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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detecting isolated resonance curves using fixed frequency voltage control tests

Isolated resonance curves, or isolas, are resonance branches of the harmonically forced system that exist separately from the main nonlinear forced response curve, leading to excessive vibrations. Traditional stepped or swept sine simulations and tests rely on continuation along the frequency parameter, typically resulting in a jump phenomenon along the primary resonance branch, prior to the disconnected isola. The main objective of this research is to propose an approach to identify isolated resonance curves by performing continuation along the input amplitude that initializes the response from a low-amplitude solution in the linear regime. Furthermore, this is achieved with the open-loop fixed frequency voltage control method that continues along the shaker voltage parameter and measures the so-called S-curves, which are theoretically a continuous solution branch that connect to the isola. The methodology is demonstrated on a fixture-wing-pylon assembly with a vibro-impact nonlinearity localized in a pylon subcomponent attachment. Multi-harmonic balance simulations are deployed to compute both the nonlinear forced response curves and S-curves to demonstrate the isola detection strategy on a reduced-order finite element model of the nonlinear system. Swept sine and fixed frequency voltage control tests are then conducted on the physical structure to demonstrate the isola detection experimentally, revealing the existence of the large amplitude vibrations that are undetected in the forces levels and frequencies measured with traditional frequency sweeping.

Characterization and Analytical Technique↗
NASA NTRS1975

Simplified simulation models for control studies of turbojet engines

The essential dynamical characteristics of a simple single spool turbojet engine were determined through simulation of low order system models on an analog computer. An accurate model was studied and system complexity was reduced through various linearizations and approximations. A derivation of a seventh order simplified simulation model is presented with a derivation of an even simpler third order model, and simulation results from each. The control problem studied is one of getting from zero fuel flow equilibrium to a high thrust equilibrium while taking into account surge margin and turbine inlet temperature constraints.

Brennan, T. C.↗
DOE OSTI2021

Data-driven learning of Mori–Zwanzig operators for isotropic turbulence

Developing reduced-order models for turbulent flows, which contain dynamics over a wide range of scales, is an extremely challenging problem. In statistical mechanics, the Mori–Zwanzig (MZ) formalism provides a mathematically exact procedure for constructing reduced-order representations of high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. Turbulence models based on MZ formalism have been scarce due to the limited knowledge of the MZ operators, which originates from the difficulty in deriving MZ kernels for complex nonlinear dynamical systems. In this work, we apply a recently developed data-driven learning algorithm, which is based on Koopman's description of dynamical systems and Mori's linear projection operator, on a set of fully resolved isotropic turbulence datasets to extract the Mori–Zwanzig operators. With data augmentation using known turbulence symmetries, the extracted Markov term, memory kernel, and orthogonal dynamics are statistically converged and the generalized fluctuation–dissipation relation can be verified. The properties of the memory kernel and orthogonal dynamics, and their dependence on the choices of observables are investigated to address the modeling assumptions that are commonly used in MZ-based models. A series of numerical experiments are then constructed using the extracted kernels to evaluate the memory effects on prediction. The results show that the prediction errors are strongly affected by the choice of observables and can be further reduced by including the past history of the observables in the memory kernel.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

System test and flight results from infrared astronomical satellite external thermal subsystem

The Infrared Astronomical Satellite (IRAS) received its system level thermal testing in a solar simulator in September and October 1982 and was launched in January 1983. In order to reduce costs and meet a tight launch schedule, a system thermal test approach was employed which combined the goals of thermal design development tests, thermal balance tests, and thermal vacuum qualification tests. This approach relied heavily on the use of a computer-controlled automatic data handling and heater control system which reduced reliance on human monitoring of test data in comparison to past projects. The validity of this approach has been borne out by flight results. During the whole mission most temperatures were within the desired range and close to predictions. Included under the external thermal subsystem are room temperature electronics and radiatively cooled surfaces with temperatures below 100 and 200K.

