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At least 163 records · Page 9

Examining the Trends in Financial Support Given to Science Teams for Data Analysis in Mission Proposals

Introduction: The goal of this summer internship research project was to analyze trends in financial support proposed for the science teams of planetary missions. The analysis focuses on the funding for Co-Investigators (Co-Is) to conduct research and/or data analysis needed to achieve the science objectives of the mission. The operational portion of the missions after launch (i.e., Phase E, including cruise and prime operations at the final destination) were examined since that is when the bulk of research is funded and conducted. The objectives of the project were to determine the average level of support for Co-Investigators, identify variation between mission competitions and over time, and determine the relationship between mission type and the amount of support requested. Methodology: This project was conducted using data from 90 proposals submitted to six mission competitions in the Discovery and New Frontiers programs. The level of support for Co-Is was determined by examining Work Breakdown Structure (WBS) 4 (Science Analysis) for Phase E, which was further subdivided into cruise and prime operations. This data represents a proxy rather than the actual funding Co-Is receive to perform research and data analysis because not every dollar in WBS 4 is spent on this activity. Therefore, the proxy obtained in this research represents an overestimate of the funds allocated to Co-Is for research and data analysis. Findings: Analysis shows that on average a Co-I receives approximately four full years of support spread across the entirety of Phase E for science analysis. The variation among proposed missions is less than expected given the variety of factors that are expected to drive this metric (length of mission, mission type, etc.). Additionally, the level of requested support for Co-Is has been remarkably consistent across every variable considered (by competition, over time, by mission type) over the six competitions and nearly 20 years spanned by this project. This remains true for cruise, primary operations, and all of Phase E. Conclusions: A remarkable amount of science is accomplished by the science teams of planetary missions. However, a surprisingly small amount of funding is requested to support the science analysis driving this productivity, both in terms of absolute magnitude of funding and as a portion of total mission cost. This suggests improvements are needed to refine the estimates of Co-I support and/or that Co-Is rely on other funding sources to conduct their research. Better estimates can be determined by engaging directly with Co-Is and NASA centers to obtain data as well as finding other data sources. Additionally, NASA could consider mandating improved reporting of requested funding levels in mission competitions.

E Murray↗

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

Abstract To predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Choi, Jang‐Geun↗

Ferroelectric phase-transition frustration near a tricritical composition point

Phase transition describes a mutational behavior of matter states at a critical transition temperature or external field. Despite the phase-transition orders are well sorted by classic thermodynamic theory, ambiguous situations interposed between the first- and second-order transitions were exposed one after another. Here, we report discovery of phase-transition frustration near a tricritical composition point in ferroelectric Pb(Zr 1-x Ti x )O 3 . Our multi-scale transmission electron microscopy characterization reveals a number of geometrically frustrated microstructure features such as self-assembled hierarchical domain structure, degeneracy of mesoscale domain tetragonality and decoupled polarization-strain relationship. Associated with deviation from the classic mean-field theory, dielectric critical exponent anomalies and temperature dependent birefringence data unveil that the frustrated transition order stems from intricate competition of short-range polar orders and their decoupling to long-range lattice deformation. With supports from effective Hamiltonian Monte Carlo simulations, our findings point out a potentially universal mechanism to comprehend the abnormal critical phenomena occurring in phase-transition materials.

42 ENGINEERING↗

Size and shape fluctuations of ultrasoft colloids

An ultrasoft colloidal particle fluctuates due to its flexibility. Such fluctuation is essential for colloidal structure and dynamics, but is challenging to quantify experimentally. We use dendrimers as a model system to study the fluctuation of ultrasoft colloids. By considering the dynamic polydispersity in the small-angle neutron scattering (SANS) model and introducing the fluctuation of invasive water into the contrast in SANS, we reveal the fluctuating amplitudes of the size and shape of the dendrimer of generation 6 at finite concentrations. The size fluctuation is suppressed while the shape fluctuation increases as the weight fraction of dendrimers passes 11%. With neutron spin echo data, we suggest that such a crossover originates from the competition between the inter- and intraparticle dynamics. Further investigation on lower-generation samples shows a contrary result, which suggests a structural basis for these dynamic phenomena.

