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At least 433 records · Page 24

Component-adaptive grid embedding

One of the major problems related to transonic flow prediction about realistic aircraft configuration is the generation of a suitable grid which encompasses such configurations. In general, each aircraft component (wing, fuselage, nacelle) requires a grid system that is usually incompatible with the grid systems of the other components; thus, the implementation of finite-difference methods for such geometrically-complex configurations is a difficult task. An approach was developed to treat such a problem. The basic idea is to generate different grid systems, each suited for a particular component. Thus, the flow field domain is divided into overlapping subdomains of different topology. These grid systems are then interfaced with each other in such a way that stability, convergence speed and accuracy are maintained.

Atta, E. H.↗

Integrated Planning and Execution for a Self-Reliant Mars Rover

Planetary rovers exploring the surface of Mars face a challenging operational environment that requires close cooperation between deliberative planning and behavioral execution in order to most efficiently leverage the robot’s capabilities into science value returned to earth. The Self-Reliant Rovers project envisions future rover missions that require only occasional high-level direction from human controllers to successfully conduct detailed in-situ studies of its Martian environs. To achieve this high degree of autonomy, this work leverages a spectrum of planning and execution techniques that allow the rover to respond appropriately to both opportunity and adversity it encounters. Small perturbations are accommodated at first by behavioral adaptation, with more and more extensive disruptions handled in turn by executive administration of plan flexibility, heuristic-guided plan repair strategies, and finally comprehensive replanning from science campaign goals. The integrated system has been deployed and tested on a terrestrial rover in an environment and under scenarios that anticipate those faced by future Mars rovers. This paper recounts complexities of planning and execution coordination faced in the rover domain and the practical solutions employed to address them. Particular emphasis is given to lessons from the field and foibles ripe for remedy by future advances in planning and execution research.

Gaines, Daniel↗

Analysis of nystagmus response to a pseudorandom velocity input

Space motion sickness was not reported during the first Apollo missions; however, since Apollo 8 through the current Shuttle and Skylab missions, approximately 50% of the crewmembers have experienced instances of space motion sickness. Space motion sickness, renamed space adaptation syndrome, occurs primarily during the initial period of a mission until habilation takes place. One of NASA's efforts to resolve the space adaptation syndrome is to model the individual's vestibular response for basis knowledge and as a possible predictor of an individual's susceptibility to the disorder. This report describes a method to analyse the vestibular system when subjected to a pseudorandom angular velocity input. A sum of sinusoids (pseudorandom) input lends itself to analysis by linear frequency methods. Resultant horizontal ocular movements were digitized, filtered and transformed into the frequency domain. Programs were developed and evaluated to obtain the (1) auto spectra of input stimulus and resultant ocular resonse, (2) cross spectra, (3) the estimated vestibular-ocular system transfer function gain and phase, and (4) coherence function between stimulus and response functions.

Lessard, C. S.↗

Adaptivity and smart algorithms for fluid-structure interaction

This paper reviews new approaches in CFD which have the potential for significantly increasing current capabilities of modeling complex flow phenomena and of treating difficult problems in fluid-structure interaction. These approaches are based on the notions of adaptive methods and smart algorithms, which use instantaneous measures of the quality and other features of the numerical flowfields as a basis for making changes in the structure of the computational grid and of algorithms designed to function on the grid. The application of these new techniques to several problem classes are addressed, including problems with moving boundaries, fluid-structure interaction in high-speed turbine flows, flow in domains with receding boundaries, and related problems.

Oden, J. Tinsley↗

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

software↗

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

python↗

System identification in the repetition domain

Procedures for system identification using realization theory in conjunction with learning control ideas are developed. The Markov parameters of the system are identified by combining data from repeated experiments. Three approaches are discussed for identification of as many Markov parameters as sample points in the experiment. Making use of all the parameters, realization theory is then employed to determine the system order and to obtain a minimal order representation. The first two approaches are non-recursive, which in the case of noise-free data yields a one step solution. The third approach uses a recursive formulation rendered from adaptive control but modified for successive experiments. A simple example shows the numerical convergence of the identified parameters as a function of the number of experiments. The procedure presented herein is an extension of the existing Eigensystem Realization Algorithm (ERA), which has been successfully applied for system identification of large structures.

