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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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Hanging by a thread? Forests and drought
Trees are the living foundations on which most terrestrial biodiversity is built. Central to the success of trees are their woody bodies, which connect their elevated photosynthetic canopies with the essential belowground activities of water and nutrient acquisition. The slow construction of these carbon-dense, woody skeletons leads to a slow generation time, leaving trees and forests highly susceptible to rapid changes in climate. Other long-lived, sessile organisms such as corals appear to be poorly equipped to survive rapid changes, which raises questions about the vulnerability of contemporary forests to future climate change. The emerging view that, similar to corals, tree species have rather inflexible damage thresholds, particularly in terms of water stress, is especially concerning. This Review examines recent progress in our understanding of how the future looks for forests growing in a hotter and drier atmosphere.
Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets
The rapid evolution of autonomous vehicles (AVs) has exposed the need for fast-paced development and testing processes of a variety of perception, planning, and control algorithms. To expedite development, the AV industry and researchers leverage virtual vehicle environments to simulate a range of test scenarios that may otherwise be costly or difficult to conduct on a real test track. However, the various virtual environments may have different results depending on the fidelity of various simulation features, such as vehicle dynamics, sensor simulation, and environment recreation. Herein, this tutorial article examines a proposed framework for constructing, parameterizing, and validating a virtual vehicle environment using an existing AV data set. First, an overview of several open source and commercially available simulation tools, including their associated workflows, for scene and scenario creation is presented. Next, various open AV data sets are examined to inform the data set selection for the validation framework. Then, an example workflow of recreating a real-world scene from the selected data set in a simulation tool with various emulated sensors parameterized to match the data set is demonstrated. Finally, an example AV-perception algorithm is subjected to data streams from virtual and real-world environments and suggested metrics for analyzing the results are discussed.
Opportunities for Industry to Provide Flexibility While Increasing Profitability
Supply and demand flexibility will both be needed to ensure the electricity system functions properly as the share from variable renewable generation continues to grow. Industrial manufacturing currently consumes about a third of primary energy worldwide, and electricity is projected to supply an increasing share of this demand as the global economy decarbonizes. Therefore, the ability for industry to flex demand poses an enticing opportunity to enable grid flexibility. However, large capital outlays prevent industry from voluntarily altering demand. Here we show that as battery costs continue to fall, industry will soon be able to profitably alter demand in accordance with electricity price variations. Focusing on two established industries– chlor-alkali and electric arc furnaces – and two industries with large future potential – methane pyrolysis and atmospheric CO 2 capture, we use a linear program (LP) optimization to assess the technoeconomic feasibility of flexible industrial demand across both historical and future-looking wholesale day-ahead marginal prices for the Electricity Reliability Council of Texas (ERCOT). We find positive net present values (NPV) from $\$$400K to $\$$50M using projected 2050 battery prices for industrial purchase of behind-the-meter batteries, using only arbitrage as a source of value. These results indicate that, with projected battery prices, profit-seeking industrial players could voluntarily play a future role in stabilizing a high-renewables grid where electricity prices act as accurate signals of grid needs.
WLCG Authorisation from X.509 to Tokens
The WLCG Authorisation Working Group was formed in July 2017 with the objective to understand and meet the needs of a future-looking Authentication and Authorisation Infrastructure (AAI) for WLCG experiments. Much has changed since the early 2000s when X.509 certificates presented the most suitable choice for authorisation within the grid; progress in token based authorisation and identity federation has provided an interesting alternative with notable advantages in usability and compatibility with external (commercial) partners. The need for interoperability in this new model is paramount as infrastructures and research communities become increasingly interdependent. Over the past two years, the working group has made significant steps towards identifying a system to meet the technical needs highlighted by the community during staged requirements gathering activities. Enhancement work has been possible thanks to externally funded projects, allowing existing AAI solutions to be adapted to our needs. A cornerstone of the infrastructure is the reliance on a common token schema in line with evolving standards and best practices, allowing for maximum compatibility and easy cooperation with peer infrastructures and services. We present the work of the group and an analysis of the anticipated changes in authorisation model by moving from X.509 to token based authorisation. A concrete example of token integration in Rucio is presented.
