Characterizing the Role of Non‐Linear Interactions in the Transition to Submesoscale Dynamics at a Dense Filament
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Mara Freilich↗
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Results for “Non linear dynamics”
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Fast Auroral Snapshot performance using a multi-body dynamic simulation
This paper examines the complex dynamic interaction between two 2.6 m long stacer booms, four 30 m long flexible wire booms and the attitude control system of the Fast Auroral SnapshoT (FAST) spacecraft. The FAST vehicle will nominally operate as a negative orbit spinner, positioned in a 83 deg inclination, 350 x 4200 km orbit. For this study, a three-axis, non-linear, seven body dynamic simulation is developed using the TREETOPS software package. The significance of this approach is the ability to model each component of the FAST spacecraft as an individual member and connect them together in order to better understand the dynamic coupling between structures and the control system. Both the wire and stacer booms are modeled as separate bodies attached to a rigid central body. The wire booms are oriented perpendicular to the spin axis at right angles relative to each other, whereas the stacer booms are aligned with the spin axis. The analysis consists of a comparison between the simulated in-plane and out-of-plane boom motions with theoretically derived frequencies, and an examination of the dynamic coupling between the control system and boom oscillations. Results show that boom oscillations of up to 0.36 deg are acceptable in order to meet the performance requirements. The dynamic motion is well behaved when the precession coil is operating, however, activation of the spin coil produces an erratic trend in the spin rate which approaches the spin rate requirement.
Zimbelman, Darrell↗
A high accuracy/resolution spectral element/Fourier–Galerkin method for the simulation of shoaling non-linear internal waves and turbulence in long domains with variable bathymetry
A high-order hybrid continuous-Galerkin numerical method, designed for the simulation of non-linear, non -hydrostatic internal waves and turbulence in long computational domains with complex bathymetry, is presented. The spatial discretization in the non-periodic wave-propagating directions, utilizes the nodal spectral element method. Such a high-order element-based discretization allows the highly accurate representation of complex domain geometry along with the flexibility of concentrating resolution in areas of interest. Under the assumption of the normal-to-isobath propagation of non-linear internal waves, a third periodic direction is incorporated via a Fourier-Galerkin discretization. The distinct non-hydrostatic nature of non-linear internal waves and, any instabilities and turbulence therein, necessitates the numerically challenging solution of the pressure Poisson problem. A defining feature of this work is the application of a domain decomposition approach, combined with block-Jacobi/deflation-based preconditioning to the pressure Poisson problem. Such a combined approach is particularly suitable for the long high aspect-ratio complex domains of interest and enables the efficient high-accuracy reproduction of the non-hydrostatic dynamics of non-linear internal waves. Implementation details are also described in the context of the stability of the solver and its parallelization strategy. A series of benchmarks of increasing complexity demonstrate the robustness of the flow solver. The benchmarks culminate with the three-dimensional simulation of a convectively breaking mode-one non-linear internal wave over a realistic South-China-Sea bathymetric transect and background current/stratification profiles.
Deflation↗
Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges
Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short- and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This Perspective discusses select examples of these approaches and provides an outlook on the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.
36 MATERIALS SCIENCE↗
Cognitive Systems Modeling and Analysis of Command and Control Systems
Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.
Norlander, Arne↗
Shallow Soil Response to a Buried Chemical Explosion With Geophones and Distributed Acoustic Sensing
Abstract Shallow sediments can respond non‐linearly to large dynamic strains and undergo a subsequent healing phase as the material gradually recovers following the passing of seismic waves. This study focuses on the physical changes in the subsurface caused by the shaking from a buried chemical explosion detonated in a borehole in Nevada, USA, as a part of the Source Physics Experiment Phase II. The explosion damaged the shallow subsurface and modified the frequency content recorded by 491 geophones and 2240 Distributed Acoustic Sensing (DAS) channels within 2.5 km from surface ground zero. We observe a gradual shift of resonance frequencies in the 10–25 Hz frequency band in the hours following the explosion and develop a method to characterize the related logarithm‐type healing process of the shallow (i.e., upper ∼25 m) subsurface. We find that stronger levels of ground motion increase the relative degree of damage and duration of the subsurface healing; with the spall region exhibiting the largest degree of damage and longest healing recovery time. We observe coherent spatial patterns of damage with the region located to the southeast of the explosion exhibiting more damage than the southwest region. This study demonstrates that both DAS and co‐located geophones capture similar temporal changes associated with the physical processes occurring in the subsurface, with the high‐density sampling of DAS measurements enabling a new capability to monitor the fine‐scale changes of the Earth's shallow subsurface following the detonation of a buried explosion.
