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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Final Scientific/Technical Report

A variety of calcifying organisms produce a transient or metastable amorphous calcium carbonate (ACC) precursor phase that is assembled and subsequently transformed into a crystalline biomineral, typically calcite or aragonite. The complex shapes, hierarchical structures, and unique physical properties of the biominerals that result from this calcification pathway have stimulated interest in adapting these concepts for the design and creation of bio-inspired functional materials in the laboratory. ACC also forms as a reactive precursor in diverse inorganic systems and is likely to play a much broader role in calcium carbonate formation. Knowledge of the structure, composition, and behavior of this metastable phase is critical for establishing a structural and mechanistic framework for calcium carbonate formation and its role in biogeochemical processes, including carbon cycling. Minor additives, such as magnesium, phosphorus, and organic macromolecules, are known to play important roles in controlling ACC stability, transformation kinetics, and selection of final crystalline polymorph. Molecular water also occurs in many types of ACC and is thought to play a structural role in its stability and transformation behavior. One of the major challenges that remain unresolved is identification of the structural basis for the role of these minor additives and molecular water. The absence of long-range order in ACC, and other amorphous phases, has posed a challenge for study by techniques commonly used for crystalline solids. Preliminary studies in our group show that the combination of two techniques, synchrotron X-ray-based pair distribution function (PDF) analysis and nuclear magnetic resonance (NMR) spectroscopy can provide entirely new insight to structural properties of synthetic ACC over length scales that are most relevant for understanding its transformation properties. Building on preliminary experiments, we propose a systematic study of synthesis, structure, and transformation behavior in abiotic systems. The work will specifically address the influence of phosphate as a minor additive. PDF analysis will utilize total X-ray scattering data collected at synchrotron facilities optimized for this method and will provide direct characterization of the short- and intermediate-range structure of ACC synthesized under controlled conditions. Parallel computational work using reverse Monte Carlo methods will allow structural models to be constructed for a more complete analysis of PDF results. NMR spectroscopy, using a variety of single- and double-resonance techniques, will provide information on H and CO3 components, including dynamical properties, and their relationship to stabilizing additives. PDF and NMR results will be complemented by parallel studies using X-ray absorption and FT-IR spectroscopy to allow direct comparison to previous studies. These techniques will be used to follow the transformation of different ACC samples, with specific additives, to crystalline phases under controlled condition (e.g., relative humidity). This work will provide the structural and mechanistic basis for understanding ACC stability, its transformation behavior, and the factors that govern polymorph selection. This new insight will directly benefit researchers in diverse fields, as well as adding to the framework of knowledge for understanding and controlling calcium carbonate formation in natural and engineered systems.

58 GEOSCIENCES↗
DOE OSTI2021

Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Development of Passive HC/NOx Trap Catalysts for Low Temperature Gasoline Applications

This project aimed to develop fundamental understanding of the chemistry of NO adsorption and reaction in Pd/zeolites so as to facilitate the rational design of passive NOx adsorber catalysts. The approach adopted combined both experimental and computational methods, which together allow a deeper understanding of the governing chemistry than the use of either method alone. The workflow began with Pd/H-CHA and Pd/H-BEA catalyst synthesis and characterization, in which the Si/Al ratio and Al siting were systematically varied. This was followed by catalyst evaluation using temperature-programed adsorption/desorption methods, as well as in situ spectroscopic measurements to probe the chemistry of NO adsorption. In parallel, the adsorption of NO and other relevant species (H 2 O, CO, HCs) was studied by means of quantum chemical calculations in order to rationalize the experimental data and provide additional insights. Catalyst aging studies were also performed with the aim of elucidating the mechanism of catalyst degradation. Finally, the insights gained in this project were applied to the preparation of an optimized HC/NOx adsorber catalyst, the performance of which was studied using exhaust gas from an engine dynamometer.

