Search NASA⌕ Search

SEARCH · Search NASA

Results for “Search algorithm”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

Wolpert, David H.↗
NASA NTRS2005

Planning with Continuous Resources in Stochastic Domains

We consider the problem of optimal planning in stochastic domains with metric resource constraints. Our goal is to generate a policy whose expected sum of rewards is maximized for a given initial state. We consider a general formulation motivated by our application domain--planetary exploration--in which the choice of an action at each step may depend on the current resource levels. We adapt the forward search algorithm AO* to handle our continuous state space efficiently.

Mausam, Mausau↗
NASA NTRS2007

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

DeLoach, Richard↗
NASA NTRS2008

Geometric Modeling of Inclusions as Ellipsoids

Nonmetallic inclusions in gas turbine disk alloys can have a significant detrimental impact on fatigue life. Because large inclusions that lead to anomalously low lives occur infrequently, probabilistic approaches can be utilized to avoid the excessively conservative assumption of lifing to a large inclusion in a high stress location. A prerequisite to modeling the impact of inclusions on the fatigue life distribution is a characterization of the inclusion occurrence rate and size distribution. To help facilitate this process, a geometric simulation of the inclusions was devised. To make the simulation problem tractable, the irregularly sized and shaped inclusions were modeled as arbitrarily oriented, three independent dimensioned, ellipsoids. Random orientation of the ellipsoid is accomplished through a series of three orthogonal rotations of axes. In this report, a set of mathematical models for the following parameters are described: the intercepted area of a randomly sectioned ellipsoid, the dimensions and orientation of the intercepted ellipse, the area of a randomly oriented sectioned ellipse, the depth and width of a randomly oriented sectioned ellipse, and the projected area of a randomly oriented ellipsoid. These parameters are necessary to determine an inclusion s potential to develop a propagating fatigue crack. Without these mathematical models, computationally expensive search algorithms would be required to compute these parameters.

Bonacuse, Peter J.↗
NASA NTRS2006

Generation of Data-Rate Profiles of Ka-Band Deep-Space Links

A short report discusses a methodology for designing Ka-band Deep-Space-to- Earth radio-communication links. This methodology is oriented toward minimizing the effects of weather on the Ka-band telecommunication link by maximizing the expected data return subject to minimum link availability and a limited number of data rates. This methodology differs from the current standard practices in which a link is designed according to a margin policy for a given link availability at 10 elevation. In this methodology, one chooses a data-rate profile that will maximize the average data return over a pass while satisfying a minimum-availability requirement for the pass, subject to mission operational limitations expressed in terms of the number of data rates used during the pass. The methodology is implemented in an intelligent search algorithm that first finds the allowable data-rate profiles from the mission constraints, spacecraft-to-Earth distance, spacecraft EIRP (effective isotropic radiated power), and the applicable zenith atmospheric noise temperature distribution, and then selects the best data rate in terms of maximum average data return from the set of allowable data-rate profiles.

Shambayati, Shervin↗
NASA NTRS2005

Quantifying Traversability of Terrain for a Mobile Robot

A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.

Howard, Ayanna↗
NASA NTRS2011

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Kumar, Sujay V.↗
NASA NTRS2012

Development of a Robust and Efficient Parallel Solver for Unsteady Turbomachinery Flows

The traditional design and analysis practice for advanced propulsion systems relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. In the design of advanced propulsion systems, CFD plays a major role in defining the required performance over the entire flight regime, as well as in testing the sensitivity of the design to the different modes of operation. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment. The turbomachinery simulation capability presented here is being developed in a computational tool called Loci-STREAM [1]. It integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci [2] which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective is to be able to routinely simulate problems involving complex geometries requiring large unstructured grids and complex multidisciplinary physics. An immediate application of interest is simulation of unsteady flows in rocket turbopumps, particularly in cryogenic liquid rocket engines. The key components of the overall methodology presented in this paper are the following: (a) high fidelity unsteady simulation capability based on Detached Eddy Simulation (DES) in conjunction with second-order temporal discretization, (b) compliance with Geometric Conservation Law (GCL) in order to maintain conservative property on moving meshes for second-order time-stepping scheme, (c) a novel cloud-of-points interpolation method (based on a fast parallel kd-tree search algorithm) for interfaces between turbomachinery components in relative motion which is demonstrated to be highly scalable, and (d) demonstrated accuracy and parallel scalability on large grids (approx 250 million cells) in full turbomachinery geometries.

