nfs-utility-suite
NFS Utility Suite is a collection of code libraries that provide convenience features for working with network filesystems.
Bertschinger, Thomas↗
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Results for “Utility”
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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A survey of numerical linear algebra methods utilizing mixed-precision arithmetic
The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine learning applications, the traditional numerical algorithms community urgently needs to reconsider the floating point formats used in the distinct operations to efficiently leverage the available compute power. In this study, we provide a comprehensive survey of mixed-precision numerical linear algebra routines, including the underlying concepts, theoretical background, and experimental results for both dense and sparse linear algebra problems.
97 MATHEMATICS AND COMPUTING↗
Towards sustainable production and utilization of plant-biomass-based nanomaterials: a review and analysis of recent developments
Abstract Plant-biomass-based nanomaterials have attracted great interest recently for their potential to replace petroleum-sourced polymeric materials for sustained economic development. However, challenges associated with sustainable production of lignocellulosic nanoscale polymeric materials (NPMs) need to be addressed. Producing materials from lignocellulosic biomass is a value-added proposition compared with fuel-centric approach. This report focuses on recent progress made in understanding NPMs—specifically lignin nanoparticles (LNPs) and cellulosic nanomaterials (CNMs)—and their sustainable production. Special attention is focused on understanding key issues in nano-level deconstruction of cell walls and utilization of key properties of the resultant NPMs to allow flexibility in production to promote sustainability. Specifically, suitable processes for producing LNPs and their potential for scaled-up production, along with the resultant LNP properties and prospective applications, are discussed. In the case of CNMs, terminologies such as cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs) used in the literature are examined. The term cellulose nano-whiskers (CNWs) is used here to describe a class of CNMs that has a morphology similar to CNCs but without specifying its crystallinity, because most applications of CNCs do not need its crystalline characteristic. Additionally, progress in enzymatic processing and drying of NPMs is also summarized. Finally, the report provides some perspective of future research that is likely to result in commercialization of plant-based NPMs.
09 BIOMASS FUELS↗
Utilization of microalgae for agricultural runoff remediation and sustainable biofuel production through an integrated biorefinery approach
Generally wastewater such agricultural runoff is considered a nuisance; however, it could be harnessed as a potential source of nutrients like nitrates and phosphates in integrated biorefinery context. In the current study, microalgae Chlorella sp. S5 was used for bioremediation of agricultural runoff and the leftover algal biomass was used as a potential source for production of biofuels in an integrated biorefinery context. The microalgae Chlorella sp. S5 was cultivated on Blue Green (BG 11) medium and a comprehensive optimization of different parameters including phosphates, nitrates, and pH was carried out to acquire maximum algal biomass enriched with high lipids content. Dry biomass was quantified using the solvent extraction technique, while the identification of nitrates and phosphates in agricultural runoff was carried out using commercial kits. The algal extracted lipids (oils) were employed in enzymatic trans-esterification for biodiesel production using whole-cell biomass of Bacillus subtilis Q4 MZ841642. The resultant fatty acid methyl esters (FAMEs) were analyzed using Fourier transform infrared (FTIR) spectroscopy and gas chromatography coupled with mass spectrometry (GC–MS). Subsequently, both the intact algal biomass and its lipid-depleted algal biomass were used for biogas production within a batch anaerobic digestion setup. Interestingly, Chlorella sp. S5 demonstrated a substantial reduction of 95% in nitrate and 91% in phosphate from agricultural runoff. The biodiesel derived from algal biomass exhibited a noteworthy total FAME content of 98.2%, meeting the quality standards set by American Society for Testing and Materials (ASTM) and European union (EU) standards. Furthermore, the biomethane yields obtained from whole biomass and lipid-depleted biomass were 330.34 NmL/g VS added and 364.34 NmL/g VS added , respectively. In conclusion, the findings underscore the potent utility of Chlorella sp. S5 as a multi-faceted resource, proficiently employed in a sequential cascade for treating agricultural runoff, producing biodiesel, and generating biogas within the integrated biorefinery concept.
