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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lithologies and Depositional Environments for the NATCARB Saline Reservoirs

This dataset summarize the results of a literature review performed to define the primary lithologies and depositional environments for the target reservoir units defined by the National Carbon Sequestration Database (NATCARB) Saline reservoir 10km Grid data layer, accessible at https://edx.netl.doe.gov/dataset/natcarb. The potential saline storage reservoirs, defined in the Saline 10km Grid layer and in this sheet as "RESOURCE_NAME", were summarized and a literature review was completed to define the primary lithology and depositional environment, and sometimes a secondary lithology and depositional environment for each rock unit. If no verifiable resources were found during the literature review, the primary and secondary lithology and depositional environments were left blank. This file is organized by sheets for each of the 7 Regional Carbon Sequestration Partnerships (RCSP): Big Sky Carbon Sequestration Partnership (BSCSP), the Midwest Geological Sequestration Consortium (MGSC), the Midwest Regional Carbon Sequestration Partnership (MRCSP), the Plains CO₂ Reduction Partnership (PCOR), the Southeast Regional Carbon Sequestration Partnership (SECARB), the Southwest Regional Partnership on Carbon Storage (SWP), and the West Coast Regional Carbon Sequestration Partnership (WESTCARB). The partnerships last updated the NATCARB database in 2015.

Basin↗
DOE OSTI2025

EDX ClaiMM

EDX ClaiMM is a centralized data & analytical platform designed to revolutionize U.S. critical minerals and materials (CMM) activities. By providing a robust digital infrastructure, ClaiMM will accelerate the combination, leveraging, and rapid utilization of vital data, advanced tools, and cutting-edge research advancements in CMM. This adaptive digital research hub connects the CMM community to essential knowledge products and offers access to interoperable datasets, databases, models, software, and tools from the National Energy Technology’s (NETL’s) Energy Data eXchange (EDX) and other authoritative sources, serving both public and private sectors. EDX ClaiMM delivers AI-informed solutions to address fundamental knowledge gaps and fosters the innovation of new techniques for enhanced characterization and recovery of CMMs within the U.S. By leveraging cloud-hosted, scalable digital infrastructure, ClaiMM meets public–private applied energy needs. It equips the CMM community with priority digital resources that harness on-site and cloud compute capabilities, enabling big data storage, advanced processing, analytics, and visualization.

Critical Materials; Critical Minerals; Rare Earth ↗
DOE OSTI2021

Anomaly Detection in Accelerator Facilities Using Machine Learning

Synchrotron light sources are user facilities and usually run about 5000 hours per year to support many beamlines operations in parallel. Reliability is a key parameter to evaluate machine performance. Even many facilities have achieved >95% beam reliability, there are still many hours of unscheduled downtime and every hour lost is a waste of operation costs along with a big impact on individual scheduled user experiments. Preventive maintenance on subsystems and quick recovery from machine trips are the basic strategies to achieve high reliability, which heavily depends on experts’ dedication. Recently, SLAC, APS, and NSLS-II collaborated to develop machine-learning-based approaches aiming to solve both situations, hardware failure prediction and machine failure diagnosis to find the root sources. In this paper, we report our facility operation status, development progress, and plans.

