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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 397 records · Page 22

Emergent inequality and self-organized social classes in a network of power and frustration

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.

97 MATHEMATICS AND COMPUTING↗

Scalable, resilient, and configurable permissioned blockchain fabric

With the advent of Bitcoin, the interest of the database community in blockchain systems has steadily grown. Many existing blockchain applications use blockchains as a platform for monetary transactions, however. We deviate from this philosophy and present ResilientDB, which can serve in a suite of non-monetary data-processing blockchain applications. Our ResilientDB uses state-of-the-art technologies and includes a novel visualization that helps in monitoring the state of the blockchain application.

97 MATHEMATICS AND COMPUTING↗

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗

EGS Collab Testbed 1: Second Set Tracer Test Results

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead, South Dakota, where hydraulic fractures were created at an injection well drilled sub-horizontal from the drift. This file contains the second set of tracer data (also include the data uploaded previously, https://gdr.openei.org/submissions/1128) for the EGS Collab testbed. The tracer tests were conducted during October 2018 - November 2019. Injected tracers include DNA, C-dots (fluorescein nano particles), fluorescein, rhodamine-b, sodium chloride, lithium bromide and cesium iodine. The tracers have been detected in three flowing wells located about 7.5 to 9 meters away from the injection interval. The tracer breakthrough curves from these locations have been adjusted to account for the residence time in the injection and production tubing. The details about the tracer test can be found in Background and Methods of Tracer Tests (Mattson et al. (2019,a,b)) (also included in this package). References Mattson, E.D., Neupane, G., Plummer, M.A., Hawkins, A., Zhang, Y. and the EGS Collab Team 2019a. Preliminary Collab fracture characterization results from flow and tracer testing efforts. In Proceedings 44th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California. Mattson, E.D., Neupane, G., Hawkins, A., Burghardt, J., Ingraham, M., Plummer, M., and the EGS Collab Team, 2019b. Fracture tracer injection response to pressure perturbations at an injection well. GRC Transactions, Vol. 43, 2019. Neupane, Ghanashyam, Earl Mattson, Adam Hawkins, Mitchell Plummer, and Yuran Zhang. EGS Collab Testbed 1: Tracer data sets. No. 1128. DOE Geothermal Data Repository; Idaho National Laboratory, 2019.

15 GEOTHERMAL ENERGY↗

Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016

This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA. Explanation of pair subdirectories: Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011). Pair subdirectories are named by starting and ending epochs in YYYYMMDD_YYYYMMDD format. Each tarred pair directory contains GRD files for phase data (radians), unwrapped range change (drhomaskd, in m), and unwrapped range change rate (drange, in m/yr). The data are given in both latitude/longitude and Universal Transverse Mercator (Zone 11N). Raw Synthetic Aperture Radar (SAR) data from the Envisat satellite mission operated by the European Space Agency (ESA) are copyrighted by ESA and were provided through the WInSAR consortium at the UNAVCO facility. Raw Synthetic Aperture Radar (SAR) data from the Sentinel-1A satellite mission operated by ESA were available free of charge through the Distributed Active Archive Center (DAAC) at the Alaska Satellite Facility (ASF) and through the Sentinels Scientific Data Hub. References: Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; Kobrick, M.; Paller, M.; Rodriguez, E.; Roth, L.; Seal, D.; Shaffer, S.; Shimada, J.; Umland, J.; Werner, M.; Oskin, M.; Burbank, D.; Alsdorf, D. The Shuttle Radar Topography Mission. Reviews of Geophysics 2007, 45, RG2004. doi:10.1029/2005RG000183. Sandwell, D.; Mellors, R.; Tong, X.; Wei, M.; Wessel, P. Open radar interferometry software for mapping surface deformation. Eos, Transactions American Geophysical Union 2011, 92, 234?234. http://dx.doi.org/10.1029/2011EO280002. doi:10.1029/2011EO280002.

