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At least 595 records · Page 33

Ab initio description of the Bi 2 Sr 2 CaCu 2 O 8+δ electronic structure

Bi-based cuprate superconductors are important materials for both fundamental research and applications. As in other cuprates, the superconducting phase in the Bi compounds lies close to an antiferromagnetic phase. Here, our density functional theory calculations based on the strongly-constrained-and-appropriately-normed exchange correlation functional in Bi 2 Sr 2 CaCu 2 O 8+δ reveal the persistence of magnetic moments on the copper ions for oxygen concentrations ranging from the pristine phase to the optimally hole-doped compound. We also find the existence of ferrimagnetic solutions in the heavily doped compounds, which are expected to suppress superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Morphological Modulation of TiO 2 Nanotube via Optimal Anodization Condition for Solar Water Oxidation

With the depletion of fossil fuels and the rising global demand for energy, photoelectrochemical (PEC) water splitting presents a promising solution to avert an energy crisis. Titanium dioxide (TiO 2 ), an n -type semiconductor, has gained popularity as a photoanode due to its remarkable PEC properties. Nevertheless, inherent challenges such as a wide band gap (~3.2 eV), charge recombination, and slow oxygen evolution reaction (OER) rates at the surface limit its practical application by constraining light absorption. To overcome these limitations, we have developed TiO 2 nanotubes (NTs) using a facile anodization method. This study examines the impact of anodization growth parameters on solar water oxidation performance. Specifically, TiO 2 NTs with modified anodization time (referred to as TiO 2 -6) showed a 3.5-fold increase in photocurrent density compared to the as-grown TiO 2 NTs. Furthermore, electrochemical analyses, such as electrochemical impedance spectroscopy (EIS), indicated a significant decrease in charge transfer resistance following the adjustment of on-off anodization time. Additionally, the TiO 2 -6 photoanode demonstrated a higher electrochemically active surface area (ECSA) than other samples. Therefore, optimal nanostructuring parameters are crucial for enhancing the PEC properties of TiO 2 NTs. Overall, our findings offer valuable insights for fabricating high-quality TiO 2 NTs photoanodes, contributing to developing efficient PEC systems for sustainable energy production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application Deconfliction Characterization and Alternatives Analysis

This report provides an overview of the domain space and solution techniques that could be used to create a robust, flexible app deconfliction service. Three approaches are reviewed with summaries of the characteristics, elements, and results from preliminary demonstrations of solution techniques based on each approach: 1) rules and heuristics, 2) cooperation, and 3) optimization. The strengths and weaknesses of each solution technique were explored through a set of numerical demonstrations on modified IEEE 123 node and 9500 node test feeders. An alternatives analysis of individual deconfliction elements was performed with each solution technique element evaluated against criteria reflecting the dynamic app environment, need to balance app objectives, and scalability issues versus the number of applications, setpoints, and distributed control areas. It is anticipated that a combined solution for a GridAPPS-D Deconfliction Service can be formulated using a combination of elements from each solution technique. The combined solution would combine 1) device control budgets to reduce the size of the solution space by constraining system setpoints to those will not result in accelerated degradation of physical assets, 2) system operations rules to constrain the solution space by eliminating setpoints that result in violations of system limits or operational best practices, 3) contextual status signals shared with or among apps such that they could update their desired setpoints based on the evolving context, 4) a mediator that incentivizes apps to come to a cooperative solution, and 5) Setpoint-informed optimization as a fallback mechanism if a cooperative solution cannot be agreed upon by applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Robust trajectory-constrained frequency control for microgrids considering model linearization error

Grid supportive modes integrated within inverter-based resources can improve the frequency response of renewable-rich microgrids. The synthesis of grid supportive modes to guarantee frequency trajectory constraints under a predefined disturbance set is challenging but essential. To tackle this challenge, a numerical optimal control (NOC)-based control synthesis methodology is proposed. Without loss of generality, a wind-diesel fed microgrid is studied, where we aim to design grid supportive functions in the wind turbine. In the control design, linearized models are used, and the linearization-induced errors are quantitatively analyzed by reachability and interval arithmetics and represented in the form of interval uncertainties. Then, the NOC problem can be formulated into a robust mixed-integer linear program. The control structure is strategically configured into two levels to realize online deployment. The proposed control is verified on the modified 33-node microgrid with a full-order three-phase nonlinear model in Simulink. In conclusion, the simulation results show the effectiveness of the proposed control paradigm and the necessity of considering linearization-induced uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Empirical Validation of a Constrained Bin Packing Algorithm for a Home Energy Management System

