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At least 739 records · Page 41

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

Singular perturbations and time scales in the design of digital flight control systems

The results are presented of application of the methodology of Singular Perturbations and Time Scales (SPATS) to the control of digital flight systems. A block diagonalization method is described to decouple a full order, two time (slow and fast) scale, discrete control system into reduced order slow and fast subsystems. Basic properties and numerical aspects of the method are discussed. A composite, closed-loop, suboptimal control system is constructed as the sum of the slow and fast optimal feedback controls. The application of this technique to an aircraft model shows close agreement between the exact solutions and the decoupled (or composite) solutions. The main advantage of the method is the considerable reduction in the overall computational requirements for the evaluation of optimal guidance and control laws. The significance of the results is that it can be used for real time, onboard simulation. A brief survey is also presented of digital flight systems.

Naidu, Desineni S.↗

Nonprincipal-plane scattering from flat plates: Second-order and corner diffraction and pattern control of horn antennas

Several high-frequency models for nonprincipal-plane scattering from a rectangular, perfectly conducting plate are examined. Two methods, the Method of Equivalent Currents and corner diffraction coefficients, are considered. Formulations for second-order Physical Theory of Diffraction equivalent currents and for corner diffracted fields are presented. Comparisons are made among plate models. Results away from grazing are accurate using only first-order terms. Near grazing, second-order and corner diffraction terms improve the results for many cases. The pattern control of horn antennas using lossy materials to coat the inner walls of the horn is also investigated. Integral Equation and Moment Method techniques are used to formulate the problem. It is clearly demonstrated that side lobe level reduction can be achieved using impedance surfaces on the inner walls of the horn.

Balanis, Constantine A.↗

Order reduction of z-transfer functions via multipoint Jordan continued-fraction expansion

The order reduction problem of z-transfer functions is solved by using the multipoint Jordan continued-fraction expansion (MJCFE) technique. An efficient algorithm that does not require the use of complex algebra is presented for obtaining an MJCFE from a stable z-transfer function with expansion points selected from the unit circle and/or the positive real axis of the z-plane. The reduced-order models are exactly the multipoint Pade approximants of the original system and, therefore, they match the (weighted) time-moments of the impulse response and preserve the frequency responses of the system at some characteristic frequencies, such as gain crossover frequency, phase crossover frequency, bandwidth, etc.

Lee, Ying-Chin↗

The Size Distribution of Stardust Injected into the ISM

A multi-component method for the description of the evolution of the grain size distribution in consideration of a size dependent grain drift and growth rate is applied in order to model dust driven winds around cool C-stars. Grain drift introduces several modifications concerning dust growth: on one hand the residence time in the region of efficient growth is reduced, on the other hand the growth efficiency is higher due to an increased collisional rate. For carbon grains the surface density of radical sites is increased, but on the other hand there is a reduction of the sticking efficiency of the growth species for drift velocities larger than a few km/s. It is found that the consideration of drift results in a considerable distortion of the size distribution as compared to the case of zero drift velocity. Generally, there are less, but larger grains if drift is included.

Krueger, D.↗

Structural Basis for Flip-Flop Action of Thiamin-Dependent Enzymes Revealed by Crystal Structure of Human Pyruvate Dehydrogenase

The biologically active derivative of vitamin B1; thiamin pyrophosphate; is used as cofactor by many enzymes that perform a wide range of catalytic functions in the pathways of energy production. In alpha2beta2-heterotetrameric human pyruvate dehydrogenase, the first catalytic component enzyme of human pyruvate dehydrogenase complex, this cofactor is used to cleave the C(sup alpha)-C(=0) bond of pyruvate followed by reductive acetyl transfer to lipoyl-dihydrolipoamide acetyltransferase, the second catalytic component of the complex. The dynamic nonequivalence of two, otherwise chemically equivalent, catalytic sites have puzzled researchers from earlier functional studies of this enzyme. In order to gain insight into the mechanism of action of this enzyme, we determined the crystal structure of the holoform of human pyruvate dehydrogenase at 1.958, resolution. We propose a kinetic model for the flip-flop action of this enzyme through the concerted approx. 2A, shuttle-like motion of the heterodimers. The similarity of thiamin pyrophosphate binding in human pyruvate dehydrogenase and other functionally related enzymes suggests this newly defined mechanism of shuttle-like motion of domains to be common for the family of thiamin pyrophosphate-dependent enzymes.

