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At least 1,189 records · Page 66

Simulations of Firn Processes Over the Greenland and Antarctic Ice Sheets: 1980-2021

Conversion of altimetry-derived ice-sheet volume change to mass requires an understanding of the evolution of the combined ice and air content within the firn column. In the absence of suitable techniques to observe the changes to the firn column across the entirety of an ice sheet, the firn column processes are typically modeled. Here, we present new simulations of firn processes over the Greenland and Antarctic ice sheets (GrIS and AIS) using the Community Firn Model and atmospheric reanalysis variables for more than four decades. A data set of more than 250 measured depth–density profiles from both ice sheets provides the basis of the calibration of the dry-snow densification scheme. The resulting scheme results in a reduction in the rate of densification, relative to a commonly used semi-empirical model, through a decreased dependence on the accumulation rate, a proxy for overburden stress. The 1980–2020 modeled firn column runoff, when combined with atmospheric variables from MERRA-2, generates realistic mean integrated surface mass balance values for the Greenland (+390 Gt yr(exp −1)) and Antarctic (+2612 Gt yr(exp −1)) ice sheets when compared to published model-ensemble means. We find that seasonal volume changes associated with firn air content are on average approximately 2.5 times larger than those associated with mass fluxes from surface processes for the AIS and 1.5 times larger for the GrIS; however, when averaged over multiple years, ice and air-volume fluctuations within the firn column are of comparable magnitudes. Between 1996 and 2019, the Greenland Ice Sheet lost nearly 5% of its firn air content, indicating a reduction in the total meltwater retention capability. Nearly all (94 %) of the meltwater produced over the Antarctic Ice Sheet is retained within the firn column through infiltration and refreezing.

Greenland↗

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reduction and analysis of seasons 15 and 16 (1991 - 1992) Pioneer Venus radio occultation data and correlative studies with observations of the near-infrared emission of Venus

Radio occultation experiments, and radio astronomical observations have suggested that significant variations (both spatial and temporal) in the abundances of sulfur-bearing gases are occurring below the Venus cloud layers. In addition, recent Near Infra-Red images of the nightside of Venus revealed large-scale features which sustain their shape over multiple rotations (the rotation periods of the features are 6.0 +/- 0.5 days). Presumably, the contrast variations in the NIR images are caused by variations in the abundance of large particles in the cloud deck. If these particles are composed of liquid sulfuric acid, one would expect a strong anticorrelation between regions with a high abundance of sulfuric acid vapor, and regions where there are large particles. One technique for monitoring the abundance and distribution of sulfuric acid vapor (H2SO4) at and below the main Venus cloud layer (altitudes below 50 km) is to measure the 13-cm wavelength opacity using Pioneer Venus Orbiter Radio Occultation Studies (PV-ORO). We are working to characterize variations in the abundance and distribution of subcloud H2SO4(g) in the Venus atmosphere by using a number of 13-cm radio occultation measurements conducted with the Pioneer Venus Orbiter near the inferior conjunction of 1991. When retrieved, the vertical profiles of the abundance of H2SO4(g) will be compared and correlated with NIR images of the night side of Venus made during the same period of time. Hopefully, the combination of these two different types of data will make it possible to constrain or identify the composition of the large particles causing the features observed in the NIR images. Considered on their own, however, the parameters retrieved from the radio occultation experiments are valuable science products.

Jenkins, Jon M.↗

Toward the Analytic Bootstrap of Energy Correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in N = 4 N=4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators with equal and unequal energy weights, where the latter are crucial ingredients for projected N N-point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

Gong, Jianyu [State Key Laboratory]↗

Characterization and Optimization of the Fitting of Quantum Correlation Functions

This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.

Chuang, Pi-Yueh [Virginia Tech,Dept. of Computer S↗

Rapid data comparison technique development for N-ray/X-ray analysis

An operational N-ray/X-ray computer analysis system for nondestructive testing problems was realized by developing: (1) more efficient data transfer routines for use in existing image processing systems; (2) the capability to store and analyze multiple N-ray/X-ray images; (3) an efficient 2-D Fast Fourier Transform; and (4) transfer functions compensation capability to correct for distortions and nonlinearities of N-rays/X-rays. Applications of the technique are summarized for the following: thermal protection system tile with hydraulic fluid; thermal protection system tile with corrosion; thermal protection system tile debonding; stainless steel tubing corrosion; defective electrical devices; fast film restoration and deblur; corrosion tracking over time; reduction of source vignetting, and identification of materials (0 rings, Teflon parts, soft goods) via table look up.