09 BIOMASS FUELS↗
Advancing lightweight mirror design: a paradigm shift in mirror preforms by utilizing design for additive manufacturing
Additive manufacturing is a disruptive technology that can be leveraged by the redesign of components in most engineering fields. Fundamental engineering resources for lightweight mirrors were developed more than 30 years ago with a main design limitation, state of the art manufacturing. In this study, we present two design methodologies for the design of lightweight mirrors. The first method utilizes analytical expressions to design a traditional isogrid mirror, which provided the foundation for most lightweight mirrors to date. The second method employs a combination of topology optimization, lattice infill, and analytical estimation to develop an advanced lightweight mirror designed for additive manufacturing. The advanced mirror design outperforms the traditional design for each functional requirement, including a 94% reduction in predicted surface quilting and a higher specific stiffness. The manufacturing of the advanced mirror is only possible with an additive manufacturing process.
36 MATERIALS SCIENCE↗
Towards a more general understanding of the algorithmic utility of recurrent connections
Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation” algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and construct hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to propagating multiple interacting tags and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.
59 BASIC BIOLOGICAL SCIENCES↗
UNNT: A novel Utility for comparing Neural Net and Tree-based models
The use of deep learning (DL) is steadily gaining traction in scientific challenges such as cancer research. Advances in enhanced data generation, machine learning algorithms, and compute infrastructure have led to an acceleration in the use of deep learning in various domains of cancer research such as drug response problems. In our study, we explored tree-based models to improve the accuracy of a single drug response model and demonstrate that tree-based models such as XGBoost (eXtreme Gradient Boosting) have advantages over deep learning models, such as a convolutional neural network (CNN), for single drug response problems. However, comparing models is not a trivial task. To make training and comparing CNNs and XGBoost more accessible to users, we developed an open-source library called UNNT (A novel Utility for comparing Neural Net and Tree-based models). The case studies, in this manuscript, focus on cancer drug response datasets however the application can be used on datasets from other domains, such as chemistry.
59 BASIC BIOLOGICAL SCIENCES↗
Bacterial diversity dynamics in microbial consortia selected for lignin utilization
Lignin is nature’s largest source of phenolic compounds. Its recalcitrance to enzymatic conversion is still a limiting step to increase the value of lignin. Although bacteria are able to degrade lignin in nature, most studies have focused on lignin degradation by fungi. To understand which bacteria are able to use lignin as the sole carbon source, natural selection over time was used to obtain enriched microbial consortia over a 12-week period. The source of microorganisms to establish these microbial consortia were commercial and backyard compost soils. Cultivation occurred at two different temperatures, 30°C and 37°C, in defined culture media containing either Kraft lignin or alkaline-extracted lignin as carbon source. iTag DNA sequencing of bacterial 16S rDNA gene was performed for each of the consortia at six timepoints (passages). The initial bacterial richness and diversity of backyard compost soil consortia was greater than that of commercial soil consortia, and both parameters decreased after the enrichment protocol, corroborating that selection was occurring. Bacterial consortia composition tended to stabilize from the fourth passage on. After the enrichment protocol, Firmicutes phylum bacteria were predominant when lignin extracted by alkaline method was used as a carbon source, whereas Proteobacteria were predominant when Kraft lignin was used. Bray-Curtis dissimilarity calculations at genus level, visualized using NMDS plots, showed that the type of lignin used as a carbon source contributed more to differentiate the bacterial consortia than the variable temperature. The main known bacterial genera selected to use lignin as a carbon source were Altererythrobacter , Aminobacter , Bacillus , Burkholderia , Lysinibacillus , Microvirga , Mycobacterium , Ochrobactrum , Paenibacillus , Pseudomonas , Pseudoxanthomonas , Rhizobiales and Sphingobium . These selected bacterial genera can be of particular interest for studying lignin degradation and utilization, as well as for lignin-related biotechnology applications.
59 BASIC BIOLOGICAL SCIENCES↗
Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development
With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called ‘genoscapes’) for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.
