A mass, momentum, and energy conservative dynamical low-rank scheme for the Vlasov equation
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70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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Results for “dynamics 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.
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Understanding the dynamic interactions of root-knot nematodes and their host: role of plant growth promoting bacteria and abiotic factors
Root-knot nematodes (Meloidogyne spp., RKN) are among the most destructive endoparasitic nematodes worldwide, often leading to a reduction of crop growth and yield. Insights into the dynamics of host-RKN interactions, especially in varied biotic and abiotic environments, could be pivotal in devising novel RKN mitigation measures. Plant growth-promoting bacteria (PGPB) involves different plant growth-enhancing activities such as biofertilization, pathogen suppression, and induction of systemic resistance. We summarized the up-to-date knowledge on the role of PGPB and abiotic factors such as soil pH, texture, structure, moisture, etc. in modulating RKN-host interactions. RKN are directly or indirectly affected by different PGPB, abiotic factors interplay in the interactions, and host responses to RKN infection. We highlighted the tripartite (host-RKN-PGPB) phenomenon with respect to (i) PGPB direct and indirect effect on RKN-host interactions; (ii) host influence in the selection and enrichment of PGPB in the rhizosphere; (iii) how soil microbes enhance RKN parasitism; (iv) influence of host in RKN-PGPB interactions, and (v) the role of abiotic factors in modulating the tripartite interactions. Furthermore, we discussed how different agricultural practices alter the interactions. Finally, we emphasized the importance of incorporating the knowledge of tripartite interactions in the integrated RKN management strategies.
59 BASIC BIOLOGICAL SCIENCES↗
Shape-persistent phthalocyanine cages
Phthalocyanine (Pc), an electro-redox active moiety, has many attractive properties stemming from its large aromatic system and ability to act as a catalyst in electrochemical reactions, such as the CO 2 reduction reaction (CO 2 RR). However, due to the synthetic challenge related to geometric requirements and poor solubility (strong aggregation), discrete shape-persistent cages consisting of site-isolated, readily accessible Pc moieties have not been available. Here, we report the synthesis of Zn- and Ni-metallated Pc-based molecular cages via one-step dynamic spiroborate linkage formation in high yields. The ZnPc cage structure is unambiguously elucidated at the atomic level by single-crystal X-ray diffraction. Moreover, owing to the site-isolated redox-active metal centers, readily accessible intrinsic cavity, and shape-persistent backbone, the Ni-metallated Pc (NiPc) cage exhibits high catalytic efficiency, selectivity, and stability, superior to the non-caged control molecules in electrocatalytic CO 2 RR.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Atomic Origin of the Autocatalytic Reduction of Monoclinic CuO in a Hydrogen Atmosphere
Reducibility is key for the use of bulk metal oxides in chemical transformation involving redox reactions but probing microscopic processes of oxide reduction is challenging. This is because the insulating nature of bulk oxides restricts ion and electron spectroscopic measurements of oxide surfaces. Herein, using a combination of environmental transmission electron microscopy and atomistic modeling, we report direct in-situ atomic-scale observations of the surface and subsurface dynamics and show that the hydrogen induced CuO reduction occurs via the surface decay of Cu-O/Cu bilayer atomic steps, formation of partially reduced CuO superstructure by the self-ordering of O vacancies in the subsurface, and collapse of Cu-O layers in the bulk. In this work, all these substeps can be traced back to the progressively increased concentration and activity of O vacancies in the surface and subsurface of the oxide, thereby leading to the self-accelerated oxide reduction. These results demonstrate the microscopic details that may have broader applicability in modulating various redox processes.
36 MATERIALS SCIENCE↗
Defect-Driven Redox Interplay on Anatase TiO 2 : Surface-Structure Dependent Activation for CO 2 Hydrogenation Catalysis
Titanium dioxide (TiO 2 ) is one of the most extensively studied oxides as an active catalyst or catalyst support, particularly in energy and environmental applications, but the atomistic mechanisms governing its dynamic response to reactive environments and their correlation to reactivity remain largely elusive. Using in situ environmental transmission electron microscopy (ETEM), synchrotron X-ray diffraction (XRD), ambient-pressure X-ray photoelectron spectroscopy (AP-XPS), temperature-programmed reduction (TPR), reactivity measurements, and theoretical modeling, we reveal the dynamic interplay between oxygen loss and replenishment of anatase TiO 2 under varying reactive conditions. Under H 2 exposure, anatase TiO 2 undergoes surface reduction via lattice oxygen loss, forming Ti 3 O 5 . In contrast, CO 2 exposure induces oxygen replenishment, reversing stoichiometry. In mixed H2/CO 2 environments, the reverse water–gas shift (RWGS) reaction proceeds selectively on stepped and high-indexed TiO 2 surfaces, whereas the thermodynamically stable TiO 2 (101) surface remains inactive and intact. Critically, H 2 pretreatment generates oxygen vacancies on TiO 2 (101), transforming it into an active Ti 3 O 5 or defect-rich surface that catalyzes RWGS. By correlating surface structure, defect dynamics, and gas-phase interactions, this work deciphers the competition between H 2 -driven reduction and CO 2 -driven oxidation pathways at the atomic scale. Furthermore, these insights establish defect engineering as a strategic lever to activate inert TiO 2 facets, advancing the design of adaptive catalysts for sustainable fuel synthesis technologies.
