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At least 37 records · Page 2

Unsteady Extinction of Opposed Jet Ethylene/Methane HIFiRE Surrogate Fuel Mixtures vs Air

A unique idealized study of the subject fuel vs. air systems was conducted using an Oscillatory-input Opposed Jet Burner (OOJB) system and a newly refined analysis. Extensive dynamic-extinction measurements were obtained on unanchored (free-floating) laminar Counter Flow Diffusion Flames (CFDFs) at 1-atm, stabilized by steady input velocities (e.g., U(sub air)) and perturbed by superimposed in-phase sinusoidal velocity inputs at fuel and air nozzle exits. Ethylene (C2H4) and methane (CH4), and intermediate 64/36 and 15/85 molar percent mixtures were studied. The latter gaseous surrogates were chosen earlier to mimic ignition and respective steady Flame Strengths (FS = U(sub air)) of vaporized and cracked, and un-cracked, JP-7 "like" kerosene for a Hypersonic International Flight Research Experimentation (HIFiRE) scramjet. For steady idealized flameholding, the 100% C2H4 flame is respectively approx. 1.3 and approx.2.7 times stronger than a 64/36 mix and CH4; but is still 12.0 times weaker than a 100% H2-air flame. Limited Hot-Wire (HW) measurements of velocity oscillations at convergent-nozzle exits, and more extensive Probe Microphone (PM) measurements of acoustic pressures, were used to normalize Dynamic FSs, which decayed linearly with pk/pk U(sub air) (velocity magnitude, HW), and also pk/pk P (pressure magnitude, PM). Thus Dynamic Flame Weakening (DFW) is defined as % decrease in FS per Pascal of pk/pk P oscillation, namely, DFW = -100 d(U(sub air)/U(sub air),0Hz)/d(pkpk P). Key findings are: (1) Ethylene flames are uniquely strong and resilient to extinction by oscillating inflows below 150 Hz; (2) Methane flames are uniquely weak; (3) Ethylene / methane surrogate flames are disproportionately strong with respect to ethylene content; and (4) Flame weakening is consistent with limited published results on forced unsteady CFDFs. Thus from 0 to approx. 10 Hz and slightly higher, lagging diffusive responses of key species led to progressive phase lags (relative to inputs) in the oscillating flames, and caused maximum weakening. At 20 to 150 Hz, diffusion-rate-limited effects diminished, causing flames to "regain strengnth," and eventually become completely insensitive beyond 300 Hz. Detailed mechanistic understanding is needed. Overall, ethylene flames are remarkably resilient to dynamic extinction by oscillating inflows. They are the strongest, with the notable exception of H2. For HIFiRE tests, the 64%/36% surrogate disproportionally retains the high dynamic FS of ethylene, so the potential for loss of scramjet flameholding (flameout) due to low frequency oscillations is significantly mitigated.

Vaden, Sarah N.↗

Search for a charged Higgs boson decaying into a heavy neutral Higgs boson and a W boson in proton-proton collisions at $ \sqrt{s}$ = 13 TeV

A search for a charged Higgs boson H ± decaying into a heavy neutral Higgs boson H and a W boson is presented. The analysis targets the H decay into a pair of tau leptons with at least one of them decaying hadronically and with an additional electron or muon present in the event. The search is based on proton-proton collision data recorded by the CMS experiment during 2016–2018 at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb –1 . The data are consistent with standard model background expectations. Upper limits at 95% confidence level are set on the product of the cross section and branching fraction for an H ± in the mass range of 300–700 GeV, assuming an H with a mass of 200 GeV. The observed limits range from 0.085 pb for an H ± mass of 300 Ge V to 0.019 pb for a mass of 700 GeV. These are the first limits on H ± production in the H ± → HW ± decay channel at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble

The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Furthermore, compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.

54 ENVIRONMENTAL SCIENCES↗

ESGF project plan for ramping down development activities and transition the project and data to a new team

This document summarizes the current software development activities carried by the ESGF team with planned delivery dates before the transition of the project to a new team. The work we started on the publishing, search and retrieval, and the backend for indexing and data management that can be deployed using Kubernetes are planned to be delivered within the next three months; however, this assumes that the current team members will continue to work on the project. The activities are listed in Table 1 by priority and in case we lose team members, development of lower priority tasks can be paused and passed to the new team with its current status. Team members can be re-assigned based on their availability and transition work needed. Table 2 below describe activities necessary to help project transition to the new team. Deadlines for these activities are before October 1 st of 2022 or the completion of a successful transition. Support during the transition period assumes that we will have 3 key ESGF members and the ESGF PI supported at the 50% level or less for the duration of the transition. The level of support is an estimate, and it depends on several factors that cannot be decided at this time. The total cost of the proposed work and support activities for fiscal year 2021 is $1,270K with $230K carry over to fiscal year 2022. The cost for the support work listed in Table 2 is the sum of the two rows “HW support” and “project support, maintenance, and transition efforts”, colored blue, in Table1 which adds up to $720K. This cost is included in the $1,270K cost in table 1.

