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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Neural Network Prediction of Failure of Damaged Composite Pressure Vessels from Strain Field Data Acquired by a Computer Vision Method

This effort used a new and novel method of acquiring strains called Sub-pixel Digital Video Image Correlation (SDVIC) on impact damaged Kevlar/epoxy filament wound pressure vessels during a proof test. To predict the burst pressure, the hoop strain field distribution around the impact location from three vessels was used to train a neural network. The network was then tested on additional pressure vessels. Several variations on the network were tried. The best results were obtained using a single hidden layer. SDVIC is a fill-field non-contact computer vision technique which provides in-plane deformation and strain data over a load differential. This method was used to determine hoop and axial displacements, hoop and axial linear strains, the in-plane shear strains and rotations in the regions surrounding impact sites in filament wound pressure vessels (FWPV) during proof loading by internal pressurization. The relationship between these deformation measurement values and the remaining life of the pressure vessels, however, requires a complex theoretical model or numerical simulation. Both of these techniques are time consuming and complicated. Previous results using neural network methods had been successful in predicting the burst pressure for graphite/epoxy pressure vessels based upon acoustic emission (AE) measurements in similar tests. The neural network associates the character of the AE amplitude distribution, which depends upon the extent of impact damage, with the burst pressure. Similarly, higher amounts of impact damage are theorized to cause a higher amount of strain concentration in the damage effected zone at a given pressure and result in lower burst pressures. This relationship suggests that a neural network might be able to find an empirical relationship between the SDVIC strain field data and the burst pressure, analogous to the AE method, with greater speed and simplicity than theoretical or finite element modeling. The process of testing SDVIC neural network analysis and some encouraging preliminary results are presented in this paper. Details are given concerning the processing of SDVIC output data such that it may be used as back propagation neural network (BPNN) input data. The software written to perform this processing and the BPNN algorithm are also discussed. It will be shown that, with limited training, test results indicate an average error in burst pressure prediction of approximately six percent,

Russell, Samuel S.↗
DOE OSTI2018

Simulation and Analysis of Hurricane-Driven Extreme Wave Climate Under Two Ocean Warming Scenarios

Ocean wave climate is an important area of research, particularly in the context of extremes driven by tropical cyclones (TC). We can now simulate global climate at resolutions sufficient to resolve TCs and for durations long enough to explore climatological changes. Both the devastating 2017 North Atlantic hurricane season and growing evidence for the connection between TC activity and increasing ocean temperature motivate investigation of possible future changes. We present two simulated 50-year global wave climate data sets under possible future warming scenarios characterized by +1.5°C and +2.0°C stabilized global mean temperatures that capture the effects of TCs. Differences in extreme wave climate between these possible scenarios and present-day conditions appear to be significant in many areas, particularly those affected by TCs. However, for computational feasibility, simulations of this kind rely on fixed sea surface temperatures, so we also investigate and elucidate effects from the lack of a dynamic ocean by simulating waves from a number of recent hurricanes and comparing output to observations. We conclude that atmosphere-only forcing is likely to result in an overestimate of extreme wind speeds and wave heights in TC-affected regions. More ensemble studies are needed to help elucidate detailed processes relevant to extreme wave climate, and important community projects such as the Coordinated Wave Climate Intercomparison Project (COWCLIP) should be supported.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Data handling with SAM and art at the NO v A experiment

During operations, NOvA produces between 5,000 and 7,000 raw files per day with peaks in excess of 12,000. These files must be processed in several stages to produce fully calibrated and reconstructed analysis files. In addition, many simulated neutrino interactions must be produced and processed through the same stages as data. To accommodate the large volume of data and Monte Carlo, production must be possible both on the Fermilab grid and on off-site farms, such as the ones accessible through the Open Science Grid. To handle the challenge of cataloging these files and to facilitate their off-line processing, we have adopted the SAM system developed at Fermilab. SAM indexes files according to metadata, keeps track of each file's physical locations, provides dataset management facilities, and facilitates data transfer to off-site grids. To integrate SAM with Fermilab's art software framework and the NOvA production workflow, we have developed methods to embed metadata into our configuration files, art files, and standalone ROOT files. A module in the art framework propagates the embedded information from configuration files into art files, and from input art files to output art files, allowing us to maintain a complete processing history within our files. Embedding metadata in configuration files also allows configuration files indexed in SAM to be used as inputs to Monte Carlo production jobs. Further, SAM keeps track of the input files used to create each output file. Parentage information enables the construction of self-draining datasets which have become the primary production paradigm used at NOvA. In this study we will present an overview of SAM at NOvA and how it has transformed the file production framework used by the experiment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Analysis of Cutter Blade Wear in Rotary Shear Mills

