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At least 1,513 records · Page 84

The IceCube realtime alert system

Although high-energy astrophysical neutrinos were discovered in 2013, their origin is still unknown. Aiming for the identification of an electromagnetic counterpart of a rapidly fading source, we have implemented a realtime analysis framework for the IceCube neutrino observatory. Several analyses selecting neutrinos of astrophysical origin are now operating in realtime at the detector site in Antarctica and are producing alerts for the community to enable rapid follow-up observations. The goal of these observations is to locate the astrophysical objects responsible for these neutrino signals. This paper highlights the infrastructure in place both at the South Pole site and at IceCube facilities in the north that have enabled this fast follow-up program to be implemented. Additionally, this paper presents the first realtime analyses to be activated within this framework, highlights their sensitivities to astrophysical neutrinos and background event rates, and presents an outlook for future discoveries.

79 ASTRONOMY AND ASTROPHYSICS↗

Advanced Multipurpose Rendezvous Tracking System Study

Rendezvous and docking (R&D) sensors needed to support Earth orbital operations of vehicles were investigated to determine the form they should take. An R&D sensor must enable an interceptor vehicle to determine both the relative position and the relative attitude of a target vehicle. Relative position determination is fairly straightforward and places few constraints on the sensor. Relative attitude determination, however, is more difficult. The attitude is calculated based on relative position measurements of several reflectors placed in a known arrangement on the target vehicle. The constraints imposed on the sensor by the attitude determination method are severe. Narrow beamwidth, wide field of view (fov), high range accuracy, and fast random scan capability are all required to determine attitude by this method. A consideration of these constraints as well as others imposed by expected operating conditions and the available technology led to the conclusion that the sensor should be a cw optical radar employing a semiconductor laser transmitter and an image dissector receiver.

Laurie, R. J.↗

CoolPINNs: A physics-informed neural network modeling of active cooling in vascular systems

Emerging technologies like hypersonic aircraft, space exploration vehicles, and batteries avail fluid circulation in embedded microvasculatures for efficient thermal regulation. Modeling is vital during the design and operational phases of these engineered systems. However, many challenges exist in developing a modeling framework. What is lacking is an accurate framework that (i) captures sharp jumps in the thermal flux across complex vasculature layouts, (ii) deals with oblique derivatives (involving tangential and normal components), (iii) handles nonlinearity because of radiative heat transfer, (iv) provides a high-speed forecast for real-time monitoring, and (v) facilitates robust inverse modeling. Here, this paper addresses these challenges by availing the power of physics-informed neural networks (PINNs). We develop a fast, reliable, and accurate Scientific Machine Learning (SciML) framework for vascular-based thermal regulation—called CoolPINNs: a PINNs-based modeling framework for active cooling. The proposed mesh-less framework elegantly overcomes all the mentioned challenges. The significance of the reported research is multi-fold. First, the framework is valuable for real-time monitoring of thermal regulatory systems because of rapid forecasting. Second, researchers can address complex thermoregulation designs since the approach is meshless. Finally, the framework facilitates systematic parameter identification and inverse modeling studies, perhaps the most significant utility of the current framework.

97 MATHEMATICS AND COMPUTING↗

High Current Cycling in a Superconcentrated Ionic Liquid Electrolyte to Promote Uniform Li Morphology and a Uniform LiF-Rich Solid Electrolyte Interphase

High-energy-density systems with fast charging rates and suppressed dendrite growth are critical for the implementation of efficient and safe next-generation advanced battery technologies such as those based on Li metal. However, there are few studies that investigate reliable cycling of Li metal electrodes under high-rate conditions. in this work, by employing a superconcentrated ionic liquid (IL) electrolyte, we highlight the effect of Li salt concentration and applied current density on the resulting Li deposit morphology and solid electrolyte interphase (SEI) characteristics, demonstrating exceptional deposition/dissolution rates and efficiency in these systems. Operation at higher current densities enhanced the cycling efficiency, e.g., from 64 ± 3% at 1 mA cm –2 up to 96 ± 1% at 20 mA cm –2 (overpotential <±0.2 V), while resulting in lower electrode resistance and dendrite-free Li morphology. A maximum current density of 50 mA cm –2 resulted in 88 ± 3% cycling efficiency, displaying tolerance for high overpotentials at the Ni working electrode (0.5 V). X-ray photoelectron microscopy (XPS), time-of-flight secondary-ion mass spectroscopy (ToF-SIMS), and scanning electron microscopy (SEM) surface measurements revealed that the formation of a stable SEI, rich in LiF and deficient in organic carbon species, coupled with nondendritic and compact Li morphologies enabled enhanced cycling efficiency at higher currents. Reduced dendrite formation at high current is further highlighted by the use of a highly porous separator in coin cell cycling (1 mAh cm –2 at 50 °C), sustaining 500 cycles at 10 mA cm –2 .