97 MATHEMATICS AND COMPUTING↗

Controls Optimization Final Report, Controls Algorithms Report, Control Optimization - SPA II: Heaving Buoy Test Results [Three reports]

The over-arching project objective is to fully develop and validate optimal controls frameworks that can subsequently be applied widely to different WEC devices and concepts. Optimal controls of WEC devices represent a fundamental building block for WEC designers that must be considered as an integral part of every stage of device development. Using a building-blocks approach to optimal controls development, this effort will result in the full development of a feed-forward and feed-back control approach and a wave prediction system. Phase I focused primarily on numerical offline optimization and validation using wave tank testing of three industry partners’ WEC devices, including; CalWave, Ocean Energy, and Resolute Marine Energy. These industry partnerships allowed us to identify optimal control strategies for these different WEC topologies at different maturity levels. Phase II focused on demonstrating an integrated control system on an at-sea prototype that is to be custom-built and maturing the HW and SW required to successfully run our advanced controls code frameworks on at-sea systems. A secondary focus during phase II is to adapt our systems identification, controls and wave-prediction frameworks to become more robust and comprehensive in respect to RT capability, robustness, and reliability.

16 TIDAL AND WAVE POWER↗

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗

Comparing Calibration Algorithms for the Rapid Characterization of Pretreated Corn Stover Using Near-Infrared Spectroscopy

Rapid characterization of biomass composition is a key enabling technology for biorefineries—the ability to measure the chemical composition of biomass materials entering the biorefinery as well as the composition of key process intermediate streams would allow real-time process control and the development of robust models to predict process performance. The utility of near-infrared (NIR) spectroscopy for rapid characterization requires multivariate algorithms for building calibration models. The most prevalent algorithm used for building calibration models using NIR spectra is the linear modeling algorithm Partial Least Squares Regression (PLS). Nonlinear regression algorithms (which are typically more computationally intensive than linear modeling approaches) have gained popularity in recent years due to their ability to solve a wide variety of classification and regression problems and the dramatic increase in available computational resources. In this work, we demonstrate that a calibration model can predict the composition of corn stover process intermediate samples pretreated with three different treatments—hot water (HW), dilute acid (DA), and deacetylation followed by dilute acid (DDA). We quantitatively compare three different algorithms for building prediction models based on near-infrared spectroscopy—partial least squares (PLS), support vector machines (SVM), and random forests (RF). We demonstrate the utility of improving model performance by accounting for instrument performance variability using repeated measurements of standard materials (e.g., the “repeatability file” strategy) and investigate its performance with nonlinear regression techniques, and we discuss methods for quantifying the uncertainties of specific predictions among the three methods.

09 BIOMASS FUELS↗

X-ray diffractometer studies of shocked materials

This study explores the utility of X-ray diffractometer scans for determination of shock pressure histories of geological materials from meteorite impact sites. The technique is based on quantification of increased crystal lattice disorder with increasing shock pressure as expressed by decreasing diffraction peak amplitude and pronounced line-broadening caused by decreasing mosaic domain size and increasing strain. The ratio of peak height (PH) to half width (HW) decreases systematically with increasing shock pressure. Data are given for experimentally shocked quartz, feldspars, pyroxene and olivine along with data for granitic materials from the Piledriver nuclear event and from the Ries Crater, Germany. Although the technique in principle may be capable of yielding relatively accurate pressure determinations, its application to naturally shocked materials may be severely limited.

