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At least 271 records · Page 15

Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASA’s Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a good option for computing wind-optimal trajectories for national and global air traffic system studies.

Ng, Hok K.↗

The Mathematics of Navigating the Solar System

In navigating spacecraft throughout the solar system, the space navigator relies on three academic disciplines - optimization, estimation, and control - that work on mathematical models of the real world. Thus, the navigator determines the flight path that will consume propellant and other resources in an efficient manner, determines where the craft is and predicts where it will go, and transfers it onto the optimal trajectory that meets operational and mission constraints. Mission requirements, for example, demand that observational measurements be made with sufficient precision that relativity must be modeled in collecting and fitting (the estimation process) the data, and propagating the trajectory. Thousands of parameters are now determined in near real-time to model the gravitational forces acting on a spacecraft in the vicinity of an irregularly shaped body. Completing these tasks requires mathematical models, analyses, and processing techniques. Newton, Gauss, Lambert, Legendre, and others are justly famous for their contributions to the mathematics of these tasks. More recently, graduate students participated in research to update the gravity model of the Saturnian system, including higher order gravity harmonics, tidal effects, and the influence of the rings. This investigation was conducted for the Cassini project to incorporate new trajectory modeling features in the navigation software. The resulting trajectory model will be used in navigating the 4-year tour of the Saturnian satellites. Also, undergraduate students are determining the ephemerides (locations versus time) of asteroids that will be used as reference objects in navigating the New Millennium's Deep Space 1 spacecraft autonomously.

Hintz, Gerald↗

Integration of Product, Package, Process, and Environment: A Food System Optimization

The food systems slated for future NASA missions must meet crew nutritional needs, be acceptable for consumption, and use resources efficiently. Although the current food system of prepackaged, moderately stabilized food items works well for International Space Station (ISS) missions, many of the current space menu items do not maintain acceptability and/or nutritive value beyond 2 years. Longer space missions require that the food system can sustain the crew for 3 to 5 years without replenishment. The task "Integration of Product, Package, Process, and Environment: A Food System Optimization" has the objective of optimizing food-product shelf life for the space-food system through product recipe adjustments, new packaging and processing technologies, and modified storage conditions. Two emergent food processing technologies were examined to identify a pathway to stable, wet-pack foods without the detrimental color and texture effects. Both microwave-assisted thermal sterilization (MATS) and pressure-assisted thermal stabilization (PATS) were evaluated against traditional retort processing to determine if lower heat inputs during processing would produce a product with higher micronutrient quality and longer shelf life. While MATS products did have brighter color and better texture initially, the advantages were not sustained. The non-metallized packaging film used in the process likely provided inadequate oxygen barrier. No difference in vitamin stability was evident between MATS and retort processed foods. Similarly, fruit products produced using PATS showed improved color and texture through 3 years of storage compared to retort fruit, but the vitamin stability was not improved. The final processing study involved freeze drying. Five processing factors were tested in factorial design to assess potential impact of each to the quality of freeze-dried food, including the integrity of the microstructure. The initial freezing rate and primary freeze drying temperature and pressure were linked to final product quality in freeze-dried corn, indicating processing modifications that could lead to improved product shelf life. Storage temperatures and packaging systems were also assessed for the impact to food quality. Reduced temperature storage had inconclusive impact to the progression of rancidity in butter cookies. Frozen storage was detrimental to fruit and vegetable textural attributes but refrigerated storage helped to sustain color and organoleptic ratings for plant-based foods. With regard to packaging systems, the metallized film overwrap significantly decreased the progression of the rancidity of butter cookies as compared to the highest barrier non-metallized film. The inclusion of oxygen scavengers resulted in noticeable moisture gains in butter cookies over time, independent of packaging film systems. Neither emergent processing technology nor the freeze dry optimization resulted in compelling quality differences from current space food provisions such that a five-year shelf life is likely with these processing changes alone. Using a combination of refrigeration and PATS processing is expected to result in organoleptically-acceptable fruit quality for most fruits through five years. The vitamin degradation will be aided somewhat by the cold temperatures but, given the labile nature of vitamin C, a more stable fortification method, such as encapsulation, should also be investigated to ensure vitamin delivery throughout the product life. Similarly, significant improvement to the packaging film used in the MATS processing, optimization of formulation for dielectric properties, vitamin fortification, and reduced temperature storage should be investigated as a hurdle approach to reach a five year shelf life in wet-pack entrees and soups. Baked goods and other environmentally-sensitive spaceflight foods will require an almost impenetrable barrier to protect the foods from oxygen and moisture ingress but scavengers and reduced storage temperature did not improve baked good shelf life and are not recommended at this time for these foods.

