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At least 1,009 records · Page 56

Experimental and analytical investigation of dynamic characteristics of extension-twist-coupled composite tubular spars

The results from a study aimed at improving the dynamic and aerodynamic characteristics of composite rotor blades through the use of extension-twist coupling are presented. A set of extension-twist-coupled composite spars was manufactured with four plies of graphite-epoxy cloth prepreg. These spars were noncircular in cross-section design and were therefore subject to warping deformations. Three different cross-sectional geometries were developed: D-shape, square, and flattened ellipse. Three spars of each type were fabricated to assess the degree of repeatability in the manufacturing process of extension-twist-coupled structures. Results from free-free vibration tests of the spars were compared with results from normal modes and frequency analyses of companion shell-finite-element models. Five global modes were identified within the frequency range from 0 to 2000 Hz for each spar. The experimental results for only one D-shape spar could be determined, however, and agreed within 13.8 percent of the analytical results. Frequencies corresponding to the five global modes for the three square spars agreed within 9.5, 11.6, and 8.5 percent of the respective analytical results and for the three elliptical spars agreed within 4.9, 7.7, and 9.6 percent of the respective analytical results.

Lake, Renee C.↗

Optical leakage mitigation in ortho-mode transducer detectors for microwave applications

Ortho-mode transducers (OMT) are a commonly used method of coupling opti-cal signals between waveguides and on-chip circuitry and detectors. While the ideal OMT-waveguide coupling requires minimal disturbance to the waveguide, when used for mm-wave applications the waveguide is often slide though and the OMT probes inserted on a thin support membrane. This interface is a potential source of signal leakage and can lead to signal loss and experimental systematics (e.g. in CMB polarization experiments where lost signal can result in temperature to polarization leakage). Here we report on the development of new OMT- waveguide coupling structures with the goal of reducing leakage at the horn-to-detector-wafer interface. The pixel to pixel optical leakage due to the gap be-tween the coupling waveguide and the backshort is reduced by means of a protrusion that passes through the OMT membrane and connects the waveguide sections on each side of the wafer. High frequency electromagnetic simulations indicate that these protrusions can reduce optical leakage in the gap by ~80% percent, with a ~60% filling factor, respect to an ordinary OMT coupling without protrusion, using designs that are compatible with current fabrication processes. We describe the design of the new coupling structure including the impact of varying two key parameters: wafer to optical coupling gap and protrusion fill factor. Prototype devices have been designed that will characterize the performance of the new design using a relative measurement with varying filling factors. We describe the simulation setup and results, and present a chip layout and sample box designed to perform an initial measurement.

Detectors↗

Mesospheric H2O Concentrations Retrieved from SABER/TIMED Measurements

The SABER instrument on board the TIMED Satellite is a limb scanning infrared radiometer designed to measure temperature and minor constituent vertical profiles and energetics parameters in the mesosphere and lower thermosphere (MLT). The H2O concentrations are retrieved from 6.3 micron band radiances. The populations of H2O(v2) vibrational levels are in non-Local Thermodynamic Equilibrium (non-LTE) above approximately 55 km altitude and the interpretation of 6.3 micron radiance requires utilizing non-LTE H2O model that includes various energy exchange processes in the system of H2O vibrational levels coupled with O2, N2, and CO2 vibrational levels. We incorporated these processes including kinetics of O2/O3 photolysis products to our research non-LTE H2O model and applied it for the development and optimization of SABER operational model. The latter has been validated using simultaneous SCISAT1/ACE occultation measurements. This helped us to estimate CO2(020)-O2(X,v=I), O2(X,v=I)- H2O(010), and O2(X,v=1) O rates at mesopause temperatures that is critical for an adequate interpretation of non-LTE H2O radiances in the MLT. The first distributions of seasonal and meridional H2O concentrations retrieved from SABER 6.3 micron radiances applying an updated non-LTE H2O model are demonstrated and discussed.

