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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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31 records · Page 2

Improved damage tolerance of SiC-based nuclear fuel cladding with novel multi-layered SiC coating design at 1200 °C

Continuous SiC fibre reinforced SiC matrix composites (SiC f -SiC m ) with monolithic SiC outer coatings are considered as a damage-tolerant cladding design for loss of coolant accident (LOCA) conditions in light water reactors. However, monolithic SiC coatings are brittle and prone to catastrophic failure. In this study, a SiC f -SiC m cladding with a novel multi-layer SiC outer coating (11 sub-layers, ∼260 µm in total thickness) was investigated under C-ring compression at room temperature and 1200 °C in argon environment. Real-time synchrotron X-ray computed tomography (XCT) was employed to capture crack initiation and propagation processes. Compared to conventional monolithic SiC outer coatings, the multi-layer coating structure facilitated crack deflection and bifurcation enhancing its damage tolerance at both temperatures. Despite pre-existing surface cracks, claddings exhibited stable mechanical-performance at both temperatures. These initial cracks did not critically affect the failure processes as they were not aligned with the maximum stress direction. Furthermore, the microstructure, distribution of residual stresses, and local properties of individual components in the material were thoroughly characterized, and compared with open literature on conventional claddings with monolithic outer coatings. These results provide new insights into the failure mechanisms of multi-layer SiC coatings and offer guidance for the future design of accident-tolerant nuclear fuel claddings.

36 - MATERIALS SCIENCE↗

Development and Validation of Quantitative Model-Based Image Reconstruction for NDE of Reinforced Steel-Lined Concrete Structures: Kal-El FY 2020

This project studied the capabilities of Model-Based Image Reconstruction (MBIR) and Machine Learning (ML) algorithms in the imaging and estimation of rebar corrosion from ultrasound signals. The application was challenging due to the introduction of a steel liner between the sensor and the concrete containing the rebar. The study focused in a synthetic specimen with a 6.35 mm thick steel liner, and a 19.05 mm diameter rebar at a depth of 44.5 mm and with four levels of corrosion; 0%, 20%, 50%, and 100% corrosion level. The corrosion was applied uniformly around the rebar, generating a ring in the perimeter of the rebar with different acoustic density. In order to generate a realistic synthetic dataset, we added random texture to the concrete of the synthetic specimens. This texture will mimic the variations encountered in real concrete specimens.We adapted our MBIR algorithm for the application and enhanced the algorithm to integrate in the physical model known specimen features, such as the steel liner thickness. The new MBIR method was able to cancel out reverberation from the steel liner and properly image the rebar. In particular, corrosion for the 50% and 100% cases were easily visible and quantitative metrics showed a slight separation for the 0% and 20% levels. The quantitative results were in agreement with the qualitative assessment. We also developed a ML XGBoost model to estimate corrosion level from the ultrasound signals. By combining the ML method with MBIR, we can pinpoint in the ultrasound signals the section that corresponds to the echoes from the rebar. The extract signals are processed by the XGBoost model for prediction. From each system scan, we obtain 15 predictions. The median prediction value is used as the final prediction. The True Acceptance Rate for the method is over 99%.

36 MATERIALS SCIENCE↗

The hard x-ray nanotomography microscope at the advanced light source

Beamline 11.3.1 at the Advanced Light Source is a tender/hard (6–17 keV) x-ray bend magnet beamline recently re-purposed with a new full-field, nanoscale transmission x-ray microscope. The microscope is designed to image composite and porous materials possessing a submicrometer structure and compositional heterogeneity that determine materials’ performance and geologic behavior. The theoretical and achieved resolutions are 55 and <100 nm, respectively. The microscope is used in tandem with a <25 nm eccentricity rotation stage for high-resolution volume imaging using nanoscale computed tomography. The system also features a novel bipolar illumination condenser for the illumination of an ~100 μm spot of interest on the sample, followed by a phase-type zone plate magnifying objective of ~52 µm field of view and a phase detection ring. The zone plate serves as the system objective and magnifies the sample with projection onto an indirect x-ray detection system, consisting of a polished single crystal CsI(Tl) scintillator and a range of high-quality Plan Fluorite visible light objectives. The objectives project the final visible light image onto a water-cooled CMOS 2048 × 2048-pixel 2 detector. Here, in this paper, we will discuss the salient features of this instrument and describe early results from imaging the internal three-dimensional microstructure and nanostructure of target materials, including fiber-reinforced composites and geomaterials.

