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At least 883 records · Page 49

Flight Dynamics and Controls Discipline Overview

This presentation will touch topics, including but not limited to, the objectives and challenges of flight dynamics and controls that deal with the pilot and the cockpit's technology, the flight dynamics and controls discipline tasks, and the full envelope of flight dynamics modeling. In addition, the LCTR 7x10-ft wind tunnel test will also be included along with the optimal trajectories for noise abatement and its investigations on handling quality. Furthermore, previous experiments and their complying results will also be discussed.

Theodore, Colin R.↗

Guidance and Control Architecture Design and Demonstration for Low Ballistic Coefficient Atmospheric Entry

We propose to develop a robust guidance and control system for the ADEPT (Adaptable Deployable Entry and Placement Technology) entry vehicle. A control-centric model of ADEPT will be developed to quantify the performance of candidate guidance and control architectures for both aerocapture and precision landing missions. The evaluation will be based on recent breakthroughs in constrained controllability/reachability analysis of control systems and constrained-based energy-minimum trajectory optimization for guidance development operating in complex environments.

Entry↗

Trades Between Opposition and Conjunction Class Trajectories for Early Human Missions to Mars

Candidate human missions to Mars, including NASA's Design Reference Architecture 5.0, have focused on conjunction-class missions with long crewed durations and minimum energy trajectories to reduce total propellant requirements and total launch mass. However, in order to progressively reduce risk and gain experience in interplanetary mission operations, it may be desirable that initial human missions to Mars, whether to the surface or to Mars orbit, have shorter total crewed durations and minimal stay times at the destination. Opposition-class missions require larger total energy requirements relative to conjunction-class missions but offer the potential for much shorter mission durations, potentially reducing risk and overall systems performance requirements. This paper will present a detailed comparison of conjunction-class and opposition-class human missions to Mars vicinity with a focus on how such missions could be integrated into the initial phases of a Mars exploration campaign. The paper will present the results of a trade study that integrates trajectory/propellant analysis, element design, logistics and sparing analysis, and risk assessment to produce a comprehensive comparison of opposition and conjunction exploration mission constructs. Included in the trade study is an assessment of the risk to the crew and the trade offs between the mission duration and element, logistics, and spares mass. The analysis of the mission trade space was conducted using four simulation and analysis tools developed by NASA. Trajectory analyses for Mars destination missions were conducted using VISITOR (Versatile ImpulSive Interplanetary Trajectory OptimizeR), an in-house tool developed by NASA Langley Research Center. Architecture elements were evaluated using EXploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), a parametric modeling tool that generates exploration architectures through an integrated systems model. Logistics analysis was conducted using NASA's Human Exploration Logistics Model (HELM), and sparing allocation predictions were generated via the Exploration Maintainability Analysis Tool (EMAT), which is a probabilistic simulation engine that evaluates trades in spacecraft reliability and sparing requirements based on spacecraft system maintainability and reparability.

Mattfeld, Bryan↗

Orion Exploration Mission Entry Interface Target Line

The Orion Multi-Purpose Crew Vehicle is required to return to the continental United States at any time during the month. In addition, it is required to provide a survivable entry from a wide range of trans-lunar abort trajectories. The Entry Interface (EI) state must be targeted to ensure that all requirements are met for all possible return scenarios, even in the event of no communication with the Mission Control Center to provide an updated EI target. The challenge then is to functionalize an EI state constraint manifold that can be used in the on-board targeting algorithm, as well as the ground-based trajectory optimization programs. This paper presents the techniques used to define the EI constraint manifold and to functionalize it as a set of polynomials in several dimensions.

Rea, Jeremy R.↗

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases [1]. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission [2]. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions.

Zwack, Mathew R.↗

Flight Test Assessments of Pilot Workload, System Usability, and Situation Awareness of TASAR

Traffic Aware Strategic Aircrew Requests (TASAR) is an onboard automation concept intended to identify trajectory optimizations, in terms of fuel and time saving objectives, clear of known traffic, weather, and airspace restrictions prior to the aircrew initiating a route-change request to Air Traffic Control (ATC). The software implementation of the TASAR concept is the Traffic Aware Planner (TAP). TASAR analysis and development is being executed by the NASA Langley Research Center's Crew Systems and Aviation Operations Branch (CSAOB) under the sponsorship of the Airspace Technology Demonstration (ATD) Project of the NASA Airspace Operations and Safety Program (AOSP). The TASAR Flight Trial-2 (FT-2) was conducted in June, 2015 out of the Newport News/Williamsburg International Airport. This flight trial was conducted using a Piaggio Avanti flight test aircraft and consisted of 12 Evaluation Flights with airline commercial pilots participating as the Evaluation Pilots, three destination airports in Atlanta and Jacksonville Air Route Traffic Control Centers, and one pair of flight plans associated with each destination airport. The primary goal of FT-2 was to reduce risk for upcoming operational trials with NASA partner airlines, Alaska Airlines and Virgin America. To accomplish this primary goal, six independent objectives were conducted during FT-2, however, this paper will report only the findings of Objective 5; the assessment of system usability, pilot perceived workload, and the degree of pilot acceptability of the TAP Human Machine Interface (HMI) during flight operations, via the administration of several subjective measures.