Feofilov, A. G.↗

Framework-Topology-Controlled Singlet Fission in Metal–Organic Frameworks

Singlet fission (SF) has been explored as a viable route to improve photovoltaic performance by producing more excitons. Efficient SF is achieved through a high degree of interchromophoric coupling that facilitates electron super exchange to generate triplet pairs. However, strongly coupled chromophores often form excimers that can serve as an SF intermediate or a low-energy trap site. The succeeding decoherence process, however, requires an optimum electronic coupling to facilitate the isolation of triplet production from the initially prepared correlated triplet pair. Conformational flexibility and dielectric modulation can provide a means to tune the SF mechanism and efficiency by modulating the interchromophoric electronic interaction. Such a strategy cannot be easily adopted in densely stacked traditional organic solids. Here, we show that the assembly of the SF-active chromophores around well-defined pores of solution-stable metal-organic frameworks (MOFs) can be a great platform for a modular SF process. A series of three new MOFs, built out from 9,10-bis(ethynylenephenyl)anthracene-derived struts, show a topology-defined packing density and conformational flexibility of the anthracene core to dictate the SF mechanism. Various steady-state and transient spectroscopic data suggest that the initially prepared singlet population can prefer either an excimer-mediated SF or a direct SF (both through a virtual charge-transfer (CT) state). Finally, these solution-stable frameworks offer the tunability of the dielectric environment to facilitate the SF process by stabilizing the CT state. Given that MOFs are a great platform for various photophysical and photochemical developments, generating a large population of long-lived triplets can expand their utilities in various photon energy conversion schemes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical behavior of SnCl 2 and influence of Cu and Ni ions in molten LiCl−KCl−CaCl 2 eutectic

Reliable transport and thermodynamic data for multivalent ions in complex molten salts are scarce, limiting model fidelity for electrorefining and impurity control. Here, we report a comprehensive electrochemical characterization of SnCl₂ in LiCl–KCl–CaCl₂ (50.5–44.2–5.3 mol%) at 685 K, including the effects of Ni 2+ and Cu + impurities. Using cyclic voltammetry (CV), chronoamperometry (CA), and chronopotentiometry (CP), we quantified Sn 2+ and Ni 2+ diffusion with exceptional agreement across methods: Sn 2+ averaged (1.03 ± 0.10) × 10 −5 cm 2 s −1 , and Ni 2+ averaged (0.75 ± 0.19) × 10 −5 cm 2 s −1 . The tight confidence-interval overlap across CV, CA, and CP strengthens confidence in these values and is uncommon in molten chloride studies. Open-circuit-potential measurements provided standard apparent reduction potentials that closely match LiCl–KCl literature, indicating minimal shift with CaCl₂ present. The Sn 2+ /Sn couple behaves as a reversible two-electron soluble–insoluble process at 685 K; the Sn 4+ /Sn 2+ couple transitions to soluble–soluble behavior near 788 K, which may correlate with the decomposition of surface bound chlorostannates, though direct characterization remains to be established. In mixed systems, Cu+/Cu overlaps Sn 2+ /Sn, limiting Cusingle bondSn electroseparation, whereas the larger potential gap between Ni 2+ /Ni and Sn 2+ /Sn supports selective Ni removal. These internally consistent transport and thermodynamic data establish a validated basis for process modeling and optimization of Sn electrorefining and impurity management in LiCl–KCl–CaCl₂.

Berzins-Delahay↗

A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

36 MATERIALS SCIENCE↗

Comparative evaluation and selection of heat exchangers using multicriteria decision-making

Here, this study presents a well-structured method for comparing and selecting Heat Exchanger (HE) technologies for Integrated Energy Systems (IES). The decision to select a HE for a particular IES configuration can vary greatly depending not only on engineering requirements but also on customer’s specific demand. In other words, the HE selection for IES requires a multicriteria decision-making approach, taking into account diverse technical, economic, and safety aspects, as well as the relative priorities considered by energy users. This study employs a HE evaluation approach combining multicriteria decision-making techniques widely used in various industries: quality function deployment (QFD) and analytic hierarchy process (AHP) techniques. Of particular interest is the use of the proposed method to select a high-temperature HEs that couples advanced nuclear reactors and industrial processes. To build a practical basis for comparing HEs within the proposed framework, efforts were made to identify the various HEs requirements for IES purposes. In addition, leveraging the insights obtained from the literature review and the market survey of commercial HE suppliers, a knowledge base was built to facilitate the comparison of each requirement across various HE designs. Also, evaluation metrics were identified for HE requirements with robust rational to enhance the quality of decisions made throughout the proposed evaluation process. The evaluation procedure and knowledge base described in this study can provide a useful basis for those interested in screening the appropriate HE designs for various IES scenarios.

Analytic Hierarchy Process (AHP)↗

Quantum State Transfer between Heterogeneous 3D QPUs

We present detailed analyses and microwave simulations of a quantum interconnect architecture that couples two distinct three-dimensional quantum processing units (QPUs): (i) a two-cell superconducting radio-frequency (SRF) cavity coupled to multiple transmon qubits and (ii) a waveguide-based cavity hosting a planar circuit with transmons and resonators. The modules are linked via a low-loss superconducting coaxial cable, which serves as a quantum bus. Finite-element electromagnetic simulations are performed to optimize coupling strengths and mode frequencies for high-fidelity quantum state transfer between cavities. These simulation results provide a comprehensive blueprint for the experimental realization of a flexible quantum interconnect architecture, coupling heterogeneous QPUs.