Cooper, Maya R.↗

Efficient Gradient-Based Shape Optimization Methodology Using Inviscid/Viscous CFD

The formerly developed preconditioned-biconjugate-gradient (PBCG) solvers for the analysis and the sensitivity equations had resulted in very large error reductions per iteration; quadratic convergence was achieved whenever the solution entered the domain of attraction to the root. Its memory requirement was also lower as compared to a direct inversion solver. However, this memory requirement was high enough to preclude the realistic, high grid-density design of a practical 3D geometry. This limitation served as the impetus to the first-year activity (March 9, 1995 to March 8, 1996). Therefore, the major activity for this period was the development of the low-memory methodology for the discrete-sensitivity-based shape optimization. This was accomplished by solving all the resulting sets of equations using an alternating-direction-implicit (ADI) approach. The results indicated that shape optimization problems which required large numbers of grid points could be resolved with a gradient-based approach. Therefore, to better utilize the computational resources, it was recommended that a number of coarse grid cases, using the PBCG method, should initially be conducted to better define the optimization problem and the design space, and obtain an improved initial shape. Subsequently, a fine grid shape optimization, which necessitates using the ADI method, should be conducted to accurately obtain the final optimized shape. The other activity during this period was the interaction with the members of the Aerodynamic and Aeroacoustic Methods Branch of Langley Research Center during one stage of their investigation to develop an adjoint-variable sensitivity method using the viscous flow equations. This method had algorithmic similarities to the variational sensitivity methods and the control-theory approach. However, unlike the prior studies, it was considered for the three-dimensional, viscous flow equations. The major accomplishment in the second period of this project (March 9, 1996 to March 8, 1997) was the extension of the shape optimization methodology for the Thin-Layer Navier-Stokes equations. Both the Euler-based and the TLNS-based analyses compared with the analyses obtained using the CFL3D code. The sensitivities, again from both levels of the flow equations, also compared very well with the finite-differenced sensitivities. A fairly large set of shape optimization cases were conducted to study a number of issues previously not well understood. The testbed for these cases was the shaping of an arrow wing in Mach 2.4 flow. All the final shapes, obtained either from a coarse-grid-based or a fine-grid-based optimization, using either a Euler-based or a TLNS-based analysis, were all re-analyzed using a fine-grid, TLNS solution for their function evaluations. This allowed for a more fair comparison of their relative merits. From the aerodynamic performance standpoint, the fine-grid TLNS-based optimization produced the best shape, and the fine-grid Euler-based optimization produced the lowest cruise efficiency.

Baysal, Oktay↗

Optimal Integration of Departures and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources, such as route segments, fixes, and runways, improves the efficiency of terminal airspace management. Problems in this category are, in general, computationally difficult compared to conventional scheduling problems. This paper presents a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA). It was first applied to a test problem introduced in existing literature. An experiment with a test problem showed that new methods can solve the 20 aircraft problem in fast time with a 65% or 440 second delay reduction using shared departure fixes. In order to test its application in a more realistic and complicated problem, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial separation in current operations, which may introduce unnecessary delays. In this work, three types of separations - spatial, temporal, and hybrid separations - were formulated using the new algorithm. The hybrid separation combines both temporal and spatial separations. Results showed that although temporal separation achieved less delay than spatial separation with a small uncertainty buffer, spatial separation outperformed temporal separation when the uncertainty buffer was increased. Hybrid separation introduced much less delay than both spatial and temporal approaches. For a total of 15 interacting departures and arrivals, when compared to spatial separation, the delay reduction of hybrid separation varied between 11% or 3.1 minutes and 64% or 10.7 minutes corresponding to an uncertainty buffer from 0 to 60 seconds. Furthermore, as a comparison with the NSGA algorithm, a First-Come-First-Serve based heuristic method was implemented for the hybrid separation. Experiments showed that the results from the NSGA algorithm have 9% to 42% less delay than the heuristic method with varied uncertainty buffer sizes.

terminal airspace↗

GA-optimization for rapid prototype system demonstration

An application of the Genetic Algorithm (GA) is discussed. A novel scheme of Hierarchical GA was developed to solve complicated engineering problems which require optimization of a large number of parameters with high precision. High level GAs search for few parameters which are much more sensitive to the system performance. Low level GAs search in more detail and employ a greater number of parameters for further optimization. Therefore, the complexity of the search is decreased and the computing resources are used more efficiently.

