Large-Scale Visualization on Exascale Hardware Technical Advances in the Era of Big Data Analysis and Visualization LDAV 2020 Panel.
Abstract not provided.
Moreland, Kenneth D.↗
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Results for “technical”
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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NM Technical Working Group: Balancing Standards Development with User Priorities and Platform Needs.
Abstract not provided.
Gunda, Thushara↗
Santa Barbara Desalination Digital Twin Technical Report
A digital twin is a computer model that has sufficient breadth and fidelity to enable diagnostic and predictive analyses for outputs of interest. We have constructed a digital twin of the SB desal plant using the ProteusLib software developed for NAWI under task 4.2.2, and specifically the ProteusLib models of pumps, filters, mixers, splitters, and reverse osmosis units and a seawater property model. The steps needed to configure this digital twin with the real conditions of the SB desal plant are: (1) Data reconciliation, which is gathering the data and plant connectivity and ensure that all relevant values are present and in the correct units and validating the data using material and energy balances, and correct for errors, gaps, or deviations; (2) Parameter estimation, which is matching model parameters with data from previous step, filling missing parameters with initial estimates, then iteratively refining estimated values. Once we completed the digital twin, we used the optimization capabilities of ProteusLib to compute outputs of interest over a chosen range of inputs. The primary output of interest to the owners of the plant is its specific energy consumption (kWh/acre-foot). The remainder of this report will provide more detail on the data reconciliation, parameter estimation, and analyses we performed.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Assessing the drivers of Isoprene SOA: laboratory studies, field observations and modeling (Final Technical Report)
This report describes the research results and products stemming from the funding award DE-SC0018221. The main goals of this project were to develop a quantitative understanding of the factors driving secondary organic aerosol (SOA) formation from biogenic volatile organic compounds, namely isoprene and monoterpenes, using a combination of laboratory measurements, field data analysis, and modeling. Specifically, we aimed to: 1) develop an observationally constrained volatility distribution of trace gases produced from the oxidation of biogenic hydrocarbons that can explain the formation of SOA from in situ observations made during DOE ASR/ARM field campaigns such as HI-SCALE and BAECC 2) use new and existing (e.g. DOE ASR funded SOAFFEE experiments) laboratory chamber experiments to develop detailed parameterizations of isoprene-derived epxoy diol (IEPOX) reactive uptake, including product branching, product volatility, and solubility constants, as well as SOA formation generally from the formation of highly oxygenated organic molecules (HOM) formed from isoprene and monoterpene photo-oxidation that can be directly incorporated into models. 3) collaborate with PNNL modeling teams to incorporate new parameterizations into detailed box models, such as MOSAIC, and regional or Earth System models such as WRF.
54 ENVIRONMENTAL SCIENCES↗
Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) (Technical Reference Manual V.4)
The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane infrastructure and transportation systems. HyRAM+ is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ includes generic probabilities for equipment failures, probabilistic models for the impact of heat flux on humans and structures, and experimentally validated first-order models of release and flame physics. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impact on people and structures. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards. HyRAM+ is a research software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals. This document provides a description of the methodology and models contained in HyRAM+ version 4.0. The most significant change for HyRAM+ version 4.0 from HyRAM version 3.1 is the incorporation of other alternative fuels, namely methane (as a proxy for natural gas) and propane into the toolkit. This change necessitated significant changes to the installable graphical user interface as well as changes to the back-end Python models. A second major change is the inclusion of physics models for the overpressure associated with the delayed ignition of an unconfined jet/plume of flammable gas.
