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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling of Grid-Forming and Grid-Following Inverters for Dynamic Simulation of Large-Scale Distribution Systems

Historically, distribution system planning studies mainly focused on steady state and quasi-steady state analysis, with limited attention paid to dynamic analysis. This paper develops three-phase, electromechanical models for both grid-forming and grid-following inverters, and integrates them into an open source, three-phase distribution network solver, thereby enabling dynamic simulation of large-scale, three-phase unbalanced distribution systems with high penetration of inverter-based DERs. The proposed inverter models are validated against electromagnetic simulation and field test data from the CERTS/AEP microgrid testbed, and simulated in an islanded 5252 node distribution system in the GridLAB-D simulation environment. Simulation verifies the effectiveness of the proposed inverter models for large-scale distribution system analysis. Finally, study results show that compared to traditional grid-following inverters, the high penetration of grid-forming inverters can improve the voltage and frequency stability of islanded distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Thermal shock resistance of multilayer silicon carbide receiver tubes for 800°C molten salt concentrating solar power application

CSP power tower receiver systems during rapid transient weather periods can be vulnerable to thermal shock conditions from rain that which can facilitate the onset of leaks and failures that can have catastrophic consequences. Silicon carbide (SiC) materials have attractive receiver application characteristics for being light weight, having high-strength and excellent thermal shock resistance performance which make them a particularly good fit for receiver absorber materials in CSP. In this investigation, the performance characteristics of Ceramic Tubular Products (CTP) SiC ceramic matrix composite (CMC), multilayered tubes were explored with respect to thermal shock performance for solar receiver applications in next generation CSP plants. Here, thermal shock testing was performed at the Sandia National Laboratories (SNL) Solar Furnace facility using a dynamic stage and thermal shock tube test setup. The tubes tested under incident solar heat flux of 100 W/cm2 were heated with inner tube temperatures reaching approximately 800 °C, with outer temperatures exceeding or just reaching 1000 El for the multilayer and monolithic SiC tubes respectively. The tubes were then quenched with simulated rain. The tubes were then cooled and subjected to hoop stress analysis using an Instron device to assess their subsequent mechanical strength. Furthermore, the on-sun study experimental results indicate an average of 24.2% and 97% higher hoop strength for the CMC tubes than those composed of monolithic SiC and aluminum oxide (A1203) respectively.

14 SOLAR ENERGY↗
DOE OSTI2025

Unified Model of Current-Limiting Grid-Forming Inverters for Large-Signal Analysis

Grid-forming (GFM) inverters can hardly withstand any overloading. As such, GFM inverters need a current limiter in their control system to avoid hardware damage during overloading or grid disturbances. When the current limiter is engaged for inverter protection, however, it dynamically changes the inverter output impedance, which can significantly affect the system behavior against large disturbances. For example, when the current limiter curtails the output power, the primary controller of the GFM inverter-which generates the voltage and angle reference-is prone to losing synchronization with the grid. This can cause large-signal instability in the network. This paper presents a unified GFM current-limiter model to gain a deeper understanding of the impact of the GFM inverter current limiting on large-signal instability and other system behaviors. The unified model captures several well-known current limiters for GFM inverters, and it reveals their large-signal equivalence characterized by the limiter angle. We use the unified model to present in-depth insights into the driving forces that cause large-signal instability in GFM inverter-driven grids. Further, this paper illustrates that the unified model can be used as a tool for assessing the system-level impacts of various GFM current-limiter designs during grid disturbances. Using numerical, analytical, electromagnetic transient models, and a hardware setup, the validity of the unified model is evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Microscopic theory of onset of decaging and bond-breaking activated dynamics in ultradense fluids with strong short-range attractions

