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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 343 records · Page 19

Accelerating discrete dislocation dynamics simulations with graph neural networks

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.

36 MATERIALS SCIENCE↗

Dirty bomb source term characterization and downwind dispersion: Review of experimental evidence

Dirty bombs are considered one of the easiest forms of radiological terrorism, a form of terrorism based on the deliberate use of radiological material to cause adverse effects in a target population. One U.S. Government official has even described a dirty bomb attack as “all but inevitable”. While people in the vicinity of the blast may experience acute radiation effects, people downwind may unknowingly be contaminated by the radioactive airborne particulate and face increased long-term cancer risk. The likelihood of increased cancer risk depends on the radionuclide used and its specific activity, its aerosolization potential, the particle sizes generated in the blast, and where a person is with respect to the detonation. Different studies have reported that plausible radionuclides for dirty bomb include 60 Co, 90 Sr, 137 Cs, 192 Ir, 241 Am based on their availability in commercial sources as well as safeguards, the amount needed for adverse health effects, previous mishandling of radionuclides and malicious uses. In order to have increased long-term cancer risk, the radionuclide would have to deposit inside the body by entering the respiratory tract and then possibly migrate to other organs or bones (ground shine is not considered in this paper because areas affected by the event will likely become inaccessible). This implies that the particles will have to be smaller than 10 μm to be inhaled. Experiments involving the detonation of dirty bombs have shown that particles or droplets smaller than 10 μm are generated, independently from the initial radionuclide or its state (e.g., powder, solution). Atmospheric tests have shown that in unobstructed terrain, the radionuclide laden cloud can travel kilometers downwind even for relatively small amounts of explosives. Furthermore, buildings in the path of the cloud can change the dose rate. For instance, in one experiment with a single building, the dose rate was 1–2 orders of magnitude lower behind the obstacle compared to its front face. For people walking around, the amount of particulate deposited on them and inhaled will depend on their path relative to the cloud, resulting in the counterintuitive result that the closer people may actually not be the ones more at risk because they could simply miss the bulk of the cloud in their wandering. In summary, the long-term cancer risk for people caught in a dirty bomb cloud away from the detonation requires considering where and when the people are, which radionuclide was used, and the layout of the obstacles (e.g., buildings, vegetation) in the path of the cloud.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Hydrogen influences thermal activation parameters for dislocation glide during low cycle fatigue of 316L stainless steel

Measurements of activation areas are used to investigate the effect of hydrogen on the kinetics of dislocation glide during cyclic deformation in cold-worked 316L stainless steel. Non-charged and hydrogen-precharged (H-precharged) specimens were tested in low cycle fatigue (LCF) under plastic strain control. A series of plastic strain rate changes was performed periodically at the peak true plastic strain from the first cycle to half-life, and at various plastic strain values around stable hysteresis loops near half-life to determine the operational activation area, Δ a ∗. Both material conditions demonstrate a rapid increase in Δ a ∗ during the initial rapid softening followed by a region of approximately constant values coinciding with a reduced rate of softening. Near half-life, hydrogen reduces Δ a ∗ at a given true stress due to its effect on the activation distance and obstacle spacing. The magnitudes of Δ a ∗ reveal that bypassing solutes, cutting forest dislocations, and initiating cross slip are important mechanisms of thermally activated dislocation glide at all amplitudes, except hydrogen suppresses cross slip at the lowest plastic strain amplitudes. These results are supported by electron microscopy characterization of deformed microstructures. A Haasen plot analysis indicates that forest dislocations control the kinetics of deformation in both material conditions. It also reveals the presence of athermal obstacles in both non-charged and H-precharged conditions, likely dense dislocation tangles and cell walls. Additionally, the effect of hydrogen on microstructure evolution (by reducing the propensity for cross slip) leads to a dependence of athermal stress on plastic strain amplitude.

Activation area↗

A NEA review on innovative structural materials solutions, including advanced manufacturing processes for nuclear applications based on technology readiness assessment

