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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 1,351 records · Page 75

AN ADVANCED CALIBRATION PROCEDURE FOR COMPLEX IMPEDANCE SPECTRUM MEASUREMENTS OF ADVANCED ENERGY STORAGE DEVICES

With the increasing demand for electric and hybrid electric vehicles and the explosion in popularity of mobile and portable electronic devices such as laptops, cell phones, e-readers, tablet computers and the like, reliance on portable energy storage devices such as batteries has likewise increased. The concern for the availability of critical systems in turn drives the availability of battery systems and thus the need for accurate battery health monitoring has become paramount. Over the past decade the Idaho National Laboratory (INL), Montana Tech of the University of Montana (Tech), and Qualtech Systems, Inc. (QSI) have been developing the Smart Battery Status Monitor (SBSM), an integrated battery management system designed to monitor battery health, performance and degradation and use this knowledge for effective battery management and increased battery life. Key to the success of the SBSM is an in-situ impedance measurement system called the Impedance Measurement Box (IMB). One of the challenges encountered has been development of an accurate, simple, robust calibration process. This paper discusses the successful realization of this process.

25 ENERGY STORAGE↗

Developing Uintah's Runtime System for Forthcoming Architectures

The need to solve ever-more complex science and engineering problems on computer architectures that are rapidly evolving poses considerable challenges for modern simulation frameworks and packages. While the decomposition of software into a programming model that generates a task-graph for execution by a runtime system make portability and performance possible, it also imposes considerable demands on that runtime system. Here, the challenge of meeting those demands for near-term and longer term systems in the context of the Uintah framework is considered in key areas such as support for data structures, tasks on heterogeneous architectures, performance portability, power management and designing for resilience by the use of replication based upon adaptive mesh refinement processes is addressed. Examples of techniques in these areas are used to illustrate performance improvements obtained for present large-scale systems and the needs of proposed systems considered.

97 MATHEMATICS AND COMPUTING↗

Designing a hybrid electrode toward high energy density with a staged Li + and PF 6 - deintercalation/intercalation mechanism

Existing lithium-ion battery technology is struggling to meet our increasing requirements for high energy density, long lifetime, and low-cost energy storage. Here, a hybrid electrode design is developed by a straightforward reengineering of commercial electrode materials, which has revolutionized the “rocking chair” mechanism by unlocking the role of anions in the electrolyte. Our proof-of-concept hybrid LiFePO 4 (LFP)/graphite electrode works with a staged deintercalation/intercalation mechanism of Li + cations and PF 6 - anions in a broadened voltage range, which was thoroughly studied by ex situ X-ray diffraction, ex situ Raman spectroscopy, and operando neutron powder diffraction. Introducing graphite into the hybrid electrode accelerates its conductivity, facilitating the rapid extraction/insertion of Li + from/into the LFP phase in 2.5 to 4.0 V. This charge/discharge process, in turn, triggers the in situ formation of the cathode/electrolyte interphase (CEI) layer, reinforcing the structural integrity of the whole electrode at high voltage. Consequently, this hybrid LFP/graphite-20% electrode displays a high capacity and long-term cycling stability over 3,500 cycles at 10 C, superior to LFP and graphite cathodes. Importantly, the broadened voltage range and high capacity of the hybrid electrode enhance its energy density, which is leveraged further in a full-cell configuration.

25 ENERGY STORAGE↗

Electronic excited states from a variance-based contracted quantum eigensolver

Electronic excited states of molecules are central to many physical and chemical processes, and yet they are typically more difficult to compute than ground states. Here, in this paper we leverage the advantages of quantum computers to develop an algorithm for the highly accurate calculation of excited states. We solve a contracted Schrödinger equation (CSE)—a contraction (projection) of the Schrödinger equation onto the space of two electrons—whose solutions correspond identically to the ground and excited states of the Schrödinger equation. While recent quantum algorithms for solving the CSE, known as contracted quantum eigensolvers (CQE), have focused on ground states, we develop a CQE based on the variance that is designed to optimize rapidly to a ground or excited state. We apply the algorithm to compute the ground and excited states of H 2 , H 4 , and BH.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IMPACTS OF INTERACTING ELEVATED ATMOSPHERIC CO2 AND O3 ON THE STRUCTURE AND FUNCTIONING OF A NORTHERN FOREST ECOSYSTEM: OPERATING AND DECOMMISSIONING THE ASPEN FACE PROJECT