25 ENERGY STORAGE↗

The dedicated ICRH system for the stellarator Wendelstein 7-X

The current status of the mechanical and electromagnetic design for the ICRF antenna system for W7-X is presented. Two antenna plugins are discussed: one consisting of a pair of straps with pre-matching to cover the first frequency band 25-38 MHz and a second one consisting of two short strap triplets to cover a frequency band around 76 MHz. This paper focusses on the two strap antenna for the lower frequency band. Power coupling of the antenna to a reference plasma profile is studied with the help of the codes TOPICA and Microwave Studio, that deliver the scattering matrix needed for the optimization of the geometric parameters of the straps and antenna box. Radiation power spectra for different phasings of the two straps are obtained using the code ANTITER II and different heating scenarii are discussed. The potential for heating, fast particle generation and current drive is discussed. The problem of RF coupling through the plasma edge and of edge power deposition is summarized. The system contains a prematching capacitor to limit the maximum voltage in the system, and the large mutual coupling between the 2 straps is counterbalanced by the use of a decoupler. The mechanical design highlights the challenges encountered with this antenna: adaptation to a large variety of plasma configurations, the limited space within the port to accommodate the necessary matching components and the watercooling needed for long pulse operation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Information Leakage Analysis using a Co-design-Based Fault Injection Technique on a RISC-V Microprocessor

The RISC-V instruction set architecture open licensing policy has spawned a hive of development activity, making a range of implementations publicly available. The environments in which RISC-V operates have expanded correspondingly, driving the need for a generalized approach to evaluating the reliability of RISC-V implementations under adverse operating conditions or after normal wear-out periods. Fault injection (FI) refers to the process of changing the state of registers or wires, either permanently or momentarily, and then observing execution behavior. The analysis provides insight into the development of countermeasures that protect against the leakage or corruption of sensitive information which might occur because of unexpected execution behavior. In this paper, we develop a hardware-software co-design architecture that enables fast, configurable fault emulation and utilize it for information leakage and data corruption analysis. Modern System-on-chip FPGAs enable building an evaluation platform where control elements run on a processor(s) (PS) simultaneously with the target design running in the programmable logic (PL). Software components of the FI system introduce faults and report execution behavior. A pair of RISC-V FI-instrumented implementations are created and configured to execute the Advanced Encryption Standard and Twister algorithms. Key and plaintext information leakage and degraded pseudo-random sequences are both observed in the output for a subset of the emulated faults.

42 ENGINEERING↗

Transparent conducting oxides: from all-dielectric plasmonics to a new paradigm in integrated photonics

During the past few years, the optics and photonics communities have renewed their attention toward transparent conducting oxides (TCOs), which for over two decades have been broadly employed for the fabrication of transparent electrodes in photovoltaic and communication technologies. This reinvigorated research curiosity is twofold: on the one hand, TCOs, with their metal-like properties, low optical absorption, and fabrication flexibility, represent an appealing alternative to noble metals for designing ultra-compact plasmonic devices. On the other hand, this class of hybrid compounds has been proved to possess exceptionally high optical nonlinearities when operating on a frequency window centered around their crossover point, the wavelength point at which the real part of the dielectric permittivity switches sign. Because TCOs are wide-bandgap materials with the Fermi level located in the conduction band, they are hybrid in nature, thus presenting both interband and intraband nonlinearities. This is the cause of a very rich nonlinear physics that is yet to be fully understood and explored. In addition to this, TCOs are epsilon-near-zero (ENZ) materials within a broad near-infrared spectral range, including the entire telecom bandwidth. In this operational window a myriad of novel electromagnetic phenomena have been demonstrated experimentally such as supercoupling, wavefront freezing, and photon doping. Furthermore, TCOs stand out among all other ENZ systems due to one fundamental characteristic, which is hardly attainable even by using structured materials. In fact, around their ENZ wavelength and for a quite generous operational range, these materials can be engineered to have an extremely small real index. This peculiarity leads to a slow-light effect that is ultimately responsible for a significant enhancement of the material nonlinear properties and is the cornerstone of the emerging field of near-zero-index photonics. In this regard, the recent history of nonlinear optics in conductive oxides is growing extremely fast due to a great number of experiments reporting unprecedentedly remarkable effects, including unitary index change, bandwidth-large frequency shift, efficient ultra-low-power frequency conversion, and many others. This review is meant to guide the reader through the exciting journey of TCOs, starting as an industrial material for transparent electrodes, then becoming a new alternative for low-loss plasmonics, and recently opening up new frontiers in integrated nonlinear optics. The present review is mainly focused on experimental observations.