The Nuclear Energy Agency (NEA) Expert Group on Innovative Structural Materials (EGISM) was established in 2008 under the guidance of the Nuclear Science Committee (NSC). Its objectives are to conduct joint and comparative studies to support the development, selection and characterisation of innovative structural materials that can be implemented in advanced nuclear fuel cycles, under long service lifetime and extreme conditions, such as high temperature, high dose/dose rate and corrosive chemical environments. In this context of growing interest and initiatives, the EGISM initiated at the beginning of 2018 an activity among its members to: Identify, in a non-exhaustive way, the currently existing programs on innovative materials and fabrication processes in NEA member countries and China; Establish a first cartography of the activities that are underway on these topics and identify common subjects and thematic; Propose a Technology Readiness Level scale to estimate the maturity of both innovative materials and fabrication processes; Carry out a reflection on what the enablers are to quickly climb this TRL scale, as well as the obstacles, in order to identify solutions to overcome them. This paper first gives definitions shared between the EGISM members on what are considered as advanced structural materials solutions. Next, some international initiatives for the accelerated development of high performance materials are presented both in non-nuclear and nuclear fields. Then, the methodology adopted for technology readiness assessment is explained. A non-exhaustive synthesis of the projects identified among the EGISM members on innovative structural materials and advanced manufacturing solutions such as additive manufacturing is presented. The TRL level of these projects is evaluated. A focus is also made on some of these projects to illustrate and explain the TRLs chosen as well as highlighting enablers or obstacles identified to climbing up the TRL scale.

36 MATERIALS SCIENCE↗

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory’s Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗

Observation of subcritical shocks in a collisional laboratory plasma: scale dependence near the resistive length

We present a study of subcritical shocks in a highly collisional laboratory plasma with a dynamically significant magnetic field. Shocks were produced by placing cylindrical obstacles into the supermagnetosonic ( $M_{{\rm MS}} \sim 1.9$ ) outflow from an inverse wire array z-pinch at the MAGPIE pulsed power facility ( $n_{e} \sim 8.5 \times 10^{17}\,{\rm cm}^{-3}$ , $v \sim 45\,{\rm km}\,{\rm s}^{-1}$ ). We demonstrate the existence of subcritical shocks in this regime and find that secondary stagnation shocks form in the downstream which we infer from interferometry and optical Thomson scattering measurements are hydrodynamic in nature. The subcritical shock width is found to be approximately equal to the resistive diffusion length and we demonstrate the absence of a jump in hydrodynamic parameters. Temperature measurements by collective optical Thomson scattering showed little temperature change across the subcritical shock ( ${<}10\,\%$ of the ion kinetic energy) which is consistent with a balance between adiabatic and Ohmic heating and radiative cooling. We demonstrate the absence of subcritical shocks when the obstacle diameter is less than the resistive diffusion length due to decoupling of the magnetic field from the plasma. These findings are supported by magnetohydrodynamic simulations using the Gorgon and AstroBEAR codes and discrepancies between the simulations and experiment are discussed.

Physics↗

Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

Single-phase high- and medium-entropy alloys with face-centred cubic (fcc) structure can exhibit high tensile ductility and excellent toughness, but their room-temperature strengths are low. Dislocation obstacles such as grain boundaries, twin boundaries, solute atoms and precipitates can increase strength. However, with few exceptions, such obstacles tend to decrease ductility. Interestingly, precipitates can also hinder phase transformations. Here, using a model, precipitate-strengthened, Fe–Ni–Al–Ti medium-entropy alloy, we demonstrate a strategy that combines these dual functions in a single alloy. The nanoprecipitates in our alloy, in addition to providing conventional strengthening of the matrix, also modulate its transformation from fcc-austenite to body-centred cubic (bcc) martensite, constraining it to remain as metastable fcc after quenching through the transformation temperature. During subsequent tensile testing, the matrix progressively transforms to bcc-martensite, enabling substantial increases in strength, work hardening and ductility. This use of nanoprecipitates exploits synergies between precipitation strengthening and transformation-induced plasticity, resulting in simultaneous enhancement of tensile strength and uniform elongation. Further, our findings demonstrate how synergistic deformation mechanisms can be deliberately activated, exactly when needed, by altering precipitate characteristics (such as size, spacing, and so on), along with the chemical driving force for phase transformation, to optimize strength and ductility.

36 MATERIALS SCIENCE↗

Avoiding fusion plasma tearing instability with deep reinforcement learning

For stable and efficient fusion energy production using a tokamak reactor, it is essential to maintain a high-pressure hydrogenic plasma without plasma disruption. Therefore, it is necessary to actively control the tokamak based on the observed plasma state, to manoeuvre high-pressure plasma while avoiding tearing instability, the leading cause of disruptions. This presents an obstacle-avoidance problem for which artificial intelligence based on reinforcement learning has recently shown remarkable performance. However, the obstacle here, the tearing instability, is difficult to forecast and is highly prone to terminating plasma operations, especially in the ITER baseline scenario. Previously, we developed a multimodal dynamic model that estimates the likelihood of future tearing instability based on signals from multiple diagnostics and actuators. Here we harness this dynamic model as a training environment for reinforcement-learning artificial intelligence, facilitating automated instability prevention. We demonstrate artificial intelligence control to lower the possibility of disruptive tearing instabilities in DIII-D, the largest magnetic fusion facility in the United States. The controller maintained the tearing likelihood under a given threshold, even under relatively unfavourable conditions of low safety factor and low torque. In particular, it allowed the plasma to actively track the stable path within the time-varying operational space while maintaining H-mode performance, which was challenging with traditional preprogrammed control. This controller paves the path to developing stable high-performance operational scenarios for future use in ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Programming entropy production hotspots via interaction patterning

