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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.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

A laboratory implementation of a fuzzy logic-tracking controller using a low cost Motorola MC68HC11E9 microprocessor is described in this report. The objective is to design the most optimal yet practical controller that can be implemented and marketed, and which gives respectable performance, even when the system loads, inertia and parameters are varying. A distinguishing feature of this work is the by-product goal of developing a marketable, simple, functional and low cost controller. Additionally, real-time nonlinearities are not ignored, and a mathematical model is not required. A number of components have been designed, built and tested individually, and in various combinations of hardware and software segments. These components have been integrated with a brushless motor to constitute the drive system. A microprocessor-based FLC is incorporated to provide robust speed and position control. Design objectives that are difficult to express mathematically can be easily incorporated in a fuzzy logic-based controller by linguistic information (in the form of fuzzy IF-THEN rules). The theory and design are tested in the laboratory using a hardware setup. Several test cases have been conducted to confirm the effectiveness of the proposed controller. The results indicate excellent tracking performance for both speed and position trajectories. For the purpose of comparison, a bang-bang controller has been tested. The fuzzy logic controller performs significantly better than the traditional bang-bang controller. The bang-bang controller has been shown to be relatively inaccurate and lacking in robustness. Description of the implementation hardware system is also given.

Rubaai, Ahmed↗
NASA NTRS2019

NtGCM User's Manual: 1.1 (High Pressure High Temperature Laser based) Nanotube Growth Chamber Monitor

This manual describes the installation and use of NtGCM software. NtGCM is software designed for monitoring the growth of nanotubes in a high temperature and high pressure chamber using a laser*. NtGCM software monitors a dozen dierent parameters that are important to understanding the growth of the nanomaterials including the laser input power, the temperature at eight separate locations inside and outside the growth chamber, as well as the pressure and ow rate of the gaseous media that control the environment in the chamber. The measurements are all made in real time. The program features a robust user account management layer and a rich data display manager that allows plotted data, displayed units and other parameters to be changed on the y for the operator's convenience.

Sauti, Godfrey↗
NASA NTRS1994

A Study on the Effect of Communication Performance on Message-Passing Parallel Programs: Methodology and Case Studies

From a source-program perspective, the performance achieved on distributed/parallel systems is governed by the underlying message-passing library overhead and the network capabilities of the architecture. Studying the impact of changes in these features on the source-program. can have a significant influence in the development of next-generation system designs. In this paper we introduce a simple and robust tool that can be used for this purpose. This tool is based on event-driven simulation of programs that generates a new set of trace events - that preserves causality and partial order - corresponding to the expected execution of the program in the simulated environment. Trace events can be visualized and source-level profile information can be used to pin-point locations of program which are most significantly affected with changing system parameters in the simulated environment. We present a number of examples from the NAS benchmark suite, executed on the Intel Paragon and iPSC/860 that are used to identify and expose performance bottlenecks with varying system parameters. Specific aspects of the system that significantly effect these benchmarks are presented and discussed,

Sarukkai, Sekhar R.↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRS1988

An application of eigenspace methods to symmetric flutter suppression

An eigenspace assignment approach to the design of parameter insensitive control laws for linear multivariable systems is presented. The control design scheme utilizes constrained optimization techniques to exploit the flexibility in eigenvector assignments to reduce control system sensitivity to changes in system parameters while maintaining performance requirements; it thus provides a systematic approach for choosing values for eigensystem design variables. The methods involve use of the singular value decomposition to provide an exact description of allowable eigenvectors in terms of a minimum number of design parameters. In a design example, the methods are applied to the problem of symmetric flutter suppression in an aeroelastic vehicle. In this example the flutter mode is sensitive to changes in dynamic pressure and eigenspace methods are used to enhance the performance of a stabilizing minimum energy/linear quadratic regulator controller and associated observer. Numerical results indicate that the methods provide feedback control laws that make the stability of the nominal closed loop systems less sensitive to changes in dynamic pressure, while maintaining acceptable control power and robustness constraints.

Fennell, Robert E.↗
NASA NTRS2004

Experimental Design for the LATOR Mission

This paper discusses experimental design for the Laser Astrometric Test Of Relativity (LATOR) mission. LATOR is designed to reach unprecedented accuracy of 1 part in 10(exp 8) in measuring the curvature of the solar gravitational field as given by the value of the key Eddington post-Newtonian parameter gamma. This mission will demonstrate the accuracy needed to measure effects of the next post-Newtonian order (near infinity G2) of light deflection resulting from gravity s intrinsic non-linearity. LATOR will provide the first precise measurement of the solar quadrupole moment parameter, J(sub 2), and will improve determination of a variety of relativistic effects including Lense-Thirring precession. The mission will benefit from the recent progress in the optical communication technologies the immediate and natural step above the standard radio-metric techniques. The key element of LATOR is a geometric redundancy provided by the laser ranging and long-baseline optical interferometry. We discuss the mission and optical designs, as well as the expected performance of this proposed mission. LATOR will lead to very robust advances in the tests of Fundamental physics: this mission could discover a violation or extension of general relativity, or reveal the presence of an additional long range interaction in the physical law. There are no analogs to the LATOR experiment; it is unique and is a natural culmination of solar system gravity experiments.

