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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Assessment of Soil Moisture Retrievals Using SMAP and ELBARA-III Measurements in a Tibetan Meadow Ecosystem

This study presents results evaluating retrievals of liquid water content for both thawed and frozen soils based on simultaneous SMAP and ELBARA-III measurements in a Tibetan meadow ecosystem. A good agreement is found between time series of the SMAP and ELBARA-III T(sub B(sup P)) measurements (R≥0.87). Differences noted between the two data sets are linked to distinct liquid water content variations found in the specific footprints, and the SMAP measurements are better explained by the in-situ liquid water content. Furthermore, the in-situ liquid water content shows better agreements with both SMAP and ELBARA-III measured T(sub B(sup P)) at horizontal polarization in the cold season, while the measurements at vertical polarization are more consistently varying with the liquid water content for the warm season. With the implementation of new vegetation and surface roughness parameterizations, the dynamics of in-situ liquid water content are better reproduced by corresponding retrievals for both thawed and frozen soils, leading to the reduction of the unbiased root mean-square error (ubRMSE) by more than 31 % in comparison to these retrievals using SMAP default parameterizations. Notably, the single channel algorithm configured with the new parameterizations using SMAP measured vertical polarization during the ascending overpass provides the best liquid water content retrievals with an ubRMSE of 0.035 cu m -cu m that outperforms the SMAP mission specification.

L-band microwave radiometry↗
NASA NTRS2012

A review of reduced Kalman filters for clock ensembles

This paper reviews the author’s previous work on free-running timescales based on Kalman filters that act upon clock comparisons. The natural Kalman clock ensemble algorithm tends to optimize long-term timescale stability at the expense of short-term stability. By subjecting each postmeasurement error covariance matrix to a non-transparent reduction operation, one obtains corrected clocks with improved short-term stability and little sacrifice of long-term stability. A new result on covariance matrix reduction is also stated.

Greenhall, Charles A.↗
DOE OSTI2021

Constrained Block Nonlinear Neural Dynamical Models

Neural network modules conditioned by known priors can be effectively trained and combined to represent systems with nonlinear dynamics. This work explores a novel formulation for data-efficient learning of deep control-oriented nonlinear dynamical models by embedding local model structure and constraints. The proposed method consists of neural network blocks that represent input, state, and output dynamics with constraints placed on the network weights and system variables. For handling partially observable dynamical systems, we utilize a state observer neural network to estimate the states of the system's latent dynamics. We evaluate the performance of the proposed architecture and training methods on system identification tasks for three nonlinear systems: a continuous stirred tank reactor, a two tank interacting system, and an aerodynamics body. Models optimized with a few thousand system state observations accurately represent system dynamics in open loop simulation over thousands of time steps from a single set of initial conditions. Experimental results demonstrate an order of magnitude reduction in open-loop simulation mean squared error for our constrained, block-structured neural models when compared to traditional unstructured and unconstrained neural network models.

Skomski, Elliott↗
NASA NTRS2014

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

GEOS5↗
NASA NTRS1972

Variable-length codes and the Fano metric.

It is shown that the metric proposed originally by Fano for sequential decoding is precisely the required statistic for minimum-error-probability decoding of variable-length codes. The analysis shows further that the 'natural' choice of bias in the metric is the code rate and gives insight into why the Fano metric has proved to be the best practical choice in sequential decoding. The recently devised Jelinek-Zigangirov 'stack algorithm' is shown to be a natural consequence of this interpretation of the Fano metric. Finally, it is shown that the elimination of the bias in the 'truncated' portion of the code tree gives a slight reduction in average computation at the sacrifice of increased error probability.

Massey, J. L.↗
NASA NTRSDate not supplied

Mapping the seasonal variability of Titan’s upper atmospheric gases using ALMA

We present a study of the impact of seasonal effects on the spatial distribution of Titan’s atmospheric gases HNC, CH3CN, and HC3N over a timescale of less than a Titan month (9 Earth months). These molecules are synthesized primarily in the upper and middle atmosphere as a result of CH4 and N2 photochemistry, and are redistributed around Titan’s globe as a result of diffusion and zonal and meridional circulation. With observations from the Atacama Large Millimeter/submillimeter Array (ALMA) obtained in August 2016 [1] and May 2017 [2], we produced high-resolution, spectrally and spatially resolved maps of the emission from these gases. These observations are contemporaneous with the end of the Cassini mission (around the time of the northern summer solstice), allowing for studies of seasonal variations in Titan’s organic chemistry through analysis of the production, destruction, and transport of complex molecules. We observed a strong reduction of 41% ± 4% in the HC3N flux coming from the north pole, while CH3CN and HNC remained relatively stable (within errors) over the 9 month period of our observations. In the south pole, CH3CN presented a 31% ± 10% increase, while HNC saw a reduction of 20% ± 8%, and HC3N remained fairly stable (within errors). The HNC emission comes primarily from the highest (thermospheric) altitudes, and is distributed more uniformly about Titan’s limb than HC3N and CH3CN; the latter two molecules show strong polar enhancements due to meridional circulation. The steep decline in the HC3N north polar concentration is consistent its short photochemical lifetime (compared to HNC and CH3CN), combined with a reduction in meridional transport of gases produced at lower latitudes, towards the northern (summer) pole. The loss of emission of HC3N in the northern hemisphere is also consistent with the breakdown of Titan’s northern polar vortex during the onset of the northern summer, leading to a loss of confinement of these species [3].

