Mesoscale Interrogation Reveals Mechanistic Origins of Lithium Filaments along Grain Boundaries in I
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A transonic flutter investigation has been made of models of the T-tail of the Blackburn NA-39 airplane. The models were dynamically and elastically scaled from measured airplane data in accordance with criteria which include a flutter safety margin. The investigation was made in the Langley transonic blowdown tunnel and covered a Mach number range from 0.73 to 1.09 at simulated altitudes extending to below sea level. The results of the investigation indicated that, if differences between the measured model and scaled airplane properties are disregarded, the airplane with the normal value of stabilizer pitching stiffness should have a stiffness margin of safety of at least 32 percent at all Mach numbers and altitudes within the flight boundary. However, the airplane with the emergency value of stabilizer pitching stiffness would not have the required margin of safety from symmetrical flutter at Mach numbers greater than about 0.85 at low altitudes. First-order corrections for some differences between the measured model and scaled airplane properties indicated that the airplane with the normal value of stabilizer pitching stiffness would still have an adequate margin of safety from flutter and that the flutter safety margin for the airplane with the emergency value of stabilizer pitching stiffness would be changed from inadequate to adequate. However, the validity of the corrections is questionable.
Oak Ridge National Laboratory (ORNL) is examining the conditions under which a criticality event could be ruled out for large packages placed in an unsaturated alluvial repository. This work specifically examines the water level in a stylized waste package that is assumed (1) to fail on the top, and (2) to empty as water is driven away—not by boiling—but by fluid flow phenomena driven by thermal gradients. This analysis uses the PFLOTRAN code package. Specifically, this year’s work includes examination of the heat rate at which water is driven away for various percolation rates using the same assumptions listed in the 2022 annual report. The STANDARDS (formerly UNF-ST&DARDS) package has predicted dual-purpose canister (DPC) neutron multiplication factors (k-effectives) ranging above 1.1 (unitless) with failed components. The DPC designs were not created with the intent to use for disposal purposes. Emplacing such packages may be worth consideration if it can be shown that criticality is either extremely unlikely or of very low consequence to the repository’s safety case. This work aims to help establish hydrologic boundary conditions for a highly hypothetical, highly stylized subsurface criticality event. The approach to critical is assumed to be slow, producing steady heating rates under a few kilowatts. For a DPC containing capillary media, the simulated power required for dry-out was proportional to the percolation rate but was unaffected by the size of a large breech on top of the DPC. Results for single cases with no capillary media in the DPC suggest that higher infiltration rates may be required in those cases to cause flooding. Bounding mechanisms and assumptions must be identified and characterized further by performing additional perturbations to various input parameters to demonstrate robustness of the results. This might be accomplished by examining responses to power pulses to determine the system transfer function required to enable a reduced order feedback model.
Lightweight aircraft design emphasizes the reduction of structural weight to maximize aircraft efficiency and agility at the cost of increasing the likelihood of structural dynamic instabilities. To ensure flight safety, extensive flight testing and active structural servo control strategies are required to explore and expand the boundary of the flight envelope. Aeroservoelastic (ASE) models can provide online flight monitoring of dynamic instabilities to reduce flight time testing and increase flight safety. The success of ASE models is determined by the ability to take into account varying flight conditions and the possibility to perform flight monitoring under the presence of active structural servo control strategies. In this continued study, these aspects are addressed by developing specific methodologies and algorithms for control relevant robust identification and model validation of aeroservoelastic structures. The closed-loop model robust identification and model validation are based on a fractional model approach where the model uncertainties are characterized in a closed-loop relevant way.
Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.
The United States National Aeronautics and Space Administration (NASA) Balloon Program has a rich history of conducting scientific research in the stratosphere, offering a unique platform for experiments in the near-space environment. One critical component of these high-altitude balloons is the choice of lift gas, which is pivotal to achieving the desired altitude and, thus, mission objectives. Traditionally, helium has been the preferred lift gas due to its inert properties and safety considerations. However, the increasing demand and limited global helium reserves have prompted NASA to explore alternative lift gases, with hydrogen emerging as the most logical choice. Hydrogen boasts several advantages, including its abundant availability, cost-effectiveness, and enhanced lift capability compared to helium. Moreover, it can support a wide range of scientific payloads, enabling extended mission durations and increased payload capacities, ultimately strengthening the program’s scientific potential. However, adopting hydrogen as a lift gas is not without challenges. Safety concerns, especially during the launch and recovery phases, are paramount. NASA and the other major players in the scientific ballooning community have been developing stringent safety protocols and engineering solutions to mitigate these risks. This development includes specialized support systems, leak detection mechanisms, and enhanced launch and recovery procedures. Additionally, environmental considerations must be carefully evaluated. Hydrogen release has the potential to increase concentrations of various greenhouse gases, and its usage must be balanced against the benefits it offers to scientific research and exploration. This paper delves into the ongoing research and development efforts to ensure balloon-based research’s long-term sustainability and its ability to continue pushing the boundaries of scientific discovery. This research demonstrates NASA’s commitment to innovation, safety, and environmental responsibility while maintaining its mission to advance our understanding of the Earth and the cosmos.