We theoretically study thermally activated “in cage” elementary dynamical processes that precede full structural relaxation in ultra-dense particle liquids interacting via strong short range attractive forces. The analysis is based on a microscopic theory formulated at the particle trajectory level built on the dynamic free energy concept and an explicit treatment of how attractive forces control the formation and lifetime of physical bonds. Mean time scales for bond breaking, the early stage of cage escape, and non-Fickian displacement by a fixed amount are analyzed in the repulsive glass, bonded repulsive (attractive) glass, fluid, and dense gel regimes. The theory predicts a strong length-scale-dependent growth of these time scales with attractive force strength at fixed packing fraction, a much weaker slowing down with density at fixed attraction strength, and a strong decoupling of the shorter bond breaking time with the other two time scales that are controlled mainly by perturbed steric caging. All results are in good accord with simulations, and additional testable predictions are made. In conclusion, the classic statistical mechanical projection approximation of replacing all bare attractive and repulsive forces with a single effective force determined by pair structure incurs major errors for describing processes associated with thermally activated escape from transiently localized states.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AT2017gfo: Bayesian inference and model selection of multicomponent kilonovae and constraints on the neutron star equation of state

The joint detection of the gravitational wave GW170817, of the short γ-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star (NS) merger observed on 2017 August 17, is a milestone in multimessenger astronomy and provides new constraints on the NS equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multicomponents models that also account for non-spherical ejecta. Observational data favour anisotropic geometries to spherically symmetric profiles, with a log-Bayes’ factor of ~104, and favour multicomponent models against single-component ones. The best-fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical–relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to q < 1.54 and the reduced tidal parameter to $120\lt \tilde{\Lambda }\lt 1110$. Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a NS of 1.4 M ⊙ to 12.2 ± 0.5 km (1σ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Process modelling for Space Station experiments

Examined here is the sensitivity of a variety of space experiments to residual accelerations. In all the cases discussed the sensitivity is related to the dynamic response of a fluid. In some cases the sensitivity can be defined by the magnitude of the response of the velocity field. This response may involve motion of the fluid associated with internal density gradients, or the motion of a free liquid surface. For fluids with internal density gradients, the type of acceleration to which the experiment is sensitive will depend on whether buoyancy driven convection must be small in comparison to other types of fluid motion, or fluid motion must be suppressed or eliminated. In the latter case, the experiments are sensitive to steady and low frequency accelerations. For experiments such as the directional solidification of melts with two or more components, determination of the velocity response alone is insufficient to assess the sensitivity. The effect of the velocity on the composition and temperature field must be considered, particularly in the vicinity of the melt-crystal interface. As far as the response to transient disturbances is concerned, the sensitivity is determined by both the magnitude and frequency of the acceleration and the characteristic momentum and solute diffusion times. The microgravity environment, a numerical analysis of low gravity tolerance of the Bridgman-Stockbarger technique, and modeling crystal growth by physical vapor transport in closed ampoules are discussed.