Turyshev, Slava G.↗
NASA NTRS2005

Fitting Nonlinear Curves by use of Optimization Techniques

MULTIVAR is a FORTRAN 77 computer program that fits one of the members of a set of six multivariable mathematical models (five of which are nonlinear) to a multivariable set of data. The inputs to MULTIVAR include the data for the independent and dependent variables plus the user s choice of one of the models, one of the three optimization engines, and convergence criteria. By use of the chosen optimization engine, MULTIVAR finds values for the parameters of the chosen model so as to minimize the sum of squares of the residuals. One of the optimization engines implements a routine, developed in 1982, that utilizes the Broydon-Fletcher-Goldfarb-Shanno (BFGS) variable-metric method for unconstrained minimization in conjunction with a one-dimensional search technique that finds the minimum of an unconstrained function by polynomial interpolation and extrapolation without first finding bounds on the solution. The second optimization engine is a faster and more robust commercially available code, denoted Design Optimization Tool, that also uses the BFGS method. The third optimization engine is a robust and relatively fast routine that implements the Levenberg-Marquardt algorithm.

Hill, Scott A.↗
NASA NTRS1988

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution, appendix 2

This thesis reviews the technique established to clear channels in the Power Spectral Estimate by applying linear combinations of well known window functions to the autocorrelation function. The need for windowing the auto correlation function is due to the fact that the true auto correlation is not generally used to obtain the Power Spectral Estimate. When applied, the windows serve to reduce the effect that modifies the auto correlation by truncating the data and possibly the autocorrelation has on the Power Spectral Estimate. It has been shown in previous work that a single channel has been cleared, allowing for the detection of a small peak in the presence of a large peak in the Power Spectral Estimate. The utility of this method is dependent on the robustness of it on different input situations. We extend the analysis in this paper, to include clearing up to three channels. We examine the relative positions of the spikes to each other and also the effect of taking different percentages of lags of the auto correlation in the Power Spectral Estimate. This method could have application wherever the Power Spectrum is used. An example of this is beam forming for source location, where a small target can be located next to a large target. Other possibilities extend into seismic data processing. As the method becomes more automated other applications may present themselves.

Ioup, George E.↗
NASA NTRS1992

Nonlinear robust controller design for multi-robot systems with unknown payloads

This work is concerned with the control problem of a multi-robot system handling a payload with unknown mass properties. Force constraints at the grasp points are considered. Robust control schemes are proposed that cope with the model uncertainty and achieve asymptotic path tracking. To deal with the force constraints, a strategy for optimally sharing the task is suggested. This strategy basically consists of two steps. The first detects the robots that need help and the second arranges that help. It is shown that the overall system is not only robust to uncertain payload parameters, but also satisfies the force constraints.

Song, Y. D.↗
NASA NTRS1990

Robust control of systems with real parameter uncertainty and unmodelled dynamics

Two significant contributions have been made during this research period in the research 'Robust Control of Systems with Real Parameter Uncertainty and Unmodelled Dynamics' under NASA Research Grant NAG-1-1102. They are: (1) a fast algorithm for computing the optimal H(sub infinity) norm for the four-block, the two block, or the one-block optimal H(sub infinity) optimization problem; and (2) a construction of an optimal H infinity controller without numerical difficulty. In using GD (Glover and Doyle) or DGKF (Doyle, Glover, Khargonekar, and Francis) approach to solve the standard H infinity norm which required bisection search. In this research period, we developed a very fast iterative algorithm for this computation. Our algorithm was developed based on hyperbolic interpolations which is much faster than any existing algorithm. The lower bound of the parameter, gamma, in the H infinity Riccati equation for solution existence is shown to be the square root of the supremum over all frequencies of the maximum eigenvalue of a given transfer matrix which can be computed easily. The lower band of gamma such that the H infinity Riccati equation has positive semidefinite solution can be also obtained by hyperbolic interpolation search. Another significant result in this research period is the elimination of the numerical difficulties arising in the construction of an optimal H infinity controller by directly applying the Glover and Doyle's state-space formulas. With the fast iterative algorithm for the computation of the optimal H infinity norm and the reliable construction of an optimal H infinity controller, we are ready to apply these tools in the design of robust controllers for the systems with unmodelled uncertainties. These tools will be also very useful when we consider systems with structured uncertainties.

