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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 1,099 records · Page 61

Dynamic Positioning System (DPS) Risk Analysis Using Probabilistic Risk Assessment (PRA)

The National Aeronautics and Space Administration (NASA) Safety & Mission Assurance (S&MA) directorate at the Johnson Space Center (JSC) has applied its knowledge and experience with Probabilistic Risk Assessment (PRA) to projects in industries ranging from spacecraft to nuclear power plants. PRA is a comprehensive and structured process for analyzing risk in complex engineered systems and/or processes. The PRA process enables the user to identify potential risk contributors such as, hardware and software failure, human error, and external events. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. This paper provides an overview of the PRA process and demonstrates how this process was applied in estimating the probability that a Mobile Offshore Drilling Unit (MODU) operating in the Gulf of Mexico and equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. The PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.

Thigpen, Eric B.↗

Difference-frequency generation in a dual-wavelength semiconductor disk laser: Model with delayed feedback

We have constructed a mathematical model of an intracavity difference-frequency generator based on a dual-wavelength semiconductor disk laser in the form of a time-delay dynamic system. Steady-state lasing (the equilibrium state of the dynamic system), its stability, and also transient dynamics after switching on the primary optical pump source are investigated. It is shown that the equilibrium state is stable in a wide range of parameters, which is of interest for possible applications of such a generator. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling pilot interaction with automated digital avionics systems: Guidance and control algorithms for contour and nap-of-the-Earth flight

A collection of technical papers are presented that cover modeling pilot interaction with automated digital avionics systems and guidance and control algorithms for contour and nap-of-the-earth flight. The titles of the papers presented are as follows: (1) Automation effects in a multiloop manual control system; (2) A qualitative model of human interaction with complex dynamic systems; (3) Generalized predictive control of dynamic systems; (4) An application of generalized predictive control to rotorcraft terrain-following flight; (5) Self-tuning generalized predictive control applied to terrain-following flight; and (6) Precise flight path control using a predictive algorithm.

Hess, Ronald A.↗

WE-D-17A-01: A Dynamic Collimation System for Spot Scanned Proton Therapy: Conceptual Overview

Purpose: In the absence of a collimation system, the lateral penumbra in pencil beam scanning (PBS) proton therapy delivered at low energies is highly dependent on the spot size. This dependence, coupled with the fact that spot sizes increase with decreasing energy, reduces the benefit of the PBS technique for treating shallow tumors such as those found in the head and neck region. In order to overcome this limitation, a dynamic collimation system (DCS) was developed for sharpening the lateral penumbra of low energy proton therapy dose distributions delivered by PBS. Methods: The proposed DCS consists of two pairs of orthogonal trimmer blades which intercept the edges of the proton beam near the target edge in the beam's eye view. Each trimmer blade is capable of rapid motion in the direction perpendicular to the central beam axis by means of a linear motor, with maximum velocity and acceleration of 2.5 m/s and 19.6 m/s{sup 2}, respectively. Two-dimensional treatment plans were created both with and without the DCS for in-air spot sizes (σ-air) of 3, 5, 7, and 9 mm, representing a wide array of clinically available equipment. Results: In its current configuration, the snout of the DCS has outer dimensions of 22.6 × 22.6 cm{sup 2} and is capable of delivering a minimum treatment field size of 15 × 15 cm{sup 2}. Using off the shelf components, the constructed system would weigh less than 20 kg. The treatment plans created with the DCS yielded a reduction in the mean dose to normal tissue surrounding the target of 26.2–40.6% for spot sizes of 3–9 mm, respectively. Conclusion: The DCS can be integrated with current or future proton therapy equipment and we believe it will serve as a useful tool to further improve the next generation of proton therapy delivery.

