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NASA NTRS1993

Interactive method for planning constrained, fuel-optimal orbital proximity operations

An interactive graphical method for planning fuel-efficient rendezvous trajectories in the multi-spacecraft environment of the space station is presented. The method allows the operator to compose a multi-burn transfer trajectory between arbitrary initial chaser and target trajectories. The available task time of the mission is limited and the maneuver is subject to various operational constraints, such as departure, arrival, plume impingement and spatial constraints. The maneuvers are described in terms of the relataive motion experienced in a Space-Station centered coordinate system. The optimization method is based on the primer vector and its extension to non-optimal trajectories. The visual feedback of trajectory shapes, operational constraints, and optimization functions, provided by user-transparaent and continuously active background computations, allows the operator to make fast, iterative design changes which rapidly converge to fuel-efficient solutions. The optimization functions are presented. A variety of simple design examples has been presented to demonstrate the usefulness of the method. In many cases the addition of a properly positioned intermediate waypoint resulted in fuel savings of up to 30%. Furthermore, due to the counter-intuitive character of the optimization functions, most fuel-optimal solutions could not have been found without the aid of the optimization tools. Operating the system was found to be very easy, and did not require any previous in-depth knowledge of orbital dynamics or trajectory. The planning tool is an example of operator assisted optimization of nonlinear cost-functions.

Abramovitz, Adrian↗

NASA NTRS1998

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. Unfortunately, an efficient parallel implementation is difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. To address this problem, we have developed PLUM, an automatic portable framework for performing adaptive large-scale numerical computations in a message-passing environment. First, we present an efficient parallel implementation of a tetrahedral mesh adaption scheme. Extremely promising parallel performance is achieved for various refinement and coarsening strategies on a realistic-sized domain. Next we describe PLUM, a novel method for dynamically balancing the processor workloads in adaptive grid computations. This research includes interfacing the parallel mesh adaption procedure based on actual flow solutions to a data remapping module, and incorporating an efficient parallel mesh repartitioner. A significant runtime improvement is achieved by observing that data movement for a refinement step should be performed after the edge-marking phase but before the actual subdivision. We also present optimal and heuristic remapping cost metrics that can accurately predict the total overhead for data redistribution. Several experiments are performed to verify the effectiveness of PLUM on sequences of dynamically adapted unstructured grids. Portability is demonstrated by presenting results on the two vastly different architectures of the SP2 and the Origin2OOO. Additionally, we evaluate the performance of five state-of-the-art partitioning algorithms that can be used within PLUM. It is shown that for certain classes of unsteady adaption, globally repartitioning the computational mesh produces higher quality results than diffusive repartitioning schemes. We also demonstrate that a coarse starting mesh produces high quality load balancing, at a fraction of the cost required a fine initial mesh. Results indicate that our parallel load balancing strategy will remain viable on large numbers of processors.

Oliker, Leonid↗

NASA NTRS1998

Subsystem Analysis/Optimization for the X-34 Main Propulsion System

The Orbital Sciences Corporation X-34 vehicle demonstrates technologies and operations key to future reusable launch vehicles. The general flight performance goal of this unmanned rocket plane is Mach 8 flight at an altitude of 250,000 feet. The Main Propulsion System (MPS) supplies liquid propellants to the main engine, which provides the primary thrust for attaining mission goals. Major MPS design and operational goals are aircraft-like ground operations, quick turnaround between missions, and low initial/operational costs. Analyses related to optimal MPS subsystem design are reviewed in this paper. A pressurization system trade weighs maintenance/reliability concerns against those for safety in a comparison of designs using pressure regulators versus orifices to control pressurant flow. A propellant dump/feed system analysis weighs the issues of maximum allowable vehicle landing weight, trajectory, and MPS complexity to arrive at a final configuration for propellant dump/feed systems.