Butterfield, R. L.↗

Scaling of energy absorbing composite plates

The energy absorption response and crushing characteristics of geometrically scaled graphite-Kevlar epoxy composite plates were investigated. Three different trigger mechanisms including chamfer, notch, and steeple geometries were incorporated into the plate specimens to initiate crushing. Sustained crushing was achieved with a simple test fixture which provided lateral support to prevent global buckling. Values of specific sustained crushing stress (SSCS) were obtained which were comparable to values reported for tube specimens from previously published data. Two sizes of hybrid plates were fabricated; a baseline or model plate, and a full-scale plate with in-plane dimensions scaled by a factor of two. The thickness dimension of the full-scale plates was increased using two different techniques; the ply-level method in which each ply orientation in the baseline laminate stacking sequence is doubled, and the sublaminate technique in which the baseline laminate stacking sequence is repeated as a group. Results indicated that the SSCS is independent of trigger mechanism geometry. However, a reduction in the SSCS of 10-25 percent was observed for the full-scale plates as compared with the baseline specimens, indicating a scaling effect in the crushing response.

Jackson, Karen↗

Scaling of energy absorbing composite plates

The energy absorption response and crushing characteristics of geometrically scaled graphite-Kevlar epoxy composite plates were investigated. Two different trigger mechanisms including notch, and steeple geometries were incorporated into the plate specimens to initiate crushing. Sustained crushing was achieved with a new test fixture which provided lateral support to prevent global buckling. Values of specific sustained crushing stress (SSCS) were obtained which were lower than values reported for tube specimens from previously published data. Two sizes of hybrid plates were fabricated; a baseline or model plate, and a full-scale plate with inplane dimensions scaled by a factor of two. The thickness dimension of the full-scale plates was increased using two different techniques: the ply-level method in which each ply orientation in the baseline laminate stacking sequence is doubled, and the sublaminate technique in which the baseline laminate stacking sequence is repeated as a group. Results indicated that the SSCS has a small dependence on trigger mechanism geometry. However, a reduction in the SSCS of 10-25% was observed for the full-scale plates as compared with the baseline specimens, indicating a scaling effect in the crushing response.

Jackson, Karen↗

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗

Millimeter-wave system-on-chip advancement for fusion plasma diagnostics

Recent advances in radio-frequency system-on-chip technology have provided mm-wave fusion plasma diagnostics with the capability to overcome major challenges such as space inefficiency, inflexible installation, sensitivity, susceptibility to EMI, and prohibitively high cost of conventional discrete component assemblies as higher imaging resolution and data accuracy are achieved by increasing the number of channels. Nowadays, shrinking transistor gate lengths on fabrication techniques have enabled hundreds of GHz operation, which is suitable for millimeter-wave diagnostics on current and future tokamaks. The Davis Millimeter Wave Research Center (DMRC) has successfully developed V-band (55-75 GHz) transmitter and receiver chips for Microwave Imaging Reflectometer (MIR) instruments. The transmitter can illuminate 8 different frequencies simultaneously within 55-75 GHz. Moreover, the receiver has the capability to amplify the reflected signal (>30 dB) while offering 10-30× reduction in noise temperature compared to current MIR instruments. Plasma diagnostics requires ultra-wideband (more than 20 GHz) operation which is approximately nine times wider bandwidth than the recent commercial impetus for communication systems. Current efforts are underway for gallium-arsenide monolithic microwave integrated circuit receiver chips at W-band (75-110 GHz) and F-band (90–140 GHz) permitting measurements at higher toroidal magnetic fields.

47 OTHER INSTRUMENTATION↗

Structural concept trends for commercial supersonic cruise aircraft design

Structural concept trends for future commercial supersonic transport aircraft are considered. Highlights, including the more important design conditions and requirements, of two studies are discussed. Knowledge of these design parameters, as determined through studies involving the application of flexible mathematical models, enabled inclusion of aeroelastic considerations in the structural-material concepts evaluation. The design trends and weight data of the previous contractual study of Mach 2.7 cruise aircraft were used as the basis for incorporating advanced materials and manufacturing approaches to the airframe for reduced weight and cost. Structural studies of design concepts employing advanced aluminum alloys, advanced composites, and advanced titanium alloy and manufacturing techniques are compared for a Mach 2.0 arrow-wing configuration concept. Appraisals of the impact of these new materials and manufacturing concepts to the airframe design are shown and compared. The research and development to validate the potential sources of weight and cost reduction identified as necessary to attain a viable advanced commercial supersonic transport are discussed.

Sakat, I. F.↗

Remote driving with reduced bandwidth communication

Oak Ridge National Laboratory has developed a real-time video transmission system for low bandwidth remote operations. The system supports both continuous transmission of video for remote driving and progressive transmission of still images. Inherent in the system design is a spatiotemporal limitation to the effects of channel errors. The average data rate of the system is 64,000 bits/s, a compression of approximately 1000:1 for the black and white National Television Standard Code video. The image quality of the transmissions is maintained at a level that supports teleoperation of a high mobility multipurpose wheeled vehicle at speeds up to 15 mph on a moguled dirt track. Video compression is achieved by using Laplacian image pyramids and a combination of classical techniques. Certain subbands of the image pyramid are transmitted by using interframe differencing with a periodic refresh to aid in bandwidth reduction. Images are also foveated to concentrate image detail in a steerable region. The system supports dynamic video quality adjustments between frame rate, image detail, and foveation rate. A typical configuration for the system used during driving has a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of less than 1s.