Dissipation in soft matter and living systems is highly heterogeneous, giving rise to complex local entropy production patterns. Recent work has identified the connection between local entropy production and locally extractable amount of work. This suggests that locally produced entropy can be recovered to power nanorobots and biological machines, prompting the need for efficient strategies to modulate and fine-tune local entropy production. In this work, we propose to program entropy production hotspots by leveraging local interaction patterns and test this approach in simulations of a fluid driven through a nanopore or past an obstacle. Here, the results show that patterning the surface of the pore with a repulsive patch gives rise to an entropy production hotspot around the patch, while an attractive patch leads to an entropy production cold spot. Varying the strength of the interaction and width of the patch enables modulating the hotness and extent of the hot spot. In flows past interaction patterned-obstacles, we show that the combined effects of steric hindrance and attraction allows to program a specific entropy production map, thereby opening the door to the precise powering of nanomachines.

Desgranges, Caroline [University of Massachusetts,↗

X-ray spectroscopy evidence for plasma shell formation in experiments modeling accretion columns in young stars

Recent achievements in laboratory astrophysics experiments with high-power lasers have allowed progress in our understanding of the early stages of star formation. In particular, we have recently demonstrated the possibility of simulating in the laboratory the process of the accretion of matter on young stars [G. Revet et al., Sci. Adv. 3, e1700982 (2017)]. The present paper focuses on x-ray spectroscopy methods that allow us to investigate the complex plasma hydrodynamics involved in such experiments. We demonstrate that we can infer the formation of a plasma shell, surrounding the accretion column at the location of impact with the stellar surface, and thus resolve the present discrepancies between mass accretion rates derived from x-ray and optical-radiation astronomical observations originating from the same object. In our experiments, the accretion column is modeled by having a collimated narrow (1 mm diameter) plasma stream first propagate along the lines of a large-scale external magnetic field and then impact onto an obstacle, mimicking the high-density region of the stellar chromosphere. A combined approach using steady-state and quasi-stationary models was successfully applied to measure the parameters of the plasma all along its propagation, at the impact site, and in the structure surrounding the impact region. The formation of a hot plasma shell, surrounding the denser and colder core, formed by the incoming stream of matter is observed near the obstacle using x-ray spatially resolved spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RNA polymerase II trapped on a molecular treadmill: Structural basis of persistent transcriptional arrest by a minor groove DNA binder

Elongating RNA polymerase II (Pol II) can be paused or arrested by a variety of obstacles. These obstacles include DNA lesions, DNA-binding proteins, and small molecules. Hairpin pyrrole-imidazole (Py-Im) polyamides bind to the minor groove of DNA in a sequence-specific manner and induce strong transcriptional arrest. Remarkably, this Py-Im–induced Pol II transcriptional arrest is persistent and cannot be rescued by transcription factor TFIIS. In contrast, TFIIS can effectively rescue the transcriptional arrest induced by a nucleosome barrier. The structural basis of Py-Im–induced transcriptional arrest and why TFIIS cannot rescue this arrest remain elusive. Here we determined the X-ray crystal structures of four distinct Pol II elongation complexes (Pol II ECs) in complex with hairpin Py-Im polyamides as well as of the hairpin Py-Im polyamides–dsDNA complex. We observed that the Py-Im oligomer directly interacts with RNA Pol II residues, introduces compression of the downstream DNA duplex, prevents Pol II forward translocation, and induces Pol II backtracking. These results, together with biochemical studies, provide structural insight into the molecular mechanism by which Py-Im blocks transcription. Our structural study reveals why TFIIS fails to promote Pol II bypass of Py-Im–induced transcriptional arrest.

59 BASIC BIOLOGICAL SCIENCES↗

Formation of hierarchically structured martensites in pure iron with ultrahigh strength and stiffness

Strong steels are primarily fabricated by introducing spatial obstacles (e.g., stacking faults and precipitates) that inhibit dislocation slips under stress to achieve high strength. However, for most low-carbon steels, such obstacles are difficult to form mainly because the martensitic transition is kinetically unfavorable by conventional methods, which precludes the attainment of high-strength materials in these steels with low solute contents. Here, we report an innovative high-pressure preparation of martensitic pure Fe with involving nano-effect, which leads to the formation of ultrastrong bulk iron with exceptionally high yield strength, ultimate strength, and hardness of 2.9 GPa, 3.7 GPa, and 9.0 GPa, respectively, exceeding those of high-speed steels. Such extraordinary mechanical properties are closely attributed to its high-density martensites with unique multiscale hierarchical structures formed due to complex phase transitions under pressure.

