Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “structured model reduction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

A simplified modal plotting technique for the representation of complex structural models

A plotting method has been developed that has proven to be useful in rapidly defining the mode shapes of a complex spacecraft. The reduction of the complex model to a simple stick plot is accomplished by augmenting the existing NASTRAN plot package with constrained plot elements. Both the existing NASTRAN modal plot package and the stick plots of a representative mode are presented for comparison. The NASTRAN plot package provides the capability of generating modal deformations (mode shapes) resulting from real eigenvalue analysis. These modal deformations of the structural model may be displayed in the deformed shape either alone or superimposed on the undeformed shape. Another available method of displaying the modal deformations is by means of displacement vectors at the grid points

Hanlein, S. L.↗
DOE OSTI2013

New Structural-Dynamics Module for Offshore Multimember Substructures within the Wind Turbine Computer-Aided Engineering Tool FAST: Preprint

FAST, developed by the National Renewable Energy Laboratory (NREL), is a computer-aided engineering (CAE) tool for aero-hydro-servo-elastic analysis of land-based and offshore wind turbines. This paper discusses recent upgrades made to FAST to enable loads simulations of offshore wind turbines with fixed-bottom, multimember support structures (e.g., jackets and tripods, which are commonly used in transitional-depth waters). The main theory and strategies for the implementation of the multimember substructure dynamics module (SubDyn) within the new FAST modularization framework are introduced. SubDyn relies on two main engineering schematizations: 1) a linear frame finite-element beam (LFEB) model and 2) a dynamics system reduction via Craig-Bampton's method. A jacket support structure and an offshore system consisting of a turbine atop a jacket substructure were simulated to test the SubDyn module and to preliminarily assess results against results from a commercial finite-element code.

17 WIND ENERGY↗
DOE OSTI2014

Higher-order Hamiltonian fluid reduction of Vlasov equation

From the Hamiltonian structure of the Vlasov equation, we build a Hamiltonian model for the first three moments of the Vlasov distribution function, namely, the density, the momentum density and the specific internal energy. We derive the Poisson bracket of this model from the Poisson bracket of the Vlasov equation, and we discuss the associated Casimir invariants.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Characteristic operator functions for quantum input-plant-output models and coherent control

We introduce the characteristic operator as the generalization of the usual concept of a transfer function of linear input-plant-output systems to arbitrary quantum nonlinear Markovian input-output models. This is intended as a tool in the characterization of quantum feedback control systems that fits in with the general theory of networks. The definition exploits the linearity of noise differentials in both the plant Heisenberg equations of motion and the differential form of the input-output relations. Mathematically, the characteristic operator is a matrix of dimension equal to the number of outputs times the number of inputs (which must coincide), but with entries that are operators of the plant system. In this sense, the characteristic operator retains details of the effective plant dynamical structure and is an essentially quantum object. We illustrate the relevance to model reduction and simplification definition by showing that the convergence of the characteristic operator in adiabatic elimination limit models requires the same conditions and assumptions appearing in the work on limit quantum stochastic differential theorems of Bouten and Silberfarb [Commun. Math. Phys. 283, 491-505 (2008)]. This approach also shows in a natural way that the limit coefficients of the quantum stochastic differential equations in adiabatic elimination problems arise algebraically as Schur complements and amounts to a model reduction where the fast degrees of freedom are decoupled from the slow ones and eliminated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

clustering, k-means, power grid, graphs↗
NASA NTRS1979

Evaluation of feasibility of prestressed concrete for use in wind turbine blades

A preliminary evaluation of the feasibility of the use of prestressed concrete as a material for low cost blades for wind turbines was conducted. A baseline blade design was achieved for an experimental wind turbine that met aerodynamic and structural requirements. Significant cost reductions were indicated for volume production. Casting of a model blade section showed no fabrication problems. Coupled dynamic analysis revealed that adverse rotor tower interactions can be significant with heavy rotor blades.

Leiblein, S.↗
NASA NTRS1989

Hierarchical Poly Tree computer architectures defined by computational multidisciplinary mechanics

This paper will develop an alternative computer architecture called the Poly Tree. Based on the requirements of computational mechanics and the concept of hierarchical substructuring, the paper will explore the development of problem-dependent parallel networks of processors which will enable significant, often superlinear, speed enhancements; provide a logical/efficient framework for linear/nonlinear and transient structural mechanics problems; and provide a logical framework from which to apply model reduction procedures. In addition, the paper will explore optimal processor arrangements which define the overall system granularity. Consideration will also be given to system I/O requirements.

Padovan, Joe↗
NASA NTRS1992

Application of piezoelectric devices to vibration suppression - From modeling and controller designs to implementation

Embedded piezoelectric devices may be ideally suited for vibration control of space structures, which lack an inertial ground. When subjected to an input voltage, an embedded piezoelectric actuator changes its dimensions, which in turn generates a pair of forces exerted on adjacent structural members. From the direct piezoelectric effect, an embedded piezoelectric transducer generates an electric charge proportional to the structural dynamic response. In this paper, the implementation, testing and modeling of an active truss structure consisting of piezoelectric sensors and actuators are described. Linear quadratic Gaussian (LQG), second-order, and direct rate feedback control schemes are designed to suppress the vibrations of the active structure. Simulation and test results are presented. It is shown that special model reduction considerations are required to achieve good correlation between test and analysis.

Won, Chin C.↗
NASA NTRS1989

Issues in CSI analysis for large scale systems

Future spacecraft such as the International Space Station result in flexible models with hundreds, or perhaps thousands of modes in a frequency range where the potential for control/structure interaction exists. This provides the analyst with a formidable model reduction problem at both the component and the system level. Approaches to normal modes as a structural representation, applicability of alternate structural representations and algorithms for selecting important modal degrees of freedom at both the component and the system level are discussed. Practical implementation of these techniques on a large scale model of the Space Station are presented.

