SEARCH · Engineering Papers

Results for “Prior Distribution”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Emergency Asset Positioning for Resilient Transmission Grid Operation

In this paper we study a problem of hurricane emergency preparedness via placement of emergency storage assets prior to its strike. We present a two-stage stochastic model for choosing locations and quantities of emergency storage to help support the power grid through a hurricane event. The expectation of losses in our two-stage model is estimated using the sample average approximation. We construct damage scenarios for sample average approximation using WIND Toolkit meteorological data and fragility curves of various electric grid components. We demonstrate the efficacy of our two-stage planning model by simulating operations during Hurricane Dolly on the 2000-bus transmission test system. Our model, coupled with our scenario selection strategy, is effective at mitigating loss of load when compared to a model without emergency storage assets placed prior to an extreme event.

emergency preparedness↗

DOE OSTI2021

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Back-Stress and Its Evolution during Primary Creep in Particle Strengthened Nickel Superalloys

According to Eshelby’s theory, inelastically inhomogeneous inclusions in a metallic matrix give rise to a distribution of internal stresses. In the case of particle strengthened materials, such as nickel base superalloys, the presence and evolution of this back-stress leads to various observable effects, such as primary creep, back-flow upon loading, and memory of prior deformation. This article presents the background of the concept of back-stress and how it applies to the scenario of creep. A derivation of an evolution equation for back-stress in the context of primary creep is also presented. The results from neutron diffraction with in-situ creep experiments on directionally solidified nickel superalloys are presented in order to demonstrate the validity of the proposed equation and the corollaries derived therefrom.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Emergency Generation Asset Positioning for Resilient Transmission Grid Operation: Preprint

In this paper we study a problem of hurricane emergency preparedness via placement of emergency generation assets prior to its strike. We present a two-stage stochastic model for choosing locations and quantities of emergency storage to help support the power grid through a hurricane event. The expectation of losses in our two-stage model is estimated using the sample average approximation. We construct damage scenarios for sample average approximation using WIND Toolkit meteorological data and fragility curves of various electric grid components. We demonstrate the efficacy of our two-stage planning model by simulating operations during Hurricane Dolly on the 2000-bus transmission test system. Our model, coupled with our scenario selection strategy, is effective at mitigating loss of load when compared to a model without emergency generation assets placed prior to an extreme event.

emergency preparedness↗

DOE OSTI2020

Imaging Cycle-Induced Damage of MnO 2 Microparticles

MnO 2 has been proposed as an electrode material in electrochemical energy storage devices. However, poor cycle life, especially in aqueous electrolytes, remains a detriment to commercialization. Prior studies have suggested a number of explanations for this capacity loss; however, experiments aimed at elucidating the details of the degradation process (es) are sparse. We describe here a microtube-membrane construct that allows for electrodeposition of monodisperse MnO 2 microparticles distributed across the membrane surface, and for subsequent electrochemical cycling of these MnO 2 particles. This allowed for a detailed analysis of the effect of cycling on the MnO 2 , by simply imaging the membrane surface before and after cycling. When an aqueous electrolyte was used, gross changes in particle shape, size and morphology were observed over the course of 500 cycles. Partial dissolution occurred as well. No such changes were observed when the MnO 2 particles were cycled (up to 500 times) in a propylene carbonate electrolyte solution.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Two-Way Coupled CFD/DEM Simulation of Electromagnetic Heating in a Fluidized Bed Reactor

A set of tools has been developed to couple a multiphase reacting computational fluid dynamics solver (MFIX) with two computational electromagnetic solvers (COMSOL and Elmer). In contrast to several recent investigations, which calculate a single static EM field prior to the CFD calculation, in the present work the electromagnetic field is periodically updated during the simulation. This enables the EM field and associated EM heating predictions to reflect the effects of evolving material properties (temperature, composition, size etc.) and the evolving distribution of material in the system. The present work uses effective medium theory (EMT) for the electromagnetic field calculations since the goal is to apply the tool for industrial scale reacting systems. Predictions using MFIX/COMSOL and MFIX/Elmer are compared to in bed thermocouple measurements from a fluidized bed experiment and recent simulation predictions and recent experiments performed at NETL. The NETL experiments also include packed bed operating conditions. Coupled MFIX/COMSOL simulations at these conditions are compared with similar simulations using only COMSOL to measure errors due to the solver coupling approach.