42 ENGINEERING↗

The D-D Neutron Generator as an Alternative to Am(Li) Isotopic Neutron Source in the Active Well Coincidence Counter

The 235 U mass assay of bulk uranium items, such as oxide canisters, fuel pellets, and fuel assemblies, is not achievable by traditional gamma-ray assay techniques due to the limited penetration of the item by the characteristic 235 U gamma rays. Instead, fast neutron interrogation methods such as active neutron coincidence counting must be used. For international safeguards applications, the most commonly used active neutron systems, the Active Well Coincidence Counter (AWCC), Uranium Neutron Collar (UNCL) and 252 Cf Shuffler, rely on fast neutron interrogation using an isotopic neutron source [i.e., 252 Cf or Am(Li)] to achieve better measurement accuracies than are possible using gamma-ray techniques for high-mass, high-density items. However, the Am(Li) sources required for the AWCC and UNCL systems are no longer manufactured, and newly produced systems rely on limited supplies of sources salvaged from disused instruments. The 252 Cf shuffler systems rely on the use of high-output 252 Cf sources, which while still available have become extremely costly for use in routine operations and require replacement every five to seven years. Lack of a suitable alternative neutron interrogation source would leave a potentially significant gap in the safeguarding of uranium processing facilities. In this work, we made use of Oak Ridge National Laboratory’s (ORNL’s) Large Volume Active Well Coincidence Counter (LV-AWCC) and a commercially available deuterium-deuterium (D-D) neutron generator to examine the potential of the D-D neutron generator as an alternative to the isotopic sources. We present the performance of the LV-AWCC with D-D generator for the assay of 235 U based on the results of Monte Carlo N-Particle (MCNP) simulations and measurements of depleted uranium (DU), low enriched uranium (LEU), and highly enriched uranium (HEU) items.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The DD Neutron Generator as an Alternative to Am(Li) Isotopic Neutron Source in the Uranium Neutron Coincidence Collar

The 235 U mass assay of bulk uranium items, such as oxide canisters, fuel pellets, and fuel assemblies, is not achievable by traditional gamma-ray assay techniques because of the limited penetration of the item by the characteristic 235 U gamma rays. Instead, fast neutron interrogation methods such as active neutron coincidence counting must be used. For international safeguards applications, the most commonly used active neutron systems, the Active Well Coincidence Counter (AWCC), Uranium Neutron Coincidence Collar (UNCL), and 252 Cf Shuffler, rely on fast neutron interrogation using an isotopic neutron source [i.e., 252 Cf or Am(Li)] to achieve better measurement accuracies than are possible using gamma-ray techniques for high-mass, high-density items. However, the Am(Li) sources required for the AWCC and UNCL systems are no longer manufactured, and newly produced systems rely on limited supplies of sources salvaged from disused instruments. The 252 Cf shuffler systems rely on the use of high-output 252 Cf sources, which while still available have become extremely costly for use in routine operations and require replacement every 5–7 years. Lack of a suitable alternative neutron interrogation source would leave a potentially significant gap in the safeguarding of uranium processing facilities. Previously we examined the performance of Oak Ridge National Laboratory’s Large Volume Active Well Coincidence Counter modified to accept a commercially available deuterium-deuterium (DD) neutron generator to examine the potential of the DD neutron generator as an alternative to the isotopic sources [1]. That work indicated that the DD generator was a viable replacement for the AWCC applications, but because of the large dimensions of that generator, the DD/AWCC would have to be run as a delayed neutron counting system to provide equivalent measurement precision. In this work we examine the performance of a standard UNCL modified to accept the DD neutron generator for the assay of 235 U based on the results of Monte Carlo N-Particle (MCNP) simulations and measurements of depleted uranium and highly enriched uranium items. The projected performance of the modified UNCL for fresh pressurized water reactor fuel assemblies operated in both traditional coincidence counting and delayed neutron counting modes is presented.

07 ISOTOPE AND RADIATION SOURCES↗

Visual display aid for orbital maneuvering - Design considerations

This paper describes the development of an interactive proximity operations planning system that allows on-site planning of fuel-efficient multiburn maneuvers in a potential multispacecraft environment. Although this display system most directly assists planning by providing visual feedback to aid visualization of the trajectories and constraints, its most significant features include: (1) the use of an 'inverse dynamics' algorithm that removes control nonlinearities facing the operator, and (2) a trajectory planning technique that separates, through a 'geometric spreadsheet', the normally coupled complex problems of planning orbital maneuvers and allows solution by an iterative sequence of simple independent actions. The visual feedback of trajectory shapes and operational constraints, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool provides an example of operator-assisted optimization of nonlinear cost functions.