36 MATERIALS SCIENCE↗
A COMPACT model reduction methodology for articulated, multi-flexible bodies structures
To simulate the dynamical motion of articulated, multiflexible body structures, one can use multibody simulation packages such as DISCOS. To this end, one need appropriate reduced-order models for all the flexible components involved. The component modes projection and assembly model reduction methodology is one way to construct these reduced-order component models. However, the generated reduced-order system models typically contain high frequency extraneous modes. The presence of high frequency extraneous modes in a reduced-order system model forces us to use a small stepsize in the numerical integration of that model, resulting in an increase in the elapsed time of the integration process. To eliminate these high-frequency modes, we first identify and discard the component modes that 'contributed' to the generations of these modes. A sensitivity analysis is then used to determine how the remaining component modes should be perturbed in order to still closely capture the selected system modes. The effectiveness of the proposed methodology has been successfully verified using a finite-element model of the Galileo spacecraft.
Lee, Allan Y.↗
Physics-Informed Active Learning With Simultaneous Weak-Form Latent Space Dynamics Identification
The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy data. Here, to enhance robustness against noise, we incorporate the weak-form estimation of nonlinear dynamics (WENDy) into gLaSDI. In the proposed weak-form gLaSDI (WgLaSDI) framework, an autoencoder and WENDy are trained simultaneously to discover intrinsic nonlinear latent-space dynamics of high-dimensional data. Compared with the standard sparse identification of nonlinear dynamics (SINDy) employed in gLaSDI, WENDy enables variance reduction and robust latent space discovery, therefore leading to more accurate and efficient reduced-order modeling. Furthermore, the greedy physics-informed active learning in WgLaSDI enables adaptive sampling of optimal training data on the fly for enhanced modeling accuracy. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including viscous and inviscid Burgers' equations, time-dependent radial advection, and the Vlasov equation for plasma physics. With data that contains 5%–10% Gaussian white noise, WgLaSDI outperforms gLaSDI by orders of magnitude, achieving 1%–7% relative errors. Compared with the high-fidelity models, WgLaSDI achieves 121 to 1779x speed-up.
97 MATHEMATICS AND COMPUTING↗
Multiobjective Dynamic Optimization for Optimal Load-Following of Natural Gas Combined Cycle Power Plants under Stress Constraints
With the increasing penetration of intermittent renewable energy sources into the electric grid, there is an associated need for conventional thermal power plants that are designed to operate at base-load conditions to cycle their load rapidly and frequently and operate under low-load conditions. Fast load-following operations lead to plant efficiency loss and the reduction of equipment life. A high-fidelity dynamic model of a natural gas combined cycle power plant, with rigorous equipment level submodels, is developed to capture the plant transient performance and the thermomechanical stress evolution at the high-pressure drum is computed to assess the drum life consumption. Stress evolution is modeled for the location of the edge at the drum/downcomer junction that experiences high circumferential stress amplitude during the fast load-following operation, leading to higher fatigue damage than locations considered under existing design standards. A dynamic optimization problem is solved for optimal load-following operation. Depending on the value of the stress constraint and the desired ramp rate, satisfying the desired stress constraint may be infeasible without relaxing the ramp rate. A multiobjective dynamic optimization problem is solved using a lexicographic approach that minimizes ramp rate relaxation and maximizes efficiency while satisfying stress constraints, avoiding spraying to saturation, and maintaining main steam and reheat steam temperature within bounds. It was observed that the optimal ramp rate can be highly nonlinear as opposed to the industry-standard linear ramp rate. Nonlinear optimal ramp-rate profiles not only help to avoid stress constraints that may be unavoidable by using the linear profile but also result in higher efficiency than the linear profile. Furthermore, the study shows that there is a strong tradeoff between the relaxation in the plant ramp rate and the time-average thermal efficiency.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Weak-form latent space dynamics identification