Ciszak, Ewa↗

Recent Improvements in Semi-Span Testing at the National Transonic Facility (Invited)

Three wind tunnel investigations of a commercial transport, high-lift, semi-span configuration have recently been conducted in the National Transonic Facility at the NASA Langley Research Center. Throughout the course of these investigations multiple improvements have been developed in the facility semi-span test capability. The primary purpose of the investigations was to assess Reynolds number scale effects on a modern commercial transport configuration up to full-scale flight test conditions (Reynolds numbers on the order of 27 million). The tests included longitudinal aerodynamic studies at subsonic takeoff and landing conditions across a range of Reynolds numbers from that available in conventional wind tunnels up to flight conditions. The purpose of this paper is to discuss lessons learned and improvements incorporated into the semi-span testing process. Topics addressed include enhanced thermal stabilization and moisture reduction procedures, assessments and improvements in model sealing techniques, compensation of model reference dimensions due to test temperature, significantly improved semi-span model access capability, and assessments of data repeatability.

Gatlin, Gregory M.↗

Recent Improvements in Semi-Span Testing at the National Transonic Facility (Invited)

Three wind tunnel investigations of a commercial transport, high-lift, semi-span configuration have recently been conducted in the National Transonic Facility at the NASA Langley Research Center. Throughout the course of these investigations multiple improvements have been developed in the facility semi-span test capability. The primary purpose of the investigations was to assess Reynolds number scale effects on a modern commercial transport configuration up to full-scale flight test conditions (Reynolds numbers on the order of 27 million). The tests included longitudinal aerodynamic studies at subsonic takeoff and landing conditions across a range of Reynolds numbers from that available in conventional wind tunnels up to flight conditions. The purpose of this paper is to discuss lessons learned and improvements incorporated into the semi-span testing process. Topics addressed include enhanced thermal stabilization and moisture reduction procedures, assessments and improvements in model sealing techniques, compensation of model reference dimensions due to test temperature, significantly improved semi-span model access capability, and assessments of data repeatability.

Gatlin, G. M.↗

Estimating the Value of Nuclear Integrated Hydrogen Production and the Dependency of Electricity and Hydrogen Markets on Natural Gas

Producing low carbon Hydrogen at a competitive price is one of the challenges to hydrogen being part of the solution to reach net-zero emission targets set by the U.S. DOE by 2050. With projected near-term improvements in technology, hydrogen production via solid oxide electrolysis cell (SOEC) / high-temperature steam electrolysis (HTSE) integrated with existing light water reactor (LWR) Nuclear Power Plants (NPP-HTSE) can produce carbon-free hydrogen competitively. In the near term, a 10-year production tax credit (PTC) found in the Inflation Reduction Act (IRA) has been passed, which will catalyze the development and improvement of hydrogen production technology to be competitive. The “1-1-1” target set by the U.S. DOE is to reduce the cost of carbon-free hydrogen by 80% to $1 per kilogram in 1 decade. Several models are available to analyze the profitability, opportunity, and technical capability of NPP-HTSE systems. In order of complexity from most complex to least complex some of these models include: RAVEN/HERON, process models using Aspen HYSYS and capital expense estimations using Aspen Process Economic Analyzer (APEA) and levelized cost of hydrogen (LCOH) calculation using the H2A model (Hydrogen Analysis Model), and custom spread sheets built by the interested party. Though some of the more advanced existing models provide detailed analysis to complex grid integrated problems, they also can take considerable time to setup and run. These advanced models are well suited to complex grid integrated analysis and the consideration of flexibility and variability of regulated and de-regulated electricity price and advanced estimation of capital and operating expenses and heat and material balances.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Complexation Properties of Self-Defensive Microgel-Modified Antimicrobial Surfaces

