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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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NASA NTRS1988

Reliability Model Generator for fault-tolerant systems

This paper discusses an analysis tool, the Reliability Model Generator, that reasons from structural and functional system design specifications to generate a reliability model for the system under investigation. The resultant model defines a system state space sufficient to characterize the effects of single and multiple component failures. This model may then be examined by the analyst or used as input to an existing reliability evaluation tool, the Semi-Markov Unreliability Range Evaluator (SURE), to compute numeric bounds for system reliability (i.e., safety, mission success, availability, etc.). In defining the input to the Reliability Model Generator, a separation of the component function from structural specification is proposed to allow easy modification for analysis of alternative architectures. A hierarchical system description paradigm promotes multiple abstractions, thereby enabling analysis at all phases of the design process. The work described in this paper has been supported under NASA contract NAS1-10899, Integrated Airframe/Propulsion Control System Architecture (IAPSA II). IAPSA II promotes a system engineering methodology and supporting analytical tools to evaluate flight control architecture configuration alternatives during early phases of the design cycle when the cost and schedule impact of design revisions is minimal. Emphasis is placed on traceability to ensure that the requirements drive the resulting design.

Catherine M McCann↗

NASA NTRS2002

Elementary Theory of Covariance Modeling

The contents include: 1. State space, spectral space, and observation space; 2. Variances and correlations; 3. Isotropic and anisotropic correlation modeling on the sphere; 4. Operational ozone data assimilation; and 5. Kalman filtering for trace constituents.

Cohn, S.↗

NASA NTRS2007

Community Coordinated Modeling Center Support of Science Needs for Integrated Data Environment

Space science models are essential component of integrated data environment. Space science models are indispensable tools to facilitate effective use of wide variety of distributed scientific sources and to place multi-point local measurements into global context. The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the- art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. The majority of models residing at CCMC are comprehensive computationally intensive physics-based models. To allow the models to be driven by data relevant to particular events, the CCMC developed an online data file generation tool that automatically downloads data from data providers and transforms them to required format. CCMC provides a tailored web-based visualization interface for the model output, as well as the capability to download simulations output in portable standard format with comprehensive metadata and user-friendly model output analysis library of routines that can be called from any C supporting language. CCMC is developing data interpolation tools that enable to present model output in the same format as observations. CCMC invite community comments and suggestions to better address science needs for the integrated data environment.

Kuznetsova, M. M.↗

DOE OSTI2021

Fluid temperature predictions of geothermal borefields using load estimations via state observers

Fluid temperature predictions of geothermal borefields usually involves temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modeled as a linear state space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised when the borefield is already operating and its load history is not registered or there are gaps in the data. This paper assesses the performance of state observers to estimate the borefield load history and obtain accurate fluid predictions. Results show that both Time-Varying Kalman Filter (TVKF) and Moving Horizon Estimator (MHE) provide predictions with average and maximum errors below 0.1 $^\circ C$ and 1 $^\circ C$ respectively. MHE outperforms TVKF in terms of n-step ahead output predictions and load history profile at the expenses of about 5 times more computational time.

Figueroa, Iago C.↗

NASA NTRS1977

Systems theoretic model of stratospheric pollution on ozone

Discrete state space analysis is applied to the development of a model for predicting the reduction in the amount of stratospheric ozone due to stratospheric pollution. The modeling approach is to segment the stratosphere into a number of altitudinal bands and to associate state variables with the state of ozone reduction in each band due to NO(x) injections. The ozone reductions in each band are then combined into an estimate of total global ozone reduction. The model proposed predicts changes in stratospheric ozone based on altitude of pollutant injection and volume of pollutant injected at that altitude. The present approach is not a detailed analysis of stratospheric constituents and their interactions, but rather an analysis procedure for modeling the results of other researchers in the field.

Wilkins, R. D.↗

NASA NTRS1973

Properties of heuristic search strategies

A directed graph is used to model the search space of a state space representation with single input operators, an AND/OR is used for problem reduction representations, and a theorem proving graph is used for state space representations with multiple input operators. These three graph models and heuristic strategies for searching them are surveyed. The completeness, admissibility, and optimality properties of search strategies which use the evaluation function f = (1 - omega)g = omega(h) are presented and interpreted using a representation of the search process in the plane. The use of multiple output operators to imply dependent successors, and thus obtain a formalism which includes all three types of representations, is discussed.

