 m/s for post-aerocapture correction burns (15% of wet mass allocated to propellant). To put this into perspective, the UOP study utilized an Earth-to-Uranus trajectory that arrives in 13 years and requires more than 1000 m/s for fully-propulsive orbit insertion (40% of wet mass allocated to propellant). Achieving the same 6.9 km/s Delta-V capability fully-propulsively is mass prohibitive (97% of wet mass allocated to propellant). Nevertheless, aerocapture has the potential to reduce interplanetary transit times to Uranus by half while delivering the same payload mass to orbit in a reduced propellant mass footprint.

Rohan Deshmukh↗
NASA NTRS2012

Engineering a Multimission Approach to Navigation Ground Data System Operations

The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.

Mission Design and Navigation (MDNAV)↗
NASA NTRS1986

Design of multivariable controllers for robot manipulators

The paper presents a simple method for the design of linear multivariable controllers for multi-link robot manipulators. The control scheme consists of multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and achieves pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. The two controllers are independent of each other and are designed separately based on the linearized robot model and then integrated in the overall control scheme. The proposed scheme is simple and can be implemented for real-time control of robot manipulators.

Seraji, H.↗
NASA NTRSDate not supplied

Enhanced Monitoring and Forecasting of South Asian Air Quality Episodes with Multi-Sensor Satellite Products and Dispersion Modeling

Air pollution and particulates represent a serious environmental, public health, and overarching societal concern in the Hindu Kush Himalaya (HKH) region of south-central Asia, especially during the boreal winter and spring months. Frequent contributors to poor air quality of the region include dust and particulate matter transport from the Middle East region and western India, persistent nocturnal fog and smog during the stable dry monsoon months, and biomass burning during the pre-monsoon months of boreal spring. Nocturnal and multi-day persistent stable fog and smog events can occur during the stable conditions of the dry monsoon months that lead to hazardous visibility reductions (e.g., at major airports such as Delhi, India)and poor air quality, particularly in urban corridors.Our project goal is therefore to design and implement a robust air quality and chemistry observation and modeling system using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. This system effectively assimilates aerosol and trace gas retrievals from geostationary and polar-orbiting satellites to advance the monitoring and prediction capabilities of air quality and visibility reductions throughout the HKH region. For this presentation, we highlight several[multi-spectral] geostationary satellite products and dispersion modeling capabilities being developed and implemented for improved situational awareness and forecasting of air quality episodes.Launched in December 2018, the Advanced Meteorological Imager (AMI) aboard the Geostationary-Korean Multi-Purpose Satellite-2A (GEO-KOMPSAT-2A, or GK2A) provides 16 channels of multi-spectral information similar to the U.S. GOES-16/17 satellites. Proven community recipes for generating multi-spectral Red-Green-Blue (RGB) composite products to detect specific meteorological phenomena are applied to the AMI data for the HKH region. We implemented four such RGB products consisting of truecolor with Rayleigh correction to aid in smoke detection; dust RGB for monitoring larger particulate matter; nighttime microphysics for fog/smog detection;and natural color fire RGB and the shortwave 3.8 micron channel for fire hot-spot detection.We additionally configured HYSPLIT for dust/sand dispersion and concentration forecasts over HKH. The HYSPLIT dispersion simulations are initially being conducted with two different methodologies: (1) dust/sand lofting based on initializing plume releases from visual inspection of the dust RGB imagery; and (2) dust/sand release and dispersion using the internal HYSPLIT algorithm that determines lofting from input wind speeds and prescribed land use. The goal is to develop a near real-time HYSPLIT modeling solution for routinely simulating the transport and dispersion of dust plumes across the HKH region. This presentation illustrates these products and capabilities for various use cases from the 2019 to 2021 period, highlighting a particularly unhealthy episode during late March 2021 across Nepal.

Remote Sensing↗
NASA NTRS2006

Implementation of a Low-Thrust Trajectory Optimization Algorithm for Preliminary Design

A tool developed for the preliminary design of low-thrust trajectories is described. The trajectory is discretized into segments and a nonlinear programming method is used for optimization. The tool is easy to use, has robust convergence, and can handle many intermediate encounters. In addition, the tool has a wide variety of features, including several options for objective function and different low-thrust propulsion models (e.g., solar electric propulsion, nuclear electric propulsion, and solar sail). High-thrust, impulsive trajectories can also be optimized.

optimization↗
NASA NTRS1988

Guaranteed properties for nonlinear gain scheduled control systems

An analysis is presented of two types of nonlinear gain-scheduled control systems: scheduling on a reference trajectory and scheduling on the plant output. Conditions are given which guarantee stability, robustness, and performance properties of the global gain-scheduled designs. These conditions confirm and formalize popular notions regarding gain-scheduled designs; e.g., that the scheduling variable should vary slowly and capture the plant's nonlinearities. These results extend the work of Shamma and Athans (1987), which addressed the case of linear plants whose dynamics depends on exogenous parameters.

Shamma, Jeff S.↗
NASA NTRS1997

Simulation of a Controlled Airfoil with Jets

Numerical simulations of a two-dimensional airfoil, controlled by an applied moment in pitch and an airfoil controlled by jets, were investigated. These simulations couple the Reynolds-averaged Navier-Stokes equations and Euler's equations of rigid body motion, with an active control system. Controllers for both systems were designed to track altitude commands and were evaluated by simulating a closed-loop altitude step response using the coupled system. The airfoil controlled by a pitching moment used an optimal state feedback controller. A closed-loop simulation, of the airfoil with an applied moment, showed that the trajectories compared very well with quasi-steady aerodynamic theory, providing a measure of validation. The airfoil with jets used a controller designed by robust control methods. A linear plant model for this system was identified using open-loop data generated by the nonlinear coupled system. A closed-loop simulation of the airfoil with jets, showed good tracking of an altitude command. This simulation also showed oscillations in the control input as a result of dynamics not accounted for in the control design. This research work demonstrates how computational fluid dynamics, coupled with rigid body dynamics, and a control law can be used to prototype control systems in problematic nonlinear flight regimes.

