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At least 775 records · Page 43

Pyrolysis temperature and soil depth interactions determine PyC turnover and induced soil organic carbon priming

Pyrogenic organic carbon (PyC) is a complex, heterogeneous class of thermally altered organic substrates, but its dynamics and how its behavior changes with soil depth remain poorly understood. We conducted a laboratory incubation study to investigate the interactive effects of pyrolysis temperature and soil depth on the turnover of PyC compared to its precursor wood and native SOC (NSOC). We incubated dual-labeled (13C and 15N) jack pine pyrogenic organic matter produced at 300 °C (PyC300), 450 °C (PyC450), and their precursor pine wood in a fine-loamy, mixed-conifer forest soil for 745 days. A mixture of surface (0–10 cm) and subsurface (50–70 cm) forest soils, with and without labeled biomass were incubated in the dark at 55% soil water field capacity and 25 °C. Total 13C from PyC and wood mineralized as 13C-CO2 (as % of C added to soil) declined with an increase in pyrolysis temperature as follows: 54 ± 7.7% for wood, 3.1 ± 0.2% for PyC300, and 0.94 ± 0.08% for PyC450. Furthermore, after 2 years, soil depth interacted with pyrolysis temperature to affect C turnover, with total wood C losses significantly declining from 70.6% in surface soils to 37.5% in subsurface soil, while total losses of PyC300 and PyC450 were unaffected by differences between surface and subsurface soils. Wood induced negative priming (i.e., decreased mineralization rates) in surface soil at days 3 and 60, while PyC300 induced positive priming (i.e., increased mineralization rates) in subsurface soil at day 60. After 2 years, unlabeled NSOC losses increased from 9.2 ± 0.8% of NSOC in unamended treatments to 16.5 ± = 2.6% of NSOC with PyC450 additions. Our results suggest that PyC pyrolyzed at a given temperature can mineralize at similar rates between soil depths, and high amounts of PyC450 in subsurface soils can stimulate NSOC losses. These findings indicate that soil depth imposes critical controls on PyC dynamics belowground.

13C-labeling↗

Impact of polymer additives on crack mitigation of rod-coated fuel cell cathode catalyst layers

Cracks in catalyst layers (CLs) are a potential source of long-term failure in a fuel cell membrane electrode assembly (MEA). While modifications to the CL ink formulation can affect the degree of cracking, these changes may lead to lower initial performance than their cracked analogues due to the established link between formulation and performance. In this work, we explored the use of polymeric additives to mitigate CL cracks. Small quantities of poly (acrylic acid), poly (ethylene oxide), poly (methyl methacrylate), or poly (vinyl alcohol) - 5 wt% relative to ionomer mass - were added to the ink prior to its final mixing. Poly (vinyl alcohol) resulted in crack-free CLs, whereas the other polymers resulted in CLs with similar crack percentages as the control CL. Through a combination of transmission electron microscopy, X-ray computed tomography, and infrared spectroscopy, we ascribed the crack-mitigating mechanism of poly (vinyl alcohol) to its ability to hydrogen-bond with Nafion, the ion conducting polymer binder in the catalyst ink. Initial performance of this non-cracked electrode exhibited nearly identical electrochemical behavior to its cracked counterpart, demonstrating that PVA additives successfully reduce cracks while maintaining cell initial performance.

30 DIRECT ENERGY CONVERSION↗

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗

Cloud Condensation Nuclei Closure Study Using Airborne Measurements Over the Southern Great Plains

Abstract Airborne measurements of non‐refractory bulk aerosol chemical composition, aerosol size distributions, and cloud condensation nuclei (CCN) were conducted onboard a research aircraft during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems field campaign in the spring and summer of 2016. A CCN closure study for the entire campaign period was performed where measured CCN concentrations at 0.24% and 0.46% supersaturation were compared with the predicted CCN concentrations calculated using κ ‐Köhler theory, three different assumptions of aerosol mixing state, and various assumptions about hygroscopicity, density, and the insoluble fraction of organic particles. We found that the Closure Ratio (CR), calculated as the ratio of predicted to measured CCN concentrations, was equal to one under two different aerosol mixing state assumptions: (a) all particles are composed of 100% organic particles, and (b) particles are externally mixed and composed of pure sulfates, nitrates, and organic particles assuming hygroscopicity values for organic particles ( ) between 0.04 and 0.17. The use of internal mixing state assumption often led to overprediction of CCN concentrations but the agreement within ±20% with the measured CCN concentrations was observed under certain closure permutations. A similar agreement, that is, within ±20%, was also observed using permuted parameters concerning density (1 and 1.5 g cm −3 ) and an insoluble fraction (0% and 20%) of organic particles. These findings may provide constraints on to predict CCN concentrations at a remote continental Southern Great Plains site.

