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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Micromechanics Analysis Code (MAC). User Guide: Version 2.0

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code's (MAC) who's predictive capability rests entirely upon the fully analytical generalized method of cells (GMC), micromechanics model is described. MAC is a versatile form of research software that 'drives' the double or triply periodic micromechanics constitutive models based upon GMC. MAC enhances the basic capabilities of GMC by providing a modular framework wherein (1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, (2) different integration algorithms may be selected, (3) a variety of constituent constitutive models may be utilized and/or implemented, and (4) a variety of fiber and laminate architectures may be easily accessed through their corresponding representative volume elements.

Wilt, T. E.↗
NASA NTRS1999

Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC): User Guide

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code, MAC, who's predictive capability rests entirely upon the fully analytical generalized method of cells, GMC, micromechanics model is described. MAC/ GMC is a versatile form of research software that "drives" the double or triply periodic micromechanics constitutive models based upon GMC. MAC/GMC enhances the basic capabilities of GMC by providing a modular framework wherein 1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, 2) different integration algorithms may be selected, 3) a variety of material constitutive models (both deformation and life) may be utilized and/or implemented, and 4) a variety of fiber architectures (both unidirectional, laminate and woven) may be easily accessed through their corresponding representative volume elements contained within the supplied library of RVEs or input directly by the user, and 5) graphical post processing of the macro and/or micro field quantities is made available.

Arnold, S. M.↗
NASA NTRS2003

Development of Algorithms for Control of Humidity in Plant Growth Chambers

Algorithms were developed to control humidity in plant growth chambers used for research on bioregenerative life support at Kennedy Space Center. The algorithms used the computed water vapor pressure (based on measured air temperature and relative humidity) as the process variable, with time-proportioned outputs to operate the humidifier and de-humidifier. Algorithms were based upon proportional-integral-differential (PID) and Fuzzy Logic schemes and were implemented using I/O Control software (OPTO-22) to define and download the control logic to an autonomous programmable logic controller (PLC, ultimate ethernet brain and assorted input-output modules, OPTO-22), which performed the monitoring and control logic processing, as well the physical control of the devices that effected the targeted environment in the chamber. During limited testing, the PLC's successfully implemented the intended control schemes and attained a control resolution for humidity of less than 1%. The algorithms have potential to be used not only with autonomous PLC's but could also be implemented within network-based supervisory control programs. This report documents unique control features that were implemented within the OPTO-22 framework and makes recommendations regarding future uses of the hardware and software for biological research by NASA.

Costello, Thomas A.↗
NASA NTRS2002

Observer-Based Magnetic Bearing Controller Developed for Aerospace Flywheels

A prototype of a versatile, observer-based magnetic bearing controller for aerospace flywheels was successfully developed and demonstrated on a magnetic bearing test rig (see the photograph) and an actual flywheel module. The objective of this development included a fast, yet low risk, control development process, and a robust, high-performance controller for a large variety of flywheels. This required a good system model, an efficient development procedure, and a model-based controller that addressed the key problems associated with flywheel and bearing imbalance, sensor error, and vibration. The model used in this control development and tuning procedure included the flexible rotor dynamics and motor-induced vibrations. Such a model was essential for low-risk scheduling of speed-dependent control parameters and for reliable evaluation of novel control strategies. The successfully tested control prototype utilized an extended Kalman filter to estimate the true rotor principal-axis motion from the raw sensor position feedback. For control refinement, the extended Kalman filter also estimated and eliminated the combined effects of mass-imbalance and sensor runouts from the input data. A key advantage of the design based on the extended Kalman filter is its ability to accurately estimate both the rotor's principal-axis position and gyroscopic rates with the least amount of phase lag. This is important for control parameter scheduling to dampen the gyroscopic motions. Because of large uncertainties in the magnetic bearing and imbalance characteristics, this state-estimation scheme alone is insufficient for containing the rotor motion within the desired 1-mil excursion radius. A nonlinear gain adjustment based on an estimation of the principal-axis orbit size was needed to provide a coarse (nonoptimal), but robust, control of the orbit growth. Control current minimization was achieved with a (steepest gradient) search of synchronous errors in the principal-axis position input data. Actual flywheel tests of this observer-based controller (developed entirely in-house) at the NASA Glenn Research Center showed that the model correctly predicted the rotor orbit growth as a function of rotational speed, and it demonstrated the capability of gain adjustments to arrest this growth. Data from these tests on an actual flywheel module spun to 26,000 rpm proved that the controller was able to contain the shaft motion to within much less than 0.5 mils of radial excursion with axis currents less than 300 mA in root-mean-square estimate. The test speed range was limited because of thermal expansion concerns for this particular flywheel unit, not because of any deficiency in the controller. Simulations for this unit indicated that the controller should be robust up to its top operating speed of 60,000 rpm. Aside from these important achievements, and most significantly, it took less than 1 week to adapt this controller from the simple test rig to the actual flywheel and to demonstrate full five-axis levitation and control. This demonstration showed that both the controller and the model-based development and tuning framework are easily adaptable to a wide range of rotors and bearing configurations and, hence, are capable of reducing design risks and costs for many future flywheel technology developments.

