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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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64 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Vegetation Detection Using Deep Learning and Conventional Methods

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.

58 GEOSCIENCES↗
DOE OSTI2021

Seed source for plasma compression in the long wavelength infrared

Two color laser pulses are used to form an air plasma and generate broadband infrared radiation suitable as a seed for backward Raman amplification of CO 2 laser pulses. Broadband radiation in the atmospheric window from 8-14 microns is observed. The infrared radiation is characterized using a long wavelength grating spectrometer specially designed to accept an ionizing laser filament at its input plane. The LWIR yield is greatly enhanced by chirping the drive pulse. Unidirectional pulse propagation simulations suggest that this is due in part to the dependence of the nonlinear refractive index on the pulse

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Hubble Space Telescope Observations of GW170817: Complete Light Curves and the Properties of the Galaxy Merger of NGC 4993

We present the complete set of Hubble Space Telescope imaging of the binary neutron star merger GW170817 and its optical counterpart AT 2017gfo. Including deep template imaging in F814W, F110W, F140W, and F160W at 3.4 yr post-merger, we reanalyze the full light curve of AT 2017gfo across 12 bands from 5 to 1273 rest-frame days after merger. We obtain four new detections of the short γ-ray burst 170817A afterglow from 109 to 170 rest-frame days post-merger. These detections are consistent with the previously observed β = -0.6 spectral index in the afterglow light curve with no evidence for spectral evolution. We also analyze our limits in the context of kilonova afterglow or IR dust echo emission but find that our limits are not constraining for these models. We use the new data to construct deep optical and IR stacks, reaching limits of M = -6.3 to -4.6 mag, to analyze the local environment around AT 2017gfo and low surface brightness features in its host galaxy NGC 4993. We rule out the presence of any globular cluster at the position of AT 2017gfo to 2.3 × 10$^{4}$L$_{⊙}$, including those with the reddest V - H colors. Finally, we analyze the substructure of NGC 4993 in deep residual imaging and find shell features that extend up to 71."8 (14.2 kpc) from NGC 4993. The shells have a cumulative stellar mass of 6.3 × 10$^{8}$M$_{⊙}$, roughly 2% of NGC 4993, and mass-weighted ages of >3 Gyr. We conclude that it was unlikely that the GW170817 progenitor system formed in the galaxy merger.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Quark and gluon helicity evolution at small x: revised and updated

We revisit the problem of small Bjorken-x evolution of the gluon and flavor-singlet quark helicity distributions in the shock wave (s-channel) formalism. Earlier works on the subject in the same framework resulted in an evolution equation for the gluon field-strength F 12 and quark “axial current” $\overline{\psi}\gamma$ + γ 5 ψ operators (sandwiched between the appropriate light-cone Wilson lines) in the double-logarithmic approximation (summing powers of α s ln 2 (1/x) with α s the strong coupling constant). In this work, we observe that an important mixing of the above operators with another gluon operator, ${}_D{}^{\leftarrow i} {}_D{}^{i}$, also sandwiched between the light-cone Wilson lines (with the repeated transverse index i = 1, 2 summed over), was missing in the previous works. This operator has the physical meaning of the sub-eikonal (covariant) phase: its contribution to helicity evolution is shown to be proportional to another sub-eikonal operator, ${}_D{}^{i} {}_D{}^{\leftarrow i}$, which is related to the Jaffe-Manohar polarized gluon distribution. In this work we include this new operator into small-x helicity evolution, and construct novel evolution equations mixing all three operators (${}_D{}^{i} {}_D{}^{\leftarrow i}$, F 12 , and $\overline{\psi}\gamma$ + γ 5 ψ), generalizing the results of . We also construct closed double-logarithmic evolution equations in the large-N c and large-N c &N f limits, with N c and N f the numbers of quark colors and flavors, respectively. Solving the large-N c equations numerically we obtain the following small-x asymptotics of the quark and gluon helicity distributions ΔΣ and ΔG, along with the g 1 structure function, $$ \Delta \Sigma \left(x,{Q}^2\right)\sim \Delta G\left(x,{Q}^2\right)\sim {g}_1\left(x,{Q}^2\right)\sim {\left(\frac{1}{x}\right)}^{3.66\sqrt{\frac{\alpha_s{N}_c}{2\pi }}} $$ in complete agreement with the earlier work by Bartels, Ermolaev and Ryskin.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Cinnamon essential oil vapor alleviates the reduction of aroma-related volatiles in cold-stored “Feicheng” peach using HS-GC-IMS

