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At least 1,081 records · Page 60

Spectrum Preprocessing in the OPAD System

To determine the readiness of a rocket engine, and facilitate decisions on continued use of the engine before servicing is required, high-resolution optical spectrometers are used to acquire spectra from the exhaust plume. Such instruments are in place at the Technology Test Bed (TTB) stand at Marshall Space Flight Center (MSFC) and the A1 stand at Stennis Space Center (SSC). The optical spectrometers in place have a wide wavelength range covering the visible and near-infrared regions, taking approximately 8000 measurements at about one Angstrom spacing every half second. In the early stages of this work, data analysis was done manually. A simple spectral model produced a theoretical spectrum for given amount of elements and an operator visually matched the theoretical and real spectra. Currently, extensive software is being developed to receive data from the spectrometer and automatically generate an estimate of element amounts in the plume. It will result in fast and reliable analysis, with the capability of real-time performance. This software is the result of efforts of several groups but mainly it has been developed and used by scientists and combustion engineers, in their effort of understanding the underlying physical processes and phenomena and creating visualization and report generation facilities. Most of the software has been developed using the IDL language and programming environment which allows for extensive data visualization. Although this environment has been very beneficial, the resulting programs execute very slowly and are not easily portable to more popular, real-time environments. The need for portability and high speed of execution is becoming more apparent as the software matures moving out of the experimentation stage and into the production stage where ease of use and short response time are the most desirable features. The purpose of the work described here is to assist the scientists who developed the original IDL-based version in the conversion of the software into the real-time, production version. Specifically, a section of the software devoted to the preprocessing of the spectra has been converted into the C language. In addition, parts of this software which may be improved have been identified, and recommendations are given to improve the functionality and ease of use of the new version.

Katsinis, Constantine↗

Design of an Ada expert system shell for the VHSIC avionic modular flight processor

The Embedded Computer System Expert System Shell (ES Shell) is an Ada-based expert system shell developed at the Avionics Laboratory for use on the VHSIC Avionic Modular Processor (VAMP) running under the Ada Avionics Real-Time Software (AARTS) Operating System. The ES Shell provides the interface between the expert system and the avionics environment, and controls execution of the expert system. Testing of the ES Shell in the Avionics Laboratory's Integrated Test Bed (ITB) has demonstrated its ability to control a non-deterministic software application executing on the VAMP's which can control the ITB's real-time closed-loop aircraft simulation. The results of these tests and the conclusions reached in the design and development of the ES Shell have played an important role in the formulation of the requirements for a production-quality expert system inference engine, an ingredient necessary for the successful use of expert systems on the VAMP embedded avionic flight processor.

Fanning, F. Jesse↗

Model compilation for real-time planning and diagnosis with feedback

This paper describes MEXEC, an implemented micro executive that compiles a device model that can have feedback into a structure for subsequent evaluation. This system computes both the most likely current device mode from n sets of sensor measurements and the n-1 step reconfiguration plan that is most likely to result in reaching a target mode - if such a plan exists. A user tunes the system by increasing n to improve system capability at the cost of real-time performance.

diagnosis↗

Model compilation for real-time planning and diagnosis with feedback

This paper describes MEXEC, an implemented micro executive that compiles a device model that can have feedback into a structure for subsequent evaluation. This system computes both the most likely current device mode from n sets of sensor measurements and the n-1 step reconfiguration plan that is most likely to result in reaching a target mode - if such a plan exists. A user tunes the system by increasing n to improve system capability at the cost of real-time performance.

Barrett, Anthony↗

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗

The Value of a Spaceflight Clinical Decision Support System for Earth-Independent Medical Operations

As NASA prepares for crewed lunar missions over the next several years, plans are also underway to journey farther into deep space. Deep space exploration will require a paradigm shift in astronaut medical support toward progressively earth-independent medical operations (EIMO). The Exploration Medical Capability (ExMC) element of NASA’s Human Research Program (HRP) is investigating the feasibility and value of advanced capabilities to promote and enhance EIMO. Currently, astronauts rely on real-time communication with ground-based medical providers. However, as the distance from Earth increases, so do communication delays and disruptions. Moreover, resupply and evacuation will become increasingly complex, if not impossible, on deep space missions. In contrast to today’s missions in low earth orbit (LEO), where most medical expertise and decision-making are ground-based, an exploration crew will need to autonomously detect, diagnose, treat, and prevent medical events. Due to the sheer amount of pre-mission training required to execute a human spaceflight mission, there is often little time to devote exclusively to medical training. One potential solution is to augment the long duration exploration crew’s knowledge, skills, and abilities with a clinical decision support system (CDSS). An analysis of preliminary data indicates the potential benefits of a CDSS to mission outcomes when augmenting cognitive and procedural performance of an autonomous crew performing medical operations, and we provide an illustrative scenario of how such a CDSS might function.