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

Highlights from the STAR Experiment

Despite the challenges of pandemic, the years 2020-21 were quite successful for STAR. We completed the Beam Energy Scan program phase 2 and installed the forward upgrade with which STAR finished data-taking for polarized p+p collisions at 510 GeV. In this contribution, we discuss STAR results on five different topics that were presented in twenty-one parallel talks, forty-seven posters, and two flash talks at the Quark Matter 11 2022 conference.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Sensitivity Analysis and Emulation for Functional Data using Bayesian Adaptive Splines

When a computer code is used to simulate a complex system, one of the fundamental tasks is to assess the sensitivity of the simulator to the different input parameters. In the case of computationally expensive simulators, this is often accomplished via a surrogate statistical model, a statistical output emulator. An effective emulator is one that provides good approximations to the computer code output for wide ranges of input values. In addition, an emulator should be able to handle large dimensional simulation output for a relevant number of inputs; it should flexibly capture heterogeneities in the variability of the response surface; it should be fast to evaluate for arbitrary combinations of input parameters, and it should provide an accurate quantification of the emulation uncertainty. In this paper we discuss the Bayesian approach to multivariate adaptive regression splines (BMARS) as an emulator for a computer model that outputs curves. We introduce modifications to traditional BMARS approaches that allow for fitting large amounts of data and allow for more efficient MCMC sampling. We emphasize the ease with which sensitivity analysis can be performed in this situation. We present a sensitivity analysis of a computer model of the deformation of a protective plate used in pressure-driven experiments. Our example serves as an illustration of the ability of BMARS emulators to fulfill all the necessities of computability, flexibility and reliable calculation on relevant measures of sensitivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Active Time Domain Reflectometry for Tamper Indication in Unattended Safeguards Systems

The International Atomic Energy Agency (IAEA) continues to expand its use of unattended measurement systems. An increasing number of systems and an expanding family of instruments create challenges in terms of deployment efficiency and the implementation of data authentication measures. In collaboration with the IAEA, tamper-indicating measures to address data-transmission authentication challenges with unattended safeguards systems are under investigation. Pacific Northwest National Laboratory is studying the viability of active time-domain reflectometry (TDR) along two parallel but interconnected paths: (1) swept-frequency TDR as the highly flexible, laboratory gold standard to which field-deployable options can be compared, and (2) a low-cost commercially available spread-spectrum TDR technology as one option for field implementation. This paper describes the TDR methods under investigation and the associated benchtop test-bed, tampering scenarios of interest,, and viability measurement results to date (e.g., comparison of relative sensitivity to tamper scenarios).

Sheen, David M.↗
DOE OSTI2025

Sensor Co-design for $\textit{smartpixels}$

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trigger for a hadron collider. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (``cluster''). To design a viable detector for deployment at an experiment, the dependence of the NN as a function of the sensor geometry, external magnetic field, and irradiation must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector depth. An external magnetic field parallel to the sensor plane induces Lorentz drift of the electron-hole pairs produced by the charged particle, broadening the cluster and improving the network performance. The absence of the external field diminishes the background rejection compared to the baseline by $\mathcal{O}$(10%). Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by $\sim$ 30 - 60%, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.

Shekar, Danush [Illinois U., Chicago]↗
DOE OSTI2019

Detoured flight direction responses along the southwest coast of Lake Erie by night-migrating birds