Modeling Losses in a Three Electrode System Towards Fast Charge Control
In this work we demonstrate the applicability of a versatile separator-reference mounted electrode in a three-electrode setup to accurately capture the primary current pathway in the battery cell during operation, calibrate a porous electrode model to the individual anode and cathode potential signals, and assign the various resistances to electrochemical phenomena in the battery cell. This calibrated electrochemical model is validated using continuous rate discharges associated with highway driving scenarios in an electric vehicle, and in turn utilized to predict the local anode potential and proximity to lithium plating onset. Finally, we demonstrate the strategy associated with utilization of the model to estimate constant anode potential charging during fast charge scenarios at various rates and starting conditions as a future look to fast charge calibration development and controls.
Validation of CTF Droplet Entrainment and Annular/Mist Closure Models using Riso Steam/Water Experiments
This report summarizes the work done to validate the droplet entrainment and de-entrainment models as well as two-phase closure models in the CTF code by comparison with experimental data obtained at Riso National Laboratory. The Riso data included a series of over 250 steam/water experiments that were performed in both tube and annulus geometries over a range of various pressures and outlet qualities. Experimental conditions were set so that the majority of cases were in the annular/mist ow regime. Measurements included liquid lm ow rate, droplet ow rate, lm thickness, and two-phase pressure drop. CTF was used to model 180 of the tubular geometry cases, matching experimental geometry, outlet pressure, and outlet ow quality to experimental values. CTF results were compared to the experimental data at the outlet of the test section in terms of vapor and entrained liquid ow fractions, pressure drop per unit length, and liquid lm thickness. The entire process of generating CTF input decks, running cases, extracting data, and generating comparison plots was scripted using Python and Matplotlib for a completely automated validation process. All test cases and scripting tools have been committed to the COBRA-TF master repository and selected cases have been added to the continuous testing system to serve as regression tests. The dierences between the CTF- and experimentally-calculated ow fraction values were con- sistent with previous calculations by Wurtz, who applied the same entrainment correlation to the same data. It has been found that CTF's entrainment/de-entrainment predictive capability in the annular/mist ow regime for this particular facility is comparable to the licensed industry code, COBRAG. While lm and droplet predictions are generally good, it has been found that accuracy is diminished at lower ow qualities. This nding is consistent with the noted deciencies in the Wurtz entrainment model employed by CTF. The CTF predicted two-phase pressure drop in the annular/mist ow regime has been found to be highly inaccurate, exhibiting a clear bias with respect to the experimental data. This inaccuracy led to an investigation that revealed deciencies in the implementation of the annular/mist interfacial friction model, which should be investigated further in the future. Looking to published COBRAG results for this same facility reveal it exhibits no bias with regard to experimental pressure drop results. In addition to the problems with pressure drop prediction, the lm thickness was also signicantly under-predicted by CTF compared to both experimental data and Wurtz's analytical calculations. Film thickness is calculated using a simple geometric relationship and lm void fraction in CTF, which is dependent on slip ratio and interfacial friction. It is possible that the issues aecting the pressure drop and lm void prediction are related.
Pittsburgh 2013 Energy Baseline: Consumption, Trends & Opportunities
The United States (U.S.) Department of Energy (DOE) and the National Energy Technology Laboratory (NETL) are working in conjunction with the City of Pittsburgh (City) to transform how energy is produced, transported, and consumed in the City. This transformation will rely on 21st Century Energy Infrastructure designs, which leverage advanced technology and design techniques to modernize energy infrastructure, create new business models and markets, and expand technology research and development opportunities. Achieving this vision will require developing solutions that are unique to the City: its climate, topography, energy needs, resources, and existing infrastructure.a In this way, the City will demonstrate what the American “City of the Future” looks like, with all its attendant environmental, economic, and job-creation benefits. It will also serve as a template for other cities seeking to reinvent their energy systems.
Cambium Documentation: Version 2021
Cambium is a tool that assembles structured data sets of simulated hourly emission, cost, and operational data for modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision-making. It was built to expand the metrics reported in the National Renewable Energy Laboratory's (NREL's) Standard Scenarios - an annually released set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, looking forward through 2050 (Cole et al. 2021) Information about Cambium and related publications can be found at https://nrel.gov/analysis/cambium.html, and the Cambium data sets for the Standard Scenarios can be viewed and downloaded at https://cambium.nrel.gov/. In this documentation, we define the metrics reported in Cambium databases (Section 4) and document the Cambium-specific methods for calculating those metrics (Section 5). As this document is intended to cover multiple Cambium data releases, we do not document specific scenarios here - for individual data releases, readers should look for an accompanying report that describes the assumptions and data that underlie that specific release. For Cambium databases that are built on NREL's Standard Scenarios, for example, reports describing the scenarios can be found on the Standard Scenarios web site (https://www.nrel.gov/analysis/standard-scenarios.html).