Brian K. Russell↗

Integrated Planning for Telepresence with Time Delays

Teleoperation of remote robotic systems over time delays in the range of 2-10 seconds poses a unique set of challenges. In the context of a supervisory control system for the JSC Robonaut humanoid robot, we have developed an 'intelligent assistant' that integrates an Artificial Intelligence planner (JSHOP2) with execution monitoring of the state of both the human supervisor and the remote robot. The assistant reasons simultaneously about the world state on both sides of the time delay, which represents a novel application of this technology. The purpose of the assistant is to provide advice to the human supervisor about current and future activities, derived from a sequence of high-level goals to be achieved. To do this, the assistant must simultaneously monitor and react to various data sources, including actions taken by the supervisor who is issuing commands to the robot (e.g. with a data glove), actions taken by the robot, and the environment of the robot, both as currently perceived over the time delay, along with the current sequence of goals. We have developed a 'leader/follower' software architecture to handle the dual time-shifted streams of execution feedback. In this paper we describe the integrated planner and its executive, and how it operates in normal and anomaly situations.

remote robotic systems↗

Effects of computing time delay on real-time control systems

The reliability of a real-time digital control system depends not only on the reliability of the hardware and software used, but also on the speed in executing control algorithms. The latter is due to the negative effects of computing time delay on control system performance. For a given sampling interval, the effects of computing time delay are classified into the delay problem and the loss problem. Analysis of these two problems is presented as a means of evaluating real-time control systems. As an example, both the self-tuning predicted (STP) control and Proportional-Integral-Derivative (PID) control are applied to the problem of tracking robot trajectories, and their respective effects of computing time delay on control performance are comparatively evaluated. For this example, the STP (PID) controller is shown to outperform the PID (STP) controller in coping with the delay (loss) problem.

Shin, Kang G.↗

Strategic styles of hardware product development could accelerate commercialization in cleantech startups

Hardware-based startups risk having longer times-to-market, deterring investment in the clean technologies that are critical to a sustainable future. We interviewed 55 leaders at hardware startups, 20 of which are cleantech, mapped their development timelines, and found prototyping to be the longest development step (median of 19 weeks per prototype) regardless of prototype complexity or iteration. Qualitative interview analysis reveals the prototyping team’s choice of development style is a major factor affecting timeline. We define two development styles: natural and structured, typified by free-form exploration and rule-based execution, respectively. On average, natural development takes 35% less time than structured, and is thus preferred for early iterations, but adopting structure at strategic points is needed for timely commercialization. Critical points of transition to a structured style include adding new team members or engaging external partners, which demand clear communication and expectations. When pivoting to a new product or market, returning to a natural style is beneficial.

Looney, Erin (ORCID:0000000168959312)↗

Common spaceborne multicomputer operating system and development environment

A preliminary technical specification for a multicomputer operating system is developed. The operating system is targeted for spaceborne flight missions and provides a broad range of real-time functionality, dynamic remote code-patching capability, and system fault tolerance and long-term survivability features. Dataflow concepts are used for representing application algorithms. Functional features are included to ensure real-time predictability for a class of algorithms which require data-driven execution on an iterative steady state basis. The development environment supports the development of algorithm code, design of control parameters, performance analysis, simulation of real-time dataflow applications, and compiling and downloading of the resulting application.

Craymer, L. G.↗

Spacecraft-Initiated Scheduling of Commercial Communications Services

We propose a software framework enabling a spacecraft in Earth orbit to schedule its own access to space communications services via ground stations and relay satellites. All operations are automated, without a human in the loop, allowing for highly responsive service to meet time-varying needs. We describe a modular software architecture allowing the framework to interface with the scheduling systems of several providers - both government and commercial. Specifically, we present the results of an experiment with Amazon Web Services (AWS) Ground Station, an operational commercial service provider. Proposed software executed scheduling of a ground station antenna with minimal lead time (less than 20 minutes before the start of a pass). During the contact AWS cloud infrastructure was used to demodulate, process, and distribute data products from an orbiting satellite. We believe this work demonstrates the framework's ability to interface with additional providers and potential to integrate more complex decision-making in the future to schedule optimal contacts.

Scheduling↗

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗

Time management situation assessment (TMSA)

TMSA is a concept prototype developed to support NASA Test Directors (NTDs) in schedule execution monitoring during the later stages of a Shuttle countdown. The program detects qualitative and quantitative constraint violations in near real-time. The next version will support incremental rescheduling and reason over a substantially larger number of scheduled events.