Viens, Loïc↗
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↗
Complexity: from Turbulence to Accelerators to Poetry
Though it may seem intuitive at times, the term 'complexity' is multifaceted, often encompassing various interacting aspects and components that follow local rules. This interaction leads to non-linearity, randomness, collective dynamics, hierarchy, and emergence. The phenomenological complexity found in large accelerators has recently been addressed by the Snowmass’21 Future Colliders Implementation Task Force (ITF). In this presentation, we will provide a concise overview of the mathematical constructs employed to assess hierarchical complexity, summarize the key findings from the ITF analysis, and offer a few examples demonstrating how this approach can be applied to analyze certain literaryclassics.
43 PARTICLE ACCELERATORS↗
A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory
The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.
Manning, Robert M.↗
Fuzzy logic controllers: A knowledge-based system perspective
Over the last few years we have seen an increasing number of applications of Fuzzy Logic Controllers. These applications range from the development of auto-focus cameras, to the control of subway trains, cranes, automobile subsystems (automatic transmissions), domestic appliances, and various consumer electronic products. In summary, we consider a Fuzzy Logic Controller to be a high level language with its local semantics, interpreter, and compiler, which enables us to quickly synthesize non-linear controllers for dynamic systems.
Bonissone, Piero P.↗
A New Forced Oscillation Capability for the Transonic Dynamics Tunnel
A new forced oscillation system has been installed and tested at NASA Langley Research Center's Transonic Dynamics Tunnel (TDT). The system is known as the Oscillating Turntable (OTT) and has been designed for the purpose of oscillating, large semispan models in pitch at frequencies up to 40 Hz to acquire high-quality unsteady pressure and loads data. Precisely controlled motions of a wind-tunnel model on the OTT can yield unsteady aerodynamic phenomena associated with flutter, limit cycle oscillations, shock dynamics, and non-linear aerodynamic effects on many vehicle configurations. This paper will discuss general design and components of the OTT and will present test data from performance testing and from research tests on two rigid semispan wind-tunnel models. The research tests were designed to challenge the OTT over a wide range of operating conditions while acquiring unsteady pressure data on a small rectangular supercritical wing and a large supersonic transport wing. These results will be presented to illustrate the performance capabilities, consistency of oscillations, and usefulness of the OTT as a research tool.
Piatak, David J.↗
Precision Measurement of Complete Black Hole Binary Inspiral-Merger-Ringdown Signals with LISA
Until recently, only the inspiral and ringdown phases of black hole binary (131-113) coalescences had been modeled. The merger signals, which were expected to be the most luminous portion of the total signal, were unavailable due to the technical difficulty of calculating the behavior of a BHB in this highly dynamical and non-linear regime. Advancements in the field of numerical relativity make it possible to include the merger segment of 131113 coalescence in the search for and characterization of gravitational wave signals. The implications for LISA include an increase in the event rate due to the increase in achievable signal-to-noise ratio, as well as potentially improved accuracy regarding the extraction of the source parameters. We investigate the degree to which mergers improve parameter estimation, by studying the impact of including mergers on achievable parameter accuracy over a significant range of masses and mass ratios for nonspinning systems, and its impact on LISA science.