Alexander, J. Iwan D.↗
NASA NTRS1993

Modeling of PCG fluid dynamics: Salient results

Materials processing in space-based laboratories has already yielded higher quality crystals during previous space flights, and opportunities for several fluids experiments are anticipated during the extended duration missions planned for the future. Crystal growth in space benefits not only from its reduced gravity environment but also from the absence of the hydrostatic pressure which assists certain crystal growth and refinement methods. Gravity-driven phenomena are thus reduced in strength, and a purely diffusive fluid's behavior can be attained. In addition, past materials science experiments have shown that microgravity can also help produce larger crystals. While gravity-related effects are definitely curtailed in space, they are nevertheless present to some degree due to the acceleration environment onboard the spacecraft. This residual acceleration level is comprised of quasi-steady, oscillatory, and transient components, and is caused by a variety of mechanisms. For example, gravity gradient forces produce low frequency disturbances, and the operation of machinery, control thrusters, solar panels, human activity, etc. contribute to higher frequency accelerations. These disturbances are collectively referred to as g-jitter, and they can be deleterious to certain experiments where the minimization of the acceleration level is important. Advanced vibration isolation techniques can be utilized to actively filter out some of the detrimental frequencies and help in obtaining optimum results. However, the successful application of this technology requires the detailed analysis of candidate fluids experiments to gauge their response to g-jitter and to determine their acceleration sensitivities. Several crystal growth experiments in the Protein Crystal Growth (PCG) area, besides others, are expected to be carried out on future shuttle flights and on Space Station Freedom. The need for vibration isolation systems or components for microgravity science experiments can be expected to grow as experiments and available hardware becomes more complex. This technology will also find increased application as the science community develops an awareness of their specific needs relative to the environment available in manned space missions. Vibration isolation research strives to develop a microgravity environment requirement that defines tolerance limits on the allowable g-level, and provides the required technology to achieve it. This effort will assist in establishing the tolerable acceleration levels for specific fluids experiments. The primary effort is directed towards modeling PCG and the approach undertaken for this investigation is outlined. The objectives of this research are: (1) to computationally determine vibration sensitivity of protein crystal growth experiments; (2) determine if these experiments can benefit from vibration isolation techniques; and (3) provide realistic requirements for vibration isolation technology.

Ramachandran, N.↗
NASA NTRS1990

Internal rotor friction instability

The analytical developments and experimental investigations performed in assessing the effect of internal friction on rotor systems dynamic performance are documented. Analytical component models for axial splines, Curvic splines, and interference fit joints commonly found in modern high speed turbomachinery were developed. Rotor systems operating above a bending critical speed were shown to exhibit unstable subsynchronous vibrations at the first natural frequency. The effect of speed, bearing stiffness, joint stiffness, external damping, torque, and coefficient of friction, was evaluated. Testing included material coefficient of friction evaluations, component joint quantity and form of damping determinations, and rotordynamic stability assessments. Under conditions similar to those in the SSME turbopumps, material interfaces experienced a coefficient of friction of approx. 0.2 for lubricated and 0.8 for unlubricated conditions. The damping observed in the component joints displayed nearly linear behavior with increasing amplitude. Thus, the measured damping, as a function of amplitude, is not represented by either linear or Coulomb friction damper models. Rotordynamic testing of an axial spline joint under 5000 in.-lb of static torque, demonstrated the presence of an extremely severe instability when the rotor was operated above its first flexible natural frequency. The presence of this instability was predicted by nonlinear rotordynamic time-transient analysis using the nonlinear component model developed under this program. Corresponding rotordynamic testing of a shaft with an interference fit joint demonstrated the presence of subsynchronous vibrations at the first natural frequency. While subsynchronous vibrations were observed, they were bounded and significantly lower in amplitude than the synchronous vibrations.

Walton, J.↗
DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Assessment of Sodium Thermal Stratification Models Utilizing the TSTF Benchmark