McDonald, J. P.↗

NASA NTRS2004

Application of a Momentum Source Model to the RAH-66 Comanche FANTAIL

A Momentum Source Model has been revised and implemented in the flow solver OVERFLOW-D. In this approach, the fan forces are evaluated from two-dimensional airfoil tables as a function of local Mach number and angle-of-attack and applied as source terms in the discretized Navier-Stokes equations. The model revisions include a new model for forces in the tip region and axial distribution of the source terms. The model revisions improve the results significantly. The Momentum Source Model agrees well with a discrete blade model for all computed collective pitch angles. The two models agree well with experimental data for thrust vs. torque. The Momentum Source Model is a good complement to Discrete Blade Models for ducted fan computations. The lower computational and labor costs make parametric studies, optimization studies and interactional aerodynamics studies feasible for cases beyond what is practical with a Discrete Blade Model today.

Nygaard, Tor A.↗

NASA NTRS2005

SOFIA'S Challenge: Scheduling Airborne Astronomy Observations

The Stratospheric Observatory for Infrared Astronomy (SOFIA) is NASA's next generation airborne astronomical observatory, and will commence operations in 2005. The facility consists of a 747-SP modified to accommodate a 2.5 meter telescope. SOFIA is expected to fly an average of 140 science flights per year over its 20 year lifetime. Depending on the nature of the instrument used during flight, 5-15 observations per flight are expected. The SOFIA telescope is mounted aft of the wings on the port side of the aircraft and is articulated through a range of 20deg to 60deg of elevation. The telescope has minimal lateral flexibility; thus, the aircraft must turn constantly to maintain the telescope's focus on an object during observations. A significant problem in future SOFIA operations is that of scheduling flights in support of observations. Investigators are expected to propose small numbers of observations, and many observations must be grouped together to make up single flights. Flight planning for the previous generation airborne observatory, the Kuiper Airborne Observatory (KAO), was done by hand; planners had to choose takeoff time, observations to perform, and decide on setup-actions (called "dead-legs") to position the aircraft prior to observing. This task frequently required between 6-8 hours to plan one flight The scope of the flight planning problem for supporting GI observations with the anticipated flight rate for SOFIA makes the manual approach for flight planning daunting. In response, we have designed an Automated Flight Planner (AFP) that accepts as input a set of requested observations, designated flight days, weather predictions and fuel limitations, and searches automatically for high-quality flight plans that satisfy all relevant aircraft and astronomer specified constraints. The AFP can generate one candidate flight plan in 5-10 minutes, of computation time, a feat beyond the capabilities of human flight planners. The rate at which the AFP can generate flights enables humans to assess and analyze complex tradeoffs between fuel consumption, estimated science quality and the percentage of scheduled observations. Due to the changing nature of SOFIA scheduling problems, this functionality will play a crucial role in optimizing science and minimizing costs during operations. In the full paper, we will summarize the technical challenges that have been met in order to build this system. These include: design of the search algorithm, design of appropriate heuristics and approximations, and reduction in the size of the search space. We will also describe technical challenges that are currently being addressed, including the extension of the existing approach to handle new solution criteria. Finally, we will describe a variety of cultural challenges that the astronomical community must address in order to successfully use SOFIA, and describe how the AFT can be used to address some of these challenges. Specifically, many of the intended science users are accustomed to using ground-based or space-based observatories; we will identify some differences that arise due to the nature of airborne observatories, and how the AFT can be extended to provide useful services to ease these cultural differences.

Frank, Jeremy↗

NASA NTRS2006

Difficult Decisions Made Easier

NASA missions are extremely complex and prone to sudden, catastrophic failure if equipment falters or if an unforeseen event occurs. For these reasons, NASA trains to expect the unexpected. It tests its equipment and systems in extreme conditions, and it develops risk-analysis tests to foresee any possible problems. The Space Agency recently worked with an industry partner to develop reliability analysis software capable of modeling complex, highly dynamic systems, taking into account variations in input parameters and the evolution of the system over the course of a mission. The goal of this research was multifold. It included performance and risk analyses of complex, multiphase missions, like the insertion of the Mars Reconnaissance Orbiter; reliability analyses of systems with redundant and/or repairable components; optimization analyses of system configurations with respect to cost and reliability; and sensitivity analyses to identify optimal areas for uncertainty reduction or performance enhancement.