Accelerator Physics↗
DOE OSTI2023

Factors Influencing Building Demand Flexibility

The U.S. Department of Energy’s National Roadmap for Grid-interactive Efficient Buildings (GEB) acknowledged that building demand flexibility (DF) is both an important strategy to decarbonizing the buildings sector and an important resource for meeting the changing needs of the electrical grid such as improving grid reliability. However, understanding the complexity and uncertainties in real building field performance of DF strategies is a large gap hindering stakeholders on both grid and buildings side to make investments on deploying such strategies. The research work in this report intended to advance understanding of the variability and influential factors in building demand flexibility. Adding such knowledge based on lab testing results and measured performance data from real buildings is an important contribution. The report uses standardized metrics and methods to quantify DF performance from field-measured DF datasets of two significant building groups of big-box retail and medium office buildings to present the challenge of building DF variability in multiple dimensions. The report presents findings related to how several key factors influence building demand flexibility from implementing a common, cost-effective DF control strategy (i.e., adjusting zone temperatures). The findings are supported by full-scale lab testing, field data analysis and simulation research. The authors also provided application-oriented recommendations to stakeholders such as building aggregators, utility program design professionals, sophisticated building portfolio owners, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Benchmarking Demand Flexibility in Commercial Buildings and Flattening the Duck – Addressing Baseline and Commissioning Challenges

With the transition from our traditional electric grid to a cleaner grid with renewable power generation, there is a need to enable building loads to be flexible. Load shedding and shifting will be essential for flattening the “Duck” for decarbonization. This paper explored the trend in the timing of DR events as a reflection of the grid’s needs using recent four years of event data from 203 retail stores in 11 states. The events are becoming significantly shorter with 2-hour duration being the most popular; shifting to late afternoon and early evening is another trend beyond California. Benchmarking will be essential for accounting DF as a reliable grid resource. This paper addresses a challenging aspect of benchmarking – inaccuracies in counterfactual baseline methods can introduce significant DF metrics variations in addition to weather and building characteristics related factors. The conventional “10/10” with adjustment baseline method has inherent limitation by design for load shifting applications. Therefore, it is imperative to identify alternative methods. This study compared three hourly regression baseline methods with “10/10” methods using two groups of commercial buildings that participated in DR programs: (1) 121 big-box retail stores, and (2) 11 office buildings in CA. The 14-day hourly outdoor temperature regression method was found to produce least error in the tested datasets and is promising for load shifting. The paper also pointed out that commissioning issues can also be a significant barrier for achieving consistent DF performance, which building managers and utilities should be aware of.

Liu, Jingjing↗
DOE OSTI2020

The First Three Seconds: a Review of Possible Expansion Histories of the Early Universe

It is commonly assumed that the energy density of the Universe was dominated by radiation between reheating after inflation and the onset of matter domination 54,000 years later. While the abundance of light elements indicates that the Universe was radiation dominated during Big Bang Nucleosynthesis (BBN), there is scant evidence that the Universe was radiation dominated prior to BBN. It is therefore possible that the cosmological history was more complicated, with deviations from the standard radiation domination during the earliest epochs. Indeed, several interesting proposals regarding various topics such as the generation of dark matter, matter-antimatter asymmetry, gravitational waves, primordial black holes, or microhalos during a nonstandard expansion phase have been recently made. In this paper, we review various possible causes and consequences of deviations from radiation domination in the early Universe - taking place either before or after BBN - and the constraints on them, as they have been discussed in the literature during the recent years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Petrographic and spectral study of hydrothermal mineralization in drill core from Hawaii: A potential analog to alteration in the martian subsurface

Abstract Continuous rock core was collected for 1764 m (5786’) on the Pohakuloa Army Training base near the center of the big island of Hawaii. The core traverses basaltic lava flows from the volcano's shield-building phase, and perched aquifers and higher temperature groundwaters were encountered. The collected samples record water-rock interactions of basaltic materials in a setting that may be a model for groundwater interactions on Mars. We collected visible and infrared point spectra of materials in the lowest portion of the core, where alteration was noted to become more prominent. We identified three types of phyllosilicate spectral signatures and three types of zeolites. The phyllosilicates show similarity to those identified on Mars using data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). Based on the field survey, 25 depths were selected for sampling and petrographic analysis of thin sections. The spectral data and thin section work have a strong agreement in the types of materials identified by the two different techniques. Both the spectral and petrographic data indicate low to moderate temperature geothermal alteration occurred in the lower half of the core. The field spectra are a useful reconnaissance tool for selecting mineralogic diversity for subsequent higher resolution and more time-consuming laboratory analysis.