As a result of certain transient scenarios, a thermally stratified layer of liquid sodium can develop in the bulk coolant volumes of a sodium-cooled fast reactor (SFR). In addition to the effects a stratification layer has on the temperature of the heat transport system, a stratification layer can also influence the transition to and establishment of natural circulation flow, which plays an important role in passive cooling and the inherent safety of a pool-type SFR. Therefore, the ability to accurately capture thermal stratification phenomena is important when demonstrating the safety basis of a pool-type SFR during transient sequences. The present work assesses various computational models with different fidelities in their ability to predict thermal stratification in the upper plenum of an SFR. Each computational model will be assessed using the data generated at the Thermal Stratification Test Facility (TSTF) located at the University of Wisconsin-Madison. Using measured flow rate and inlet temperature data, the measured temperature distributions of the tests are compared to the predictions of the lumped volume-based models in SAS4A/SASSYS-1, a 1D-based model in SAM, and a 3-D computational fluid dynamics (CFD) model using STAR-CCM+. The relative performance of the various computational methods is assessed with respect to key metrics such as bulk coolant temperature distribution and plenum exit temperature. A total of eight tests are analyzed, covering different combinations of flow rates (3 and 10 GPM) and upper internal structure (UIS) configurations (none, solid, porous, and open) The perfect mixing model of SAS4A/SASSYS-1 provides the highest accuracy when the flow rate is high and there is no UIS in the test vessel, as high flow rate injection promotes thermal mixing of the sodium in the test vessel. For most of the analyzed tests, the stratified volume model of SAS4A/SASSYS-1 is able to predict the delay in the outlet temperature drop and temperature distribution in the test vessel by a small number of layers to represent thermal stratification. However, the stratified volume model can only simulate a maximum of three temperature layers within a volume and when a layer approaches the elevation of the outlet, the predicted outlet temperature can demonstrate rapid, non-physical changes. The 1-D axial mixing model of SAM provides results that agree reasonably well with the measured data in the prediction of the temporal evolution of the outlet temperature with the exception of the case with a high flow rate and no UIS. The SAM 1-D model has a similar level of accuracy to CFD results when it comes to predicting the outlet temperature. CFD shows overall good agreement in predicting the temperature distribution in the test vessel and outlet temperature. As CFD can model the test vessel geometry in detail, it performs well in the cases of complex geometries such as tests that included a UIS and internal flow through the UIS resulting in active mixing of the coolant in the test vessel. Each of the models discussed in the present work has the potential to be useful during the various stages of reactor design, analysis, and licensing. The lumped-volume approach can be applied for fast turnaround safety calculations to obtain overall reactor behavior during transients. The 1-D models provide improved accuracy when stratification is expected for a relatively low increase in the computational cost. The CFD model can be utilized for confirmatory analysis of the 1-D model, when experimental measurements are not available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Excited Carrier Dynamics in a Dye-Sensitized Niobate Nanosheet Photocatalyst for Visible-Light Hydrogen Evolution

Dye-sensitized photocatalysts that consist of a light-absorbing dye and a wide gap oxide semiconductor have been studied extensively as components of solar energy conversion systems. Although surface modification by a metal and/or metal oxide has a significant impact on the photocatalytic efficiency, the mechanism by which these modifications increase the activity has not been fully understood. Here a dye-sensitized H 2 evolution system was constructed by using Pt-intercalated HCa 2 Nb 3 O 10 nanosheets, Ru(II) complex photosensitizers ([Ru(4,4’-(CH 3 ) 2- bpy) 2 (4,4’-(PO 3 H 2 ) 2- bpy)] 2+ and [Ru(4,4’-(CH 3 ) 2- bpy) 2 (4,4’-(CH 2 PO 3 H 2 ) 2- bpy)] 2+ , abbreviated as RuP 2+ and RuCP 2+ ; bpy = 2,2'-bipyridine), and amorphous Al 2 O 3 as building blocks. In the presence of iodide as the electron donor, the H 2 evolution rate from Pt/HCa 2 Nb 3 O 10 nanosheets sensitized by RuP 2+ was increased by modification of the nanosheets with Al 2 O 3 . On the other hand, Al 2 O 3 had a negative impact on the H 2 evolution rate when RuCP 2+ was employed. These hybrid materials were studied by transient diffuse reflectance spectroscopy and steady-state emission spectroscopy. A detailed analysis of the transient absorption profiles of the adsorbed Ru(II) complexes revealed that there are at least three states of the complexes on the nanosheet surface. The transient bleaching of the ground state absorbance had different lifetime components ranging from a few μs to several hundred μs, which mainly reflect back electron transfer rates from HCa 2 Nb 3 O 10 to the oxidized Ru(II) complexes. Here, the Al 2 O 3 modifier could inhibit not only the back electron transfer events but also electron injection from the excited state photosensitizer. Interestingly, the negative effect of Al 2 O 3 on the electron injection rate was negligible in the case of RuP 2+ , which also had a higher H 2 evolution rate. This work highlights that suppressing fast back electron transfer from Pt/HCa 2 Nb 3 O 10 to the oxidized Ru(II) complex, which occurs on a time scale of a few μs, and maximizing the electron injection efficiency are both necessary for improving dye-sensitized H 2 evolution.