Titan↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
NASA NTRSDate not supplied

Modeling Measurement Error in Dose-Response Models of Community Annoyance to Low-Noise Supersonic Flight

The primary research goal of the forthcoming NASA Quesst mission community test campaign is to collect representative community response data in support of the development of supersonic overflight noise certification standards. Beginning in 2026, NASA will fly the novel X-59 demonstrator aircraft over select communities in United States in order to demonstrate the possibility of low-noise supersonic flight over land and to collect objective measurements and subjective data on the perceptual experience of this new noise source. It is believed that a regression of a binary perceptual response (‘highly annoyed’ or ‘not’) on estimated noise levels (doses, measured in decibels) will provide a useful dose-response relationship for regulators. However, as these estimated doses will be subject to measurement error, naïve estimators of regression coefficients are inconsistent and slopes may be subject to attenuation bias. In this presentation, I contrast functional modeling of measurement error via simulation extrapolation (SIMEX) with structural Bayesian measurement error models. These methods are applied to available data collected during two NASA risk reduction studies in California in 2011 and Texas in 2018. I’ll conclude noting that in the presence of nonnegligible measurement errors, probabilities of annoyance may be overpredicted for low noise levels and underpredicted for high noise levels, therefore, methods of correcting for measurement error will be necessary to improve the utility of the dose-response relationship for policy-making purposes.

simulation↗
DOE OSTI2020

Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data

Scientific simulations in high-performance computing (HPC) environments generate vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for postanalysis. Unlike traditional data reduction schemes such as deduplication or lossless compression, not only can error-controlled lossy compression significantly reduce the data size but it also holds the promise to satisfy user demand on error control. Pointwise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications with lossy compression since error control can adapt to the error bound in the dataset automatically. Pointwise relative-error-bounded compression is complicated and time consuming. In this article, we develop efficient precomputation-based mechanisms based on the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error-bounded compression with excellent compression ratios. In addition, we reduce traversing operations for Huffman decoding, significantly accelerating the decompression process in SZ. Experiments with eight well-known real-world scientific simulation datasets show that our solution can improve the compression and decompression rates (i.e., the speed) by about 40 and 80 p, respectively, in most of cases, making our designed lossy compression strategy the best-in-class solution in most cases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2013

GNOSIS: THE FIRST INSTRUMENT TO USE FIBER BRAGG GRATINGS FOR OH SUPPRESSION

The near-infrared is an important part of the spectrum in astronomy, especially in cosmology because the light from objects in the early universe is redshifted to these wavelengths. However, deep near-infrared observations are extremely difficult to make from ground-based telescopes due to the bright background from the atmosphere. Nearly all of this background comes from the bright and narrow emission lines of atmospheric hydroxyl (OH) molecules. The atmospheric background cannot be easily removed from data because the brightness fluctuates unpredictably on short timescales. The sensitivity of ground-based optical astronomy far exceeds that of near-infrared astronomy because of this long-standing problem. GNOSIS is a prototype astrophotonic instrument that utilizes 'OH suppression fibers' consisting of fiber Bragg gratings and photonic lanterns to suppress the 103 brightest atmospheric emission doublets between 1.47 and 1.7 {mu}m. GNOSIS was commissioned at the 3.9 m Anglo-Australian Telescope with the IRIS2 spectrograph to demonstrate the potential of OH suppression fibers, but may be potentially used with any telescope and spectrograph combination. Unlike previous atmospheric suppression techniques GNOSIS suppresses the lines before dispersion and in a manner that depends purely on wavelength. We present the instrument design and report the results of laboratory and on-sky tests from commissioning. While these tests demonstrated high throughput ( Almost-Equal-To 60%) and excellent suppression of the skylines by the OH suppression fibers, surprisingly GNOSIS produced no significant reduction in the interline background and the sensitivity of GNOSIS+IRIS2 is about the same as IRIS2. It is unclear whether the lack of reduction in the interline background is due to physical sources or systematic errors as the observations are detector noise dominated. OH suppression fibers could potentially impact ground-based astronomy at the level of adaptive optics or greater. However, until a clear reduction in the interline background and the corresponding increasing in sensitivity is demonstrated optimized OH suppression fibers paired with a fiber-fed spectrograph will at least provide a real benefit at low resolving powers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS)