Depiero, Frederick W.↗

Neural blockade during exercise augments central command's contribution to carotid baroreflex resetting

This investigation was designed to determine central command's role on carotid baroreflex (CBR) resetting during exercise. Nine volunteer subjects performed static and rhythmic handgrip exercise at 30 and 40% maximal voluntary contraction (MVC), respectively, before and after partial axillary neural blockade. Stimulus-response curves were developed using the neck pressure-neck suction technique and a rapid pulse train protocol (+40 to -80 Torr). Regional anesthesia resulted in a significant reduction in MVC. Heart rate (HR) and ratings of perceived exertion (RPE) were used as indexes of central command and were elevated during exercise at control force intensity after induced muscle weakness. The CBR function curves were reset vertically with a minimal lateral shift during control exercise and exhibited a further parallel resetting during exercise with neural blockade. The operating point was progressively reset to coincide with the centering point of the CBR curve. These data suggest that central command was a primary mechanism in the resetting of the CBR during exercise. However, it appeared that central command modulated the carotid-cardiac reflex proportionately more than the carotid-vasomotor reflex.

NASA Discipline Cardiopulmonary↗

Data Science-Driven Discovery of Multimetallic Oxygen-cycle Electrocatalysts for Enhanced Energy Conversion

The overarching objective of this effort has been to combine state-of-the-art data science techniques, first principles analyses, and molecular-level characterization of electrocatalyst structure and reactivity to identify both in-situ mechanisms for degradation and transformation of electrocatalysts with highly complex catalytic structures and the impact of these transformations on catalytic activity. The primary catalysts of interest have been multielemental alloys, including high entropy alloys (HEA’s), which are characterized by a high degree of disorder and up to 20 different elements within a single nanoparticle. We have applied these strategies primarily to energy-critical oxygen cycle electrocatalytic reactions, including oxygen reduction (ORR), but we have also considered extensions to non-electrochemical chemistries such as ammonia synthesis and decomposition. We have made strong progress in the development of computational methods on both the level of machine learning methods development as well as first principles-based treatments of HEA’s, and we have leveraged these insights to propose promising HEA catalysts for the ORR. On the experimental side, we developed new HEA synthesis and characterization protocols relevant to these reactions and developed a database combining our experimental results with corresponding computational tools.

36 MATERIALS SCIENCE↗

Graphite/epoxy Composite Laminates with Co-cured Interlaminar Damping Layers

Damped composite laminates were fabricated by co-curing viscoelastic damping film with graphite/epoxy prepreg plies. The dynamic response of the damped plates was measured using an impulse response technique and compared with the response of similar undamped laminates. Modal damping was computed from the frequency response data. Micrographs of the damped laminates showed that the damping layers retained their integrity during the fabrication process. The layers significantly increased the damping in the composite laminates. The use of the constrained viscoelastic film as an integral part of composite structures appears to be a feasible approach to passive vibration control. Composite plates manufactured with co-cured damping layers may have commercial applications in cases where light weight, strength, and vibration and noise reduction are important considerations.

Pereira, J. Michael↗

Visualization of Subsurface Defects in Composites using a Focal Plane Array Infrared Camera

A technique for enhanced defect visualization in composites via transient thermography is presented in this paper. The effort targets automated defect map construction for multiple defects located in the observed area. Experimental data were collected on composite panels of different thickness with square inclusions and flat bottom holes of different depth and orientation. The time evolution of the thermal response and spatial thermal profiles are analyzed. The pattern generated by carbon fibers and the vignetting effect of the focal plane array camera make defect visualization difficult. An improvement of the defect visibility is made by the pulse phase technique and the spatial background treatment. The relationship between a size of a defect and its reconstructed image is analyzed as well. The image processing technique for noise reduction is discussed.

Plotnikov, Yuri A.↗

Observations and Mitigation of RFI in ALOS PALSAR SAR Data; Implications for the Desdyni Mission

Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystems, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems as well. Therefore the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands is of considerable interest. RFI is observed in ALOS PALSAR in California, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straightforward spectral normalization to time-domain, multi-phase filtering techniques are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

InSAR↗

Toward the analytic bootstrap of energy correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in $\mathcal{N}$ = 4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators in the multi-collinear limit with equal and unequal energy weights, where the latter are crucial ingredients for projected N -point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

jet substructure↗