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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data for Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry: Sequence Data

Climate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to one meter in depth from irrigated and planted field treatments and analyzed using a suite of omics and chemical analyses. Carbon cycling processes in the surface soil were dominated by plant-microbe interactions that drive organic carbon cycling, whereas inorganic carbon chemistry dominated in deeper soil layers. Both irrigation and plant cover impacted organic and inorganic carbon pools in the soil profiles. This study reveals the complex interactions between water, plants, minerals, and microorganisms that govern organic and inorganic pools of soil carbon at different depths.

Naasko, Katherine I↗
NASA NTRS1982

Optimal weighting of data to detect climatic change - Application to the carbon dioxide problem

It is suggested that a weighting of surface temperature data, using information about the expected level of warming in different seasons and geographical regions and statistical information about the amount of natural variability in surface temperature, can improve the chances of early detection of carbon dioxide concentration-induced climatic warming. A preliminary analysis of the optimal weighting method presented suggests that it is 25 per cent more effective in revealing surface warming than the conventional method, in virtue of the fact that 25 per cent more data must conventionally be analyzed in order to arrive at a similar probability of detection. An approximate calculation suggests that the warming ought to have already been detected, if the only sources of significant surface temperature variability had time scales of less than one year.

Bell, T. L.↗
NASA NTRS1984

Sputtering processes - Erosion and chemical change

Laboratory data and models of sputter-induced erosion and chemical alterations in ice films are reviewed and the results are applied to icy grains and satellites exposed to magnetospheric ion bombardment. It is shown that the source of the plasma in the inner magnetosphere of Saturn is likely to be the sputter erosion of the icy objects in this region and the sputter erosion and possible stabilization of the E-ring are considered. Ion-induced polymerization is discussed as a source of the darkened rings of Uranus.

Johnson, R. E.↗
NASA NTRS1986

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗
NASA NTRS1981

The Development and Use of a Computer-Interactive Data Acquisition and Display System in a Flight Environment

The flight test data requirements at the NASA Dryden Flight Research Center increased in complexity, and more advanced instrumentation became necessary to accomplish mission goals. This paper describes the way in which an airborne computer was used to perform real-time calculations on critical flight test parameters during a flight test on a winglet-equipped KC-135A aircraft. With the computer, an airborne flight test engineer can select any sensor for airborne display in several formats, including engineering units. The computer is able to not only calculate values derived from the sensor outputs but also to interact with the data acquisition system. It can change the data cycle format and data rate, and even insert the derived values into the pulse code modulation (PCM) bit stream for recording.

Computer Systems↗
NASA NTRS2004

AveBoost2: Boosting for Noisy Data

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the pre- vious base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. In previous work, we developed an algorithm, AveBoost, that constructed distributions orthogonal to the mistake vectors of all the previous models, and then averaged them to create the next base model s distribution. Our experiments demonstrated the superior accuracy of our approach. In this paper, we slightly revise our algorithm to allow us to obtain non-trivial theoretical results: bounds on the training error and generalization error (difference between training and test error). Our averaging process has a regularizing effect which, as expected, leads us to a worse training error bound for our algorithm than for AdaBoost but a superior generalization error bound. For this paper, we experimented with the data that we used in both as originally supplied and with added label noise-a small fraction of the data has its original label changed. Noisy data are notoriously difficult for AdaBoost to learn. Our algorithm's performance improvement over AdaBoost is even greater on the noisy data than the original data.

Oza, Nikunj C.↗
NASA NTRS2017

Kepler Planet Reliability Metrics: Astrophysical Positional Probabilities for Data Release 25

This document is very similar to KSCI-19092-003, Planet Reliability Metrics: Astrophysical Positional Probabilities, which describes the previous release of the astrophysical positional probabilities for Data Release 24. The important changes for Data Release 25 are:1. The computation of the astrophysical positional probabilities uses the Data Release 25 processed pixel data for all Kepler Objects of Interest.2. Computed probabilities now have associated uncertainties, whose computation is described in x4.1.3.3. The scene modeling described in x4.1.2 uses background stars detected via ground-based high-resolution imaging, described in x5.1, that are not in the Kepler Input Catalog or UKIRT catalog. These newly detected stars are presented in Appendix B. Otherwise the text describing the algorithms and examples is largely unchanged from KSCI-19092-003.