Allan, Brian G.↗
NASA NTRS2018

An Overview of the Layered and Extensible Aircraft Performance System (LEAPS) Development

The Layered and Extensible Aircraft Performance System (LEAPS) is a new sizing and synthesis tool being developed within the Aeronautics Systems Analysis Branch (ASAB) at NASA Langley Research Center. It is a modular, multidisciplinary, multi- fidelity sizing and synthesis tool for modeling advanced aircraft concepts and architectures such as electric/hybrid-electric propulsion, unconventional propulsion airframe integration, and non-traditional mission trajectories. The development of LEAPS is motivated by the lack of existing tools that meet the needs of ASAB. The Flight Optimization System (FLOPS) has been the primary sizing and synthesis tool of ASAB for three decades. However, FLOPS has a number of limitations that make it dicult to use for unconventional aircraft designs. Three high-level goals have been adopted to guide the LEAPS development pro- cess. LEAPS is being developed in Python with an architecture built to enable a exible and extensible analysis capability using the concept of an aircraft object that combines data and analysis models. Five challenge problems for LEAPS have been identi ed to measure progress: analysis of a conventional tube-and-wing aircraft using legacy methods, coupled aeroelastic analysis for weight estimation of a conventional tube-and-wing aircraft, analysis of an advanced hybrid-electric concept, analysis of the X-57 Maxwell distributed electric propulsion aircraft, and optimization of the trajectory of a supersonic vehicle to minimize sonic boom. LEAPS will be a publicly available capability of exceptional quality with modularity and extensibility that makes it a robust tool for design and analysis of current and future unconventional aircraft concepts.

Welstead, Jason R.↗
NASA NTRS1994

A software architecture for hard real-time execution of automatically synthesized plans or control laws

The design of a flexible, real-time software architecture for trajectory planning and automatic control of redundant manipulators is described. Emphasis is placed on a technique of designing control systems that are both flexible and robust yet have good real-time performance. The solution presented involves an artificial intelligence algorithm that dynamically reprograms the real-time control system while planning system behavior.

Schoppers, Marcel↗
NASA NTRS2008

Ares-I Bending Filter Design using a Constrained Optimization Approach

The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output is required to ensure adequate stable response to guidance commands while minimizing trajectory deviations. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares-I time-varying dynamics and control system can be frozen over a short period of time, the bending filters are designed to stabilize all the selected frozen-time launch control systems in the presence of parameter uncertainty. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constrains minimizes performance degradation caused by the addition of the bending filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The bending filter designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC MAVERIC 6DOF nonlinear time domain simulation.

Hall, Charles↗
NASA NTRS1991

Neural network application to aircraft control system design

The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

Troudet, Terry↗
NASA NTRS2011

Overview and Applications of UAVSAR's Multi-Squint Polarimetric Imaging Mode

NASA's Jet Propulsion Laboratory has developed a reconfigurable polarimetric L-band synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track interferometric (RTI) SAR data for application to monitoring surface deformation and vegetation structure measurements. The system employs a precision autopilot developed by NASA Dryden that allows the plane to fly precise trajectories usually within a 5 m tube. Also required for robust repeat pass applications is the ability to point the antenna in the same direction on repeat passes to a fraction of an azimuth beamwidth (8? for UAVSAR). This precise pointing is achieved using an electronically scanned antenna whose pointing is based on inertial navigation unit (INU) attitude angle data. The radar design is fully polarimetric with an 80 MHz bandwidth (2 m range resolution) and has a greater than 20 km range swath when flying at its nominal altitude of 12500 m. The ability to electronically steer the beam on a pulse-to-pulse basis has allowed a new mode of SAR data acquisition whereby the radar beam is steered to different squint angles on successive pulses thereby simultaneously generating images at multiple squint angles. This mode offers the possibility of generating vector deformation measurements with a single pair of repeat passes and to obtain greater kz diversity for vegetation studies with a reduced number of passes. This paper will present an overview of the mode, discuss its potential for deformation and vegetation, and show some examples using UAVSAR data.

multisquint↗
NASA NTRS1991

Neural network application to aircraft control system design

The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

Troudet, Terry↗
NASA NTRS2014

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

VanZwieten, Tannen↗
DOE OSTI2025

Learning plasma dynamics and robust rampdown trajectories with predict-first experiments at TCV

The rampdown phase of a tokamak pulse is difficult to simulate and often exacerbates multiple plasma instabilities. To reduce the risk of disrupting operations, we leverage advances in Scientific Machine Learning (SciML) to combine physics with data-driven models, developing a neural state-space model (NSSM) that predicts plasma dynamics during Tokamak à Configuration Variable (TCV) rampdowns. The NSSM efficiently learns dynamics from a modest dataset of 311 pulses with only five pulses in a reactor-relevant high-performance regime. The NSSM is parallelized across uncertainties, and reinforcement learning (RL) is applied to design trajectories that avoid instability limits. High-performance experiments at TCV show statistically significant improvements in relevant metrics. A predict-first experiment, increasing plasma current by 20% from baseline, demonstrates the NSSM’s ability to make small extrapolations. The developed approach paves the way for designing tokamak controls with robustness to considerable uncertainty and demonstrates the relevance of SciML for fusion experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