47 OTHER INSTRUMENTATION↗

Surrogate Modelling of 3rd Integer Resonant Extraction at Fermilab Delivery Ring

We present an ongoing work in which a surrogate model is being developed to reproduce the response dynamics of the third-integer resonant extraction process in the Delivery Ring (DR) at Fermilab. This effort is in pursuit of smoothly extracting circulating beam to the Mu2e Experiment s production target, wherein the goal is to extract a uniform slice of the circulating $1e12$ protons in the DR over 25,000 turns (43~ms). The DR contains 3 harmonic sextupoles which excite a third-integer resonance as well as three fast, tune-ramping quadrupole magnets which drive the horizontal tune towards the $29/3$ resonance. In our initial work the surrogate model trains on a semi-analytical simulation provided in the same format as live data. Using Reinforcement Learning (and other potential ML methods), the trained surrogate acts as the environment in which a simple ML control agent could learn to dynamically adjust the quadrupole ramp at 430 break points within the 43 microsecond spill window. The control agent will be hosted on a dedicated Arria 10 FPGA, introducing its own requirements on control agent architecture. In this work we report the accuracy and fidelity of surrogate models in comparison to the response dynamics of the physics simulator.

Narayanan, Aakaash [Fermilab] (ORCID:0000000157944↗

Integral Field Probe for Mapping of Curved Magnets

The Single Stretched Wire (SSW) method allows highly precise integral field measurements by recording voltage across a tensioned wire mounted to 2-axis linear stages at either end of the magnet aperture. However, traditional SSW probes are not well suited for curved accelerator magnets, which are essential for steering charged particles along arced trajectories in storage rings or beamlines. The tension required to eliminate sag demands a purely straight path, making them incompatible with non-linear magnet geometries. To address this limitation for curved magnets, a modified approach was developed using a segmented, 3D-printed support structure that incorporates a pre-shaped anti-sag curve. Under its own weight and that of the wire bundle, the structure deforms to lie flat while conforming to the curvature of the magnet in the horizontal plane. The optimal geometry of the probe was derived using an iterative process combining FEA simulations in Ansys Mechanical with testing of various carbon fiber-reinforced filaments. The printed and assembled probe was successfully used to measure the SDD-059 magnet at Fermilab, yielding promising results.

Jakopin, Alexander [Northern Illinois U.]↗

The Triple Catalytic Action of Tertiary Nitrogen Catalysts in Recyclable Epoxy-Anhydride Thermosets

The thermosetting polymer matrix in fiber reinforced composites is an important component for energy related applications, such as the lightweighting of vehicles or their use in wind and waterpower turbine blades, due to their ability to provide superior adhesion, stiffness, and applicability to a wide range of manufacturing processes. Despite these benefits, today's thermosets are widely considered to be unrecyclable; thus, there is a large interest in redesigning these materials to be inherently recyclable so that energy intensive production of fibers and monomers can be circumvented, bolstering composite manufacture supply chains. Polyester covalent adaptable networks (PECANs) are one such promising alternative to the incumbent, nonrecyclable epoxy-amine thermosets. PECANs can be formed from the ring-opening co-polymerization (ROCOP) of epoxy-anhydride monomer mixtures and subsequent curing at mild temperatures to exhibit similar performance to conventional epoxies while also possessing unique dynamic chemistries along the ester-hydroxyl backbone that are capable of transesterification and thus reprocessability. While significant advancements have been made in formulating these materials for improved mechanical properties or optimizing solvolysis and reprocessing strategies, less attention has been placed on the impact of the residing amine catalyst used to generate the polyester network. In this work, we evaluated the triple-catalytic efficacy of 12 tertiary amines that act as a curing (bulk ROCOP), a transesterification (internal bond exchange), and a deconstruction (methanolysis) catalyst for PECAN thermosets. Specifically, we first distinguish between chain-growth and step-growth polymerization mechanisms for epoxy-amine and epoxy-anhydride mechanisms. We also utilized density functional theory (DFT) to estimate the basicity (pKb) of each catalyst. Of the tested catalysts, the ROCOP of the studied PECAN network can be completed between 95 and 247 min (at 80 degrees C), with variable gelation phenomena. Additionally, the stress relaxation (transesterification metric) efficiency of the tested PECAN networks with alternative embedded catalysts ranged from 95% to 15% reduction in stress after 5 h at 200 degrees C, and the depolymerization efficacy ranged from 2.5% to 9.8% deconstruction after 36 h at 130 degrees C. Overall, the nitrogen-based moieties were demonstrated to influence polymerization kinetics, catalyze the dynamic transesterification exchange mechanism, and aid in the solvolysis of the thermosets at end-of-life.