Two of the most important and pervasive greenhouse gases driving global change and impacting forests in the U.S. and around the world are atmospheric CO2 and tropospheric O3. As the only free air, large-scale manipulative experiment studying the interaction of elevated CO2 and O3 on forests, the Aspen FACE experiment was uniquely designed to address the long-term ecosystem level impacts of these two greenhouse gases on aspen-birch-maple forests, which dominate the richly forested Lake States region. The project was established in 1997 to address the overarching scientific question: “What are the effects of elevated [CO2] and [O3], alone and in combination, on the structure and functioning of northern hardwood forest ecosystems?” From 1998 through the middle of the 2009 growing season, we examined the interacting effects of elevated CO2 and O3 on ecosystem processes in an aggrading northern forest ecosystem to compare the responses of early-successional, rapid-growing shade intolerant trembling aspen and paper birch to those of a late successional, slower growing shade tolerant sugar maple. Fumigations with elevated CO2 (560 ppm during daylight hours) and O3 (approximately 1.5 x ambient) were conducted during the growing season from 1998 to 2008, and in 2009 through harvest date. Response variables quantified during the experiment included growth, competitive interactions and stand dynamics, physiological processes, plant nutrient status and uptake, tissue biochemistry, litter quality and decomposition rates, hydrology, soil respiration, microbial community composition and respiration, VOC production, treatment-pest interactions, and treatment-phenology interactions. In 2009, we conducted a detailed harvest of the site. The harvest included detailed sampling of a subset of trees by component (leaves and buds, fine branches, coarse branches and stem, coarse roots, fine roots) and excavation of soil to a depth of 1 m. Throughout the experiment, aspen and birch photosynthesis increased with elevated CO2 and tended to decrease with elevated O3, compared to the control. In contrast to aspen and birch, maple photosynthesis was not enhanced by elevated CO2. Elevated O3 did not cause significant reductions in maximum photosynthesis in birch or maple. In addition, photosynthesis in ozone sensitive clones was affected to a much greater degree than that in ozone tolerant aspen clones. Treatment effects on photosynthesis contributed to CO2 stimulation of aboveground and belowground growth that was species and genotype dependent, with birch and aspen being most responsive and maple being least responsive. The positive effects of elevated CO2 on net primary productivity NPP were sustained through the end of the experiment, but negative effects of elevated O3 on NPP had dissipated during the final three years of treatments. The declining response to O3 over time resulted from the compensatory growth of O3-tolerant genotypes and species as the growth of O3-sensitive individuals declined over time. Cumulative NPP over the entire experiment was 39% greater under elevated CO2 and 10% lower under elevated O3. Enhanced NPP under elevated CO2 was sustained by greater root exploration of soil for growth-limiting N, as well as more rapid rates of litter decomposition and microbial N release during decay. Results from Aspen FACE clearly indicate that plants growing under elevated carbon dioxide, regardless of community type or ozone level, obtained significantly greater amounts of soil N. These results indicate that greater plant growth under elevated carbon dioxide has not led to “progressive N limitation”. If similar forests growing throughout northeastern North America respond in the same manner, then enhanced forest NPP under elevated CO2 may be sustained for a longer duration than previously thought, and the negative effect of elevated O3 may be diminished by compensatory growth of O3-tolerant plants as they begin to dominate forest communities. By the end of the experiment, elevated CO2 increased ecosystem C content by 11%, whereas elevated O3 decreased ecosystem C content by 9%. Total ecosystem C content in the interaction treatment (elevated CO2 and O3) did not significantly differ from that of the control. Total ecosystem C content responded similarly to the treatments across the three forest communities. The treatment effects on ecosystem C content resulted from differences in tree biomass, particularly woody tissues (branches, stem, and coarse roots), and lower C content in the near-surface mineral soil. During its duration, the Aspen FACE project involved collaboration between scientists from 9 countries, and over the course of the experiment there were over 120 Aspen FACE scientific users. These scientists helped produce 75 publications during the most recent funding period (2008-2014) and 207 peer-reviewed publications (169 in refereed journals) since the beginning of the project.

