Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Dynamical Systems”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

System Impact Study of the Eastern Grid of Sumba Island, Indonesia: Steady-State and Dynamic System Modeling for the Integration of One and Two 850-kW Wind Turbine Generators

The goal of this project was to study the impact of integrating one and two 850-kW wind turbine generators into the eastern power system network of Sumba Island, Indonesia. A model was created for the 20-kV distribution network as it existed in the first quarter of 2015 with a peak load of 5.682 MW. Detailed data were collected for each element of the network. Load flow, short-circuit, and transient analyses were performed using DIgSILENT PowerFactory 15.2.1.

17 WIND ENERGY↗
NASA NTRS1993

Mass properties measurement system dynamics

The MPMS mechanism possess two revolute degrees-of-freedom and allows the user to measure the mass, center of gravity, and the inertia tensor of an unknown mass. The dynamics of the Mass Properties Measurement System (MPMS) from the Lagrangian approach to illustrate the dependency of the motion on the unknown parameters.

Doty, Keith L.↗
NASA NTRS2003

Earth System Dynamics: The Determination and Interpretation of the Global Angular Momentum Budget using the Earth Observing System

The objective of this investigation has been to examine the mass and momentum exchange between the atmosphere, oceans, solid Earth, hydrosphere, and cryosphere. The investigation has focused on changes in the Earth's gravity field, its rotation rate, atmospheric and oceanic circulation, global sea level change, ice sheet change, and global ground water circulation observed by contemporary sensors and models. The primary component of the mass exchange is water. The geodetic observables provided by these satellite sensors are used to study the transport of water mass in the hydrological cycle from one component of the Earth to another, and they are also used to evaluate the accuracy of models. As such, the investigation is concerned with the overall global water cycle. This report provides a description of scientific, educational and programmatic activities conducted during the period July 1, 1999 through June 30,2000. Research has continued into measurements of time-varying gravity and its relationship to Earth rotation. Variability of angular momentum and the related excitation of polar motion and Earth rotation have been examined for the atmosphere and oceans at time-scales of weeks to several years. To assess the performance of hydrologic models, we have compared geodetic signals derived from them with those observed by satellites. One key component is the interannual mass variability of the oceans obtained by direct observations from altimetry after removing steric signals. Further studies have been conducted on the steric model to quantify its accuracy at global and basin-scales. The results suggest a significant loss of water mass from the Oceans to the land on time-scales longer than 1-year. These signals are not reproduced in any of the models, which have poorly determined interannual fresh water fluxes. Output from a coupled atmosphere-ocean model testing long-term climate change hypotheses has been compared to simulated errors from the Gravity Recovery and Climate Experiment (GRACE) mission. Results indicate that GRACE will be able to observe seasonal signals at half-wavelengths ranging from 1000 to 10000 km, and may be able to observe secular trends at half- wavelengths of greater than 2000-3000 km for soil moisture and snow depth if they are as large as some of the climate experiments predict.

Source record↗
NASA NTRS1993

Synthesis of Optimal Nonlinear Feedback Laws for Dynamic Systems Using Neural Networks

Open-loop solutions of dynamical optimization problems can be numerically computed usingexisting software packages. The computed time histories of the state and control variables, formultiple sets of end conditions can then be used to train a neural network to 'recognize' the optimal,nonlinear feedback relation between the states and controls of the system. The 'learned' network canthen be used to output an approximate optimal control given a full set (or a partial set) of measuredsystem states. With simple neural networks, we have successfully demonstrated the efficacy of theproposed approach using a minimum-time orbit injection problem. The usefulness and limitations ofthis novel approach on real-life optimal guidance and control problems, with many state and control variables as well as path inequality constraints, remain to be seen.