Source record↗

NASA NTRS2008

James Webb Space Telescope - Applying Lessons Learned to I&T

The James Webb Space Telescope (JWST) is part of a new generation of spacecraft acquiring large data volumes from remote regions in space. To support a mission such as the JWST, it is imperative that lessons learned from the development of previous missions such as the Hubble Space Telescope and the Earth Observing System mission set be applied throughout the development and operational lifecycles. One example of a key lesson that should be applied is that core components, such as the command and telemetry system and the project database, should be developed early, used throughout development and testing, and evolved into the operational system. The purpose of applying lessons learned is to reap benefits in programmatic or technical parameters such as risk reduction, end product quality, cost efficiency, and schedule optimization. In the cited example, the early development and use of the operational command and telemetry system as well as the establishment of the intended operational database will allow these components to be used by the developers of various spacecraft components such that development, testing, and operations will all use the same core components. This will reduce risk through the elimination of transitions between development and operational components and improve end product quality by extending the verification of those components through continual use. This paper will discuss key lessons learned that have been or are being applied to the JWST Ground Segment integration and test program.

Johns, Alan↗

NASA NTRS1954

Analysis of Rocket, Ram-Jet, and Turbojet Engines for Supersonic Propulsion of Long-Range Missles. II - Rocket Missile Performance

The theoretical performance of a two-stage ballistic rocket mis having a centerbody and two parallel boosters was investigated for J oxygen and ammonia-fluorine propellants. Both power-plant and missi parameters were optimized to give minimum cost on-the basis of the analysis for a range of 5500 nautical miles. After optimum values were found, each parameter was varied independently to determine its effect on performance of the missile. The missile using the ammonia-fluorine propellant weighs about one half as much as a missile using JP4-oxygen. Based on an expected unit cost of fluorine in quantity production, the ammonia-fluorine missile has a substantially lower relative cost than a JP4-oxygen missile. Optimum chamber pressures for both propellant systems and for both the centerbody and boosters were between 450 and 600 pounds per square inch. High design altitudes for the exhaust nozzle are desirable for both the centerbody and boosters. For the centerbody, the design altitude should be between 45,000 and 60,000 feet, with the value for ammonia-fluorine lower than that for JP4-oxygen. For the boosters, the design altitude should be 20,000 to 30,000 feet, with the value for the ammonia-fluorine. missile higher.

Huff, Vearl N.↗

NASA NTRS2013

The General-Use Nodal Network Solver (GUNNS) Modeling Package for Space Vehicle Flow System Simulation

The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.

Harvey, Jason↗

NASA NTRS2015

Computational Process Modeling for Additive Manufacturing (OSU)

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

Bagg, Stacey↗

NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Atmospheric probes have been successfully flown to planets and moons in the solar system to conduct in situ measurements. They include the Pioneer Venus multi-probes, the Galileo Jupiter probe, and Huygens probe. Probe mission concepts to five destinations, including Venus, Jupiter, Saturn, Uranus, and Neptune, have all utilized similar-shaped aeroshells and concept of operations, namely a 45-degree sphere cone shape with high density heatshield material and parachute system for extracting the descent vehicle from the aeroshell. Each concept designed its probe to meet specific mission requirements and to optimize mass, volume, and cost. At the 2017 International Planetary Probe Workshop (IPPW), NASA Headquarters postulated that a common aeroshell design could be used successfully for multiple destinations and missions. This "common probe" design could even be assembled with multiple copies, properly stored, and made available for future NASA missions, potentially realizing savings in cost and schedule and reducing the risk of losing technologies and skills difficult to sustain over decades. Thus the NASA Planetary Science Division funded a study to investigate whether a common probe design could meet most, if not all, mission needs to the five planetary destinations with extreme entry environments. The Common Probe study involved four NASA Centers and addressed these issues, including constraints and inefficiencies that occur in specifying a common design. Study methodology: First, a notional payload of instruments for each destination was defined based on priority measurements from the Planetary Science Decadal Survey. Steep and shallow entry flight path angles (EFPA) were defined for each planet based on qualification and operational g-load limits for current, state-of-the-art instruments. Interplanetary trajectories were then identified for a bounding range of EFPA. Next, 3-degrees-of-freedom simulations for entry trajectories were run using the entry state vectors from the interplanetary trajectories. Aeroheating correlations were used to generate stagnation point convective and radiative heat flux profiles for several aeroshell shapes and entry masses. High fidelity thermal response models for various Thermal Protection System (TPS) materials were used to size stagnation-point thicknesses, with margins based on previous studies. Backshell TPS masses were assumed based on scaled heat fluxes from the heatshield and also from previous mission concepts. Presentation: We will present an overview of the study scope, highlights of the trade studies and design driver analyses, and the final recommendations of a common probe design and assembly. We will also indicate limitations that the common probe design may have for the different destinations. Finally, recommended qualification approaches for missions will be presented.