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.
In this paper, we develop a novel form of differentiable predictive control (DPC) with safety and robustness guarantees. DPC is a form of approximate model predictive control (MPC), wherein the control policy is a neural network that learns a receding horizon, optimal control law. The proposed approach exploits a new form of sampled-data barrier function to enforce safety, while only interrupting the neural network-based controller near the boundary of the safe set. The effectiveness of the proposed approach is demonstrated in simulation.
Many advanced reactor designs rely on passive systems to provide assurance that certain safety functions, such as reactivity control and reactor heat removal, are maintained during transient scenarios. The performance of these systems is sensitive to boundary and environmental conditions and can lead to functional failure, which is the inability of the system to perform as intended even without any physical failures. Additionally, conditions can cause the passive systems to operate in an intermediate or degraded state. These operational modes of passive systems and their overall reliability can be difficult to capture in traditional probabilistic frameworks where discrete operating modes are assumed or time-dependent boundary conditions are not accounted for. Novel strategies and methods are needed to be able to capture the reliability of these passive systems and their impact on facility safety. The current abstract provides a summary of such a methodology and examples of its use in a case study, the GE Hitachi (GEH) PRISM probabilistic safety assessment (PSA), and the U.S. Department of Energy (USDOE) Versatile Test Reactor (VTR) PSA.
The transmission electron microscopic (TEM) examination of an irradiated tristructural isotropic (TRISO) coated particle from advanced gas reactor (AGR) 2 fuel Compact 2-2-2 is presented in this report. Compact 2-2-2 refers to the compact in Capsule 2 at Level 2 of Stack 2. The examination on AGR2 222 RS019 is focused on the interface between the silicon carbide (SiC) to inner pyrolytic carbon (IPyC) layer, central part of SiC, and the interface between SiC and outer pyrolytic carbon layer. The SiC grain boundary distribution and associated fission product precipitates were characterized by scanning transmission electron microscopy (STEM) energy dispersive spectroscopy (EDS), and precession electron diffraction (PED) in the transmission electron microscope. Two separate locations on SiC layer were selected for on the basis of the intact of the buffer layer in the irradiated TRISO particle. The key observation in this particle is that the compositional nature of grain boundary precipitates is more complex near IPyC/SiC layer where Pd, Pd-Ag, Pd-U containing precipitates can be observed. However, the compositions of precipitate towards outer most region of SiC mainly contain Pd. Ag has been observed in the IPyC/SiC layer in one of the two locations. Comparison of the results to previously irradiated and analyzed, Variant 3, safety tested AGR-1 TRISO particles (AGR1-433-001 and AGR1 222-RS004) showed the grain boundary distributions have some noticeable differences. The differences in coincident site lattice grain boundary and misorientation angles are possibly inherent to the fabrication process. Neutron irradiation induced void distribution has been found to be nonuniform. A high concentration of smaller voids is found at stacking faults compared to those in the SiC matrix. Larger void sizes are observed in the SiC location that is near to the broken buffer layer. This void size variation with integrity of buffer layer can potentially affect the fission product retention. However, the average void size continuously decreases along the radius of SiC in both locations.
The Advanced Test Reactor (ATR) is a light water reactor with aluminum-clad driver fuel. A primary mission of the ATR is to support the next generation of nuclear reactors. This support necessarily requires irradiation of advanced materials such as sodium, fuel salts, and metal eutectics. Irradiation of advanced materials in the ATR environment presents a challenge when completing accident analyses and demonstrating compliance to the Safety Analysis Report (SAR). Many advanced materials have the possibility to react with the ATR protective barriers such as the cladding or primary coolant system (PCS) boundary during postulated accident scenarios. Further, molten fuel experiments fall outside of the standard regulatory framework for dose consequence analyses. ATR is currently developing new safety analysis methods to support irradiation of advanced materials. The primary considerations for this development are 1) experiment containment design requirements, 2) primary coolant system response to an experiment containment failure, and 3) dose analyses for molten fuels.
The Advanced Test Reactor (ATR) is a light water reactor with aluminum-clad driver fuel. A primary mission of the ATR is to support the next generation of nuclear reactors. This support necessarily requires irradiation of advanced materials such as sodium, fuel salts, and metal eutectics. Irradiation of advanced materials in the ATR environment presents a challenge when completing accident analyses and demonstrating compliance to the Safety Analysis Report (SAR). Many advanced materials have the possibility to react with the ATR protective barriers such as the cladding or primary coolant system (PCS) boundary during postulated accident scenarios. Further, molten fuel experiments fall outside of the standard regulatory framework for dose consequence analyses. ATR is currently developing new safety analysis methods to support irradiation of advanced materials. The primary considerations for this development are 1) experiment containment design requirements, 2) primary coolant system response to an experiment containment failure, and 3) dose analyses for molten fuels.