60 APPLIED LIFE SCIENCES↗

Conceptual design of a self-deployable, high performance parabolic concentrator for advanced solar-dynamic power systems

A summary is presented of the concentrator conceptual design work performed under a NASA-funded project. The design study centers around two basic efforts: conceptual design of a self-deploying, high-performance parabolic concentrator; and materials selection for a lightweight, shape-stable concentrator. The primary structural material selected for the concentrator is PEEK/carbon fiber composite. The deployment concept utilizes rigid gore-shaped reflective panels. The assembled concentrator takes a circular shape with a void in the center. The deployable solar concentrator concept is applicable to a range of solar dynamic power systems of 25 kWe to more than 75 kWe.

Dehne, Hans Joachim↗

Acceleration levels on board the Space Station and a tethered elevator for micro and variable-gravity applications

This paper investigates the dynamics and acceleration levels of a new tethered system for micro and variable-gravity applications. The system consists of two platforms tethered on opposite sides to the Space Station. A fourth platform, the elevator, is placed in between the Space Station and the upper platform. Variable-g levels on board the elevator are obtained by moving this facility along the upper tether, while micro-g experiments are carried out on board the Space Station. By controlling the length of the lower tether the position of the system CM can be maintained on board the Space Station despite variations of the station's distribution of mass. The paper illustrates the mathematical model, the environmental perturbations and the control techniques which have been adopted for the simulation and control of the system dynamics. Two sets of results from two different simulation runs are shown. The first set shows the system dynamics and the acceleration spectra on board the Space Station and the elevator during station-keeping. The second set of results demonstrates the capability of the elevator to attain a preselected g-level.

Lorenzini, E. C.↗

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Battery Energy Storage Scenario Analyses Using the Lithium-Ion Battery Resource Assessment (LIBRA) Model

Meeting aggressive carbon emission goals will entail widespread deployment of renewable sources of electricity. Because these sources are variable, there is a need to develop scalable energy storage technologies. The U.S. Department of Energy is supporting efforts to increase U.S. manufacturing and recycling capabilities for LIBs and to decrease costs of stationary storage batteries. Many factors influence the domestic manufacturing and cost of stationary storage batteries, including availability of critical raw materials (lithium, cobalt, and nickel), competition from various demand sectors (consumer electronics, vehicles, and battery energy storage), resource recovery (recycling), government policies, and learning in the industry, among other factors. Understanding how these factors interact and identifying synergies and bottlenecks is important for developing effective strategies for the LIB stationary energy storage system. We developed the Lithium-Ion Battery Resource Analysis (LIBRA) model as a tool to help stakeholders better understand the following types of questions: What are the roles of R&D, industrial learning, and scaling of demand in lowering the cost of battery energy storage system production? How do the intersections between the EV and stationary storage sectors affect the battery supply chain? For various stationary storage and EV penetration scenarios, what volumes of critical materials might be required and what role can resource recovery play? What does expected demand for both EVs and stationary storage portend for mineral resources and overall mineral scarcity? The LIBRA model is developed using a System dynamics (SD) modeling approach to represent interactions across the segments of the battery materials supply chain. System dynamics models can capture the complex interactions and feedback between the various system components that influence supply and demand. The LIBRA model is comprised of several interacting modules that represent specific portions of the LIB supply chain. The model tracks the buildout of the domestic LIB industry over time (2020 - 2050) and in the context of competing demands for raw materials, recycling, and markets for LIBs. The LIBRA model represents major systemic feedback loops and delays across the supply chain. This report provides a complete documentation for the LIBRA model, including model assumptions, data, scenario analysis results, and sensitivity analysis of the model's input space.

25 ENERGY STORAGE↗

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗

Capabilities and applications of a computer program system for dynamic loads analyses of flexible airplanes with active controls /DYLOFLEX/

This paper describes and illustrates the capabilities of the DYLOFLEX Computer Program System. DYLOFLEX is an integrated system of computer programs for calculating dynamic loads of flexible airplanes with active control systems. A brief discussion of the engineering formulation for each of the nine DYLOFLEX programs is described. The capabilities of the system are illustrated by the analyses of two example configurations.

