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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

Although all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid-latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm’s adaptability displayed mixed results, as Two-Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm’s applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non-idealized images.

Julian Schima↗
NASA NTRS2026

Outgassing Characterization of Common Trash Items for Disposal By Nanoracks Airlock on the International Space Station

The arrival of the Nanoracks Airlock to the International Space Station (ISS) has provided the ISS program the capability to dispose of common trash items. The concept of operations involved the crew bagging up those items into a trash bag and then utilizing the robotic arm and the airlock to jettison the trash bag. Because of the unknown thermal vacuum stability of some of the items, a molecular contamination concern was raised by the ISS program as the trash is exposed to vacuum upon the evacuation of air from the airlock and the robotic arm moving the airlock to its jettison location. In order to characterize the representative outgassing rates for ISS trash, thermal vacuum testing was performed at White Sands Test Facility. Trash was sorted into a “lower” outgassing bag and a “mixed” bag. The “mixed” trash bag contained more items that were suspected to be not vacuum stable. Load cells were chosen as the primary means for measuring mass loss. A sharp decay in the outgassing rate was observed in the first 30 minutes followed by a slower decay. As expected, the “mixed” bag lost more mass. While Quartz Crystal Microbalances (QCMs) are often utilized to measure long term outgassing rates and the sticking coefficients of contaminants at different operating temperatures for vacuum stable materials, these measurements proved difficult due to the amount and the inclusion of materials with suspect thermal vacuum stability. Because of high rates of material outgassing, the facility was unable to maintain the CQCM temperature setpoint of 80 K QCMs.. The QCMs operating at the warmer temperatures also saturated on occasion due to high levels of condensed matter. Though testing was able to confirm high risk of outgassing contamination for the program, true sticking coefficients could not be determined, available measurements are provided herein.

Alvin Y Huang↗
NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗
DOE OSTI2015

Zeolites: Exploring Molecular Channels

Synthetic zeolites contain microscopic channels, sort of like a sponge. They have many uses, such as helping laundry detergent lather, absorbing liquid in kitty litter, and as catalysts to produce fuel. Of the hundreds of types of zeolites, only about 15 are used for catalysis. PNNL catalysis scientists Ilke Arslan and Mirek Derewinksi are studying these zeolites to understand what make them special. By exploring the mystery of these microscopic channels, their fundamental findings will help design better catalysts for applications such as biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2015

Relative permeability of hydrate-bearing sediments from percolation theory and critical path analysis: theoretical and experimental results

Relative permeabilities to water and gas are important parameters for accurate modeling of the formation of methane hydrate deposits and production of methane from hydrate reservoirs. Experimental measurements of gas and water permeability in the presence of hydrate are difficult to obtain. The few datasets that do exist suggest that relative permeability obeys a power law relationship with water or gas saturation with exponents ranging from around 2 to greater than 10. Critical path analysis and percolation theory provide a framework for interpreting the saturation-dependence of relative permeability based on percolation thresholds and the breadth of pore size distributions, which may be determined easily from 3-D images or gas adsorption-desorption hysteresis. We show that the exponent of the permeability-saturation relationship for relative permeability to water is related to the breadth of the pore size distribution, with broader pore size distributions corresponding to larger exponents. Relative permeability to water in well-sorted sediments with narrow pore size distributions, such as Berea sandstone or Toyoura sand, follows percolation scaling with an exponent of 2. On the other hand, pore-size distributions determined from argon adsorption measurements we performed on clays from the Nankai Trough suggest that relative permeability to water in fine-grained intervals may be characterized by exponents as large as 10 as determined from critical path analysis. We also show that relative permeability to the gas phase follows percolation scaling with a quadratic dependence on gas saturation, but the threshold gas saturation for percolation changes with hydrate saturation, which is an important consideration in systems in which both hydrate and gas are present, such as during production from a hydrate reservoir. Our work shows how measurements of pore size distributions from 3-D imaging or gas adsorption may be used to determine relative permeabilities.

Daigle, Hugh↗
DOE OSTI2015

GOTTCHA, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.

Freitas, Tracey↗
DOE OSTI2015

GOTTCHA Database, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.

Freitas, Tracey↗
DOE OSTI2016

Unboxing Space Rocks

The box was inconspicuous, but Lawrence Livermore National Laboratory (LLNL) postdoctoral researcher Megan Bruck Syal immediately knew its contents: two meteorites around the size of walnuts. They formed about 4.6 billion years ago and survived a history of violent collisions in the asteroid belt before being bumped into a near-Earth-object orbit by gravitational interactions with the planets. After finally raining down on Earth, these rocks were scavenged in Antarctica by researchers, sorted and classified at NASA Johnson Space Center, then mailed first-class to Bruck Syal. Now that these space rocks are in Bruck Syal’s hands, they are mere months away from fulfilling their destiny. They are to be vaporized by a high-powered laser, and the data they yield on asteroid deflection could one day save the planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Fermentation process using specific oxygen uptake rates as a process control

Specific oxygen uptake (OUR) is used as a process control parameter in fermentation processes. OUR is determined during at least the production phase of a fermentation process, and process parameters are adjusted to maintain the OUR within desired ranges. The invention is particularly applicable when the fermentation is conducted using a microorganism having a natural PDC pathway that has been disrupted so that it no longer functions. Microorganisms of this sort often produce poorly under strictly anaerobic conditions. Microaeration controlled by monitoring OUR allows the performance of the microorganism to be optimized.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Method and system to discover and recommend interesting documents

Disclosed are several examples of systems that can read millions of news feeds per day about topics (e.g., your customers, competitors, markets, and partners), and provide a small set of the most relevant items to read to keep current with the overwhelming amount of information currently available. Topics of interest can be chosen by the user of the system for use as seeds. The seeds can be vectorized and compared with the target documents to determine their similarity. The similarities can be sorted from highest to lowest so that the most similar seed and target documents are at the top of the list. This output can be produced in XML format so that an RSS Reader can format the XML. This allows for easy Internet access to these recommendations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock

Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper will describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Futility

The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.

