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At least 1,513 records · Page 84

Role of environmental correlations in the non-Markovian dynamics of a spin system

We study the dynamics of a chain of interacting quantum particles affected by an individual or collective environment(s), focusing on the role played by the environmental quantum correlations over the evolution of the chain. The presence of entanglement in the state of the environment magnifies the non-Markovian nature of the chain's dynamics, giving rise to structures in figures of merit such as spin entanglement and purity that are not observed under a separable environmental state. Our analysis can be relevant to problems tackling the open-system dynamics of biological complexes of strong current interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Insights on the continuous representations of piecewise-smooth nonlinear systems: limits of applicability and effectiveness

Dynamical systems subject to intermittent contact are often modeled with piecewise-smooth contact forces. However, the discontinuous nature of the contact can cause inaccuracies in numerical results or failure in numerical solvers. Representing the piecewise contact force with a continuous and smooth function can mitigate these problems, but not all continuous representations may be appropriate for this use. Here, five representations used by previous researchers (polynomial, rational polynomial, hyperbolic tangent, arctangent, and logarithm-arctangent functions) are studied to determine which ones most accurately capture nonlinear behaviors including super- and subharmonic resonances, multiple solutions, and chaos. The test case is a single-DOF forced Duffing oscillator with freeplay nonlinearity, solved using direct time integration. This work intends to expand on past studies by determining the limits of applicability for each representation and what numerical problems may occur.

42 ENGINEERING↗

Error behavior of multistep methods applied to unstable differential systems

The problem of modeling a dynamic system described by a system of ordinary differential equations which has unstable components for limited periods of time is discussed. It is shown that the global error in a multistep numerical method is the solution to a difference equation initial value problem, and the approximate solution is given for several popular multistep integration formulas. Inspection of the solution leads to the formulation of four criteria for integrators appropriate to unstable problems. A sample problem is solved numerically using three popular formulas and two different stepsizes to illustrate the appropriateness of the criteria.

Brown, R. L.↗

Error behaviour of multistep methods applied to unstable differential systems

The problem of modelling a dynamic system described by a system of ordinary differential equations which has unstable components for limited periods of time is discussed. It is shown that the global error in a multistep numerical method is the solution to a difference equation initial value problem, and the approximate solution is given for several popular multistep integration formulae. Inspection of the solution leads to the formulation of four criteria for integrators appropriate to unstable problems. A sample problem is solved numerically using three popular formulae and two different stepsizes to illustrate the appropriateness of the criteria.

Brown, R. L.↗

Backward differentiation approximations of nonlinear differential/algebraic systems

Finite-difference approximations of dynamical systems modeled by nonlinear, semiexplicit, differential/algebraic equations are analyzed. Convergence for the backward differentiation method is proved for index two and index three problems when the numerical initial values obey certain constraints. The appropriate asymptotic convergence rates and the leading error terms are determined.

Brenan, Kathryn E.↗

Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

Balas, Mark J.↗

Quantitative comparison of adaptive sampling methods for protein dynamics

Adaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. Here, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a priori knowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Bioeconomy Growth through the Public Release of the Biomass Scenario Model

The Biomass Scenario Model (BSM) is an important tool for exploring vibrant future bioeconomy scenarios that leverage domestic resources. Developed by NREL and BETO, this model of the domestic biofuels supply chain has been used to explore success strategies for BETO's activities towards bioeconomy growth. The BSM offers a robust test bed for detailed exploration of effects of BETO activities within the complex context of resource availability; physical, technological, and economic constraints; behavior; and policy. The public release of the model in 2017 will allow broad engagement with the theme of the conference as model users can analyze bioeconomy growth, domestic biomass resource use, and associated effects. The BSM is a carefully validated, state-of-the-art, dynamic model of the biomass to biofuels supply chain. Using a system dynamics simulation modeling approach, the model tracks long-term deployment of biofuels given technology development and investment, considering land availability, the competing oil market, consumer demand, and government policies over time. Sample outputs include biofuels production, feedstock use, capital investment, incentives, and costs of feedstocks and fuels. BSM scenarios reveal technological, economic, and policy challenges, as well as opportunities for dynamic growth of the bioeconomy with strategic public and private investment at key points in the system. The model logic and results have been reviewed extensively, through collaborative analysis, expert reviews and external publications (https://www.zotero.org/groups/bsm_publications/).

09 BIOMASS FUELS↗

The Problem of Package Guidance with Incomplete Information for a Linear Control System with a Delay

The control-package method is applied to solve the problem of constructing guaranteed positional guidance for a linear control dynamical system with a delay under incomplete information about the initial state. The problem is solved for the case when the initial state is contained in a compact functional set. A solvability criterion and a method for the construction of a guidance program package are proposed. The proposed procedure is applied to a particular linear control system of delayed differential equations.

97 MATHEMATICS AND COMPUTING↗

The dynamics and control of the orbiting spacecraft control laboratory experiment (SCOLE) during station keeping

A mathematical model is developed to predict the dynamics of the proposed orbiting Spacecraft Control Laboratory Experiment during the station keeping phase. The Shuttle as well as the reflector are assumed to be rigid, the mast is flexible and is assumed to undergo elastic displacements very small as compared with its length. The equations of motion are derived using a Newton-Euler formulation. The model includes the effects of gravity, flexibility, and orbital dynamics. The control is assumed to be provided to the system through the Shuttle's three torquers, and through six actuators located by pairs at two points on the mast and at the mass center of the reflector. At each of the locations, an actuator acts parallel to the roll axis while the other one acts parallel to the pitch axis. It is seen that, in the presence of gravity-gradient torques in the system dynamics, the system assumes a new equilibrium position about which the equations must be linearized, primarily due to the offset in the mast attachment point to the reflector. The linear regulator theory is used to derive control laws for the linear model of the SCOLE including the first four flexible modes. Numerical results confirm the robustness of this control strategy for station keeping with maximum control efforts significantly below saturation levels.