Recent work in data-driven modeling has demonstrated that a weak formulation of model equations enhances the noise robustness of a wide range of computational methods. In this paper, we demonstrate the power of the weak form to enhance the LaSDI (Latent Space Dynamics Identification) algorithm, a recently developed data-driven reduced order modeling technique. We introduce a weak form-based version WLaSDI (Weak-form Latent Space Dynamics Identification). WLaSDI first compresses data, then projects onto the test functions and learns the local latent space models. Notably, WLaSDI demonstrates significantly enhanced robustness to noise. With WLaSDI, the local latent space is obtained using weak-form equation learning techniques. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form guarantees a robust and precise latent space recovery, hence allowing for a fast, robust, and accurate simulation. We demonstrate the efficacy of WLaSDI vs. LaSDI on several common benchmark examples including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in the case of 1D inviscid Burgers' simulations with the addition of up to 100% Gaussian white noise, the relative error remains consistently below 6% for WLaSDI, while it can exceed 10,000% for LaSDI. Similarly, for radial advection simulations, the relative errors stay below 15% for WLaSDI, in stark contrast to the potential errors of up to 10,000% with LaSDI. Moreover, speedups of several orders of magnitude can be obtained with WLaSDI. For example applying WLaSDI to 1D Burgers' yields a 140X speedup compared to the corresponding full order model.
97 MATHEMATICS AND COMPUTING↗
Crashworthiness of recycled carbon fiber composite sinusoidal structures at dynamic rates
Fiber reinforced polymer composites are finding applications in the automotive space for structurally critical applications including crash management. The use of recycled carbon fiber reinforcement can greatly reduce carbon emissions. In this study, recycled carbon fiber composites were manufactured into a self-supporting geometry using three matrices: polyphenylene sulfide (PPS), acrylonitrile butadiene styrene (ABS), and a structural epoxy, and subsequently crushed between flat platens at dynamic rates ranging from 4.6 to 9.1 ms -1 at temperatures in a range of -40°C to 80°C. Load-displacement data was used to evaluate their specific energy absorption, crush efficiency, and steady-state crush stress. Further, the energy absorption of the ABS composites was strongly sensitive to temperature, while the PPS composites exhibited strong crush efficiency dependence with both rate and temperature. The epoxy composites exhibited stable crush behavior at dynamic crush rates but exhibited a dramatic reduction in crush efficiency relative to quasi-static tests. The results of this study indicate that recycled fiber composites can achieve very high energy absorption levels (50–80kJkg -1 at room temperature) that make them an excellent alternative to more expensive and less environmentally friendly continuous virgin fiber laminates.
42 ENGINEERING↗
Semiclassical transition state theory through the lens of the restricted partition function
The wide adoption of transition state theory in resolving the rates of molecular processes relies on the simplification from reducing the formal and numerical expense of dynamics by a geometric constraint. Such a reduction is at odds with the uncertainty in localization that the uncertainty principle requires. While many forms of semiclassical transition state theory (SCTST) have been aimed at addressing this challenge, a popular approach has relied on resolving the underlying phase space structure of the exact rate formula to leverage Bohr–Sommerfeld quantization. Here, the Hernandez–Miller SCTST reframed the thermal rate formula into an integral of the so-called restricted partition function (RPF) over the action associated with the reaction. The density-of-state SCTST has reframed the rate formula in terms of the instanton’s density of states (DoS). Here, we show the relationship between the RPF-SCTST and the DoS-SCTST and derive the latter from the former. In this way, we help unify these branches of SCTST and provide a clearer formalism for future advances.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Reduced Switching Frequency Finite Control Set Model Predictive Control (FCS-MPC) for DFIG
An enhanced Finite Control Set Model Predictive Control (FCS-MPC) strategy with a two-step prediction horizon for a Doubly-Fed Induction Generator (DFIG) is the focus of this paper. The DFIG and RL filter's discrete-time model is used in the proposed control scheme for a two-step prediction horizon of rotor and filter currents for the converter's eight possible switching states. Afterward, the control algorithm selects the ideal switching state, which minimizes currents' objective function. The proposed control scheme does not require a modulation stage for internal controllers. We use Lagrange extrapolations to predict the dynamic changes in currents. The switching frequency reduction is achieved by integrating an optimization constraint in the algorithm's cost function. Furthermore, the Total Harmonic Distortion level of currents is kept below 5%, according to IEEE Std 519-14. Obtained results reveal that the switching frequency of the DFIG converters is considerably reduced without losing control; it is reduced by 13.89KHz for the Grid Side Converter (GSC) and by 1.78KHz for the Rotor Side Converter (RSC).
doubly-fed induction generator↗
Weak-Form Latent Space Dynamics Identification
This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.
