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At least 1,081 records · Page 60

Linking Improvements in Sulfur Dioxide Emissions to Decreasing Sulfate Wet Deposition By Combining Satellite and Surface Observations With Trajectory Analysis

Sulfur dioxide (SO2), a criteria pollutant, and sulfate (SO42−) deposition are major environmental concerns in the eastern U.S. and both have been on the decline for two decades. In this study, we use satellite column SO2 data from the Ozone Monitoring Instrument (OMI), and SO42− wet deposition data from the NADP (National Atmospheric Deposition Program) to investigate the temporal and spatial relationship between trends in SO2 emissions and the downward sulfate wet deposition over the eastern U.S. from 2005 to 2015. To establish the relationship between SO2 emission sources and receptor sites, we conducted a Potential Source Contribution Function (PSCF) analysis using HYSPLIT back trajectories for five selected Air Quality System (AQS) sites - (Hackney, OH, Akron, OH, South Fayette, PA, Wilmington, DE, and Beltsville, MD) - in close proximity to NADP sites with large downward SO42− trends since 2005. Back trajectories were run for three summers (JJA) and three winters (DJF) and used to generate seasonal climatology PSCFs for each site. The OMI SO2 and interpolated NADP sulfate deposition trends were normalized and overlapped with the PSCF, to identify the areas that had the highest contribution to the observed drop. The results suggest that emission reductions along the Ohio River Valley have led to decreases in sulfate deposition in eastern OH and western PA (Hackney, Akron and South Fayette). Farther to the east, emission reductions in southeast PA resulted in improvements in sulfate deposition at Wilmington, DE, while for Beltsville, reductions in both the Ohio River Valley and nearby favorably impacted sulfate deposition. For Beltsville, sources closer than 300 km from the site contribute roughly 56% observed deposition trends in winter, and 82% in summer, reflecting seasonal changes in transport pattern as well as faster oxidation and washout of sulfur in summer. This suggests that emissions and wet deposition are linked through not only the location of sources relative to the observing sites, but also to photochemistry and the weather patterns characteristic to the region, as evidenced by a west to east shift in the contribution between winter and summer. The method developed here is applicable to other regions with significant trends such as China and India, and can be used to estimate the potential benefits of emission reduction in those areas.

sulfur dioxide emissions↗

Flight Trajectory Prediction Based on Hybrid-Recurrent Networks

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing the limited available spectrum for communications among aircraft and ground systems. Emerging approaches to autonomous allocation of aviation spectrum mostlyrely on machine learning techniques, where 4D (longitude, latitude, altitude, time) trajectory prediction is an important data input to enable real-time resource allocation. This study explores and evaluates effective data sources and deep recurrent neural network techniques when determining flight trajectories. Specifically, data are collected and evaluated in a 100-day and 14-day period. Sources of data include NASA Sherlock Data Warehouse, MIT Lincoln Labs Corridor Integrated Weather Service (CIWS), and assorted NOAA weather datasets. Deep learning models for 4D predictions all utilize a hybrid-recurrent technique. A baseline model is considered via the convolutional-LSTM design from the existing literature. The modified design considers Gated Recurrent Units (GRU), Independently Recurrent Neural Networks (IndRNN), and stand-alone self-attention layers. Results indicatethe effectiveness of LSTM and GRUcells for state-of-the-art data processing (interpolation). Additionally, GRUs may be quickly trained with limited data, allowing for exacting improvements with optimizer selection. Attention mechanisms provide notable performance improvements to convolutional layers and may extend dimensional capabilities of a learning model. Finally, NOAA measurements provide only a supplemental value, requiring support from tailored measurements for Air Traffic Management.

Nathan Schimpf↗

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↗

Osiris-Rex Post-Tag Observation Trajectory Design and Navigation Performance

NASA’s OSIRIS-REx spacecraft successfully collected a sample of asteroid regolith from the surface of near-Earth asteroid Bennu in October of 2020. Subsequent imaging of the sampler head showed material leaking from the collection mechanism, thus stowage of the sample precluded execution of any planned maneuvers in the following days. Optical navigation imaging also ceased in the days following sample collection. The desire to image the sample site to investigate the results of the spacecraft-to-surface interaction led to the Navigation team designing a trajectory to return to Bennu after several months in order to image the surface one final time. After several iterations a trajectory design was created that satisfied the numerous constraints that were levied in order to place utmost importance on the safety of the spacecraft and stowed sample, while also closely emulating previously obtained imaging conditions to provide a close comparison of site pre- and post-contact. Significant analysis was necessary in order to reliably reacquire the asteroid after several months without optical navigation imagery. The final design required five maneuvers to return the spacecraft to Bennu and perform a final flyby of the asteroid at a distance of 3.8 kilometers. Successful execution of the phase provided key insights regarding the performance of the sample collection activities and the subsurface composition of the asteroid.