The complexation of cationic antimicrobials with polyanionic microgels on a biomaterial surface can render that surface self-defensive against bacteria by killing those bacteria which physically contact the antimicrobial-loaded microgels. This killing has been attributed to the contact-driven transfer of antimicrobial from a microgel to a challenging bacterium, though much remains unknown about this process. Here, in this study, we use a combination of experiments and computational modeling to identify key aspects of the complexation phenomena which influence the self-defensive properties. We synthesize poly(acrylic acid) (PAA) microgels (∼2–5 μm diameter) via membrane emulsification and electrostatically deposit them onto polycaprolactone (PCL) coupons or onto glass to form a discontinuous submonolayer. Subsequent microgel loading with colistin or with Sub5 antimicrobial peptide (AMP) causes microgel deswelling. Under physiological conditions Sub5 remains stably sequestered whereas colistin is quickly released. Coarse-grained molecular dynamics (CGMD) simulations confirm stronger Sub5/PAA complexation. CGMD calculations also indicate that Sub5 forms dimers and higher-order structures, a prediction confirmed experimentally by Small-Angle X-ray Scattering (SAXS). Supramolecular structure entropically enhances the complexation strength because of enhanced counterion release per complexation event, and this finding can help identify other antimicrobials well suited for such a nonelutive yet self-defensive strategy. CGMD simulations also show that Sub5 has a higher complexation strength with the Staphylococcus aureus membrane than it does with PAA, confirming that there is a thermodynamic driving force for antimicrobial transfer. Such self-defensive surfaces significantly reduce S. aureus colonization (over 90% reduction relative to unmodified controls) in an in vitro hematogenous contamination model and remain cyto-compatible as evidenced by mesenchymal stem cell spreading and proliferation.

36 MATERIALS SCIENCE↗

Mechanistic Insights for Plasma-Catalytic CO 2 Reduction over TiO 2 in a Dielectric Barrier Discharge Reactor

Reaction kinetics experiments coupled with phenomenological kinetic modeling and parameter estimation are used to elicit insights into the mechanism and active sites for the plasma-catalytic dissociation of CO 2 on TiO 2 . Experimental and model insights showed that gas-phase reactions contribute at least two-thirds of the overall product formation at explored conditions; weak temperature dependence, strong sensitivity to specific energy input (SEI), apparent first order in CO 2 , and positive influence of cofed argon (Ar) and oxygen (O 2 ) for the gas-phase contributions all suggest that expected plasma reaction steps such as electron-impact and high-energy collisions are the dominant modes for CO 2 dissociation. The Arrhenius-like expression for gas contributions resulted in a preexponential of 4.40 × 10 –3 s –1 , an E SEI,g of 7.90 × 10 –4 mol/kJ, and an E a,g of 1.00 × 10 –3 J/mol. For surface contributions, the small apparent barrier of 16.3 kJ/mol, relatively weaker dependence on SEI, first-order dependence on CO 2 , and insensitivity to cofed Ar and O 2 all point to CO 2 dissociation on TiO 2 surface facets without vacancies and aided by plasma (leading to vibrationally excited CO 2 and/or a reactive surface with significant surface charge accumulation). The Arrhenius-like expression resulted in a preexponential of 7.81 × 10 –2 s –1 , an E SEI,s of 1.90 × 10 –3 mol/kJ, and an E a,s of 1.63 × 10 4 J/mol. The derived kinetic model further enabled a systematic evaluation of the effect of inputs (plasma power, flow rate, CO 2 inlet concentration, and temperature) to identify process trends and optimal operating conditions.

catalyst↗

Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations

This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discussed in detail and methods for their solution are proposed. New results on the calculation of state sensitivity functions via reduced order models are given. Several methods for speeding convergence and reducing computation time are also discussed.