Geochemistry & Geophysics↗
DOE OSTI2020

Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)

This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019) (Final Report)

Supersymmetry (SUSY) is one of most elegant extensions of the Standard Model (SM) and explains the puzzles of the SM by providing a candidate to explain the dark matter content of the universe, allowing scientists to understand the origin of the electroweak scale requiring the top mass to be around 170 GeV and leading to the unification of forces at a grand unified scale. Further the minimal supersymmetric standard model (MSSM) predicts the Higgs boson mass to be less than 135 GeV. The discovery of the Higgs Boson with mass around 125 GeV at the LHC has provided a major support to SUSY ideas. Searches for SUSY are ongoing at the Large Hadron Collider (LHC). Direct and indirect dark matter experiments are searching for a particle dark matter candidate which arises most naturally in SUSY models. Proton decay predicted by SUSY grand unified theories is being searched for at deep underground experiments. In addition, recent advances in neutrino and dark matter physics, observational astrophysics, precision cosmology and the promising new window into the cosmos opened by the direct detection of gravitational waves, have brought new ideas on the potential connections between new fundamental particles and our understanding of their impact on the early universe and its evolution. At present, the major questions include: Is SUSY still the best candidate for models beyond the SM? Do we have any well motivated alternative to SUSY? Have we exhausted all possibilities to search for new physics at high and low energy scales? XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019), hosted by Texas A&M University – Corpus Christi during May 20-24, 2019, provided a unique venue to discus and understand the status of SUSY, connection between particle physics and cosmology, supersymmetry and its alternative, Higgs sector, neutrino sector, flavor sector, dark matter, electroweak phase transition, astroparticle physics, gravitational waves and string theory. Discussion of results from the LHC, recent neutrino experiments and observations, direct and indirect dark matter detection experiments, detection of gravitational waves, data from particle colliders, as well as measurements of the CMB and Large Scale Structure were an integral part of SUSY 2019. To ensure the younger participants will benefit from the conference the most, the conference was preceded by the 4 day long pre-SUSY summer school for graduate students and postdocs. The invited speakers were leading scientists in the fields of SUSY interest. The school took place on Texas A&M University – Corpus Christi campus during the week prior the SUSY 2019 conference (May 15 – 18, 2019). Since its inception in 1993, SUSY has become one of the most important and widely attended international meetings in high energy physics, devoted to new ideas in fundamental particle physics. SUSY 2019 brought together approximately 250 scientists, theorists, phenomenologists, experimentalists and cosmologists, (including over 60 graduate students and 70 postdocs) representing 22 nations: Australia, Belgium, Canada, Chile, China, Colombia, France, Germany, India, Italy, Japan, Mexico, Peru, Portugal, Romania, South Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom and United States. SUSY 2019 provided a stimulating venue for the exchange of scientific ideas among experts in dark matter, neutrino physics, particle physics, astrophysics and cosmology. The following scientific topics were delivered during SUSY 2019 in form of 44 plenary talks and over 200 parallel talks: Unification of Forces; Electroweak, Top and Higgs Physics; Precision Calculations and MC tools; BSM in Flavor Physics; Neutrino Masses: Models and Phenomenology; Cosmology and Gravitational Waves; Dark Matter, Astroparticle Physics; Formal Field Theory and Strings; Alternatives to Supersymmetry; Quantum Information: Machine Learning/Big Data. 28 talks were given during the pre-SUSY program related to the following topics: Neutrino Physics; Big Data; Collider Physics & SUSY; String Phenomenology; Cosmology; Dark Matter; SUSY Models and Phenomenology

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Evaluating the Effectiveness of an Ultrasonic Acoustic Deterrent in Reducing Bat Fatalities at Wind Energy Facilities

