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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS1985

New Directions in Asymptotically Stable Finite-dimensional Adaptive Control of Linear Distributed Parameter Systems

Distributed Parameter Systems (DPS), such as systems described by partial differential equations, require infinite-dimensional state space descriptions to correctly model their dynamical behavior. However, any adaptive control algorithm must be finite-dimensional in order to be implemented via on-line digital computers. Finite-dimensional adaptive control of linear DPS requires stability analysis of nonlinear, time-varying, infinite-dimensional systems. The structure of nonadaptive finite-dimensional control of linear DPS is summarized as it relates to the existence of limiting systems for adaptive control. Two candidate schemes for finite-dimensional adaptive control of DPS are described and critical issues in infinite-dimensional stability analysis are discussed, in particular, the invariance principle, center manifold theory, and relationships between input-output and internal stability.

Balas, M. J.↗
NASA NTRS1986

Provably conservative approximations to complex reliability models

Complex models can be the bases for derivation of provably conservative and optimistic reliability models that incorporate a reduced state space and fewer transitions; they accordingly possess solutions that are more cost-effective than those of the original complex models. Design space can thereby be extensively explored without incurring the expense of multiple complex model solutions. A conservative-optimistic pair of derived models produces a band that includes the solution to the complex model. Sensitivity analysis can be performed on this pair of models to determine those parameters of the original model that are most sensitive to change and therefore require further expense in obtaining tighter specifications.

Smotherman, M.↗
NASA NTRS1989

Control law synthesis and optimization software for large order aeroservoelastic systems

A flexible aircraft or space structure with active control is typically modeled by a large-order state space system of equations in order to accurately represent the rigid and flexible body modes, unsteady aerodynamic forces, actuator dynamics and gust spectra. The control law of this multi-input/multi-output (MIMO) system is expected to satisfy multiple design requirements on the dynamic loads, responses, actuator deflection and rate limitations, as well as maintain certain stability margins, yet should be simple enough to be implemented on an onboard digital microprocessor. A software package for performing an analog or digital control law synthesis for such a system, using optimal control theory and constrained optimization techniques is described.

Mukhopadhyay, V.↗
NASA NTRS1989

Multidisciplinary Expert-aided Analysis and Design (MEAD)

The MEAD Computer Program (MCP) is being developed under the Multidisciplinary Expert-Aided Analysis and Design (MEAD) Project as a CAD environment in which integrated flight, propulsion, and structural control systems can be designed and analyzed. The MCP has several embedded computer-aided control engineering (CACE) packages, a user interface (UI), a supervisor, a data-base manager (DBM), and an expert system (ES). The supervisor monitors and coordinates the operation of the CACE packages, the DBM; the ES, and the UI. The DBM tracks the control design process. Models created or installed by the MCP are tracked by date and version, and results are associated with the specific model version with which they were generated. The ES is used to relieve the control engineer from tedious and cumbersome tasks in the iterative design process. The UI provides the capability for a novice as well as an expert to utilize the MCP easily and effectively. The MCP version 2(MCP-2.0) is fully developed for flight control system design and analysis. Propulsion system modeling, analysis, and simulation is also supported; the same is true for structural models represented in state-space form. The ultimate goal is to cover the integration of flight, propulsion, and structural control engineering, including all discipline-specific functionality and interfaces. The current MCP-2.0 components and functionality are discussed.

Hummel, Thomas C.↗
NASA NTRS1995

Techniques for modeling the reliability of fault-tolerant systems with the Markov state-space approach

This paper presents a step-by-step tutorial of the methods and the tools that were used for the reliability analysis of fault-tolerant systems. The approach used in this paper is the Markov (or semi-Markov) state-space method. The paper is intended for design engineers with a basic understanding of computer architecture and fault tolerance, but little knowledge of reliability modeling. The representation of architectural features in mathematical models is emphasized. This paper does not present details of the mathematical solution of complex reliability models. Instead, it describes the use of several recently developed computer programs SURE, ASSIST, STEM, and PAWS that automate the generation and the solution of these models.