Following development of an analytical abrasive wear model to predict wear of components in a rotary shear mill, the team used a finite element analysis (FEA) approach to calculate forces and loads acting on particles responsible for abrasive wear. The analytical model related critical rotary shear process parameters (shear geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness and elastic modulus) that enabled us to model the wear of shear cutters in a rotary shear milling system developed by Forest Concepts. With proper knowledge of the forces acting between abrasive particles and cutter components built into it, the model can accurately predict wear of the cutters and provides a quality by design (QbD) approach to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches. During this reporting period, researchers at Oak Ridge National Laboratory applied an FEA package to simulate the local stresses and forces between an abrasive silica particle and two rotary shear cutters as the distance between the cutters decreases. The output of the FEA was used to provide more accurate projections of the loads applied to the particles in the analytical wear model. Comparison of the FEA force calculations are in good agreement with the loads assumed in the analytical predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Simulating competition in the US bioeconomy to produce hard‐to‐electrify transportation fuels using limited biomass resources

This study presents a novel bioeconomy optimization framework, BiOpt, designed to address critical questions regarding the strategic use of limited US biomass resources for biofuel production. By integrating detailed techno-economic analyses, life cycle assessments, and resource assessment data, BiOpt optimizes resource distributions across competing technologies to maximize economic performance and/or minimize greenhouse gas emissions. Using feedstock scenarios from the 2023 Billion Ton Study, the analysis explores optimal biomass allocations across sustainable aviation fuel, diesel, and marine biofuel conversion pathways given varying production targets and policy incentives. Results demonstrate distinct feedstock preferences and pathway utilizations when prioritizing economic returns vs. emissions reductions. For instance, fats, oils, and greases were highly favored in cost-optimized scenarios, while low-carbon feedstocks such as wet waste dominated greenhouse gas-minimized strategies. The findings underscore the pivotal role of policy incentives and technological advances in shaping biofuel supply chains and provide actionable insights for scaling sustainable biofuel production to decarbonize hard-to-electrify sectors. This framework offers a robust tool for policymakers and stakeholders to evaluate biofuel strategies that balance energy output, economic viability, and environmental impact.

09 BIOMASS FUELS↗
DOE OSTI2020

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Reconfiguring Power Systems to Minimize Cascading Failures: Models and Algorithms

The main goal of this project was to develop new scientific tools, based on optimization techniques, with the purpose of controlling and modeling cascading failures of electrical power transmission systems. We have developed a high-quality tool for simulating cascading failures. The problem of how to control a cascade was addressed, with the aim of stopping the cascade with a minimum of load lost. Yet another aspect of cascade is the investigation of which events would trigger a cascade, or more appropriately the computation of the most harmful initiating event given some constraint on the severity of the event. One common feature of the cascade models described (indeed, of several of the cascade models found in the literature) is that we study thermally-induced line tripping. We have produced a study that accounts for exogenous randomness (e.g. wind and ambient temperature) that could affect the thermal behavior of a line, with a focus on controlling the power flow of the line while maintaining safe probability of line overload. This was done by means of a rigorous analysis of a stochastic version of the heat equation. We incorporated a model of randomness in the behavior of wind power output; again modeling an OPF-like problem that uses chance-constraints to maintain low probability of line overloads; this work has been continued so as to account for generator dynamics as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Impact Outputs for A Representative Extended Duration Artemis Mission

