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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Learned magnetic map cues and two mechanisms of magnetoreception in turtles

Growing evidence indicates that migratory animals exploit the magnetic field of the Earth for navigation, both as a compass to determine direction and as a map to determine geographical position. It has long been proposed that, to navigate using a magnetic map, animals must learn the magnetic coordinates of the destination, yet the pivotal hypothesis that animals can learn magnetic signatures of geographical areas has, to our knowledge, yet to be tested. Here, in this work, we report that an iconic navigating species, the loggerhead turtle ( Caretta caretta ), can learn such information. When fed repeatedly in magnetic fields replicating those that exist in particular oceanic locations, juvenile turtles learned to distinguish magnetic fields in which they encountered food from magnetic fields that exist elsewhere, an ability that might underlie foraging site fidelity. Conditioned responses in this new magnetic map assay were unaffected by radiofrequency oscillating magnetic fields, a treatment expected to disrupt radical-pair-based chemical magnetoreception, suggesting that the magnetic map sense of the turtle does not rely on this mechanism. By contrast, orientation behaviour that required use of the magnetic compass was disrupted by radiofrequency oscillating magnetic fields. The findings provide evidence that two different mechanisms of magnetoreception underlie the magnetic map and magnetic compass in sea turtles.

animal behaviour↗
DOE OSTI2025

Status of the FCC-ee interaction region design

This paper presents a comprehensive overview of the Machine Detector Interface (MDI) design developed for the FCC-ee Feasibility Study. It highlights novel studies related to the lightweight interaction region, including a mechanical model of the vacuum chambers, integration of the vertex detector, the MDI alignment system, and assessments of machine-induced backgrounds. The small beam pipe radius and thickness, as well as the high power to be dissipated, require state-of-the-art mechanical design. The integration of all mechanical elements and detectors is challenging, necessitating careful studies to allow fulfilling conflicting requirements. The optimisation of the machine detector interface against formidable backgrounds is presented.

Beam-induced backgrounds↗
DOE OSTI2021

Numerical Analysis of Time Resolved Photoluminescence for Alumina/Cd(Se,Te) Double Heterostructures

Al2O3 has demonstrated excellent Cd(Se,Te) surface passivation. In this work, recombination mechanisms were investigated by comparing simulations of time resolved photoluminescence (TRPL) to PL decay data (320 ns effective lifetime) for Al2O3 /Cd(Se,Te)/Al2O3 double heterostructures. Models were employed to investigate the effects of bulk and surface recombination, electric fields, mobility, and doping by simulating intensity-dependent single- (1PE) and two-photon excitation (2PE) TRPL. 2PE simulations replicate decay behavior while 1PE simulations require attention to charge redistribution. Various coupled mechanisms cannot be distinguished from PL decay data alone. Complementary measurements are required to constrain the model parameters and isolate mechanisms.

CdTe↗
DOE OSTI2023

Transition in helium bubble strengthening of copper from quasi-static to dynamic deformation

Damage from low-temperature irradiation and the subsequent degradation of materials performance pose significant challenges for the storage of radioactive materials and for peripheral components in some nuclear reactor designs. Fully understanding the mechanical behavior of such materials requires test data for strain rates in both the quasi-static (< 10/s) and dynamic (>> 10/s) regimes. While dynamic testing has generally been avoided in the past for neutron irradiated (contamination concerns) and ion irradiated (insufficient volume) materials, surface-sensitive Richtmyer-Meshkov instability (RMI) tests were used in the present work to overcome these limitations. Here, nanopillar compression, nanoindentation, and RMI testing data from a helium implanted surface layer (~10 µm thick) were compiled to explore the effects of helium bubbles on the materials strength of high-purity copper at strain rates of 0.001/s – 10 8 /s. While nano-mechanical testing revealed increases in yield strength and hardness with increasing helium dose from 1000 to 4000 appm He, RMI indicated no significant changes in strength as compared to unimplanted copper. Here, this discrepancy in behavior was rationalized through a combination of recent literature and follow-on molecular dynamics (MD) simulations, leading to the conclusion that the nanoscale helium bubbles acting as dispersed barriers to dislocation motion at quasi-static strain rates collapse under shock loading and cease to be effective barriers at high strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗
DOE OSTI2024