This project was designed to use thermal video cameras and fatality monitoring to evaluate the effectiveness of an ultrasonic acoustic deterrent (UAD) on bat activity and mortality, respectively. Our goals were to redesign the UAD device and installation infrastructure, determine the placement on wind turbines to optimize safety, compatibility and functionality, and to compare the mortality among the following conditions: Control (deterrents off and turbines feathered up to the manufacturer’s cut-in speed of 3.5 m/s), Deterrent (deterrents on and turbines feathered up to the manufacturer’s cut-in speed of 3.5 m/s), Curtailment (deterrents off and turbines feathered up to 5/ m/s), and combination (deterrents on and turbines feathered up to 5 m/s). The project was divided into a Feasibility Study and Comparative Study. The objectives for the Feasibility Study were to develop an installation strategy, redesign a previous iteration of a UAD to improve performance and weatherization, and test the effectiveness of the deterrents on bat activity. The Feasibility Study was intended to work out potential issues using a relatively small number of devices prior to manufacturing and installing numerous devices for a larger-scale comparative study. The division of the project into these separate studies was based on previous experience and the challenges of assessing the capabilities of an untested UAD. During the initial development and manufacturing of the UAD, NRG Systems decided to use a piezoelectric transducer rather than an electrostatic transducer, which was used by a previous device (i.e. Deaton UAD). NRG Systems conducted lab testing (i.e., IP67 or Ingress Protection) to ensure no water or dust ingress. In addition, shock/drop trials and variations in temperature exposure were conducted as part of the reliability testing. NRG Systems also developed a communications system to allow for continuous performance monitoring of the UADs. For the Feasibility Study, we installed 6 UADs on each of 2 Gamesa G90 2-MW wind turbines (Turbine 14 and 8) at the South Chestnut Wind Energy Facility, Pennsylvania and monitored activity under control and treatment (i.e. Deterrent) conditions using thermal video monitoring. There are two major sources of variation in bat activity (beyond the anticipated treatment effect): 1) environment around the turbines might inherently favor more activity at one than the other; 2) weather conditions on any given night or within season difference (e.g., migration later during the study period) might favor more activity on some nights than on other nights. Because we could only monitor two turbines on any night, we sought to control the potential influences of these two sources by alternating the turbine on which deterrents were activated each night. If there were no loss of data due to technical failures, this design would result in an equal number of deterrent and control nights at each turbine through the monitoring period, balancing the effects of both sources of variation. We compared the time bats spent and the number of events that occurred in overlapping cameras FOV as an indicator of risk, since 80% of the overlapping FOV of the cameras was in the RSA. Equipment failures, majority due to lightning, resulted in only 17 nights with useable data, with unbalanced treatment assignment within turbines and uneven distribution of treatment assignment throughout the observational period. This resulted in a confounding of treatment assignment and seasonal change. Deterrent treatment was measured at Turbine 14 on only 2 of the first 8 usable nights (spanning the period from 8/18-9/17), whereas 6 times on Turbine 8. From 9/18-927, deterrent was on at Turbine 14 on 6 of the remaining 10 nights, and 4 on Turbine 8. We recorded a total of 1,057 bats and observed a reduction in number of events and duration of events at the UAD-activated turbine when it was Turbine 14. When Turbine 8 had the UAD activated, we observed no difference in number or duration of events. Variation between turbines is not unusual and can cause issues when study designs have no true replication, i.e., multiple turbines per treatment. Within-turbine differences suggested a trend for reduced activity when UADs were activated, particularly for Turbine 14. These results may be caused by the overall higher bat activity at Turbine 8 and confounding of treatment assignment and seasonal trends. We mapped 58 bat events in 3-dimensional space (3D), 30 and 28 events during control and treatment conditions, respectively. We observed bats crossing the rotor plane under both control and treatment conditions and observed a total of 40 confirmed or near-collisions (i.e., target close to blade but no visual confirmation of a strike) out of a total of 1,491 medium and high confidence bat observations (880 control, 611 at treatment). Twice as many collisions/possible collisions were observed during control conditions. Given the challenges with the equipment and potential confounding of the data (i.e., different activity levels at the two wind turbines), we were unable to determine whether this initial turbine placement and orientation was optimal. Given no new information on how best to install the devices, we elected to use the same placement and orientation for the comparative study. For the