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At least 1,171 records · Page 65

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗

Constraining the Low-Temperature Oxidation Mechanism of n -Hexanol through the Detection and Identification of C 6 Elusive Intermediates

Alcohol-based fuels are currently considered to be viable energy carriers for the transportation sector. Consequently, a comprehensive mechanistic understanding of the low-temperature oxidation of alcohols is essential for application in advanced low-temperature compression engines. Here, in this work, a multidimensional approach involving experimental investigations, kinetic modeling, and theoretical calculations was used to provide new insights into the low-temperature oxidation mechanism of a C 6 alcohol, n -hexanol (CH 3 (CH 2 ) 5 OH), through the detection and identification of elusive C 6 intermediates. The oxidation of n-hexanol was investigated in a jet-stirred reactor under stoichiometric conditions (ϕ = 1.0), an initial fuel concentration of 2%, a residence time of 2 s, a temperature range between 500 and 660 K, and a pressure of 700 Torr. The reactants, intermediates, and final products were detected and identified by means of molecular-beam mass spectrometry coupled with single-photon ionization employing tunable synchrotron-generated vacuum ultraviolet radiation. Chemical kinetic simulations were performed using a previously published kinetic model (Togbé et al., Energy Fuels 2010, 11, 5859−5875) to predict the reactivity of n-hexanol and elucidate the predominant formation pathways of the observed low-temperature species. Experimental photoionization efficiency curves in conjunction with ab initio calculations, enabled the identification of important low-temperature species, such as C 6 unsaturated alcohols, C 6 olefinic hydroperoxides, C 6 cyclic ethers, C 6 diones, and C 6 ketohydroperoxides. The results of this study provide valuable insight into the mechanism of the low-temperature oxidation chemistry of n -hexanol, contributing to the development of kinetic models for the low-temperature oxidation of n-hexanol and other long-chain linear alcohols.

alcohols↗

Instrumentation and experimental procedures for robust collection of X-ray diffraction data from protein crystals across physiological temperatures

Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure–function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Furthermore, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that can be directly related to biological function. Given this capability, the next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperature. This challenge is addressed herein. The approach described provides complete diffraction data sets with total collection times as short as ~5 s from single protein crystals, dramatically increasing the quantity of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09–1.54 Å resolution data over a temperature range of 293–363 K for proteinase K, thaumatin and lysozyme crystals at BL14-1 at the Stanford Synchrotron Radiation Lightsource. Here, the analyses presented here indicate that the diffraction data are of high quality and do not suffer from excessive dehydration or radiation damage.

36 MATERIALS SCIENCE↗

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the Organization of Economic Cooperation and Development / Nuclear Energy Agency Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). Previous analyses as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. In this paper, we present a new RELAP5-3D model of HTTF with finer radial nodalization built to assess the impact of radial heat transfer. We describe the new model and compare it against the old one at full-power steady state and for the pressurized conduction cooldown (PCC) transient. These analyses are based on the code-to-code comparison exercise for the PCC problem of the HTGR T/H benchmark. We compare maximum block temperature as the primary figure of merit and include discussion on intracore natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Study of Unsteady Flows with Concave Wall Effect

This paper presents computational fluid dynamic studies of the inlet turbulence and wall curvature effects on the flow steadiness at near wall surface locations in boundary layer flows. The time-stepping RANS numerical solver of the NASA Glenn-HT RANS code and a one-equation turbulence model, with a uniform inlet turbulence modeling level of the order of 10 percent of molecular viscosity, were used to perform the numerical computations. The approach was first calibrated for its predictabilities of friction factor, velocity, and temperature at near surface locations within a transitional boundary layer over concave wall. The approach was then used to predict the velocity and friction factor variations in a boundary layer recovering from concave curvature. As time iteration proceeded in the computations, the computed friction factors converged to their values from existing experiments. The computed friction factors, velocity, and static temperatures at near wall surface locations oscillated periodically in terms of time iteration steps and physical locations along the span-wise direction. At the upstream stations, the relationship among the normal and tangential velocities showed vortices effects on the velocity variations. Coherent vortices effect on the velocity components broke down at downstream stations. The computations also predicted the vortices effects on the velocity variations within a boundary layer flow developed along a concave wall surface with a downstream recovery flat wall surface. It was concluded that the computational approach might have the potential to analyze the flow steadiness in a turbine blade flow.

Wang, Chi R.↗

Heat transfer of phase-change materials in two-dimensional cylindrical coordinates

Two-dimensional phase-change problem is numerically solved in cylindrical coordinates (r and z) by utilizing two Taylor series expansions for the temperature distributions in the neighborhood of the interface location. These two expansions form two polynomials in r and z directions. For the regions sufficiently away from the interface the temperature field equations are numerically solved in the usual way and the results are coupled with the polynomials. The main advantages of this efficient approach include ability to accept arbitrarily time dependent boundary conditions of all types and arbitrarily specified initial temperature distributions. A modified approach using a single Taylor series expansion in two variables is also suggested.