15 GEOTHERMAL ENERGY↗

Big Data Mining for Assessing Calibration of Building Energy Models

Residential and commercial buildings in China, India, the United States (US), United Kingdom (UK), and Italy consume 39-45% of each nation's primary energy. Building energy models can be used to automatically optimize the return-on-investment for retrofits to improve a building’s energy efficiency. However, with an average of 3,000 building descriptors necessary to accurately simulate a single building, there is a market need to reduce the transaction cost for creating a more robust model for simulating every building in a city and accurately estimate savings prior to capital expenditures.We used two of the world’s fastest supercomputers, assembled unique datasets, and developed innovative algorithms for big data mining to assess different methods to create an accurate building energy model. The team has leveraged a total of eight high performance computing resources and 218 servers to analyze the best methods, metrics, and algorithms for creating an accurate building energy model beyond current industry standards necessary for private-sector financing. The project developed the world’s fastest buildings simulator, has completed over 8 million simulations totaling over 300TB, and mined this data with over 130,000 parallel artificial intelligence algorithms. This was used to quantify accuracy of AI-developed calibration algorithms with results that surpass industry standard guidelines and can identify individual building parameters to between 15% and 32% of their actual value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Public Data Set: The New Pegasus-III Experiment

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in A.C. Sontag et al., 'The New Pegasus-III Experiment,' IEEE Transactions on Plasma Science 50, 4009 (2022).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cumulative Spatial Impact Layers™

Cumulative Spatial Impact Layers™ (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Applying a recursive quadtree method and multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets simultaneously by calculating data, record, or attribute density. The CSIL tool was designed based on the original approach (Bauer et al. 2015) and more information on the tool overall along with applications can be found in Romeo et al. 2019). Providing an efficient summary of disparate geospatial data, CSIL bridges the gap between understanding data and analysis. Bauer, J. R., Nelson, J., Romeo, L., Eynard, J., Sim, L., Halama, J., Rose, K., & Graham, J. (2015). A spatio-temporal approach to analyze broad risks and potential impacts associated with uncontrolled hydrocarbon release events in the offshore Gulf of Mexico (NETL-TRS-2-2015 EPAct Technical Report Series). U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV; p 60. Romeo, L., Nelson, J., Wingo, P., Bauer, J., Justman, D., & Rose, K. (2019). Cumulative spatial impact layers: A novel multivariate spatio-temporal analytical summarization tool. Transactions in GIS.

Multivariate Visualization↗

Automated Measurement and Verification and Innovative Occupancy Detection Technologies

In support of DOE’s sensors and controls research, the goal of this project is to move toward integrated building to grid systems by building on previous work to develop and demonstrate a set of load characterization measurement and evaluation tools that are envisioned to be part of a suite of applications for transactive efficient buildings, built upon data-driven load characterization and prediction models. This will include the ability to include occupancy data in the models, plus data collection and archival methods to include different types of occupancy data with existing networks and a taxonomy for naming these data within a Volttron agent platform.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Exploratory study on potential safeguards applications for shared ledger technology

The International Atomic Energy Agency (IAEA) is responsible for providing credible assurance that countries are meeting their obligations not to divert or misuse nuclear materials and facilities for non-peaceful purposes. To this end, the IAEA integrates information about States’ nuclear material inventories and transactions with other types of data to draw its safeguards conclusions. As the amount and variety of data and information has increased, the IAEA’s data acquisition, management, and analysis processes have greatly benefited from advancements in computer science, data management, and cybersecurity during the last 20 years. Despite these advancements, inconsistent use of advanced computer technologies as well as political concerns among certain IAEA Member States centered on trust, transparency, and IAEA authorities limit the overall effectiveness and efficiency of IAEA safeguards. As a result, there is an ongoing need to strengthen the effectiveness and efficiency of IAEA safeguards while improving Member State cooperation and trust in the safeguards system. These chronic safeguards needs could be met with some emerging technologies, specifically those associated with the digital currency bitcoin.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Corrections to the General (2,4) and (4,4) FDTD Schemes

The sampling weights associated with two general higher order FDTD schemes were derived by Smith, et al. and published in a IEEE Transactions on Antennas and Propagation article in 2012. Inconsistencies between governing equations and their resulting solutions were discovered within the article. In an effort to track down the root cause of these inconsistencies, the full three-dimensional, higher order FDTD dispersion relation was re-derived using Mathematica TM . During this process, two errors were identi ed in the article. Both errors are highlighted in this document. The corrected sampling weights are also provided. Finally, the original stability limits provided for both schemes are corrected, and presented in a more precise form. It is recommended any future implementations of the two general higher order schemes provided in the Smith, et al. 2012 article should instead use the sampling weights and stability conditions listed in this document.

