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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 1,513 records · Page 84

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NASA NTRS2009

A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes

In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I

Martin, Rodney Alexander↗

NASA NTRS2017

LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints

This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.

optimal variance control↗

DOE OSTI2020

Subsurface Biogeochemical Research: Watershed System Science for Energy

The Subsurface Biogeochemical Research (SBR) program within the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research is strategically aligned with DOE’s mission to ensure U.S. security and prosperity through watershed system science. Water resources critical for energy production are under pressure from growing water demand, contamination, drought, flooding, and saltwater intrusion. Sustainable management of watershed systems and their coupling with the built environment rely on understanding the hydrological and biogeochemical processes that control watershed system dynamics and water availability and quality. Next-generation science-based models of watershed systems are needed to address many U.S. energy and environmental challenges, including contaminant cleanup, clean water availability, safe storage of energy and nuclear byproducts in the subsurface, nutrient availability for sustainable biofuel crops, and recovery of subsurface energy resources.

09 BIOMASS FUELS↗

NASA NTRS2002

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

Rabinowitz, Matthew↗

NASA NTRS1973

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

Frederick, D. K.↗

NASA NTRS1985

The effects of type of knowledge upon human problem solving in a process control task

The question of what the operator of a dynamic system needs to know was investigated in an experiment using PLANT, a simulation of a generic dynamic production process. Knowledge of PLANT was manipulated via different types of instruction, so that four different groups were created: (1) minimal instructions only; (2) minimal instructions and guidelines for operation (procedures); (3) minimal instructions and dynamic relationships (principles); and (4) minimal instructions, and procedures, and principles. Subjects controlled PLANT in a variety of situations which required maintaining production while also diagnosing familiar and unfamiliar failures. Despite the fact that these manipulations resulted in differences in subjects' Knowledge, as assessed via a written test at the end of the experiment, instructions had no effect upon achievement of the primary goal of production, or upon subjects' ability to diagnose unfamiliar failures. However, those groups receiving procedures controlled the system in a more stable manner. Possible reasons for the failure to find an effect of principles are presented, and the implications of these results for operator training and aiding are discussed.

Morris, N. M.↗

NASA NTRS1982

Effects of higher order control systems on aircraft approach and landing longitudinal handling qualities

An investigation of approach and landing longitudinal flying qualities, based on data generated using a variable stability NT-33 aircraft combined with significant control system dynamics is described. An optimum pilot lead time for pitch tracking, flight path angle tracking, and combined pitch and flight path angle tracking tasks is determined from a closed loop simulation using integral squared error (ISE) as a performance measure. Pilot gain and lead time were varied in the closed loop simulation of the pilot and aircraft to obtain the best performance for different control system configurations. The results lead to the selection of an optimum lead time using ISE as a performance criterion. Using this value of optimum lead time, a correlation is then found between pilot rating and performance with changes in the control system and in the aircraft dynamics. It is also shown that pilot rating is closely related to pilot workload which, in turn, is related to the amount of lead which the pilot must generate to obtain satisfactory response. The results also indicate that the pilot may use pitch angle tracking for the approach task and then add flight path angle tracking for the flare and touchdown.

Pasha, M. A.↗

NASA NTRS2014

3D Visualization of Cooperative Trajectories

Aerodynamicists and biologists have long recognized the benefits of formation flight. When birds or aircraft fly in the upwash region of the vortex generated by leaders in a formation, induced drag is reduced for the trail bird or aircraft, and efficiency improves. The major consequence of this is that fuel consumption can be greatly reduced. When two aircraft are separated by a large enough longitudinal distance, the aircraft are said to be flying in a cooperative trajectory. A simulation has been developed to model autonomous cooperative trajectories of aircraft; however it does not provide any 3D representation of the multi-body system dynamics. The topic of this research is the development of an accurate visualization of the multi-body system observable in a 3D environment. This visualization includes two aircraft (lead and trail), a landscape for a static reference, and simplified models of the vortex dynamics and trajectories at several locations between the aircraft.

aerodynamic drag↗

NASA NTRS1982

The dynamics and control of large flexible space structures-V

A general survey of the progress made in the areas of mathematical modelling of the system dynamics, structural analysis, development of control algorithms, and simulation of environmental disturbances is presented. The use of graph theory techniques is employed to examine the effects of inherent damping associated with LSST systems on the number and locations of the required control actuators. A mathematical model of the forces and moments induced on a flexible orbiting beam due to solar radiation pressure is developed and typical steady state open loop responses obtained for the case when rotations and vibrations are limited to occur within the orbit plane. A preliminary controls analysis based on a truncated (13 mode) finite element model of the 122m. Hoop/Column antenna indicates that a minimum of six appropriately placed actuators is required for controllability. An algorithm to evaluate the coefficients which describe coupling between the rigid rotational and flexible modes and also intramodal coupling was developed and numerical evaluation based on the finite element model of Hoop/Column system is currently in progress.