Juang, Jer-Nan↗

The Mechanisms for the Onset and Explosive Eruption of Coronal Mass Ejections and Eruptive Flares

We have investigated the onset and acceleration of coronal mass ejections (CMEs) and eruptive flares. To isolate the eruption physics, our study uses the breakout model, which is insensitive to the energy buildup process leading to the eruption. We performed 2.5D simulations with adaptive mesh refinement that achieved the highest overall spatial resolution to date in a CME/eruptive flare simulation. The ultra-high resolution allows us to separate clearly the timing of the various phases of the eruption. Using new computational tools, we have determined the number and evolution of all X- and O-type nulls in the system, thereby tracking both the progress and the products of reconnection throughout the computational domain. Our results show definitively that CME onset is due to the start of fast reconnection at the breakout current sheet. Once this reconnection begins, eruption is inevitable; if this is the only reconnection in the system, however, the eruption will be slow. The explosive CME acceleration is triggered by fast reconnection at the flare current sheet. Our results indicate that the explosive eruption is caused by a resistive instability, not an ideal process. Moreover, both breakout and flare reconnections begin first as a form of weak tearing characterized by a slowly evolving plasmoids, but eventually transition to a fast form with well-defined Alfvenic reconnection jets and rapid flux transfer. This transition to fast reconnection is required for both CME onset and explosive acceleration. We discuss the key implications of our results for CME/flare observations and for theories of magnetic reconnection.

Karpen, Judith T.↗

Flexible Generation of Kalman Filter Code

Domain-specific program synthesis can automatically generate high quality code in complex domains from succinct specifications, but the range of programs which can be generated by a given synthesis system is typically narrow. Obtaining code which falls outside this narrow scope necessitates either 1) extension of the code generator, which is usually very expensive, or 2) manual modification of the generated code, which is often difficult and which must be redone whenever changes are made to the program specification. In this paper, we describe adaptations and extensions of the AUTOFILTER Kalman filter synthesis system which greatly extend the range of programs which can be generated. Users augment the input specification with a specification of code fragments and how those fragments should interleave with or replace parts of the synthesized filter. This allows users to generate a much wider range of programs without their needing to modify the synthesis system or edit generated code. We demonstrate the usefulness of the approach by applying it to the synthesis of a complex state estimator which combines code from several Kalman filters with user-specified code. The work described in this paper allows the complex design decisions necessary for real-world applications to be reflected in the synthesized code. When executed on simulated input data, the generated state estimator was found to produce comparable estimates to those produced by a handcoded estimator

Richardson, Julian↗

Compatibility of information and mode of control: The case for natural control systems

The operation of control systems has been determined largely by mechanical constraints. Compatibility with the characteristics of the operator is a secondary consideration, with the result that control may never be optimal, control workload may interfere with performance of secondary tasks, and learning may be more difficult and protracted than necessary. With the introduction of a computer in the control loop, the mode of operation can be adapted to the operator, rather than vice versa. The concept of natural control is introduced to describe a system that supports control of the information used by the operator in achieving an intended goal. As an example, control of speed during simulated approach to a pad by helicopter pilots is used to contrast path-speed control with direct control of global optical flow-pattern information. Differences are evidenced in the performance domains of control activity, speed, and global optical flow velocity.

Owen, Dean H.↗

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗

Integrated adaptive filtering and design for control experiments of flexible structures

A novel method is presented of identifying a state space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relations between the state space model and the finite difference model for linear stochastic systems derived through projection filters. It is proven that least squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model. In estimating the corresponding state estimator gain, a z-domain method is used. First the deterministic component of the output is subtracted out, and then the state estimator gain is obtained by whitening the remaining signal. Experimental example is used to illustrate the feasibility of the method.

Huang, Jen-Kuang↗

Design alternatives for process group membership and multicast

Process groups are a natural tool for distributed programming, and are increasingly important in distributed computing environments. However, there is little agreement on the most appropriate semantics for process group membership and group communication. These issues are of special importance in the Isis system, a toolkit for distributed programming. Isis supports several styles of process group, and a collection of group communication protocols spanning a range of atomicity and ordering properties. This flexibility makes Isis adaptable to a variety of applications, but is also a source of complexity that limits performance. This paper reports on a new architecture that arose from an effort to simplify Isis process group semantics. Our findings include a refined notion of how the clients of a group should be treated, what the properties of a multicast primitive should be when systems contain large numbers of overlapping groups, and a new construct called the casuality domain. As an illustration, we apply the architecture to the problem of converting processes into fault-tolerant process groups in a manner that is 'transparent' to other processes in the system.