BACKGROUND: As NASA and private industry begin preparation for long-duration spaceflight, quantifying the impact that potential human health and performance capabilities have on crew health outcomes is imperative for medical risk mitigation. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to estimate these outcomes. OVERVIEW: As NASA prepares to return to the Moon, medical system planning has already begun for extended Artemis missions, which will see humans spending months at a time in cis-lunar space and on the surface of the Moon. The Long Duration Lunar Orbital and Lunar Surface (LDLOLS) design reference mission (DRM) lasts 9 months, including 3 months on the lunar surface, and involves 2 male and 2 female crewmembers. LDLOLS assumes no extravehicular activities (EVAs) in orbit, but, while on the lunar surface, involves 2-4 EVAs/month in a pressurized rover and 2-4 EVAs/month in an unpressurized rover or on foot. This DRM assumes a physician level Crew Medical Officer with commensurate knowledge, skills, and abilities. The IMPACT tool was utilized to estimate in-flight medical risk for this mission. More specifically, 100,000 simulations of this DRM were modeled, and overall estimates for loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost (TTL; a measure of disability) were calculated. A recommended medical capability set, with appropriate mass and volume constraints, was also generated. DISCUSSION: This abstract reviews the IMPACT-derived risk for these mission outcomes with and without treatment, a macroscopic look at the total mass and volume necessary for full diagnostic and treatment capability, and how these change with input mission parameters.

J G Steller↗
DOE OSTI2018

SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data

Scientific simulations on high performance computing (HPC) platforms generate large quantities of data. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. However, a systematic solution to support these steps has been lacking in the current HPC software ecosystem. To that end, this paper develops SIRIUS, a progressive JPEG-like data management scheme for storing and analyzing big scientific data. It co-designs data decimation, compression, and data storage, taking the hardware characteristics of each storage tier into considerations. With reasonably low overhead, our approach refactors simulation data, using either topological or uniform decimation, into a much smaller, reduced-accuracy base dataset, and a series of deltas that is used to augment the accuracy if needed. The base dataset and deltas are compressed and written to multiple storage tiers. Data saved on different tiers can then be selectively retrieved to restore the level of accuracy that satisfies data analytics. Thus, SIRIUS provides a paradigm shift towards elastic data analytics and enables end users to make trade-offs between analysis speed and accuracy on-the-fly. This paper further develops algorithms to preserve statistics for data decimation, a common requirement for reducing data. Here, we assess the impact of SIRIUS on unstructured triangular meshes, a pervasive data model used in scientific simulations. In particular, we evaluate two realistic use cases: the blob detection in fusion and high-pressure area extraction in computational fluid dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

DOE-Managed HLW and SNF Research: FY15 EBS and Thermal Analysis Work Package Status.

This report examines the technical elements necessary to evaluate EBS concepts and perform thermal analysis of DOE-Managed SNF and HLW in the disposal settings of primary interest – argillite, crystalline, salt, and deep borehole. As the disposal design concept is composed of waste inventory, geologic setting, and engineered concept of operation, the engineered barrier system (EBS) falls into the last component of engineered concept of operation. The waste inventory for DOE-Managed HLW and SNF is closely examined, with specific attention to the number of waste packages, the size of waste packages, and the thermal output per package. As expected, the DOE-Managed HLW and SNF inventory has a much smaller volume, and hence smaller number of canisters, as well a lower thermal output, relative to a waste inventory that would include commercial spent nuclear fuel (CSNF). A survey of available data and methods from previous studies of thermal analysis indicates that, in some cases, thermo-hydrologic modeling will be necessary to appropriately address the problem. This report also outlines scope for FY16 work -- a key challenge identified is developing a methodology to effectively and efficiently evaluate EBS performance in each disposal setting on the basis of thermal analyses results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Discretization effects in the finite element simulation of seismic waves in elastic and elastic-plastic media