Bainum, P. M.↗

DOE OSTI2022

Smart Charging for Electric Ride-Hailing Vehicles using Renewables: A San Francisco Case Study

Charging large fleets of electric ride-hailing vehicles (ERVs) is a complex matter that could serve different objectives: lower carbon dioxide emissions, lower monetary expenditures, or maximize solar photovoltaics (PV) energy consumption. Currently, it is unclear how each of those objectives could impact the business and performance of a ride-hailing fleet. In order to fill this gap, this article employs a dynamic transportation model: a smart charging simulation that combines agent-based, discrete-event, and system dynamic modelling by comparing the above-mentioned objectives in separate scenarios. The results show that each scenario successfully manages to shift between 34% and 87% of all load to hours of the day when the objectives of those scenarios are met. Therefore, in comparison to the baseline, smart charging can save between 5% and 26% of monthly emissions and between 4% and 57% of monthly expenditures. The solar PV scenario, however, results in the highest savings, while ensuring profitable economics via net metering in the short- as well as long term. Finally, the sensitivity analysis points to important trade-offs between several fleet performance metrics. The article concludes by giving business and policy recommendations for maximising the economic, energy and environmental efficiency of large ERV fleets.

ADVANCED PROPULSION SYSTEMS,SOLAR ENERGY↗

NASA NTRS1972

Analysis and design of a capsule landing system and surface vehicle control system for Mars exporation

The problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars were investigated. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; navigation, terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks were studied: vehicle model design, mathematical modeling of dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement and transport parameter evaluation.

Frederick, D. K.↗

DOE OSTI2022

Kernel learning backward SDE filter for data assimilation

In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. Further, to characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous global approximation for the conditional probability density function of the target state by using discrete approximated density values as training data. Numerical experiments demonstrate that the kernel learning backward SDE is highly effective.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1972

A comparison of the effects of small nonlinearities on several estimation schemes.

A variety of techniques are available for estimating the states of nonlinear dynamic systems from noisy data. These procedures are generally equivalent when applied to linear systems. This paper investigates the difference between several of these procedures in the presence of small dynamic and observational nonlinearities. In particular, it examines one least square batch processing algorithm, and three recursive algorithms similar to the Kalman filter. To first order, all the estimators have the same covariance. Expressions for the means, however, show that each estimator has a different bias. The examples presented show that the biases can be a strong function of such parameters as initial covariances and number of data points being considered.

Conrad, B.↗

NASA NTRS1983

Analysis of severe storm data

The Mesoscale Analysis and Space Sensor (MASS) Data Management and Analysis System developed by Atsuko Computing International (ACI) on the MASS HP-1000 Computer System within the Systems Dynamics Laboratory of the Marshall Space Flight Center is described. The MASS Data Management and Analysis System was successfully implemented and utilized daily by atmospheric scientists to graphically display and analyze large volumes of conventional and satellite derived meteorological data. The scientists can process interactively various atmospheric data (Sounding, Single Level, Gird, and Image) by utilizing the MASS (AVE80) share common data and user inputs, thereby reducing overhead, optimizing execution time, and thus enhancing user flexibility, useability, and understandability of the total system/software capabilities. In addition ACI installed eight APPLE III graphics/imaging computer terminals in individual scientist offices and integrated them into the MASS HP-1000 Computer System thus providing significant enhancement to the overall research environment.

Hickey, J. S.↗

NASA NTRS1988

Strategy for earth explorers in global earth sciences

The goal of the current NASA Earth System Science initiative is to obtain a comprehensive scientific understanding of the Earth as an integrated, dynamic system. The centerpiece of the Earth System Science initiative will be a set of instruments carried on polar orbiting platforms under the Earth Observing System program. An Earth Explorer program can open new vistas in the earth sciences, encourage innovation, and solve critical scientific problems. Specific missions must be rigorously shaped by the demands and opportunities of high quality science and must complement the Earth Observing System and the Mission to Planet Earth. The committee believes that the proposed Earth Explorer program provides a substantial opportunity for progress in the earth sciences, both through independent missions and through missions designed to complement the large scale platforms and international research programs that represent important national commitments. The strategy presented is intended to help ensure the success of the Earth Explorer program as a vital stimulant to the study of the planet.

Source record↗

NASA NTRS1989

Parallel and vector computation for stochastic optimal control applications

A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.

Hanson, F. B.↗

NASA NTRS1991

Robust controller design for structures with displacement sensors

The passivity theorem may be used to design robust controllers for structures with positive transfer functions. The authors obtain a similar result for systems with displacement sensors. In order to illustrate the ideas discussed, a specific second-order dynamic system is considered.

Morris, K. A.↗