Kim, Jinwoo↗

VIPER: Introduction to the Resource Prospecting Mission

With the Artemis Program, NASA plans to return humans to the Moon to stay, which means if there are local materials available, they could be deployed to help support extended lunar stays. Since the moon’s polar regions have confirmed the presence of volatiles, as revealed by LCROSS, LRO and other lunar missions, the next step is to understand the nature and distribution of those candidate resources and how they might be extracted. Recent studies have even indicated local volatiles could be processed into propellants and human life-supporting resources, significantly aiding in sustaining humans on the Moon, and eventually and later to support missions to Mars. The Volatiles Investigating Polar Exploration Resource (VIPER) is an in-situ resource utilization (ISRU) mission within NASA’s Science Mission Directorate (SMD), based on the pathfinding development of the Resource Prospector (RP) mission concept. This clever mission is targeting late 2023 and may spend over 100 days mapping and surveying four different Ice Stability Regions to understand the nature and distribution of water and volatiles already confirmed to be there, including measuring mineralogical content such as silicon and light metals from lunar regolith. The knowledge attained by a mission like VIPER could have many-fold benefits for space exploration, but also commercial applications. VIPER is an essential, early mission supporting the “moon rush” which has developed over the past few years, with both governments and commercial entities making their cases for lunar exploration. VIPER aims to understand just how the water-ice and other volatiles are distributed, both horizontally and vertically, enabling creation of volatiles resource maps, which will guide what might be required to harvest those resources at scale. With sufficient infrastructural investment, led by governments and then optimized by the commercial marketplace, VIPER will be a pathfinder mission addressing key decadal lunar science and early strategic knowledge gaps.

Daniel Andrews↗

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↗

Resource and environmental surveys from space with the thematic mapper in the 1980's

The selection of observation of vegetation is the primary optimization objective of the thematic mapper. The following are aspects of plans for the thematic mapper: (1) to include an appropriately modified first generation MSS in the thematic mapper mission; (2) to provide assured coverage for a minimum of six years to give agencies and other users an opportunity to justify the necessary commitment of resources for the transition into a completely valid operational phase; (3) to provide for global, direct data read-out, without the necessity for on-board data storage or dependence on foreign receiving stations; (4) to recognize the operational character of the thematic mapper after successful completion of its experimental evaluation; and (5) to combine future experimental packages with compatible orbits as part of the operational LANDSAT follow-on payloads.

Source record↗

A Framework for Optimization-Based ISRU Tool Design Using Discrete Element Modeling

Novel robotic excavation technologies are needed to perform in-situ resource utilization (ISRU) tasks at levels required to sustain a long-term presence on the lunar surface. Developing and testing multiple iterations of functional hardware is time and cost prohibitive, thus slowing down the pace of progress and delaying humanity’s settlement of the Moon. High-fidelity, physics-based simulation can reduce the time and effort required to develop and deploy robotic systems [1]. We have adopted this approach to create high-fidelity models of robotic test hardware to enable rapid virtual design and optimization of excavation technologies [2]. Such models can leverage modern computational tools like Discrete Element Method (DEM) simulations that can be coupled with automated design approaches like topology optimization to reduce the amount of prototyping and physical testing needed to realize useful tools.

ISRU↗

Controlling Distributed Planning

A system of software implements an extended version of an approach, denoted shared activity coordination (SHAC), to the interleaving of planning and the exchange of plan information among organizations devoted to different missions that normally communicate infrequently except that they need to collaborate on joint activities and/or the use of shared resources. SHAC enables the planning and scheduling systems of the organizations to coordinate by resolving conflicts while optimizing local planning solutions. The present software provides a framework for modeling and executing communication protocols for SHAC. Shared activities are represented in each interacting planning system to establish consensus on joint activities or to inform the other systems of consumption of a common resource or a change in a shared state. The representations of shared activities are extended to include information on (1) the role(s) of each participant, (2) permissions (defined as specifications of which participant controls what aspects of shared activities and scheduling thereof), and (3) constraints on the parameters of shared activities. Also defined in the software are protocols for changing roles, permissions, and constraints during the course of coordination and execution.

Clement, Bradley↗

An Analytical Solution for Yaw Maneuver Optimization on the International Space Station and Other Orbiting Space Vehicles

This paper presents a new method for optimizing yaw maneuvers, which are the most common large maneuvers on the International Space Station (ISS). The goal of the maneuver optimization is to find a maneuver trajectory with minimal torques acting on the vehicle during the maneuver. Therefore, the thruster firings necessary to perform the maneuver are minimized. Reduction of thruster firings saves propellant and decreases structural loads and contamination of the vehicle critical elements, thus saving the service life of the thrusters and the vehicle itself. Equations describing the pitch and roll motion needed to counteract the major torques during a yaw maneuver are obtained. Also, a yaw rate profile is suggested. In the obtained optimized case, the torques are significantly reduced. The proposed approximate analytical solution does not require extensive computer resources and, therefore, can be implemented using software onboard the ISS. As a result, the maneuver execution will be automatic. This is one of the major benefits of the simplified solution presented in this paper with respect to existing computational approaches. The suggested maneuver optimization method can be used not only for the ISS, but for other space vehicles as well.