CFD↗

DOE OSTI2026

Two-Way Coupled CFD/DEM Simulation of Electromagnetic Heating in a Fluidized Bed Reactor - Extended Abstract

CFD↗

DOE OSTI2020

Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know

Remote sensing instruments are heavily used to provide observations for both the operational and research communities. These sensors do not provide direct observations of the desired atmospheric variables, but instead, retrieval algorithms are necessary to convert the indirect observations into the variable of interest. It is critical to be aware of the underlying assumptions made by many retrieval algorithms, including that the retrieval problem is often ill posed and that there are various sources of uncertainty that need to be treated properly. In short, the retrieval challenge is to invert a set of noisy observations to obtain estimates of atmospheric quantities. The problem is often complicated by imperfect forward models, by imperfect prior knowledge, and by the existence of nonunique solutions. Optimal estimation (OE) is a widely used physical retrieval method that combines measurements, prior information, and the corresponding uncertainties based on Bayes’s theorem to find an optimal solution for the atmospheric state. Furthermore, OE also allows the relative contributions of the different sources of error to the uncertainty in the final retrieved atmospheric state to be understood. Here, we provide a novel Python library to illustrate the use of OE for inverse problems in the atmospheric sciences. We introduce two example problems: how to retrieve drop size distribution parameters from radar observations and how to retrieve the temperature profile from ground-based microwave sensors. Using these examples, we discuss common pitfalls, how the various error sources impact the retrieval, and how the quality of the retrieval results can be quantified.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Novel Technique for Distributed Measuring of Strain in the Vadose Zone