Orbit injection problem↗
DOE OSTI2014

Potential and flux field landscape theory. II. Non-equilibrium thermodynamics of spatially inhomogeneous stochastic dynamical systems

We have established a general non-equilibrium thermodynamic formalism consistently applicable to both spatially homogeneous and, more importantly, spatially inhomogeneous systems, governed by the Langevin and Fokker-Planck stochastic dynamics with multiple state transition mechanisms, using the potential-flux landscape framework as a bridge connecting stochastic dynamics with non-equilibrium thermodynamics. A set of non-equilibrium thermodynamic equations, quantifying the relations of the non-equilibrium entropy, entropy flow, entropy production, and other thermodynamic quantities, together with their specific expressions, is constructed from a set of dynamical decomposition equations associated with the potential-flux landscape framework. The flux velocity plays a pivotal role on both the dynamic and thermodynamic levels. On the dynamic level, it represents a dynamic force breaking detailed balance, entailing the dynamical decomposition equations. On the thermodynamic level, it represents a thermodynamic force generating entropy production, manifested in the non-equilibrium thermodynamic equations. The Ornstein-Uhlenbeck process and more specific examples, the spatial stochastic neuronal model, in particular, are studied to test and illustrate the general theory. This theoretical framework is particularly suitable to study the non-equilibrium (thermo)dynamics of spatially inhomogeneous systems abundant in nature. This paper is the second of a series.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents

The increasing complexity of power system has made it difficult to simulate large-scale power system in detail. Therefore, to improve computational efficiency, model reduction techniques has been applied to reduce the external area and focus on the dynamics of the internal area. This paper proposes a measurement-based model reduction method which reduces the external system by replacing external system with ARX equivalents. The modeled transfer function parameters are obtained using system identification approach. Case studies on the NPCC system and EI system are carried out. Results show that the proposed reduction method can effectively retain the dynamic behavior of the study area while mitigating computation burden.

Jiang, Zhihao↗
DOE OSTI2020

STEPS: A Portable Numerical Simulation Toolkit for Electrical Power System Dynamic Studies

Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. In this paper we introduce an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.

42 ENGINEERING↗
DOE OSTI2026

Empirical Comparison of Machine Learning Approaches for Black-Box Modeling of Power Conversion System Dynamics

Inverter-based resources are key components in modern power systems, but accurately modeling their complex behavior can be challenging. Standard, generic converter models often oversimplify inverter dynamics, leading to significant errors in predicting performance. In this work, we compare several data-driven machine learning (ML) approaches for inverter modeling, performing experiments on power conversion systems, systematically varying input conditions, and recording the resulting voltages and currents. The ML models were then trained on this measured data to capture the inverter's dynamic response and to predict the inverter's output current. A performance comparison between the four ML models under study is conducted, laying the foundation for future work on hardware implementation for real-time inference.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Computational assessment of smooth and rough parameter dependence of statistics in chaotic dynamical systems

An assumption of smooth response to small parameter changes, of statistics or long-time averages of a chaotic system, is generally made in the field of sensitivity analysis, and the parametric derivatives of statistical quantities are critically used in science and engineering. In this paper, we propose a numerical procedure to assess the differentiability of statistics with respect to parameters in chaotic systems. Here, we numerically show that the existence of the derivative depends on the Lebesgue integrability of a certain density gradient function, which we define as the derivative of logarithmic SRB density along the unstable manifold. We develop a recursive formula for the density gradient that can be efficiently computed along trajectories, and demonstrate its use in determining the differentiability of statistics. Our numerical procedure is illustrated on low-dimensional chaotic systems whose statistics exhibit both smooth and rough regions in parameter space.

