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At least 469 records · Page 26

Lift Equivalence and Cancellation for Airfoil Surge–Pitch–Plunge Oscillations

A NACA 0018 airfoil in freestream velocity is oscillated in longitudinal, transverse, and angle-of-attack directions with respect to the freestream velocity, known as surge, plunge, and pitch. The lift-based equivalence method introduces phase shifts between these three motions to construct in-phase sinusoidal components for maximum lift, waveform construction. Lift cancellation is also determined with the exact negative pitch and plunge motion amplitudes found from the equivalence method to achieve out-of-phase wave destruction. Lift cancellation occurs when a combination of these motions is sought to obtain a constant lift magnitude throughout the oscillation cycle. To achieve both equivalence and cancellation of lift, a prescribed pure pitch amplitude through the Theodorsen theory equates the corresponding equivalent plunge amplitude and pitch–plunge phase shift. These Theodorsen, linear superposition findings of pitch–plunge are leveraged toward the Greenberg theory to determine a closed-form, surge–pitch–plunge solution through the addition of a surge–plunge phase shift and optimal surge amplitude for lift cancellation. The lift cancellation surge–pitch–plunge amplitudes define the equivalence amplitude investigated here and theoretically limit the experiment to combinations of the first lift harmonic of the Greenberg theory. The analytical results are then compared with experimental lift force measurements and dye visualization. Finally, the normalized lift differences due to unsteady wake and boundary-layer behavior are examined to explore the extents of the Greenberg theory for these cases of lift-based equivalence and cancellation.

42 ENGINEERING↗

Whence the Interstellar Magnetic Field Shaping the Heliosphere?

Measurements of starlight polarized by aligned interstellar dust grains are used to probe the relation between the orientation of the ambient interstellar magnetic field (ISMF) and the ISMF traced by the ribbons of energetic neutral atoms discovered by the Interstellar Boundary Explorer spacecraft. We utilize polarization data, many acquired specifically for this study, to trace the configuration of the ISMF within 40 pc. A statistical analysis yields a best-fit ISMF orientation, B magpol , aligned with Galactic coordinates ℓ = 42°, b = 49°. Further analysis shows the ISMF is more orderly for "downfield" stars located over 90° from Bmagpol. The data subset of downfield stars yields an orientation for the nearby ISMF at ecliptic coordinates λ, β ≈ 219° ± 15°, 43° ± 9° (Galactic coordinates l, b ≈ 40°, 56°, ±17°). This best-fit ISMF orientation from polarization data is close to the field direction obtained from ribbon models. This agreement suggests that the ISMF shaping the heliosphere belongs to an extended ordered magnetic field. Extended filamentary structures are found throughout the sky. A previously discovered filament traversing the heliosphere nose region, "Filament A," extends over 300° of the sky, and crosses the upwind direction of interstellar dust flowing into the heliosphere. Filament A overlaps the locations of the Voyager kilohertz emissions, three quasar intraday variables, cosmic microwave background (CMB) components, and the inflow direction of interstellar grains sampled by Ulysses and Galileo. These features are likely located in the upstream outer heliosheath where ISMF drapes over the heliosphere, suggesting Filament A coincides with a dusty magnetized plasma. A filament 55° long is aligned with a possible shock interface between local interstellar clouds. A dark spot in the CMB is seen within 5° of the filament and within 10° of the downfield ISMF direction. Two large magnetic arcs are centered on the directions of the heliotail. The overlap between CMB components and the aligned dust grains forming Filament A indicates the configuration of dust entrained in the ISMF interacting with the heliosphere provides a measurable foreground to the CMB.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploration of a Potential Desirability of Outcome Ranking Endpoint for Complicated Intra-Abdominal Infections Using 9 Registrational Trials for Antibacterial Drugs

Abstract Background Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI). Methods Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator. Results Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator. Conclusions We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease–specific DOOR endpoints.