Grunwald, Arthur J.↗

The Upper Atmosphere Research Satellite microwave limb sounder instrument

The microwave limb sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) is the first satellite experiment using limb sounding techniques at microwave frequencies. Primary measurement objectives are stratospheric ClO, O3, H2O, temperature, and pressure. Measurements are of thermal emission: all are performed simultaneously and continuously and are not degraded by ice clouds or volcanic aerosols. The instrument has a 1.6-m mechanically scanning antenna system and contains heterodyne radiometers in spectral bands centred near 63, 183, and 205 GHz. The radiometers operate at ambient temperature and use Schottky-diode mixers with local oscillators derived from phase-locked Gunn oscillators. Frequency tripling by varactor multipliers generates the 183- and 205-GHz local oscillators, and quasi-optical techniques inject these into the mixers. Six 15-channel filter banks spectrally resolve stratospheric thermal emission lines and produce an output spectrum every 2 s. Thermal stability is sufficient for 'total power' measurements which do not require fast chopping. Radiometric calibration, consisting of measurements of cold space and an internal target, is performed every 65-s limb scan. Instrument in-orbit performance has been excellent, and all objectives are being met.

Barath, F. T.↗

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

A conflict detection and resolution (CD&R) concept for the terminal maneuvering area (TMA) was evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. The CD&R concept is being designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The purpose of the study was to evaluate the performance of aircraft-based CD&R algorithms in the TMA, as a function of surveillance accuracy. This paper gives an overview of the CD&R concept, simulation study, and results. The Next Generation Air Transportation System (NextGen) concept for the year 2025 and beyond envisions the movement of large numbers of people and goods in a safe, efficient, and reliable manner [1]. NextGen will remove many of the constraints in the current air transportation system, support a wider range of operations, and provide an overall system capacity up to three times that of current operating levels. Emerging NextGen operational concepts [2], such as four-dimensional trajectory based airborne and surface operations, equivalent visual operations, and super density arrival and departure operations, require a different approach to air traffic management and as a result, a dramatic shift in the tasks, roles, and responsibilities for the flight deck and air traffic control (ATC) to ensure a safe, sustainable air transportation system.

Jones, Denise R.↗

Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks

The paper presents a distributed approach for operating a network of inverter-based energy storage resources embedded in a bulk power system. Departing from their traditional role of steady-state reserves, the storage assets in the network are utilized as frequency-responsive resources shaping system dynamics. The power electronics converter systems interfacing the storage resources are equipped with local controllers designed to respond under transient disturbances. To this end, a safety-constrained distributed control strategy is explored. The paper compares the performance of converter-interfaced grid-forming and grid-following storage networks for fast frequency control and disturbance containment/localization. Sensitivity studies are performed to study the impact of storage size, steady-state dispatch, and controller design on dynamic performance. The findings are presented through case studies with results from the IEEE test systems.

Chatterjee, Kaustav (ORCID:0000000153273860)↗

Learning Optimal Solutions for Extremely Fast AC Optimal Power Flow: Preprint

We develop, in this paper, a machine learning approach to optimize the real-time operation of electric power grids. In particular, we learn feasible solutions to the AC optimal power flow (OPF) problem with negligible optimality gaps. The AC OPF problem aims at identifying optimal operational conditions of the power grids that minimize power losses and/or generation costs. Due to the computational challenges with solving this nonconvex problem, many efforts have focused on linearizing or approximating the problem in order to solve the AC OPF on faster timescales. However, many of these approximations can be fairly poor representations of the actual system state and still require solving an optimization problem, which can be time consuming for large networks. In this work, we learn a mapping between the system loading and optimal generation values, enabling us to find near-optimal and feasible AC OPF solutions. This allows us to bypass solving the traditionally nonconvex AC OPF problem, resulting in a significant decrease in computational burden for grid operators.

machine learning↗

Pushing the Limits of Aquatic Remote Sensing: Synthetic Data and Deep Learning for Fast Inverse Emulation of A Coupled Ocean-Atmosphere Radiative Transfer Model

The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.

Jeremy Alan Kravitz↗

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗

Estimate long-term impact on battery degradation by considering electric vehicle real-world end-use factors

Many estimates of battery capacity degradation are based on accelerated lab tests that involve charge-discharge cycles or rely on data or electrochemical modeling. These methods are reasonable for technology benchmarking but rarely consider real-world end-use factors. To address this issue, this study develops the Battery Run-down under Electric Vehicle Operation (BREVO) model. It links the driver's travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. It finds that, over a 10-year timespan, firstly, for a random driver situated in the New England area, daily direct-current fast charging (60 kW) could lead to up to 22% less battery capacity when compared to daily Level-1 charging (1.8 kW). Second, the battery thermal management system can delay battery degradation by approximately 0.5% in the New England area. Third, warmer ambient temperatures enhance BEV battery usage. The model indicates that the battery capacity in the Los Angeles area is 6% higher than that in the New England area. The BREVO model provides crucial information for consumers and BEV manufacturers on range anxiety, BEV battery design, and decision support of battery warranty.

25 ENERGY STORAGE↗