APP↗
NASA NTRS2011

Easing the Discovery of NASA and International Near-Real-Time Data Using the Global Change Master Directory

The Global Change Master Directory (GCMD) provides an extensive directory of descriptive and spatial information about data sets and data-related services, which are relevant to Earth science research. The directory's data discovery components include controlled keywords, free-text searches, and map/date searches. The GCMD portal for NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE) data products leverages these discovery features by providing users a direct route to NASA's Near-Real-Time (NRT) collections. This portal offers direct access to collection entries by instrument name, informing users of the availability of data. After a relevant collection entry is found through the GCMD's search components, the "Get Data" URL within the entry directs the user to the desired data. http://gcmd.nasa.gov/r/p/gcmd_lance_nrt.

Olsen, Lola↗
NASA NTRSDate not supplied

On the Advantages of Using Harmonized Landsat Sentinel-2 Data for Monitoring Environmental Change

NASA coordinates the Satellite Needs Working Group, dedicated to identifying, communicating, and addressing Earth observation needs of federal agencies. In 2016, the Harmonized Landsat Sentinel-2 (HLS) dataset was formulated and implemented to fulfill multiple needs. The combination of acquisitions from the Landsat and Sentinel-2 platforms results in a global dataset of surface reflectance with a temporal resolution of two days, while retaining the geometry and 30-meter spatial resolution of Landsat data. This harmonization allows for seamless integration with the 40-year archive of Landsat data. The HLS dataset is now available on the Google Earth Engine, enabling HLS utilization in various algorithms and frameworks essential for monitoring environmental change worldwide. During this presentation, we will demonstrate and discuss the advantages of using HLS data in comparison to using separate streams of Landsat and Sentinel-2 data in existing time series-based frameworks for change monitoring. Specifically, we will explore the application of HLS for continuous monitoring of deforestation using time series-based algorithms traditionally run with Landsat data. Additionally, we will showcase the benefits of HLS data for near real-time monitoring of forest disturbance in tropical regions. These examples underscore the value and utility of the HLS dataset for environmental monitoring and analysis.

Pontus Olofsson↗
NASA NTRS1974

Systematic monitoring and evaluation of M7 scanner performance and data quality

An investigation was conducted to provide the information required to maintain data quality of the Michigan M7 Multispectral scanner by systematic checks on specific system performance characteristics. Data processing techniques which use calibration data gathered routinely every mission have been developed to assess current data quality. Significant changes from past data quality are thus identified and attempts made to discover their causes. Procedures for systematic monitoring of scanner data quality are discussed. In the solar reflective region, calculations of Noise Equivalent Change in Radiance on a permission basis are compared to theoretical tape-recorder limits to provide an estimate of overall scanner performance. M7 signal/noise characteristics are examined.

Stewart, S.↗
NASA NTRS1991

Data principles for the U.S. Global Change Research Program

The U.S. Interagency Working Group on Data Management for Global Change has developed a set of data management and access principles. The overall purpose of these statements of principle is to stimulate responsible stewardship for data and related information and to facilitate full and open access to them. These statements have been accepted by the U.S. Agencies responsible for the Global Change Research Program. The statements of principle are presented and discussed.

Ludwig, George H.↗
NASA NTRS1982

Evaluation of land cover change detection techniques using Landsat MSS data

Four techniques for detecting land cover change with Landsat MSS data were evaluated for a test site in east central Louisiana where forestland is being converted to cropland and pasture. The four techniques were: (1) post-classification differencing, (2) composite classification, (3) radiance value shift, and (4) regression modeling. Three of the techniques gave acceptable accuracies. The main differences were the amount of computer time and the level of complexity.