Presented here is a numerical investigation that (re-)appraises standard rules for space/time discretization in seismic wave propagation analyses. Although the issue is almost off the table of research, situations are often encountered where (established) discretization criteria are not observed and inaccurate results possibly obtained. In particular, a detailed analysis of discretization criteria is carried out for wave propagation through elastic and elastic-plastic media. The establishment of such criteria is especially important when accurate prediction of high-frequency motion is needed and/or in the presence of highly non-linear material models. Current discretization rules for wave problems in solids are critically assessed as a conditio sine qua non for improving verification/validation procedures in applied seismology and earthquake engineering. For this purpose, the propagation of shear waves through a 1D stack of 3D finite elements is considered, including the use of wide-band input motions in combination with both linear elastic and non-linear elastic-plastic material models. The blind use of usual rules of thumb is shown to be sometimes debatable, and an effort is made to provide improved discretization criteria. Possible pitfalls of wave simulations are pointed out by highlighting the dependence of discretization effects on time duration, spatial location, material model and specific output variable considered.

58 GEOSCIENCES↗
DOE OSTI2023

Laminar Burning Speed Measurements of Hydrogen/Natural Gas Mixtures

Abstract To address the shortage of fossil fuels and the environmental impact of exhaust emissions, research efforts in combustion seek to identify candidates for sustainable fuels. Hydrogen is an example, from which water is produced as the main combustion product. However, when used as neat hydrogen, it is very difficult to control hydrogen combustion due to its high flame speed, pre-ignition propensity, and flashback characteristics. One method to control hydrogen combustion is to blend it with a well-established fuel. Natural gas is a common fuel for use in engines or gas turbines. Natural gas is characterized by slow flame speeds and poor lean-burn ability; thus, engine power is decreased in the lean-burn region. Consequently, natural gas engines are typically operated at stoichiometric conditions to maximize output. Blending hydrogen to natural gas has several advantages: (i) Control of hydrogen’s ignition characteristics, (ii) extension of Natural gas’s lower flammability limit — making it easier to ignite, and (iii) reduced greenhouse gas emissions. In this study, the laminar burning speed (LBS) for neat natural gas and natural gas/hydrogen mixtures at 5 atm and 296 K were measured. Schlieren optical imaging was utilized to validate laminar flame conditions and further investigate the structure of natural gas/hydrogen flames. Results indicate that replacing 50% of natural gas with hydrogen increases the peak laminar burning velocity by a factor of ∼1.6 times. LBS simulations were conducted with NUI 1.1 and UCF NG/H2 mechanisms; Predictions by both mechanisms were found to be satisfactory for neat NG mixtures. However, for 50% NG/ 50% H2 mixture, the true LBS for fuel-lean conditions was under-predicted by both models, while predictions for fuel-rich conditions were satisfactory. Additionally, a literature review and similar experimental analysis will be performed for methane, ammonia, and hydrogen fuel blends to better understand the combustion phenomena of natural gas fuels.

Yovino, Louis↗
DOE OSTI2025

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated, including a single-, double-, and multi-lateral design. The subsurface within the area of interest is characterized by deep, hot (> 200 degrees C) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lie(s) within a target depth of 6 km, where temperatures are estimated to approach 300 degrees C. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot, dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down techno-economic analysis model. The results show that the performance- and cost-optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60 degrees C/km. By injecting 20 degrees C-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth (i.e., 2.2 MWe net plant output) can be achieved, resulting in an LCOE and LCOH of $136/MWhe and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal↗
DOE OSTI2020

Empirically verified analysis of dual pre-cooling system for hydrogen refuelling station

The dual cooling system at the California State University Los Angeles Hydrogen Research and Fueling Facility is analysed to predict the output hydrogen temperature in different ambient conditions. Initially, the facility was built with a coil chiller T20 cooling, sufficient for occasional fuelings. A flat plate evaporator system was added in series to resolve any issues for multiple fuelings even in the hottest weather. This study was commenced to verify the set points and determine the control requirements for the dual setup in order to inform future designs. A numerical-empirical model of the cooling system was developed by reverse engineering, using the station experimental measurements and database records. The subsystems are characterized separately but validated as a whole system imposing specific and standard operating conditions. The cooling model is tested with different inputs to validate the pre-set parameter variation of the cooling components. Ten scenarios were investigated to evaluate the fueling output parameters, testing two hydrogen temperature input trends (according to the facility initial conditions) and five ambient temperatures (from 15 °C to 35 °C). In closing, the simulation results have confirmed that the hydrogen output temperature remains within the range imposed by the SAE J2601 for each scenario studied, around -22 °C and -25 °C.