Blelloch, Paul↗
DOE OSTI2016

Shock structures in a strongly coupled self-gravitating opposite-polarity dust plasma

A strongly coupled, self-gravitating, opposite-polarity dust plasma (containing strongly coupled inertial positive and negative dust fluids, and inertialess weakly coupled ions) is considered. The generalized hydrodynamic model and the reductive perturbation method are employed to examine the possibility for the formation of the dust-acoustic (DA) shock structures in such an opposite-polarity dust plasma. It has been shown that the strong correlation among charged dust is a source of dissipation and is responsible for the formation of the DA shock structures in such the opposite-polarity dust plasma medium. The parametric regimes for the existence of the DA shock structures (associated with electrostatic and gravitational potentials) and their basic properties (viz., polarity, amplitude, width, and speed) are found to be significantly modified by the combined effects of positively charged dust component, self-gravitational field, and strong correlation among charged dust. The implications of our results in different space plasma environments and laboratory plasma devices are briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Methodology Development for Passive Component Reliability Modeling in a Multi-Physics Simulation Environment

Reduction in safety margin can be expected as passive structures and components undergo degradation with time. Limitations in the traditional probabilistic risk assessment (PRA) methodology constrain its value as an effective tool to address the impact of aging effects on risk and for quantifying the impact of aging management strategies in maintaining safety margins. A methodology has been developed to address multiple aging mechanisms involving large numbers of components (with possibly statistically dependent failures) within the PRA framework in a computationally feasible manner when the sequencing of events is conditioned on the physical conditions predicted in a simulation environment, such as the New Generation System Code (NGSC) concept. Both epistemic and aleatory uncertainties can be accounted for within the same phenomenological framework and maintenance can be accounted for in a coherent fashion. The framework accommodates the prospective impacts of various intervention strategies such as testing, maintenance, and refurbishment. The methodology is illustrated with several examples.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics↗
DOE OSTI2023

Polyethylene Blends for Improved Oxygen Barrier: Processing-Dependent Microstructure and Gas Permeability

Here this work demonstrates a greater than expected enhancement of oxygen barrier properties in linear low-density polyethylene (LLDPE)-based materials by blending LLDPE with high-density polyethylene (HDPE). The films made by melt pressing the LLDPE/HDPE blends had a greater reduction in oxygen permeability coefficients (PO 2 ) than predicted using common permeability reduction models, i.e., the harmonic average model and zero-permeability nanofiller model. The reduction of PO 2 was attributed to the presence of spherulite crystal structures, as revealed by atomic force microscopy combined with infrared spectroscopy (AFM-IR). The LLDPE matrix exhibited significant spherulite formation even at a relatively low addition of HDPEs, which likely formed tortuous pathways for diffusing oxygen molecules. Transport results from melt-pressed films contrast with the results from films with similar compositions prepared by film blowing, which did not show barrier enhancement beyond expectation. AFM-IR revealed that the blown films lacked spherulite crystals likely due to stretching in the machine direction followed by rapid cooling. These findings demonstrate the role of processing in controlling microstructures and thus the oxygen barrier performance. This work offers the possibility of achieving easily recyclable LLDPE-based packaging materials by simple blending of polyethylenes with different crystalline content.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Gray-Box Modeling for Distribution Systems With Inverter-Based Resources: Integrating Physics-Based and Data-Driven Approaches

Here, in this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, we utilize partial physical knowledge of the system, including the inverters’ structures and control diagrams, as well as the equivalent network model simplified through Kron reduction. The white-box model containing unknown parameters is then constructed with mathematical equations and an optimization-based method is subsequently employed to identify these unknown parameters within the white-box model. Next, the graybox modeling framework is then constructed by embedding the output variables of the white-box model into the input vector of a black-box model (represented using a neural network). Finally, the black-box section is trained using the collected input-output datasets and the gray-box model is then obtained. Furthermore, case studies demonstrate that our gray-box modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

42 ENGINEERING↗
NASA NTRS1984

Fitting aerodynamic forces in the Laplace domain: An application of a nonlinear nongradient technique to multilevel constrained optimization

A technique which employs both linear and nonlinear methods in a multilevel optimization structure to best approximate generalized unsteady aerodynamic forces for arbitrary motion is described. Optimum selection of free parameters is made in a rational function approximation of the aerodynamic forces in the Laplace domain such that a best fit is obtained, in a least squares sense, to tabular data for purely oscillatory motion. The multilevel structure and the corresponding formulation of the objective models are presented which separate the reduction of the fit error into linear and nonlinear problems, thus enabling the use of linear methods where practical. Certain equality and inequality constraints that may be imposed are identified; a brief description of the nongradient, nonlinear optimizer which is used is given; and results which illustrate application of the method are presented.

Tiffany, S. H.↗
NASA NTRS1988

Recent advances in control of nonlinear and distributed parameter systems, robust control, and aerospace control applications; Proceedings of the Symposium, ASME Winter Annual Meeting, Chicago, IL, Nov. 27-Dec. 2, 1988

Papers are presented on the control of distributed parameter systems using the coprime factorization approach, a hierarchy of geometrically exact models of rotating beams, and the temperature stability of a flux modulated radiant slab. Also considered are a network representation for robots, recovery from controller bounding, and the design of controllers for robust tracking and model following. Other topics include an active control law synthesis for flexible aircraft, the low-order control of large aerospsace structures using residual model filters, and a comparison of component cost methods for component model reduction.

Bentsman, Joseph↗