Comparative Study, the objectives were to investigate the relative mortality rates among 4 treatments. We searched the area within 90 m of each turbine daily to recover the highest number of fresh fatalities possible. We were unable to detect a clear reduction in mortality from deterrents alone for any individual species. Surprisingly, mortality rate of the eastern red bat (Lasiurus borealis) was estimated to be 1.3–4.2 times as much when turbines were operating normally and UADs were on than when UADs were off. Reduction in mortality of all bat species combined due to curtailment of turbines was estimated to be between 0%–38%. This effect was nullified when, in addition to curtailment, UADs were on, with 95% confidence interval ranging from a 45% reduction to a 36% increase in mortality. This was likely due to the large proportion of eastern red bats in the total carcass population. Mortality of all low-frequency echolocating bats combined (i.e. hoary bat [L. cinereus], big brown bat [Eptesicus fuscus], silver-haired bat [Lasionycteris noctivagans]) relative to control was lower when curtailed (95% CI: 0%–74%), but the addition of UADs had no detectable effect (95%CI: 13%–79%). The combined treatment reduced mortality in silver-haired bats relative to control by 11%–99%, compared to curtailment (81% reduction–67% increase) or deterrent (82% reduction–67% increase) alone. Because silver-haired bats comprised a large proportion of low-frequency calling bats found during this study, a similar effect was seen for that group. The higher mortality observed for eastern red bats at UAD compared to control could have been caused by several factors, such as the effective range of the UAD, particularly at higher frequencies, behavior, positioning of the devices on the nacelle, or a combination of these. We used 3D thermal videography to compare control and UAD bat behavior from two turbines using a total of 203 3D bat-tracks across 34 nights. We recorded a similar number of bat-tracks between treatment groups, with 51% and 49% for control and UAD, respectively. Due to potential differences in bat behavior around spinning vs stationary turbine blades, we examined UAD effectiveness separately for non-operating turbines (feathered below cut-in speed of 3.5 m/s) and operating (normal operation above wind speed of 3.5 m/s). We found a higher proportion of bat-tracks at operating turbines (82%) compared to non-operating turbines (18%), although this does not account for overall time turbines were operating versus not. At non-operating turbines the UAD appears to be effective at reducing the amount of time, flight length, and number of passes through the rotor plane, compared to control. In addition, we found bats approached turbines similarly between control and treatment turbines, with 61% of control and 63% of UAD bat-tracks originating leeward of the hub. In contrast, at operating turbines, we saw little change in bat behavior in response to UADs. For example, we found an increase in the average duration of bat-tracks between non-operating and operating turbines for UAD but at control turbines we found average duration decreased once turbines became operational. Both control and UAD had a high proportion of bat-tracks that crossed the rotor plane (i.e., collision risk) originate from the windward side when turbines were operational 65% to 92%, respectively. Given that the UAD devices closest to the blades were orientated parallel to the blades, its possible bats were not exposed to the signal until they were close to the turbine blades, as suggested by the slightly higher mean duration within 5 meters of the blades for UAD turbines. Future research should consider concentrating UAD intensity on the areas of risk (i.e. blades) with enough buffer to allow bats to react to the sound before entering the rotor-swept area (RSA). In addition, investigating the potential of installing UAD units windward of the turbine blades (e.g. a hub-mounted UAD), particularly since even under control conditions, a relatively high proportion (65%) of crosses through the blade plane originated windward. 3D thermal videography provided valuable information on future testing strategies (e.g. device placement, UAD orientation) to improve UAD effectiveness when bats are at risk (i.e., operating wind turbines). Across the entire project we experienced issues with the operation and communication with the UADs. Most of the issues occurred during the Feasibility Study and were resolved prior to the Comparability Study. Additional challenges surfaced during the Comparability Study but were remedied immediately and are thought to have little impact on the results. We had logistical constraints at the project that limited our ability use traditional methods in our camera calibration. Several calibrations showed inaccurate scales, which may have been related to inadequate spatial coverage of “points” in the camera calibration volume. Because we were using actual video recordings of bats at a wind turbine, the behavior of bats could have concentrated “points” in specific areas of the turbine (i.e. leeward of nacelle), and limited “points” in other areas, resulting in camera calibration issues. We have plans to address these inconsistencies and improving the software and related methodologies by early 2020.