Salazar, R. P.↗
NASA NTRS1995

A Game Theoretic Fault Detection Filter

The fault detection process is modelled as a disturbance attenuation problem. The solution to this problem is found via differential game theory, leading to an H(sub infinity) filter which bounds the transmission of all exogenous signals save the fault to be detected. For a general class of linear systems which includes some time-varying systems, it is shown that this transmission bound can be taken to zero by simultaneously bringing the sensor noise weighting to zero. Thus, in the limit, a complete transmission block can he achieved, making the game filter into a fault detection filter. When we specialize this result to time-invariant system, it is found that the detection filter attained in the limit is identical to the well known Beard-Jones Fault Detection Filter. That is, all fault inputs other than the one to be detected (the "nuisance faults") are restricted to an invariant subspace which is unobservable to a projection on the output. For time-invariant systems, it is also shown that in the limit, the order of the state-space and the game filter can be reduced by factoring out the invariant subspace. The result is a lower dimensional filter which can observe only the fault to be detected. A reduced-order filter can also he generated for time-varying systems, though the computational overhead may be intensive. An example given at the end of the paper demonstrates the effectiveness of the filter as a tool for fault detection and identification.

Chung, Walter H.↗
DOE OSTI2021

Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Mean-square error bounds for reduced-error linear state estimators

The mean-square error of reduced-order linear state estimators for continuous-time linear systems is investigated. Lower and upper bounds on the minimal mean-square error are presented. The bounds are readily computable at each time-point and at steady state from the solutions to the Ricatti and the Lyapunov equations. The usefulness of the error bounds for the analysis and design of reduced-order estimators is illustrated by a practical numerical example.

Baram, Y.↗
NASA NTRS1987

Mean-square-error bounds for reduced-order linear state estimators

The mean-square error of reduced-order linear state estimators for continuous-time linear systems is investigated. Lower and upper bounds on the minimal mean-square error are presented. The bounds are readily computable at each time-point and at steady state from the solutions to the Ricatti and the Liapunov equations. The usefulness of the error bounds for the analysis and design of reduced-order estimators is illustrated by a practical numerical example.

Baram, Y.↗
NASA NTRS1981

Parameter estimation of large flexible aerospace structures with application to the control of the Maypole Deployable Reflector

Systems such as the Maypole deployable reflector have a distributed parameter nature. The flexible column and hoop structure and the circular antenna of 30-100 meter diameter which it supports are described by partial, rather than ordinary, differential equations. Progress completed in reduced order modelling andd controller design and digital parameter estimation and control is summarized. Topics covered include depolyment and on-orbit operation; quasi-static (steady state) operation; dynamic distributed parameter system; autoregressive moving average identification; frequency domain procedures; direct or implicit active control; adaptive observers; parameter estimation using a linear reinforcement learning factor; feedback control; and reduced order modeling for nonlinear systems.

Balas, M. J.↗
NASA NTRS1988

Space shuttle main engine monitoring experience and advanced monitoring systems development

Advanced space transportation systems must provide improved availability, reliability, safety, and reduced cost in order to make a new, more vigorous level of space activity economically feasible. Earth-to-Orbit (ETO) propulsion monitoring systems are a major factor in progress toward these improvements, and in the success of current systems. Operational experience with the Space Shuttle Main Engine (SSME), the first reusable ETO rocket engine, is valuable for examining current rocket engine monitoring capability and technology developments. Here, Space Shuttle Main Engine (SSME) monitoring practice and experience are surveyed. Unique aspects of rocket engine mission requirements are highlighted to provide improved understanding of engine monitoring practices and technology needs. Current ETO engine transportation systems mission needs are outlined. With this foundation, the techniques and components addressed within current technology programs are discussed to complete a picture of ETO propulsion monitoring status and development.