Bainum, Peter M.↗

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

A NASTRAN/TREETOPS solution to a flexible, multi-body dynamics and controls problem on a UNIX workstation

Demands for nonlinear time history simulations of large, flexible multibody dynamic systems has created a need for efficient interfaces between finite-element modeling programs and time-history simulations. One such interface, TREEFLX, an interface between NASTRAN and TREETOPS, a nonlinear dynamics and controls time history simulation for multibody structures, is presented and demonstrated via example using the proposed Space Station Mobile Remote Manipulator System (MRMS). The ability to run all three programs (NASTRAN, TREEFLX and TREETOPS), in addition to other programs used for controller design and model reduction (such as DMATLAB and TREESEL, both described), under a UNIX Workstation environment demonstrates the flexibility engineers now have in designing, developing and testing control systems for dynamically complex systems.

Benavente, Javier E.↗

Singularity perturbed zero dynamics of nonlinear systems

Stability properties of zero dynamics are among the crucial input-output properties of both linear and nonlinear systems. Unstable, or 'nonminimum phase', zero dynamics are a major obstacle to input-output linearization and high-gain designs. An analysis of the effects of regular perturbations in system equations on zero dynamics shows that whenever a perturbation decreases the system's relative degree, it manifests itself as a singular perturbation of zero dynamics. Conditions are given under which the zero dynamics evolve in two timescales characteristic of a standard singular perturbation form that allows a separate analysis of slow and fast parts of the zero dynamics.

Isidori, A.↗

Update on ORNL TRANSFORM Tool: Simulating Multi-Module Advanced Reactor with End-to-End I&C

The Small Modular Reactor (SMR) Dynamic System Modeling Tool project is in the fourth year of development. The project is designed to support collaborative modeling and study of various advanced SMR (non-light water cooled reactor) concepts, including the use of multiple coupled reactors at a single site. The focus of this report is the development of a steam generator and drum system model that includes the complex dynamics of typical steam drum systems, the development of instrumentation and controls for the steam generator with drum system model, and the development of multi-reactor module models that reflect the full power reactor innovative small module design concept. The objective of the project is to provide a common simulation environment and baseline modeling resources to facilitate rapid development of dynamic advanced reactor models; ensure consistency among research products within the Instrumentation, Controls, and Human-Machine Interface technical area; and leverage cross-cutting capabilities while minimizing duplication of effort. The combined simulation environment and suite of models are identified as the TRANSFORM tool. The critical elements of this effort include (1) defining a standardized, common simulation environment that can be applied throughout the Advanced Reactors Technology program; (2) developing a library of baseline component modules that can be assembled into full plant models using available geometry, design, and thermal-hydraulic data; (3) defining modeling conventions for interconnecting component models; and (4) establishing user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energetically consistent model reduction for metriplectic systems

The metriplectic formalism is useful for describing complete dynamical systems which conserve energy and produce entropy. This creates challenges for model reduction, as the elimination of high-frequency information will generally not preserve the metriplectic structure which governs long-term stability of the system. Based on proper orthogonal decomposition, a provably convergent metriplectic reduced-order model is formulated which is guaranteed to maintain the algebraic structure necessary for energy conservation and entropy formation. Further, numerical results on benchmark problems show that the proposed method is remarkably stable, leading to improved accuracy over long time scales at a moderate increase in cost over naive methods.

42 ENGINEERING↗

Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks

The paper presents a distributed approach for operating a network of inverter-based energy storage resources embedded in a bulk power system. Departing from their traditional role of steady-state reserves, the storage assets in the network are utilized as frequency-responsive resources shaping system dynamics. The power electronics converter systems interfacing the storage resources are equipped with local controllers designed to respond under transient disturbances. To this end, a safety-constrained distributed control strategy is explored. The paper compares the performance of converter-interfaced grid-forming and grid-following storage networks for fast frequency control and disturbance containment/localization. Sensitivity studies are performed to study the impact of storage size, steady-state dispatch, and controller design on dynamic performance. The findings are presented through case studies with results from the IEEE test systems.

Chatterjee, Kaustav (ORCID:0000000153273860)↗

Scaling laws for dynamical plasma phenomena

A scaling and similarity technique is a useful tool for developing and testing reduced models of complex phenomena, including plasma phenomena. Similarity and scaling arguments will be applied to highly dynamical systems where the plasma is evolving from some initial to some final state, which may differ dramatically from each other in size and plasma parameters. A question then arises whether, in order to better understand the behavior of one such system, is it possible to create another system, possibly much smaller (or larger) than the original one, but whose evolution would accurately replicate that of the original one, from its initial to its final state. This would allow a researcher, by an experimental study of this second system, to make confident predictions about the behavior of the first one (which may be otherwise inaccessible, as is the case of some astrophysical objects, or too expensive and hard to diagnose, as in the case of fusion applications of pulsed plasma systems, or for other reasons). The scaling and similarity techniques for dynamical plasma systems will be presented as a set of case studies of problems from various domains of plasma physics, including collisional and collisionless plasmas. Finally, among the results discussed are similar for MHD systems with an emphasis on high-energy-density laboratory astrophysics, interference between collisionless and collisional phenomena in the context of shock physics, and similarity for liner-imploded plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