Vanderbrug, G. J.↗

NASA NTRS2026

Development, Characterization, and Validation of Elevated-Temperature Constitutive Models: Deformation and Damage

This report provides a brief review of experimentally observed hereditary and nonhereditary material behavior along with background information on standard as well as advanced internal state variable constitutive modeling at elevated temperature. A description of exploratory, characterization, and validation testing is presented along with a detailed outline of what constitutes “sufficient” data content (i.e., quality and quantity) for developing or enhancing, characterizing, and validating a particular sophisticated nonlinear time- and history-dependent (hereditary) class of constitutive models known as GVIPS (generalized viscoplasticity with potential structure). The tests described are necessary to reveal a material’s behavior in the reversible (or viscoelastic) and irreversible (or viscoplastic) regimes, for the identification of both deformation and damage model parameters. Results presented are primarily for metallic materials. In all cases, both uniaxial and multiaxial tests are described, and the linkage between the specific tests and the parameters within the model that can be characterized from the results of these tests are also discussed. Discussion is also provided relative to the role information management must play relative to material data collection, analysis, maintenance, and dissemination. The need for such an information system is particularly important as both analyst and designer move toward utilizations of sophisticated, nonlinear time- and history dependent (hereditary) constitutive models. Lastly, the concept of state space and its utility in understanding and establishing constitutive models is addressed throughout. The intent behind this document is to help both the modeler and experimentalist understand each other’s specific points of view and provide guidance for both model development and characterization. Emphasis has been placed on providing the mechanician with information regarding how tests are performed and what issues to be aware of when interpreting results. It is hoped that experimentalists will take away a new perspective on the types of information that modelers and analysts are looking for from them.

Constitutive Modeling↗

NASA NTRS2007

Advanced Control Algorithms for Compensating the Phase Distortion Due to Transport Delay in Human-Machine Systems

The desire to create more complex visual scenes in modern flight simulators outpaces recent increases in processor speed. As a result, simulation transport delay remains a problem. New approaches for compensating the transport delay in a flight simulator have been developed and are presented in this report. The lead/lag filter, the McFarland compensator and the Sobiski/Cardullo state space filter are three prominent compensators. The lead/lag filter provides some phase lead, while introducing significant gain distortion in the same frequency interval. The McFarland predictor can compensate for much longer delay and cause smaller gain error in low frequencies than the lead/lag filter, but the gain distortion beyond the design frequency interval is still significant, and it also causes large spikes in prediction. Though, theoretically, the Sobiski/Cardullo predictor, a state space filter, can compensate the longest delay with the least gain distortion among the three, it has remained in laboratory use due to several limitations. The first novel compensator is an adaptive predictor that makes use of the Kalman filter algorithm in a unique manner. In this manner the predictor can accurately provide the desired amount of prediction, while significantly reducing the large spikes caused by the McFarland predictor. Among several simplified online adaptive predictors, this report illustrates mathematically why the stochastic approximation algorithm achieves the best compensation results. A second novel approach employed a reference aircraft dynamics model to implement a state space predictor on a flight simulator. The practical implementation formed the filter state vector from the operator s control input and the aircraft states. The relationship between the reference model and the compensator performance was investigated in great detail, and the best performing reference model was selected for implementation in the final tests. Theoretical analyses of data from offline simulations with time delay compensation show that both novel predictors effectively suppress the large spikes caused by the McFarland compensator. The phase errors of the three predictors are not significant. The adaptive predictor yields greater gain errors than the McFarland predictor for short delays (96 and 138 ms), but shows smaller errors for long delays (186 and 282 ms). The advantage of the adaptive predictor becomes more obvious for a longer time delay. Conversely, the state space predictor results in substantially smaller gain error than the other two predictors for all four delay cases.