Burns, G. S.↗
DOE OSTI2025

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗
DOE OSTI2023

Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication

Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.

Tan, Nigel↗
DOE OSTI2025

Repetitive proteins that undergo large conformational changes evade structural prediction algorithms

Protein structure prediction algorithms, such as AlphaFold, have accelerated protein design and advanced the understanding of the relationship between amino acid sequence and protein structure. However, these algorithms are limited in their ability to predict the structures of conformationally dynamic, intrinsically disordered, and stimuli-responsive proteins. To evaluate sequence-to-structure predictions of such challenging proteins, we explored a class of conformationally dynamic, repeats-in-toxin (RTX) proteins. RTX proteins adopt intrinsically disordered conformations in the absence of calcium and undergo reversible folding into β-roll structures upon binding to calcium. RTX proteins are characterized by tandem repeats of the sequence GGXGXDXUX, in which X can be any amino acid and U is an aliphatic amino acid. We designed RTX sequence variants with global substitutions of nonconserved amino acids, tandem repeats of consensus sequences GGAGXDTLY, and tandem repeats of scrambled sequences GGAGXDTYL. AlphaFold2 and AlphaFold3 predicted that all of these RTX variants adopt β-roll structures, characteristic of wild-type RTX bound to calcium. However, modeling the predicted structures with molecular dynamics simulations and characterizing the protein variants with circular dichroism spectroscopy, small-angle x-ray scattering, and x-ray crystallography revealed that variants adopt diverse, sequence-dependent structures in the absence and presence of calcium. To better design proteins for applications in biotechnology and sustainability, it is critical to build predictive tools that consider intrinsically disordered protein states and validate these tools with multi-mode, multi-scale experimental data.

Chang, Marina P. [Stanford Univ., CA (United State↗
DOE OSTI2026

Continual Learning for Production-Level Machine Learning in Particle Accelerators

Particle accelerators operate in complex environments where data distribution can change dynamically, leading to data drifts that significantly challenge Machine Learning (ML) models. These non-stationary conditions often cause ML models to deteriorate in performance, making it difficult to maintain reliable predictions in operation. The primary sources of data drifts are changes in accelerator settings and changes in equipment performance which cannot be measured directly. To bridge this gap between ML development and long-term deployment in operational settings, we identify key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. We will provide a practical guide on selecting the appropriate method given resource constraints and desired stability plasticity trade offs. As a concrete example, we will present a real-world use case for anomaly detection to predict errant beams at the Spallation Neutron Source accelerator, where continual learning has been employed to demonstrate stable performance on drifting data streams. We will present practical challenges, lessons learned, and the results from the deployed ML model.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2023

polishCLR: A Nextflow Workflow for Polishing PacBio CLR Genome Assemblies

Long-read sequencing has revolutionized genome assembly, yielding highly contiguous, chromosome-level contigs. However, assemblies from some third generation long read technologies, such as Pacific Biosciences (PacBio) continuous long reads (CLR), have a high error rate. Such errors can be corrected with short reads through a process called polishing. Although best practices for polishing non-model de novo genome assemblies were recently described by the Vertebrate Genome Project (VGP) Assembly community, there is a need for a publicly available, reproducible workflow that can be easily implemented and run on a conventional high performance computing environment. Here, we describe polishCLR (https://github.com/isugifNF/polishCLR), a reproducible Nextflow workflow that implements best practices for polishing assemblies made from CLR data. PolishCLR can be initiated from several input options that extend best practices to suboptimal cases. It also provides re-entry points throughout several key processes, including identifying duplicate haplotypes in purge_dups, allowing a break for scaffolding if data are available, and throughout multiple rounds of polishing and evaluation with Arrow and FreeBayes. PolishCLR is containerized and publicly available for the greater assembly community as a tool to complete assemblies from existing, error-prone long-read data.

59 BASIC BIOLOGICAL SCIENCES↗