The increasing number of intelligent electrical appliances and home energy management systems provide a big opportunity for demand response services from residential and small commercial buildings to the grid. Simultaneously, direct control of individual devices by utilities can cause communication bottlenecks, as well as coordination and privacy concerns. These challenges can be addressed by combining the constituent devices into a single house battery equivalent for the purposes of demand response, using Minkowski sum and a 2d bin packing problem. However, the well-studied traditional problems have not been tested in a real house, as implementation carries significant challenges of its own. We deploy the packing problem on residential devices in a controllable house. We report the barriers we found, such as charge forecast and scalability of the algorithm, and discuss our solutions. The study serves as an intermediate step between existing theoretical research and possible future steps, such as prototype deployments of systems that provide residential demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Iterative Reconstruction for Multimodal Neutron Tomography

Here, we describe a unified framework for model-based iterative 3-D reconstruction of multimodal neutron transmission, hydrogen-scatter, and induced-fission images from low resolution data recorded using 14.1-MeV neutrons and the associated-particle imaging (API) technique. The framework, which was developed to facilitate use in challenging field-deployment scenarios, is centered around physics-based system models and a total variation (TV) constrained implementation of the simultaneous iterative reconstruction technique (SIRT). Modified to solve a statistically weighted least squares (WLS) problem, the SIRT algorithm is accelerated using ordered subsets and Nesterov’s momentum for which we derive a near-optimal value of the governing Lipschitz constant. The approach enables the reconstruction of images that are high resolution compared to the acquired data and is robust to both limited statistics and a limited number of projection angles. Moreover, the framework is fast enough to be practical. Example images are provided that demonstrate both the ability to perform fast-neutron imaging of high-atomic-number materials with low radiation dose and the benefit of multimodal neutron imaging to identify key materials.

Hydrogen scatter↗

Bound Constrained Partial DifferentialEquation Inverse Problem Solution by theSemi-Smooth Newton Method

We present the mathematical derivation, software implementation details, and computational results for a semi-smooth Newton method applied to two inverse problems governed by partial differential equations with bound constraints. The two problems share mathematical structural similarities to density-based topology optimization problems. The semi-smooth Newton method provides a mesh independent solution computation for the two test problems. A key step is that the complementarity part of the necessary optimality conditions are reformulated with the use of a complementarity functionφsuch that the complementarity conditions are satisfied if and only if a zero of a nonsmooth function has been obtained. The modular finite element package MFEM is utilized for the software implementation. In addition we constructed a matrix-free Operator to enable the use of efficient Krylov subspace IterativeSolver of MFEM for the solution of our two target problems.

97 MATHEMATICS AND COMPUTING↗

Control of High-Temperature Static and Transient Thermomechanical Behavior of SiMo Ductile Iron by Al Alloying

Abstract Silicon and molybdenum ( SiMo ) ductile iron is commonly used for exhaust manifolds because these components experience thermal cycling in oxidizing environment, which requires resistance to fatigue during transient thermomechanical loads. Previous studies have demonstrated that alloying elements, such as Al , to SiMo ductile iron reduces the amount of surface degradation during static high-temperature exposure. However, deterioration of sphericity of the graphite nodules and a decrease in ductility could affect the tendency of cracking during thermal cycling. In this article, the effect of Al alloying on static and transient thermomechanical behavior of SiMo ductile iron was investigated to optimize the amount of Al alloying. A thermodynamic approach was used to confirm the effect of the Al alloying on the phase transformations in two SiMo cast irons, alloyed by 1.8% Al and 3% Al . These two alloys were cast in a laboratory along with the baseline SiMo ductile iron. Several experimental methods were used to evaluate the dimensional stability, physical properties, static oxidation, and failure resistance during constrained thermal cycling testing to compare their high-temperature capability. Experimental results verified that Al alloying increases the temperature range and decreases volume change during eutectoid transformation, which together with enhancement of oxidation protection improved the dimensional stability. Thermocycling tests showed that the number of cycles to failure depends on the amount of Al alloying and the applied high-temperature exposure during each cycle. SEM/EDX, high-resolution TEM and µCT analysis were used to verify the mechanism resulting from the Al alloying protection. It was shown that an optimal level of Al alloying for balancing oxidation and thermal cracking resistance depends on thermomechanical conditions of application.