42 ENGINEERING↗
DOE OSTI2019

An anomaly detection framework for dynamic systems using a Bayesian hierarchical framework

Complex systems are susceptible to many types of anomalies, faults, and abnormal behavior caused by a variety of off-nominal conditions that may ultimately result in major failures or catastrophic events. Early and accurate detection of these anomalies using system inputs and outputs collected from sensors and smart devices has become a challenging problem and an active area of research in many application domains. In this article, we present a new Bayesian hierarchical framework that is able to model the relationship between system inputs (sensor measurements) and outputs (response variables) without imposing strong distributional/parametric assumptions while using only a subset of training samples and sensor attributes. Then, an optimal cost-sensitive anomaly detection framework is proposed to determine whether a sample is an anomalous one taking into consideration the trade-off between misclassification errors and detection rates. The model can be used for both supervised and unsupervised settings depending on the availability of data regarding the behavior of the system under anomaly conditions. The unsupervised model is particularly useful when it is prohibitive to identify in advance the anomalies that a system may present and where no data are available regarding the behavior of the system under anomaly conditions. A Bayesian hierarchical setting is used to structure the proposed framework and help with accommodating uncertainty, imposing interpretability, and controlling the sparsity and complexity of the proposed anomaly detection framework. A Markov chain Monte Carlo algorithm is also developed for model training using past data. Furthermore, the numerical experiments conducted using a simulated data set and a wind turbine data set demonstrate the successful application of the proposed work for system response modeling and anomaly detection.

17 WIND ENERGY↗
DOE OSTI2017

Transcendental First Integrals of Dynamical Systems on the Tangent Bundle to the Sphere

In this paper, we examine the existence of transcendental first integrals for some classes of systems with symmetries. We obtain sufficient conditions of existence of first integrals of second-order nonautonomous homogeneous systems that are transcendental functions (in the sense of the theory of elementary functions and in the sense of complex analysis) expressed as finite combinations of elementary functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Dynamical system analysis of Einstein–Skyrme model in a Kantowski–Sachs spacetime

The present work deals with anisotropic (but zero heat flux) Skyrme fluid with a constant radial profile in locally rotational Kantowski–Sachs spacetime in the background of Einstein gravity. By suitably change of variables the field equations are transformed to an autonomous system. To examine the stability of the system critical points are determined. For hyperbolic critical points the analysis of the system is done using Hartman–Grobman theorem, while center manifold theory is used to analyze non-hyperbolic critical points. Also stability at infinity is analyzed to visualize the global evolution of the Universe. As a result the 3D-phase space is identified with the Poincaré 3-sphere embedded in R{sup 4}. It is found that the parameters in the autonomous system play a crucial role for phase transition of the Universe. Finally possible bifurcation scenarios are discussed to identify the point of phase transition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2016

Propulsion System Dynamic Modeling of the NASA Supersonic Concept Vehicle for AeroPropulsoServoElasticity

A summary of the propulsion system modeling under NASA's High Speed Project (HSP) AeroPropulsoServoElasticity (APSE) task is provided with a focus on the propulsion system for the low-boom supersonic configuration developed by Lockheed Martin and referred to as the N+2 configuration. This summary includes details on the effort to date to develop computational models for the various propulsion system components. The objective of this paper is to summarize the model development effort in this task, while providing more detail in the modeling areas that have not been previously published. The purpose of the propulsion system modeling and the overall APSE effort is to develop an integrated dynamic vehicle model to conduct appropriate unsteady analysis of supersonic vehicle performance. This integrated APSE system model concept includes the propulsion system model, and the vehicle structural aerodynamics model. The development to date of such a preliminary integrated model will also be summarized in this report

Propulsion Dynamics↗
NASA NTRS1985

Rotor/bearing system dynamic stiffness measurements

Sweep perturbation testing as used in Modal Analysis when applied to a rotating machine has to take into consideration the machine dynamic state of equilibrium at its operational rotative speed. This stands in contrasts to a static equilibrium of nonrotating structures. The rotational energy has a significant influence on rotor dynamic characteristics. The best perturbing input for rotating machines is a forward or reverse rotating, circular force applied directly to the shaft. Determination of Dynamic Stiffness Characteristics of the rotor bearing system by nonsynchronous perturbation of a symmetric rotating shaft supported in one relatively rigid and one oil lubricated bearing.

Muszynska, A.↗