DECOVALEX-2023: Task E Final Report

This is the Task E final report for DECOVALEX-2023. Task E is focused on understanding thermal, two-phase hydrological, and mechanical (TH2M) processes, especially related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and essentially non-porous in the far field (away from excavations). Investigation of the short-term (days to years) near-field (centimeters to tens of meters) behavior of salt is important for radioactive waste disposal because this early period strongly controls the amount of brine in a salt repository. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment. The main test case used in Task E is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, USA. The Task was divided into a series of Steps. Step 0 was an introduction to processes in salt, that included matching historical unheated brine inflow data from boreholes at WIPP and matching temperature observations during BATS heater test 1a. Step 1 included validation of models against a thermo-poroelastic analytical solution relevant to heated boreholes in salt, and two-phase flow around an excavation in salt. Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the BATS 1a heater test. There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. The key learning points from Task E have been: • Heat conduction through salt typically requires non-linear thermal conductivity (as a function of temperature), but most models do a good job matching observations, given appropriate adjustments to the applied power and some thermocouple locations. • Thermal pressurization requires coupled thermal-hydrological-mechanical (THM) responses that consider the thermal expansion of the fluid and solid phases. • Initialization of two-phase flow models around a borehole or excavation in salt are more realistically represented as “wetting up”, rather than “drying down” (i.e., the initial state after excavation is mostly dry, rather than mostly wet). • The BATS 1a heater test includes a significant release of brine after the end of heating, which requires a large increase in permeability to recreate. Task E has been a great learning experience for all the teams involved, and feedback from the modeling teams has led to changes in the design of follow-on BATS experiments, which are now ongoing underground at WIPP. There was a balance throughout the task between freedom to model phenomena how each team saw fit, and prescriptiveness in problem design to bring the modeling teams closer together to allow attribution of smaller differences between models to different modeling choices. The modeling approaches seem to go through two phases: an early phase of discovery or testing, and a later phase of refinement and improvement. In future modeling efforts, different field data could be used (e.g., BATS 2) and more time should be included in the processes for teams to make multiple model refinement or even significant changes to their conceptual model or setup, based on lessons learned from the modeling exercise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Autonomous Hydrogen Fueling Station

This project “Autonomous Hydrogen Fueling Station” covered the autonomous refueling with both gaseous hydrogen and liquid hydrogen. The part on gaseous hydrogen focused on the development of an autonomous robotic fueling arm that would couple to a fuel cell engine for hydrogen refueling without guidance from the forklift operator and budget period. Research was also covered for the robotic fueling with a commercial vehicle. The second phase of the project created the baseline for an autonomous liquid hydrogen transfer system that would minimize boil off losses by operating at thermodynamically efficient state points. For the development of the robotic fueling arm, testing was conducted to establish a baseline measurement of the accuracy and repeatability of a human operator positioning a lift truck in front of a dispenser. The goal was to establish the range of motion required for an autonomous fueling mechanism to mate a hydrogen nozzle with a receptacle on a fuel cell system installed in a forklift. The final design comprised a selective compliance articulated robot arm (SCARA)-type mechanism with two arms for horizontal motion and a ball screw for vertical movement and color and LIDAR cameras were used for marker identification and proximity awareness to guide the robotic arm to its target receptacle. Initial tests resulted in 199 out of 200 successful attempts at autonomous coupling of the dispensing coupler and a fuel cell engine, without hydrogen. The dispenser prototype was modified to include tubing for both hydrogen fuel and air purge lines, but subsequent tests were confounded by the shoulder motor over current errors which limited the robot from getting to the fully inserted position to achieve a positive latch. Robotic hydrogen refueling was successfully demonstrated over 1.5 hours of testing, Plug completed 29 successful latches with an average number of 4 sequential latches before failure. However, a robot capable of placing the nozzle with more force is required for higher reliability. For budget period two, a small scale (10 kg / transfer) automated control system was designed that would operate valves to control pressure and flow of liquid nitrogen between a source and receiving tank with an aim to minimize boil off losses by operating at the most thermodynamically efficient state points. Control system logic flow and a P&ID were developed prior to system safety characterization via HAZOP. A control narrative and system state points were defined. Delays in approval for a change of project objective and procurement issues precluded the construction and test of the final prototype system.