Immunology↗

Volumetric and shear strain localization throughout triaxial compression experiments on rocks

Deformation localization is a widely observed, but rarely quantified process in the crust. Recent observations suggest that the localization of seismicity and fracture networks can help identify the approach to catastrophic failure. Here, we quantify the localization processes of the volumetric and deviatoric strain components in twelve triaxial compression experiments imaged with X-ray tomography. We capture three-dimensional images of the rock cores during triaxial compressing toward failure, and then calculate the local strain components using digital volume correlation. The divergence and curl of the incremental displacement vector field provide the volumetric and deviatoric components of the strain field. We quantify localization using the proportion of the rock occupied by high magnitudes of the volumetric and deviatoric strains, and the Gini coefficient of these high magnitude strains, which measures the deviation from a uniform process. We find that the vast majority, but not all, of the experiments experience strain localization toward failure. The rocks typically experience their maximum degree of strain localization not immediately preceding failure, but on average at 90% of the failure stress. The volumetric strain tends to localize more than the deviatoric strain. Finally, these observations support using the localization of the volumetric strain, along with the deviatoric strain, to identify the evolution of the precursory phase preceding earthquakes.

58 GEOSCIENCES↗

THERMAL STRUCTURAL AND SHOCK EVENT EVALUATIONS OF THE FUELING PELLET INJECTION SYSTEM FOR ITER

The US is among seven partner nations in a collaborative effort to design, build, and demonstrate fusion’s ability to be a large-scale carbon free energy source. Each country has its own Domestic Agencies (DA) that contribute directly to the ITER project. US ITER, which is a DOE Office of Science project managed by Oak Ridge National Laboratory, is developing world class engineering solutions to the design, construction, and assembly of the burning plasma experiment that can demonstrate the scientific and technological feasibility of fusion. US ITER’s scope includes completing the preliminary and final design, qualifying materials and processes for manufacture and testing, executing manufacturing, and delivering the Fueling Pellet Injection System (FPIS) to the ITER site for assembly. The US-ITER FPIS system is designed to inject cryogenically frozen pellets of deuterium-tritium (D-T) into the plasma. The FPIS has two main functions: 1. Provide a steady supply of deuterium and tritium fuel, 2. Mitigating the impact of edge localized modes on the plasma facing components. The FPIS will have the capability to reside in three port cells within a tritium second barrier containment cask. Each pellet cask contains three flight tubes linking with penetrations on the torus cryopump housing and vacuum vessel (VV): two for the magnetic high field side (HFS) pellet injection and one for the magnetic low field side (LFS) pellet injection. This paper presents results of the thermal-structural analyses of the FPIS flight tube structural components when subjected to various loads such as electromagnetic (EM) loads, nuclear heating, seismic, and operational, and dynamic shock events. The resulting temperatures and stresses under combined conditions have been found to satisfy the design criteria to ensure safe and reliable operation of the FPIS flight tubes within the vacuum vessel.

Martinez, Oscar↗

Effect of the scanning strategy on the formation of residual stresses in additively manufactured Ti-6Al-4V

During the laser-powder bed fusion (L-PBF) process, high laser intensities, short interaction times and highly localized heat input drive large thermal gradients that result in a state of high residual stresses. Generally, the residual stresses that develop during the L-PBF process can compromise the performance of the component. Up to now, the literature has indicated that the magnitude of the residual stresses can be affected by various process parameters. In this study, all process parameters such as laser power and speed are held fixed and the focus is solely on the effect of the laser scan strategy on the three-dimensional residual stress state of L-PBF metallic components. Four Ti-6Al-4V bridge shaped components were built using island and continuous scanning patterns parallel and offset 45° from the sample axes. High-energy X-ray diffraction was used to determine the residual stress field in each of the components. Two of them were re-measured after being partially removed from the build plate. The assumptions implicit in diffraction measurements of stress are reviewed and discussed in depth because the unique microstructure associated with L-PBF Ti-6Al-4V renders the validity of those assumptions uncertain. Specifically, additional data was collected and analyzed to evaluate the relationship between grain scale and macroscopic scale stresses. The observed residual stresses were large, ½ to ¾ of the yield strength, particularly the build direction stresses near the lateral edges of the bridges. Here in this work, the higher stresses were observed in the bridges built via the island scan strategies, chiefly near the edges of the parts.