17 WIND ENERGY↗
DOE OSTI2020

TURBO: Terabits/s Using Reconfigurable Bandwidth Optics (Final Report)

Large scale, big science applications are generating petabytes of data that need to be shared among multiple locations. Moving a petabyte of data at 100 Gb/s takes 22 hours. Reducing this to single digit hours or below is clearly attractive and with future applications anticipating exabyte scale transfers, multi-terabit per second capacities are needed. This scale of capacity is available using optical systems. Core optical systems have aggregate per fiber capacities on the order of 10 Tb/s and more than 100 Tb/s system experiments have been realized in the lab. But large optical capacities are not just reserved for the core as similar system capacities are available in metro networks right up to the enterprise, campus, or data center. In general, the same technology is used today in the metro area as in the long-haul networks—reconfigurable optical add drop multiplexing (ROADM) node-based wavelength division multiplexing (WDM) systems. Data centers already support massive internal capacities on the scale of 100’s of Tb/s. As new photonic integrated technologies mature, for example through initiatives such as the Integrated Photonics Innovative Manufacturing Institute (IP-IMI), the cost of optical interfaces is expected to decrease, and higher capacity and higher performance interfaces will become more affordable. This set of circumstances creates the potential that Tb/s capacities will be available at the enterprise and campus level to support large scale science network applications.

42 ENGINEERING↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Other 95% [Slides]

This planetarium presentation shares some basic facts about the universe. It’s very OLD. It's very BIG. The visible Universe contains billions of galaxies. The Universe is EXPANDING. The expansion is speeding up. 95% of the Universe is dark. Dark Energy is discussed in more detail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

