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

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗
DOE OSTI2015

SU-E-P-12: Pinnacle-Based Tool to Evaluate the Effect of Prostate Rotation as Determined by Calypso

Purpose: When the Calypso reports a large prostate rotation and one does not have the means to make corrections, it is helpful to quantify its dosimetric effects. We have devised a simple scheme to achieve this in Pinnacle TPS. If it is determined that the PTV margin is inadequate, an alternate larger-margin plan may be adapted for the day. Methods: A three-step process using the Pinnacle Image fusion module was formulated to analyze the clinical effect of prostate rotation. The process includes (1) translating the image set such that the rotational axis is about the isocenter, (2) performing 3D rotations of the structures of interest, and (3) restoring the coordinates associated with the plan. The rotated structures are imported and overlayed on the original plan for evaluation. The tool was applied to three prostate cancer patients with relatively large rotations (95 fractions total). Prostate rotations are primarily due to variations in bladder and rectal filling, which may also affect the seminal vesicles. It is difficult to estimate the perturbation of seminal vesicles for a given prostate rotation. Therefore, the Calypso-derived rotation matrix was applied only to CTV and PTV (CTV+5mm). Results: The rotations were predominantly in the pitch direction with an absolute value ranging from 0–29 degrees (Median = 10°, Average = 14.5°). For various magnitudes of rotation, the CTV V100 decreased from the original 100% to 99.6%/99%/95% for 10°/15°/29° rotations, respectively. Likewise, the PTV V100 diminished from 95% to 92%/89%/82%. Conclusion: A tool, consisting only of features within a TPS, was used to evaluate the dosimetric effect of prostate rotation. Our study shows that under large uncorrected rotations, the tumor coverage is degraded and may require intervention in the form of plan adaptation. To this end, alternate plans with variable margins can be generated in advance for daily adaption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Two-dimensional glass transition–like behavior of Janus particle–laden interface

Abstract Understanding the interactive behavior of Janus particles (JPs) is a growing field of research. The enhancement in binding energy, in comparison to homogenous particles, and the dual characteristic of JPs open up new possibilities for novel applications. In many such applications, interfacial materials become subjected to flows that produce dilational and shear stresses. Therefore, it is important to understand the impact that the Janus character brings to interfaces. In this work, we study the microstructure of two-dimensional (2D) JP monolayers formed at the air–water interface and examine the shear viscoelasticity with an interface rheometer that was adapted for in situ surface pressure control via a Langmuir trough. We extend concepts from bulk rheology to data obtained from interfacial rheology as a tool to understand and predict the monolayer’s viscoelastic behavior. Finally, by calculating the time relaxation spectrum from the measured 2D dynamic moduli, we conclude that a phenomenon similar to glass transition is taking place by analogy.

42 ENGINEERING↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2022

Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions

Polysaccharide utilization loci (PULs) are co-regulated bacterial genes that sense nutrients and enable glycan digestion. Human gut microbiome members, notably Bacteroides, contain numerous PULs that enable glycan utilization and shape ecological dynamics. To investigate the role of PULs on fitness and inter-species interactions, we develop a CRISPR-based genome editing tool to study 23 PULs in Bacteroides uniformis (BU). BU PULs show distinct glycan-degrading functions and transcriptional coordination that enables the population to adapt upon loss of other PULs. Exploiting a BU mutant barcoding strategy, we demonstrate that in vitro fitness and BU colonization in the murine gut are enhanced by deletion of specific PULs and modulated by glycan availability. PULs mediate glycan-dependent interactions with butyrate producers that depend on the degradation mechanism and glycan utilization ability of the butyrate producer. Thus, PULs determine community dynamics and butyrate production and provide a selective advantage or disadvantage depending on the nutritional landscape.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Unlocking nature’s biosynthetic potential by directed genome evolution

Microorganisms have been increasingly explored as microbial cell factories for production of fuels, chemicals, drugs, and materials. Among the various metabolic engineering strategies, directed genome evolution has emerged as one of the most powerful tools to unlock the full biosynthetic potential of microorganisms. Furthermore we summarize the directed genome evolution strategies that have been developed in recent years, including adaptive laboratory evolution and various targeted genome-scale engineering strategies, and discuss their applications in basic and applied biological research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Footprints of Worldwide Adaptation in Structured Populations of Drosophila melanogaster Through the Expanded DEST 2.0 Genomic Resource

Abstract Large-scale genomic resources can place genetic variation into an ecologically informed context. To advance our understanding of the population genetics of the fruit fly Drosophila melanogaster, we present an expanded release of the community-generated population genomics resource Drosophila Evolution over Space and Time (DEST 2.0; https://dest.bio/). This release includes 530 high-quality pooled libraries from flies collected across six continents over more than a decade (2009 to 2021), most at multiple time points per year; 211 of these libraries are sequenced and shared here for the first time. We used this enhanced resource to elucidate several aspects of the species' demographic history and identify novel signs of adaptation across spatial and temporal dimensions. For example, we showed that the spatial genetic structure of populations is stable over time, but that drift due to seasonal contractions of population size causes populations to diverge over time. We identified signals of adaptation that vary between continents in genomic regions associated with xenobiotic resistance, consistent with independent adaptation to common pesticides. Moreover, by analyzing samples collected during spring and fall across Europe, we provide new evidence for seasonal adaptation related to loci associated with pathogen response. Furthermore, we have also released an updated version of the DEST genome browser. This is a useful tool for studying spatiotemporal patterns of genetic variation in this classic model system.