Chang, Bor-Chin↗
NASA NTRS1993

The use of designed experiments in the process development of continuous propellant mixing

A continuous mix pilot plant was constructed at Aerojet Propulsion Division in Sacramento, California to develop a robust propellant mixing process for the full scale plant that was to be built at the NASA Advanced Solid Rocket Motor facility Yellow Creek, Mississippi. The plant was used to conduct dozens of subsystem and full system mixing tests for evaluation of equipment, processing methods, and control schemes for later use at the production plant. As a culmination to this work, a series of designed experiments were conducted using an eight run Taguchi analysis with four factors at two levels each to determine the primary effect of processing parameters on propellant ballistic and mechanical properties. The factors examined in these runs included the propellant production rate (454 (1000) and 622 kg/hr (1371 Ib/hr)), the product temperature out of the mixer (49 (120) and 63 deg C (145 deg F)), mixer screw speed (75 and 90 rpm), and the deaerator excess capacity (20 and 80 percent). Measured response variables included the uncured and cured density, Crawford Bomb liquid strand burning rates, and selected mechanical properties. The experiment revealed that several of the response variables displayed significant changes from run-to-run with the product temperature being the single most important factor. After concluding this experiment, a twenty-six hour confirmation run was conducted to verify the conclusions reached in the designed experiment. The extended run produced over 12,250 kgs (27,000 lbs) of propellant meeting all of the pre-run targeted properties including density (1.803 g/cc (0.065 lb/in(exp 3)) with a 0.12 percent coefficient of variation (CV) at 25 deg C (77 deg F)), liquid strand burn rate (0.889 cm/s (0.350 in/s) with a 0.69 percent CV at 4210 KPa (610 psig), 15.6 deg C (60 deg F)), nominal maximum stress (828 KPa (120 psig) with a 2.84 percent CV, S&E at 25 deg C (77 deg F), 5.08 cm/min (2 in/min)), strain at nominal maximum (47.4 percent with a 3.96 percent CV), and initial tangent modulus (5349 KPa (775 psig) with a 7.26 percent CV).

Campbell, J. A.↗
NASA NTRS2016

The Soil Moisture Acttive Passive Mission: Fault Protection Performance and Lessons Learned

Fault protection as a discipline involves a collection of flight software logic and operational processes for detecting unacceptable anomalous behavior, responding prior to reaching criticality, restricting the propagation of a failure beyond a fault containment region, and recovering the vehicle back to full or degraded functionality if possible. The System Fault Protection (SFP) design for the SMAP Earth orbiter was put to the test during its 90-day vehicle commissioning activities. During this time, the SFP software autonomously protected the vehicle from multiple faults to critical hardware, and the operations team successfully returned the observatory to its science state. The SFP also performed well in the presence of anomalous behavior below true safety limits by not taking unnecessary response actions, instead allowing the operations team time to monitor the behavior. Certain aspects of the SFP design were modified during operations via both parameter updates and a full flight software update in order to better match the vehicle behavior in the flight environment. An evaluation of the SMAP SFP performance during vehicle Commissioning will be provided in this paper, as well as a set of lessons learned largely focused on visibility, SFP mutability in operations, responses to peripheral device faults, and Safe Mode recovery and design. By capturing some of the knowledge gained during SMAP Commissioning, it is intended that this paper provide guidance for making future System Fault Protection designs more robust and supportive of operations.

Clark, Jessica↗
NASA NTRS2013

Characterizing Wheel-Soil Interaction Loads Using Meshfree Finite Element Methods: A Sensitivity Analysis for Design Trade Studies

A wheel experiencing sinkage and slippage events poses a high risk to planetary rover missions as evidenced by the mobility challenges endured by the Mars Exploration Rover (MER) project. Current wheel design practice utilizes loads derived from a series of events in the life cycle of the rover which do not include (1) failure metrics related to wheel sinkage and slippage and (2) performance trade-offs based on grouser placement/orientation. Wheel designs are rigorously tested experimentally through a variety of drive scenarios and simulated soil environments; however, a robust simulation capability is still in development due to myriad of complex interaction phenomena that contribute to wheel sinkage and slippage conditions such as soil composition, large deformation soil behavior, wheel geometry, nonlinear contact forces, terrain irregularity, etc. For the purposes of modeling wheel sinkage and slippage at an engineering scale, meshfree nite element approaches enable simulations that capture su cient detail of wheel-soil interaction while remaining computationally feasible. This study implements the JPL wheel-soil benchmark problem in the commercial code environment utilizing the large deformation modeling capability of Smooth Particle Hydrodynamics (SPH) meshfree methods. The nominal, benchmark wheel-soil interaction model that produces numerically stable and physically realistic results is presented and simulations are shown for both wheel traverse and wheel sinkage cases. A sensitivity analysis developing the capability and framework for future ight applications is conducted to illustrate the importance of perturbations to critical material properties and parameters. Implementation of the proposed soil-wheel interaction simulation capability and associated sensitivity framework has the potential to reduce experimentation cost and improve the early stage wheel design proce

