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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Optimizing observations of drizzle onset with millimeter-wavelength radars

Cloud Doppler radars are increasingly used to study cloud and precipitation microphysical processes. Typical bulk cloud properties such as liquid or ice content are usually derived using the first three standard moments of the radar Doppler spectrum. Recent studies demonstrated the value of higher moments for the reduction of retrieval uncertainties and for providing additional insights into microphysical processes. Large effort has been undertaken, e.g., within the Atmospheric Radiation Measurement (ARM) program to ensure high quality of radar Doppler spectra. However, a systematic approach concerning the accuracy of higher moment estimates and sensitivity to basic radar system settings, such as spectral resolution, integration time and beam width, are still missing. Here In this study, we present an approach on how to optimize radar settings for radar Doppler spectra moments in the specific context of drizzle detection. The process of drizzle development has shown to be particularly sensitive to higher radar moments such as skewness. We collected radar raw data (I/Q time series) from consecutive zenith-pointing observations for two liquid cloud cases observed at the cloud observatory JOYCE in Germany. The I/Q data allowed us to process Doppler spectra and derive their moments using different spectral resolutions and integration times during identical time intervals. This enabled us to study the sensitivity of the spatiotemporal structure of the derived moments to the different radar settings. The observed signatures were further investigated using a radar Doppler forward model which allowed us to compare observed and simulated sensitivities and also to study the impact of additional hardware-dependent parameters such as antenna beam width. For the observed cloud with drizzle onset we found that longer integration times mainly modify spectral width (S w ) and skewness (S k ), leaving other moments mostly unaffected. An integration time of 2 s seems to be an optimal compromise: both observations and simulations revealed that a 10 s integration time – as it is widely used for European cloud radars – leads to a significant turbulence-induced increase of S w and reduction of S k compared to 2 s integration time. This can lead to significantly different microphysical interpretations with respect to drizzle water content and effective radius. A change from 2 s to even shorter integration times (0. 4 s) has much smaller effects on S w and S k . We also find that spectral resolution has a small impact on the moment estimations, and thus on the microphysical interpretation of the drizzle signal. Even the coarsest spectral resolution studied, 0. 08 ms -1 , seems to be appropriate for calculation moments of drizzling clouds. Moreover, simulations provided additional insight into the microphysical interpretation of the skewness signatures observed: in low (high)-turbulence conditions, only drizzle larger than 20 µm (40 µm) can generate S k values above the S k noise level (in our case 0.4). Higher S k values are also obtained in simulations when smaller beam widths are adopted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

On-the-fly data set combinations with RNTuple

With the expected data volume increase for HL-LHC and the even more complex computing challenges set by future colliders, the need for efficient data storage and processing becomes more pressing. ROOT’s next-generation data format and I/O subsystem, RNTTuple, is designed to address these challenges. RNTTuple already demonstrates a clear improvement in storage and I/O efficiency, as well as overall stability and robustness with respect to its predecessor, TTTree. These improvements provide a solid baseline to introduce novel extensions to common high-energy and nuclear physics (HENP) workflows. Notably, many workflows could benefit from the ability to arbitrarily join and chain data set samples at runtime, which could reduce overall storage requirements and improve application runtime and ergonomics. In this paper, we present the RNTupleProcessor, which enables HENP data set combinations with RNTuple. We will discuss the main design considerations, present the interfaces to support data set combinations and show how they integrate in typical workflows.

de Geus, Florine Willemijn [CERN; Twente U., Ensch↗
DOE OSTI2016

The Path to Nitrate Salt Disposition

The topic is presented in a series of slides arranged according to the following outline: LANL nitrate salt incident as thermal runaway (thermally sensitive surrogates, full-scale tests), temperature control for processing, treatment options and down selection, assessment of engineering options, anticipated control set for treatment, and summary of the overall steps for RNS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Use of microbial carbonation process to enable self‑carbonation of reactive MgO cement mixes

The low hydration and carbonation of reactive MgO cement (RMC) under ambient conditions causes prolonged setting and low compressive strengths (~4 MPa). This study proposed a unique technique which led to the enhancement of the hydration and carbonation processes via the synergistic combination of microbial carbonation process (MCP) with a hydration agent (HA) that enabled the self‑carbonation of RMC-based mixes without using of any special curing environments. Through hydrolysing urea (CO(NH{sub 2}){sub 2}) using ureolytic bacteria, CO{sub 3}{sup 2−} ions were produced to facilitate the carbonation of dissolved Mg{sup 2+} ions to form hydrated magnesium hydroxy carbonates (HMHCs). The self‑carbonation of RMC enabled by the MCP resulted in formation of brucite with a poor crystallinity and its rapid conversion into HMHCs, which improved the setting time and compressive strength of RMC-based samples. The simultaneous use of MCP with 2 M urea and HA revealed HMHCs with improved morphologies, resulting in the highest compressive strength (~15 MPa).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Large-Scale Data Analytics and Its Relationship to Simulation