Le, Dzu K.↗
NASA NTRS2010

Joint SatOPS Compatibility Efforts

This slide presentation reviews NASA Goddard Space Flight Center's (GSFC) participation in the interagency cooperation committee, the Joint SatOps Compatibility Committee (JSCC), and the compatible Sat 2 efforts. Part of GSFC's participation in the JSCC is to work with the Goddard Mission Systems Evolution Center (GMSEC) to provides a publish/subscribe framework to enable rapid integration of commercially available satellite control products.

Smith, Danford↗
NASA NTRS2016

A Multi-Center Space Data System Prototype Based on CCSDS Standards

Deep space missions beyond earth orbit will require new methods of data communications in order to compensate for increasing Radio Frequency (RF) propagation delay. The Consultative Committee for Space Data Systems (CCSDS) standard protocols Spacecraft Monitor & Control (SM&C), Asynchronous Message Service (AMS), and Delay/Disruption Tolerant Networking (DTN) provide such a method. However, the maturity level of this protocol stack is insufficient for mission inclusion at this time. This Space Data System prototype is intended to provide experience which will raise the Technical Readiness Level (TRL) of this protocol set. In order to reduce costs, future missions can take advantage of these standard protocols, which will result in increased interoperability between control centers. This prototype demonstrates these capabilities by implementing a realistic space data system in which telemetry is published to control center applications at the Jet Propulsion Lab (JPL), the Marshall Space Flight Center (MSFC), and the Johnson Space Center (JSC). Reverse publishing paths for commanding from each control center are also implemented. The target vehicle consists of realistic flight computer hardware running Core Flight Software (CFS) in the integrated Power, Avionics, and Power (iPAS) Pathfinder Lab at JSC. This prototype demonstrates a potential upgrade path for future Deep Space Network (DSN) modification, in which the automatic error recovery and communication gap compensation capabilities of DTN would be exploited. In addition, SM&C provides architectural flexibility by allowing new service providers and consumers to be added efficiently anywhere in the network using the common interface provided by SM&C's Message Abstraction Layer (MAL). In FY 2015, this space data system was enhanced by adding telerobotic operations capability provided by the Robot API Delegate (RAPID) family of protocols developed at NASA. RAPID is one of several candidates for consideration and inclusion in a new international standard being developed by the CCSDS Telerobotic Operations Working Group. Software gateways for the purpose of interfacing RAPID messages with the existing SM&C based infrastructure were developed. Telerobotic monitor, control, and bridge applications were written in the RAPID framework, which were then tailored to the NAO telerobotic test article hardware, a product of Aldebaran Robotics.