Richardson, Michael B.↗

SchedInspector: A Batch Job Scheduling Inspector Using Reinforcement Learning

Improving the performance of job executions is an important goal of HPC batch job schedulers, such as minimizing job waiting time, slowdown, or completion time. Such a goal is often accomplished using carefully designed heuristics based on job features, such as job size and job duration. However, these heuristics overlook important runtime factors (e.g., cluster availability and waiting job patterns), which may vary across time and make a previously sound scheduling decision not hold any longer. In this study, we propose a new approach to incorporate runtime factors into batch job scheduling for better job execution performance. The key idea is to add a scheduling inspector on top of the base job scheduler to scrutinize its scheduling decisions. The inspector will take the runtime factors into consideration and accordingly determine the fitness of the scheduled job. It then either accepts the scheduled job or rejects it and asks the base schedulers to try again later. We realize such an inspector, namely SchedInspector, by leveraging the intelligence of reinforcement learning. Through extensive experiments, we show SchedInspector can intelligently integrate the runtime factors into various batch job scheduling policies, including the state-of-the-art one, to gain better job execution performance, such as smaller average bounded job slowdown (up to 69% better) or average job waiting time (up to 52% better), across various real-world workloads. We also show that although rejecting scheduling decisions may leave the resources idle hence affect the system utilization, SchedInspector is able to achieve the job execution performance improvement with marginal impact on the system utilization (typically less than 1%). We consider one key advantage of SchedInspector is it automatically learns to work with and improve existing job scheduling policies without changing them, which makes it promising to serve as a generic enhancer for various batch job scheduling policies.

Zhang, Di↗

Object-based task-level control: A hierarchical control architecture for remote operation of space robots

Expanding man's presence in space requires capable, dexterous robots capable of being controlled from the Earth. Traditional 'hand-in-glove' control paradigms require the human operator to directly control virtually every aspect of the robot's operation. While the human provides excellent judgment and perception, human interaction is limited by low bandwidth, delayed communications. These delays make 'hand-in-glove' operation from Earth impractical. In order to alleviate many of the problems inherent to remote operation, Stanford University's Aerospace Robotics Laboratory (ARL) has developed the Object-Based Task-Level Control architecture. Object-Based Task-Level Control (OBTLC) removes the burden of teleoperation from the human operator and enables execution of tasks not possible with current techniques. OBTLC is a hierarchical approach to control where the human operator is able to specify high-level, object-related tasks through an intuitive graphical user interface. Infrequent task-level command replace constant joystick operations, eliminating communications bandwidth and time delay problems. The details of robot control and task execution are handled entirely by the robot and computer control system. The ARL has implemented the OBTLC architecture on a set of Free-Flying Space Robots. The capability of the OBTLC architecture has been demonstrated by controlling the ARL Free-Flying Space Robots from NASA Ames Research Center.

Stevens, H. D.↗

GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]

The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence. The microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. During the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result. To be able to perform such testing multiple tools had to be developed included in this repository including: - Real time model of microgrid (Urban-Banshee, Remote-smaller model) - Test sequence configuration tools - Test execution real-time scripts - Post processing scripts - Human Machine Interface software

Koralewicz, Przemyslaw↗

A flow-through gamma detection system for sub-surface radioxenon tracer measurements in LYNM PE1

A continuous flow-through, real-time radioxenon sensor array has been designed to monitor either 127 Xe or 133 Xe tracer gas as part of a series of underground chemical explosions in the Low-Yield Nuclear Monitoring (LYNM) Physics Experiment 1 (PE1). The sensors are pairs of shielded thallium-doped sodium iodide gamma-ray detectors that surround a gas measurement chamber. Each measurement chamber is connected to a sampling location in the geology surrounding the chemical explosion or in the access tunnel. The first experiment in the series, PE1 A, occurred in 2023 and the system quantified the 127 Xe tracer gas in the gas sampling lines for four weeks following the experiment execution. The array generated a set of radioxenon concentration time series with a 15-minute resolution that will be used to refine subsurface gas transport models.

Gamma-ray coincidence detection↗

The LISE package: solvers for static and time-dependent superfluid local density approximation equations in three dimensions

Nuclear implementation of the density functional theory (DFT) is at present the only microscopic framework applicable to the whole nuclear landscape. The extension of DFT to superfluid systems in the spirit of the Kohn-Sham approach, the superfluid local density approximation (SLDA) and its extension to time-dependent situations, time-dependent superfluid local density ap- proximation (TDSLDA), have been extensively used to describe various static and dynamical problems in nuclear physics, neutron star crust, and cold atom systems. In this paper, we present the codes that solve the static and time-dependent SLDA equations in three-dimensional coordinate space without any symmetry restriction. These codes are fully parallelized with the message passing interface (MPI) library and take advantage of graphic processing units (GPU) for accelerating execution. The dynamic codes have checkpoint/restart capabilities and for initial conditions one can use any generalized Slater determinant type of wave function. The code can describe a large number of physical problems: nuclear fission, collisions of heavy ions, the interaction of quantized vor- tices with nuclei in the nuclear star crust, excitation of superfluid fermion systems by time dependent external fields, quantum shock waves, domain wall generation and propagation, the dynamics of the Anderson-Bogoliubov-Higgs mode, dynamics of fragmented condensates, vortex rings dynamics, generation and dynamics of quantized vortices, their crossing and recombinations and the incipient phases of quantum turbulence.

Jin, Shi↗