Characterizing water content and pressure changes in the vadose zone is important to understanding a variety of geologic processes, ranging from permeability, to evapotranspiration, and aquifer recharge. Changes in water content, or pressure, cause strain in the solid porous medium of the vadose zone, and it is possible that measuring those strains could be used a characterization tool. The Coherence-length-gated Microwave Photonics Interferometry (CMPI) technique measures strain at high resolution along many intervals defined by pairs of reflectors distributed along an optical fiber. This technique has recently been developed at Clemson University, and it has the spatial, and temporal resolution to characterize the strains that are expected to occur with hydrologic changes in the vadose zone. However, the technique has never been used to measure strain in porous media, so its capabilities remain uncertain. The objective of this thesis is to evaluate the ability of using CMPI to measure strain changes in the vadose zone. The research approach consists of conducting laboratory tests using a column filled with sand that was subjected to changes in water content and pressure. An optical fiber with CMPI reflectors was deployed in a high surface area ribbon and used to measure strain along the axis of the column. The column was made from 8-inch, Schedule 40 PVC pipe (75 cm tall, 20 cm inner diameter) and filled with medium-grained sand (K = 2.5x10-6 m/s, porosity = 0.28, Coefficient of Uniformity = 2, van Genuchten (n = 4.34 and  = 0.00039 m-1), Young’s Modulus = 18 – 47 MPa). Five pressure and four temperature sensors attached to probes inserted into the wall. The optical fiber includes five reflectors spaced 10 cm apart on the inside and outside of the column along the vertical axis. Strain measurements are made between pairs of reflectors. The reflectors are created in 250-micron-diameter acrylate-coated single mode Corning SMF28e+ optical fiber using a femtosecond laser. The optical fiber was laminated between two pieces of polyester film creating a large surface area to transfer strain from the porous media to the optical fiber. The experiments were conducted by filling the column from the bottom or infiltrating water from the top. The water was allowed to equilibrate to room temperature prior to each test in order to limit thermoelastic strain. Five injection tests with a rate of 250 ml/min and three infiltration tests at varying rates were conducted, and the results show patterns of strain and pressure are generally similar. Hydrologic conditions define three zones based on the pressure magnitude and distribution. 1.) Ambient Zone where the pressure heads are quasi-static and the pressure gradient is roughly unity (head gradient of zero). This is the uppermost zone and is characterized by negative pressures. 2.) Transition Zone where the pressures increase from ambient to zero, are changing relatively rapidly and the pressure gradient is relatively steep (pressure head gradients of 2). The Transition zone is 10 to 15 cm thick. 3.) Positive Pressure Zone where the pressure is positive, the rate of change is slower than in the transition zone and the gradient is flatter (pressure head gradient 1.1 to 1.2). This is the lowest zone in the column. Injection of water causes the pressure to increase and the three zones to move upward. The Transition zone moves at a rate of approximately 0.0002 m/s +/- .00005, according to analyses of pressure profiles. This is the same as the average velocity of the water calculated as volumetric flux/effective porosity =5.4x10-5 m/s/0.28. Strain signals in the range of 10s  were observed with a noise level of generally less than 0.1  (signal to noise ratio of greater than 100) during injection and drainage. The spatial and temporal distributions of strain caused by injection depend on the location of the moving pressure zones. The locations of the different pressure zones were determined from pressure profiles at different times and these data were transferred to strain time series. This showed that strain in the Ambient pressure zone is either unchanged or slightly compressive, whereas strain in Transition zone is tensile and roughly proportional to the pressure change, and strain ranges from tensile to compressive in the Positive Pressure zone. In general, the strain is variable at the top of the Positive Pressure zone, but it appears to be consistently tensile lower in the zone. The spatial distribution of strain causes three distinct stages in the strain times series measured between pairs of CMPI reflectors. The strain is unchanged or slightly compressive during Stage 1, it increases (positive strain is tensile) approximately linearly at a rate of 0.02 to 0.03 μ/s during the Stage 2, and then flattens out in Stage 3. The strain increases again during Stage 4 of the time series. The pressure also changes in stages. It is unchanged during Stage 1 and then increases relatively rapidly at a rate of between 4 and 10 Pa/s during Stage 2 and continues to increase during Stages 3 and 4, but at a rate slightly slower than during Stage 2 (from 2.5 to 3.5 Pa/s). The rates of pressure and strain change are consistent with basic analyses. The rate of pressurization is similar to the calculated velocity of flow in the saturated zone, and this is similar to the measured velocity of the strain increase. The ratio of the pressurization rate and strain rate during Stage 2 (2.5 (Pa/s) /0.03 (μ/s)) is 80 MPa, which is approximately equal to the upper range expected considering the uniaxial compression and the Young’s Modulus of the sand. An interesting effect occurs when the upper surface of the sand becomes saturated. Significant compression (several 10s of ) occurs as the pressure and saturation increase at the upper surface. Compression occurs throughout the column, but the effect is greatest at the top of the column. The rate of compression is fastest slightly before ponding occurs, but it slows markedly and nearly stops when water starts to accumulate at the surface (ponding). This effect reverses when the surface of the sand is drained, resulting in tension throughout the column. The compression caused by this effect can be as large or larger than the tensile strain that accumulated during filling. This effect was unexpected because increasing pressure is normally associated with tensile strain. Nevertheless, this effect was observed consistently in all tests where the pressure changes at the upper surface, including tests where water was injected from below or infiltrated from above. This effect behaves as if the pore pressure at the upper surface of the sand exerts a normal force on the boundary (increasing pore pressure exerts a downward compression on the boundary). The results of these laboratory experiments indicate that CMPI can measure strain caused by fluid pressure changes in the vadose zone with a signal to noise ratio of 100 or more. Injection and drainage cause a strain signal that is complex, but repeatable. The magnitudes of the strain signal are consistent with magnitudes that are expected based on poroelastic calculations using independently measured properties of the sand. These results indicate that the CMPI technique with an optical fiber laminated in a polyester ribbon generates data that represent the strain distribution during hydrologic processes of imbibition and drainage in variably saturated sand. This suggests that distributed strain measurements using CMPI could be a viable approach for evaluating processes in the vadose zone, laying the groundwork for future field implementation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

An all-oxide electrolysis cells for syngas production with tunable H 2 /CO yield via co-electrolysis of H 2 O and CO 2