Hwang, H. H.↗

NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Atmospheric probes have been successfully flown to planets and moons in the solar system to conduct in-situ measurements. They include the Pioneer Venus multi-probes, the Galileo Jupiter probe, and Huygens probe. Probe mission concepts to five destinations, including Venus, Jupiter, Saturn, Uranus, and Neptune, have all utilized similar-shaped aeroshells and concept of operations, namely a 45 deg sphere cone shape with high density heatshield material and parachute system for extracting the descent vehicle from the aeroshell. Each concept designed its probe to meet specific mission requirements and to optimize mass, volume, and cost. At the 2017 IPPW, NASA Headquarters postulated that a common aero-shell design could be used successfully for multiple destinations and missions. This "common probe" design could even be assembled with multiple copies, properly stored, and made available for future NASA missions, potentially realizing savings in cost and schedule and reducing the risk of losing technologies and skills difficult to sustain over decades. Thus the NASA Planetary Science Division funded a study to investigate whether a common probe design could meet most, if not all, mission needs to the five planetary destinations with extreme entry environments. The Common Probe study involved four NASA Centers and addressed these issues, including constraints and inefficiencies that occur in specifying a common design.Study methodology: First, a notional payload of instruments for each destination was defined based on priority measurements from the Planetary Science Decadal Survey. Steep and shallow entry flight path angles (EFPA) were defined for each planet based on qualification and operational g-load limits for current, state-of-the-art instruments. Interplanetary trajectories were then identified for a bounding range of EFPA. Next, 3-DoF simulations for entry trajectories were run using the entry state vectors from the interplanetary trajectories. Aeroheating correlations were used to generate stagnation point convective and radiative heat flux profiles for several aeroshell shapes and entry masses. High fidelity thermal response models for various TPS materials were used to size stagnation point thicknesses, with margins based on previous studies. Backshell TPS masses were assumed based on scaled heat fluxes from the heatshield and also from previous mission concepts.

Hwang, Helen H.↗

NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Hwang, Helen H.↗

NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Introduction: Atmospheric probes have been successfully flown to planets and moons in the solar system to conduct in situ measurements. They include the Pioneer Venus multiprobes, the Galileo Jupiter probe, and Huygens probe. Probe mission concepts to five destinations, including Venus, Jupiter, Saturn, Uranus, and Neptune, have all utilized similarshaped aeroshells and concept of operations, namely a 45° sphere cone shape with high density heatshield material and parachute system for extracting the descent vehicle from the aeroshell. The current paradigm is to design a probe to meet specific mission requirements and to optimize mass, volume, and cost for a single mission. However, this methodology means repeated efforts to design an aeroshell for different destinations with minor differences. A new paradigm has been explored that has a "common probe" design that could be flown at these different destinations and could be assembled in advance with multiple copies, properly stored, and made available for future NASA missions.

Hwang, Helen H.↗

NASA NTRS2022

Realizability Checking of Requirements in FRET

Requirements formalization has become increasingly popular in industrial settings as an effort to disambiguate designs and optimize development time and costs for critical system components. Formal requirements elicitation also enables the employment of analysis tools to prove important properties, such as consistency and realizability. In this report, we present the realizability analysis framework that we developed as part of the Formal Requirements Elicitation Tool (FRET). Our framework prioritizes usability, and employs state-of-the-art analysis algorithms that support infinite theories. We demonstrate the workflow for realizability checking, showcase the diagnosis process that supports visualization of conflicts between requirements and simulation of counterexamples, and discuss results from industrial-level case studies.