Purpose: A test object (phantom) is an important tool to evaluate comparability and stability of CT scanners used in multicenter and longitudinal studies. However, there are many sources of error that can interfere with the test object-derived quantitative measurements. Here the authors investigated three major possible sources of operator error in the use of a test object employed to assess pulmonary density-related as well as airway-related metrics. Methods: Two kinds of experiments were carried out to assess measurement variability caused by imperfect scanning status. The first one consisted of three experiments. A COPDGene test object was scanned using a dual source multidetector computed tomographic scanner (Siemens Somatom Flash) with the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) inspiration protocol (120 kV, 110 mAs, pitch = 1, slice thickness = 0.75 mm, slice spacing = 0.5 mm) to evaluate the effects of tilt angle, water bottle offset, and air bubble size. After analysis of these results, a guideline was reached in order to achieve more reliable results for this test object. Next the authors applied the above findings to 2272 test object scans collected over 4 years as part of the SPIROMICS study. The authors compared changes of the data consistency before and after excluding the scans that failed to pass the guideline. Results: This study established the following limits for the test object: tilt index ≤0.3, water bottle offset limits of [−6.6 mm, 7.4 mm], and no air bubble within the water bottle, where tilt index is a measure incorporating two tilt angles around x- and y-axis. With 95% confidence, the density measurement variation for all five interested materials in the test object (acrylic, water, lung, inside air, and outside air) resulting from all three error sources can be limited to ±0.9 HU (summed in quadrature), when all the requirements are satisfied. The authors applied these criteria to 2272 SPIROMICS scans and demonstrated a significant reduction in measurement variation associated with the test object. Conclusions: Three operator errors were identified which significantly affected the usability of the acquired scan images of the test object used for monitoring scanner stability in a multicenter study. The authors’ results demonstrated that at the time of test object scan receipt at a radiology core laboratory, quality control procedures should include an assessment of tilt index, water bottle offset, and air bubble size within the water bottle. Application of this methodology to 2272 SPIROMICS scans indicated that their findings were not limited to the scanner make and model used for the initial test but was generalizable to both Siemens and GE scanners which comprise the scanner types used within the SPIROMICS study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

A surrogate-based uncertainty quantification with quantifiable errors

Surrogate models are often employed to reduce the computational cost required to complete uncertainty quantification, where one is interested in propagating input parameters uncertainties throughout a complex engineering model to estimate responses uncertainties. An improved surrogate construction approach is introduced here which places a premium on reducing the associated computational cost. Unlike existing methods where the surrogate is constructed first, then employed to propagate uncertainties, the new approach combines both sensitivity and uncertainty information to render further reduction in the computational cost. Mathematically, the reduction is described by a range finding algorithm that identifies a subspace in the parameters space, whereby parameters uncertainties orthogonal to the subspace contribute negligible amount to the propagated uncertainties. Moreover, the error resulting from the reduction can be upper-bounded. The new approach is demonstrated using a realistic nuclear assembly model and compared to existing methods in terms of computational cost and accuracy of uncertainties. Although we believe the algorithm is general, it will be applied here for linear-based surrogates and Gaussian parameters uncertainties. The generalization to nonlinear models will be detailed in a separate article. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Functional Independent Scaling Relation for ORR/OER Catalysts

A widely used adsorption energy scaling relation between OH* and OOH* intermediates in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), has previously been determined using density functional theory and shown to dictate a minimum thermodynamic overpotential for both reactions. Here, we show that the oxygen–oxygen bond in the OOH* intermediate is, however, not well described with the previously used class of exchange-correlation functionals. By quantifying and correcting the systematic error, an improved description of gaseous peroxide species versus experimental data and a reduction in calculational uncertainty is obtained. For adsorbates, we find that the systematic error largely cancels the vdW interaction missing in the original determination of the scaling relation. An improved scaling relation, which is fully independent of the applied exchange–correlation functional, is obtained and found to differ by 0.1 eV from the original. Lastly, this largely confirms that, although obtained with a method suffering from systematic errors, the previously obtained scaling relation is applicable for predictions of catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