Dobrinskaya, Tatiana↗

Electronic neural network for dynamic resource allocation

A VLSI implementable neural network architecture for dynamic assignment is presented. The resource allocation problems involve assigning members of one set (e.g. resources) to those of another (e.g. consumers) such that the global 'cost' of the associations is minimized. The network consists of a matrix of sigmoidal processing elements (neurons), where the rows of the matrix represent resources and columns represent consumers. Unlike previous neural implementations, however, association costs are applied directly to the neurons, reducing connectivity of the network to VLSI-compatible 0 (number of neurons). Each row (and column) has an additional neuron associated with it to independently oversee activations of all the neurons in each row (and each column), providing a programmable 'k-winner-take-all' function. This function simultaneously enforces blocking (excitatory/inhibitory) constraints during convergence to control the number of active elements in each row and column within desired boundary conditions. Simulations show that the network, when implemented in fully parallel VLSI hardware, offers optimal (or near-optimal) solutions within only a fraction of a millisecond, for problems up to 128 resources and 128 consumers, orders of magnitude faster than conventional computing or heuristic search methods.

Thakoor, A. P.↗

Spatial Coverage Planning and Optimization for Planetary Exploration

We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

autonomy↗

User Preference Optimization for Oversubscribed Scheduling of NASA’s Deep Space Network

NASA’s Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process — oversubsubscription and how to “fairly” reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗

Increasing Efficiency at the NTF by Optimizing Model AoA Positioning

The National Transonic Facility (NTF) at NASA Langley Research Center (LaRC) is a national resource for aeronautical research and development. The government, military and private industries rely on the capability of this facility for realistic flight data. Reducing the operation costs and keeping the NTF affordable is essential for aeronautics research. The NTF is undertaking an effort to reduce the time between data points during a pitch polar. This reduction is being driven by the operating costs of a cryogenic facility. If the time per data point can be reduced, a substantial cost savings can be realized from a reduction in liquid nitrogen (LN2) consumption. It is known that angle-of-attack (AoA) positioning is the longest lead-time item between points. In January 2005 a test was conducted at the NTF to determine the cause of the long lead-time so that an effort could be made to improve efficiency. The AoA signal at the NTF originates from onboard instrumentation then travels through a number of different systems including the signal conditioner, digital voltmeter, and the data system where the AoA angle is calculated. It is then fed into a closed loop control system that sets the model position. Each process along this path adds to the time per data point affecting the efficiency of the data taking process. Due to the nature of the closed loop feed back AoA control and the signal path, it takes approximately 18 seconds to take one pitch pause point with a typical AoA increment. Options are being investigated to reduce the time delay between points by modifying the signal path. These options include: reduced signal filtering, using analog channels instead of a digital volt meter (DVM), re-routing the signal directly to the AoA control computer and implementing new control algorithms. Each of these has potential to reduce the positioning time and together the savings could be significant. These timesaving efforts are essential but must be weighed against possible loss of data quality. For example, a reduction in filtering can introduce noise into the signal and using analog channels could result in some loss of accuracy. Data quality assessments need to be performed concurrently with timesaving techniques since data quality parameters are essential in maintaining facility integrity. This paper will highlight time saving efforts being undertaken or studied at the NTF. It will outline the instrumentation and computer systems involved in setting of the model pitch attitude then suggest changes to the process and discuss how these system changes would effect the time between data points. It also discusses the issue of data quality and how the potential efficiency changes in the system could affect it. Lastly, it will discuss the possibility of using an open loop control system and give some pros and cons of this method.

Crawford, Bradley L.↗

Atmospheric Mining in the Outer Solar System: Aerospacecraft Analysis, Propulsion, and Resource Capturing Implications

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. With these two additional gases, the potential for fueling small and large fleets of additional exploration and exploitation vehicles exists. Analyses of orbital transfer vehicles (OTVs), landers, and in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points. Aerospacecraft with closed cycle gas core propulsion are used to capture the 3He and deuterium from the outer planet atmospheres. Additional analyses of aerospacecraft sizing led to important results, reducing the overall mining system mass by many thousands of metric tons. Earlier analyses had focused on small aerospacecraft payloads. Important influences on mining time in the atmosphere were also analyzed and will be presented.

In Situ Resource Utilization↗