02 PETROLEUM↗
Regulation of Chloroplast Division and Compartment Size (Final Technical Report)
During leaf growth and development, chloroplasts numbers increase as cells expand to maximize energy capture and photosynthetic capacity. Chloroplasts proliferate by dividing in the middle, producing a large population of small organelles of similar size and shape. This process is orchestrated by macromolecular complexes located both inside and outside the chloroplast whose assembly and contractile activity across the two envelope membranes must be coordinated and spatially regulated. Through research supported by our DOE funding, and by exploiting the powerful model system Arabidopsis thaliana, we have significantly advanced our knowledge of how coordination of the division complexes is achieved and how division-site placement is spatially restricted to the middle of the chloroplast. Using chloroplast division mutants, we gained new understanding of how chloroplast size and shape influence chloroplast movement and photosynthetic performance. We identified a gene contributing to natural variation in chloroplast size. Major findings are highlighted.
59 BASIC BIOLOGICAL SCIENCES↗
Boundary Layer Controls on the Shallow-to-Deep Cumulus Transition (Final Technical Report)
This project advanced our understanding of the processes governing cumulus cloud formation and provides an improved observational basis for validating earth system models. To be specific, the project used laser- and radar-remote sensors to examine the physical properties of updrafts that rise from earth’s surface and initiate clouds deeper in the atmosphere. These updrafts comprise “thermals” and “plumes” and occur at small spatial and temporal scales (e.g., 10s of minutes, 100s of meters). These small scales preclude explicit representation in most earth system and climate models, and thus necessitate “sub-grid-scale” parameterization of updraft processes. The innovation of this project was to directly measure the size, shape, strength and water vapor content of these updrafts with Doppler and Raman lidars, respectively, and to link these updraft properties to cloud processes using vertically pointed weather radars. The resulting data sets comprise 100s of thousands of updrafts and thousands of clouds, which far exceeds previous efforts, and thereby provides a robust statistical and physical representation of these processes. From these large datasets the project produced a sequence of scientific analyses that: (1) Elucidate how variations in the turbulent structure of the convective boundary layer control shallow cumulus convection, (2) Quantify the upward transport of water vapor to cloud base via thermals and plumes, (3) Validate large-eddy simulations of updrafts and shallow convective clouds, (4) Demonstrate a size-to-strength relationship between updraft width and updraft speed, and (5) Demonstrate how updrafts interact with the stability at the top of the convective boundary layer to modulate the depth and vigor of convective clouds. These results have been disseminated via several published journal articles, academic theses, and conference presentations. Collectively these results contribute to the Atmospheric System Research (ASR) program’s goal to “improve understanding of the key cloud, aerosol, precipitation, and radiation processes that affect the Earth’s radiative balance and hydrological cycle, particularly processes that limit the predictive ability of regional and global earth system models”.
54 ENVIRONMENTAL SCIENCES↗
CO 2 Source Assessment, Wabash CarbonSAFE Subtask 10.1 (Technical Report)
This document describes the CO 2 source at Wabash Valley Resources, namely the gasification process and configuration of the facility, and separation of the hydrogen product from the CO 2 byproduct which will be captured for subsurface storage. This document then presents a summary of CO 2 storage considerations and estimated project expenses for adding CO 2 capture and sequestration to the existing gasification plant.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
MHKiT: Application of the IEC TC-114 Technical Specifications for Data Processing.
Abstract not provided.