Gupta, N. K.↗

Fractionalized excitations probed by ultrasound

In this work, we study magnetoelastic interactions by means of ultrasound experiments in 𝛼−RuCl 3 —a prototypical material for the Kitaev spin model on the honeycomb lattice, with a possible spin-liquid state featuring Majorana fermions and ℤ 2 -flux excitations. We present results of the temperature and in-plane magnetic-field dependence of the sound velocity and sound attenuation for several longitudinal and transverse phonon modes propagating along high-symmetry crystallographic directions. A comprehensive data analysis above the magnetically ordered state provides strong evidence of phonon scattering by Majorana fermions. This scattering depends sensitively on the value of the phonon velocities relative to the characteristic velocity of the low-energy fermionic excitations describing the spin dynamics of the underlying Kitaev magnet. Moreover, our data displays a distinct reduction of anisotropy of the sound attenuation, consistent with the presence of thermally excited ℤ 2 visons. Here, we demonstrate the potential of phonon dynamics as a promising probe for uncovering fractionalized excitations in 𝛼−RuCl 3 and provide new insights into the 𝐻−𝑇 phase diagram of this material.

Kitaev magnet↗

Fuel Properties of Oxymethylene Ethers with Terminating Groups from Methyl to Butyl

Oxymethylene ethers (OMEs) have been studied as possible additives or replacements for diesel fuels. Typically, studies have considered only methyl-terminated OMEs. Recent structure-property relationship models suggest that extended-alkyl OMEs may provide improvements to many of the properties of methyl-terminated OMEs that make them less suitable as diesel fuel blendstocks. In this work, we describe the synthesis and characterization of 16 different OMEs with methyl, ethyl, propyl, butyl, isopropyl, and isobutyl terminating alkyl groups with varying oxymethylene chain length. Indicated Cetane Number, Lower Heating Value, Flash Point, Density, Viscosity, Vapor Pressure, and Oxidative Stability are tested via ASTM standard methods. Additionally, Water Solubility, Boiling Point, seal material compatibility, and sooting propensity (via the Yield Sooting Index) are measured for these fuels. For diesel compatibility, all tested OMEs except smaller methyl and ethyl OMEs, and the branched isopropyl OME, meet cetane number requirements. Further, extending the alkyl end group increases the heating value, but all OMEs, due to their oxygen content, have heating values less than diesel; despite this, all OMEs show significant reductions in soot production per unit heating value. Only the heaviest OMEs meet diesel viscosity requirements, and most are higher density than diesel. OMEs with larger alkyl groups show the highest stability under accelerated auto-oxidation conditions. Increases in alkyl group length cause order of magnitude reduction in water solubility, from hundreds of g/L for methyl terminated OMEs to hundreds of mg/L for butyl terminated OMEs. Limited seal material testing indicates that PEEK polymers are unaffected by OMEs; while extended alkyl groups may improve compatibility with FKM (Viton), other common elastomers (NBR, silicone) remain incompatible with all tested OMEs. Overall, it is found that methyl-terminated OMEs exhibit the most potential for soot reduction, but OMEs with larger propyl and butyl terminating alkyl groups show improved compatibility with existing diesel systems.