42 ENGINEERING↗

Closed Loop Control Compact Exercise Device for Use on MPCV

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. To combat spaceflight physiological deconditioning, astronauts will use resistive and aerobic exercise regimens for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the mass and volume available for an exercise device in the next generation of spacecraft is limited. Therefore, compact exercise device prototypes are being developed for human in the loop evaluations. The NASA Human Research Program (HRP) is managing Advanced Exercise Concepts (AEC) requirements development and candidate technology maturation for all exploration mission profiles from Multi-Purpose Crew Vehicle (MPCV) exploration missions (e.g., EM-2, up to 21 day) to Mars Transit (up to 1000 day) missions. Numerous technologies have been considered and evaluated against HRP-approved functional requirements and include flywheel, pneumatic and closed-loop microprocessor-controlled motor driven power plants. Motor driven technologies offer excellent torque density and load accuracy characteristics as well as the ability to create custom mechanical impedance (the dynamic relationship between force and velocity) and custom load versus position exercise algorithms. Further, closed-loop motor-driven technologies offer the ability to monitor exercise dose parameters and adapt to the needs of the crewmember for real time optimization of exercise prescriptions. A simple proportional-integral-derivative (PID) controller is demonstrated in a prototype motor driven exercise device with comparison to resistive static and dynamic load set points and aerobic work rate targets. The resistive load term in the algorithm includes a constant force component (Fcmg) as well as inertial component (Fima) and a discussion of system tuning is presented in terms of addressing key functional requirements and human interfaces. The device aerobic modality is modelled as a rowing exercise using ground data sets obtained from Concept 2 rowers as well as competitive rowing1. A discussion of software and electronic implementations are presented which demonstrate unique approaches to meeting the constrained mass, volume and power requirements of the MPCV. . In addition to utilizing traditional PID control, controllers utilizing state feedback with gains solved using a Linear Quadratic Regulator will be developed. Controllability and observability will be utilized to investigate the need for state measurement in the design. As the control system directly interacts with human test subjects, robust methods such as H-infinity are also being investigated.1. Kleshnev V. Biomechanics. In: Rowing, Handbook of Sports Medicine and Science. ed. by Secher N., Voliantis S. IOC Medical Commission, Blackwell Pub. pp. 22-34, 2007

microgravity↗

Streamlining Energy Sprawl: Assessment of Geothermal Impacts on Public Lands

Renewable energy power generation, including geothermal, solar photovoltaics (PV), and wind, can have significant land use impacts depending on the technology and the size of the facility. At the same time, innovations across these renewable technologies are working to improve plant efficiency per acre of disturbance. Through a survey of satellite imagery and other sources, this analysis reevaluates the impact of geothermal power generation and examines the variations in land use for different geothermal technologies (binary, flash, and dry steam). Geothermal operations on Bureau of Land Management (BLM) sites serve as the focus for this analysis - i.e., only active sites with federal mineral ownership for which the BLM receives royalties from power production. The results show significant variation in direct land disturbance across the operations sites and across these three geothermal technologies. Although there is variation across plants within the same geothermal technology category, dry steam plants (The Geysers) were shown to have the lowest impact, in acres per megawatt capacity and acres per gigawatt-hour generation, followed by flash steam and binary plants. Overall, direct land impacts relative to capacity and generation have declined 16-27% for facilities constructed since 2000 as compared to those constructed prior, even though most new facilities are binary plants (which traditionally had higher land disturbance). Additionally, capacity factors based on actual net production data were found to average only 50% across all operations sites, suggesting that previous estimates based on nameplate capacity only may lead to an undercounting of generation-based land disturbance metrics. Should the geothermal industry capture additional market share, improving land disturbance metrics through accurate net production and capacity data and further minimizing impacts will be increasingly important as competition over land use intensifies.

GEOTHERMAL ENERGY↗

Leading Energy Analysis: Data-Driven Insights That Power Our Energy Future

Energy analysts at the National Renewable Energy Laboratory (NREL) use a broad set of expertise and cutting-edge tools to capture the complexities of our interconnected energy system. Decision-makers rely on these insights to drive cost savings, enhance grid reliability, support long-term innovation, and bolster America's energy workforce and global competitiveness. This fact sheet highlights some of NREL's high-impact analyses, data, and tools, largely focusing on power grid analysis.

data↗

Predicting Plant-Soil Feedback in the Field: Meta-Analysis Reveals That Competition and Environmental Stress Differentially Influence PSF