Olson, Sterling Stewart↗
High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)
Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Final Technical Report - Fuel-Efficient Platooning in Mixed Traffic Highway Environments
Platooning has become a focus area for heavy-duty vehicle fuel savings during highway driving. Often, the platoon formation is controlled by a system called Coordinated Adaptive Cruise Control (CACC). CACC platooning seeks aerodynamic fuel economy benefits while simultaneously decreasing driver strain by setting and maintaining a desired headway from preceding vehicles. Under close following conditions, the controller must exhibit robust characteristics during testing to be considered safe. Specific to this study, real-time vehicle to vehicle (V2V) communication shares vehicle state information among members of the same platoon, enhancing control response as the platoon members adjust to surrounding vehicles. Trucks not on the leading or trailing edge of the platoon exhibit benefits stemming from a push effect from the truck behind and a pull effect from the truck preceding it.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Exploring Novel Technologies for Particle Tracking in Gas TPCs (Final Technical Report)
This report provides the final results from R&D on a novel 2D readout for a time projection chamber (TPC), which operates with negative-ion drift. The readout consists of two gas electron multiplier (GEM) devices places at an angle with respect to each other. The 2D range of particles interacting in the TPC is reconstructed using pulse-shape timing only. Due to the low diffusion and drift speeds of the negative-ions carrying the track information to the anode, the track resolution is <200 microns. Acquiring this level of resolution for short, low energy particle tracks in a standard TPC would require a fine granularity strip or pixel readout with many 1000s of electronic channels. With this novel readout, only two channels are needed. Our results showed that the concept is fundamentally sound. We found a number of issues related to how well the timing signals are determined from the pulse waveforms. Solutions for these had to be left for future R&D.
47 OTHER INSTRUMENTATION↗
Nanometal-Interconnected Carbon Conductors (NICCS) for Advanced Electric Machines (RIT Final Technical Report)
Recent advancements in carbon nanotube (CNT) research have enabled lightweight, conductive wires as a transformative technology. Metal-carbon nanotube (CNT) hybrid conductors aim to combine the high conductivity of traditional metals with the low mass and temperature coefficient of resistance (TCR) of carbon nanotubes. The high conductivity of copper makes it a promising candidate to combine with CNTs in a hybrid structure, but there is limited physical and electrical interaction between copper and CNTs. The use of an interfacial layer offers one method of improving the interconnection of a Cu-CNT hybrid conductor. Over the course of this grant, a joule heating-driven chemical vapor deposition (CVD) technique was developed to deposit nanometal seeds throughout a porous, low-density (0.12 g/cm 3 , ~10 tex or mg/m) CNT roving template. Modification of the applied current to the CNT roving allows for the tuning of depositions towards either hot-spot site-specificity or overall uniformity. The effects of temperature, pressure, precursor mass, and the interval of applied current were investigated, demonstrating nanometal depositions ranging from less than 5 % w/w to over 85 % w/w. The versatility of CVD allows for a wide variety of metals to be deposited including copper, titanium, nickel, silver, tungsten, palladium, platinum, ruthenium, rhodium, and iridium. One preferred demonstration involved using platinum depositions to improve the electrical properties of metal-seeded CNTs across all mass loadings studied. Moreover, when the metal-seeded CNT wires were electroplated with copper, densified, and annealed under hydrogen/argon; the result was a Cu-CNT hybrid conductor with the highest conductivities reported to date. The good interconnection of the metal and CNT portions results in a stable conductor. An electrical conductivity of 16-20 MS/m was achieved for multiple Cu-CNT hybrid conductors at 150 °C, which exceeds the program goal for conductivity of greater than 15 MS/m for a 1 m long CNT wire. Overall, the research outcomes from the project showed improvements in CNT wire fabrication from roll-to-roll CVD grown carbon nanotube wires using nanometal interconnects to bridge CNT-to-CNT junctions, thus mitigating network contact resistances. Advanced nanometal interconnected carbon conductors (NICCs) were developed as a means to achieve novel light-weight wiring appropriate for applications that require the conductivity of metallic (i.e., Cu, Al, etc.) wires at elevated temperatures. High conductivity, low TCR electrical conductors such as the nanometal interconnected Cu-CNT hybrids have numerous future applications towards high efficiency motors, generators, and transformers. Specifically, the advanced wires have the ability to operate at lower resistance during conditions for standard electric motors at 150 °C, which would improve the electrical efficiency while lowering energy needs.