Abstract Migratory birds encounter the Great Lakes while moving through eastern North America toward breeding grounds to the North, which offers a good opportunity to study variation in migratory behavior as birds face a potentially influencing topographical feature. Using passive infrared technology, we documented the direction of relatively low-flying, nocturnal, mostly passerine migration in spring along the southern coast of Lake Erie’s western basin. We examined the extent to which spring migrants flew across Lake Erie as a continuation of the inland, northeasterly broad front migratory direction, as determined by weather radar and infrared observations, or displayed a tendency to deviate to more closely follow the direction of the coastline. We found that an estimated 62% of all low-flying migrants deviated their flight directions toward the coast of Lake Erie at 2 coastal sites, Cedar Point and Ottawa, which were characterized by northwest–southeast oriented coastlines. Migrants at a third coastal location, Maumee Bay, which has a more east–west oriented coastline, did not display similarly deviated flight directions. We found that even when winds were energetically favorable for a lake crossing, many migrants still routinely displayed deviated flight directions that approached paralleling the coastline. Further, the mean flight direction at one site, Ottawa, shifted more in the direction of the coastline as the night progressed, suggesting that time of night could influence the shift to a more coastal flight direction. The data indicate that the western basin of Lake Erie acts as a salient topographical feature influencing the flight directions of nocturnal migrants. The data further suggest that birds are making active decisions while in flight, based on current environmental and physiological conditions, about whether to continue to cross Lake Erie or take a coastal detour.

Zoology↗
DOE OSTI2015

Development of a 5 MW reference gearbox for offshore wind turbines: 5 MW reference gearbox

This paper presents detailed descriptions, modeling parameters and technical data of a 5MW high-speed gearbox developed for the National Renewable Energy Laboratory offshore 5MW baseline wind turbine. The main aim of this paper is to support the concept studies and research for large offshore wind turbines by providing a baseline gearbox model with detailed modeling parameters. This baseline gearbox follows the most conventional design types of those used in wind turbines. It is based on the four-point supports: two main bearings and two torque arms. The gearbox consists of three stages: two planetary and one parallel stage gears. The gear ratios among the stages are calculated in a way to obtain the minimum gearbox weight. The gearbox components are designed and selected based on the offshore wind turbine design codes and validated by comparison to the data available from large offshore wind turbine prototypes. All parameters required to establish the dynamic model of the gearbox are then provided. Moreover, a maintenance map indicating components with high to low probability of failure is shown. The 5 MW reference gearbox can be used as a baseline for research on wind turbine gearboxes and comparison studies. It can also be employed in global analysis tools to represent a more realistic model of a gearbox in a coupled analysis.

17 WIND ENERGY↗
DOE OSTI2021

FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking

In this work, we present the Feature Tracking Kit (FTK), a framework that simplifies, scales, and delivers various feature-tracking algorithms for scientific data. The key of FTK is our simplicial spacetime meshing scheme that generalizes both regular and unstructured spatial meshes to spacetime while tessellating spacetime mesh elements into simplices. The benefits of using simplicial spacetime meshes include (1) reducing ambiguity cases for feature extraction and tracking, (2) simplifying the handling of degeneracies using symbolic perturbations, and (3) enabling scalable and parallel processing. The use of simplicial spacetime meshing simplifies and improves the implementation of several feature-tracking algorithms for critical points, quantum vortices, and isosurfaces. As a software framework, FTK provides end users with VTK/ParaView filters, Python bindings, a command line interface, and programming interfaces for feature-tracking applications. We demonstrate use cases as well as scalability studies through both synthetic data and scientific applications including tokamak, fluid dynamics, and superconductivity simulations. We also conduct end-to-end performance studies on the Summit supercomputer. FTK is open sourced under the MIT license: https://github.com/hguo/ftk.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗
DOE OSTI2020

Turbulence driven widening of the near-SOL power width in ASDEX Upgrade H-Mode discharges