The rapidly growing demand of electrical vehicle (EV) requires high-energy-density lithium-ion batteries (LIBs) with excellent cycling stability and safety performance. However, conventional polycrystalline high-Ni cathodes severely suffer from intrinsic chemo-mechanical degradation and fast capacity fade. The emerging single-crystallization strategy offers a promising pathway to improve the chemo-mechanical stability, however, the single-crystallinity of the cathode is not always guaranteed and residual grain boundaries (GBs) could persist in nonideal synthesis conditions, leading to the formation of ‘quasi’ single-crystalline (QSC) cathodes. So far, there is a lack of understanding of the influence of these residual GBs on the electrochemical performance and structural stability. Herein, we investigate the degradation pathway of a QSC high-Ni cathode through transmission electron microscopy and X-ray techniques. The residual GBs caused by insufficient calcination time, dramatically exacerbate the cathode’s chemo-mechanical instability and cycling performance. Our work offers important guidance for the next-generation cathodes for long-life LIBs.
Since some years, the IRSN has developed a new project to simulate accurately the interaction between neutronic and thermal hydraulic phenomena. This project called ANTARES (Advanced Neutronics and Thermal-hydraulic for the Analysis of Reactor Safety) couples the thermal hydraulic code CATHARE-3 with the 3D neutronic nodal code PARCS. The purpose of this project is to take the advantage of the complementary of these 2 codes, by the knowledge of the 3D core power distribution in CATHARE-3 (computed by PARCS) and improving the thermal hydraulic boundaries conditions in PARCS. In this way, the IRSN diversifies and enlarges its available tools to perform safety analysis with improved accuracy. The current technique usually adopted in France for the safety demonstrations for Reactivity Insertion Accident (RIA) is the so-called 'conservative' approach, which consists of reducing all the feedback (Doppler and moderator effects) and in modifying some physical quantities in such a way to increase a power peak. For this reason, these facilities ('penalties') have been implemented in ANTARES. In this paper we will give two examples of accidental transients that can be simulated with ANTARES: a Main Steam Line Break (MSLB) and an inadvertent boron dilution event. (authors)
Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.
With the number of heat waves expect to increase in both in their severity and frequency in the coming years, an insight into their impact on planetary boundary layer (PBL) heights is essential for one development of future emergency and safety plans. Using High-Resolution Rapid Refresh (HRRR) atmospheric model output, an analysis is done on the effects a heat wave has on PBL heights and temperature inversions across the Savannah River Site (SRS). This study showed that due to its adjacency to anthropogenic land use, SRS experiences a non-negligible gradient in its PBL height, with higher heights to the northwest. The singular location PBL heigh measurement and forecasts for SRS do not account for this gradient, which has potential implications on pollutant and smoke dispersion onsite. During a heat wave this gradient is present but PBL heights are less impacted than surrounding developed areas, possibly attributable to the woody wetlands that surround the Savannah River's banks. Additionally, the heat wave appears to strongly enhance the nocturnal temperature inversions that the site and surrounding areas experience. This is possibly due to increased stability from higher pressure conditions, which are often associated with heat waves. This influence on nocturnal inversions, however, is limited to their intensity, leaving their timing relatively unaltered. The impact a heat wave has on PBL heights and temperature inversions across SRS is seen to be more dependent on adjacent land use and features rather than the unique land use types onsite.
The viewgraphs and discussion of the status of the F-16XL SSLFC numerical design validation are provided. The F-16XL Supersonic Laminar Flow Control Program (SSLFC) is a joint effort involving Rockwell's North American Aircraft Division, NASA Ames-Dryden Flight Research Facility, and NASA Langley Research Center. The objectives of the program are to demonstrate that laminar flow can be obtained on a highly swept wing at supersonic speeds, validate the capabilities of a numerical methodology designed to predict boundary layer transition, and validate the capabilities of the methodology in the design of active and passive laminar flow control (LFC) concepts. The F-16XL SSLFC Program consists of the design, fabrication, installation, and flight test of an active laminar flow control glove for the F-16XL. The glove design emphasized the active (suction) control of attachment line and crossflow boundary condition instabilities. The glove design envelop was constrained by the existing geometry, safety of flight considerations, and space requirements for the suction mechanism. The leading edge extension of the glove was limited to 10 inches for consideration of asymmetric flying qualities and the glove height above the existing surface restricted to two inches. The active (suction) portion of the wing extends to nominally 25 percent chord. The glove was constructed of a micro-perforated titanium sheet (hole diameter = 0.025 inches, spacing ratio = 1/8, and sheet thickness = 0.0025 inches). The glove design includes 22 separate chambers to allow suction variation in the chordwise direction. The F-16XL SSLFC program is currently in the flight test phase.