Hanss, R. E.↗

Supersymmetric dark matter above the W mass

The cosmological consequences are studied for the minimal supersymmetric extension of the standard model in the case that the neutralino is heavier than W. The cross section was calculated for annihilation of heavy neutralinos into final states containing gauge and Higgs bosons (XX yields WW, ZZ, HH, HW, HZ), where X is the lightest, nth neutralino and the results are compared with the results with those previously obtained for annihilation into fermions to find the relic cosmological abundance for the most general neutralino. The new channels are particularly important for the Higgsino-like and mixed-state neutralinos, but are sub-dominant (to the fermion-antifermion annihilation channels) in the case that the neutralino is mostly a gaugino. The effect of the top quark mass is also considered. Using these cross sections and the cosmological constraint omega(sub X)h squared is less than or approximately 1, the entire range of cosmologically acceptable supersymmetric parameter space is mapped and a very general bound on the neutralino mass is discovered. For a top quark mass of less than 180 GeV, neutralinos heavier than 3200 GeV are cosmologically inconsistent, and if the top quark mass is less than 120 GeV, the bound is lowered to 2600 GeV. Neutralino states that are mostly gaugino are constrained to be lighter than 550 GeV. It is found that a heavy neutralino that contributes omega(sub X) is approximately 1 arises for a very wide range of model parameters and makes, therefore, a very natural and attractive dark matter candidate.

Griest, Kim↗

Smaller Coaxial-View Welding Torch

Coaxial-view torch for gas/tungsten arc welding has only two-thirds length and width of its predecessor. Shape and size similar to that of commercial arc-welding torch (Linde HW-27 or equivalent), even though it contains lens system. Collet that holds electrode has unique design allowing greater passage of light. Used in small spaces previously inaccessible, also introduced into production welding operations with minimum of disturbance.

Gangl, Kenneth J.↗

Size Exclusion Chromatography Studies of the Initial Self-Association Steps of Chicken Egg White Lysozyme Nucleation

Nucleation is one of the least understood aspects of crystallogenesis. In the case of macromolecule nucleation, this understanding is further hampered by uncertainty over what precisely is being discussed. We define the process of solute self-association (aggregation, oligomerization, interaction, clustering, etc.) whereby n-mers (n > or = 2) having a crystallographic or nascent crystallographic arrangement leading to the critical nucleus reversibly form in the solution, to be part of the nucleation process. This reversible self-association process is a fundamental part of the nucleation process, and occurs as a function of the solute concentration. In the case of chicken egg white lysozyme, a considerable body of experimental evidence leads us to the conclusion that it also forms the crystal growth units. Size exclusion chromatography is a simple and direct method for determining the equilibrium constants for the self-association process. A Pharmacia FPLC system was used to provide accurate solution flow rates. The column, injection valve, and sample loop were all mounted within a temperature-controlled chamber. Chromatographically re-purified lysozyme was first dialyzed against the column equilibration buffer, with injection onto the column after several hours pre-incubation at the running temperature. Preliminary experiments, were carried out using a Toyopearl HW-50F column (1 x 50cm), equilibrated with 0.1 M sodium acetate, 5% sodium chloride, pH 4.6, at 15C. Protein concentrations from 0.1 to 4 mg/ml were employed (C(sub sat) = 1.2 mg/ml). The data from several different protein preparations consistently shows a progressively decreasing elution volume with increasing protein concentration, indicating that reversible self-association is occurring. The dotted line indicates the monomeric lysozyme elution volume. However, lysozyme interacts with the column matrix in these experiments, which complicates data analysis.Accordingly, we are testing silica-based HPLC columns in an effort to eliminate this problem and substantially reduce the column volume and experimental run time. The results and data analysis from these and subsequent experiments will be presented.

Ewing, Felecia↗

A survey of the chemical properties of the M17 and Cepheus A cloud cores

We present the results of a systematic survey of the chemical properties of two giant molecular cloud (GMC) cores in M17 and Cepheus A. In all, we have mapped the emission from 32 molecular transitions of 13 molecules and seven isotopic variants over a 4' x 5' region in each core. Each map includes known sites of massive star formation, as well as the more extended quiescent material. In M17 most molecules have emission peaks away from the H II region/molecular cloud interface, while two species, HC3N and CH3C2H, deviate from this structure with sharp maxima closer to this interface. In Cepheus A the core is influenced by a compact high-velocity molecular outflow and a more extended low-velocity flow. The molecular emission distributions in this source are generally quite similar, with most molecules peaking near the center of the core to the east of the compact H II region HW 2. A few molecules, SO, CH3OH, H13CN, and C18O, have more extended emission. Only two molecules, CO and HCO+, appear to trace the high- and low-velocity outflows; all other species are tracing the quiescent core. We have used the results of previous studies of the density and temperature of the dense gas in the same cloud cores to derive accurate abundances relative to CO for several positions in each core. The principal result is that the chemical composition of all the cores we have surveyed (which include OMC-1 as well as M17 and Cepheus A) show remarkable similarity, both within a given core and among the cores. This suggests that the chemical processes are similar in quiescent GMC core material. In M17 the lack of variation of molecular abundances is remarkable because the radiation field and the gas temperature are known to vary appreciably throughout the surveyed region, suggesting that the bulk of the emission arises from gas that is well shielded from radiation.