TASAR↗

Low Thrust Mission Trajectories to Near Earth Asteroids

The discovery of 2016 HO3 and its classification as a quasi-satellite has sparked a stronger interest towards Near Earth Asteroids (NEAs). This work presents low-thrust low-power mission designs to various NEAs using an EELV Secondary Payload Adapter (ESPA). A global trajectory optimizer (EMTG) was used to generate mission solutions to a select 13 NEAs using a 200 watt BHT-200 thruster as a proof of concept. The missions presented here demonstrate that a low-cost electric propulsion ESPA mission to NEAs is a feasible concept for many asteroids.

Asteroid↗

TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation

This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.

surface operations↗

MONTE: the Next Generation of Mission Design and Navigation Software

The Mission Analysis, Operations and Navigation Toolkit Environment (MONTE) is an astrodynamic toolkit produced by the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory. It provides a single integrated environment for all phases of deep space and Earth orbiting missions. Capabilities include: trajectory optimization and analysis, operational orbit determination, flight path control, and 2D/3D visualization. MONTE is presented to the user as an importable Python language module. This allows a simple but powerful user interface via CLUI or script. In addition, the Python interface allows MONTE to be used seamlessly with other canonical scientific programming tools such as SciPy, NumPy, and Matplotlib. MONTE is the prime operational orbit determination software for all JPL navigated missions.

Optimization↗

Simulation and Flight Test Environments for the TASAR Traffic Aware Planner

The Traffic Aware Planner (TAP) software is a flight deck decision support tool that enhances the flight crew’s ability to make flight-optimizing route change requests while airborne. The software provides conflict-free, optimized trajectory suggestions during en route flight to produce time- and fuel-savings compared to the current trajectory. The TAP software requires evaluation in an operational environment with real pilot users to validate projected benefits. To this end, a set of developmental test environments have been developed to mature the software and mitigate technical risk prior to entering operational evaluation. The unique attributes of each test environment were leveraged to provide a range of purpose- and case-dependent TAP software tests. This paper describes the elements of a testing environment, discusses several environments of varying fidelity used to test the TAP software, and provides a review of two case studies highlighting the vital role testing played in the TAP software development process.

Barney, Terique L.↗

Evolution and Impact of Saturn V on Space Launch System from a Guidance, Navigation, and Mission Analysis Perspective

The Saturn V launch vehicle represented a jump in capability for heavy lift launch vehicles, enabling the Lunar Orbit Rendezvous approach to planetary exploration employed by the Apollo program 50 years ago. Following Apollo, and the development of the Space Transportation System, the NASA space exploration program shifted focus from lunar exploration to long-term, sustained, re-usable access to Low Earth Orbit. With the recent focus of NASA on the Artemis program and continued exploration of cislunar space as a precursor to Martian exploration, the shift has swung back to heavy lift capability. To meet this need, NASA has developed the Space Launch System. While the vehicle is a new design, it is heavily influenced by the engineering solutions and approach used on the Saturn V while taking advantage of the state of the art of launch vehicle design. The approach to abort, for example, shares many familiarities with the triggers and concept of operations used on Saturn V. Analysis approaches to dispersed trajectory performance are also very similar, but advances in computing technology have enabled a much more expanded set of inputs that can be modelled and assessed in a rapid manner. Additionally, guided flight algorithms share similar first principles but have expanded to include day of launch wind information. Trajectory optimization has also advanced significantly due to the availability of computing resources, but similar maneuvers and profiles are flown across both vehicles. Also, while the approach of onboard inertial navigation has been maintained between the two programs, the shift from platform to strapdown systems enables reduced complexity in the system design while maintaining required performance. As described, the Space Launch System is the evolution of NASA launch vehicle designs, owing a large heritage to the Saturn vehicle program and incorporating advances in propulsion systems, avionics, computing, and sensor technology over the past 50 years.