14 SOLAR ENERGY↗
Microhole drilling technology utilizing a golden section search algorithm
A fundamental issue in microhole drilling is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings An optimization algorithm called a golden section search (GSS) was used to systematically identify the preferred WOB for a given set of conditions. This research focused on implementing and evaluating two low WOB drilling technologies for microhole drilling: - Laser-assisted mechanical drill, which was tested in the laboratory - Lightly modified commercial off-the-shelf (COTS) percussive hammer, which was tested in a limited field test. Data were collected for microhole GSS using WOB optimization via simulation as well as at the Blue Canyon Dome Site in Socorro, NM. Information on the attached files and folders are as follows: - the .tdms files are LabView data files, which can be opened within Excel using a .tdms add-in or using a Matlab .tdms converter - the .tdms_index files are part of the .tdms file structure - sampling rate, column headers, and length data within the .tdms files follow SOP when utilizing Excel and/or Matlab as described above
15 GEOTHERMAL ENERGY↗
Derisking Superhot Geothermal Plays with Value of Information: Utilizing Play Fairway Analysis, Geophysics and Technoeconomics
This paper describes a methodology for evaluating how the play fairways analysis (e.g., favorability) can improve our chances of making geothermal development decisions. We make statistical resource assessments and couple them with technoeconomic analysis utilizing previous favorability work performed for the Newberry Volcano. We demonstrate how the favorability can be used in a decision analysis framework because the Newberry favorability also estimated an associated uncertainty. The specific decision considered is how large of a power plant to build, which is difficult given the uncertainty about the resource size. Our results focus on two resource types, hydrothermal and enhanced geothermal systems, and they demonstrate how estimates of the minimum, most likely, and maximum estimates of the geothermal resource (denoted as the P10, P50, and P90, respectively) can be used in a decision analysis framework. Lastly, the value of information results explore using favorability with and without the magnetotelluric and gravity data from the Newberry Volcano. As expected, the favorability is more reliable, according to our methodology, at indicating the resource size when it includes the two geophysical models.
enhanced geothermal system↗
Momentary Cessation: Improving Dynamic Performance and Modeling of Utility-Scale Inverter Based Resources During Grid Disturbances
Sandia National Laboratories worked with NERC staff to provide stakeholder guidance in responding to a May 2018 NERC alert regarding dynamic performance and modeling issues for utility-scale inverter-based resources. The NERC alert resulted from event analyses for grid disturbances that occurred in southern California in August 2016 and October 2017. Those disturbances revealed the use of momentary cessation of transmission connected inverter-based generation- a short time period when they ceased to inject current into the grid, counter to desired transmission operation. The event analyses concluded that, in many cases, the Western Interconnection system models used to determine planning and operating criteria do not reflect the actual behavior of solar plants, resulting in overly optimistic planning assessments and substandard operational responses. This technical report summarizes the gaps between the models and actual performance that were observed at those times, and the guidance that Sandia and NERC provided to owners of solar PV power plants, transmission planners, transmission operators and planning/reliability coordinators to modify existing models to reflect that actual performance
24 POWER TRANSMISSION AND DISTRIBUTION↗
Development and Analysis of Control Strategies for a 1 MW/3.2 MWh Energy Storage System at Avista Utilities
This report documents the work performed by Pacific Northwest National Laboratory (PNNL) and Washington State University (WSU) supporting an effort to develop control strategies for a 1 MW/3.2 MWh energy storage system (ESS) at Avista Utilities (Avista). The ESS project is funded though the Washington Clean Energy Fund (CEF) program administered by the Washington State Department of Commerce (DOC). A tri-party Cooperative Research and Development Agreement (CRADA), namely the CRADA 360, was created in 2015 to facilitate this work.