Labdon, M. B.↗

Retrieval of Vegetation Water Content Using Brightness Temperatures from the Soil Moisture Active Passive (SMAP) Mission

In this paper, we explore a time series approach to using the tau-omega (τ-ω) model to retrieve vegetation water content (kg/m2) with minimal use of ancillary data. Analytically, this approach calls for nonlinear optimization in two steps. First, multiple days of co-located brightness temperature observations are used to retrieve the effective vegetation opacity, which incorporates the combined radiometric and polarization effects of surface roughness and vegetation opacity. The resulting effective vegetation opacity is then used to retrieve vegetation water content to within a gain factor α and an offset factor β. By using a climatological vegetation water content ancillary database as the one adopted in the development of the SMAP standard and enhanced soil moisture products, α and β can be determined globally using the annual minimum and annual maximum of vegetation water content. The resulting values of α and β can then be used to reconstruct the retrieved vegetation water content. Formulation, assumptions, and limitations of this approach are presented alongside the preliminary global retrieval of vegetation water content using one year (2016) ofSMAP brightness temperature observations.

radiative transfer↗

Passive optical and infrared meteorology

Applications of passive visible and infrared techniques to the study of meteorological parameters are presented. For the remote sensing of temperature and humidity profiles, infrared sounder improvements have proceeded with the narrow band-pass channels approach, and the partially scanned interferogram approach. Current and planned infrared and microwave sea-surface temperature sounders have an expected accuracy of approximately 2 K, and this can be improved by using three super window channels from the 3.7 micron window region, with narrow band passes away from principal water vapor absorption lines. Cloud data remote sensing is currently performed from satellites, and these visible and infrared images have been used to track weather patterns. In addition, a passive infrared correlation-spectroscopy technique has been proposed for wind measurements. Finally, these techniques have also been applied to monitor such parameters as the Solar Constant, aerosols, and minor gas constituents.

Chahine, M. T.↗

Laser-induced annealing of aged PuO 2

Plutonium dioxide (PuO 2 ) is an important compound used in nuclear fuel, irradiation targets, and heat sources. As such, improved understanding of its structural and spectroscopic properties has numerous applications. Alpha particle-induced damage of a PuO 2 crystal lattice modifies several properties of its Raman spectrum, including band intensities, positions, and widths. The decay also induces growth of new bands and creates electron-trapped defects with luminescent properties. Herein, we show for the first time that laser-induced heating can reverse damage to an aged and damaged PuO 2 lattice. Using automated instrumentation to heat a single 6–10 μm spot to temperatures above 1,300°C, we show that laser-induced annealing of aged PuO 2 results in restoration of T2g band intensity with a concomitant decrease in defect band intensity, a result that indicates laser annealing can be used to reverse age-damage in PuO 2 . This laser annealing approach permitted in situ observation of temperature-dependent Raman spectral changes, thereby providing insight into the thermodynamics of structural alterations in a radiolytically damaged PuO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

36 MATERIALS SCIENCE↗

Caustic Singularities Of High-Gain, Dual-Shaped Reflectors

Report presents study of some sources of error in analysis, by geometric theory of diffraction (GTD), of performance of high-gain, dual-shaped antenna reflector. Study probes into underlying analytic causes of singularity, with view toward devising and testing practical methods to avoid problems caused by singularity. Hybrid physical optics (PO) approach used to study near-field spillover or noise-temperature characteristics of high-gain relector antenna efficiently and accurately. Report illustrates this approach and underlying principles by presenting numerical results, for both offset and symmetrical reflector systems, computed by GTD, PO, and PO/GO methods.

Galindo, Victor↗

Early Career: Mesoscale Fragments of Crystalline Silicon by Chemical Synthesis (Final Technical Report)

Silicon has transformed the modern era, with applications in computing, solar cells, energy storage, and beyond. The traditional approach to making silicon is a high-temperature “top-down” process that affords only the most stable form of silicon, leaving hidden vast swathes of structure-function space. The goal of this program was to establish new approaches to making silicon-based materials from the bottom-up, allowing structural precision from the atomic level up to the bulk, and to understand how structure influences function. Key results included the development of the cyclosilane building blocks and low-temperature methods for their polymerization, as well as new tools for spectroscopic characterization. In addition to revealing new materials chemistry insights, in the five-year period covered by this award, this work resulted in 11 publications and three graduate student theses.