Perry, B., III↗

Dynamic Braking System of a Tidal Generator

Renewable energy generation has experienced significant cost reductions during the past decades, and it has become more accepted by the global population. In the beginning, wind generation dominated the development and deployment of renewable energy; however, during recent decades, photovoltaic (PV) generation has grown at a very significant pace due to the tremendous decrease in the cost of PV modules. The focus on renewable energy generation has now expanded to include new types with promising future applications, such as river and tidal generation. The input water flow to these types of resources is more predictable than wind or solar generation. The data used in this paper is representative of a typical river or tidal generator. The analysis is based on a generator with a power rating of 40 kW. The tidal generator under consideration is driven by two sets of helical turbines connected to each side of the generator located in between the turbines. The generator is operated in variable speed, and it is controlled to maximize the energy harvested as well as the operation of the turbine generator. The electrical system consists of a three-phase permanent magnet generator connected to a three-phase passive rectifier. The output of the rectifier is connected to a DC-DC converter to match the rectifier output to the DC bus voltage of the DC-AC inverter. The three-phase inverter is connected to the grid, and it is controlled to provide a good interface with the grid. One important aspect of river and tidal generation is the braking mechanism. In a tidal generator, the braking mechanism is important to avoid a runaway condition in case the connection to the grid is lost when there is a fault in the lines. A runaway condition may lead to an overspeed condition and cause extreme stresses on the turbine blade structure and eventual disintegration of the mechanical structure. In this paper, the concept of the dynamic braking system is developed and investigated for normal and abnormal operations. The main objective is to optimize the performance under emergency braking while designing the system to be as simple as possible to avoid overdesigning the power electronics or exceeding the target budget.

13 HYDRO ENERGY↗

Model Order Reduction Algorithm for Estimating the Absorption Spectrum

The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the quantum propagator’s eigenspectrum for medium-to-large sized systems, traditional approaches based on the partial diagonalization of the propagator often encounter oscillatory and stagnating convergence. Electronic structure methods which solve the molecular response problem through the solution of spectrally shifted linear systems, such as the complex polarization propagator, offer an alternative approach which is agnostic to the underlying spectral density or domain location. This generality comes at a seemingly high computational cost associated with solving a large linear system for each spectral shift in some discretization of the spectral domain of interest. In this work, we present a novel, adaptive solution to this high computational overhead based on model order reduction techniques via interpolation. Model order reduction reduces the computational complexity of mathematical models and is ubiquitous in the simulation of dynamical systems and control theory. The efficiency and effectiveness of the proposed algorithm in the ab initio prediction of X-ray absorption spectra is demonstrated using a test set of challenging water clusters which are spectrally dense in the neighborhood of the oxygen K-edge. On the basis of a single, user defined tolerance we automatically determine the order of the reduced models and approximate the absorption spectrum up to the given tolerance. We also illustrate that, for the systems studied, the automatically determined model order increases logarithmically with the problem dimension, compared to a linear increase of the number of eigenvalues within the energy window. Furthermore, we observed that the computational cost of the proposed algorithm only scales quadratically with respect to the problem dimension.

IDREAM, K-Edge, theoretical, computational, electr↗

Direct statistical simulation of the Lorenz96 system in model reduction approaches

Direct statistical simulation (DSS) of nonlinear dynamical systems bypasses the traditional route of accumulating statistics by lengthy direct numerical simulations by solving the equations that govern the statistics themselves. DSS suffers, however, from the curse of dimensionality as the statistics (such as correlations) generally have higher dimensions than the underlying dynamical variables. Here we investigate two approaches to reduce the dimensionality of DSS, illustrating each method with numerical experiments with the Lorenz96 dynamical system. The forms of DSS chosen here involve approximate closures at second and third order in the equal-time cumulants. We demonstrate significant reduction in computational effort that can be achieved without sacrificing the accuracy of DSS. The methods developed here can be applied to turbulent fluid and magnetohydrodynamical systems. Published by the American Physical Society 2025