08 HYDROGEN↗
DOE OSTI2024

FFTF HT9 Cladding Microstructure Characterization

The sodium-cooled fast reactor (SFR) is a promising candidate for next generation nuclear reactors, operating at extreme conditions which include high temperatures (>500?C core outlet temperature) and significant neutron damage. High-Cr martensitic HT9 steel is an excellent candidate for SFR cladding and duct material due to its compatibility with liquid sodium, good thermal conductivity, resistance to void swelling, and strong creep rupture strength [1-4].However, the harsh in-core environment of SFRs can cause complex microstructural changes and mechanical property degradation in HT-9. Ensuring the safe use of HT9 cladding for metallic fuel requires both a thorough understanding of its mechanical response to microstructure evolution as well as reliable microstructure-sensitive modeling predictions. Microstructure-sensitive modeling of high temperature creep behavior in HT9 cladding for SFR applications currently lack experimental data to model the phenomena accurately. To fill this need, methods to perform microstructural characterization have been developed and performed on HT9.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of electron beam irradiation on CrMnV and CrMnTiV high entropy alloys: Nano-mechanical, structural, and thermodynamic perspectives

Beam exit windows are crucial components of any particle accelerator as they provide an interface between the beamline vacuum and target material at atmospheric media. For high beam power machines, special materials and designs are required to withstand high radiation and mechanical loads, while minimizing energy loss during transition and maximizing window lifetime. This research investigates the impact of electron beam exposure to bulk CrMnV and CrMnTiV high entropy alloys (HEAs) with the primary goal of identifying suitable candidate materials for the design of robust and durable exit window settings. The selection criteria include intrinsic characteristics, power dissipation, and mechanical responses. According to the thermodynamic calculations, both equiatomic CrMnV and the addition of 7% of Ti with equiatomic CrMnV yield solid-solutions phases. The structural and mechanical properties of CrMnV and CrMnTiV samples were tested using field emission scanning electron microscopy, atomic force microscopy, scanning electron microcopy with energy dispersive x-ray spectroscopy, x-ray diffraction, and nanoindentation before and after exposure to a dose of ~66 kGy from a 10 MeV e-beam accelerator. Despite exhibiting beam transmission characteristics comparable to Cr and V, the indentation hardness of HEAs exceeded that of the Cr and V samples by five to six times. The examination of the CrMnTiV irradiated samples revealed organized deformation patterns depicting new features, which we suspect twinning and twin boundaries due to the addition of Ti to CrMnV. Ti, a hexagonal-close-packed crystal structure, is commonly known for deformation twinning behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Experimental investigation of turbulent wake flows in a helically wrapped rod bundle in presence of localized blockages

In nuclear sodium fast reactors, bundles of rods are tightly packed into a triangular lattice, enclosed in a hexagonal duct, and each pin is spirally wrapped with a thin wire. Flow blockages can potentially impact the local flow characteristics and heat transfer mechanisms in the bundle due to its small subchannel size. The effects of the blockage on the flow structures and heat transfer mechanisms are important aspects that require an accurate investigation. In this study, the flow-field characteristics in the vicinity of a blockage located in the exterior subchannel of rod bundles with helically wrapped wires were experimentally investigated. The velocity fields in the exterior subchannel were acquired by applying matched-index-of-refraction and time-resolved particle image velocimetry (TR-PIV) techniques for Reynolds numbers of Re 1 = 4000 and Re 2 = 17 000, i.e., equivalent to Rew 1 = 19 600 and Rew 2 = 83 200, respectively, based on the blockage width. The results from the TR-PIV measurements revealed an arch-shaped vortex with a large flow recirculation and a pair of counter-rotating vortices in the wake region downstream of the blockage, which is commonly observed in the wake flow of bluff bodies. The relative lateral distance and angle between the two vortices decreased when the Reynolds numbers increased. Profiles of maximum turbulence intensity along the shear layers illustrated the transition process including the growth, peak, and decay along the flow direction. From the spectral analysis of the turbulent velocities extracted at points along the shear layer, the Strouhal numbers ( St ) representing the vortex shedding frequency were found to be St = 0.25 and St = 0.56 for the left and right shear layers, respectively. Characteristics of shear layers generated by the blockage in the exterior subchannel were investigated via the two-point cross correlation of fluctuating velocities. The patiotemporal cross correlations of turbulent velocities, computed at points in the region where the left shear layer exhibited rolling effects and vortex breakdowns, were considerably wider and longer. The convection velocity U c was estimated to be ~0.82 U m to 0.93 U m . Proper orthogonal decomposition (POD) analysis was applied to the instantaneous velocity fields to extract the statistically dominant flow structures. It was found that POD modes 2–3 and 4–5 formed the pair modes when the corresponding POD temporal coefficients depicted sinusoidal shapes and exhibited nearly circular orbits in the phase space. Spectral analysis of the POD temporal coefficients confirmed the vortex shedding frequencies detected in the analysis of turbulent velocities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Nanoscale simulation of the thylakoid membrane response to extreme temperatures