97 MATHEMATICS AND COMPUTING↗

National Renewable Energy Laboratory (NREL) Topic 2 Final Report: End-to-End Communication and Control System to Support Clean Energy Technologies

This document is the final report of a two-year development, test, and demonstration project, 'Cohesive Application of Standards- Based Connected Devices to Enable Clean Energy Technologies.' The project was part of the National Renewable Energy Laboratory's (NREL's) Integrated Network Testbed for Energy Grid Research and Technology (INTEGRATE) initiative hosted at Energy Systems Integration Facility (ESIF). This project demonstrated techniques to control distribution grid events using the coordination of traditional distribution grid devices and high-penetration renewable resources and demand response. Using standard communication protocols and semantic standards, the project examined the use cases of high/low distribution voltage, requests for volt-ampere-reactive (VAR) power support, and transactive energy strategies using Volttron. Open source software, written by EPRI to control distributed energy resources (DER) and demand response (DR), was used by an advanced distribution management system (ADMS) to abstract the resources reporting to a collection of capabilities rather than needing to know specific resource types. This architecture allows for scaling both horizontally and vertically. Several new technologies were developed and tested. Messages from the ADMS based on the common information model (CIM) were developed to control the DER and DR management systems. The OpenADR standard was used to help manage grid events by turning loads off and on. Volttron technology was used to simulate a homeowner choosing the price at which to enter the demand response market. Finally, the ADMS used newly developed algorithms to coordinate these resources with a capacitor bank and voltage regulator to respond to grid events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Purchase Card Approver Training

The purpose of this training is to provide Purchase Card Approver with an understanding of the Los Alamos National Laboratory Purchase Card (P-Card) program so that they can be authorized to approve their cardholders U.S. Bank-issued VISA® card transactions and to ensure they are in compliance with Laboratory policies and procedures governing card use.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

California CO 2 Storage Assurance Facility Enterprise (C2SAFE): Final Technical Report

