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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗
DOE OSTI2024

Development of High-Fidelity and Efficient Modeling Capabilities for Enabling Co-Optimization of Fuels and Multi-Mode Engines

The objective of this closely coordinated research project is to develop improved physical sub-models and innovative numerical algorithms to enable accurate and efficient predictions of multi-mode combustion to support EERE’s Co-Optima program. To this end, a research pro-gram is proposed that seeks • to develop accurate submodels for predicting multi-mode combustion regimes, wall-heat transfer, non-equilibrium plasma ignition, and combustion-mode transition, • to develop dynamic load-rebalancing algorithms and efficient semi-implicit time-integration schemes for enabling exascale computing, • to validate the computational submodels against experiments and direct numerical simulation (DNS) data in conjunction with sensitivity analysis, and • to support the direct transition of the resulting sub-models into other engine-simulation tools through the development of self-contained modules. All sub-models will be integrated into the open-source exascale engine-simulation platform Nek5000.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Automatic parameter selection for electron ptychography via Bayesian optimization

Abstract Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and to study electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior to those processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.

42 ENGINEERING↗
DOE OSTI2021

Investigation of turbulent inflow specification in Euler–Lagrange simulations of mid-field spray

The process of atomization of a liquid jet by a parallel high-speed gas stream results in a spray, whose downstream development is of considerable interest to several applications. The round jet spray can be spatially divided into (i) a near-field (near-nozzle) region of liquid atomization and (ii) a downstream mid-field region of fully-dispersed droplets. In order to accurately model mid-field droplet dispersion, this work aims at developing a rigorous and robust injection model for Euler–Lagrange spray simulations. Results from experiments are used to obtain the relevant droplet number density, size distribution, and mean and standard deviation velocity distributions of the injection model, systematically in a step-by-step process. Two-phase large eddy simulations are performed by stochastically generating the Lagrangian droplets at the inlet of the mid-field region. Number flux, diameter distribution, mean velocity, and other time-averaged statistics at several downstream locations are shown to agree well with the corresponding experimental data.

42 ENGINEERING↗
DOE OSTI2023

Uncertainty Quantification for Multiphase Computational Fluid Dynamics Closure Relations with a Physics-Informed Bayesian Approach

Multiphase Computational Fluid Dynamics (MCFD) based on the two-fluid model is considered a promising tool to model complex two-phase flow systems. MCFD simulation can predict local flow features without resolving interfacial information. As a result, the MCFD solver relies on closure relations to describe the interaction between the two phases. Those empirical or semi-mechanistic closure relations constitute a major source of uncertainty for MCFD predictions. In this paper, we leverage a physics-informed uncertainty quantification (UQ) approach to inversely quantify the closure relations’ model form uncertainty in a physically consistent manner. This proposed approach considers the model form uncertainty terms as stochastic fields that are additive to the closure relation outputs. Combining dimensionality reduction and Gaussian processes, the posterior distribution of the stochastic fields can be effectively quantified within the Bayesian framework with the support of experimental measurements. As this UQ approach is fully integrated into the MCFD solving process, the physical constraints of the system can be naturally preserved in the UQ results. Here, in a case study of adiabatic bubbly flow, we demonstrate that this UQ approach can quantify the model form uncertainty of the MCFD interfacial force closure relations, thus effectively improving the simulation results with relatively sparse data support.

42 ENGINEERING↗
DOE OSTI2020

Time Series Classification for Locating Forced Oscillation Sources

Here, this article presents a machine learning based time-series classification method for using synchrophasor measurements to locate the source of forced oscillation (FO) for fast disturbance removal. First, multivariate time series (MTS) matrices are constructed by the most informative measurements selected by sequential feature selection from each power plant. Then, the Mahalanobis matrix is trained such that the Mahalanobis distance between the MTSs from the same class (i.e., with the same FO source location) are minimized and from different classes (i.e., with different FO source locations) are maximized. This allows MTSs to be classified by classifiers with class membership corresponding to the location of each FO source. To meet the runtime requirements of online matching, class templates are constructed to reduce data size and improve matching efficiency. To account for uncertainty in identifying the exact beginning of an FO event, dynamic time warping is used to align the out-of-sync MTSs. IEEE 39bus and WECC 179bus systems are used for algorithm development and validation. Simulation results demonstrate that the algorithm meets online operation runtime requirement with high accuracy using misaligned data sets.