Butler, Ricky W.↗
NASA NTRS2018

Output Measurement Equations for Flexible Aircraft Flight Dynamics

A summary of output measurement equations for onboard sensors used in flight testing of flexible aircraft is presented. These equations include the effects of structural flexibility and are considerably more complex than the standard equations for rigid-body aircraft. The output equations discussed include accelerations from linear accelerometers, strains, angular rates, angular accelerations, Euler angles, true airspeed, and air flow angles. The output equations are derived in full form and then simplified in some cases. Linearized output equations, suitable for state-space or transfer function models, are also developed. Example flight test data from the X-56A subscale aeroelastic demonstrator is discussed, for reference.

Grauer, Jared A.↗
NASA NTRS2019

A Simple Control to Reduce the Voltage Stress of Non-Conducting Switches in Three-Level ANPC Converter

With the development of wide band-gap (WBG) technology, the switching speed of power semiconductor devices is increased, which makes circuits more sensitive to parasitics. For three-level active neutral point clamped (3L-ANPC) converters, the over-voltage of non-conducting switches can be an issue. This paper analyzes the multiple commutation loops in 3L-ANPC converter and summarizes the impact factors of the over-voltage for the non-conducting switch. It is found that the nonlinearity of the output capacitance of the device can significantly influence the over-voltage. A simple control without introducing any additional hardware circuit is proposed to attenuate the impact of the nonlinearity. With the proposed control, the peak over-voltage of the non-conducting switch can be reduced significantly. Multi-pulse test is conducted for a 3L- ANPC converter built with silicon carbide (SiC) MOSFETs. The testing results show that the peak over-voltage decreases from 892 V to 624 V with the proposed control. More detailed analysis and experimental results will be provided in the final paper.

SiC MOSFET↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2023

Uncertainty quantification for equations of state: copper as an example

Equations of state are essential for providing a fundamental description of materials properties in thermodynamic equilibrium and are used to provide closure relations for hydrodynamics simulations. Generally, equations of state rely on simple physics-based parameterized materials models to inform on the free energy of a material through out a given thermodynamic state space. Historically the parameters of these models have been tuned by hand to fit various experimental data. However, modern optimization and uncertainty quantification techniques allow us to quickly test thousands of parameter combinations and obtain meaningful uncertainty estimates on the parameters, opening opportunities for assessing systematic uncertainties in experiments, assessing model adequacy, and more. In this report, we use Bayesian inference to fit the solid (fcc) equation of state of copper. We focus on fitting five different experimental datasets, including the isobaric density, isobaric heat capacity, room temperature isotherm, principal isentrope, and principal Hugoniot. We fit all five data types simultaneously, and then explore the extent to which combinations of 2 subsets of the 5 datasets can constrain the EOS parameters, as compared to the fit to all 5. This information is useful for investigating the extent to which different datasets can con strain EOS models and thereby help guide experimental investigations in order to best constrain the EOS. We also discuss ways that the methodologies can be used to investigate systematic discrepancies between experiments, as well as how the methods can be used to assess model uncertainty. The framework we develop is general, in that it can be used with a variety of optimization or uncertainty quantification techniques and with a variety of data sources, including both experimental and ab-inito data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Assessment of current state of the art in modeling techniques and analysis methods for large space structures

Advances in continuum modeling, progress in reduction methods, and analysis and modeling needs for large space structures are covered with specific attention given to repetitive lattice trusses. As far as continuum modeling is concerned, an effective and verified analysis capability exists for linear thermoelastic stress, birfurcation buckling, and free vibration problems of repetitive lattices. However, application of continuum modeling to nonlinear analysis needs more development. Reduction methods are very effective for bifurcation buckling and static (steady-state) nonlinear analysis. However, more work is needed to realize their full potential for nonlinear dynamic and time-dependent problems. As far as analysis and modeling needs are concerned, three areas are identified: loads determination, modeling and nonclassical behavior characteristics, and computational algorithms. The impact of new advances in computer hardware, software, integrated analysis, CAD/CAM stems, and materials technology is also discussed.

Noor, A. K.↗
NASA NTRS1989

Model reduction in the physical coordinate system

In the dynamics modeling of a flexible structure, finite element analysis employs reduction techniques, such as Guyan's reduction, to remove some of the insignificant physical coordinates, thus producing a dynamics model that has smaller mass and stiffness matrices. But this reduction is limited in the sense that it removes certain degrees of freedom at a node points themselves in the model. From the standpoint of linear control design, the resultant model is still too large despite the reduction. Thus, some form of the model reduction is frequently used in control design by approximating a large dynamical system with a fewer number of state variables. However, a problem arises from the placement of sensors and actuators in the reduced model, because a model usually undergoes, before being reduced, some form of coordinate transformations that do not preserve the physical meanings of the states. To correct such a problem, a method is developed that expresses a reduced model in terms of a subset of the original states. The proposed method starts with a dynamic model that is originated and reduced in finite element analysis. Then the model is converted to the state space form, and reduced again by the internal balancing method. At this point, being in the balanced coordinate system, the states in the reduced model have no apparent resemblance to those of the original model. Through another coordinate transformation that is developed, however, this reduced model is expressed by a subset of the original states.