36 MATERIALS SCIENCE↗

Thermally induced cracking on the massive concrete structure of the NSLS II synchrotron and its engineering remediation

Synchrotron accelerator facilities such as the NSLS II require extreme stability, both transient (short-term) and quasi-static (long-term) to achieve the desired resolution performance. Consequently, even μm-level movements, particularly differential movements between locations in the concrete structure supporting the accelerator electron beam lattice (storage ring) or high sensitivity experiments (experimental floor) will lead to serious degradation of its performance. Differential settlement in the overall structure or structural movement exceeding anticipated levels will inevitably degrade the performance and will require intervention. Presented in this paper are the design philosophy of the NSLS II ring structure favoring a monolithic ring, the observed cracking behavior of the young NSLS II concrete following casting and in combination with extreme ambient temperature fluctuation, the results of a non-linear, high-fidelity numerical analysis used to emulate the observed cracking and establish the driving mechanism, the numerical analysis-based identification of the crack-arresting solution and finally the implementation of the remediation solution and the long-term performance of the adopted engineering solution. The multi-stage process revealed that computational methods such as non-linear finite element methods have the potential of providing engineering guidance even when complex structures and in combination with non-linear materials, such as steel reinforcement and concrete are involved.

42 ENGINEERING↗

Intermediate States Enable Keratin-like α-To-β Transformations in Strain-Responsive Synthetic Polypeptides

Nature’s fibrous proteins, such as α-keratin, achieve remarkable mechanical properties by undergoing strain-induced α-to-β conformational transitions. Inspired by these materials, we report a strategy for designing synthetic polypeptides that undergo similar transformations at elevated temperatures far exceeding keratin’s operational range. By employing helix-confined ring-opening polymerization (ROP) of N -carboxyanhydrides (NCAs) initiated by a short poly(γ-benzyl- L -glutamate) (PBLG) precursor, we synthesized poly( O -benzyl- L -serine) (PBLS) chains that adopt an α-helical structure yet transition into β-sheets upon heating. Compression molding at carefully chosen temperatures drives PBLS segments into an α-β intermediate state, characterized by relaxed intrachain hydrogen bonds and a hexagonal packing arrangement. Under mechanical strain, these intermediate states convert in situ into β-sheets, producing significant strain-hardening well below the spontaneous α-to-β temperature threshold. Further, this approach extends to polypeptides bearing different side chains, such as poly(S-benzyl- L -cysteine), demonstrating robust mechanical reinforcement across a wide temperature window up to ∼ 200 °C. In situ synchrotron X-ray analysis confirms that chain alignment, β-sheet formation, and domain growth occur stepwise during deformation. By harnessing the intermediate states and the supramolecular cooperativity conferred by compression-molded films, our method provides a versatile platform for developing next-generation polypeptide materials with tunable mechanical resilience and responsiveness─surpassing the temperature limitations of natural fibrous proteins and enabling potential applications demanding broad-temperature mechanical adaptability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning for Slow Spill Regulation in the Fermilab Delivery Ring for Mu2e

A third-integer resonant slow extraction system is being developed for the Fermilab’s Delivery Ring to deliver protons to the Mu2e experiment. During a slow extraction process, the beam on target is liable to experience small intensity variations due to many factors. Owing to the experiment’s strict requirements in the quality of the spill, a Spill Regulation System (SRS) is currently under design. The SRS primarily consists of three components - slow regulation, fast regulation, and harmonic content tracker. In this presentation, we shall present the investigations of using Machine Learning (ML) in the fast regulation system, including further optimizations of PID controller gains for the fast regulation, prospects of an ML agent completely replacing the PID controller using supervised learning schemes such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) ML models, the simulated impact and limitation of machine response characteristics on the effectiveness of both PID and ML regulation of the spill. We also present here nascent results of Reinforcement Learning efforts, including continuous-action soft actor-critic methods, to regulate the spill rate.

43 PARTICLE ACCELERATORS↗

Reinforcement Learning for In-Spill Optimization of the Mu2e Resonant Extraction: Compensating Non-Stationarity

We present design considerations and challenges for the fast machine learning component of a third-order resonant beam extraction regulation system being commissioned to deliver steady beam rates to the mu2e experiment at Fermilab. Dedicated quadrupoles drive the tune toward the 29/3 resonance each spill, extracting beam at kV multiwire septa. The overall Spill Regulation System consists of (1) a “slow” process using ~100-spill averages to adjust the base quad ramp infrequently, (2) a feedforward harmonic content compensator, and (3) the “fast” ML agent reacting during each ongoing spill with on-the-fly additive corrections to the sum of (1) and (2). We have demonstrated improved beam-rate steadying for a fast ML agent compared to a PID controller using a quasi-physical spill simulation, and demonstrated distillation of that simulation into a predictive surrogate model. Current work includes a data-and-training pipeline to generate data-aware surrogates with real-world dynamics, even as the dynamics shift unpredictably. The surrogates are to act as RL environments against which to train our fast ML control agents before deploying them on FPGA in the live system. Further current efforts focus on modeling and controlling beam loss around the storage ring, understanding additional available hardware inputs to the model, and the interplay of these with beam-steadying performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First M87 Event Horizon Telescope Results. IX. Detection of Near-horizon Circular Polarization