36 MATERIALS SCIENCE↗

Earthworms significantly enhance the temperature sensitivity of soil organic matter decomposition: Insights into future soil carbon budgeting

How and what soil fauna influence the soil organic matter (SOM) decomposition rate (Rs) and its temperature sensitivity (Q 10 ) have been largely ignored, although this is a crucial matter, especially under the scenario of global change. Further, in this study, a novel approach was adopted with a continuous changing-temperature incubation (daytime, from 7 °C to 22 °C; nighttime, from 22 °C to 7 °C) with rapid and continuous measurement, to examine the effect of soil macrofauna (specifically, earthworms) on Rs and Q 10 with three densities (no addition, low density, and high density). According to the results, the earthworms accelerated Rs. Furthermore, Rs with earthworm addition had a symmetrical pattern during daytime and nighttime cycles, which is contrary to traditional soil incubation, with only soil microbe as asymmetrical. More importantly, earthworm addition increased Q 10 markedly, ranging from 48% to 67%. Overall, the findings highlight the pivotal role of earthworms as soil macrofauna that regulating soil carbon release, and their effects should be integrated into process-based ecological models in future.

60 APPLIED LIFE SCIENCES↗

Spectrally accelerated edge and scrape-off layer gyrokinetic turbulence simulations

This paper presents the first gyrokinetic (GK) simulations of edge and scrape-off layer (SOL) turbulence accelerated by a velocity-space spectral approach in the full-f GK code GENE-X. Building upon the original grid velocity-space discretization, we derive and implement a new spectral formulation and verify the numerical implementation using the method of manufactured solution. We conduct a series of spectral turbulence simulations focusing on the TCV-X21 reference case (Oliveira et al., 2022 [26]) and compare these results with previously validated grid simulations (Ulbl et al., 2023 [25]). The spectral approach reproduces the outboard midplane (OMP) profiles (density, temperature, and radial electric field), dominated by trapped electron mode (TEM) turbulence, with excellent agreement and significantly lower velocity-space resolution. As a consequence, the spectral approach reduces the computational cost (CPUh) by at least an order of magnitude, of approximately 50 for the TCV-X21 case. This enables high-fidelity GK simulations to be performed within a few days on modern CPU-based supercomputers for medium-sized devices and establishes GENE-X as a powerful tool for studying edge and SOL turbulence, moving towards reactor-relevant devices like ITER.

Gyrokinetic↗

Isotope effects in supercooled H 2 O and D 2 O and a corresponding-states-like rescaling of the temperature and pressure

Water shows anomalous properties that are enhanced upon supercooling. The unusual behavior is observed in both H 2 O and D 2 O, however, with different temperature dependences for the two isotopes. It is often noted that comparing the properties of the isotopes at two different temperatures (i.e., a temperature shift) approximately accounts for many of the observations—with a temperature shift of 7.2 K in the temperature of maximum density being the most well-known example. However, the physical justification for such a shift is unclear. Motivated by recent work demonstrating a “corresponding-states-like” rescaling for water properties in three classical water models that all exhibit a liquid–liquid transition and critical point, the applicability of this approach for reconciling the differences in the temperature- and pressure-dependent thermodynamic properties of H 2 O and D 2 O is investigated here. Utilizing previously published data and equations-of-state for H 2 O and D 2 O, we show that the available data and models for these isotopes are consistent with such a low temperature correspondence. These observations provide support for the hypothesis that a liquid–liquid critical point, which is predicted to occur at low temperatures and high pressures, is the origin of many of water’s anomalies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Room temperature persisting surface charge carriers driven by intense terahertz electric fields in a topological insulator Bi 2 Se 3

Topologically protected surface current is highly promising for next-generation low-dissipation and disorder-tolerant quantum electronics and computing. Yet, electric transport from the co-existing bulk state dominates the responses of the Dirac surface state, especially at elevated temperatures relevant to technological applications. Here, we present an approach that convincingly showcases the generation, disentanglement, and precise control of enduring surface charge carriers on a topological insulator, Bi 2 Se 3 , with high bulk conductivity, all achieved at room temperature. By using pump–probe modulation spectroscopy under ultrabroadband driving tunable from 4 meV to 1.55 eV, we show the terahertz (THz) field-induced surface carriers by discovering their initial temporal responses dominant over high density trivial bulk carriers. Strikingly, the response of the induced surface carrier responses persists for more than ~5 ps and is enhanced by reducing pump photon energy. The dynamics and lifetime of the distinct surface response manifest themselves as the enhanced THz pump-induced THz transmission, which directly correlates with the transient negative THz conductivity. Increasing the THz driving field reduces the induced surface carrier lifetime and identifies, particularly, an optimal pump field of E s ~ 224 kV cm -1 for generating the dominant surface response relative to the bulk. This surface carrier dominant regime is suppressed by a joint effect of enhanced surface-bulk scattering and a more rapid saturation of surface excitation compared to the bulk that sets in above E s . The controllability of room temperature topologically surface carriers through pump photon energy offer compelling possibilities for extending this approach to other topological complex materials.

36 MATERIALS SCIENCE↗

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