Yae, K. Harold↗
NASA NTRS1990

Approximations of thermoelastic and viscoelastic control systems

Well-posed models and computational algorithms are developed and analyzed for control of a class of partial differential equations that describe the motions of thermo-viscoelastic structures. An abstract (state space) framework and a general well-posedness result are presented that can be applied to a large class of thermo-elastic and thermo-viscoelastic models. This state space framework is used in the development of a computational scheme to be used in the solution of a linear quadratic regulator (LQR) control problem. A detailed convergence proof is provided for the viscoelastic model and several numerical results are presented to illustrate the theory and to analyze problems for which the theory is incomplete.

Burns, J. A.↗
NASA NTRS2008

Program Model Checking: A Practitioner's Guide

Program model checking is a verification technology that uses state-space exploration to evaluate large numbers of potential program executions. Program model checking provides improved coverage over testing by systematically evaluating all possible test inputs and all possible interleavings of threads in a multithreaded system. Model-checking algorithms use several classes of optimizations to reduce the time and memory requirements for analysis, as well as heuristics for meaningful analysis of partial areas of the state space Our goal in this guidebook is to assemble, distill, and demonstrate emerging best practices for applying program model checking. We offer it as a starting point and introduction for those who want to apply model checking to software verification and validation. The guidebook will not discuss any specific tool in great detail, but we provide references for specific tools.

Pressburger, Thomas T.↗
NASA NTRS1983

On-board estimation technology for space station - Current status and future developments.

Design considerations and projected solutions to on-board automated estimation techniques for advanced technology controls on a space station are described, with emphasis on the state estimator. The space station is modelled as a collection of rigid and flexible bodies connected at a finite number of hinges. The systems dynamics are characterized by angular velocities of the base body, gimbal angles, and deflections of the flexible appendages. The state estimator evolution is projected to occur in four generations, with the first being control logic in the Viking and Voyager spacecraft, the second in the Shuttle and Galileo probe, the third being large antennas and the prototype space station, the last, around the year 2000, for the actual space station. Considerations for attitude, ephemeris, shape determination, and position estimation through each generation are discussed.

Rodriguez, G.↗
NASA NTRS1987

Modelling the performance of the monogroove with screen heat pipe for use in the radiator of the solar dynamic power system of the NASA Space Station

A computer code to model the steady-state performance of a monogroove heat pipe for the NASA Space Station is presented, including the effects on heat pipe performance of a screen in the evaporator section which deals with transient surges in the heat input. Errors in a previous code have been corrected, and the new code adds additional loss terms in order to model several different working fluids. Good agreement with existing performance curves is obtained. From a preliminary evaluation of several of the radiator design parameters it is found that an optimum fin width could be achieved but that structural considerations limit the thickness of the fin to a value above optimum.

Evans, Austin Lewis↗
DOE OSTI2021

Transient recovery problem in acoustics: A multichannel model-based deconvolution approach

Critical acoustical systems operating in complex environments contaminated with disturbances and noise offer an extreme challenge when excited by out-of-the-ordinary, impulsive, transient events that can be undetected and seriously affect their overall performance. Transient impulse excitations must be detected, extracted, and evaluated to determine any potential system damage that could have been imposed; therefore, the problem of recovering the excitation in an uncertain measurement environment becomes one of multichannel deconvolution. Recovering a transient and its initial energy has not been solved satisfactorily, especially when the measurement has been truncated and only a small segment of response data is available. The development of multichannel deconvolution techniques for both complete and incomplete excitation data is discussed, employing a model-based approach based on the state-space representation of an identified acoustical system coupled to a forward modeling solution and a Kalman-type processor for enhancement and extraction. In conclusion, synthesized data are utilized to assess the feasibility of the various approaches, demonstrating that reasonable performance can be achieved even in noisy environments.

42 ENGINEERING↗