Search NASA⌕ Search

SEARCH · Search NASA

Results for “EM algorithm”

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.

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

At least 73 records · Page 4

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

WE-A-17A-03: Catheter Digitization in High-Dose-Rate Brachytherapy with the Assistance of An Electromagnetic (EM) Tracking System

Purpose: To investigate the use of a system using EM tracking, postprocessing and error-detection algorithms for measuring brachytherapy catheter locations and for detecting errors and resolving uncertainties in treatment-planning catheter digitization. Methods: An EM tracker was used to localize 13 catheters in a clinical surface applicator (A) and 15 catheters inserted into a phantom (B). Two pairs of catheters in (B) crossed paths at a distance <2 mm, producing an undistinguishable catheter artifact in that location. EM data was post-processed for noise reduction and reformatted to provide the dwell location configuration. CT-based digitization was automatically extracted from the brachytherapy plan DICOM files (CT). EM dwell digitization error was characterized in terms of the average and maximum distance between corresponding EM and CT dwells per catheter. The error detection rate (detected errors / all errors) was calculated for 3 types of errors: swap of two catheter numbers; incorrect catheter number identification superior to the closest position between two catheters (mix); and catheter-tip shift. Results: The averages ± 1 standard deviation of the average and maximum registration error per catheter were 1.9±0.7 mm and 3.0±1.1 mm for (A) and 1.6±0.6 mm and 2.7±0.8 mm for (B). The error detection rate was 100% (A and B) for swap errors, mix errors, and shift >4.5 mm (A) and >5.5 mm (B); errors were detected for shifts on average >2.0 mm (A) and >2.4 mm (B). Both mix errors associated with undistinguishable catheter artifacts were detected and at least one of the involved catheters was identified. Conclusion: We demonstrated the use of an EM tracking system for localization of brachytherapy catheters, detection of digitization errors and resolution of undistinguishable catheter artifacts. Automatic digitization may be possible with a registration between the imaging and the EM frame of reference. Research funded by the Kaye Family Award 2012.

07 ISOTOPE AND RADIATION SOURCES↗

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗

Parallel State Estimation Assessment with Practical Data

This paper presents a full-cycle parallel state estimation (PSE) implementation using a preconditioned conjugate gradient algorithm. The developed code is able to solve large-size power system state estimation within 5 seconds using real-world data, comparable to the Supervisory Control And Data Acquisition (SCADA) rate. This achievement allows the operators to know the system status much faster to help improve grid reliability. Case study results of the Bonneville Power Administration (BPA) system with real measurements are presented. The benefits of fast state estimation are also discussed.

State Estimation, Preconditioned Conjugate Gradien↗

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Biochemistry & Molecular Biology↗

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗

Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models

We derive an asymptotic expansion for the log-likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals an intimate connection between two types of algorithms for parameter estimation: the method of moments and likelihood optimizing algorithms such as Expectation-Maximization (EM). We show that likelihood optimization in the low SNR regime reduces to a sequence of least squares optimization problems that match the moments of the estimate to the ground truth moments one by one. This connection is a stepping stone towards the analysis of EM and maximum likelihood estimation in a wide range of models. A motivating application for the study of low SNR mixture models is cryo-electron microscopy data, which can be modeled as a GMM with algebraic constraints imposed on the mixture centers. We discuss the application of our expansion to algebraically constrained GMMs, among other example models of interest. © 2022 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.

97 MATHEMATICS AND COMPUTING↗

Large Scale Frequent Pattern Mining using MPI One-Sided Model

In this paper, we propose a work-stealing runtime --- Library for Work Stealing LibWS --- using MPI one-sided model for designing scalable FP-Growth --- {\em de facto} frequent pattern mining algorithm --- on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art O(p) to O(f + p/f) for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. An experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (87\% efficiency for Power-law and 91% for Poisson). The proposed distributed FP-Tree merging algorithm provides 38x communication speedup on 4096 cores.

Vishnu, Abhinav↗

DARMA-EMPIRE Integration and Performance Assessment – Interim Report

We begin by presenting an overview of the general philosophy that is guiding the novel DARMA developments, followed by a brief reminder about the background of this project. We finally present the FY19 design requirements. As the Exascale era arises, DARMA is uniquely positioned at the forefront of asychronous many-task (AMT) research and development (R&D) to explore emerging programming model paradigms for next-generation HPC applications at Sandia, across NNSA labs, and beyond. The DARMA project explores how to fundamentally shift the expression(PM) and execution(EM)of massively concurrent HPC scientific algorithms to be more asynchronous, resilient to executional aberrations in heterogeneous/unpredictable environments, and data-dependency conscious—thereby enabling an intelligent, dynamic, and self-aware runtime to guide execution.

97 MATHEMATICS AND COMPUTING↗

Real-Time Prediction of Power System Frequency in FNET: A State Space Approach

This paper proposes a novel approach to predict power frequency by applying a state-space model to describe the time-varying nature of power systems. It introduces the Expectation maximization (EM) and prediction error minimization (PEM) algorithms to dynamically estimate the parameters of the model. This paper discusses how the proposed models can be used to ensure the efficiency and reliability of power systems in Frequency Monitoring Network (FNET), if serious frequency fluctuation or measurement failure occur at some nodes; this is achieved without requiring the exact model of complex power systems. Our approach leads to an easy online implementation with high precision and short response time that are key to effective frequency control. We randomly pick a set of frequency data for one power station in FNET and use it to estimate and predict the power frequency based on past measurements. Several computer simulations are provided to evaluate the method. Simulation results showed that the proposed technique could achieve good performance regarding the frequency monitoring with very limited measurement input information.

