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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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New, efficient solution minimizes run time. Approach based on approved theorem provides formal basis for assuring generality and rapid execution. Theorem does not directly address nuisance of square law growth. Analysis of algorithm shows it tends to avoid square-law growth, and rigorous testing verified algorithm tends to enjoy almost linear growth.
This paper describes the selection of a method for determining line-of-sight in real-time simulations for the NASA Ames Vertical Motion Simulator (VMS) facility. Five different combinations of terrain representation and line-of-sight determination algorithms were tested. A gridpost terrain format, in conjunction with a Digital Differential Analyzer algorithm, was found to best meet the simulation criteria of high speed, low storage requirements, and accuracy.
Three solution algorithms, explicit underrelaxation, point implicit, and lower upper symmetric Gauss-Seidel (LUSGS), are used to compute nonequilibrium flow around the Apollo 4 return capsule at 62 km altitude. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness. The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15, 23, and 30, the LUSGS method produces an eight order of magnitude drop in the L2 norm of the energy residual in 1/3 to 1/2 the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 23 and above. At Mach 40 the performance of the LUSGS algorithm deteriorates to the point it is out-performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.
Weakly-coupled Markov decision processes can be decomposed into subprocesses that interact only through a small set of bottleneck states. We study a hierarchical reinforcement learning algorithm designed to take advantage of this particular type of decomposability. To test our algorithm, we use a decision-making problem faced by autonomous planetary rovers. In this problem, a Mars rover must decide which activities to perform and when to traverse between science sites in order to make the best use of its limited resources. In our experiments, the hierarchical algorithm performs better than Q-learning in the early stages of learning, but unlike Q-learning it converges to a suboptimal policy. This suggests that it may be advantageous to use the hierarchical algorithm when training time is limited.
NASA Langley Research Center (LaRC) has developed a comprehensive test and analysis program to evaluate the ability of LS-DYNA to model the materials and the phenomena involved in soil and water landing impacts of the Orion crew module. Elemental, scale boilerplate, and full-scale prototype testing is being conducted in support of the simulation verification and validation approach. Aspects of the simulations evaluated against test data include soil constitutive properties, water equations of state, and contact algorithms. Subsystems tested include airbags, crushable energy absorbing honeycomb materials, and energy absorbing seat support struts. The procedures, instrumentation, and general observations from each test series are presented. Plans for a series of swing tests of a full-scale boilerplate into a purpose-built water basin are described. Further plans for swing tests of flight-like prototypes into the water basin are noted.
To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at NASA’s Marshall Space Flight Center have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. The probe also includes the ability to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL Finite Element Analysis and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller thatmitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.
To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at National Aeronautics and Space Administration’s (NASA’s) Marshall Space Flight Center (MSFC) have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. We have also used high temperature ovens to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL finite element analysis (FEA) and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller that mitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.
The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.
The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results
The paper is concerned with the task of estimating modal parameters from system response measurement in aircraft flutter testing. A frequency-domain derivation of an instrumental-variables algorithm is presented for a linear time-invariant dynamic system of order n. Basically, this algorithm fits a set of poles and zeros to the measured transfer function. An illustrative example is provided regarding the application of the algorithm to aeroelasticity testing. It is shown that the algorithm can be implemented for on-line data reduction with a microcomputer-based analysis system. By using instrumental variables the sensitivity of the modal parameter estimates to noise in the system-response measurements is reduced greatly. The algorithm is expected to be a powerful and valuable tool for on-line estimation of modal parameters in flutter testing and should be useful in control system and structural dynamics tests.
The development and testing of a real-time takeoff performance monitoring system is discussed. The algorithm is madeup of two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate schedule performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six degree of freedom airplane model in a computer simulation. Results from a series of sensitivity analysis are also included.
The development and testing of a real-time takeoff performance monitoring system is discussed. The algorithm is made up of two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate schedule performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six degree of freedom airplane model in a computer simulation. Results from a series of sensitivity analysis are also included.
Over the past two decades, the emergence of highly effective software testing frameworks has greatly simplified the development and use of unit tests and has led to new software development paradigms such as test driven development (TDD). However, technical computing introduces a number of unique testing challenges, including distributed parallelism and numerical accuracy. This webinar will begin with a basic introduction to the use of pFUnit (parallel Fortran Unit testing framework) to develop tests for Message Passing Interface (MPI) plus Fortran (MPI+Fortran) software and then present some of the new capabilities in the latest release. We will also discuss some specialized methodologies for testing numerical algorithms and speculate about future framework capabilities that may improve our ability to test at exascale.