36 MATERIALS SCIENCE↗

Ultra-High-Speed X-ray Tomography: Bridging the Gaps to See the Unknown

Rapid, time-varying, three-dimensional physics underpin numerous engineering challenges. Often, these physics occur within opaque environments, internal to a component, severely limiting applicable diagnostics. Development of novel diagnostics is necessary to understand and predict transient three-dimensional (3D) phenomena within opaque environments. This report highlights progress in four key areas leading to advancements in high-speed X-ray radiography and tomography. The first area is enabling MHz-rate imaging of energetics at the Advanced Photon Source at Argonne National Laboratory. The second is modeling a high-flux, rotating-anode X-ray source to understand the heat loads on the anode. The third effort was to develop a novel reconstruction algorithm that is validated by ground experimental tomography data and synthetic tomography data. The fourth is the development of a novel approach to two-color X-ray imaging.

42 ENGINEERING↗

Modulation and Modeling of Three-Dimensional Nanowire Assemblies Targeting Gas Sensors with High Response and Reliability

Despite improved sensitivity, simple downsizing of gas-sensing components to randomly arranged nanostructures often faces challenges associated with unpredictable electrical conduction pathways. In the present study, controlled fabrication of three-dimensional (3D) metal oxide nanowire networks is demonstrated that can greatly improve both signal stability and sensor response compared to random nanowire arrays. For example, the highest ever reported H 2 S gas response value, and a 5 times lower relative standard deviation of baseline resistance than that of random nanowires assemblies, are achieved with the ordered 3D nanowire network. Systematic engineering of 3D geometries and their modeling, utilizing equivalent circuit components, provide additional insights into the electrical conduction and gas-sensing response of 3D assemblies, revealing the critical importance of wire-to-wire junction points and their arrangement. Here these findings suggest new design rules for both enhanced performance and reliability of chemical sensors, which may also be extended to other devices based on nanoscale building blocks.

36 MATERIALS SCIENCE↗

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗

Shock tube simulations for the three-layer Richtmyer–Meshkov instability with single-mode and multimode perturbations

While the canonical two-component, single-mode Richtmyer–Meshkov instability (RMI) has been extensively studied, relatively less work has focused on the effects of an additional intermediate-density middle layer. This work investigates such three-material RMI configurations at two Atwood number scenarios using the ARES hydrodynamics code. After validation against previous experimental and computational studies, setups corresponding to recent three-layer shock tube experiments are simulated. Cases with both single-mode and multimode perturbations are studied to quantify mixing across the interface between the materials with highest and intermediate density. In particular, this work is able to comprehensibly examine differences between two- and three-dimensional setups for the single-mode and multimode problems. Observations from previous two-layer investigations still apply in the three-layer setup, but over the time horizons considered, there appears to be insufficient nonlinear mode coupling to create significant differences between two- and three-dimensional simulations following the first passage of a shock. Finally, additional reshock simulations have additional nonlinear growth that does result in expected differences between two- and three-dimensional cases in this three-layer setup, but significant differences do not manifest during the time horizon studied.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hanford Low-Activity Waste Glass Minor Component Concentration Boundary Expansion

This study investigated the effects of increasing concentrations of minor components on simulated Hanford low-activity waste (LAW) glass properties to allow for LAW glass composition envelope expansion. A test matrix of ten glasses was generated by spiking three previously studied simulated Hanford LAW glass compositions with increasing concentrations of minor component mixes up to a total concentration of 2 wt%. In this study, the ten glasses were fabricated, and key properties were measured including crystal formation after canister centerline cooling (CCC), crystallinity as a function of temperature, density, viscosity, electrical conductivity, glass durability using the Vapor Hydration Test (VHT), product consistency using the Product Consistency Test (PCT), and sulfur solubility. The data from these tests are presented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The impact of $γN$ and $γ^∗N$ interactions on our understanding of nucleon excitations