08 HYDROGEN↗
NASA NTRS2011

Flight Test Results of a GPS-Based Pitot-Static Calibration Method Using Output-Error Optimization for a Light Twin-Engine Airplane

As part of the NASA Aviation Safety Program (AvSP), a novel pitot-static calibration method was developed to allow rapid in-flight calibration for subscale aircraft while flying within confined test areas. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. This method has been demonstrated in subscale flight tests and has shown small 2- error bounds with significant reduction in test time compared to other methods. The current research was motivated by the desire to further evaluate and develop this method for full-scale aircraft. A goal of this research was to develop an accurate calibration method that enables reductions in test equipment and flight time, thus reducing costs. The approach involved analysis of data acquisition requirements, development of efficient flight patterns, and analysis of pressure error models based on system identification methods. Flight tests were conducted at The University of Tennessee Space Institute (UTSI) utilizing an instrumented Piper Navajo research aircraft. In addition, the UTSI engineering flight simulator was used to investigate test maneuver requirements and handling qualities issues associated with this technique. This paper provides a summary of piloted simulation and flight test results that illustrates the performance and capabilities of the NASA calibration method. Discussion of maneuver requirements and data analysis methods is included as well as recommendations for piloting technique.

Martos, Borja↗
DOE OSTI2020

Relativistic Shear Boundary Layer and the Gamma-Ray Emission of GW170817

We present an analysis of the radiation characteristics of kinetic shear boundary layers created by relativistic plasma jets. Using a model of electromagnetic field data based on particle-in-cell simulations of an electron–ion plasma, we solve the motion of individual test electrons and compute their instantaneous radiated power and peak frequency. By analyzing a large number of test electrons in this manner, we find two distinct electron populations present around the shear boundary layer. The most highly radiative electrons execute looping motion due to crossed electric and magnetic fields as they are accelerated along the bulk flow of the jet, and eventually cross the shear boundary interface at steep angles. Electrons that never cross the shear boundary interface radiate much less energy as a group. Summing over all of the highly radiative electrons, we compute the distribution of the total radiated energy as a function of the angle relative to the bulk flow. Furthermore, this result has important potential implications for the observed radiation output of short gamma-ray bursts viewed at large angles from the jet axis, such as the neutron star merger event GW170817/GRB 170817A.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Local Phasor-Based Control of DER Inverters for Voltage Regulation on Distribution Feeders

We introduce a new control paradigm termed Phasor-Based Control (PBC) to coordinate Distributed Energy Resources (DER) for improved voltage regulation and other objectives. PBC is a multi-layer control framework where the state of the distribution grid is represented by voltage phasors, and Phasor Measurement Units (PMUs) measure the state at critical points in the distribution grid. In the PBC paradigm, a supervisory controller (S-PBC) sets phasor targets which local controllers track. In this paper, we propose a Proportional Integral (PI) implementation for the local control layer (LPBC), to regulate real and reactive power output of distributed inverters to track a voltage phasor target computed by the supervisory layer. We tune the PI controller gains offline with a genetic algorithm that yields better performance than the Ziegler-Nichols method. We benchmark the proposed L-PBC controller against droop volt-var control (DVVC) and observe improved voltage regulation in simulation on the IEEE 13 node unbalanced test feeder (IEEE 13NF). Furthermore, by means of numerical simulation we observe the response of the L-PBC controllers to small and large grid disturbances. Simulations on larger feeders, IEEE 123-node and 647-node, demonstrate challenges with tuning controllers in setups with different amounts of power-voltage coupling.

42 ENGINEERING↗