Guo, Liwen↗

NASA NTRS1986

Static shape control for flexible structures

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

Rodriguez, G.↗

NASA NTRS1993

Issac, Jason Cherian ses in transonic flow

Flutter analysis of a two degree of freedom airfoil in compressible flow is performed using a state-space representation of the unsteady aerodynamic behavior. Indicial response functions are used to represent the normal force and moment response of the airfoil. The structural equations of motion of the airfoil with bending and torsional degrees of freedom are coupled to the unsteady air loads and the aeroelastic system so modelled is solved as an eigenvalue problem to determine the stability. The aeroelastic equations are also directly integrated with respect to time and the time-domain results compared with the results from the eigenanalysis. A good agreement is obtained. The derivatives of the flutter speed obtained from the eigenanalysis are calculated with respect to the mass and stiffness parameters by both analytical and finite-difference methods for various transonic Mach numbers. The experience gained from the two degree of freedom model is applied to study the sensitivity of the flutter response of a wing with respect to various shape parameters. The parameters being considered are as follows: (1) aspect ratio; (2) surface area of the wing; (3) taper ratio; and (4) sweep. The wing deflections are represented by Chebyshev polynomials. The compressible aerodynamic state-space model used for the airfoil section is extended to represent the unsteady aerodynamic forces on a generally laminated tapered skewed wing. The aeroelastic equations are solved as an eigenvalue problem to determine the flutter speed of the wing. The derivatives of the flutter speed with respect to the shape parameters are calculated by both analytical and finite difference methods.

Issac, Jason Cherion↗

NASA NTRS1989

Modeling and control system design and analysis tools for flexible structures

Described here are Boeing software tools used for the development of control laws of flexible structures. The Boeing Company has developed a software tool called Modern Control Software Package (MPAC). MPAC provides the environment necessary for linear model development, analysis, and controller design for large models of flexible structures. There are two features of MPAC which are particularly appropriate for use with large models: (1) numerical accuracy and (2) label-driven nature. With the first feature MPAC uses double precision arithmetic for all numerical operations and relies on EISPAC and LINPACK for the numerical foundation. With the second feature, all MPAC model inputs, outputs, and states are referenced by user-defined labels. This feature allows model modification while maintaining the same state, input, and output names. In addition, there is no need for the user to keep track of a model variable's matrix row and colunm locations. There is a wide range of model manipulation, analysis, and design features within the numerically robust and flexible environment provided by MPAC. Models can be built or modified using either state space or transfer function representations. Existing models can be combined via parallel, series, and feedback connections; and loops of a closed-loop model may be broken for analysis.

Anissipour, Amir A.↗

NASA NTRS2000

Timing analysis by model checking

The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.

Naydich, Dimitri↗

NASA NTRS1994

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗

NASA NTRS1989

Parallel processing environment for multi-flexible body dynamics

The implementation of a dynamics solution algorithm with inherent parallelism which is applicable to the dynamics of large flexible space structures is described. The algorithm is unique in that parts of the solution can be computed simultaneously by working with different branches of its tree topology. The algorithm exhibits close to 0(n) type behavior. The data flow within the solution algorithm is discussed along with results from its implementation in a multiprocessing environment. A model of the United States Space Station is used as an example. The results show that, with fast multiple scalar processors, an efficient algorithm, and symbolically generated equations of motion, real-time performance can be achieved with present-day hardware technology, even with complex dynamical models.

Venugopal, Ravi↗

NASA NTRS1994

Modeling of aircraft unsteady aerodynamic characteristics. Part 1: Postulated models

A short theoretical study of aircraft aerodynamic model equations with unsteady effects is presented. The aerodynamic forces and moments are expressed in terms of indicial functions or internal state variables. The first representation leads to aircraft integro-differential equations of motion; the second preserves the state-space form of the model equations. The formulations of unsteady aerodynamics is applied in two examples. The first example deals with a one-degree-of-freedom harmonic motion about one of the aircraft body axes. In the second example, the equations for longitudinal short-period motion are developed. In these examples, only linear aerodynamic terms are considered. The indicial functions are postulated as simple exponentials and the internal state variables are governed by linear, time-invariant, first-order differential equations. It is shown that both approaches to the modeling of unsteady aerodynamics lead to identical models.

Klein, Vladislav↗

DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation: Preprint

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

Bayesian structural time series↗

NASA NTRS1997

Algorithms for Performance, Dependability, and Performability Evaluation using Stochastic Activity Networks

Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure.

Deavours, Daniel D.↗

NASA NTRS2005

A Comprehensive Study of Three Delay Compensation Algorithms for Flight Simulators

This paper summarizes a comprehensive study of three predictors used for compensating the transport delay in a flight simulator; The McFarland, Adaptive and State Space Predictors. The paper presents proof that the stochastic approximation algorithm can achieve the best compensation among all four adaptive predictors, and intensively investigates the relationship between the state space predictor s compensation quality and its reference model. Piloted simulation tests show that the adaptive predictor and state space predictor can achieve better compensation of transport delay than the McFarland predictor.

Guo, Liwen↗