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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Convolutions on the sphere: commutation with differential operators

We generalize the definition of convolution of vectors and tensors on the 2-sphere, and prove that it commutes with differential operators. Moreover, vectors and tensors that are normal/tangent to the spherical surface remain so after the convolution. These properties make the new filtering operation particularly useful to analyzing and modeling nonlinear dynamics in spherical systems, such as in geophysics, astrophysics, and in inertial confinement fusion applications. An essential tool we use is the theory of scalar, vector, and tensor spherical harmonics. We then show that our generalized filtering operation is equivalent to the (traditional) convolution of scalar fields of the Helmholtz decomposition of vectors and tensors.

42 ENGINEERING↗
DOE OSTI2024

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

Here, this paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from $\mathscr{O}(\mathscr{N}^{2.37286})$ classically to $\mathscr{O}(\mathscr{N}^{2} log \mathscr{N}$ x $p$ log $p)$ in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Robust state estimation of feeding–blending systems in continuous pharmaceutical manufacturing

State estimation is a fundamental part of monitoring, control, and real-time optimization in continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard constraints, moving horizon estimation (MHE) can estimate the current state by solving a well-defined optimization problem where process complexities are explicitly considered as constraints. Traditional MHE techniques assume random measurement noise governed by some normal distributions. However, state estimates can be unreliable if noise is not normally distributed or measurements are contaminated with gross or systematic errors. In this paper, to improve the accuracy and robustness of state estimation, we incorporate robust estimators within the standard MHE skeleton, leading to an extended MHE framework. The proposed MHE approach is implemented on two pharmaceutical continuous feeding–blending system (FBS) configurations which include loss-in-weight (LIW) feeders and continuous blenders. Numerical results show that our MHE approach is robust to gross errors and can provide reliable state estimates when measurements are contaminated with outliers and drifts. Finally and moreover, the efficient solution of the MHE realized in this work, suggests feasible application of on-line state estimation on more complex continuous pharmaceutical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Feedback Control Approaches for Restoration of Power Grids from Blackouts

The automated restoration of power systems with variable energy resources is a timely problem to tackle. Automated restoration advice can support operators in deciding on strategic actions to restore power grids from a blackout with a mix of conventional and renewable generation resources. To this end, this paper frames the restoration process of power grids with solar resources as a nonlinear dynamic model with algebraic constraints in discrete time which is steered by feedback control loops. We discuss two feedback-control strategies based on greedy and reinforcement learning algorithms, and contrast their performance with restoration plans generated by a mixed-integer linear program. We found that the reinforcement learning algorithm infers restoration actions faster than the greedy one. However, the tuning process of the reinforcement learning parameters is slower than for the greedy one.

machine learning↗
DOE OSTI2020

Determination of permeability for hydrocarbon release due to excavation-induced stress redistribution in rock salt

Due to a stress redistribution after the excavation of an underground tunnel for radioactive waste disposal, an Ed/DZ (excavation disturbed/damaged zone) will be generated in the near field of the opening, resulting in significant changes in the hydraulic and mechanical properties of the rock mass in the zone. Initially more or less randomly distributed hydrocarbons at grain boundaries in rock salt, which sometimes can only be observed with ultraviolet light, can then be mobilised and migrate at a potentially significant rate towards the excavation. Within the international cooperative project DECOVALEX 2019, the migration mechanism of such fluid inclusions in rock salt is being studied intensively. Specifically, a multi-scale modelling strategy has been developed. A macroscale coupled hydro-mechanical modelling of an underground excavation was performed to determine hydraulic and time-dependent deviatoric stress conditions, by taking into account the rock salt creep behaviour. Under the obtained macro-scale constraints, micro-scale modelling of a pathway dilation along halite grain boundaries was performed using different model strategies: a) coupled hydromechanical modelling with a consideration of hydraulic pressure-induced dilatant deformation, b) nonlinear dynamic model taking account of fluid migration, stress-dependent grain boundary wetting and shear-induced dilatancy of salt, and c) phase-field modelling of flow pathway propagation. The permeability increase resulting from the pathway dilation is estimated to be as high as two orders of magnitude. Based on the permeability determined, a series of pressure buildups measured from a borehole with a high hydrocarbon release rate, a total of 430 build-ups within a monitoring time of 938 days, can be simulated with a macro-scale compressible flow model accounting for different zones around the opening.