54 ENVIRONMENTAL SCIENCES↗

Modeling and simulation of transitional Rayleigh–Taylor flow with partially averaged Navier–Stokes equations

In this work, the partially averaged Navier–Stokes (PANS) equations are used to predict the variable-density Rayleigh–Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number 500. This is a prototypical problem of material mixing, featuring laminar, transitional, and turbulent flow, instabilities and coherent structures, density fluctuations, and production of turbulence kinetic energy by both shear and buoyancy mechanisms. These features pose numerous challenges to modeling and simulation, making the RT flow ideal to develop the validation space of the recently proposed PANS Besnard–Harlow–Rauenzahn-linear eddy viscosity model closure. The numerical simulations are conducted at different levels of physical resolution and test three approaches to set the parameters $f_\phi$ defining the range of physically resolved scales. The computations demonstrate the efficiency (accuracy vs cost) of the PANS model predicting the spatiotemporal development of the RT flow. Results comparable to large-eddy simulations and direct numerical simulations are obtained at significantly lower physical resolution without the limitations of the Reynolds-averaged Navier–Stokes equations in these transitional flows. The data also illustrate the importance of appropriate selection of the physical resolution and the resolved fraction of each dependent quantity $\phi$ of the turbulent closure, $f_\phi$. These two aspects determine the ability of the model to resolve the flow phenomena not amenable to modeling by the closure and, as such, the computations’ fidelity.

Navier Stokes equations↗

Compaction and Morphology of Lost Circulation Materials

Lost circulation material (LCM) selection is critical to effectively and efficiently treating wellbore fluid losses in geothermal drilling where costs of treatment can be as much as 30% of the total drilling cost. We conducted several uniaxial compaction experiments on 10 different materials and several material mixtures to identify critical mechanical parameters of each. Materials degraded at 200°C were also investigated to understand how elevated temperatures in geothermal wells would degrade their compaction behavior. Granular materials tended to have lower compressibility and higher compression resistance, while more elongated and softer materials had less mechanical stiffness. Mixing materials tended to moderate the mechanical behaviors while heating universally increased the compaction of materials. Microscopy showed that particle strength tended to correlate positively with roundness and circularity and negatively with elongation of a material. Convexity of the degraded and undegraded materials showed heating may have increased the convexity or roughness of the individual particles. In conclusion, we concluded that granular materials are likely to provide the best seals in wells but that a mixture of size distribution, mechanical rigidity, and elongation is more likely to form a better seal for geothermal wells.

annular pressure drilling↗

Highly Efficient Regeneration Module for Carbon Capture Systems in NGCC Applications

The objective of this project is to design, fabricate, and test a highly efficient regeneration module capable of providing an ultra-lean absorption solution that is required for capturing CO 2 from dilute sources at 95% or better efficiency. By integrating this advanced regenerator module with SRI International’s Mixed Salt Process (MSP) absorption modules, SRI expects to demonstrate significant progress toward a reduction in cost of capture versus the DOE reference natural gas combined cycle (NGCC) plant with carbon capture. SRI designed, built, and tested an advanced stripper to enhance the performance of SRI’s MSP for CO 2 capture – a transformational ammonia-based solvent technology – for natural gas (NG) power sources. The testing of the advanced stripper for MSP was conducted at an SRI site using a simulated flue gas stream equivalent to about 10 kWe. The research work included modeling of the advanced stripper and integrating it with the MSP absorbers; studying the strategies for producing very highly alkaline lean solvent with minimized emissions; operating the stripper with advanced heat integration to improve process efficiencies; and collecting critically important data for a detailed techno-economic analysis (TEA). The project tasks were designed to address concerns relating to scale-up and integration of the technology to NG power plants—more specifically, to maximize the carbon capture efficiency achievable with MSP and identify pathways to achieve higher capture efficiencies and ultimately zero net carbon emissions. SRI teamed up with a process modeling company (OLI Systems), a process and chemical engineering company (Trimeric Corporation), and a cost-sharing commercial partner (Baker-Hughes – a leading multinational company that designs, manufactures, and services transformative energy technologies) to execute the project. The research findings will accelerate the MSP development and pave the way for the technology to reach the DOE’s goal, and ultimately commercialization of the MSP technology for low-cost CO 2 capture from NGCC flue gas and other dilute CO 2 sources.