09 BIOMASS FUELS↗

Uncertainty analysis for techno-economic and life-cycle assessment of wet waste hydrothermal liquefaction with centralized upgrading to produce fuel blendstocks

Wet waste hydrothermal liquefaction is a promising technology for producing transportation fuels with much lower greenhouse gases emissions than petroleum-based fuels. However, its techno-economic and life cycle assessment are primarily based on laboratory scale testing data, subject to considerable uncertainties, and even bias, due to knowledge gaps. Here, a preliminary uncertainty analysis of key economic measures was conducted based on the 2019 state-of-technology model for biocrude production. Building on the preliminary analysis, this work presents a comprehensive uncertainty analysis in both economic and environmental measures of the entire supply chain of wet waste hydrothermal liquefaction to fuel blendstocks including biocrude upgrading based on the 2021 state-of-technology model. The analysis includes the most recent developments in hydrothermal liquefaction and biocrude upgrading technologies and Monte Carlo simulation based on an integrated model system including an improved reactor yield model, reduced-order process model, discounted cash flow economic model and simplified life-cycle assessment model. The estimated biocrude yield ranges from 42.2% to 52.4% with a median of 47.3%. The estimated fuel yield ranges from 34.7% to 42.7% with a median of 38.7%. The estimated minimum fuel selling price ranges from $\$ $2.28/gge to $\$ $3.45/gge with a median of $\$ $2.80/gge. Relative to petroleum-derived diesel, the estimated reduction in supply chain greenhouse gas emissions ranges from 73.4% to 81.8% with a median of 77.7%. Compared to the 2019 state-of-technology analysis, a significant improvement in biocrude selectivity and economic measures and reduction in uncertainties were achieved due to the incorporation of additional continuous experimental data sets, technology development and de-risking, and improvement in model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Hydromechanical Modeling of Induced Seismicity From CO 2 Injection in the Illinois Basin

Injection of CO 2 for geologic carbon sequestration into deep sedimentary formations involves fluid pressure increases that engage hydromechanical processes that can cause seismicity by activation of existing faults. In this work, we use a coupled multiphase fluid flow and geomechanical simulator to model spatiotemporal fluid pressure and stress changes in order to study the poroelastic effect of CO 2 injection on faults in crystalline basement rock below the injection zone. The seismicity rate along features interpreted to be basement faults is modeled using Dieterich's rate-and-state earthquake nucleation model. The methodology is applied to microseismicity detected during CO 2 injection into the Mount Simon formation during the Illinois Basin—Decatur Project. The modeling accurately captures an observed reduction in seismicity rate when the injection in the second well was into a slightly shallower zone above the base of the Mount Simon formation. Moreover, the modeling shows that it is important to consider poroelastic stress changes, in addition to fluid pressure changes for accurately modeling of the observed seismicity rate.

58 GEOSCIENCES↗

Wake Effects in Lower Carbon Future Scenarios

In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.

17 WIND ENERGY↗

Topology-Dependent Performance of Free-Space Photonic Quantum Networks Under Noise

Photonic quantum communication enables secure and high-fidelity information transfer beyond classical limits, with direct relevance to emerging quantum networks operating in free-space environments. While physical-layer models of depolarizing noise, Gamma–Gamma turbulence statistics, entanglement swapping, and decoy-state QKD security bounds are individually well established, prior work typically treats these components in isolation or under fixed network assumptions. In this work, we develop a unified topology-aware analytical framework that simultaneously integrates free-space optical link budgets, turbulence-induced visibility degradation, depolarizing qubit noise, multi-hop entanglement cascade dynamics, teleportation fidelity thresholds, CHSH nonlocality certification, and asymptotic decoy-state secret key rate bounds across star, mesh, and ring graph structures. Rather than introducing new physical channel models, we demonstrate that identical physical links exhibit fundamentally different end-to-end performance once embedded within different network topologies. Mesh architectures minimize visibility cascade through hop-count reduction but incur quadratic hardware scaling. Star topologies minimize link count but concentrate noise and synchronization overhead at the hub. Ring configurations offer linear hardware scaling with multiplicative fidelity degradation. The results establish topology as a first-order design parameter in near-term free-space quantum networks operating without full quantum repeater infrastructures. While motivated by distributed multi-agent architectures, the framework applies broadly to terrestrial, airborne, and satellite-assisted photonic quantum communication systems.

QKD↗