Formal Requirements Elicitation Tool↗

NASA NTRSDate not supplied

Turbine Electrified Energy Management with Model Predictive Control

Affordability, sustainability, and efficiency are primary motivators driving the future of NASA aeronautics research. These factors are realized, in part, through the development and implementation of new technologies and strategies enabling efficient, affordable, and safe hybrid-electric aircraft. Research supporting electrified aircraft propulsion control systems exemplifies such new methodologies, offering varied opportunities to integrate electric machines with gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures seek to introduce energy storage and exploit electrical power system components to assist gas-based system components. Capitalizing on the electric machines in hybridized engines, Turbine Electrified Energy Management (TEEM) is a control approach that enhances transient operability to improve overall propulsion and vehicle efficiency by injecting or extracting power from engine shafts. Traditionally implemented with proportional-integral (PI) control, this study expands the application of TEEM by presenting model predictive control (MPC) schemes to execute the TEEM concept. Via cost function design and constraint selection, the transient operability goals for TEEM are considered in the controller designs. The proposed MPCs are simulated on a nonlinear turbofan engine model at two environmental conditions, with comparisons drawn to a baseline PI. Performance is evaluated using compressor maps and two TEEM-specific metrics: transient stack usage and transient excursion integral. Simulation results reveal the developed schemes perform comparably to the benchmark controller and can be implemented in two distinct configurations. Potential modifications for future investigations include cost function measures that optimize energy use, additional performance effectiveness measures, and battery storage capabilities.

Elyse D. Hill↗

NASA NTRS2019

Exploring Network-Related Optimization Problems Using Quantum Heuristics

Network-related connectivity optimization problems are underlying a wide range of applications and are also of high computational complexity. We consider studying network optimization problems using two types of quantum heuristics.One is quantum annealing, and the other Quantum Alternating Operator Ansatz, an extension of the Quantum Approximate Optimization Algorithms for gate-model quantum computation, in which a cost-function based unitary and a non-commuting mixing unitary are applied alternately. We present problem mappings for problems of finding the spanning-tree or spanning-graph of a graph that optimizes certain costs, and a variant that further requires the spanning-tree be degree-bounded. With quantum annealing, all constraints are cast into penalty terms in the cost Hamiltonian, and the solution is encoded as the ground state of the Hamiltonian. We provide three mappings to the quadratic unconstrained binary optimization (QUBO) form, compare the resource requirements, and analyze the tradeoffs. For QAOA, we give special focus on the design of mixers based on the constraints presented in the problem, such that the system evolution remains in a subspace of the full Hilbert space where all constraints are satisfied. In the spanning-tree problem, one such hard constraint is that a mixer applied to a spanning-tree needs also be a spanning tree. This involves checking the connectivity of a subgraph, which is a global condition common for most network-related problems. We show how this feature can be efficiently represented in the mixer in a quantum coherent way, based on manipulation of a descendant-matrix and an adjacent matrix. We further develop a mixer for the spanning-graphs based on the spanning-tree mixer.

Wang, Zhihui↗

NASA NTRS2019

Study network-related optimization problems using quantum alternating optimization ansatz

Network-related connectivity optimization problems are underlying a wide range of applications and are also of high computational complexity. We consider studying network optimization problems using two types of quantum heuristics. One is quantum annealing, and the other Quantum Alternating Operator Ansatz, an extension of the Quantum Approximate Optimization Algorithms for gate-model quantum computation, in which a cost-function based unitary and a non-commuting mixing unitary are applied alternately. We present problem mappings for problems of finding the spanning-tree or spanning-graph of a graph that optimizes certain costs, and a variant that further requires the spanning-tree be degree-bounded. With quantum annealing, all constraints are cast into penalty terms in the cost Hamiltonian, and the solution is encoded as the ground state of the Hamiltonian. We provide three mappings to the quadratic unconstrained binary optimization (QUBO) form, compare the resource requirements, and analyze the tradeoffs. For QAOA, we give special focus on the design of mixers based on the constraints presented in the problem, such that the system evolution remains in a subspace of the full Hilbert space where all constraints are satisfied. In the spanning-tree problem, one such hard constraint is that a mixer applied to a spanning-tree needs also be a spanning tree. This involves checking the connectivity of a subgraph, which is a global condition common for most network-related problems. We show how this feature can be efficiently represented in the mixer in a quantum coherent way, based on manipulation of a descendant-matrix and an adjacent matrix. We further develop a mixer for the spanning-graphs based on the spanning-tree mixer.

Zhihui Wang↗