58 GEOSCIENCES↗
DOE OSTI2017

Elementary dispersion analysis of some mimetic discretizations on triangular C-grids

Spurious modes supported by triangular C-grids limit their application for modeling large-scale atmospheric and oceanic flows. Their behavior can be modified within a mimetic approach that generalizes the scalar product underlying the triangular C-grid discretization. The mimetic approach provides a discrete continuity equation which operates on an averaged combination of normal edge velocities instead of normal edge velocities proper. An elementary analysis of the wave dispersion of the new discretization for Poincaré, Rossby and Kelvin waves shows that, although spurious Poincaré modes are preserved, their frequency tends to zero in the limit of small wavenumbers, which removes the divergence noise in this limit. However, the frequencies of spurious and physical modes become close on shorter scales indicating that spurious modes can be excited unless high-frequency short-scale motions are effectively filtered in numerical codes. We argue that filtering by viscous dissipation is more efficient in the mimetic approach than in the standard C-grid discretization. Lumping of mass matrices appearing with the velocity time derivative in the mimetic discretization only slightly reduces the accuracy of the wave dispersion and can be used in practice. Thus, the mimetic approach cures some difficulties of the traditional triangular C-grid discretization but may still need appropriately tuned viscosity to filter small scales and high frequencies in solutions of full primitive equations when these are excited by nonlinear dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model

With the onset of climate change, regions relied upon for water supply are increasingly subject to end-member fluctuations between periods of severe drought followed by extreme precipitation. The impacts of these extreme conditions on watershed hydrodynamics in water-resource sensitive regions such as California are unknown despite their great importance for resilience and water management purposes. Understanding these impacts requires high-resolution physically based models to capture sharp variations of topography, land use, wetting fronts, etc. Here, an integrated hydrologic model was used in a high-performance computing framework to study the complex nonlinear dynamics occurring at a representative Californian watershed. The Cosumnes Watershed, one of the last major rivers in California without a dam, offers a rare opportunity to isolate the effects of water management from climate extremes. Here, we show model validation with comparisons between model outputs and local measurements in addition to various satellite-based products including (1) Snow Water Equivalent (SWE) with Snow Data Assimilation System (SNODAS) and a reconstruction method by Bair and co-authors, (2) soil moisture with Soil Moisture Active Passive (SMAP), and (3) evapotranspiration (ET) with Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC). To assess changes in hydrodynamic behavior during climate extremes and their transitions, a simulation spanning a recent drought followed by the highest precipitation year on record (2015–2017) is discussed. From these simulations, we are able to highlight regions that are the most sensitive to climate extremes, which depend on many factors including hydrologic connectivity, geology and topography. These analyses provide a better understanding of the physical phenomena occurring in the watershed, strengthening our knowledge of how the system may respond to extreme conditions which might become the “new normal.”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Inference of phase field fracture models

The phase field approach to modeling fracture uses a diffuse damage field to represent cracks. This representation mollifies singularities that arise in computations with sharp interface models and some of the resultant difficulties in the mathematical and numerical treatment of fracture. Phase field fracture models have proven effective at representing crack propagation, branching, and merging. Specific formulations, beginning with brittle fracture, have also been shown to converge to classical solutions. Extensions to cover the range of material failure, including ductile and cohesive fracture, lead to an array of possible models. There exists a large body of literature focusing on this class of models and on the impact of model form on the predicted crack evolution. However, there have not been systematic studies into how optimal models may be chosen. Here, we take a first step in this direction by developing formal methods for identification of the best parsimonious model of phase field fracture given full-field data on the damage and deformation fields. We consider some of the main models that have been used for the degradation of elastic response due to damage and its propagation. Our approach builds upon Variational System Identification (VSI), a weak form variant of the Sparse Identification of Nonlinear Dynamics (SINDy). Furthermore, in this first communication we focus on synthetically generated data but we also consider central issues associated with the use of experimental full-field data, such as data sparsity and noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