High-rate production of syngas with tunable H 2 /CO and coke-free operation is achieved in a solid-oxide electrolysis cell (SOEC). Prior to operation, controlled pre-reduction of La 0.7 Sr 0.3 Fe 0.9 Ni 0.1 O 3-δ (LSFNi) cathode is used to trigger the in-situ exsolution of Ni-Fe alloy nanoparticles with an average size of ~45 nm uniformly distributed and socketed on LSFNi backbone, enabling efficient co-electrolysis of H 2 O and CO 2 to H 2 and CO. At 1.5 V, the current density reaches ~1.0 A cm-2 at 750 °C and ~2.4 A cm -2 at 850 °C with near 100% Faradaic Efficiency. We demonstrate the feasibility of tuning the output H 2 /CO ratio by nearly two orders of magnitude (from ~0.1 to ~7) by manipulating H 2 O/CO 2 ratio of feed gas, operating temperature, and current density. Finally, stable operation for >100 h is obtained without evidence of carbon deposition, although high current density operation leads to observable deterioration of anode/electrolyte interface due to the rapid oxygen evolution.

25 ENERGY STORAGE↗

DOE OSTI2020

Tomography of the positive-pitch fast-ion velocity distribution in DIII-D plasmas with Alfvén eigenmodes and neoclassical tearing modes

Understanding the effect of Alfvén eigenmodes (AEs) and neoclassical tearing modes (NTMs) on fast ions is highly important for fusion reactors due to potentially strong resonant interactions between the fast ions and the modes. Here, we use the four-view fast-ion D-alpha (FIDA) diagnostic installed in the DIII-D tokamak to reconstruct the fast-ion velocity distribution at two radial positions during two sequential discharges with strong and weak mode activity, respectively. The velocity-space coverage of the diagnostics, however, only allows reliable reconstructions of fast ions with positive pitches. Therefore, we suggest new tomographic inversion methods relying on prior information outside the well-diagnosed region. We find that within the population of fast ions with positive pitches, ions, at all energies, are transported away from the measurement volumes. Comparisons between the reconstructions and kick model simulations, where the mode activity is considered, reveal that low-frequency modes such as the NTMs and low-frequency AEs contribute significantly to the positive-pitch fast-ion transport in the central measurement volume, whereas TAEs and EAEs become important farther out and are responsible for decreased fast-ion confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts

Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated text, enabling reliable attribution and tracing of malicious usage of LLMs. Despite recent progress, existing methods still face key limitations: some become computationally infeasible for large messages, while others suffer from a poor trade-off between text quality and decoding accuracy. Moreover, the decoding accuracy of existing methods drops significantly when the number of tokens in the generated text is limited, a condition that frequently arises in practical usage. To address these challenges, we propose XMark, a novel method for encoding and decoding binary messages in LLM-generated texts. The unique design of XMark’s encoder produces a less distorted logit distribution for watermarked token generation, preserving text quality, and also enables its tailored decoder to reliably recover the encoded message with limited tokens. Extensive experiments across diverse downstream tasks show that XMark significantly improves decoding accuracy while preserving the quality of watermarked text, outperforming prior methods. The code will be made publicly available upon acceptance.

Xu, Jiahao [University of Nevada, Reno]↗

DOE OSTI2024

The Dynamics of Debris Disk Creation in Neutron Star Mergers

Abstract The detection of GW170817/AT2017gfo inaugurated an era of multimessenger astrophysics, in which gravitational-wave and multiwavelength photon observations complement one another to provide unique insight into astrophysical systems. A broad theoretical consensus exists, in which the photon phenomenology of neutron star mergers largely rests upon the evolution of the small amount of matter left on bound orbits around the black hole or massive neutron star remaining after the merger. Because this accretion disk is far from inflow equilibrium, its subsequent evolution depends very strongly on its initial state, yet very little is known about how this state is determined. Using both snapshot and tracer particle data from a numerical relativity/MHD simulation of an equal-mass neutron star merger that collapses to a black hole, we show how gravitational forces arising in a nonaxisymmetric, dynamical spacetime supplement hydrodynamical effects in shaping the initial structure of the bound debris disk. The work done by hydrodynamical forces is ∼10 times greater than that due to time-dependent gravity. Although gravitational torques prior to remnant relaxation are an order of magnitude larger than hydrodynamical torques, their intrinsic sign symmetry leads to strong cancellation; as a result, hydrodynamical and gravitational torques have a comparable effect. We also show that the debris disk’s initial specific angular momentum distribution is sharply peaked at roughly the specific angular momentum of the merged neutron star’s outer layers, a fewr g c, and identify the regulating mechanism.