54 ENVIRONMENTAL SCIENCES↗

Tool for Rapid Analysis of Monte Carlo Simulations

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Restrepo, Carolina↗

Restoring Escaped Zincate in Rechargeable Alkaline Zinc Batteries with a Seed-in-Nanoshell Design

Rechargeable alkaline zinc batteries are promising candidates for safe and low-cost energy storage, but suffer from ZnO dissolution that causes irreversible active material loss and rapid capacity decay. Here, we report a seed-in-nanoshell ZnO anode architecture that mitigates dissolution by combining physical confinement with electrochemical restoration of dissolved zincate species. ZnO particles are encapsulated within an ion-sieving carbon nanoshell that restricts zincate diffusion, maintains electrical conductivity, and stabilizes repeated solid–solution–solid transformations. Silver (Ag) nanoparticles incorporated into the nanoshell act as zincophilic nucleation seeds, lowering the Zn deposition barrier and directing the redeposition of dissolved zincate back to metallic Zn during charging. This confinement-enabled restoration mechanism converts zincate dissolution from an irreversible loss pathway into a recoverable process, enabling improved performance under harsh test conditions. The anode also delivers 227.9 mAh g −1 at −40 °C. Finally, a scalable tens-of-gram synthesis of ZnO@Ag is demonstrated, underscoring the practical potential of this strategy for advanced aqueous zinc batteries.

25 ENERGY STORAGE↗

Hydrogen station in situ back-to-back fueling data for design and modeling

Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, here this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during "back-to-back fuelings", with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.

08 HYDROGEN↗

3D treatment planning systems

Three-dimensional (3D) treatment planning systems have evolved and become crucial components of modern radiation therapy. The systems are computer-aided designing or planning softwares that speed up the treatment planning processes to arrive at the best dose plans for the patients undergoing radiation therapy. Furthermore, the systems provide new technology to solve problems that would not have been considered without the use of computers such as conformal radiation therapy (CRT), intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT). The 3D treatment planning systems vary amongst the vendors and also the dose delivery systems they are designed to support. As such these systems have different planning tools to generate the treatment plans and convert the treatment plans into executable instructions that can be implemented by the dose delivery systems. The rapid advancements in computer technology and accelerators have facilitated constant upgrades and the introduction of different and unique dose delivery systems than the traditional C-arm type medical linear accelerators. The focus of this special issue is to gather relevant 3D treatment planning systems for the radiation oncology community to keep abreast of technology advancement by assess the planning tools available as well as those unique ''tricks or tips'' used to support the different dose delivery systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accelerating Hydraulic Fracture Imaging by Deep Transfer Learning

Deep transfer learning has a great success story in computer vision (CV), natural language processing, and many other fields. In this communication, we are going to push forward the deep transfer learning to the hydraulic fracture imaging problem by proposing a two-step approach: 1) train a convolutional neural network (CNN) to reconstruct target geometries by a relatively large amount of approximated field patterns generated from a simplified model and 2) fine-tune the top layers of transferred CNN by a small amount of true field patterns generated through a full model. The advantages include the rapid generation of large amount of data through the simplified model and the high reconstruction accuracy through a careful design of the deep transfer learning. Here, the CNN trained through the deep transfer learning can accurately reconstruct the lateral extent and direction of fractures with unseen conductivity and white Gaussian noise, showing a notable acceleration/accuracy enhancement over the previous CNN trained by mixing a small number of true data into the approximated data as data augmentation.

02 PETROLEUM↗

A portable parton-level event generator for the high-luminosity LHC

The rapid deployment of computing hardware different from the traditional CPU+RAM model in data centers around the world mandates a change in the design of event generators for the Large Hadron Collider, in order to provide economically and ecologically sustainable simulations for the high-luminosity era of the LHC. Parton-level event generation is one of the most computationally demanding parts of the simulation and is therefore a prime target for improvements. We present a production-ready leading-order parton-level event generation framework capable of utilizing most modern hardware and discuss its performance in the standard candle processes of vector boson and top-quark pair production with up to five additional jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The LDRD ER “Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats” was conceived to address a need for rapid, scalable, evaluation of computationally designed therapeutic or prophylactic antibodies and vaccine antigens, two important classes of protein medical countermeasure (MCM). This was done in complement to a computationally driven LDRD 20ERD032 “Active Learning for Rapid Design of Vaccines and Antibodies.” Natural antibodies and antigens are often insufficiently broad or robust across different pathogens and their variants. Leveraging a collaboration of simulation driven machine learning, structural expertise, and high-throughput characterization of candidate antibodies, we successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro. Our antibody design work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, we computationally designed derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Our designs were successful, including a pair of designs which provide potent neutralization of not only Omicron BA.1 and BA.1.1, but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23.