Divertor heat flux data from infra red (IR) from various tokamaks in H-Mode regime show that the power width, $\lambda_{q}$, scales approximately like 1.6 $(R/a) ρ_{s,pol}$. However, the IR based scaling comes with the restriction that only discharges were considered with attached divertor conditions. Here we set up a new data base covering low edge density data but also including high density plasmas reaching the H-mode density limit. We use Thomson-scattering to measure the electron temperature decay length which will set the near-SOL power width through parallel heat conduction. We present scaling results for the density, temperature and pressure separatrix fall-off lengths. As the principal result we derive a generalized power width scaling which reads as $\lambda_{q}\propto\,\rho_{s,pol}\cdot(1+2.1\alpha_{t}^{1.7})$ where $\alpha_{t}$ describes a normalized collisionality ($\alpha_{t} = 3\cdot\,10^{-18}\,R\,q^2\,n\,Z_{eff}T^{-2}$). The parameter $\alpha_{t}$ describes the relative importance of the interchange effect on drift-wave turbulence as proposed by Scott and is found to be closely linked to the diamagnetic parameter αd introduced by Rogers, Drake and Zeiler (RDZ). The edge operational space for ASDEX Upgrade displays a boundary qualitatively in agreement with the region labelled as density limit in the edge plasma phase space proposed by RDZ. The data base shows in the limit of low edge densities ($\alpha_{t}\simeq\,0.2$) accurate agreement to the IR based power width scaling. At elevated separatrix densities ($\alpha_{t}\simeq\,1$) the power width is broadened by a factor of up to about three accompanied by a reduction of the $\text{H}_{98,y2}$ confinement factor. Finally, plasmas with higher triangularity show higher values for $\text{H}_{98,y2}$ in the same range of normalized collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Solar wind magnetic fluctuations and electron non-thermal temperature anisotropy: survey of Wind-SWE-VEIS observations

The solar wind electron velocity distribution function (eVDF) exhibits a variety of non-thermal features that deviate from thermal equilibrium. These deviations from equilibrium provide a local source for electromagnetic fluctuation emissions, including the commonly observed electron whistler-cyclotron and firehose instabilities. We present a systematic analysis of Wind-SWE-VEIS observations of solar wind electron plasma and associated Wind-MFI observed magnetic fluctuations. For the first time using the full solar wind electron distribution and its moments, without separation of the various electron components, we show clear evidence that the temperature anisotropy threshold of the parallel electron cyclotron anisotropic instability bounds solar wind electrons during slow solar wind periods. We also demonstrate that during periods of slow solar wind, collisions—while infrequent—are the dominant mechanism by which solar wind electrons are constrained, leading to isotropization. During fast solar wind periods, magnetic fluctuations and solar wind anisotropies are enhanced above the parallel whistler anisotropic threshold boundary and collisional effects are significantly reduced. Preliminary calculations further show that the oblique electron whistler mirror anisotropic instability bounds both the slow and fast solar wind. Regardless of speed, the solar wind electron thermal anisotropy appears globally bounded by the parallel electron firehose instability for anisotropies T{sub e⊥}/T{sub e||}<1. Our results indicate that collisions, while infrequent, play a necessary role in regulating the solar wind eVDFs. In striking contrast to solar wind ions, solar wind electron plasma, when considered globally as a single eVDF, is only marginally stable with respect to parallel propagating instabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

FTP 100: An Ultra-High Speed Data Transfer Service Over Next Generation 100 Gigabit Per Second Network

Data-intensive applications, including high energy and nuclear physics, astrophysics, climate modeling, nano-scale materials science, genomics, and financing, are expected to generate exabytes of data over the coming years, which must be transferred, visualized, and analyzed by geographically distributed teams of users. High-performance network capabilities must be available to these users at the application level in a transparent, virtualized manner. Moreover, the application users must have the capability to move large datasets from local and remote locations across network environments to their home institutions. To solve these challenges, the main goal of our project is to design and evaluate high-performance data transfer software to support various data-intensive applications. First, we have designed a middleware software that provides access to Remote Direct Memory Access (RDMA) functionalities. This middleware integrates network access, memory management and multitasking in its core design. We address a number of issues related to its efficient implementation, for instance, explicit buffer management and memory registration, and parallelization of RDMA operations, which are vital to delivering the benefit of RDMA to the applications. Built on top of this middleware, an implementation and experimental evaluation of the RDMA-based FTP software, RFTP, is described and evaluated. This application has been implemented by our team to exploit the full capabilities of advanced RDMA mechanisms for ultra-high speed bulk data transfer applications on Energy Sciences Network (ESnet). Second, we designed our data transfer software to optimize TCP/IP based data transfer performance such that RFTP can be fully compatible with today’s Internet. Our kernel optimization techniques with Linux system calls sendfile and splice, can reduce data copy cost. In this report, we summarize the technical challenges of our project, the primary software design methods, the major project milestones achieved, as well as the testbed evaluation work and demonstrations during our project life time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Iterative Importance Sampling Algorithms for Parameter Estimation

