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At least 289 records · Page 16

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Failure analysis of aluminum alloy components

Analysis of six service failures in aluminum alloy components which failed in aerospace applications is reported. Identification of fracture surface features from fatigue and overload modes was straightforward, though the specimens were not always in a clean, smear-free condition most suitable for failure analysis. The presence of corrosion products and of chemically attacked or mechanically rubbed areas here hindered precise determination of the cause of crack initiation, which was then indirectly inferred from the scanning electron fractography results. In five failures the crack propagation was by fatigue, though in each case the fatigue crack initiated from a different cause. Some of these causes could be eliminated in future components by better process control. In one failure, the cause was determined to be impact during a crash; the features of impact fracture were distinguished from overload fractures by direct comparisons of the received specimens with laboratory-generated failures.

Johari, O.↗

Variability of near-fault seismic risk to reinforced concrete buildings based on high-resolution physics-based ground motion simulations

Broadband physics-based simulated earthquake ground motions are utilized to characterize the regional-scale seismic risk to modern reinforced concrete (RC) structures. A highly dense dataset of ground motions covering a 100-km urn:x-wiley:00988847:media:eqe3413:eqe3413-math-0001 40-km domain was generated using kinematic fault rupture models with varying rupture characteristics to represent shallow crustal earthquakes and resolved up to frequencies of 5 Hz. Over 40,000 nonlinear response history simulations of short- and mid-rise RC special moment frame buildings were conducted using simulation models that are capable of representing nonlinear behavior and component deterioration effects. The spatial variability of structural risk within a single earthquake scenario and between different rupture scenarios is examined, and the regions of strongest directivity effects and highest structural demands are identified. The structural demands may vary by factor of up to 8.0 at very short distances from the fault, and the large dispersion in the demands decreases significantly beyond a distance of 15 km. The interstory drift and member rotation demands are substantially impacted by important features of the geological structure and the characteristics of the rupture scenarios, particularly the presence of localized high-slip regions. The frequency characteristics of the structures are found to play an important role in determining the effects of near-fault ground motions on the structural response and expected damage. The results of this study suggest that the simulated ground motions, particularly those generated using the hybrid rupture approach, may offer reasonable structural risk estimates for low-frequency structures and conservative estimates for high-frequency structures.

58 GEOSCIENCES↗

Modeling the infrared cascade spectra of small PAHs: the 11.2 μm band

The profile of the 11.2 μm feature of the infrared (IR) cascade emission spectra of polycyclic aromatic hydrocarbon (PAH) molecules is investigated using a vibrational anharmonic method. Several factors are found to affect the profile including: the energy of the initially absorbed ultraviolet (UV) photon, the density of vibrational states, the anharmonic nature of the vibrational modes, the relative intensities of the vibrational modes, the rotational temperature of the molecule, and blending with nearby features. Each of these factors is explored independently and influence either the red or blue wing of the 11.2 μm feature. The majority impact solely the red wing, with the only factor altering the blue wing being the rotational temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nucleus++ : a new tool bridging AME and NUBASE for advancing nuclear data analysis

The newly developed software, Nucleus++ , is an advanced tool for displaying basic nuclear physics properties from NUBASE and integrating comprehensive mass information for each nuclide from Atomic Mass Evaluation. Additionally, it allows users to compare experimental nuclear masses with predictions from different mass models. Building on the success and learning experiences of its predecessor, Nucleus , this enhanced tool introduces improved functionality and compatibility. With its user-friendly interface, Nucleus++ was designed as a valuable tool for scholars and practitioners in the field of nuclear science. Finally, this article offers an in-depth description of Nucleus++ , highlighting its main features and anticipated impacts on nuclear science research.

AME↗

Translation of DNA Damage Response Inhibitors as Chemoradiation Sensitizers From the Laboratory to the Clinic

Combination therapies with agents targeting the DNA damage response (DDR) offer an opportunity to selectively enhance the therapeutic index of chemoradiation or eliminate use of chemotherapy altogether. The successful translation of DDR inhibitors to clinical use requires investigating both their direct actions as (chemo)radiosensitizers and their potential to stimulate tumor immunogenicity. Beginning with high-throughput screening using both viability and DNA damage-reporter assays, followed by validation in gold-standard radiation colony-forming assays and in vitro assessment of mechanistic effects on the DDR, we describe proven strategies and methods leading to the clinical development of DDR inhibitors both with radiation alone and in combination with chemoradiation. Beyond these in vitro studies, we discuss the impact of key features of human xenograft and syngeneic mouse models on the relevance of in vivo tumor efficacy studies, particularly with regard to the immunogenic effects of combined therapy with radiation and DDR inhibitors. Finally, we describe recent technological advances in radiation delivery (using the small animal radiation research platform) that allow for conformal, clinically relevant radiation therapy in mouse models. This overall approach is critical to the successful clinical development and ultimate Food and Drug Administration approval of DDR inhibitors as (chemo)radiation sensitizers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Molecular dynamics studies of grain boundary mobility and anisotropy in BCC γ-uranium