Daniel R Wibben↗

Mars 2020 Perseverance trajectory reconstruction and performance from launch through landing

The Mars 2020 (M2020) Mission carrying Perseverance, the most advanced rover ever sent to Mars, successfully launched on an Atlas V 541 (AV-088) launch vehicle from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 11:50:00 UTC (T-Zero time) on July 30, 2020. After some station reconfiguration, carrier/telemetry were locked at both Deep Space Network (DSN) Canberra and Goldstone stations. Perseverance entered the Martian atmosphere at 20:36:50 Spacecraft Event Time (SCET) UTC, and landed inside Jezero Crater at 20:43:49 SCET UTC on February 18, 2021. Confirmation of nominal landing was received at the DSN Goldstone and Madrid tracking stations via the Mars Reconnaissance Orbiter at 20:55:11 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometric characteristics.

Abilleira, Fernando↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

Using Reinforcement Learning to Design Missed Thrust Resilient Trajectories

From ion thrusters to solar sails, spacecraft continue to adopt new and more efficient forms of propulsion. As these low-thrust propulsion meth- ods have become more prevalent, new challenges have arisen. Depending on the mission, low-thrust propulsion elements may need to thrust con- tinuously for days/months. During these thrusting periods, external fac- tors, such as a micro-meteoroid impact or a software glitch, may cause the spacecraft to prematurely cease its thrust stage. Half of all deep space missions enter a safe mode where they cannot thrust every four months. These missed thrust events can result in the complete loss of a space- craft for time-dependent trajectories like planetary rendezvous. This paper demonstrates how neural networks, trained using reinforcement learning, can autonomously correct for missed thrust events during an interplanetary trajectory.

Laipert, Frank E.↗

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

Enabling Thread Safety and Parallelism in the Program to Optimize Simulated Trajectories II

Development of the Program to Optimize Simulated Trajectories (POST) began in the 1970s. Since then, it has become widely utilized across NASA, industry, and academia to solve a variety of atmospheric ascent and entry problems. Its successor, POST2, has undergone many upgrades since its release in the 1990s. Recently, there has been an increasing desire to take advantage of the advances in parallel computing for both offline and online systems. Thus, modifications were made to allow POST2 to simulate multiple trajectories simultaneously without adversely affecting results. This capability is leveraged to calculate optimization solutions in parallel as opposed to sequentially. A demonstration of the benefits is presented using a small set of POST2 regression tests, as well as a project simulating a human-scale Lunar lander.

R. Anthony Williams↗

Enabling Thread Safety and Parallelism in the Program to Optimize Simulated Trajectories II

Development of the Program to Optimize Simulated Trajectories (POST) began in the 1970s. Since then, it has become widely utilized across NASA, industry, and academia to solve a variety of atmospheric ascent and entry problems. Its successor, POST2, has undergone many upgrades since its release in the 1990s. Recently, there has been an increasing desire to take advantage of the advances in parallel computing for both offline and online systems. Thus, modifications were made to allow POST2 to simulate multiple trajectories simultaneously without adversely affecting results. This capability is leveraged to calculate optimization solutions in parallel as opposed to sequentially. A demonstration of the benefits is presented using a small set of POST2 regression tests, as well as a project simulating a human-scale Lunar lander.

Anthony Williams↗

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

This paper presents a comparison of trajectory generation methodologies using acoustic source noise models of different fidelity for motion planning for an acoustically-aware aircraft subject to constraints on the vehicle dynamic performance, mission, and acoustic footprint of the vehicle at a set of (three-dimensional) observer locations. The performance of a pre-mission Bézier curve-based planner and a (near) real-time stochastic model predictive control planner are compared. Additionally, a comparison is made between the motion planning performance using a lower-fidelity acoustic model based on propeller tip Mach number and omni-directional sound power radiation, and a hemisphere-based higher-fidelity acoustic model. It is demonstrated that the asymmetry in hemisphere-based acoustic model can be exploited for improved flight path planning and trajectory-tracking performance in the presence of acoustic constraints.

Kasey A Ackerman↗

Mars 2020 Perseverance Trajectory Reconstruction and Performance from Launch through Landing

The Mars 2020 (M2020) Mission carrying Perseverance, the most advanced rover ever sent to Mars, successfully launched on an Atlas V 541 (AV-088) launch vehicle from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 11:50:00 UTC (T-Zero time) on July 30, 2020. After some station reconfiguration, carrier/telemetry were locked at both Deep Space Network (DSN) Canberra and Goldstone stations. Perseverance entered the Martian atmosphere at 20:36:50 Spacecraft Event Time (SCET) UTC, and landed inside Jezero Crater at 20:43:49 SCET UTC on February 18, 2021. Confirmation of nominal landing was received at the DSN Goldstone and Madrid tracking stations via the Mars Reconnaissance Orbiter at 20:55:11 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometric characteristics.