Large-Scale Data Analytics (LSDA) problems require finding meaningful patterns in data sets that are so large as to require leading-edge processing and storage capability. LSDA problems are increasingly important for government mission work, industrial application, and scientific discovery. Effective solution of some important LSDA problems requires a computational workload that is substantially different from that associated with traditional High Performance Computing (HPC) simulations intended to help understand physical phenomena or to conduct engineering. While traditional HPC application codes exploit structural regularity and data locality to improve performance, many analytics problems lead more naturally to very fine-grained communication between unpredictable sets of processors, resulting in less regular communication patterns that do not map efficiently on to typical HPC systems. In both simulation and analytics domains, however, data movement increasingly dominates the performance, energy usage, and price of computing systems. It is therefore plausible that we could find a more synergistic technology path forward. Even though future machines may continue to be configured differently for the two domains, a more common technological roadmap between them in the form of a degree of convergence in the underlying componentry and design principles to address these common technical challenges could have substantial technical and economic benefits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Search for B 0 → π – τ + ν τ with hadronic tagging at Belle

We search for the process B 0 → π – τ + ν τ using the full Belle data set of 711 fb –1 , corresponding to 772 × 10 6 BB¯ pairs, collected at the Υ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e + e – collider. Here, we reconstruct one B meson in a hadronic decay and search for the B 0 → π – τ + ν τ process in the remainder of the event. No significant signal is observed and an upper limit of B(B 0 → π – τ + ν τ ) < 2.5 × 10 –4 is obtained at the 90% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Developing a Roadmap for Total Nuclear Plant Transformation

Commercial nuclear power plants (NPPs) provide emission free, always-on electricity that must be part of the energy mix if U.S. industry and business are to remain competitive while enjoying the benefits of a clean environment. Most U.S. NPPs in operation today were licensed using state-of-the-art analog technology of the 1970’s. While these systems are well proven and designed with multiple redundant channels, they required extensive manual surveillance and testing procedures to demonstrate their continued functioning. All of this adds up to increasing labor costs as the only means to increase plant availability. The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program is performing a study to determine how an NPP can fully modernize, improve safety, and improve efficiency enough to make nuclear power competitive with current and future market conditions. The study is a process improvement analysis whereby current operational processes are evaluated to identify where efficiencies and cost-savings can be realized. This report will describe a process that will provide each utility with the tools to evaluate their present state, set goals for where they want to be regarding Operation and Maintenance (O&M) costs, while offering transformative pathways to achieve these improvements. The transformative changes will be divided into 1) work process improvements, 2) technology solutions, and 3) regulatory reform. By applying these pathways in combination, NPPs can achieve the dramatic O&M savings needed to sustain safe and economic operation into the future.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Constraint-Based Modeling of Carbon Fixation and the Energetics of Electron Transfer in Geobacter metallireducens

Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species. Author Summary The ability of microorganisms to exchange electrons directly with their environment has large implications for our knowledge of industrial and environmental processes. For decades, it has been known that microbes can use electrodes as electron acceptors in microbial fuel cell settings. Geobacter metallireducens has been one of the model organisms for characterizing microbe-electrode interactions as well as environmental processes such as bioremediation. Here, we significantly expand the knowledge of metabolism and energetics of this model organism by employing constraint-based metabolic modeling. Through this analysis, we build the metabolic pathways necessary for carbon fixation, a desirable property for industrial chemical production. We further discover a novel growth condition which enables the characterization of autotrophic (i.e., carbon-fixing) metabolism in Geobacter. Importantly, our systems-level modeling approach helped elucidate the key metabolic pathways and the energetic cost associated with extracellular electron transfer. This model can be applied to characterize and engineer the metabolism and electron transfer capabilities of Geobacter for biotechnological applications.

Feist, AM↗
DOE OSTI2018

Advanced Laboratory and Field Arrays: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave-SPARC) (Task 8)

This task focused on advancing the mission of the Wave-SPARC project by (1) establishing a user-centered Set-Based Design methodology to enable industrial partners to design higher performance WECs, (2) assessing the means through which WEC concepts and WEC design processes are evaluated by employing and potentially improving Wave-SPARC’s Technological Performance Level (TPL) metric, and (3) clarifying how the Set-Based Design approach to WEC design would be applicable for devices of different scales and/or maritime markets.

13 HYDRO ENERGY↗
DOE OSTI2014

Arc plasma assisted rotating electrode process for preparation of metal pebbles

Spherical beryllium pebbles of size ranging from 0.2-2 mm are required as neutron multiplying material in solid Test Blanket Module (TBM) of International Thermonuclear Experimental Reactor (ITER). Rotating electrode process (REP) has been identified as a suitable technique for preparation of beryllium pebbles. In REP, arc plasma generated between non-consumable electrode (cathode) and rotating metal electrode (anode) plays a major role for continuous consumption of metal electrode and preparation of spherical metal pebbles. This paper focuses on description of the process, selection of sub-systems for development of REP experimental set up and optimization of arc parameters, such as, cathode geometry, arc current, arc voltage, arc gap and carrier gas flow rate for preparation of required size spherical metal pebbles. Other parameters which affect the pebbles sizes are rotational speed, metal electrode diameter and physical properties of the metal. As beryllium is toxic in nature its surrogate metals such as stainless steel (SS) and Titanium (Ti) were selected to evaluate the performance of the REP equipment. Several experiments were carried out using SS and Ti electrode and process parameters have been optimized for preparation of pebbles of different sizes. (author)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Managing work flow and logistic at waste processing facilities using the waste compliance and tracking system - 15392