FLC Notable Technology Award Oleo-Furan Surfactant

It’s a well-kept secret that laundry detergents are harmful to the environment. The important chemical in laundry detergent, called a surfactant. Surfactants are the workhorses of laundry detergent and soaps, and they're attracted to things like grease on your hands and dirt in your clothes to wash them away. Surfactants are used in everything from shampoo, hand soap, laundry detergent, and cosmetics. Many current surfactants are made from petroleum feedstock. These petroleum-derived building blocks come with a big carbon footprint. As the need for greener feedstock alternatives for synthesizing surfactants became obvious, manufacturers turned to natural oils, such as palm kernel and coconut oil. However, these oils are costly, particularly in areas where they are not domestically produced, and using them for surfactant synthesis competes with the food supply chain. Surfactants deactivate and do not work in hard water. Hard water is common - 85% of the U.S. water supply is considered hard because of the presence of small metal ions. These metal ions cover the surfactants making them useless. To solve this problem, many manufacturers add chemicals called chelators to bind the metal ions and make the water less hard, enhancing the effectiveness of the laundry detergent. However, this solution leads to more problems, including increased cost of detergent production and a large output of environmentally harmful chemicals. There remains a strong need for effective laundry detergents that do not negatively impact the environment and are available to consumers at an affordable cost. The American Cleaning Institute (ACI), a surfactant manufacturer organizing body, is emphasizing commitment to developing bio-renewable alternatives to current surfactants in laundry detergents. That’s why chemists at SIRONIX Renewables partnered with Los Alamos National Laboratory to further develop Oleo-furan surfactants (OFS). OFS are a new class of non-toxic, non-irritating surfactants for laundry detergent. It is the only surfactant that performs effectively in cold and hard water without chelators to bind the metal ions in hard water. OFS can be produced readily from sustainable, bio-derived molecules. They are multi-functional molecules - performing the role of a surfactant and a chelator in one - and are completely bio-degradable. OFS does not rely on petroleum feedstock and is synthesized from non-food, bio-renewable cellulosic feedstock. OFS solves each of the pertinent problems facing detergents and our environment today.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallel filesystems called Atlas and Alpine)) and also began power and cooling upgrades for a 2021 exascale system called Frontier. While continuing exceptional operation of Titan, Eos, and Rhea, the OLCF released the Summit supercomputer for production on January 1, 2019. Summit debuted as the most capable and efficient system in its class and has been recognized as the most powerful system in the world for its performance on both the high performance linpack (HPL) and conjugate gradient (HPCG) benchmark applications since June 2018 according to TOP500. Summit represents the culmination of a multiyear effort between the OLCF, IBM, NVIDIA, and Mellanox to deliver a system that is unmatched for modeling, simulation, data analysis, and learning. To hit the ground running with science-ready applications on day one, application teams worked closely with the OLCF through the Center for Accelerated Application Readiness (CAAR) program for years in advance of the Summit deployment. CY 2019 was filled with outstanding results and accomplishments: a very high rating from users on overall satisfaction for the sixth year in a row; a tremendous amount of core-hours delivered to researchers from two leadership-class systems; and success in delivering on the allocation split of roughly 60%, 30%, and 10% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director's Discretionary (DD) programs, respectively (see Operational Performance section). These accomplishments, coupled with the high utilization rates (overall and capability usage), represent the fulfillment of the promise of both leadership-class machines: efficient facilitation of leadership-class computational applications. Table ES.1 presents a summary of the 2019 OLCF metric targets and the associated results. More information can be found in the Operational Performance section for each OLCF resource. The scientific accomplishments of OLCF users are a strong indication of long-term operational success, with publications this year in such notable journals and publications as Nature, Nature Physics, Nature Plants, Physical Review X, Journal of the American Physical Society, Cell, Nano Letters, and Trends in Biotechnology. Crucial domain-specific discoveries facilitated by resources at the OLCF are described in the High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility (OAR) Strategic Results section. For example, researchers used Summit to pinpoint and understand the production of proteins from genetic information, including mutations and the functional expression of disease (Section 8.2).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development and Characterization of 3D-Printed Cementitious Sytems for Innovative Nuclear Systems

The Transformational Challenge Reactor (TCR) is being developed to demonstrate a revolutionary approach to deploying new nuclear power systems by building and operating an additively manufactured microreactor. This initiative provides a unique opportunity to investigate the possibility of taking advantage of the recent development of the 3D-printed concrete system using the Sky Big Area Additive Manufacturing (SkyBAAM) printer at the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory. Two pathways have been pursued in parallel since the end of the second quarter of FY19: 1. Development of methods to characterize the performance of additive manufacturing concrete using traditional Portland-cement based solution, and 2. Investigation of the opportunity to develop innovation of printable materials with higher irradiation-resistance performance using nontraditional concrete solutions in favor of carbonated cementitious materials (CCMs). This report describes the results achieved to date for both pathways. The main results are listed below: 1. A test protocol has been established to characterize the fracture properties of 3D-printed concrete; this protocol will be used to assess the performance of printed traditional and nontraditional cementitious materials, with a focus on performance of the interfaces inherent to the additive manufacturing process. 2. A state-of-the-art review of the mechanisms, fabrication method, and performance of CCMs was conducted. CCMs appear to be a viable, highly innovative, more performant alternative to Portland-based cementitious solution for the erection of biological shield pending some materials development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