West, Jeff↗
NASA NTRS2014

Swarmie User Manual: A Rover Used for Multi-agent Swarm Research

The ability to create multiple functional yet cost effective robots is crucial for conducting swarming robotics research. The Center Innovation Fund (CIF) swarming robotics project is a collaboration among the KSC Granular Mechanics and Regolith Operations (GMRO) group, the University of New Mexico Biological Computation Lab, and the NASA Ames Intelligent Robotics Group (IRG) that uses rovers, dubbed "Swarmies", as test platforms for genetic search algorithms. This fall, I assisted in the development of the software modules used on the Swarmies and created this guide to provide thorough instructions on how to configure your workspace to operate a Swarmie both in simulation and out in the field.

Robotics↗
NASA NTRS2012

An Examination of Coarse Sun Sensor Contingencies in Attitude Determination and the Sun Vector Calculation

Satellite pointing is vital to the success of a mission. One element of that entails describing the position of the sun relative to the frame of the satellite. Coarse Sun Sensors (CSS) are typically used to provide the information to calculate the sun's position in Safe Modes or contingency operations. In the OCO-2 configuration there are 13 CSS total, which provide redundant 4 celestial coverage. Failures of the individual CSS elements can introduce holes in the celestial coverage resulting in potential loss of sun knowledge. These failures must be analyzed to determine if the contingency plan is sufficient to assure mission success. First the static case was looked at and determined that at a maximum, 3 CSS failures can be sustained on the body and 1 on the array without causing coverage holes. Also array sensors are more important to mission success. The Sun Vector calculation has been transcribed to MATLAB code and failure scenarios are being examined to determine the maximum error given a set of failure scenarios. This activity indicated that if there is a loss of the sun, the sun-searching algorithm could be modified to use XZ rotation as that is guaranteed to find it whereas the design using the YZ rotation misses the sun if it is at the + or - Y orientation.

celestial bodies↗
NASA NTRS2016

Orion GN&C Fault Management System Verification: Scope And Methodology

In order to ensure long-term ability to meet mission goals and to provide for the safety of the public, ground personnel, and any crew members, nearly all spacecraft include a fault management (FM) system. For a manned vehicle such as Orion, the safety of the crew is of paramount importance. The goal of the Orion Guidance, Navigation and Control (GN&C) fault management system is to detect, isolate, and respond to faults before they can result in harm to the human crew or loss of the spacecraft. Verification of fault management/fault protection capability is challenging due to the large number of possible faults in a complex spacecraft, the inherent unpredictability of faults, the complexity of interactions among the various spacecraft components, and the inability to easily quantify human reactions to failure scenarios. The Orion GN&C Fault Detection, Isolation, and Recovery (FDIR) team has developed a methodology for bounding the scope of FM system verification while ensuring sufficient coverage of the failure space and providing high confidence that the fault management system meets all safety requirements. The methodology utilizes a swarm search algorithm to identify failure cases that can result in catastrophic loss of the crew or the vehicle and rare event sequential Monte Carlo to verify safety and FDIR performance requirements.

Brown, Denise↗
NASA NTRS2017

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Englander, Arnold C.↗
NASA NTRS2017

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Englander, Arnold C.↗
NASA NTRS2015

Efficient Maneuver Placement for Automated Trajectory Design

When designing a mission, the addition of a maneuver at the right spot often improves the utility of an otherwise mediocre trajectory. However, the additional degrees of freedom of finding the best maneuver location can severely complicate automated broad-search algorithms. A computationally-efficient formulation that reduces the maneuver design space to a single dimension is presented, where the efficacy of additional maneuvers along previously computed transfers is calculated explicitly via Lawden's "primer vector." Examples include leveraging maneuvers to ease capture at Europa, phasing maneuvers to enable resonant-hopping among Saturn's moons, and broken-plane maneuvers on transfers to Mars.