Work flow and logistics at a busy radioactive waste processing complex or permitted treatment, storage, and disposal facility (TSDF) can pose a monumental challenge. An efficient operation requires good communication between engineering, logistics, and waste operators. The Los Alamos National Laboratory (LANL) has implemented an application that facilitates seamless communication of work flow requirements, between engineering, logistics, and waste operations personnel in the field. The Waste Compliance and Tracking System (WCATS), a comprehensive waste management system designed at LANL, provides four key elements to support logistics: (a) the container work path, (b) directed unit operation requests, (c) notification of pending operations, and (d) real-time status tools for office and field workers. The combination of these elements allows everyone to function as a team, with a shared knowledge of what is needed to accomplish facility objectives. The first element is like a road map indicating which unit operations are needed and in what sequence they should be performed; this is referred to as a 'work path'. It automatically routes a waste item or container from operation to operation. For example, a given work path might indicate that waste items require radiological survey, radioassay, and a technical review, in that order. When the work path is assigned to a container, the system enforces the correct order of operations. Directed unit operation 'requests', the second element, fills a gap between pre-planned, formal 'work path' activities and the need for flexibility to direct preparatory operations or deal with unexpected issues, like staging or mining containers in preparation for a shipment or transferring containers from one storage unit to another to clear a path for building maintenance. Logistics engineers prepare these 'requests', and the system monitors the status and completion of the work. The third element, notifications, allows team members to subscribe to and receive notice that an operation is pending, initiated, or complete. This functionality supports a range of communication options, including e-mail, cell phone, pager, or application in-box messaging. Notifications allow waste operations personnel to multi-task, and remain in the loop on the status of facility-wide activities. Finally, the fourth element provides tools that communicate work path pending operations and directed requests to field workers on their mobile computer, allowing them to mine or pick containers from storage units, and leverage the capabilities of a bar-code scanner to avoid selection mistakes. Oversight and summary tools are provided, allowing logistics personnel to monitor work path and request task status, identify work-flow bottlenecks, and maximize the efficiency of waste operations. The Waste Compliance and Tracking System (WCATS) provides an innovative, comprehensive set of tools that allow large-scale radioactive waste processing facilities to manage logistics, maximize efficient use of the workforce, and create a team environment, where everyone from management to the waste handlers have an understanding of the work load and what needs to be accomplished. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Vibrational processing of a dynamic structural flight system: A multichannel spectral estimation approach

Dynamic testing of large flight vehicles (rockets) is not only complex, but also can be very costly. These flights are infrequent and can lead to disastrous effects if something were to fail during the flight. The development of sensors coupled to internal components offers a great challenge in reducing their size, yet still maintaining their precision. Sounding rockets provide both a viable and convenient alternative to the more costly vehicular flights. Some of the major objectives are to test various types of sensors for monitoring components of high interest as well as investigating real-time processing techniques. Signal processing presents an extreme challenge in this noisy multichannel environment. The estimation and tracking of modal frequencies from vibrating structures is an important set of features that can provide information about the components under test; therefore, high resolution multichannel spectral processing is required. Finally, the application of both single channel and multichannel techniques capable of producing reliable modal frequency estimates of a vibrating structure from uncertain accelerometer measurements is discussed.

42 ENGINEERING↗
DOE OSTI2014

A nonvoxel-based dose convolution/superposition algorithm optimized for scalable GPU architectures

Purpose: Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. Methods: The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy into a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. Results: The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. Conclusions: The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2023

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton

ABSTRACT Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8–2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life. IMPORTANCE Single-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers’ efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Laboratory Investigations of Aerosol-Cloud Interactions in an Entraining, Turbulent Environment (Final Technical Report)

The effects that aerosol particles have on clouds in Earth’s atmosphere and the role that clouds play in determining the fate of aerosol particles play a crucial role in determining the human experience on this planet. These interwoven interactions can determine whether it rains or snows, is comfortable, hot or cold, or whether the cloud you gaze at in the sky looks like a tiger or a lump of porridge. How clouds mix with the air surrounding them, a process known as entrainment, further affects these processes. We conducted laboratory experiments of aerosol-cloud interactions in a setting in which we can measure the effects of entrainment – the first laboratory experiments since the pioneering work of Latham and Reed in 1977. We measured the effects of entrainment on aerosol-cloud interactions in the Pi Chamber and also used a state-of-the-art large eddy simulation (LES) to investigate processes in fine detail.

54 ENVIRONMENTAL SCIENCES↗