We review recent progress in our understanding of the nucleon excitation spectrum. Thanks to dedicated efforts at facilities such as ELSA, MAMI and Jefferson Lab, several new nucleon resonances have been discovered, and evidence for previously elusive states has been significantly improved. Numerous decay channels have been observed for the first time, and resonance properties are being extracted from these data by several groups through coupled-channel analyses of varying complexity. Electroproduction experiments have provided further insights into the internal structure of light baryon resonances – for example, the long-debated Roper resonance N (1440) is observed as a three-quark state with a significant meson-cloud component. While the non-relativistic quark model remains a valuable tool for organizing the spectrum of nucleon and Δ resonances, a variety of theoretical frameworks have emerged to offer deeper understanding, including phenomenological quark models, holographic QCD, functional methods, effective field theories, and lattice QCD. We examine the interplay between these approaches, highlight their respective strengths and explore how they complement each other in shaping our knowledge of light baryon resonances. We address several open questions in baryon spectroscopy, including the nature of the enigmatic Λ (1405), ongoing searches for exotic states such as hybrid baryons and pentaquarks, and the dichotomy between microscopic descriptions of baryons in terms of quarks and gluons versus effective hadronic descriptions based on meson-baryon dynamics.

Baryon resonances↗

Towards multi-fidelity deep learning of wind turbine wakes

We report engineering wake models that accurately predict wake in a computationally efficient manner are very important for tasks such as layout optimization and control of wind farms. In this paper, we explore an application of deep learning (DL) to learn the wake model from hierarchies of physics-based approaches ranging from analytical models to an approximate form of the Reynolds-averaged Navier-Stokes equations. We first illustrate the application of principal component analysis to obtain a lower-dimensional representation that allows a computationally tractable training and deployment of DL models. Then, the DL model is trained to learn the mapping from input parameter space to the principal components, which are then used to reconstruct the three-dimensional flow field. Additionally, we investigate a composite framework consisting of two neural networks to learn the correlation between low- and high-fidelity data with Gauss and curl models treated as proxies for low- and high-fidelity models, respectively. The prediction from both DL models matches well with the high-fidelity data with a maximum relative percentage error for the kinetic energy flux of <1%. This work opens up possibilities for data-efficient construction of surrogate models for wake prediction that can be used to study the influence of wind speed and yaw angles on wind farm power production.

17 WIND ENERGY↗

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗

Investigating controls on sea ice algal production using E3SMv1.1-BGC

We present the analysis of global sympagic primary production (PP) from 300 years of pre-industrial and historical simulations of the E3SMv1.1-BGC model. The model includes a novel, eight-element sea ice biogeochemical component, MPAS-Seaice zbgc, which is resolved in three spatial dimensions and uses a vertical transport scheme based on internal brine dynamics. Modeled ice algal chlorophyll-a concentrations and column-integrated values are broadly consistent with observations, though chl-a profile fractions indicate that upper ice communities of the Southern Ocean are underestimated. Simulations of polar integrated sea ice PP support the lower bound in published estimates for both polar regions with mean Arctic values of 7.5 and 15.5 TgC/a in the Southern Ocean. However, comparisons of the polar climate state with observations, using a maximal bound for ice algal growth rates, suggest that the Arctic lower bound is a significant underestimation driven by biases in ocean surface nitrate, and that correction of these biases supports as much as 60.7 TgC/a of net Arctic PP. Simulated Southern Ocean sympagic PP is predominantly light-limited, and regional patterns, particularly in the coastal high production band, are found to be negatively correlated with snow thickness.