Past research on plant-soil feedbacks (PSF), largely undertaken in highly controlled greenhouse conditions, has established that plant species differentially alter abiotic and biotic soil conditions that in turn affect growth of other conspecific and heterospecific individuals in that soil. Yet, whether feedbacks under controlled greenhouse conditions reflect feedbacks in natural environments where plants are exposed to a range of abiotic and biotic pressures is still unresolved. To address how environmental context affects PSF, we conducted a meta-analysis of previously published studies that examined plant growth responses to multiple forms of competition, stress, and disturbance across various PSF methodology. We asked the following questions: (1) Can competition, stress, and disturbance alter the direction and/or strength of PSF? (2) Do particular types of competition, stress, or disturbance affect the direction and/or strength of PSF more than others? and (3) Do methods of conducting PSF research (i.e., greenhouse vs. field experiments and whether the source of soil inoculum conditioning is from the field vs. greenhouse) affect plant growth responses to PSF or competition, stress, and disturbance, or their interactions? We discovered four patterns that may be predictive of what future PSF studies conducted under more realistic conditions might reveal. First, relatively little is known about how PSF responds to environmental stress and disturbance compared to plant-plant competition. Second, specific types of competition enhanced negative effects of soil microbes on plant growth, and specific environmental stressors enhanced positive effects of soil microbes on plant growth. Third, whether PSF experiments are conducted in the field or greenhouse can change plant growth responses. And, fourth, how the soil conditioning phase is conducted can change plant growth responses. With more detail than previously shown, these results confirm that environmental context writ large can change plant growth responses in PSF experiments. These data should aid theory and predictions for conservation and restoration applications by showing the relative importance of competition, stress, and disturbance in PSF studies over time. Lastly, these data demonstrate how variation in experimental methods can alter interpretation and conclusions of PSF studies.

54 ENVIRONMENTAL SCIENCES↗

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Electrothermodynamic Model with Distributed Properties for Effective Permittivities of Sea Ice

This paper presents a model to calculate the temperature dependence of effective permittivities for sea ice, a heterogeneous medium containing multiphase scatterers. With the strong permittivity fluctuation approach the model accounts for the electrodynamic scattering effect together with the quasi-static characteristics of multiple species and subspecies of inhomogeneities with distributed orientations, sizes, and shapes. Because of a preferential direction in the orientation distribution, the medium is effectively anisotropic. The size distribution is described with a probability density function in terms of normalized volumetric sizes. Scatterer shapes are nonuniform and have a general ellipsoidal form characterized by arbitrary axial ratios of correlation lengths which are related to physical geometries of the scatterers. In this formulation, sea ice consisting of solid ice, liquid brine, and gaseous inclusions is modeled to derive effective permittivities with thermodynamic phase redistribution and structural metamorphism. Theoretical results are in good agreement with experimental data at the C band frequency of 4.8 GHz for saline ice undergoing warming and cooling cycles. A competitive effect between the increase of liquid brine and the shape rounding of ellipsoidal scatterers at increasing temperatures explains the trend observed in measured data. Sensitivities of effective permittivities to structural and physical parameters characterizing sea ice are also studied.

Nghiem, S. V.↗

Leaf angle as a leaf and canopy trait: Rejuvenating its role in ecology with new technology

Abstract Life on Earth depends on the conversion of solar energy to chemical energy by plants through photosynthesis. A fundamental challenge in optimizing photosynthesis is to adjust leaf angles to efficiently use the intercepted sunlight under the constraints of heat stress, water loss and competition. Despite the importance of leaf angle, until recently, we have lacked data and frameworks to describe and predict leaf angle dynamics and their impacts on leaves to the globe. We review the role of leaf angle in studies of ecophysiology, ecosystem ecology and earth system science, and highlight the essential yet understudied role of leaf angle as an ecological strategy to regulate plant carbon–water–energy nexus and to bridge leaf, canopy and earth system processes. Using two models, we show that leaf angle variations have significant impacts on not only canopy‐scale photosynthesis, energy balance and water use efficiency but also light competition within the forest canopy. New techniques to measure leaf angles are emerging, opening opportunities to understand the rarely‐measured intraspecific, interspecific, seasonal and interannual variations of leaf angles and their implications to plant biology and earth system science. We conclude by proposing three directions for future research.

Yang, Xi↗

Factors Affecting Fiber Design and Selection for Advanced Ceramic Composites

Structural Ceramic Matrix Composites (CMC) have the potential for application in the hot sections of a variety of advanced propulsion and power systems. It is therefore necessary to have a general understanding of the key properties of CMC and Reinforcing Fibers. This need is complicated by the wide variety of application conditions and structural requirements for which CMC's will be used, and the proprietary concerns of the design engineers. CMC's, to be successful, must display properties which are competitive with the currently used high temperature structural materials: (i.e., Iron and Nickel based superalloys, tough monolithic ceramics, and carbon/carbon composites.) Structural CMC offers several areas of competition: (1) performance, (i.e., strength and strength retention, creep resistance, and thermal conductivity), (2) reliability (i.e., environmental durability, and damage tolerance) and (3) processing (i.e., capability for varying sizes and shapes, and cost effective fabrication). The presentation further discusses, and illustrates with fiber and CMC data the key fiber properties and processes which strongly affect each CMC area of competition. The presentation further discusses the current knowledge of the important factors which control the key fiber properties. A design guidelines for the optimum fiber characteristics is developed, and the currently available fibers are compared against those guidelines.