The California CO 2 Storage Assurance Facility Enterprise (C2SAFE) project conducted a preliminary study into the feasibility of a commercial-scale carbon dioxide (CO 2 ) storage complex located in California’s Southern San Joaquin Valley (SSJV). The work represents the first phase of a multi-phased development approach outlined by the United States Department of Energy’s (DOE’s) Carbon Storage Assurance and Facility Enterprise (CarbonSAFE) program meant to develop carbon storage sites capable of permanently storing 50 million metric tonnes of CO 2 , or greater, injected over a typical facility life of 20 to 30 years. This report represents the culmination of work performed under C2SAFE and outlines a phased implementation plan for large-scale, industrial carbon capture and permanent storage in California’s SSJV. The report is meant to be a standalone document and as such provides high-level summaries of all tasks of the project, but is also meant to complement the other three topical reports issued by the project – reports referenced herein. The study considered multiple scenarios including an east-side storage facility, a west-side storage facility, and potential multi-site storage facilities. The east-side storage facility is to be located at Clean Energy Systems, Inc.’s Kimberlina Power Plant, or nearby, and the west-side facility will be located at the California Resources Corporation’s (CRC’s) Elk Hills oil field. The majority of carbon emissions are planned to be captured from existing sources and transported to the selected and verified storage site(s). Capture from the single closest source to the eastern storage facility and the sources within the Elk Hills field would meet the CarbonSAFE storage goal of 50 million tonnes. The study has shown there is sufficient storage capacity to meet this requirement and more; thus, capture from any of the numerous additional large nearby sources would substantially leverage the CarbonSAFE investment. A comparison of preliminary CO 2 capture, transportation, and storage costs to economic value and incentives in the state shows current market conditions make it economically feasible to develop large-scale industrial storage sites in California’s SSJV. The business case for Carbon Capture and Storage (CCS) in California’s SSJV appears economically viable today for large CO 2 point sources involved in the production of transportation fuels, such as oilfield cogeneration units and steam boilers. The overall levelized CCS cost is estimated at roughly 125 per tonne of CO 2 , which includes CO 2 amine-solvent post-combustion capture, transportation, and storage. The levelized CO 2 capture cost is based on today’s technology, with no future cost reduction factored in for technology improvement. The sum of the value of incentives and revenue from California Low Carbon Fuel Standard (LCFS) credits (discounted roughly 20% from their current transaction value), sale of California cap-and-trade emission allowances, and Section 45Q tax credits—either for saline storage or the Enhanced Oil Recovery (EOR) credit plus CO 2 sales revenue—is about 165/tonne-CO 2 . The economic viability of CCS for Natural Gas Combined Cycle (NGCC) power plants in the SSJV is more site-specific. A plant providing power solely to the electric grid, if it added CCS, should be eligible for Section 45Q tax credits and could sell its excess cap-and-trade emission allowances, but it would not generate LCFS credits. Using the cost and incentive values detailed in this report, it would not be economical for such a plant to add CCS today, barring other considerations. An NGCC plant within an oilfield (e.g., CRC Elk Hills and NRG Sunrise) that provides power to the oilfield as well as to the grid should receive “partial credit” in terms of generating LCFS credits if it added CCS (pro-rated for the fraction of power going to the oilfield). Such a plant should also be eligible for Section 45Q tax credits and garner revenue from selling its excess cap-and-trade emission allowances. Using the cost and incentive values described in this report, the economic viability of adding CCS today would depend on the relative fractions of electricity supplied to the oilfield and the grid. As the value of cap-and-trade emission allowances grows over time (either by market forces or the escalating floor price), the relative fraction of power needing to remain in the oilfield to achieve “breakeven” would diminish. At some point, even plants providing all their power to the grid would be candidates for economical CCS application. The C2SAFE team has proposed to expand upon the knowledge gained during this study by conducting a detailed feasibility assessment under a follow-on phase of the program, Phase II – Feasibility. This would include detailed data collection at the two sites, analysis, reporting, stakeholder outreach, and risk mitigation activities to support the development of a commercial carbon storage complex in the SSJV.

58 GEOSCIENCES↗

Final Technical Report: Amicus O&M Cooperative

Despite the maturation of the broader solar PV industry, the operations and maintenance (O&M) market segment is still relatively under developed. The lack of industry coherence jeopardizes the long-term performance of multiple gigawatts of installed capacity, and thus, the legitimacy of solar PV as a dependable source of electricity generation in the U.S. To address these challenges, the project team formed a new company, the Amicus Operations and Maintenance (O&M) Cooperative, whose mission is to ensure that solar PV fulfills its promise as a responsible and reliable energy source, for generations to come. Amicus O&M Cooperative created solutions to the market gaps by establishing a consistent level of O&M service offerings; standardizing scopes of work and legal agreements; training and certifying technicians; minimizing transaction costs for asset owners; and mitigating risk by creating redundancy in the companies who are able to perform work to these standards. We attracted double the number of member-companies originally forecast (goal: 10, actual: 20), broadening the reach of the service area, minimizing travel costs, and reducing response times for O&M services. We built a professional website and a software platform for managing work orders. Lastly, we have established multiple channels for communication among members, including monthly calls for sales topics and for technical/operational topics, an intranet for announcements/ questions/articles, and regular in-person meetings in association with the meetings of our sister cooperative, Amicus Solar. Throughout the project, participants sought feedback, input, and insights from stakeholders in the O&M market segment, including current and potential member-companies and potential clients. The problem statement above was confirmed many times over, with additional insight on the need for more workforce development, driving efficiency and lowering cost through better data analysis and remote diagnostics, and finding ways to reduce the cost of secondary and ancillary services as well (including items such as vegetation management and module cleaning). For solar to maintain its status as a reliable energy source – and for it to continue attracting investment – it must perform to expectation. This is where solar PV O&M technicians come into play. The cooperative helps them perform their work more cost effectively by streamlining “soft costs” including legal costs and work management, as well as reducing travel time and expenses. The new cooperative has demonstrated significant price reductions for O&M services relative to reported industry averages, which benefits clients directly and the public indirectly through cleaner air, economic development, and job growth.

14 SOLAR ENERGY↗