Djouadi, Seddik M↗

RICH: OPEN-SOURCE HYDRODYNAMIC SIMULATION ON A MOVING VORONOI MESH

We present here RICH, a state-of-the-art two-dimensional hydrodynamic code based on Godunov’s method, on an unstructured moving mesh (the acronym stands for Racah Institute Computational Hydrodynamics). This code is largely based on the code AREPO. It differs from AREPO in the interpolation and time-advancement schemeS as well as a novel parallelization scheme based on Voronoi tessellation. Using our code, we study the pros and cons of a moving mesh (in comparison to a static mesh). We also compare its accuracy to other codes. Specifically, we show that our implementation of external sources and time-advancement scheme is more accurate and robust than is AREPO when the mesh is allowed to move. We performed a parameter study of the cell rounding mechanism (Lloyd iterations) and its effects. We find that in most cases a moving mesh gives better results than a static mesh, but it is not universally true. In the case where matter moves in one way and a sound wave is traveling in the other way (such that relative to the grid the wave is not moving) a static mesh gives better results than a moving mesh. We perform an analytic analysis for finite difference schemes that reveals that a Lagrangian simulation is better than a Eulerian simulation in the case of a highly supersonic flow. Moreover, we show that Voronoi-based moving mesh schemes suffer from an error, which is resolution independent, due to inconsistencies between the flux calculation and the change in the area of a cell. Our code is publicly available as open source and designed in an object-oriented, user-friendly way that facilitates incorporation of new algorithms and physical processes.

79 ASTRONOMY AND ASTROPHYSICS↗

Direction-optimizing Label Propagation and its Application for Community Detection

Label Propagation is a machine learning algorithm typically used for classification. It has also been found to be an effective method for detecting communities in networks. It has two attractive features as a community detection method: it has nearly linear runtime and it requires no \textit{a priori} community information. We propose a new Direction Optimizing Label Propagation Algorithm (DOLPA) that relies on the use of {\em frontiers} and alternates between label {\em push} and label {\em pull} operations to enhance the performance of LPA. Specifically, DOLPA has parameters for tuning the processing order of vertices in a graph. This reduces the number of edges visited and improves the quality of solution. We apply DOLPA to community detection and present the design and implementation of the algorithm as well as its shared-memory parallelization using OpenMP. Empirically, we evaluate our algorithm using synthetic graphs as well as real-world networks. Compared with the state-of-art \textit{Parallel Label Propagation} algorithm, we achieve at least two times the F-Score while reducing the runtime by 50\% for synthetic graphs with overlapping communities. We also compare DOLPA against the state-of-art parallel implementation of the Louvain method using the same graphs and show that DOLPA achieves about three times the F-Score at 10\% the runtime. On real-world graphs, we get a speedup of up to $10\times$ using 64 threads.

Liu, X↗

Ionospheric Transfer Function Tests: Line of Sight and Slab

Ionospheric transfer function (ITF) algorithms determine the effects of the ionosphere on an electromagnetic (EM) signal as it propagates through. In this report, analytic formulas are derived which can be used to compare results of ITF calculations from certain algorithms.

97 MATHEMATICS AND COMPUTING↗

An Innovative Energy Management System for Microgrids with Multiple Grid-Forming Inverters

As increasingly more grid-forming (GFM) inverter-based resources replace traditional fossil-fueled synchronous generators as the GFM sources in microgrids, the existing microgrid energy management systems (EMS) need to be updated to control and coordinate multiple GFM inverters that consider system control objectives under different microgrid connection states.For each state, we formulate an optimization problem and apply a real-time feedback-based control algorithm; altogether, the control algorithms seamlessly connect the states into a generic microgrid EMS that controls the nodal voltages and frequencies, becomes a virtual power plant (VPP) when connected to the main grid, and coordinates power sharing responsibility among GFM sources when islanded. We showcase the EMS on a real-world simulation of a microgrid under the different states to demonstrate its operational effectiveness.

energy management system↗

An Innovative Energy Management System for Microgrids with Multiple Grid-Forming Inverters

As increasingly more grid-forming (GFM) inverter-based resources replace traditional fossil-fueled synchronous generators as the GFM sources in microgrids, the existing microgrid energy management systems (EMS) need to be updated to control and coordinate multiple GFM inverters that consider system control objectives under different microgrid connection states. For each state, we formulate an optimization problem and apply a real-time feedback-based control algorithm; altogether, the control algorithms seamlessly connect the states into a generic microgrid EMS that controls the nodal voltages and frequencies, becomes a virtual power plant (VPP) when connected to the main grid, and coordinates power sharing responsibility among GFM sources when islanded. We showcase the EMS on a real-world simulation of a microgrid under the different states to demonstrate its operational effectiveness.

energy management systems↗

Characterizing nanoscale scanning probes using electron microscopy: A novel fixture and a practical guide

The nanoscale geometry of probe tips used for atomic force microscopy (AFM) measurements determines the lateral resolution, contributes to the strength of the tip-surface interaction, and can be a significant source of uncertainty in the quantitative analysis of results. While inverse imaging of the probe tip has been used successfully to determine probe tip geometry, direct observation of the tip profile using electron microscopy (EM) confers several advantages: it provides direct (rather than indirect) imaging, requires fewer algorithmic parameters, and does not require bringing the tip into contact with a sample. In the past, EM-based observation of the probe tip has been achieved using ad hoc mounting methods that are constrained by low throughput, the risk of contamination, and repeatability issues. We report on a probe fixture designed for use in a commercial transmission electron microscope that enables repeatable mounting of multiple AFM probes as well as a reference grid for beam alignment. This communication describes the design, fabrication, and advantages of this probe fixture, including full technical drawings for machining. Further, best practices are discussed for repeatable, non-destructive probe imaging. Finally, examples of the fixture’s use are described, including characterization of common commercial AFM probes in their out-of-the-box condition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