Science & Technology - Other Topics↗

Audible enclaves crafted by nonlinear self-bending ultrasonic beams

Delivering audible content to a targeted listener without disturbing others is paramount in audio engineering. However, achieving this goal has long been challenging due to the diffraction of low-frequency (long-wavelength) audio waves in linear acoustics. Here, we introduce an approach for creating remote audio spots, dubbed audible enclaves, by harnessing the local nonlinear interaction of two self-bending ultrasonic beams with distinct spectra. The self-bending ultrasonic beams created by acoustic metasurfaces, though inaudible, can bypass obstacles such as human heads. At their intersection behind obstacles, highly localized audible enclaves are formed due to the local nonlinear interactions. Additionally, we demonstrate the ultrabroadband capabilities of our metasurface-based implementation both numerically and experimentally, spanning from 125 Hz to 4 kHz (6 octave bands), covering the majority of the audible frequency range. The practicality of our proposed technique is underscored by its compact implementation size (0.16 m, equivalent to 0.06 wavelengths at 125 Hz), as well as its robust performance under wideband transient audio signal excitation and in a common room with reverberations. Our proposed audible enclaves hold significant potential for various applications in advanced audio engineering, including private speech communications, immersive spatial audio reproduction, and high-resolution sound/quiet zone control.

Science & Technology - Other Topics↗

Effect of helium bubbles on the mobility of edge dislocations in copper

Abstract Helium bubbles can form in materials upon exposure to irradiation. It is well known that the presence of helium bubbles can cause changes in the mechanical behavior of materials. To improve the lifetime of nuclear components, it is important to understand deformation mechanisms in helium-containing materials. In this work, we investigate the interactions between edge dislocations and helium bubbles in copper using molecular dynamics (MD) simulations. We focus on the effect of helium bubble pressure (equivalently, the helium-to-vacancy ratio) on the obstacle strength of helium bubbles and their interaction with dislocations. Our simulations predict significant differences in the interaction mechanisms as a function of helium bubble pressure. Specifically, bubbles with high internal pressure are found to exhibit weaker obstacle strength as compared to low-pressure bubbles of the same size due to the formation of super-jogs in the dislocation. Activation energies and rate constants extracted from the MD data confirm this transition in mechanism and enable upscaling of these phenomena to higher length-scale models.

36 MATERIALS SCIENCE↗

Computation of forces and stresses in solids: Towards accurate structural optimization with auxiliary-field quantum Monte Carlo

The accurate computation of forces and other energy derivatives has been a long-standing challenge for quantum Monte Carlo methods. A number of technical obstacles contribute to this challenge. We discuss how these obstacles can be removed with the auxiliary-field quantum Monte Carlo (AFQMC) approach. AFQMC is a general, high-accuracy, many-body total-energy method for molecules and solids. The implementation of back-propagation for pure estimators allows direct calculation of gradients of the energy via the Hellmann-Feynman theorem. A planewave basis with norm-conserving pseudopotentials is used for the study of periodic bulk materials. Completeness of the planewave basis minimizes the effect of so-called Pulay terms. The ionic pseudopotentials, which can be incorporated in AFQMC in exactly the same manner as in standard independent-electron methods, regulate the force and stress estimators and eliminate any potential divergence of the Monte Carlo variances. The resulting approach allows applications of full geometry optimizations in bulk materials. As a result, it also paves the way for many-body computations of the phonon spectrum in solids.

36 MATERIALS SCIENCE↗

Protecting Customer Privacy Through Distributed Energy Resource Anonymization

Due to their stochastic nature, the increase of Renewable Energy Resources (RERs) as a primary source of energy for power grids creates challenges regarding the reliability and resilience of the system. In order to combat these obstacles, expansion of Distributed Energy Resources (DERs) and their participation in Demand Response (DR) programs is necessary. Widespread participation requires prioritizing customer privacy and addressing concerns that may arise regarding communication between DERs and the Grid Service Provider (GSP). This paper discusses the use of flow reservation resources to split the operating cycles of DER load profiles into unique phases. The splitting of phases increases anonymization of the DERs by making it more difficult to determine the individual characteristics of the device. We discuss an example of this using simulated DER load profile data and examine the resulting effectiveness by using a machine learning algorithm for classification, called Support Vector Machine (SVM).

Distributed Energy Resource, Anonymization, Renewa↗