Landau, Damon↗
NASA NTRS2015

Trajectories for a Near Term Mission to the Interstellar Medium

Trajectories for rapid access to the interstellar medium (ISM) with a Kuiper Belt Object (KBO) flyby, launching between 2022 and 2030, are described. An impulsive-patched-conic broad search algorithm combined with a local optimizer is used for the trajectory computations. Two classes of trajectories, (1) with a powered Jupiter flyby and (2) with a perihelion maneuver, are studied and compared. Planetary flybys combined with leveraging maneuvers reduce launch C3 requirements (by factor of 2 or more) and help satisfy mission-phasing constraints. Low launch C3 combined with leveraging and a perihelion maneuver is found to be enabling for a near-term potential mission to the ISM.

ISM↗
NASA NTRS2016

Trajectories for Europa Flyby Sample Return

Ballistic trajectories are computed which would enable a sample return mission to Europa without capturing, descending, or landing. The low-cost mission concept utilizes a free return trajectory that also involves a close flyby of Europa. Near Europa, a small impactor would kinetically impact the icy moon and generate a plume, subsequently sampled by the spacecraft. A broad search algorithm is developed to construct feasible itineraries, which considers Venus and Earth gravity assist sequences. High-quality solutions are then differentially corrected to be continuous using high-fidelity dynamics. The complete methodology is applicable to other outer-planet moons, notably Enceladus. The outbound VEEGA option is found to signifcantly reduce launch C3 compared to alternate options. The characteristics and quality of the solutions exhibit substantial variation over the 12-year period of Jupiter. Nevertheless, a variety of optimized results are computed with C3 as low as 16.0 sq.km/sq.sec, re-entry speed well below that of the Stardust capsule, and flight times of 9 to 15 years.

Jones, Drew Ryan↗
NASA NTRS2016

Trajectories for Flyby Sample Return at Saturn's Moons

Ballistic trajectories are computed which would enable a sample return mission to Titan or Enceladus without capturing, descending, or landing. The low-cost mission concept utilizes a free return trajectory that also involves a close flyby of the moon. This work extends the concept, and related trajectory analysis methodology, previously applied to a Europa mission. Specifically, a broad search algorithm is employed to systematically locate potentially feasible itineraries over an entire Saturn period. High-quality approximate solutions are then optimized to be continuous using high-fidelity dynamics. Techniques and software from the Europa analysis, were readily adapted and able to find numerous mission enabling trajectories. A direct mission to Titan is possible with flight time under 16 years and Earth-relative speeds below 11.0 km/sec. The VEEGA option is shown to substantially reduce launch C3, but flight times exceed 21 years. Unfortunately, an Enceladus mission requires a flight time of 25 years or more, and incurs fairly high relative speeds. Nevertheless, an optimized reference mission is computed.

Jones, Drew Ryan↗
NASA NTRS2019

Dynamic Replanning of Low Noise Rotorcraft Operations

A new method for rapidly planning and dynamically replanning low noise rotorcraft flight operations is developed. A large database of rotorcraft maneuver segments is generated, and an acoustic cost is assigned to each segment by using a computationally efficient semiempirical rotorcraft noise modeling method that accurately models the changes in rotor noise caused by maneuvering flight. Combinatoric optimization techniques are then employed to combine these maneuver segments into a low noise optimal flight path. A simple heuristic for estimating the total acoustic cost required to reach the target location is developed and incorporated into the search algorithm, allowing the computation of low noise paths in seconds. A procedure for implementing an “anytime” version of the method is described, enabling feasible solutions to be dynamically replanned “on the fly”—i.e., in fractions of a second—and refined over time to a low noise optimal solution.

Greenwood, Eric↗