42 ENGINEERING↗
DOE OSTI2023

Steady Laminar Flame for 1-Step Thermal Decomposition Model of PBX 9501

We have recently developed a new 1-step thermal decomposition model of PBX 9501 high explosive. In this report, we examine the behavior of the model in 1-D steady laminar flame calculations. In particular, the dependencies of the steady laminar flame velocity on initial pressure, thermal conductivies and parameters of the thermal decomposition model are investigated. The results of our numerical calculations are compared to available experimental data.

42 ENGINEERING↗
DOE OSTI2023

Evaluating Named Data Networking for Industrial Control System [Slides]

Current proposed work is: See if the inherent security that comes with Named Networking (NDN) can be applied to Industrial Control Systems; and, Every packet is required to be cryptographically signed which makes every single piece of data communicated in the system secure and authenticated.

42 ENGINEERING↗
DOE OSTI2020

Data-Centric Communication Framework for Multicast IEC 61850 Routable GOOSE Messages over the WAN in Modern Power Systems

In this paper, a data-centric communication framework is proposed for multicast routable generic object-oriented substation event (GOOSE) messages (MRGM) over the wide area network (WAN) for effective substation-to-substation (SS2SS) and substation to control center (SS2CC) communications. In this structure, the IEC 61850 GOOSE message is transmitted over the WAN using the data distribution service (DDS) as a fast, reliable, and secure data-centric communication middleware. The main feature of this framework is its multicast capability, where several authorized subscribers can receive a published message simultaneously. This can significantly improve the system monitoring and control of the protection systems in modern smart grids, where intelligent schemes can be applied. The effectiveness of the proposed platform, in terms of total end-to-end delay between participants, is evaluated through experimental results obtained from the actual hardware-based test setup developed at the Florida International University (FIU) smart grid testbed. The results demonstrate that the latency between sending and receiving a GOOSE message among participants is within its maximum time span defined by the IEC 61850-90-5 working group for communications over the WAN.

42 ENGINEERING↗
DOE OSTI2020

High performance context switching for virtualized FPGA accelerators

A hardware context manager in a field-programmable gate array (FPGA) device includes configuration logic configured to program one or more programming regions in the FPGA device based on configuration data for implementing a target configuration of the one or more programming regions. Context management logic in the hardware context manager is coupled with the configuration logic and saves a first context corresponding to the target configuration by retrieving first state information from the set of one or more programming regions, where the first state information is generated based on the target configuration, and storing the retrieved first state information in a context memory. The context management logic restores the first context by transferring the first state information from the context memory to the one or more programming regions, and causing the configuration logic to program the one or more programming regions based on the configuration data.

42 ENGINEERING↗
DOE OSTI2022

Investigations of Advanced Measurement Methods for High-Temperature Heat-Pipe Experiments

Various types of microreactor designs are under consideration, and among those, the heat-pipe cooled reactor designs are currently being actively investigated at Idaho National Laboratory (INL). In order to support non-nuclear testing and demonstration of technology under the Department of Energy (DOE) Microreactor Program (MRP), Single Primary Heat Extraction and Removal Emulator (SPHERE) was designed and constructed to perform high-temperature heat pipe (HP) experiments at INL. Based on the SPHERE experimental setup, this summary paper conducts the preliminary investigations among the available literature and summarizes some potential advanced measurement techniques for operando high-temperature heat pipe which can be implemented to support MRP. The primary objective for the extensive literature research is to investigate the possibilities and feasibilities for designing and construct an advanced experimental test facility with the aim of producing high-fidelity high-resolution heat pipe data during its operations.

42 ENGINEERING↗
DOE OSTI2025

Transportability of exogenous microbial community correlates with interwell connectivity in deep aquifers