First benchmarked electron cooling simulations from first principles

We present the first microscopic electron cooling simulations from first principles with accurate prediction of cooling time. These simulations were performed using our previously developed numerical method, PHAD, which is the first efficient large-scale collisional numerical method in beam physics. The simulation results are benchmarked with the experimental data of the low energy bunched electron cooling of ion beams at the storage ring CSRm at the IMP facility in China. Here, we have accurately considered the nonlinear dynamics in the whole accelerator system in addition to the electron cooling section. As a result, our simulations correctly reproduced cooling times of the experiments from first principles and without any tuning or fitting parameters in the code.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Integrated simulation of vertical fracture propagation induced by water injection and its borehole electromagnetic responses in shale gas systems

We analyze fracture propagation induced by hydraulic fracturing with water injection and examine their detectability with crosswell electromagnetic (EM) geophysical methods. For rigorous 3D coupled flow-geomechanical modeling, we employ a numerical method that can model failure by tensile and shear stresses, dynamic nonlinear permeability, dual continuum approach, and thermo-poro-mechanical effects. From numerical simulation, we find that the fracture propagation is not the same as propagation of the water front, because fracturing is governed by geomechanics whereas water saturation is determined by multiphase flow. At early times, the water front is almost identical to the fracture tip, suggesting that the fracture is mostly filled with the injected water. However, at late times, movement of the water front is retarded compared to fracture propagation, yielding a significant gap between the water front and the fracture top, filled with reservoir gas. During fracture propagation, the coupled flow-geomechanical models are transformed via a rock-physics model into electrical conductivity models. We employ a full 3D finite-element EM geophysical simulator to evaluate the sensitivity of the crosswell EM method to fracture propagation. It is shown that anomalous distribution of electrical conductivity is closely related to the injected water saturation, but not closely related to newly created unsaturated fractures. Our numerical modeling experiments demonstrate that the crosswell EM method can be highly sensitive to electrical conductivity changes that directly indicate the migration pathways of the injected fluid. Accordingly, the EM method can serve as an effective monitoring tool for monitoring the injected fluids during hydraulic fracturing operations.

58 GEOSCIENCES↗
DOE OSTI2021

Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Viscoplastic Interpretation of Localized Compaction Creep in Porous Rock

Recent laboratory evidence shows that compaction creep in porous rocks may develop through stages of acceleration, especially if the material is susceptible to strain localization. This paper provides a mechanical interpretation of compaction creep based on viscoplasticity and nonlinear dynamics. For this purpose, a constitutive operator describing the evolution of compaction creep is defined to evaluate the spontaneous accumulation of pore collapse within an active compaction band. This strategy enables the determination of eigenvalues associated with the stability of the response which is able to differentiate decelerating from accelerating strain. This mathematical formalism was linked to a constitutive law able to simulate compaction localization. Material point simulations were then used to identify the region of the stress space where unstable compaction creep is expected, showing that accelerating strains correspond to pulses of inelastic strain rate. Such pulses were also found in full-field numerical analyses of delayed compaction, revealing that they correspond to stages of inception and propagation of new bands across the volume of the simulated sample. These results illustrate the intimate relation between the spatial patterns of compaction and their temporal dynamics, showing that while homogeneous compaction develops with decaying rates of accumulation, localized compaction occurs through stages of accelerating deformation caused by the loss of strength taking place during the formation of a band. In addition, they provide a predictive modeling framework to simulate and explain the spatio-temporal dynamics of compaction in porous sedimentary formations.