Test Site Verification Team: Optimal and Nominal Nuclear-Testing Programs [Slides]
Objectives of the Optimal and Nominal Nuclear-Testing Programs: Define optimal and nominal nuclear-testing programs; Discuss underground development for nuclear operations; Discuss underground nuclear operations, safety, and health; Compare drift complexes of optimal and nominal testing programs; Compare drift complexes for nuclear testing and commercial production; Discuss a potential future look of underground development and operations.
Optimal and Nominal Nuclear Testing Programs
The intent of this paper is to encourage thought on what the Test Site Verification Team (TSVT) might encounter primarily in terms of observable infrastructure when deployed to assess and verify an explosion, and/or a nuclear-testing program, site, or facility. A primary objective is to present the concept of a continuum of nuclear-testing programs between optimal and nominal end members as defined primarily by their observable infrastructure. Key objectives are: 1. Define optimal and nominal nuclear testing programs; 2. Discuss underground development for nuclear operations; 3. Discuss underground nuclear operations, safety, and health; 4. Compare drift complexes of optimal and nominal testing programs; 5. Compare drift complexes for nuclear testing and commercial production; 6. Discuss a potential future look of underground development and operations. A secondary objective is to interpret the intent of the three TSVT verification scenarios, primarily by defining “consistent with” nuclear or non-nuclear or listing criteria that “verify” nuclear or non-nuclear. Before discussing optimal and nominal nuclear testing programs, an understanding of the three verification scenarios is deemed beneficial.
A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change
The adoption of enterprise digital imaging, along with the development of quantitative imaging methods and the re-emergence of statistical learning, has opened the opportunity for more personalized cancer treatments through transformative data science research. In the last 5 years, accumulating evidence has indicated that noninvasive advanced imaging analytics (i.e., radiomics) can reveal key components of tumor phenotype for multiple lesions at multiple time points over the course of treatment. Many groups using homegrown software have extracted engineered and deep quantitative features on 3-dimensional medical images for better spatial and longitudinal understanding of tumor biology and for the prediction of diverse outcomes. These developments could augment patient stratification and prognostication, buttressing emerging targeted therapeutic approaches. Unfortunately, the rapid growth in popularity of this immature scientific discipline has resulted in many early publications that miss key information or use underpowered patient data sets, without production of generalizable results. Quantitative imaging research is complex, and key principles should be followed to realize its full potential. The fields of quantitative imaging and radiomics in particular require a renewed focus on optimal study design and reporting practices, standardization, interpretability, data sharing, and clinical trials. Standardization of image acquisition, feature calculation, and statistical analysis (i.e., machine learning) are required for the field to move forward. A new data-sharing paradigm enacted among open and diverse participants (medical institutions, vendors and associations) should be embraced for faster development and comprehensive clinical validation of imaging biomarkers. In this review and critique of the field, we propose working principles and fundamental changes to the current scientific approach, with the goal of high-impact research and development of actionable prediction models that will yield more meaningful applications of precision cancer medicine.
Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past
September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.
The Completion of Surrogate Testing for Low-Temperature TEX and a Look Towards the Future
To address the mounting need for below room temperature nuclear data validation, the Low-Temperature Thermal Epithermal eXperiments (LT-TEX) have been designed. Validation of low-temperature neutron cross sections is necessary to verify any operation at temperatures below room temperature which is typically observed in environments far from the equator. For example, a fissile material transportation truck may routinely observe ambient temperatures down to -40°C, which is the lower temperature bound of the normal conditions of transportation defined in the United States Title 10 Code of Federal Regulations §71.71c2. Additionally, sub-room temperature benchmarks can validate newly produced cross sections, that include novel thermal scattering laws, from North Carolina State University.
IER 537: CERBERUS I - Completed Benchmark and a Look to the Future
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Application of Quantum Computing to Biochemical Systems: A Look to the Future
Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.
WIPP PA: An Overview with CRA-2019 PA Results and a Look to the Future.
Abstract not provided.