36 MATERIALS SCIENCE↗
R3IT, Rapid Rural Resilient Interconnection Toolkit, Final Technical Report
Utilities nationwide are beginning to experience multiple solar interconnection requests per day. This request volume will soon overwhelm utility engineers, especially at smaller utilities which serve the majority of the landmass of the United States. In this project, we developed open-source software tool that automates the interconnection approval process and removes 80% of the time required to approve an interconnection and hence allow more solar to be quickly and safely integrated with the grid. This software is accompanied by a guidebook detailing interconnection best practices and utility lessons learned. Competing solar interconnection software is extremely expensive at ten times the cost of typical distribution engineering tools, it’s closed source which makes it hard to integrate into utility workflows, and it doesn’t address the hardest power flow modeling challenges of interconnection screening. Our solution was built built with our utility partners who are already experiencing multiple interconnection requests per day and integrates best practices from our past work with DOE and the cooperative community on solar integration. The resulting free and open-source solution has been disseminated through our media channels and conferences that engage over 1,900 utilities nationwide.
14 SOLAR ENERGY↗
NASNF Processing and Packaging Technical Study
The ABD program will require development of a strategy for the dispositioning the Non-Aluminum Spent Nuclear Fuel (NASNF), some of which will be very challenging to handle and dissolve as described in this report. Not all the NASNF is suitable for processing through the electrolytic dissolver. The strategy may involve dissolution of the majority of the NASNF inventory in the electrolytic dissolver combined with some other disposition alternative(s) for the fraction that is not suitable for electrolytic dissolution. This report highlights the risks and challenges associated with the baseline approach of using the electrolytic dissolver to process all of the NASNF. In addition, the characteristics of the NASNF and how those characteristics relate to the risks associated with electrolytically dissolving the specific fuel types.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Light Relics of the Early Universe (Final Technical Report)
The research supported by this award invested two types of signals left over of the early universe that might be observed in maps of the universe: (i) particles produced (thermal relics) during the hot big bang and (ii) signals left in the seeds of structure left from from an inflationary epoch prior to the hot big bang (inflationary relics). The research into thermal relics exposed new signatures of the cosmic neutrino background in the distribution of galaxies, culminating in the first measurement of the neutrino induced phase shift of the baryon acoustic oscillations. Subsequent research explored implications of constraints on hot light particles from the cosmic microwave background and the large scale structure for the physics of dark matter. Green and collaborations also investigated cosmological signatures from the inflationary epoch, including the best constraint to date on oscillatory features in seeds of structure and the first viable proposal to test the quantum origin of structure in the universe.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Simultaneous mitigation of density and energy errors in approximate DFT for transition metal chemistry (Final Technical Report)
There were three major goals and objectives of this project: 1) Develop tools to understand density-driven errors in transition metal complexes, 2) Evaluate and minimize energy delocalization error and static correlation error through judicious functional choice, and 3) applying this workflow to machine-learning accelerated screening of redox couples. Over the reporting period, we developed a framework for eliminating flat plane errors. We introduced fully non-empirical coefficients. We demonstrated the approach on both molecules and solids. We investigated and eliminated density driven errors and demonstrated their impact on potential energy surfaces. We trained machine learning models both in a method-dependent fashion and to predict errors in method accuracy. We built large data sets of small molecule energetics and multi-reference character.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Regimes of Kinetic Magnetic Reconnection in the Laboratory (Final Technical Report)
The DOE award No. DE-SC0019153, supported in part one graduate student (J. Olson) and material expenses, enabling the student to prepare a basic plasma physics experiment on magnetic reconnection (which we now call the Terrestrial Reconnection Experiment, TREX) within at the Wisconsin Plasma Physics Laboratory (WiPPL). The study of the collisionless magnetic reconnection constituted the primary research carried out under this grant and lead to new observations of unexpected shock formation below the TREX reconnection layer. The shock formation was found fundamental to regulating the normalized rate of reconnection, and the results were part of our experimental observations detailed in a paper first authored by Dr. J. Olson and now published in the Journal of Plasma Physics. In this Report we review the general motivation of this work and provide an overview of our experimental results enabled by the support through the award.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