Biochemistry & Molecular Biology↗
DOE OSTI2016

Projections of water stress based on an ensemble of socioeconomic growth and climate change scenarios: A case study in Asia

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

PIPER: Performance Insight for Programmers and Exascale Runtimes: Guiding the Development of the Exascale Software Stack

The PIPER project set out to develop methodologies and software for measurement, analysis, attribution, and presentation of performance data for extreme-scale systems. Goals of the project were to support analysis of massive multi-scale parallelism, heterogeneous architectures, multi-faceted performance concerns, and to support both post-mortem performance analysis to identify program features that contribute to problematic performance and on-line performance analysis to drive adaptation. This final report summarizes the research and development activity at Rice University as part of the PIPER project. Producing a complete suite of performance tools for exascale platforms during the course of this project was impossible since both hardware and software for exascale systems is still a moving target. For that reason, the project focused broadly on the development of new techniques for measurement and analysis of performance on modern parallel architectures, enhancements to HPCToolkit’s software infrastructure to support our research goals or use on sophisticated applications, engaging developers of multithreaded runtimes to explore how support for tools should be integrated into their designs, engaging operating system developers with feature requests for enhanced monitoring support, engaging vendors with requests that they add hardware measure- ment capabilities and software interfaces needed by tools as they design new components of HPC platforms including processors, accelerators and networks, and finally collaborations with partners interested in using HPCToolkit to analyze and tune scalable parallel applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Measuring Saturn's Electron Beam Energy Spectrum using Webb's Wedges

It is very difficult to measure the voltage of the load on the Saturn accelerator. Time-resolved measurements such as vacuum voltmeters and V-dot monitors are impractical at best and completely change the pulsed power behavior at the load at worst. We would like to know the load voltage of the machine so that we could correctly model the radiation transport and tune our x-ray unfold methodology and circuit simulations of the accelerator. Step wedges have been used for decades as a tool to measure the end - point energies of high energy particle beams. Typically, the technique is used for multi-megavolt accelerators, but we have adapted it to Saturn's modest <2 MV end-point energy and modified the standard bremsstrahlung x-ray source to extract the electron beam without changing the physics of the load region. We found clear evidence of high energy electrons >2 MV. We also attempted to unfold an electron energy spectrum using a machine learning algorithm and while these results come with large uncertainties, they qualitatively agree with PIC simulation results.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Brief Overview of the DOE/NNSA Nuclear Criticality Safety Program [Slides]

The mission of the DOE/NNSA Nuclear Criticality Safety Program is to provide sustainable expert leadership, direction and the technical infrastructure necessary to develop, maintain, and disseminate the essential technical tools, training, and data required to support safe, efficient fissionable material operations within DOE. The vision of the program is to create a continually improving, adaptable, and transparent program that communicates and collaborates globally to incorporate technology, practices, and programs to be responsive to the essential technical needs of those responsible for developing, implementing, and maintaining nuclear criticality safety.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
NASA NTRS1973

Beam lead forming tool

Tool was designed for table-top manual operation that can bend leads to any desired angle up to 90 degrees. It can be readily adapted to electrical, hydraulic, or pneumatic operation. This innovation may be of interest to electronics, sheet metal, and appliance industries.

Clemons, P. W.↗
NASA NTRS1980

"Grinding" cavities in polyurethane foam

Grinding tool installed on conventional milling machine cuts precise cavities in foam blocks. Method is well suited for prototype or midsize production runs and can be adapted to computer control for mass production. Method saves time and materials compared to bonding or hot wire techniques.

Brower, J. R.↗
NASA NTRS1988

Image processing software for imaging spectrometry

The paper presents a software system, Spectral Analysis Manager (SPAM), which has been specifically designed and implemented to provide the exploratory analysis tools necessary for imaging spectrometer data, using only modest computational resources. The basic design objectives are described as well as the major algorithms designed or adapted for high-dimensional images. Included in a discussion of system implementation are interactive data display, statistical analysis, image segmentation and spectral matching, and mixture analysis.

Mazer, Alan S.↗
NASA NTRS1994

Hydraulic Extractor For Electronic Connectors

Tool separates multipin electrical connectors in electronic equipment. Based on use of hydraulic pressure to apply balanced forces to connector and gently pull it free without damage. Easily assembled from readily available parts. Includes actuator syringe, two extractor syringes of disposable plastic 5-mL type, several pieces of flexible plastic tubing, and adjustable mounting components that brace tool in desired spacing configuration to suit connector extracted. Tubes and syringes filled with suitable fluid. Designed specifically for use on "D"-type connectors, also adapted for use wherever linear extraction motion used.

Smith, Larry D.↗
NASA NTRS2005

Self-consistent Evolution of Cosmic-Ray Shocks

Several key accomplishments were achieved under this grant. In the first year we combined our novel adaptive mesh refinement code for diffusive shock acceleration with the implementation of the Malkov/Volk thermal leakage injection model to produce an extremely powerful new modeling tool. We used it to examine the time evolution of highly modified CR shocks in a systematic way, finding that characteristic proton injection efficiencies for strong quasi-parallel shocks should be a few parts in l0(exp -4). That is sufficient for even moderately strong shocks to become efficient CR accelerators and substantially modified in structure. Those results were published in the Astrophysical Journal.

Jones, Thomas W.↗