terramechanics↗
NASA NTRS1986

System identification for modeling for control of flexible structures

The major components of a design and operational flight strategy for flexible structure control systems are presented. In this strategy an initial distributed parameter control design is developed and implemented from available ground test data and on-orbit identification using sophisticated modeling and synthesis techniques. The reliability of this high performance controller is directly linked to the accuracy of the parameters on which the design is based. Because uncertainties inevitably grow without system monitoring, maintaining the control system requires an active on-line system identification function to supply parameter updates and covariance information. Control laws can then be modified to improve performance when the error envelopes are decreased. In terms of system safety and stability the covariance information is of equal importance as the parameter values themselves. If the on-line system ID function detects an increase in parameter error covariances, then corresponding adjustments must be made in the control laws to increase robustness. If the error covariances exceed some threshold, an autonomous calibration sequence could be initiated to restore the error enveloped to an acceptable level.

Mettler, Edward↗
NASA NTRSDate not supplied

Application of Regolith Polymer Composite Fused Granular Fabrication Construction in Simulated Lunar Conditions

NASA’s Artemis program has the goal of creating a sustained lunar presence to provide unprecedented opportunities for scientific discovery and to ensure industry’s access to the unlimited resources and commercial potential in space. To achieve this goal, NASA must incrementally develop and expand its capabilities beyond the short lunar stays of the Apollo program to a robust continued presence with infrastructure and equipment to reduce mission risk. Kennedy Space Center’s Granular Mechanics and Regolith Operations laboratory (a.k.a. Swamp Works) has partnered with SpaceFactory and LERA Consulting Structural Engineers to develop the architectural and structural design of a robotically constructable unpressurized shelter. The shelter, called Lunar Infrastructure Asset (LINA), is designed to protect astronauts and surface assets from radiation, meteoroid impact, thermal gradients, and to withstand moonquakes. A Fused Granular Fabrication (FGF) construction process using regolith polymer composites was developed. The construction system and associated print parameters are discussed along with the environmental simulation equipment and a summary of test conditions. Test samples were printed in dirty thermal vacuum conditions (~10-3 torr, ~-200 °C,) and subscale versions of LINA were printed on a regolith simulant substrate in vacuum (~10-4 torr). Full scale LINA design optimization, simulation, and construction concept of operations are discussed.

lunar infrastructure↗
NASA NTRSDate not supplied

Selection, Production and Properties of Regolith Polymer Composite for Lunar Construction

NASA’s Artemis program has the goal of creating a sustained lunar presence to provide unprecedented opportunities for scientific discovery and to ensure industry’s access to the unlimited resources and commercial potential in space. To achieve this goal, NASA must incrementally develop and expand its capabilities beyond the short lunar stays of the Apollo program to a robust continued presence with infrastructure and equipment to reduce mission risk. Kennedy Space Center’s Granular Mechanics and Regolith Operations laboratory (a.k.a. Swamp Works) has partnered with SpaceFactory and LERA Consulting Structural Engineers to develop the architectural and structural design of a robotically constructable unpressurized shelter. The shelter, called Lunar Infrastructure Asset (LINA), is designed to protect astronauts and surface assets from radiation, meteoroid impact, thermal gradients, and to withstand moonquakes. A Fused Granular Fabrication (FGF) construction process using regolith polymer composites was developed. The construction system and associated print parameters are discussed along with the environmental simulation equipment and a summary of test conditions. Test samples were printed in dirty thermal vacuum conditions (~10-3 torr, ~-200 °C,) and subscale versions of LINA were printed on a regolith simulant substrate in vacuum (~10-4 torr). Full scale LINA design optimization, simulation, and construction concept of operations are discussed.

lunar infrastructure↗
NASA NTRS1983

A robust Feasible Directions algorithm for design synthesis

A nonlinear optimization algorithm is developed which combines the best features of the Method of Feasible Directions and the Generalized Reduced Gradient Method. This algorithm utilizes the direction-finding sub-problem from the Method of Feasible Directions to find a search direction which is equivalent to that of the Generalized Reduced Gradient Method, but does not require the addition of a large number of slack variables associated with inequality constraints. This method provides a core-efficient algorithm for the solution of optimization problems with a large number of inequality constraints. Further optimization efficiency is derived by introducing the concept of infrequent gradient calculations. In addition, it is found that the sensitivity of the optimum design to changes in the problem parameters can be obtained using this method without the need for second derivatives or Lagrange multipliers. A numerical example is given in order to demonstrate the efficiency of the algorithm and the sensitivity analysis.

Vanderplaats, G. N.↗