Collins, Benjamin S.↗
DOE OSTI2017

Big Data, Big Solutions

Data—lots of data—generated in seconds and piling up on the internet, streaming and stored in countless databases. Big data is important for commerce, society and our nation’s security. Yet the volume, velocity, variety and veracity of data is simply too great for any single analyst to make sense of alone. It requires advanced, data-intensive computing. Simply put, data-intensive computing is the use of sophisticated computers to sort through mounds of information and present analysts with solutions in the form of graphics, scenarios, formulas, new hypotheses and more. This scientific capability is foundational to PNNL’s energy, environment and security missions. Senior Scientist and Division Director Bill Pike and his team are developing analytic tools that are used to solve important national challenges, including cyber systems defense, power grid control systems, intelligence analysis, climate change and scientific exploration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Chain of Custody Item Monitor Message Viewer v.1.0 Beta

The CoCIM Message Viewer software allows users to connect to and download messages from a Chain of Custody Item Monitor (CoCIM) connected to a serial port on the user’s computer. The downloaded messages are authenticated and displayed in a Graphical User Interface that allows the user a limited degree of sorting and filtering of the downloaded messages as well as the ability to save downloaded files or to open previously downloaded message history files.

Schwartz, Steven Robert↗
DOE OSTI2017

System Dynamics Analysis of Strategies to Reduce Energy Use in Aluminum-Intensive Sectors

Aluminum is one of the most widely used materials in industry, with applications in buildings, vehicles, aircraft, and consumer products. Its ubiquity is also on the rise: aluminum is beginning to supplant steel in lightweight vehicles and aircraft, and is used in many green or LEED-certified buildings. Although aluminum tends to be highly recycled, particularly by manufacturers of aluminum products, the sector as a whole is still far from a closed system. As a result, the increase in aluminum consumption also means an increase in primary aluminum production-an energy-intensive process-and an increase in consumption of the raw material bauxite, which in the U.S. is almost entirely imported. Our objectives for this study are to identify and analyze aluminum sector technologies and practices that reduce the energy required to manufacture aluminum products and reduce U.S. dependence on imported aluminum and bauxite. To accomplish these objectives, we will develop a system dynamics (SD) model of aluminum production, use and recycling in key application areas, including aerospace, ground vehicles and consumer products. The model will cover the entire aluminum supply chain as it exists in the U.S., from bauxite importing and refining, to the manufacture of products, to the product use phase and end-of-life processing steps. Aluminum flows throughout the model will be determined by the annual domestic demand for each application area as well as demand projections that extend to 2030. Energy consumption will be tracked based on the flows of aluminum through each step of the supply chain. Using the SD model, we will evaluate several technologies and practices that have the potential to reduce energy consumption and reliance on imported bauxite. These include implementation of advanced primary aluminum production technologies, increased recycling within and between application areas, increased material efficiency and increased product lifetimes. Each of these strategies results in short term reductions in energy use, and every strategy except the advance production technologies will also reduce the need for imported bauxite. This model differs from other SD models previously built to study aluminum stocks and flows in two key areas- alloy recycling and product lifetimes. Aluminum recycling is frequently complicated by the need to maintain quality of many different alloys, especially in aerospace applications. This necessitates scrap sorting and product disassembly to avoid contamination; advanced recycling processes of this type are one of the strategies to be evaluated. Product lifetime similarly complicates aluminum recycling, as products with longer lifetimes yield smaller recycling streams compared to disposable or short lifetime products, such as soda cans. When these additional complexities are accounted for in the SD model, a more realistic idea of the short term and long term impacts of the various strategies can be captured, as can any potential synergies and trade-offs between the strategies. Results of the analysis will indicate which strategy, or combination of strategies, yields the lowest cumulative energy consumption and bauxite consumption required to satisfy current and future demand for aluminum products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Deep Interactive Learning with Sharkzor

Sharkzor is a web application for machine-learning assisted image sort and summary. Deep learning algorithms are leveraged to infer, augment, and automate the user’s mental model. Initially, images uploaded by the user are spread out on a canvas. The user then interacts with the images to impute their mental model into the applications algorithmic underpinnings. Methods of interaction within Sharkzor’s user interface and user experience support three primary user tasks: triage, organize and automate. The user triages the large pile of overlapping images by moving images of interest into proximity. The user then organizes said images into meaningful groups. After interacting with the images and groups, deep learning helps to automate the user’s interactions. The loop of interaction, automation, and response by the user allows the system to quickly make sense of large amounts of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

2018 DOE Solid-State Lighting Project Portfolio

The 2018 Solid-State Lighting Project Portfolio provides an overview of all SSL projects that have been funded by DOE since 2000. Projects that were active during 2017 are found in the main body of this report, and all historic projects can be found in the appendix. Within these sections, project profiles are sorted by technology type (i.e., LED or OLED) and then by performer name. A profile is provided on each project. Each profile includes a brief technical description, as well as information about project partners, funding, and the research period. This report is updated annually, although the research described in the Portfolio changes periodically as new projects are initiated and existing ones are concluded.

SSL, lighting, project, LED, OLED, portfolio, awar↗