Ahmad, Naeem↗

Implicit Formulations of Bounded-Impulse Trajectory Models for Preliminary Interplanetary Low-Thrust Analysis

The bounded-impulse approach to low-thrust interplanetary trajectory optimization is widely used. In an effort to efficiently implement this approach using NASA’s OpenMDAO optimization software, the authors have implemented implicit formulations of the forward shooting/backwards-shooting methods commonly used in bounded-impulse models. These implicit approaches allow for vectorization of the underlying calculations which can significantly reduce runtime in interpreted languages. An implicit approach may be either converged by using an underlying nonlinear solver to converge the state propagation, or as a constraint in an optimizer-driven multiple-shooting approach. Significant computational efficiency gains are realized through the utilization of the modular approach to unified derivatives. Further computational efficiency is achieved by capitalizing on the sparsity of the constraint Jacobian matrix. This work demonstrates that a vectorized multiple-shooting approach for propagating a state-time history is superior in terms of computational efficiency as the number of segments in the state-propagation is increased.

Falck, Robert D↗

Supersonic Retro-Propulsion for Future High-Mass Robotic Mars Lander Missions

A feasibility study was conducted to investigate the potential performance advantages of Supersonic Retro-Propulsion in support of future high-mass Mars robotic landing missions. A notional reference architecture for a potential future Mars Sample Return formed the basis for assuming a 4.7 m diameter SRP entry vehicle containing the Mars Ascent Vehicle element. Configuration analysis was conducted to ensure that the payload and required SRP components (including engines and propellant) fit within in the capsule volume. Optimized trajectory analysis highlighted several key performance sensitivities of SRP for ballistic coefficients of 150, 300, and 450 kg/m2. These results indicated a broad SRP ignition envelope (1-4 km altitude, 300-750 m/s velocity), as well as relatively small propellant mass fraction sensitivities to SRP thrust/weight, landing site elevation, and the application of a 4-g entry deceleration constraint (relevant for future crewed mission trajectories). Finally, mass-sizing was performed to assess sensitivities to ballistic coefficient and entry velocity, and showcased the ability of the SRP system to land payload masses on the order of twice that of MSL.

Whetsel, Charles↗

Post-Flight Performance Analysis of Navigation and Advanced Guidance Algorithms on a Terrestrial Suborbital Rocket Flight

There is currently renewed interest in robotic and crewed landers for a return to the lunar surface. Advanced guidance and navigation algorithms are essential to accurately delivering cargo and crew safely to the moon successfully. This paper reports the overall performance of an integrated set of navigation and guidance algorithms flown on a terrestrial suborbital rocket up to an altitude of approximately 100km. The navigation algorithm consists of an onboard extended Kalman Filter (EKF) that ingests multiple sensor measurements, one of which is the output from a terrain relative navigation (TRN) algorithm that cross-references camera images to on-board satellite imagery to perform feature correlation within the camera image. The guidance algorithm solves for a 6-degree-of-freedom (DoF) optimal trajectory using a successive convexification method during powered descent. The altitude range as well as the landing dynamics experienced during this test flight are realistic for an extraterrestrial landing and provide an invaluable data set to gauge the current development of these landing algorithms in an effort to advance the overall software readiness levels (SRL). This paper will delve into different aspects of each algorithm and present an analysis of the in-flight performance of the algorithms. This flight was conducted under the National Aeronautics and Space Administration (NASA) Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project focused on technology advancement for landing applications.

Guidance↗

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

Dynamic Orbital Slingshot for Rendezvous with Interstellar Objects

The solar sail “statite” concept presents a potential means to study interstellar objects (ISOs). A new class of asteroids and comets, ISOs offer a unique scientific opportunity to answer fundamental scientific questions about the origin of solar system volatiles, the compositions of exo-solar systems, and the transfer rates of material between solar systems. Unfortunately, they are also challenging to study due to their high excess energies and the short lead time offered by present detection infrastructure. By using its solar sail to “hover” in place, a statite is able to await the discovery of an ISO and, when called upon, convert the enormous potential energy of its stationary state into the velocity necessary to rendezvous with the targeted comet or asteroid. The investigation completed in Phase I focused on establishing the viability of the proposed mission concept. To do so, optimal trajectories to the two known ISOs were demonstrated and the relationship between statite placement and the resulting trajectory was explored. Post-launch trajectories from the Earth to strategic statite states were also shown to be feasible. Concurrently with these efforts, a thorough review of published ISO population estimates was conducted and preliminary steps towards creating a database of synthetic ISO ephemerides were completed. If renewed for a Phase II, this will be used to characterize the capabilities of the statite concept.

NIAC Phase I↗

On the Myth of Fuel Consumption Minimization of a Lunar Lander

Many articles have based the solution of trajectory optimization of a lunar lander on minimizing fuel consumption. This optimization is attempted by minimizing the burn-time of the descent engine, or by maximizing the total mass of the vehicle during the maneuver. The general myth, is that minimizing fuel is possible. However, the first law of thermodynamics cannot be violated. Therefore, the work that the descent engine must do to dissipate the energy of the vehicle from orbit to landing is constant. The higher the power setting of the engine, the less time it takes to dissipate the total mechanical energy, but it does not save any fuel.

Guidance↗

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