59 BASIC BIOLOGICAL SCIENCES↗

User-Centered Evaluation of Visual Analytics

Visual analytics systems are becoming very popular. More domains now use interactive visualizations to analyze the ever-increasing amount and heterogeneity of data. More novel visualizations are being developed for more tasks and users. We need to ensure that these systems can be evaluated to determine that they are both useful and usable. A user-centered evaluation for visual analytics needs to be developed for these systems. While many of the typical human-computer interaction (HCI) evaluation methodologies can be applied as is, others will need modification. Additionally, new functionality in visual analytics systems needs new evaluation methodologies. There is a difference between usability evaluations and user-centered evaluations. Usability looks at the efficiency, effectiveness, and user satisfaction of users carrying out tasks with software applications. User-centered evaluation looks more specifically at the utility provided to the users by the software. This is reflected in the evaluations done and in the metrics used. In the visual analytics domain this is very challenging as users are most likely experts in a particular domain, the tasks they do are often not well defined, the software they use needs to support large amounts of different kinds of data, and often the tasks last for months. These difficulties are discussed more in the section on User-centered Evaluation. Our goal is to provide a discussion of user-centered evaluation practices for visual analytics, including existing practices that can be carried out and new methodologies and metrics that need to be developed and agreed upon by the visual analytics community. The material provided here should be of use for both researchers and practitioners in the field of visual analytics. Researchers and practitioners in HCI and interested in visual analytics will find this information useful as well as a discussion on changes that need to be made to current HCI practices to make them more suitable to visual analytics. A history of analysis and analysis techniques and problems is provided as well as an introduction to user-centered evaluation and various evaluation techniques for readers from different disciplines. The understanding of these techniques is imperative if we wish to support analysis in the visual analytics software we develop. Currently the evaluations that are conducted and published for visual analytics software are very informal and consist mainly of comments from users or potential users. Our goal is to help researchers in visual analytics to conduct more formal user-centered evaluations. While these are time-consuming and expensive to carryout, the outcomes of these studies will have a defining impact on the field of visual analytics and help point the direction for future features and visualizations to incorporate. While many researchers view work in user-centered evaluation as a less-than-exciting area to work, the opposite is true. First of all, the goal is user-centered evaluation is to help visual analytics software developers, researchers, and designers improve their solutions and discover creative ways to better accommodate their users. Working with the users is extremely rewarding as well. While we use the term “users” in almost all situations there are a wide variety of users that all need to be accommodated. Moreover, the domains that use visual analytics are varied and expanding. Just understanding the complexities of a number of these domains is exciting. Researchers are trying out different visualizations and interactions as well. And of course, the size and variety of data are expanding rapidly. User-centered evaluation in this context is rapidly changing. There are no standard processes and metrics and thus those of us working on user-centered evaluation must be creative in our work with both the users and with the researchers and developers.

intelligence analysis↗

Application of Multiharmonic QCM-D for Detection of Plasmin at Hydrophobic Surfaces Modified by β-Casein

Plasmin protease plays an important role in many processes in living systems, including milk. Monitoring plasmin activity is important for control of the nutritional quality of milk and other dairy products. We designed a biosensor to detect the proteolytic activity of plasmin, using multiharmonic quartz crystal microbalance with dissipation (QCM-D). The β-casein immobilized on the hydrophobic surface of 1-dodecanethiol on the AT-cut quartz crystal was used to monitor plasmin activity. We demonstrated detection of plasmin in a concentration range of 0.1–20 nM, with the limit of detection about 0.13 ± 0.01 nM. The analysis of viscoelastic properties of the β-casein layer showed rapid changes of shear elasticity modulus, μ, and coefficient of viscosity, η, at plasmin sub-nanomolar concentrations, followed by modest changes at nanomolar concentrations, indicating multilayer architecture β-casein. A comparative analysis of viscoelastic properties of β-casein layers following plasmin and trypsin cleavage showed that the higher effect of trypsin was due to larger potential cleavage sites of β-casein.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of optimization in structural model refinement