Grain morphologies such as grain size and aspect ratio in uranium-based metallic fuels are important microstructural features that can impact various fuel performance properties such as fission-gas-induced swelling, thermal transport, high burnup structure formation, and radiation resistance. Accurate prediction of the fuel grain morphologies requires knowledge of critical grain growth parameters such as grain boundary (GB) mobility and anisotropy. In this work, molecular dynamics simulations were performed to study the GB mobility and its anisotropy in pure body-centered-cubic (BCC) γ uranium. Nine GBs with different combinations of misorientation angles (20°, 30°, 45°) and rotation axes (<100>, <110>, <111>), as well as an additional <111> 38.2° GB were studied using three interatomic potentials. Here, it is found that the GB mobility anisotropy has complex trends, depending on both rotation axis and misorientation. However, in general the <110> rotation axis has the fastest GB mobility at the same misorientation. The results of this work can be used as not only baselines for future studies of GB mobility in uranium-based alloys such as uranium-molybdenum (U-Mo) fuels, but also input for mesoscale modeling of grain growth in uranium-based alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Mapping strain and structural heterogeneities around bubbles in amorphous ionically conductive Bi 2 O 3

While amorphous materials are often approximated to have a statistically homogeneous atomic structure, they frequently exhibit localized structural heterogeneity that challenges simplified models. This study uses 4D scanning transmission electron microscopy to investigate the strain and structural modifications around gas bubbles in amorphous Bi 2 O 3 induced by argon irradiation. We present a method for determining strain fields surrounding bubbles that can be used to measure the internal pressure of the gas. Compressive strain is observed around the cavities, with higher-order crystalline symmetries emerging near the cavity interfaces, suggesting paracrystalline ordering as a result of bubble coarsening. This ordering, along with a compressive strain gradient, indicates that gas bubbles induce significant localized changes in atomic packing. By analyzing strain fields with maximum compressive strains of 3%, we estimate a lower bound on the internal pressure of the bubbles at 2.5 GPa. These findings provide insight into the complex structural behavior of amorphous materials under stress, particularly in systems with gas inclusions, and offer new methods for probing the local atomic structure in disordered materials. Although considering structural heterogeneity in amorphous systems is non-trivial, these features have crucial impacts on material functionalities, such as mechanical strength, ionic conductivity, and electronic mobility.

36 MATERIALS SCIENCE↗

Modulation of Tropical Convection-Circulation Interaction by Aerosol Indirect Effects in Convective Self-Aggregation Simulations of a Gray Zone Global Model

Disentangling the response of tropical convective updrafts to enhanced aerosol concentrations has been challenging. Leading theories for explaining the influence of aerosol concentrations on tropical convection are based on the dynamical response of convection to changes in cloud microphysics, neglecting possible changes in the environment. In recent years, global convection-permitting models (GCPM) have been developed to circumvent problems arising from imposing artificial scale separation on physical processes associated with deep convection. Here, we use a global model in the convective gray zone that partially simulates deep convection to investigate how enhanced concentrations of aerosols that act as cloud condensate nuclei (CCN) impact tropical convection features by modulating the convection-circulation interaction. Results from a pair of idealized non-rotating radiative-convective equilibrium simulations show that the enhanced CCN concentration leads to weaker large-scale circulation, the closeness of deep convective systems to the moist cluster edges, and more mid-level cloud water at an equilibrium state in which convective self-aggregation occurred. Correspondingly, the enhanced CCN concentration modulates how the physical processes that support or oppose convective aggregation maintain the aggregated state at equilibrium. Overall, the enhanced CCN concentration facilitates the development of deep convection in a drier environment but reduces mean precipitation. Our results emphasize the importance of allowing atmospheric phenomena to evolve continuously across spatial and temporal scales in simulations when investigating the response of tropical convection to changes in cloud microphysics.

54 ENVIRONMENTAL SCIENCES↗

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗

Progress toward hydro-equivalent ignition in OMEGA direct-drive DT-layered implosions

Considerable progress has been made in deuterium-tritium-layered implosion experiments on the OMEGA Laser System, bringing the prospects for thermonuclear ignition in direct-drive configurations with megajoule-class lasers closer to reality. Doing so has required navigating the balance between improved 1D performance and multidimensional stability. Using statistical modeling based on over 350 cryogenic implosions to identify various degradation mechanisms, and combined with multidimensional simulations and experimental techniques such as target offsets to combat residual flows, core conditions have repeatably been achieved that extrapolate to the burning-plasma state when scaled to 2.15 MJ of symmetric laser illumination. Using high implosion velocities (⁠> 450 km/s) and moderately high adiabats (⁠~5⁠), these experiments produced record-high scaled Lawson parameters in direct drive equal to 89 ± 2% of that required for ignition with expected yields of up to 1.5 ± 0.2 MJ. To improve these results still further, focused physics studies are performed to improve physics understanding and identify routes to even greater performance. Recent studies include investigations into the impact of mounting features, laser imprint, reduced fuel temperatures, and greater on-target intensities through subscale experiments. This manuscript gives a summary of the cryogenic direct-drive program on the OMEGA laser, including routes taken to achieve the current best performance, the status of recent focused physics investigations, and future designs—such as target solutions to laser imprint and reducing vapor density to increase convergence—that are expected lead to the demonstration of hydro-equivalent ignition on OMEGA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Impact of Bias Row Noise to Photometric Accuracy: Case Study Based on a Scientific CMOS Detector