DiCarlo, James A.↗

On the uncertainty of estimating photovoltaic soiling using nearby soiling data

The accumulation of dust on the surface of photovoltaic modules can reduce their performance and affect the cost competitiveness of this technology. This phenomenon is known as soiling and can be mitigated through appropriate corrective and/or preventive actions. In order to maximize its effectiveness, it is important to plan the soiling mitigation strategy even before the PV system is operational. This is typically done through a nearest neighbor approach, by estimating soiling using data from the nearest operational photovoltaic system. This work focuses on understanding the uncertainty related to this practice. For this purpose, the semi-variance function is used to study the dissimilarity between the soiling losses of two locations in California depending on their distance. The results show that, when the soiling loss at a nearby system is used to estimate soiling of a site, the uncertainty can be approximated to increase linearly at a rate of 0.08-0.10%/km up to 60 or 80 km. After this distance, the use of a nearest neighbor approach is no longer justified, as it produces an uncertainty as big as the average soiling loss of the sites in the dataset used in this study. In some conditions, uncertainties > 0% are found also for sites located within 25 km, meaning that even close-by systems might soil differently.

14 SOLAR ENERGY↗

U.S. Department of Energy Collegiate Wind Competition 2025 Rules - Phase 1

The U.S. Department of Energy (DOE) Wind Energy Technologies Office's (WETO) Collegiate Wind Competition (CWC, also referred to as the "Competition" in this rules document) invites interdisciplinary teams of undergraduate students from a variety of academic programs to solve complex wind energy challenges. Through the competition, WETO intends to offer students direct industry experience, valuable exposure to wind energy career pathways, and greater knowledge of wind energy's potential to contribute to a clean energy future. The competition will select up to 35 teams to start, making them eligible to compete for a cash prize pool of up to $280,000 . Each year, the competition identifies a new challenge and set of activities that address real-world research questions, thus demonstrating skills that students will need to work in the wind or wider renewable energy industries. The Collegiate Wind Competition 2025 challenge requires participants to compete simultaneously in four contests: 1) Turbine Prototype Contest: Design, build, and present a unique, wind-driven power system based on market research; 2) Turbine Testing Contest: Test the wind turbine in a competition wind tunnel at the final event; 3) Project Development Contest: Research wind resource data, transmission infrastructure, and environmental factors to create a site plan and financial analysis for a hypothetical wind farm; and Connection Creation Contest: Partner with wind industry professionals, raise awareness of wind energy in your local community, and work with local media to promote your team's accomplishments. The competition does not prescribe a power system market or wind regime. It is expected that each team will participate in all four contests.

collegiate wind competition↗

U.S. Department of Energy Collegiate Wind Competition 2025: Rules - Phases 2 and 3

The U.S. Department of Energy (DOE) Wind Energy Technologies Office's (WETO) Collegiate Wind Competition (CWC, also referred to as the "competition" in this rules document) invites interdisciplinary teams of undergraduate students from a variety of academic programs to solve complex wind energy challenges. Through the competition, WETO intends to offer students direct industry experience, valuable exposure to wind energy career pathways, and greater knowledge of wind energy's potential to contribute to a clean energy future. The competition will select up to 35 teams to start, making them eligible to compete for a cash prize pool of up to $280,000. Each year, the competition identifies a new challenge and set of activities that address real-world research questions, thus demonstrating skills that students will need to work in the wind or wider renewable energy industries. The Collegiate Wind Competition 2025 challenge requires participants to compete simultaneously in four contests: 1) Turbine Design Contest: Design, build, and present a unique, wind-driven power system. 2) Turbine Testing Contest: Test the wind turbine in a competition wind tunnel at the final event. 3) Project Development Contest: Research wind resource data, transmission infrastructure, and environmental factors to create a site plan and financial analysis for a hypothetical wind farm. 4) Connection Creation Contest: Partner with wind industry professionals, raise awareness of wind energy in your local community, and work with local media to promote your team's accomplishments. The competition does not prescribe a power system market or wind regime. It is expected that each team will participate in all four contests.

Collegiate Wind Competition↗

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