To evaluate the role that optimization can play in structural model refinement, it is necessary to examine the existing environment for the structural design/structural modification process. The traditional approach to design, analysis, and modification is illustrated. Typically, a cyclical path is followed in evaluating and refining a structural system, with parallel paths existing between the real system and the analytical model of the system. The major failing of the existing approach is the rather weak link of communication between the cycle for the real system and the cycle for the analytical model. Only at the expense of much human effort can data sharing and comparative evaluation be enhanced for the two parallel cycles. Much of the difficulty can be traced to the lack of a user-friendly, rapidly reconfigurable engineering software environment for facilitating data and information exchange. Until this type of software environment becomes readily available to the majority of the engineering community, the role of optimization will not be able to reach its full potential and engineering productivity will continue to suffer. A key issue in current engineering design, analysis, and test is the definition and development of an integrated engineering software support capability. The data and solution flow for this type of integrated engineering analysis/refinement system is shown.

Lehman, L. L.↗

Modeling and control of beam-like structures

The most popular finite element codes are based upon appealing theories of convergence of modal frequencies. For example, the popularity of cubic elements for beam-like structures is due to the rapid convergence of modal frequencies and stiffness properties. However, for those problems in which the primary consideration is the accuracy of response of the structure at specified locations it is more important to obtain accuracy in the modal costs than in the modal frequencies. The modal cost represents the contribution of a mode in the norm of the response vector. This paper provides a complete modal cost analysis for beam-like continua. Upper bounds are developed for mode truncation errors in the model reduction process and modal cost analysis dictates which modes to retain in order to reduce the model for control design purposes.

Hu, A.↗

Momentum and Heat Flux Measurements in the Exhaust of VASIMR using Helium Propellant

Interplanetary travel requires propulsion systems that can provide high specific impulse (Isp), while also having sufficient thrust to rapidly accelerate large payloads. One such propulsion system is the Variable Specific Impulse Magneto-plasma Rocket (VASIMR), which creates, heats, and ejects plasma to provide variable thrust and Isp, designed to optimally meet the mission requirements. The fraction of the total energy invested in creating the plasma, as compared to the plasma's total kinetic energy, is an important factor in determining the overall system efficiency. In VASIMR, this 'frozen flow loss' is appreciable when at high thrust, but negligible at high Isp. The loss applies to other electric thrusters as well. If some of this energy could be recovered through recombination processes, and reinjected as neutral kinetic energy, the efficiency of VASIMR, in its low Isp/high thrust mode may be improved. An experiment is being conducted to investigate the possibility of recovering some of the energy used to create the plasma by studying the flow characteristics of the charged and neutral particles in the exhaust of the thruster. This paper will cover the measurements of momentum flux and heat flux in the exhaust of the VASIMR test facility using helium as the propellant where the heat flux is comprised of both kinetic and plasma recombination energy. The flux measurements also assist in diagnosing and verifying the plasma conditions in the existing experiment.

Chavers, D. Gregory↗

Rapid 3D nanoscale coherent imaging via physics-aware deep learning

Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of phase recovery is iterative in nature. As a result, the image formation is time consuming and computationally expensive, precluding real-time imaging. Here, we use 3D nanoscale X-ray imaging as a representative example to develop a deep learning model to address this phase retrieval problem. We introduce 3D-CDI-NN, a deep convolutional neural network and differential programing framework trained to predict 3D structure and strain, solely from input 3D X-ray coherent scattering data. Our networks are designed to be “physics-aware” in multiple aspects; in that the physics of the X-ray scattering process is explicitly enforced in the training of the network, and the training data are drawn from atomistic simulations that are representative of the physics of the material. We further refine the neural network prediction through a physics-based optimization procedure to enable maximum accuracy at lowest computational cost. 3D-CDI-NN can invert a 3D coherent diffraction pattern to real-space structure and strain hundreds of times faster than traditional iterative phase retrieval methods. Our integrated machine learning and differential programing solution to the phase retrieval problem is broadly applicable across inverse problems in other application areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