54 ENVIRONMENTAL SCIENCES↗

Direct evidence from high-field magnetotransport for a dramatic change of quasiparticle character in van der Waals ferromagnet Fe 3−𝑥 ⁢GeTe 2

Magnetometry and magnetoresistance (MR) data taken on the van der Waals ferromagnet Fe 3−𝑥 ⁢GeTe 2 (FGT) reveal three distinct contributions to the MR: a linear negative component, a contribution from closed Fermi-surface orbits, and an enhancement proportional to the square of the applied magnetic field which is linked to a noncoplanar spin arrangement. Contrary to earlier studies on FGT, by accounting for the field dependence of the anomalous Hall effect, we find that the ordinary Hall coefficient decreases markedly below 80 K, indicating a significant change in character of the electrons and holes on the Fermi-surface at this temperature. The resulting altered ground state eventually causes the Hall coefficient to reverse sign at 35 K. Our Hall data support the proposal that Kondo-lattice behavior develops in this 𝑑-electron material below 80 K. Additional evidence comes from the negative linear component of the MR, which arises from electron-magnon scattering with an atypical temperature dependence attributable to the onset of Kondo screening.

36 MATERIALS SCIENCE↗

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗

Expression of V-nitrogenase and Fe-nitrogenase in Methanosarcina acetivorans is controlled by molybdenum, fixed nitrogen, and the expression of Mo-nitrogenase

ABSTRACT All nitrogen-fixing bacteria and archaea (diazotrophs) use molybdenum (Mo) nitrogenase to reduce dinitrogen (N 2 ) to ammonia, with some also containing vanadium (V) and iron-only (Fe) nitrogenases that lack Mo. Among diazotrophs, the regulation and usage of the alternative V-nitrogenase and Fe-nitrogenase in methanogens are largely unknown. Methanosarcina acetivorans contains nif , vnf , and anf gene clusters encoding putative Mo-nitrogenase, V-nitrogenase, and Fe-nitrogenase, respectively. This study investigated nitrogenase expression and growth by M. acetivorans in response to fixed nitrogen, Mo/V availability, and CRISPRi repression of the nif , vnf , and/or anf gene clusters. The availability of Mo and V significantly affected growth of M. acetivorans with N 2 but not with NH 4 Cl. M. acetivorans exhibited the fastest growth rate and highest cell yield during growth with N 2 in medium containing Mo, and the slowest growth in medium lacking Mo and V. qPCR analysis revealed the transcription of the nif operon is only moderately affected by depletion of fixed nitrogen and Mo, whereas vnf and anf transcription increased significantly when fixed nitrogen and Mo were depleted, with removal of Mo being key. Immunoblot analysis revealed Mo-nitrogenase is detected when fixed nitrogen is depleted regardless of Mo availability, while V-nitrogenase and Fe-nitrogenase are detected only in the absence of fixed nitrogen and Mo. CRISPRi repression studies revealed that V-nitrogenase and/or Fe-nitrogenase are required for Mo-independent diazotrophy, and unexpectedly that the expression of Mo-nitrogenase is also required. These results reveal that alternative nitrogenase production in M. acetivorans is tightly controlled and dependent on Mo-nitrogenase expression. IMPORTANCE Methanogens and closely related methanotrophs are the only archaea known or predicted to possess nitrogenase. Methanogens play critical roles in both the global biological nitrogen and carbon cycles. Moreover, methanogens are an ancient microbial lineage and nitrogenase likely originated in methanogens. An understanding of the usage and properties of nitrogenases in methanogens can provide new insight into the evolution of nitrogen fixation and aid in the development nitrogenase-based biotechnology. This study provides the first evidence that a methanogen can produce all three forms of nitrogenases, including simultaneously. The results reveal components of Mo-nitrogenase regulate or are needed to produce V-nitrogenase and Fe-nitrogenase in methanogens, a result not seen in bacteria. Overall, this study provides a foundation to understand the assembly, regulation, and activity of the alternative nitrogenases in methanogens.

Biotechnology & Applied Microbiology↗