Subsurface resource engineering operations often utilize continuous injection of externally-sourced water into geological reservoirs for formation pressure maintenance, resource recovery or energy/waste storage. Such injected water generally contains naturally occurring microbes. Little is known, however, about how the injectate microbes transport through geological media as a community, how such transportability is affected by injector-producer connectivity, and whether such knowledge can be utilized for flowpath characterization. In this study, we analyzed daily-to-weekly timeseries microbial community data from the injected- and produced-fluids of a ten-month flow test at a deep, well-characterized engineered aquifer. We found that the injectate microbial community was distinct from the indigenous community at the amplicon sequence variant (ASV) level, and that the transportability of injectate community towards a given producer, quantified by an “nASV-Overlap” metric we propose, had strong and significant positive correlation with known injector-producer connectivities at our site. This suggests that the better the connectivity, the higher the probability for more injectate species to flow through the interwell region and arrive at a producer. Because interwell connectivity is an important yet usually unknown parameter in subsurface resource engineering, such correlation in turn points to nASV-Overlap as a useful indicator of interwell connectivity for aquifer characterization and long-term monitoring. Based on our findings, an nASV-Overlap-based microbial tracing approach was developed for characterizing and monitoring the relative connectivities across multiple producers with a given injector. A side-by-side comparison between the new nASV-Overlap approach and traditional artificial tracer methods is presented, and their respective strengths and limitations are discussed.

Deep biosphere↗
DOE OSTI2025

Fuel Property Effects on Stochastic Preignition Events During Engine Load Transitions

Stochastic preignition (SPI) is an abnormal combustion phenomenon that can cause catastrophic engine damage. There have been several proposed mechanisms of SPI, where a uniform source is still not certain, however, SPI tendencies have been shown to be influenced by engine operating conditions, oil composition, engine age, and fuel chemical and physical properties. Laboratory research and testing for SPI propensity is challenging given the stochastic nature of events, as well as the potential for significant degradation of the engine platform and measuring equipment over time. Thus, SPI specific experiments are generally conducted under either sustained or cyclic patterning of steady-state operating conditions to avoid the influence of transient engine boundary conditions on test parameters of interest (e.g. oil additive package, fuel properties, engine speed/load, etc.). In this work a cyclically varying SPI test sequence involves a 5 min engine warmup period at a low engine load of around 4 bar gross indicated mean effective pressure (IMEPg), followed by a transition to high load (~20 bar IMEPg) at a constant 2000 rev/min engine speed for a total of 25 min. This individual test sequence load schedule is then sequentially repeated 10 times to generate significant statistical data for analysis. This work examines the influence of fuel chemical and physical properties on SPI tendency during the unsteady portion of the 10-cycle sequence (the first 5 min of the high load operation in each sequence of the loading cycle) which has been discarded from previous analyses due to the uncertainty in engine operating and thermal boundary conditions. Results from this analysis suggest an increasing trend in the ratio of SPI events during the unsteady test period relative to the steady test period with increasing fuel Reid Vapor Pressure (RVP), implying differences in uncontrolled ignition source terms, possibly from, fuel wall interactions and retention during the load transition phase of the test.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗
DOE OSTI2023

Engineering the formation of spin-defects from first principles

The full realization of spin qubits for quantum technologies relies on the ability to control and design the formation processes of spin defects in semiconductors and insulators. We present a computational protocol to investigate the synthesis of point-defects at the atomistic level, and we apply it to the study of a promising spin-qubit in silicon carbide, the divacancy (VV). Our strategy combines electronic structure calculations based on density functional theory and enhanced sampling techniques coupled with first principles molecular dynamics. We predict the optimal annealing temperatures for the formation of VVs at high temperature and show how to engineer the Fermi level of the material to optimize the defect’s yield for several polytypes of silicon carbide. Our results are in excellent agreement with available experimental data and provide novel atomistic insights into point defect formation and annihilation processes as a function of temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Estimation of the orientation of stress in the Earth’s crust without earthquake or borehole data

Abstract Mechanical stress acting in the Earth’s crust is a fundamental property that is important for a wide range of scientific and engineering applications. The orientation of maximum horizontal compressive stress can be estimated by inverting earthquake source mechanisms and measured directly from borehole-based measurements, but large regions of the continents have few or no observations. Here we present an approach to determine the orientation of maximum horizontal compressive stress by measuring stress-induced anisotropy of nonlinear susceptibility, which is the derivative of elastic modulus with respect to strain. Laboratory and Earth experiments show that nonlinear susceptibility is azimuthally dependent in an anisotropic stress field and is maximum in the orientation of maximum horizontal compressive stress. We observe this behavior in the Earth—in Oklahoma and New Mexico, U.S.A, where maximum nonlinear susceptibility coincides with the orientation of maximum horizontal compressive stress measured using traditional methods. Our measurements use empirical Green’s functions and solid-earth tides and can be applied at different temporal and spatial scales.

58 GEOSCIENCES↗