Rich, Thomas M.↗
NASA NTRSDate not supplied

A Survey of Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗
NASA NTRSDate not supplied

Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Urban Air Mobility↗
NASA NTRSDate not supplied

Cyber Threats & Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗
NASA NTRS2021

Improving the Representation of Subtropical Boundary Layer Clouds in the NASA GEOS Model with the Eddy-Diffusivity/Mass-Flux Parameterization

A systematic underestimation of subtropical planetary boundary layer (PBL) stratocu-mulus clouds by the GEOS model has been significantly improved by a new Eddy-Diffusivity/Mass-Flux (EDMF) parameterization. The EDMF parameterization representsthe subgrid-scale transport in the dry and moist parts of the PBL in a unified mannerand it combines an adjusted eddy-diffusivity PBL scheme from GEOS with a stochasticmulti-plume mass-flux model. The new EDMF version of the GEOS model is first com-pared against the CONTROL version in a single-column model (SCM) framework for twobenchmark cases representing subtropical stratocumulus and shallow cumulus clouds, andvalidated against large eddy simulations. Global simulations are performed and comparedagainst observations and reanalysis data. The results show that the EDMF version of theGEOS model produces more realistic subtropical PBL clouds. Noteworthy, the EDMF im-provements first detected in the SCM framework translate into similar improvements of theglobal GEOS model.

Kay Suselj↗
NASA NTRSDate not supplied

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

Motivation - Noise management is one of the major barriers to Urban Air Mobility - Approaches to noise mitigation (non-exhaustive) - Vehicle configuration - Directivity control via propeller phase synchronization - Trajectory optimization Objective - Create framework for trajectory generation integrating location-based acoustic metrics and vehicle performance limitations - Multiple trajectory optimization methods and acoustic noise models - Mission-relevant constraints - Mission duration, airspace restrictions, ... - Vehicle dynamic constraints - Aircraft structural limitations, min/max airspeed, ... - Vehicle separation/obstacle avoidance - Acoustic constraints at a number of discrete observer locations

Kasey A. Ackerman↗
NASA NTRSDate not supplied

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

Motivation - Noise management is one of the major barriers to Urban Air Mobility - Approaches to noise mitigation (non-exhaustive) - Vehicle configuration - Directivity control via propeller phase synchronization - Trajectory optimization Objective - Create framework for trajectory generation integrating location-based acoustic metrics and vehicle performance limitations - Multiple trajectory optimization methods and acoustic noise models - Mission-relevant constraints - Mission duration, airspace restrictions, ... - Vehicle dynamic constraints - Aircraft structural limitations, min/max airspeed, ... - Vehicle separation/obstacle avoidance - Acoustic constraints at a number of discrete observer locations

Kasey A Ackerman↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗
DOE OSTI2022

Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods

We report home energy management systems (HEMS) have been shown to reduce energy bills and to provide grid services including peak demand reduction and demand flexibility. However, uncertainty in residential energy systems is a significant issue and can reduce the benefits of a HEMS to the homeowner or grid operator. Sources of uncertainty include weather forecasts, predictions of energy-related occupant activities (e.g., hot water draws), and parameter estimation for the building envelope and energy-consuming equipment. This paper tackles the problem of uncertainty by developing a framework that simulates HEMS in uncertain conditions and evaluates the performance of multiple control strategies. A linear, reduced-order residential building model for model predictive control applications is derived and compared to a full-order model. Stochastic model predictive control is shown to perform better than deterministic and heuristic methods when considering realistic forecasts with uncertainty. The framework can evaluate the performance of HEMS in real-world applications, which can help de-risk HEMS deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1987

Active stability augmentation of large space structures: A stochastic control problem

A problem in SCOLE is that of slewing an offset antenna on a long flexible beam-like truss attached to the space shuttle, with rather stringent pointing accuracy requirements. The relevant methodology aspects in robust feedback-control design for stability augmentation of the beam using on-board sensors is examined. It is framed as a stochastic control problem, boundary control of a distributed parameter system described by partial differential equations. While the framework is mathematical, the emphasis is still on an engineering solution. An abstract mathematical formulation is developed as a nonlinear wave equation in a Hilbert space. That the system is controllable is shown and a feedback control law that is robust in the sense that it does not require quantitative knowledge of system parameters is developed. The stochastic control problem that arises in instrumenting this law using appropriate sensors is treated. Using an engineering first approximation which is valid for small damping, formulas for optimal choice of the control gain are developed.

Balakrishnan, A. V.↗