This Technical Memorandum describes four contributions made by the authors to a larger team effort toward developing a distributed system for scheduling commercial flights at navigation fixes and/or airport runways. These contributions are as follows: (1) a proof of correctness for a scheduling algorithm published previously by Meyn, (2) an improvement of Meyn's algorithm from quadratic to linear time, (3) two independent implementations of the algorithm with test results identical to those published, and (4) an extension of Meyn's algorithm to support minimum usable time intervals.
A collection is presented of MHD problems that will provide researchers who have interests in modeling MHD phenomena with a battery of tests (a 'test suite') for calibrating their numerical algorithms. Use of these tests will provide a common reference for comparison of different numerical MHD algorithms. The test suite includes both 1D and 2D problems. Taken together, these problems test the abilities of a numerical method to propagate accurately all of the MHD wave families in moving and stationary media, to capture MHD shocks and contact discontinuities, and to model accurately Lorentz force terms in multiple dimensions. An example solution of each test problem is presented. Diagnostic convergence-testing procedures that provide a quantitative evaluation of MHD algorithms are demonstrated.
The catalytic performance of atomically dispersed catalysts (ADCs) is greatly influenced by their atomic configurations, such as atom–atom distances, clustering of atoms into dimers and trimers, and their distributions. Scanning transmission electron microscopy (STEM) is a powerful technique for imaging ADCs at the atomic scale; however, most STEM analyses of ADCs thus far have relied on human labeling, making it difficult to analyze large data sets. Here, we introduce a convolutional neural network (CNN)-based algorithm capable of quantifying the spatial arrangement of different adatom configurations. The algorithm was tested on different ADCs with varying support crystallinity and homogeneity. Results show that our algorithm can accurately identify atom positions and effectively analyze large data sets. Here, this work provides a robust method to overcome a major bottleneck in STEM analysis for ADC catalyst research. We highlight the potential of this method to serve as an on-the-fly analysis tool for catalysts in future in situ microscopy experiments.
The proliferation of smart meters has resulted in a large amount of data being generated. It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the privacy of the consumers. The sector is scrambling to define policies, such as the so called ‘15/15 rule’, to respond to the need. However, the current policies fail to adequately guarantee privacy. Here, in this paper, we address the problem of allowing third parties to apply K-means clustering, obtaining customer labels and centroids for a set of load time series by applying the framework of differential privacy. We leverage the method to design an algorithm that generates differentially private synthetic load data consistent with the labeled data. We test our algorithm’s utility by answering summary statistics such as average daily load profiles for a 2-dimensional synthetic dataset and a real-world power load dataset.
At present, actuation systems for the Thrust Vector Control (TVC) for launch vehicles are hydraulic systems. The Advanced Launch System (ALS), a joint initiative between NASA and the Air Force, is a launch vehicle that is designed to be cost effective, highly reliable and operationally efficient with a goal of reducing the cost per pound to orbit. As part of this initiative, an electromechanical actuation system is being developed as an attractive alternative to the hydraulic systems used today. NASA-Lewis is developing and demonstrating an Induction Motor Controller Actuation System with a 40 hp peak rating. The controller will integrate 20 kHz resonant link Power Management and Distribution (PMAD) technology and Pulse Population Modulation (PPM) techniques to implement Field Oriented Vector Control (FOVC) of a new advanced induction motor. Through PPM, multiphase variable frequency, variable voltage waveforms can be synthesized from the 20 kHz source. FOVC shows that varying both the voltage and frequency and their ratio (V/F), permits independent control of both torque and speed while operating at maximum efficiency at any point on the torque-speed curve. The driver and the FOVC will be microprocessor controlled. For increased system reliability, a Built-in Test (BITE) capability will be included. This involves introducing testability into the design of a system such that testing is calibrated and exercised during the design, manufacturing, maintenance and prelaunch activities. An actuator will be integrated with the motor controller for performance testing of the EMA TVC system. The design and fabrication of the motor controller is being done by General Dynamics Space Systems Division. The University of Wisconsin-Madison will assist in the design of the advanced induction motor and in the implementation of the FOVC theory. A 75 hp electronically controlled dynamometer will be used to test the motor controller in all four quadrants of operation using flight type control algorithms. Integrated testing of the controller and actuator will be conducted at a facility yet to be named. The EMA system described above is discussed in detail.