“Feicheng” peach is popular for its unique aroma, but its defect of being highly sensitive to chilling injury (CI) often leads to aroma loss and internal browning. Essential oils (EOs) are often used to enhance the antioxidant capacity of plants and fruits, as well as to trigger their defense against biotic/abiotic stresses. This study aimed to examine the effect of cinnamon essential oil (CEO) vapor treatment on the aroma quality of peach fruit during cold storage using HS-GC-IMS. The results showed that 50 μL/L CEO vapor reduced the severity of internal browning (IB) in peaches at the stage of 7 ~ 21 d during refrigeration (Significantly, the L * value was higher and the IB index was lower than that of control, p < 0.05). Meanwhile, the evident reduction or loss of aroma content caused by CI was restored to a higher level than the control ( p < 0.05). Furthermore, CEO treatment promoted the release of aroma-related volatiles as evidenced by more propyl acetate, and the dimer of amyl acetate, isoamyl acetate, butyl acetate detected than that on harvest day and no-treated group after 21 d of cold storage plus 2 d of shelf life. Genes of PpLOX1 , PpLOX2 , PpHPL1 and PpADH1 associated with aroma-related volatile biosynthesis revealed higher transcript abundance in peach fruits treated with CEO than the control ( p < 0.05). Overall, our study demonstrated that CEO in vapor phase may be beneficial to alleviate the quality deterioration in aroma and flesh color of “Feicheng” peaches caused by CI, which lays a theoretical reference for maintaining postharvest quality of peach fruits.

Wang, Dan↗
DOE OSTI2022

Spatial heterogeneity effects on land surface modeling of water and energy partitioning

Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM), soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model (ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating feasible light configurations for fish restoration: an ethological insight

Light environment significantly impacts the effectiveness of fish population restoration in developed watersheds, subserving fish passage reconstruction in hydraulic complex and habitat rehabilitation. To develop an interior connection between light-related fish response from the laboratory and field fish conservation practice, we employed a new indexing system, consisting of phototaxis rate, relative swimming speed (RSS), and optic evasion coefficient (OEC), to quantify the light-induced behaviors in Ptychobarbus kaznakovi, a representative rare cyprinid in Tibet, China, at four experimental illuminance levels (15 lx, 30 lx, 60 lx, 120 lx) and four wavelengths (red, yellow, green, blue). The fish showed negative phototaxis at all given illuminances and wavelengths. Under red light, the OEC increased significantly from 0.642 at 15 lx to 0.782 at 30 lx (P = 0.029), while the RSS decreased significantly from 3.752 to 2.383 (P < 0.001). Behaviorally, the fish shifted from sprint to wandering around, indicating the alteration of dominant physiological activity from behavioral stress response to negative phototaxis. Under the green treatment, P. kaznakovi swam around quickly and presented slight negative phototaxis, and OEC values were uniform among all illuminances, probably because of the similarity of green light to the ambient color of the habitat. Accordingly, ecologists and fisheries practitioners can utilize red light to exclude fish from dangerous waters and green light to guide them to ideal habitats, laying the necessary groundwork for the light-driven fish recovery effort. Furthermore, the appropriate light configuration can yield economic benefits through the tradeoff among fish protection, power generation, and investment costs.

Lin, Chenyu↗
DOE OSTI2025

Clarifying the trophic state concept to advance macroscale freshwater science and management

For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use‐specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non‐algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re‐evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.

classification↗
DOE OSTI2020

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

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

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