14 SOLAR ENERGY↗
DOE OSTI2020

Molecular bond stabilization in the strong-field dissociation of O 2 +

We theoretically examine the rotational and vibrational dynamics of O 2 + molecular ions exposed to intense, short laser pulses for conditions realized in contemporary pump-probe experiments. We solve the time-dependent Schrödinger equation within the Born-Oppenheimer approximation for an initial distribution of randomly aligned molecular ions. For fixed peak intensities, our numerical results show that total, angle-integrated O 2 + → O( 3 P) + O + ( 4 S 0 ) dissociation yields do not monotonically increase with increasing infrared-probe pulse duration. We find this pulse-duration-dependent stabilization to be consistent with the transient trapping of nuclear probability density in a light-induced (bond-hardening) potential-energy surface and robust against rotational excitation. We analyze this stabilization effect and its underlying bond-hardening mechanism (i) in the time domain, by following the evolution of partial nuclear probability densities associated with the dipole-coupled O 2 + (a 4 Π u ) and O 2 + (f 4 Π g ) cationic states, and (ii) in the frequency domain, by examining rovibrational quantum-beat spectra for the evolution of the partial nuclear probability densities associated with these states. In this work, our analysis reveals the characteristic timescale for the bond-hardening mechanism in O 2 + and explains the onset of bond stabilization for sufficiently long pulse durations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Examination of Semi-Analytical Solution Methods in the Coarse Operator of Parareal Algorithm for Power System Simulation

With continuing advances in high-performance parallel computing platforms, parallel algorithms have become powerful tools for development of faster than real-time power system dynamic simulations. In particular, it has been demonstrated in recent years that parallel-in-time (Parareal) algorithms have the potential to achieve such an ambitious goal. Here, the selection of a fast and reasonably accurate coarse operator of the Parareal algorithm is crucial for its effective utilization and performance. This paper examines semi-analytical solution (SAS) methods as the coarse operators of the Parareal algorithm and explores performance of the SAS methods to the standard numerical time integration methods. Two promising time-power series-based SAS methods were considered; Adomian decomposition method and Homotopy analysis method with a windowing approach for improving the convergence. Numerical performance case studies on 10-generator 39-bus system and 327-generator 2383-bus system were performed for these coarse operators over different disturbances, evaluating the number of Parareal iterations, computational time, and stability of convergence. All the coarse operators tested with different scenarios have converged to the same corresponding true solution (if they are convergent) and the SAS methods provide comparable computational speed, while having more stable convergence to the true solution in many cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2006

STRANAL-PMC Version 2.0

Version 2.0 of the Strain Rate Dependent Analysis of Polymer Matrix Composites (STRANAL-PMC) software has been released. A prior version was reported in Analyzing Loads and Strains in Polymer- Matrix Composites (LEW-17227), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 36. To recapitulate: Modified versions of constitutive equations of viscoplasticity of metals are used to represent deformation of a polymeric matrix. The equations are applied in a micromechanical approach, proceeding upward from slices of unit cells, through the ply level, to the laminate level. The constitutive equations are integrated in time by a Runge- Kutta technique. To predict the ultimate strength of each composite ply, failure criteria are implemented within the micromechanics. The inputs to STRANAL-PMC are the laminate geometry, properties of the fiber and matrix materials, and applied stress or strain versus time. The outputs are time-dependent stresses and strains at the slice, ply, and laminate levels. The improvements in version 2.0 include more rigorous representation of hydrostatic- stress effects in the matrix, refinement and extension of ply failure models, and capabilities to analyze transverse shear stresses. Version 2.0 can be implemented as a material-model code within transient dynamic finite-element codes.

Goldberg, Robert↗