Astronomy & Astrophysics↗

DOE OSTI2022

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Variable frequency response testbed to validate protective relays up to 20 kHz☆

Microgrids operate in islanding or utility grid mode. In islanding mode, distributed energy sources with power electronics inverters can generate fault currents over a wide range of frequencies. To gain a better understanding of the nature of these events, it is crucial to measure currents at frequencies of up to 20 kHz at transient states with protective relays. Protective relays at these frequency responses should be tested prior to being installed in microgrids. However, testing at high-frequency currents cannot be done with Relay Test Equipment (RTE) that generate signals up to 50th Harmonic for 60 Hz (3 kHz). In this study, a frequency response method and testbed for high-frequency currents of up to 20.16 kHz was developed and tested. The testbed utilized a RTE and High-Frequency Power Source/ Amplifier. Furthermore, frequency relay experiments were run at frequencies of up to 1 and 20.16 kHz at a current magnitude of 0.1 and 0.5 A, respectively. The events were collected, and the current magnitude and frequency were plotted at time and frequency domain, respectively. The study of current magnitude and frequencies of up to 20.16 kHz for two overcurrent relays was performed and validated the variable frequency testbed and methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Grid-Interactive Electric Vehicle and Building Coordination Using Coupled Distributed Control: Preprint

As an increasing number of controllable devices are introduced onto the grid, they can individually provide ancillary services in support of grid stability. However, the goals of each device differ due to their type and individual objectives, causing instances where they may conflict. To reduce the chances of these devices contributing to grid instability, these devices must effectively communicate in a cooperative manner to both meet their own needs while providing services to the grid. Previous work demonstrates that the NALD (Network Lasso-ADMM - Limited Communication - DMPC) algorithm allows coordination between two subsystems that use different control algorithms (building and charging stations) to provide services to the grid and individually optimize their performance in a specific scenario. The ideal NALD algorithm should be generalized to allow plug-and-play capabilities across devices of differing characteristics. This paper takes a step toward generalizability by updating the electric vehicle charging objective and re-defining the communication scheme compared to prior work to generalize the coordination and, as a result, improve the performance of the NALD algorithm.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

DOE OSTI2023

TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

Dynamic graph embedding has emerged as a very effective technique for addressing diverse temporal graph analytic tasks (i.e., link prediction, node classification, recommender systems, anomaly detection, and graph generation) in various applications. Such temporal graphs exhibit heterogeneous transient dynamics, varying time intervals, and highly evolving node features throughout their evolution. Hence, incorporating long-range dependencies from the historical graph context plays a crucial role in accurately learning their temporal dynamics. In this paper, we develop a graph embedding model with uncertainty quantification, TransformerG2G, by exploiting the advanced transformer encoder to first learn intermediate node representations from its current state (t) and previous context (over timestamps [t–1,t–l], l is the length of context). Moreover, we employ two projection layers to generate lower-dimensional multivariate Gaussian distributions as each node's latent embedding at timestamp t. We consider diverse benchmarks with varying levels of "novelty" as measured by the TEA (Temporal Edge Appearance) plots. Here, our experiments demonstrate that the proposed TransformerG2G model outperforms conventional multi-step methods and our prior work (DynG2G) in terms of both link prediction accuracy and computational efficiency, especially for high degree of novelty. Furthermore, the learned time-dependent attention weights across multiple graph snapshots reveal the development of an automatic adaptive time stepping enabled by the transformer. Importantly, by examining the attention weights, we can uncover temporal dependencies, identify influential elements, and gain insights into the complex interactions within the graph structure. For example, we identified a strong correlation between attention weights and node degree at the various stages of the graph topology evolution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Designing for cooperative grain boundary segregation in multicomponent alloys

Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only competition is possible between solute species. In this paper, we show that solute elements can cooperate in the way they segregate to grain boundaries: In properly targeted alloys, the different chemical species cooperate to each fill complementary grain boundary sites disfavored by the other. By developing a theoretical “spectral” approach to this problem based on quantum-accurate grain boundary site distributions, we show how grain boundaries can be cooperatively alloyed, whether by depletion or enrichment. We provide machine-learned cosegregation information for over 700 ternary aluminum-based alloys and experimentally validate the concept in one ternary alloy where cosegregation is not expected by prior models but is expected based on the cooperative model.

grain boundaries↗