25 ENERGY STORAGE↗
Distributed Acoustic Sensing (DAS) on Opportunistic Networks_ A Feasibility Study Utilizing Fiber Optic Infrastructure at NEON Sites for DAS
This study demonstrates the feasibility of using Distributed Acoustic Sensing (DAS) on the opportunistic optical fiber infrastructure presented by NEON (National Ecological Observatory Network) sites. The test took place at the NEON Terrestrial Site designated D10 CPER. Unlit portions of the local fiber network were successfully spliced together and optimized for length and a Silixa iDAS sensor was installed. The resulting array (composed of 12 spliced fiber runs) totaled 875m in length. Over a period of 2 weeks, we gathered a high spatial and temporal resolution data set to characterize discernable signals and understand background noise. The data set was reviewed to extract wave signatures of identifiable origin, both anthropogenic and otherwise. Continent wide distribution of these sites makes them an interesting candidate for DAS and identifying measurable signal sources informs future DAS application on opportunistic fiber networks. These observations validate the utility of both the NEON and similarly small fiber networks (<1km) for geoscience, environmental, and security DAS applications and indicate possibilities for further inquiry in methods for DAS data collection and analysis.
42 ENGINEERING↗
The transparent soil microcosm: a window into the spatial distribution and dynamics of carbon utilization and microbial interspecies interactions (Final Report)
This document contains the summary and final report for award DE-SC0013887 (The transparent soil microcosm: a window into the spatial distribution and dynamics of carbon utilization and microbial interspecies interactions), including the overall description of the accomplishments obtained during this work, the manuscripts published with its support, and the list of personnel funded to conduct this research.
59 BASIC BIOLOGICAL SCIENCES↗
High Speed Hybrid Reluctance Motor Utilizing Anisotropic Materials
With high cost and volatility driving continued efforts to decrease reliance on the critical heavy rare earth materials used in traction drive applications, General Motors developed three variants of heavy rare earth-free (HRE-free) electric motors. The variants focused on taking advantage of advanced magnet technologies and new rotor topologies to improve mechanical strength and achieve power targets. The three variants were a HRE-free permanent magnet reluctance motor, a synchronous reluctance motor utilizing small HRE-free permanent magnets, and an induction motor with inserted copper bars and cast aluminum end-rings. Motors were designed with the intent of primary or secondary traction applications, depending on the topology. Variant 1 achieved performance comparable to HRE-containing permanent magnet motors through optimized topology and validation of HRE-free magnets, focusing on achieving energy products and demagnetization resistance comparable to those of HRE-containing magnets. Demagnetization testing demonstrated the motor robustness to currents and temperatures exceeding expected vehicle conditions, a key challenge to the use of HRE-free magnets. The Variant 1 motor also showed the best capability of meeting the US Drive technology 2020 targets, due to the high power-density of the permanent magnet motor and the potential cost reductions enabled by the removal of heavy rare earth materials. Variant 2 exhibited high efficiency in high speed regions due to the low high-speed losses, an important consideration for secondary traction applications, and significantly thrifted on magnet mass to reduce cost. Variant 3 contained copper bars within the induction rotor to reduce losses compared to cast aluminum, while using cast aluminum end-rings to reduce the cost and mass of the rotor. Optimization of the Cu-Al interface were focused on, as the interface is prone to forming brittle intermetallic compounds during the casting process. Prototypes of each motor variant were built and tested for performance, mechanical strength, and demagnetization resistance (Variants 1 and 2 only), with torque and power resulting close to the predicted values.
33 ADVANCED PROPULSION SYSTEMS↗
Universal Utility Data Exchange (UUDEX) Phase 3 Demonstration Environment and Results
This report summarizes the Universal Utility Data Exchange (UUDEX) Phase 3 demonstration environment and tasks performed during the initial Phase 3 demonstration.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Automated Transit Fleet Electrification Planning in Response to Route Dynamics, Vehicle Utilization, and Local Climate
Transit electrification is difficult, requiring the consideration of many factors including route dynamics, vehicle utilization, and local ambient temperatures. Incumbent planning tools typically rely upon static vehicle efficiency numbers which do not consider local factors specific to each fleet. This paper summarizes a collaboration between NREL and Microgrid Labs, which produced an automated sizing tool capable of producing vehicle battery and motor sizing for drop-in electrification. Furthermore, the workflow also exports the electric-vehicle supply equipment needed to support fleet electrification. The paper summarizes the model theory and includes a sample pilot study performed in support of the Via Mobility transit fleet.
33 ADVANCED PROPULSION SYSTEMS↗