Wong, Mau↗

Multi-Party Flight Trajectory Negotiation for Upper Class E Traffic Management

A new operational concept has been proposed in Upper Class E airspace at or above 60,000 feet (Flight Level / FL600), which will allow operators of diverse vehicle characteristics to cooperatively manage and share their operational intents with neighboring operators to avoid conflict. There is a consensus in the community that negotiation for strategic deconfliction is needed, but there are no specific guidelines for how the negotiation should be conducted. There is a need for a structured and cooperative way to resolve the conflict between a wide variety of aircraft projected to be operating in Upper Class E for the negotiation to be carried out routinely. The use of negotiation models are a promising solution that can resolve conflict risks during flight in real-time while taking into account the uncertainty of future vehicle positions and dynamic business considerations. A two-party negotiation model has been researched, but as the traffic demand grows, there is a higher likelihood of conflict involving multiple aircraft that would require a method to handle multi-party conflict. This paper proposes a cooperative multi-party negotiation model inspired by game theory concepts for application to flight trajectory negotiation in Upper Class E traffic management. This model can be applied in flight with operators communicating directly after a potential conflict is detected. Some of the model’s benefits include allowing business costs to be private to operators, allowing operators to collaborate together to find conflict-free flight trajectories, and being compatible with different aircraft and operation types. This model provides a structured procedure for conflict resolution that can handle conflict involving multiple parties, assuming each operator is willing to take on a small cost to themselves in order to reduce the total cost to the group.

Upper Class E Traffic Management (ETM)↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of A Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of a Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

6-DoF Uranus Aerocapture Trajectory Analysis

The Uranus Orbiter and Probe mission has been identified as the highest priority flagship mission for this decade. Delays in launch opportunities may make existing fully-propulsive orbit insertion mission types unfeasible. Aerocapture can potentially alleviate these challenges while providing a solution flexible to different launch opportunities. While the space technology that aerocapture leverages have been flight-proven, aerocapture as-a-whole has not been formally demonstrated. This paper presents a novel 6-DoF aerocapture trajectory analysis applied to Uranus. The paper presents the 6-DoF simulation framework, inspired from Mars Science Laboratory. Trajectory comparisons, including Monte Carlo simulations, to existing 3-DoF solutions are presented to understand the information learned from increasing the modeling level-of-fidelity.

Rohan G Deshmukh↗

Blade and Takeoff Trajectory Optimization of a Propeller-Driven Electric Aircraft with Acoustic Constraints

In this work, a multi-disciplinary toolchain is described and used to optimize the takeoff trajectory of a electrified general aviation aircraft, subjected to acoustic constraints. The Dymos multi-disciplinary optimal control library is used to optimize the trajectory, with propeller aerodynamic and acoustic models provided by blade element momentum theory (CCBlade.jl) and acoustic analogy (AcousticAnalogies.jl) codes, respectively. Each model is implemented in the OpenMDAO framework, with all derivatives calculated either analytically or via automatic differentiation tools. The toolchain is applied to a hypothetical electrified form of the Cirrus SR20 and compared to the conventional piston-driven form.

Aerodynamics↗

Evaluation of Magnet Configurations for Magnetohydrodynamic Trajectory Control during Planetary Entry

Magnetohydrodynamics is a phenomenon that can be harnessed during planetary entry to augment aerodynamic drag and may enable higher mass payloads to safely reach the surface. The magnetohydrodynamic force is quantified over a wide range of freestream conditions using computational fluid dynamics results from a previous study. The force is calculated for an array of small electromagnets, a large non-superconducting magnet, a large superconducting magnet, and a uniform field. The superconducting magnet produces a magnetohydrodynamic force within an order of magnitude of aerodynamic drag for velocities higher than 10 km/s, indicating that it may have a reasonable impact on the trajectory for some cases. The array of small magnets and non-superconducting magnet produced a magnetohydrodynamic force that is less than 1% of the aerodynamic drag, so their magnetic fields are not strong enough to affect an entry trajectory. Additionally, the magnet placement plays an important role in magnetohydrodynamic force magnitude, with a magnet located near the shoulder producing approximately eight times more force than a magnet placed on the axis of symmetry. A mass and power budget for each magnet configuration is given assuming current state-of-the-art magnet technology. This study also discusses implementation challenges for each type of magnet on a spacecraft.

Magnetohydrodynamics↗