Abstract We tested a new model of CMOS detector manufactured by the Gpixel Inc, for potential space astronomical application. In laboratory, we obtain some bias images under the typical application environment. In these bias images, clear random row noise pattern is observed. The row noise also contains some characteristic spatial frequencies. We quantitatively estimated the impact of this feature to photometric measurements, by making simulated images. We compared different bias noise types under strict parameter control. The result shows the row noise will significantly deteriorate the photometric accuracy. It effectively increases the readout noise by a factor of 2–10. However, if it is properly removed, the image quality and photometric accuracy will be significantly improved.

Astronomy & Astrophysics↗

Progress toward favorable landscapes in quantum combinatorial optimization

The performance of variational quantum algorithms relies on the success of using quantum and classical computing resources in tandem. Here, we study how these quantum and classical components interrelate. In particular, we focus on algorithms for solving the combinatorial optimization problem MaxCut, and study how the structure of the classical optimization landscape relates to the quantum circuit used to evaluate the MaxCut objective function. In order to analytically characterize the impact of quantum features on the critical points of the landscape, we consider a family of quantum circuit ansätze composed of mutually commuting elements. We identify multiqubit operations as a key resource and show that overparameterization allows for obtaining favorable landscapes. Namely, we prove that an ansatz from this family containing exponentially many variational parameters yields a landscape free of local optima for generic graphs. However, we further prove that these ansätze do not offer superpolynomial advantages over purely classical MaxCut algorithms. Here, we then present a series of numerical experiments illustrating that noncommutativity and entanglement are important features for improving algorithm performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

"Safety First: Though on the Other Hand, Time is Critical”

This talk describes the deployment of research-quality software and hardware for open-road driving experiments by fleets of vehicles. Technological advancements in single-vehicle autonomy have expanded beyond the academic community, and are driven largely by industry stakeholders and manufacturers. However, as the penetration rate of cars with advanced driver assistance features increases, the impact on emergent behavior in traffic is still unknown. Compelling reasons to experiment within open-road conditions must be considered alongside the technical and human factor safety issues in deploying experimental controllers. This is even more challenging when it is necessary to deploy experimental fleets at scale. The talk will describe approaches for co-design of a research testbed for societal-scale systems. Discussion is devoted to the research-quality data gathering and control layers and their technical implementation, the different interfaces for experts in other fields to use these testbeds for research without violating safety requirements, and process and management considerations when deploying the platforms at scale when considering training time and operation complexity of human operators.

Sprinkle, Jonathan↗

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Zhang, Weiyu [University of Leeds (United Kingdom)↗

Lay out, test verification and in orbit performance of HELIOS a temperature control system

HELIOS temperature control system is described. The main design features and the impact of interactions between experiment, spacecraft system, and temperature control system requirements on the design are discussed. The major limitations of the thermal design regarding a closer sun approach are given and related to test experience and performance data obtained in orbit. Finally the validity of the test results achieved with prototype and flight spacecraft is evaluated by comparison between test data, orbit temperature predictions and flight data.

Brungs, W.↗

A review of several propulsion integration features applicable to supersonic-cruise fighter aircraft

A brief review has been made of the propulsion integration features which may impact the design of a supersonic cruise fighter type aircraft. The data used for this study were obtained from several investigations conducted in the Langley 16-foot transonic and 4 by 4 foot supersonic pressure wind tunnels. Results of this study show: (1) that for conventional nozzle installations, contradictory design guidelines exist between subsonic and supersonic flight condition, (2) that substantial drag penalties can be incurred by use of dry power nozzles during supersonic cruise; and (3) that a new and unique concept, the nonaxisymmetric nozzle, offers the potential for solving many of the current propulsion installation problems.

Berrier, B. L.↗

Io, its atmosphere and optical emissions

The paper outlines current understanding of phenomena associated with Io's atmosphere and optical emissions, along with a review of their relationships. The discussion covers the sodium D-line emission from Io, the ultraviolet emission observed from Pioneer 10, other optical emission lines, and future observational work on Io's line emission. Analysis of Io's ionosphere indicates that the atmosphere may be cooler than the observed sodium and that the exobase probably stands well above Io's surface. Also discussed is Io as a source of hydrogen and as a source of sodium. The observed electron profiles and the constraints provided by the emission cloud are consistent with two models of Io's neutral atmosphere. In the first model, hydrogen is supplied by dissociation of ammonia, whereas proton charge exchange is the primary source of hydrogen in the second model. Both models have the common feature that meteoritic impact or sputtering of the surface provides a source for sodium.

Brown, R. A.↗