36 MATERIALS SCIENCE↗

Implications of the search for optical counterparts during the second part of the Advanced LIGO’s and Advanced Virgo’s third observing run: lessons learned for future follow-up observations

ABSTRACT Joint multimessenger observations with gravitational waves and electromagnetic (EM) data offer new insights into the astrophysical studies of compact objects. The third Advanced LIGO and Advanced Virgo observing run began on 2019 April 1; during the 11 months of observation, there have been 14 compact binary systems candidates for which at least one component is potentially a neutron star. Although intensive follow-up campaigns involving tens of ground and space-based observatories searched for counterparts, no EM counterpart has been detected. Following on a previous study of the first six months of the campaign, we present in this paper the next five months of the campaign from 2019 October to 2020 March. We highlight two neutron star–black hole candidates (S191205ah and S200105ae), two binary neutron star candidates (S191213g and S200213t), and a binary merger with a possible neutron star and a ‘MassGap’ component, S200115j. Assuming that the gravitational-wave (GW) candidates are of astrophysical origin and their location was covered by optical telescopes, we derive possible constraints on the matter ejected during the events based on the non-detection of counterparts. We find that the follow-up observations during the second half of the third observing run did not meet the necessary sensitivity to constrain the source properties of the potential GW candidate. Consequently, we suggest that different strategies have to be used to allow a better usage of the available telescope time. We examine different choices for follow-up surveys to optimize sky localization coverage versus observational depth to understand the likelihood of counterpart detection.

79 ASTRONOMY AND ASTROPHYSICS↗

Small Nuclear Reactors for Maritime Ports

Maritime ports are entering a period of sharply rising electricity demand as operations are electrified, shore power adoption grows, and energy-intensive industries expand near ports. This report evaluates the feasibility of small nuclear reactors at U.S. ports, which could offer stable baseload power and reduced dependence on regional grids. The report describes the current state of advanced reactor technologies and other factors important for future deployment such as safety and operations, siting requirements, regulatory environments and policy, and other co-benefit considerations. A structured evaluation across a diverse group of U.S. ports highlights the wide variation in feasibility. Fifteen ports were analyzed through port interviews and data collection to assess the port-specific conditions that most impact advanced reactor deployment. The analysis found that the most feasible ports for deployment have favorable geotechnical stability, supportive regulatory environments, and substantial energy loads in a grid-constrained environment. Additionally, an initial reactor size matching was done for the ports based on their reported energy consumption across different modes of operation. However, further analysis and detailed data will be required in the future to determine the optimal reactor-port matching. The economic viability to adopt this technology will be dictated by competitive cost of nuclear-generated electricity compared to other alternatives. Overall, small nuclear reactors present a promising but highly site-dependent pathway for ports seeking resilient, high-capacity energy solutions that support future energy demands. This report identifies key areas for future research and highlights ports that warrant further evaluation to assess the viability of small nuclear reactor implementation. By establishing these priorities, the analysis provides support for the development of informed strategies for potential advanced nuclear technology deployment. The inclusion of ports in this report does not imply their endorsement of nuclear energy generation, and the authors are grateful for the information, expertise, and perspectives they contributed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling a divertor with mid-leg pumping for high-power H-mode scenarios in DIII-D considering E x B drift flows

Edge-plasma simulations of a baffled, long-legged divertor in DIII-D, performed using the multi-fluid code UEDGE, indicate that the position of the detachment front is constrained to the location of the pump duct along the low-field side (LFS) baffle. Simulations including magnetic and E x B drifts were performed for 12.5 MW deuterium plasmas including intrinsic carbon and seeded neon to assess the optimal location of the LFS divertor pump to create a stable detachment front between the target and the X-point. The radiation front position in the simulations, taken to be indicative of the detachment front, can be controlled between the pump and X-point in the favorable magnetic field direction for H-mode access by moving the pump duct location upstream of the target along the LFS baffle. In the unfavorable magnetic field direction, the radial E θ x B drift flows are directed towards the pumping surface, efficiently removing the injected deuterium gas and limiting the sensitivity of the radiation front location to the gas injection rate. The role of pumping rate and drift direction on the pumping efficiency are also found to affect the divertor plasma conditions and detachment front location in UEDGE simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients

Abstract The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource constrained environments the clinical utility of such data-driven predictive tools may be limited by the cost or unavailability of certain laboratory tests. We leveraged EHR data to develop an ML-based tool for predicting adverse outcomes that optimizes clinical utility under a given cost structure. We further gained insights into the decision-making process of the ML models through an explainable AI tool. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Health System in northwest Ohio and southeastern Michigan. We tested the performance of various ML approaches for predicting either increasing ventilatory support or mortality. We performed post hoc analysis to obtain optimal feature sets under various budget constraints. We demonstrate that it is possible to achieve a significant reduction in cost at the expense of a small reduction in predictive performance. For example, when predicting ventilation, it is possible to achieve a 43% reduction in cost with only a 3% reduction in performance. Similarly, when predicting mortality, it is possible to achieve a 50% reduction in cost with only a 1% reduction in performance. This study presents a quick, accurate, and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

97 MATHEMATICS AND COMPUTING↗

Dark Energy Survey: A 2.1% measurement of the angular baryonic acoustic oscillation scale at redshift z eff = 0.85 from the final dataset