Choi, Youngsoo↗
Physics Guided Simulation of Electrostatic Discharge: Technical Report
Triboelectrically-charged objects may create threshold sparks, electrostatic discharge (ESD) events, to equilibrate charge between themselves and other relatively charged objects. ESD events exhibit many complex physical phenomena. They are a nexus of several fields of physics with disparate characteristic scales: plasma physics, chemical kinetics, hydrodynamics, circuit models, etc. These scales can span many orders of magnitude from the varied collisions thermalizing information within a plasma on the $\mathcal{O}(fs/ps)$ to the physical size of the plasma channel on the $\mathcal{O}(100µm)$, to the speed of a nonlinear hydrodynamic wave propagating at $\mathcal{O}(µm, ns)$. These threshold ESD events may occur in situations of programmatic importance, delivering energy and power profiles to a “victim load” generating deleterious consequences. To predict and mitigate these consequences we must answer questions about the spark’s energy budget: how much energy goes into producing the spark channel; how much gets radiated away; how much energy is advected away into the hydrodynamics; and how much energy is delivered to a victim load. An ESD simulation toolset has been created and evolved in order to answer these questions. An appropriate, physics guided implementation for simulation can be done by gaining insight into its constituent physics and leveraging that intuition to choose a suitable numerical operator. We examine in detail the chemical kinetics, circuit discharge, and hydrodynamics to deter mine dominant regimes, values, timescales, and interactions to uncover the underlying physical dynamics. We also examine and propose model reduction schemes for high-dimensional chemical kinetics. We use past and current work with experimentally validated and theoretically-verified hydrodynamics to calculate applicability limits of the non-ionizing strong shock limit. We quantify the energy budget from a hydrodynamic perspective and demonstrate that a significant fraction of the stored energy is “earmarked” for hydrodynamic advection as an energy terminus. Lastly, we combine the constituent physics of an ESD event (chemical kinetics, circuit model, and hydrodynamics) into a cohesive, actionable toolset and obtain promising results from an isothermal test case. We then propose a viable, modular evolution of the ESD toolset based upon the performed examination of the physics uncovering dominant physical scales and the stiffness of the compositional differential system.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Framework for a Digital Documented Safety Analysis
This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Finite element analysis using NASTRAN applied to helicopter transmission vibration/noise reduction
A finite element NASTRAN model of the complete forward rotor transmission housing for the Boeing Vertol CH-47 helicopter was developed and applied to reduce transmission vibration/noise at its source. In addition to a description of the model, a technique for vibration/noise prediction and reduction is outlined. Also included are the dynamic response as predicted by NASTRAN, test data, the use of strain energy methods to optimize the housing for minimum vibration/noise, and determination of design modifications which will be manufactured and tested. The techniques presented are not restricted to helicopters but are applicable to any power transmission system. The transmission housing model developed can be used further to evaluate static and dynamic stresses, thermal distortions, deflections and load paths, fail-safety/vulnerability, and composite materials.
Howells, R. W.↗
STS-1 orbital trajectory reconstruction using unmodelled acceleration estimation
A postflight trajectory reconstruction and analysis were conducted in order to determine the effects of unmodeled thrusting on the Space Shuttle Orbiter, to generate representative thrusting uncertainties for input to error analyses, and to evaluate the accuracy of the Ancillary trajectory data product and real-time vectors. The methods of selecting appropriate data arcs, time placement of compensation forces, limitations of the orbit determination process, and methods of evaluating solutions obtained from various force combinations are presented. It is shown that the estimation of forces to compensate for uncoupled attitude maneuvers and attitude hold maintenance thrusting significantly improves the postflight reconstruction of Space Shuttle Orbiter trajectories. A reduction of measurement residual statistics due to dynamic model uncertainties yields improved accuracy for postflight orbit determination.
Lacarna, R. J.↗
Loads and aeroelasticity division research and technology accomplishments for FY 1983 and plans for FY 1984
Research was done in the following areas: development and validation of solution algorithms, modeling techniques, integrated finite elements for flow-thermal-structural analysis and design, optimization of aircraft and spacecraft for the best performance, reduction of loads and increase in the dynamic structural stability of flexible airframes by the use of active control, methods for predicting steady and unsteady aerodynamic loads and aeroelastic characteristics of flight vehicles with emphasis on the transonic range, and methods for predicting and reducing helicoper vibrations.
Gardner, J. E.↗