Cikanek, Harry A.↗
DOE OSTI2023

A Systematic, Polynomial-Cost Approach to Exact Correlation Energies (Final Technical Report)

The full configuration interaction (FCI) wave function provides the exact solution to the Schrödinger equation in a given basis set. While FCI is intractable due to exponential computational costs, the many-body expansion (or the method of increments) can reduce scaling to a low-order polynomial with system size. This project entailed advances in the incremental FCI (iFCI) approach, designed to allow iFCI to reach larger system sizes and maintain its intrinsic high accuracy. This document describes advances in solvers for iFCI, strategies to treat multiple charge and spin states, and virtual state management methods to reduce memory requirements. Overall, this project allows iFCI to correlate (for the first time) 142 valence electrons in 444 orbitals in a realistic model of a transition metal complex.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Hamiltonian reduction of Vlasov–Maxwell to a dark slow manifold

In this work, we show that non-relativistic scaling of the collisionless Vlasov–Maxwell system implies the existence of a formal invariant slow manifold in the infinite-dimensional Vlasov–Maxwell phase space. Vlasov–Maxwell dynamics restricted to the slow manifold recovers the Vlasov–Poisson and Vlasov–Darwin models as low-order approximations, and provides higher-order corrections to the Vlasov–Darwin model more generally. The slow manifold may be interpreted to all orders in perturbation theory as a collection of formal Vlasov–Maxwell solutions that do not excite light waves, and are therefore ‘dark’. We provide a heuristic lower bound for the time interval over which Vlasov–Maxwell solutions initialized optimally near the slow manifold remain dark. We also show how the dynamics on the slow manifold naturally inherits a Hamiltonian structure from the underlying system. After expressing this structure in a simple form, we use it to identify a manifestly Hamiltonian correction to the Vlasov–Darwin model. The derivation of higher-order terms is reduced to computing the corrections of the system Hamiltonian restricted to the slow manifold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Reduced-Order Models of Static Power Grids based on Spectral Clustering

For large-scale interconnected power systems that cover large geographical areas, certain electrical studies are required so that appropriate decisions ensure system reliability and low cost. For such studies, it is often neither practical nor necessary to model in detail the entire power system, which is increasingly complex due to a more diverse range of grid assets to choose from in both short and long-term planning. The goal of this paper is to present a methodology to reduce the order of large-scale power networks based on spectral graph theory given that current methods for static network reduction are not scalable. A brief analysis of some spectral clustering properties to determine which graph Laplacian matrix should be used and why is included. The analysis shows that the utilization of the normalized graph Laplacian is more advantageous for clustering purposes. Techniques are proposed to approximate cost functions for the aggregated generators. This is done via linear regression. The reduced-order model obtained with the proposed methodology has an accuracy above 94% and solves the scalability issue commonly present in other reduction methods. If the utilization of the reduced-order model is either constrained to load levels above mid-peak demand, or cost functions of aggregated units are approximated via a piecewise quadratic approach, then the error distribution is in the order of 10^-3. .

Baquedano-Aguilar, Mario D.↗
NASA NTRS1975

On the invertibility of linear multivariable systems

Some results concerning invertibility of a class of linear, time-invariant systems are presented. It is shown that by an appropriate factorization of the transfer matrix of such a system, the problem of checking its invertibility can be reduced to that of checking the invertibility of a lower-order system. A sufficient condition for invertibility is also obtained.