On the sea-state bias of the Geosat altimeter

The sea-state bias in a satellite altimeter's range measurement is caused by the influence of ocean waves on the radar return pulse; it results in an estimate of sea level that is too low according to some function of the wave height. This bias is here estimated for Geosat by correlating collinear differences of altimetric sea-surface heights with collinear differences of significant wave heights (H1/3). Corrections for satellite orbit error are estimated simultaneously with the sea-state bias. Based on twenty 17-day repeat cycles of the Geosat Exact Repeat Mission, the solution for the sea-state bias is 2.6 + or - 0.2 percent of H1/3. The least-squares residuals, however, show a correlation with wind speed U, so the traditional model of the bias has been supplemented with a second term: H1/3 + alpha-2H1/3U. This second term produces a small, but statistically significant, reduction in variance of the residuals. Both systematic and random errors in H1/3 and U tend to bias the estimates of alpha-1 and alpha-2, which complicates comparisons of the results with ground-based measurements of the sea-state bias.

Ray, Richard D.↗
DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗
DOE OSTI2023

A divergence-free constrained magnetic field interpolation method for scattered data

An interpolation method to evaluate magnetic fields, given its unstructured and scattered magnetic data, is presented. The method is based on the reconstruction of the global magnetic field using a superposition of orthogonal functions. The coefficients of the expansion are obtained by minimizing a cost function defined as the L2 norm of the difference between the ground truth and the reconstructed magnetic field evaluated on the training data. The divergence-free condition is incorporated as a constraint in the cost function, allowing the method to achieve arbitrarily small errors in the magnetic field divergence. An exponential decay of the approximation error is observed and compared with the less favorable algebraic decay of local splines. Compared to local methods involving computationally expensive search algorithms, the proposed method exhibits a significant reduction of the computational complexity of the field evaluation, while maintaining a small error in the divergence even in the presence of magnetic islands and stochasticity. Finally, applications to the computation of Poincaré sections using data obtained from numerical solutions of the magnetohydrodynamic equations in toroidal geometry are presented and compared with local methods currently in use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Accelerating Relative-error Bounded Lossy Compression for HPC datasets with Precomputation-Based Mechanisms

Scientific simulations in high-performance computing (HPC) environments are producing vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for post-analysis. Unlike the traditional data reduction schemes (such as deduplication or lossless compression), not only can error-controlled lossy compression significantly reduce the data size but it can also hold the promise to satisfy user demand on error control. Point-wise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications in the lossy compression, since error control can adapt to the precision in the dataset automatically. Point-wise relative error bounded compression is complicated and time consuming. In this work, we develop efficient precomputation-based mechanisms in the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error bounded compression with excellent compression ratios. In addition, our mechanisms also help reduce traversing operations for Huffman decoding, and thus significantly accelerate the decompression process in SZ. Experiments with four well-known real-world scientific simulation datasets show that our solution can improve the compression rate by about 30% and decompression rate by about 70% in most of cases, making our designed lossy compression strategy the best choice in class in most cases.

compression rate↗
DOE OSTI2023

Significant reduction in the low-field magnetization of Nb 3 Sn superconducting strands using the internal oxidation APC approach

Nb 3 Sn superconductors are promising for building accelerator magnets for future energy-frontier circular colliders. A critical factor for this application is the low-field persistent-current magnetization because it leads to several critical issues: e.g. low-field instability (including flux jumps), hysteresis loss, and field errors in magnet bores. Suppression of low-field magnetization requires reduction of low-field critical current density (J c ) or effective subelement size (d eff ). However, reduction of deff of state-of-the-art Nb 3 Sn conductors—the restacked-rod-process (RRP ® ) type—below 40–50 μm without a pronounced decrease in high-field J c is difficult. On the other hand, the internal oxidation method which forms artificial pinning centers (APC) in Nb 3 Sn offers an alternative approach to reducing the low-field magnetization. Compared with a conventional Nb 3 Sn conductor whose flux pinning force versus field (F p –B) curve peaks at ~20% of its irreversibility field (B irr ), the F p –B curve peaks of APC conductors shift to higher fields due to the point pinning effect, leading to flattening of the J c –B curves. The goal of this paper is to quantitatively study how much the APC approach can reduce the low-field magnetization. Here we measured the J c –B curves of an RRP ® conductor and two APC conductors (reacted at 700 °C) from zero field to B irr using a high-field vibrating sample magnetometer. Here the results showed that the APC conductors have higher non-Cu J c at high fields (e.g. 32%–41% higher at 16 T) and simultaneously lower non-Cu Jc at low fields (e.g. 28%–34% lower at 1 T) compared with the RRP ® . This effect is due to a competition between their Nb3Sn layer fraction ratios and layer F p ratios. Suppose they reach the same 16 T non-Cu J c , then the 1 T non-Cu J c and magnetization of the APC conductors are only half or even less compared with the RRP ® conductor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