Event Horizon Telescope (EHT) observations have revealed a bright ring of emission around the supermassive black hole at the center of the M87 galaxy. EHT images in linear polarization have further identified a coherent spiral pattern around the black hole, produced from ordered magnetic fields threading the emitting plasma. Here we present the first analysis of circular polarization using EHT data, acquired in 2017, which can potentially provide additional insights into the magnetic fields and plasma composition near the black hole. Interferometric closure quantities provide convincing evidence for the presence of circularly polarized emission on event-horizon scales. We produce images of the circular polarization using both traditional and newly developed methods. All methods find a moderate level of resolved circular polarization across the image ( $\langle$| v |$\rangle$ < 3.7%), consistent with the low image-integrated circular polarization fraction measured by the Atacama Large Millimeter/submillimeter Array (| v int |< 1%). Despite this broad agreement, the methods show substantial variation in the morphology of the circularly polarized emission, indicating that our conclusions are strongly dependent on the imaging assumptions because of the limited baseline coverage, uncertain telescope gain calibration, and weakly polarized signal. We include this upper limit in an updated comparison to general relativistic magnetohydrodynamic simulation models. This analysis reinforces the previously reported preference for magnetically arrested accretion flow models. We find that most simulations naturally produce a low level of circular polarization consistent with our upper limit and that Faraday conversion is likely the dominant production mechanism for circular polarization at 230 GHz in M87*.

79 ASTRONOMY AND ASTROPHYSICS↗

Third-integer Resonant Extraction Regulation System for Mu2e

A third-integer resonant slow extraction system is being developed for Fermilab's Delivery Ring to deliver protons to the upcoming Mu2e experiment. The timescale of the extraction (or spill) duration is 43 milliseconds, which is extremely short and unprecedented. Additionally, the experiment's strict and challenging requirements on the quality of the spill at this time scale has led to the development of a new Spill Regulation System (SRS) design. The SRS primarily consists of three components - slow regulation, fast regulation, and harmonic content suppressor. Contributions to the first two components of the SRS, i.e., Slow Regulation and Fast Regulation subsystems, will be presented in which new adaptive learning algorithm schemes for the slow regulation of the spill -- validated using particle tracking simulations -- shall be described. In addition to these novel methods for the enhancement of the spill regulation system, results of employing Machine Learning in enhancing the performance of the resonant extraction are also presented. At the forefront of applying ML techniques to solve non-linear accelerator control problems, this work includes optimizing the PID gains as well as the replacement of the traditional PID controller using Recurrent Neural Networks and Gated Recurrent Unit (GRU) ML models to achieve efficiencies greater than a PID controller. Cutting-edge on-going Reinforcement Learning efforts, including an actor-critic family of learning algorithms, to regulate the spill rate will be reviewed, as well as present analytical calculations pertaining the transit time of particles in a third-integer resonant extraction. Detailed numerical investigations and validations of such calculations, the model of which could be exported and reliably used in future analytical modeling of any resonant extraction, are discussed.

43 PARTICLE ACCELERATORS↗

Collaborative Research: Polymer Macrocycles: A novel topology to control dynamics of rubbery materials

Understanding the dynamics of polymers of different topologies is an important field of study and one of the most important unanswered questions in this field is "how do circular polymers move," particularly in the melt state. New information suggests that molecular topology, specifically circular rings, impacts the response of materials in nanometer- scale confinement. The work performed here tackles these subjects through a collaboration in which specialists in polymer synthesis, polymer rheology and scattering methods, and in the physics of nanoconfinement work together to investigate the thermophysical behavior of circular macromolecules. The project goals are to use a novel synthesis method of "green" oxidative polymerization to produce high purity macrocycles and to investigate their linear viscoelastic behavior in order to fully characterize the dynamics of circular macromolecules to sizes that correspond to linear molecule entanglement densities higher than previously obtainable with synthetic polymers. Chemical chain end characterization and critical edge fractionation coupled with direct visualization of the prepared polymers through the use of polymer amplification methods are proposed in order to quantify the numbers of circular and linear molecules in each sample. The study of the linear viscoelastic response of blends of linear and circular molecules is also to be undertaken in the project. Nonlinear viscoelastic measurements, including extensional viscosity, are to be made. Strong differences in behavior between linear chains and circular ones also provides an important opportunity for new technology to break the "magic triangle" for tires: it is believed that improving one of the three key attributes - traction, wear, rolling resistance - necessarily sacrifices at least one of the others. Rubber made from cyclic polymers has the potential to break out of this triangle by reducing the so-called Payne effect in reinforced rubbers because circular macromolecules are less sensitive to nanoconfinement than their linear counterparts. The work has as one objective to characterize the impact of nanoconfinement on the behavior of large circular macromolecules. In addition, the dynamics of carbon black filled circular macromolecules are to be studied to test the hypothesis that the resulting rubbery materials will exhibit a reduced Payne effect.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