Here, we present the angular diameter distance measurement obtained with the baryonic acoustic oscillation (BAO) feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6 < z <1.2, with an effective redshift at z eff = 0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to D M ⁡(z eff )/r d = 19.51 ± 0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by planck Λ⁢CDM via the BAO shift parameter α =(D M /r d )/(D M /r d ) PLANCK . To achieve this, the BAO shift is measured with three different methods, angular correlation function (ACF), angular power spectrum (APS), and projected correlation function (PCF), obtaining α = 0.952 ± 0.023, 0.962 ± 0.022, and 0.955 ± 0.020, respectively, which we combine to α = 0.957 ± 0.020, including systematic errors. When compared with the Λ⁢CDM model that best fits planck data, this measurement is found to be 4.3% and 2.1⁢σ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at z > 0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position, and it is shown to be robust against analysis choices, data removal, redshift calibrations, and observational systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraining the nuclear gluon PDF with inclusive hadron production data

The nuclear parton distribution functions (nPDFs) of gluons are known to be difficult to determine with fits of deep inelastic scattering (DIS) and Drell-Yan (DY) data alone. Therefore, the nCTEQ15 analysis of nuclear PDFs added inclusive neutral pion production data from RHIC to help in constraining the gluon. In this analysis, we present a new global analysis of nuclear PDFs based on a much larger set of single inclusive light hadron data from RHIC and the LHC. Using our new nCTEQ code (nCTEQ++) with an optimized version of INCNLO we study systematically the limitations of the theory and the impact of the fragmentation function uncertainty.

Duwentäster, Pit↗

Black-Box Neural System Identification and Differentiable Programming to Improve Earth System Model Predictions February

Focal Area(s): Focal Area 2: AI for predictive modeling, including AI-derived model components, and AI-enabled applications including parameter optimization, data assimilation, and uncertainty quantification. Focal Area 1: AI-assisted data assimilation using numerical Earth system models. Science Challenge: Earth system models have structural biases that lead to uncertain predictions, and their complexity and expense makes it difficult constraining the models with data or improved physical understanding.

54 ENVIRONMENTAL SCIENCES↗

Data driven drift correction for complex optical systems

To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam trajectory. Maintaining the optimal trajectory over several hours of an experiment with the needed precision necessitates active drift control. Here, we outline time varying Bayesian optimization (TVBO) as a data driven approach for robust drift correction, and illustrate its application for a split and delay optical system composed of six crystals and twelve input dimensions. Using numerical simulations, we exhibit the application of TVBO for linear drift, non-smooth temporal drift as well as constrained TVBO for multi-objective control settings, representing real-life operating conditions. This approach can be easily adapted to other X-ray beam conditioning and guidance systems, including multi-crystal monochromators and grazing-incidence mirrors, to maintain sub-micrometer and nanoradian beam stability over the course of an experiment spanning several hours.

Bayesian optimization↗

Decomposable Formulation of Transmission Constraints for Decentralized Power Systems Optimization

One of the most complicating factors in decentralized solution methods for a broad range of power system optimization problems is the modeling of power flow equations. Existing formulations for direct current power flows either have limited scalability or are very dense and unstructured, making them unsuitable for large-scale decentralized studies. Here, in this work, we present a novel sparsified variant of the injection shift factors formulation, which has a decomposable block-diagonal structure and scales well for large systems. We also propose a decentralized solution method, based on the alternating direction multiplier method, that efficiently handles transmission line outages in N-1 security requirements. Benchmarks on multizonal security-constrained unit commitment problems show that the proposed formulation and algorithm can reliably and efficiently solve interconnection-level test systems with up to 6,515 buses with no convergence or numerical issues.

Alternating-method of multipliers (ADMM)↗

Validation of Jezebel Reactivity Coefficients and Sensitivity Analysis

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor ($k_{eff}$). $K_{eff}$ is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while $k_{eff}$ is the most documented parameter and its uncertainties and sensitivities have been evaluated in great detail, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific isotope nuclear data by optimally designing experiments that are, or are not sensitive to a suite of measurement parameters beyond $k_{eff}$. By identifying parameters that are sensitive to each other, oppositely sensitive, or have substantial magnitude differences in sensitivity, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes the sensitivity of reactivity coefficients. Reactivity coefficients compare reactivity, which is related to $k_{eff}$ at two different states therefore being sensitive to small changes in the system. The most common type of reactivity coefficient measurements is comparison to void for a small sample within the assembly. It is key that the sample sizes are small enough to not affect the flux of the full system. Reactivity coefficients were evaluated for many early experiments to better understand transport corrected cross sections. In fact, ICSBEP includes reactivity coefficient results as “Supplemental Measurements” in appendices for a handful of older benchmarks. One of those benchmarks is Jezebel, the bare Pu critical assembly. This paper compares new simulations of reactivity coefficients for Jezebel, and explores the sensitivity of reactivity coefficients to small changes in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