58 GEOSCIENCES↗
DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗
DOE OSTI2025

Learning Physically Interpretable Atmospheric Models From Data With WSINDy

The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.

58 GEOSCIENCES↗
DOE OSTI2017

Direct observation of coherent energy transfer in nonlinear micromechanical oscillators

Energy dissipation is an unavoidable phenomenon of physical systems that are directly coupled to an external environmental bath. In an oscillatory system, it leads to the decay of the oscillation amplitude. In situations where stable oscillations are required, the energy dissipated by the vibrations is usually compensated by replenishment from external energy sources. Consequently, if the external energy supply is removed, the amplitude of oscillations start to decay immediately, since there is no means to restitute the energy dissipated. Here, we demonstrate a novel dissipation engineering strategy that can support stable oscillations without supplying external energy to compensate losses. The fundamental intrinsic mechanism of resonant mode coupling is used to redistribute and store mechanical energy among vibrational modes and coherently transfer it back to the principal mode when the external excitation is off. To experimentally demonstrate this phenomenon, we exploit the nonlinear dynamic response of microelectromechanical oscillators to couple two different vibrational modes through an internal resonance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Nonlinear electronic excitation in water under proton irradiation: a first principles study

Nonlinear dynamics of electronic excitation bridge physical and physicochemical stages of water radiolysis under proton irradiation, a multi-scale physicochemical process that is fundamental to a wide range of technological and medical applications of high-energy protons. We study the spatial and temporal changes to the excited holes generated in this ionization event using first-principles theory simulation. A significant majority of holes are formed in the immediate vicinity of the irradiating proton paths, and these holes decay rapidly, while secondary excitations are simultaneously induced in regions farther away. While the hole population remains constant, the observed spatially spreading hole distribution cannot be described as concentration-dependent diffusion current. Compared to the primary excitation induced by the irradiating protons, the secondary excitation farther away is somewhat less energetic. Here, the first-principles theory simulation here provides a detailed description of how the primary excitation by proton radiation precedes the formation of cationic holes, which undergo ultrafast chemical processes in water radiolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Aperiodic signals processing via parameter-tuning stochastic resonance in a photorefractive ring cavity

Based on solving numerically the generalized nonlinear Langevin equation describing the nonlinear dynamics of stochastic resonance by Fourth-order Runge-Kutta method, an aperiodic stochastic resonance based on an optical bistable system is numerically investigated. The numerical results show that a parameter-tuning stochastic resonance system can be realized by choosing the appropriate optical bistable parameters, which performs well in reconstructing aperiodic signals from a very high level of noise background. The influences of optical bistable parameters on the stochastic resonance effect are numerically analyzed via cross-correlation, and a maximum cross-correlation gain of 8 is obtained by optimizing optical bistable parameters. This provides a prospective method for reconstructing noise-hidden weak signals in all-optical signal processing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Formation and ultraslow propagation of infrared solitons in graphene under an external magnetic field

Unusual dispersion relation of graphene nanoribbons for electrons can lead to an exceptionally strong optical response in the infrared regime and exhibits a very good tunable frequency. According to quantum optics and solid-material scientific principles, here we show the possibility to generate ultraslow infrared bright and dark solitons in graphene under the action of strong magnetic and infrared laser fields. By means of quantum-mechanical density-matrix formalism, we derive the equations of motion that govern the nonlinear evolution of the probe-pulse envelope in this scheme. It is found that, by properly choosing the parameters of the system, the formation and ultraslow propagation of infrared spatial solitons originate from the balance between nonlinear effects and the dispersion properties of the graphene under infrared excitation. Moreover, the unique electronic properties and selection rules near the Dirac point provide more freedom for us to study the linear and nonlinear dynamical responses of the photonics and graphene system. These results may have potential applications in telecommunication and optical information processing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