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is a challenging task. Several sampling algorithms have been proposed over the past years that take an iterative approach to constructing a proposal distribution. We investigate the applicability of such algorithms by applying them to two realistic and challenging test problems, one in subsurface flow, and one in combustion modeling. More specifically, we implement importance sampling algorithms that iterate over the mean and covariance matrix of Gaussian or multivariate t-proposal distributions. Our implementation leverages massively parallel computers, and we present strategies to initialize the iterations using “coarse” MCMC runs or Gaussian mixture models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Understanding scale-dependent soft-error behavior of scientific applications

Analyzing application fault behavior on large-scale systems is time-consuming and resource-demanding. Currently, researchers need to perform fault injection campaigns at full scale to understand the effects of soft errors on applications and whether these faults result in silent data corruption. Both time and resource requirements greatly limit the scope of the resilience studies that can be currently performed. In this work, we propose a methodology to model application fault behavior at large scale based on a reduced set of experiments performed at small scale. We employ machine learning techniques to accurately model application fault behavior using a set of experiments that can be executed in parallel at small scale. Our methodology drastically reduces the set and the scale of the fault injection experiments to be performed and provides a validated methodology to study application fault behavior at large scale. We show that our methodology can accurately model application fault behavior at large scale by using only small scale experiments. In some cases, we can model the fault behavior of a parallel application running on 4,096 cores with about 90% accuracy based on experiments on a single core.

Kestor, Gokcen G.↗
DOE OSTI2019

Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays

The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using Global Arrays (GA). To analyze parallel performance, DHSVM was used to simulate two significantly sized river basins located in northwest continental United States and southwest Canada at 90~m resolution: (1) Clearwater (25,000~km2) and (2) Columbia (668,000~km2). Meteorological forcing applied to both basins was dynamically down-scaled from a global circulation model using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps each time step. We report parallel code speed up was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum speed up of 105 was attained with 480 processors while simulating the Columbia basin. Speed up was limited by input dominated tasks, particularly the input of meteorological forcing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Violation of Field Line Conservation and Associated Spatial Scales in Particle-in-Cell Simulations and MMS Data

For the first time, space flight technology exists to detect, in situ, violation of magnetic field line conservation. The violation of magnetic line conservation on scales smaller than the system size is a necessary and sufficient condition for finite magnetic field reconnection. We demonstrate that violation of line conservation produces a detectable, structured signature both in particle-in-cell simulations of reconnection and in data from the Magnetospheric Multi-Scale mission. In particle-in-cell simulations of asymmetric reconnection, the quantity—which we call M—that identifies this violation achieves significant values in electron skin depth-scale layers that extend away from the separator, with higher values emerging on the low-density, high-magnetic-field side of the current sheet. At the separator, M owes largely to perpendicular gradients in the parallel electric field, while it attains its highest values away from the separator in dispersed, layered structures associated with gradients in the perpendicular nonideal electric field and electron transport. Sub-ion scale bipolar forms of the quantity also appear further from the separator. In two MMS burst data intervals detecting the electron diffusion region, we find that M exceeds measurement uncertainties both at the separator and near the separatrices. One interval has highly sheared reconnecting fields and the other a stronger guide field. For one event, we determine the location and scale of M and the inner electron diffusion region relative to electron outflows and the magnetic separatrices. The measure can therefore serve as a potent diagnostic for magnetic reconnection in space measurements.

79 ASTRONOMY AND ASTROPHYSICS↗