Li, Kuan↗

Constraining chaos: Enforcing dynamical invariants in the training of reservoir computers

Drawing on ergodic theory, we introduce a novel training method for machine learning based forecasting methods for chaotic dynamical systems. The training enforces dynamical invariants—such as the Lyapunov exponent spectrum and the fractal dimension—in the systems of interest, enabling longer and more stable forecasts when operating with limited data. The technique is demonstrated in detail using reservoir computing, a specific kind of recurrent neural network. Finally, results are given for the Lorenz 1996 chaotic dynamical system and a spectral quasi-geostrophic model of the atmosphere, both typical test cases for numerical weather prediction.

97 MATHEMATICS AND COMPUTING↗

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution

Recent works exploring deep learning application to dynamical systems modeling have demonstrated that embedding physical priors into neural networks can yield more effective, physically-realistic, and data-efficient models. However, in the absence of complete prior knowledge of a dynamical system's physical characteristics, determining the optimal structure and optimization strategy for these models can be difficult. In this work, we explore methods for discovering neural state space dynamics models for system identification. Starting with a design space of block-oriented state space models and structured linear maps with strong physical priors, we encode these components into a model genome alongside network structure, penalty constraints, and optimization hyperparameters. Demonstrating the overall utility of the design space, we employ an asynchronous genetic search algorithm that alternates between model selection and optimization and obtains accurate physically consistent models of three physical systems: an aerodynamics body, a continuous stirred tank reactor, and a two tank interacting system.

genetic algorithms, neural architecture search, ne↗

Computational methods and software systems for dynamics and control of large space structures

The deployment, assembly and mission-oriented maneuvering of space structures in orbit will trigger large motions of flexible, truss-type structures. In addition, the presence of on-board controls both for attitude stabilization and specified vibration tolerance requirements may further complicate the dynamic behavior of the orbiting structures. Because of safety and cost considerations, the dynamic response of the combined structural and control systems must be predicted reliably. This need can only be met through the development of reliable and efficient simulation capabilities, since there is general agreement that on-orbit experiments should be limited because of cost, time and facility constraints. The long-term objective of this research effort is to develop a next-generation computer simulator for the dynamics and control of large space structures. The simulator will be based on integrating four research thrusts: a new multibody dynamics formulation methodology, modeling capabilities in long/slender truss-beam components with realistic joints, efficient computational procedures that can be implemented either in sequential or concurrent computers, and prototype simulation modules that can be easily processed into a modern large-scale engineering software system such as the NASA/Computational Structural Mechanics (CSM) testbed.

Park, K. C.↗

Limitations for Quantum Algorithms to Solve Turbulent and Chaotic Systems

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (QCL) algorithm answering one of their open questions. We provide a further significant limitation for any quantum algorithm that aims to output a quantum state that approximates the normalized solution vector. Given a natural choice of coordinates for a dynamical system with one or more positive Lyapunov exponents and solutions that grow sub-exponentially, we prove that any such algorithm has complexity scaling at least exponentially in the integration time. As such, an efficient quantum algorithm for simulating chaotic systems or regimes is likely not possible.

97 MATHEMATICS AND COMPUTING↗

A biplane roentgen videometry system for dynamic /60 per second/ studies of the shape and size of circulatory structures, particularly the left ventricle.

A roentgen-television digital-computer technique and a display system developed for dynamic circulatory structure studies are described. Details are given for a videoroentgenographic setup which is used for obtaining biplane roentgen silhouettes of a left ventricle. A 60 per sec measurement of the shape and volume of angiographically outlined cardiac chambers can be made by this technique along with simultaneous ECG, pressure, and flow measurements accessible for real-time digital computer processing and analysis.

Ritman, E. L.↗