Patel, R. V.↗
NASA NTRS2005

Heart Pump Design for Cleveland Clinic Foundation

Through a Lewis CommTech Program project with the Cleveland Clinic Foundation, the NASA Lewis Research Center is playing a key role in the design and development of a permanently implantable, artificial heart pump assist device. Known as the Innovative Ventricular Assist System (IVAS), this device will take on the pumping role of the damaged left ventricle of the heart. The key part of the IVAS is a nonpulsatile (continuous flow) artificial heart pump with centrifugal impeller blades, driven by an electric motor. Lewis is part of an industry and academia team, led by the Ohio Aerospace Institute (OAI), that is working with the Cleveland Clinic Foundation to make IVAS a reality. This device has the potential to save tens of thousands of lives each year, since 80 percent of heart attack victims suffer irreversible damage to the left ventricle, the part of the heart that does most of the pumping. Impeller blade design codes and flow-modeling analytical codes will be used in the project. These codes were developed at Lewis for the aerospace industry but will be applicable to the IVAS design project. The analytical codes, which currently simulate the flow through the compressor and pump systems, will be used to simulate the flow within the blood pump in the artificial heart assist device. The Interdisciplinary Technology Office heads up Lewis' efforts in the IVAS project. With the aid of numerical modeling, the blood pump will address many design issues, including some fluid-dynamic design considerations that are unique to the properties of blood. Some of the issues that will be addressed in the design process include hemolysis, deposition, recirculation, pump efficiency, rotor thrust balance, and bearing lubrication. Optimum pumping system performance will be achieved by modeling all the interactions between the pump components. The interactions can be multidisciplinary and, therefore, are influenced not only by the fluid dynamics of adjacent components but also by thermal and structural effects. Lewis-developed flow-modeling codes to be used in the pump simulations will include a one-dimensional code and an incompressible three-dimensional Navier-Stokes flow code. These codes will analyze the prototype pump designed by the Cleveland Clinic Foundation. With an improved understanding of the flow phenomena within the prototype pump, design changes to improve the performance of the pump system can be verified by computer prior to fabrication in order to reduce risks. The use of Lewis flow modeling codes during the design and development process will improve pump system performance and reduce the number of prototypes built in the development phase. The first phase of the IVAS project is to fully develop the prototype in a laboratory environment that uses a water/glycerin mixture as the surrogate fluid to simulate blood. A later phase of the project will include testing in animals for final validation. Lewis will be involved in the IVAS project for 3 to 5 years.

Source record↗
NASA NTRS1992

Functional implications of component commonality in operational systems

The application of commonality in a system represents an attempt to reduce costs by reducing the number of unique components. Research in this area has primarily addressed a significant benefit of commonality, the reduction of parts inventories in assemble-to-order manufacturing systems. Likewise, in an operational system subject to component failures, spares inventories are reduced through the increased commonality of components. However, commonality tends to degrade system performance parameters, a degradation that can preclude commonality in resource-constrained systems such as spacecraft. The functional impacts of component commonality on a system is addressed in a manner that allows inclusion in a commonality analysis.

Thomas, Lawrence D.↗
NASA NTRS1986

Minimum-fuel control of high-order systems

The minimum-fuel control problem is of special interest in various space systems. To date, solutions of minimum-fuel control problems have been carried out for relatively low-order systems. Space structures, however, are generally characterized by a large number of degrees of freedom, so that minimum-fuel control of such systems requires a new approach. In the independent modal-space control (IMSC) method, the control laws are designed in the modal space for each mode independently. The minimum-fuel problem reduces to that of a set of independent second-order systems, so that minimum-fuel control is possible. This paper shows how the IMSC method can be used to control a space structure with a minimum amount of fuel. A numerical example is presented.

Shenhar, J.↗
DOE OSTI2024

Enhancing Interlayer Charge Transport of Two-Dimensional Perovskites by Structural Stabilization via Fluorine Substitution

Two-dimensional lead-halide perovskites provide a more robust alternative to three-dimensional perovskites in solar energy and optoelectronic applications due to increased chemical stability afforded by interlayer ligands. At the same time, the ligands create barriers for interlayer charge transport, reducing device performance. Using a recently developed ab initio simulation methodology, we demonstrate that ligand fluorination can enhance both hole and electron mobility by 1–2 orders of magnitude. The simulations show that the enhancement arises primarily from improved structural order and reduced thermal atomic fluctuations in the system rather than increased interlayer electronic coupling. Arising from stronger hydrogen bonding and dipolar interactions, the higher structural stability decreases the reorganization energy that enters the Marcus formula and increases the charge transfer rate. The detailed atomistic insights into the electron and hole transfer in layered perovskites indicate that the use of interlayer ligands that make the overall structure more robust is beneficial simultaneously for chemical stability and charge transport, providing an important guideline for the design of new, efficient materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