Birman, Kenneth P.↗

Research in Parallel Algorithms and Software for Computational Aerosciences

Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Domel, Neal D.↗

Research in Parallel Algorithms and Software for Computational Aerosciences

Phase I is complete for the development of a Computational Fluid Dynamics parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Domel, Neal D.↗

High-Performance 3D Articulated Robot Display

In the domain of telerobotic operations, the primary challenge facing the operator is to understand the state of the robotic platform. One key aspect of understanding the state is to visualize the physical location and configuration of the platform. As there is a wide variety of mobile robots, the requirements for visualizing their configurations vary diversely across different platforms. There can also be diversity in the mechanical mobility, such as wheeled, tracked, or legged mobility over surfaces. Adaptable 3D articulated robot visualization software can accommodate a wide variety of robotic platforms and environments. The visualization has been used for surface, aerial, space, and water robotic vehicle visualization during field testing. It has been used to enable operations of wheeled and legged surface vehicles, and can be readily adapted to facilitate other mechanical mobility solutions. The 3D visualization can render an articulated 3D model of a robotic platform for any environment. Given the model, the software receives real-time telemetry from the avionics system onboard the vehicle and animates the robot visualization to reflect the telemetered physical state. This is used to track the position and attitude in real time to monitor the progress of the vehicle as it traverses its environment. It is also used to monitor the state of any or all articulated elements of the vehicle, such as arms, legs, or control surfaces. The visualization can also render other sorts of telemetered states visually, such as stress or strains that are measured by the avionics. Such data can be used to color or annotate the virtual vehicle to indicate nominal or off-nominal states during operation. The visualization is also able to render the simulated environment where the vehicle is operating. For surface and aerial vehicles, it can render the terrain under the vehicle as the avionics sends it location information (GPS, odometry, or star tracking), and locate the vehicle over or on the terrain correctly. For long traverses over terrain, the visualization can stream in terrain piecewise in order to maintain the current area of interest for the operator without incurring unreasonable resource constraints on the computing platform. The visualization software is designed to run on laptops that can operate in field-testing environments without Internet access, which is a frequently encountered situation when testing in remote locations that simulate planetary environments such as Mars and other planetary bodies.

Powell, Mark W.↗

MARIKA - A model revision system using qualitative analysis of simulations

This paper describes portions of a novel system called MARIKA (Model Analysis and Revision of Implicit Key Assumptions) to automatically revise a model of the normal human orientation system. The revision is based on analysis of discrepancies between experimental results and computer simulations. The discrepancies are calculated from qualitative analysis of quantitative simulations. The experimental and simulated time series are first discretized in time segments. Each segment is then approximated by linear combinations of simple shapes. The domain theory and knowledge are represented as a constraint network. Incompatibilities detected during constraint propagation within the network yield both parameter and structural model alterations. Interestingly, MARIKA diagnosed a data set from the Massachusetts Eye and Ear Infirmary Vestibular Laboratory as abnormal though the data was tagged as normal. Published results from other laboratories confirmed the finding. These encouraging results could lead to a useful clinical vestibular tool and to a scientific discovery system for space vestibular adaptation.

Groleau, Nicolas↗

Extrasolar planet detection

This paper discusses the concept of extrasolar planet detection using a large-aperture infared imaging telescope. Coronagraphic stellar apodization techniques are less efficient at infrared wavelengths compared to the visible, as a result of practical limitations on aperture dimensions, thus necessitating additional starlight suppression to make planet detection feasible in this spectral domain. We have been investigating the use of rotational shearing interferometry to provide up to three orders of magnitude of starlight suppression over broad spectral bandwidths. We present a theoretical analysis of the system performance requirements needed to make this a viable instrument for planet detection, including specifications on the interferometer design and telescope aperture characteristics. The concept of using rotational shearing interferometry as a wavefront error detector, thus providing a signal that can be used to adaptively correct the wavefront, will be discussed. We also present the status of laboratory studies of on-axis source suppression using a recently constructed rotational shearing interferometer that currently operates in the visible.

Korechoff, R. P.↗