Yaker, Joey [Fermilab]↗

Integration of Propulsion-Airframe-Aeroacoustic Technologies and Design Concepts for a Quiet Blended-Wing-Body Transport

This paper summarizes the results of studies undertaken to investigate revolutionary propulsion-airframe configurations that have the potential to achieve significant noise reductions over present-day commercial transport aircraft. Using a 300 passenger Blended-Wing-Body (BWB) as a baseline, several alternative low-noise propulsion-airframe-aeroacoustic (PAA) technologies and design concepts were investigated both for their potential to reduce the overall BWB noise levels, and for their impact on the weight, performance, and cost of the vehicle. Two evaluation frameworks were implemented for the assessments. The first was a Multi-Attribute Decision Making (MADM) process that used a Pugh Evaluation Matrix coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This process provided a qualitative evaluation of the PAA technologies and design concepts and ranked them based on how well they satisfied chosen design requirements. From the results of the evaluation, it was observed that almost all of the PAA concepts gave the BWB a noise benefit, but degraded its performance. The second evaluation framework involved both deterministic and probabilistic systems analyses that were performed on a down-selected number of BWB propulsion configurations incorporating the PAA technologies and design concepts. These configurations included embedded engines with Boundary Layer Ingesting Inlets, Distributed Exhaust Nozzles installed on podded engines, a High Aspect Ratio Rectangular Nozzle, Distributed Propulsion, and a fixed and retractable aft airframe extension. The systems analyses focused on the BWB performance impacts of each concept using the mission range as a measure of merit. Noise effects were also investigated when enough information was available for a tractable analysis. Some tentative conclusions were drawn from the results. One was that the Boundary Layer Ingesting Inlets provided improvements to the BWB's mission range, by increasing the propulsive efficiency at cruise, and therefore offered a means to offset performance penalties imposed by some of the advanced PAA configurations. It was also found that the podded Distributed Exhaust Nozzle configuration imposed high penalties on the mission range and the need for substantial synergistic performance enhancements from an advanced integration scheme was identified. The High Aspect Ratio Nozzle showed inconclusive noise results and posed significant integration difficulties. Distributed Propulsion, in general, imposed performance penalties but may offer some promise for noise reduction from jet-to-jet shielding effects. Finally, a retractable aft airframe extension provided excellent noise reduction for a modest decrease in range.

Hill, G. A.↗

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Christa D Peters-lidard↗

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Christa D Peters-lidard↗

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level

Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.

Rajbhandaril, Narayan↗

A Multiscale Approach to Simulate Non‐Isothermal Multiphase Flow in Deformable Porous Materials

Coupled thermal, hydraulic, and mechanical processes in porous materials play important roles in several energy and environmental technologies. The Darcy-Brinkman-Biot (DBB) framework has proven effective in modeling multiphase fluid flow in deformable porous solids across both pore and Darcy scales, including in systems where fractures coexist with a porous matrix. In this study, we extend the DBB framework, originally designed for isothermal conditions, to address non-isothermal problems by incorporating an energy conservation equation. The resulting solver, hybridBiotThermalInterFoam, enables simulations of coupled multiphase fluid flow, heat transfer, and solid deformation in hybrid-scale systems containing both solid-free regions and ductile porous domains. The new solver is validated through comparisons with analytical solutions and, also, against established heat transfer solvers chtMultiRegionFoam and compressibleInterFoam. Further, a series of 2D and 3D case studies, including two-phase heat transfer in solid-free, static, or deformable porous media, highlights the solver's capacity to simulate complex flow dynamics and heat transport in systems involving high mobility ratios, viscous fingering, and fracture propagation. Our results establish the feasibility of incorporating thermal effects in simulations of a wide variety of energy geotechnics and environmental applications, including enhanced hydrocarbon recovery, soil remediation, and enhanced geothermal energy systems.

04 OIL SHALES AND TAR SANDS↗

pH Regulates Ion Dynamics in Carboxylated Mixed Conductors

Coupled ionic and electronic transport underpins processes as diverse as electrochemical energy conversion, biological signaling, and soft adaptive electronics. Yet, how chemical environments such as pH modulate this coupling at the molecular scale remains poorly understood. Here, we show that the protonation state of carboxylated polythiophenes provides precise chemical control over ion dynamics, doping efficiency, solvent uptake, and mechanical response. Using a suite of multimodal operando techniques, supported by simulations, we reveal that pH dictates the balance of cation/anion uptake during electrochemical doping. Mapping across pH uncovers a quasi-nonswelling regime (≈pH 3–3.5) where charge compensation proceeds with minimal volumetric change yet pronounced stiffening. These findings establish molecular acidity as a general strategy to program ionic preference and mechanical stability, offering design principles for pH-responsive mixed conductors and soft electronic materials that couple ionic, electronic, and mechanical functionality.

PH↗

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land-surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snow pack evolution now support a range of drought indicators that better reflect coupled water, energy and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Drought↗

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