Abstract The thylakoid membrane is in a temperature‐sensitive equilibrium that shifts repeatedly during the life cycle in response to ambient temperature or solar irradiance. Plants respond to seasonal temperature variation by changing their thylakoid lipid composition, while a more rapid mechanism for short‐term heat exposure is required. The emission of the small organic molecule isoprene has been postulated as one such possible rapid mechanism. The protective mechanism of isoprene is unknown, but some plants emit isoprene at high temperature. We investigate the dynamics and structure for lipids within a thylakoid membrane across temperatures and varied isoprene content using classical molecular dynamics simulations. The results are compared with experimental findings for temperature‐dependent changes in the lipid composition and shape of thylakoids. The surface area, volume, and flexibility of the membrane, as well as the lipid diffusion, increase with temperature, while the membrane thickness decreases. Saturated thylakoid 34:3 glycolipids derived from eukaryotic synthesis pathways exhibit altered dynamics relative to lipids from prokaryotic synthesis paths, which could explain the upregulation of specific lipid synthesis pathways at different temperatures. Increasing isoprene concentration was not observed to have a significant thermoprotective effect on the thylakoid membranes, and that isoprene readily permeated the membrane models tested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The Effects of Silicon and Niobium Concentration on the Solidification Behavior and Microstructure of Cast Monel Alloys

Cast Monel alloys are used in applications requiring a combination of good mechanical properties and excellent resistance to corrosion. Despite prevalent industrial use, relatively few studies have been conducted to investigate the relationships between composition, solidification behavior, and microstructure. Given that these alloys are used in the cast and welded conditions, these factors have a significant influence over the material properties. Here, in this work, microstructural characterization, electron probe microanalysis, X-ray diffraction, and differential scanning calorimetry were used to study how changes in Si and Nb concentrations affected the solidification path and microstructure of Monel alloys. It was found that increasing Nb concentration stabilized higher amounts of MC carbides and suppressed graphite formation during solidification. It was also found that the high nominal concentration and segregation of Si to the liquid led to the formation of Ni 31 Si 12 and other silicides via terminal eutectic reactions at the end of solidification. A pseudo-binary solidification diagram was constructed using experimental data and was applied to predict the mass fraction of solidified eutectic as a function of composition. The modeled microstructures were found to be in good agreement with experimentally measured phase fractions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Influence of Nominal Composition on the Microstructure, Tensile Properties, and Weldability of Cast Monel Alloys

Cast Monel alloys are used in many industrial applications that require a combination of good mechanical properties and excellent resistance to corrosion. Despite relative widespread use, there has been limited prior research investigating the fundamental composition–structure–property relationships. Here in this work, microstructural characterization, thermal analysis, electron probe microanalysis, tensile testing, and Varestraint testing were used to assess the effects of variations in nominal composition on the solidification path, microstructure, mechanical properties, and solidification cracking susceptibility of cast Monel alloys. It was found that Si segregation caused the formation of silicides at the end of solidification in grades containing at least 3 wt pct Si. While increases to Si content led to significant improvements in strengthening due to the precipitation of β 1 -Ni 3 Si, the silicide eutectics acted as crack nucleation sites during tensile loading which severely reduced ductility. The solidification cracking susceptibility of low-Si Monel alloys was found to be relatively low. However, increases to Si concentration and the onset of associated eutectic reactions increased the solidification temperature range and drastically reduced cracking resistance. Increases in the Cu and Mn concentrations were found to reduce the solubility limit of Si in austenite which promoted additional eutectic formation and exacerbated the reductions in ductility and/or weldability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mechanism of drying-induced change in the physical properties of concrete: A mesoscale simulation study

Although many studies have found that drying alters the mechanical properties of concrete, the mechanism behind this change remains unclarified. The aim of this study is to elucidate the mechanism of change in properties of concrete after drying through the numerical calculation: a 3D mesoscale rigid-body-spring model (RBSM) with three phases, i.e. mortar, aggregate, and the interfacial transition zone while considering the properties changes of mortar due to drying. Based on the RBSM results, it is concluded that the change in compressive strength due to drying and heating is determined by a balance of the impact of drying-induced microcracking around coarse aggregates and the change in mechanical properties of the mortar due to drying. These mechanisms change the applied load required to reach the critical crack width and distribution, at which rim of the specimen begins to isolate from the core region and the load sustained by the rim decreases.

36 MATERIALS SCIENCE↗