Non-NASA Center↗

Rotorcraft Diagnostics

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Haste, Deepak↗

Is Structured Agile an Oxymoron? Tales from Implementing and Executing Agile in a US Government Environment

To paraphrase a famous quote, "No plan survives contact with the reality." Software (SW) development is often a classic example of this: whatever the plan was for a particular development, it often does not survive contact with technical realities, budget realities, program realities and schedule realities. Traditionally, SW development has followed a waterfall methodology with requirements being rigorously specified before the design, which was completed before the coding and unit testing started, which were in turn finished before validation and verification started. This model of SW engineering derives much from the HW engineering of large systems, and has been the standard methodology used in US government software acquisitions and systems for decades, with highly variable results. US Government SW requirements are built around Waterfall concepts, which assume that the plan will survive contact with reality, or at least that modifications to the plan are relatively small, and relatively few.Because of the inefficiencies and difficulties inherent in Waterfall, the commercial SW world started using a different SW development methodology called Agile more than 20 years ago. Agile believes that a plan should evolve and learn rapidly in response to the realities encountered. At its core, there are a few key elements of Agile:- A small team of people which is highly flexible and adaptive. The team collaborates and interoperates through sophisticated development architectures and release environments- An iterative, incremental development and release approach which is based upon the concept that knowledge comes from experience within the team, and that the team makes decisions based upon what it knows- A team culture which prizes transparency, inspection and adaptation. These values are necessary so that the team experience and decision making is transparent and responsive to the realities encountered during development and testingSo, how to use Agile in a US Government environment? GMSEC (Goddard Mission Services Evolution Center) develops satellite ground system software for NASA and other US Government agencies. The SW developed by the team contains a large code base of many applications used within satellite mission operations centers. It spans the full gamut of SW development types: from SW which is in a classic maintenance and sustainment mode, to new developments with a fairly well understood scope and approach, to new developments whose scope and approach are quite unclear and which require significant research and prototyping. Team members move between all of these different types of SW development. Waterfall was inadequate to the programmatic and technical needs of the team, as well as the various types of SW development being done. The software plan was not surviving contact with the technical and programmatic realities experienced by the team. To address this, the team started a small pilot project in 2016 to test the use of Agile within a small subset of the team for a new web services application. In early 2018, the use of Agile was expanded to the whole team and all the software, but we had to fulfill the NASA SW development requirements. And we needed to do this while still remaining true to the key Agile elements of transparency, inspection and adaption. In order to do this, the team worked very closely with the Software Process Improvement (SPI) team at NASA Goddard, as well as NASA engineering manageme

Beech, Theresa W.↗

Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning

It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational footprints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.

Drgona, Jan↗

Modeling Contact Angle vs. Temperature for the Quartz-Water-Decane System

Innovative approaches are needed to improve the efficiency of oil recovery technologies to meet the growing demands of fossil-fuel based energy consumption. Enhanced oil recovery (EOR) methods such as low-salinity waterflooding and chemically tuned waterflooding aim to optimize the reservoir’s wetting properties, detaching oil globules from rock surfaces and allowing easier oil flow through pore throats. This wetting behavior is commonly quantified by contact angle measurements of the rock-oil-brine interface, which have been thoroughly investigated and theorized for many systems at ambient temperatures and pressures. However, few studies exist for extending contact angle theories away from ambient conditions. In this paper, we model the contact angles of a quartz-water-decane system at elevated temperatures using the surface tension component (STC) approach. Temperature-dependent van der Waals [Lifshitz-van der Waals (LW)] interactions and hydrogen-bonding (acid-base) interactions were calculated and are incorporated into the model for the quartz-water-decane interface. Additionally, the Hough and White procedure was used to create temperature-dependent dielectric functions of quartz, water, and normal decane for calculations of Hamaker coefficients. Hamaker coefficients calculated this way are highly linear with temperature and agree well with Israelachvili’s approximation. The acid-base interactions likely contribute the most to system wettability changes. Resulting contact angles of the quartz-water-decane system shift from water-wet (16°) to slightly water-wet (57.4°) as temperature increases. The model was also successfully verified for the quartz-air-water system. Our results can be used in future studies to determine optimal injected water compositions for specific rock-oil-brine and other systems with consideration of reservoir temperature.

02 PETROLEUM↗