McWilliams, Sean T.↗
Turbulent mixing in supercritical jets: effect of compressibility factor and inflow condition
Fuel injection and turbulent mixing at supercritical pressures determines ignition and combustion in numerous engineering applications. Flow evolution under such conditions is characterized by strong non-linear coupling between dynamics, transport coefficients, and thermodynamics. Experimental studies observe that the jets injected at supercritical pressures exhibit significantly different dynamics from the jets at subcritical conditions, owing to the lack of distinct liquid and gas phases in supercritical state. Thus, the averaged flow quantities such as the potential core length, jet spatial growth rate and velocity decay profiles differ in the two conditions, resulting in different mixed-fluid distributions. In this study, turbulent jet direct numerical simulations (DNS) are performed to examine the variations in flow statistics between injection of Nitrogen (N₂) in Nitrogen (N₂) at both subcritical (perfect-gas) and supercritical conditions. In all cases, isothermal round jets at Reynolds number (Re_{D}), based on jet diameter (D) and jet orifice velocity (U₀), of 5000 are considered. For mixing analyses, a passive scalar transported with the flow is examined.
Sharan, Nek↗
Quantum Non-Equilibrium Dynamics Prediction of Electronic Transport Coefficients in Non-Linear Regimes
The goal of this work was to develop unique LLNL capabilities for the computational prediction of electrical, optical and thermal transport properties from quantum simulations. Using a recently developed theory of microscopic quantum transport, we were able to model compressed metallic hydrogen and it’s non-linear and out-of-equilibrium contributions in electrical and thermal transport. This theory was implemented in the open-source, real-space time-dependent density functional theory code Octopus. This model is general and widely applicable to high energy density systems that are important to LLNL and NNSA mission areas.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Aerodynamic control of NASP-type vehicles through vortex manipulation, volume 4
Forebody Vortex Control (FVC) is an emerging technology that has received widespread and concentrated attention by many researchers for application on fighter aircraft to enhance aerodynamic controllability at high angles of attack. This research explores potential application of FVC to a NASP-type configuration. The configuration investigated is characterized by a slender, circular cross-section forebody and a 78 deg swept delta wing. A man-in-the-loop, six-degress-of-freedom, high-fidelity simulation was developed that demonstrates the implementation and advantages of pneumatic forebody vortex control. Static wind tunnel tests were used as the basis for the aerodynamic characteristics modeled in the simulation. Dynamic free-to-roll wind tunnel tests were analyzed and the wing rock motion investigated. A non-linear model of the dynamic effects of the bare airframe and the forebody vortex control system were developed that closely represented the observed behavior. Multiple state-of-the-art digital flight control systems were developed that included different utilizations of pneumatic vortex control. These were evaluated through manned simulation. Design parameters for a pneumatic forebody vortex control system were based on data collected regarding the use of blowing and the mass flow required during realistic flight maneuvers.
Smith, Brooke C.↗
Global System Reduction Order Modeling for Localized Feature Inclusion
The development of reduced-order models remains an active research area, despite advances in computational resources. Here we develop a novel order-reduction approach that is designed to incorporate isolated regions that contain, for example, nonlinearitites or accumulating damage. The approach is designed to use global modes of the overall system response, which are then naturally coupled to the response in the isolated region of interest. Two examples are provided to demonstrate both the accuracy and the computational efficiency of the proposed approach. The performance of this approach is compared to the exact response corresponding to a finite element simulation for the chosen problems. In addition, the accuracy and computational efficiency are shown relative to a standard Galerkin reduction based on the linear normal modes. It is found that the proposed reduction offer computational efficiency comparable to a Galerkin reduction, but more accurately represents the response of the system when both are compared to the finite element simulation.
42 ENGINEERING↗
Output Tracking for Systems with Non-Hyperbolic and Near Non-Hyperbolic Internal Dynamics: Helicopter Hover Control
A technique to achieve output tracking for nonminimum phase linear systems with non-hyperbolic and near non-hyperbolic internal dynamics is presented. This approach integrates stable inversion techniques, that achieve exact-tracking, with approximation techniques, that modify the internal dynamics to achieve desirable performance. Such modification of the internal dynamics is used (1) to remove non-hyperbolicity which an obstruction to applying stable inversion techniques and (2) to reduce large pre-actuation time needed to apply stable inversion for near non-hyperbolic cases. The method is applied to an example helicopter hover control problem with near non-hyperbolic internal dynamic for illustrating the trade-off between exact tracking and reduction of pre-actuation time.
Devasia, Santosh↗
Archetypes for Organisational Safety
We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.
Marais, Karen↗