03 NATURAL GAS↗

Development of a two-zone zero-dimensional mixing model for actively fueled prechamber engines

In this numerical work, a zero-dimensional, two-zone mixing model was developed and validated to capture the mixture preparation process of an actively fueled prechamber engine. The model was developed for ethanol-gasoline fuel blends but is applicable to various fuels of interest relevant to prechamber applications. The model was exercised to demonstrate the effects of boundary conditions, fuel composition, and residual content on the mixture stoichiometry predictions. The 0D model showed reasonable agreement in prechamber equivalence ratio predictions with higher fidelity computational fluid dynamics modeling, but the accuracy of model was constrained to the governing assumptions of the injection process. The modeling assumptions surrounding the non-dimensional injection of mass into the prechamber were scrutinized to identify key areas of model improvement. The results indicate heat transfer effects play a crucial role in the evaporation of the fuel within the confined auxiliary chamber, especially when considering fuels with high latent heat of vaporization. Additionally, the presence of fuel films that collect on the prechamber surfaces complicated the modeled evaporative cooling loses as the modeling suggests the films evaporate primarily by means of conduction from the boundary. Furthermore, the developed model serves as a simplified framework to generate calibration maps of prechamber fueling or run real time as an open loop control strategy such that desired prechamber mixture proportions are effectively targeted.

Zero-dimensional↗

Quantitative concentration measurements in a turbulent helium jet using rainbow schlieren deflectometry

Rainbow schlieren deflectometry (RSD) is applied to acquire quantitative concentration measurements in a turbulent environment for the first time. RSD methodology is developed and validated using Rayleigh scattering data available in the literature. Experiments were performed in an initially laminar, momentum-driven helium jet injected into ambient air. Full-field measurements are acquired that span the laminar, transition, and fully turbulent regions of the jet. Furthermore, the RSD results are shown to provide accurate measurements in each region and also confirm the self-similar nature of the fully turbulent jet. Analysis shows that the transition from laminar to turbulent flow occurs across an axial span that decreases with increasing Reynolds number. Experiments with a long exposure time were conducted to evaluate the limitations of hardware averaging of the RSD signal in comparison with software averaging.

02 PETROLEUM↗

Light scalars in neutron star mergers

Due to their unique set of multimessenger signals, neutron star mergers have emerged as a novel environment for studies of new physics beyond the Standard Model (SM). As a case study, we consider the simplest extension of the SM scalar sector involving a light CP-even scalar singlet S mixing with the SM Higgs boson. These S particles can be produced abundantly in neutron star mergers via the nucleon bremsstrahlung process. Here, we show that the S particles may either be trapped in or stream freely out of the merger remnant, depending on the S mass, its mixing with the SM Higgs boson, and the temperature and baryon density in the merger. In the free-streaming region, the scalar S will provide an extra channel to cool down the merger remnant, with cooling timescales as small as Script O(ms). On the other hand, in the trapped region, the Bose gas of S particles could contribute a larger thermal conductivity than the trapped neutrinos in some parts of the parameter space, thus leading to faster thermal equilibration than expected. Therefore, future observations of the early postmerger phase of a neutron star merger could effectively probe a unique range of the S parameter space, largely complementary to the existing and future laboratory and supernova limits. In view of these results, we hope the merger simulation community will be motivated to implement the effects of light CP-even scalars into their simulations in both the free-streaming and trapped regimes.

79 ASTRONOMY AND ASTROPHYSICS↗

Precision half-life determination for the β + emitter N 13

A new precision half-life measurement of 13 N has been conducted using the TwinSol β-counting station at the University of Notre Dame. Here, the measured value of $t^{new}_{1/2}$ = 597.05(19) s differs from the previous world value by about 2.8σ. An evaluation of the 13N half-life results in a $t^{world}_{1/2}$ = 597.19(22) s. Updated Standard Model predictions for the Fermi to Gamow-Teller mixing ratio ρ and its associated correlation parameters have been calculated using the new 13 N world half life in preparation for a future measurement of the mixing ratio. Finally, an ab initio no-core configuration interaction (NCCI) calculation for the B(GT) of this decay, carried out using the Daejeon16 interaction, has been carried out, revealing the need for higher-order chiral corrections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

One-Step Ahead Prediction of Thermal Mixing Tee Sensors with Long Short Term Memory (LSTM) Neural Networks

High-temperature advanced reactors under development, such as sodium fast reactors (SFR) and molten salt cooled reactors (MSCR), are expected to offer lower levelized cost of energy (LCOE) compared to existing light water reactor (LWR’s). In the existing light water reactors (LWR’s), operation and maintenance (O&M) expenses constitute the largest fraction of the total operating cost. Some of the O&M costs are related maintenance of sensors which can fail due to exposure to harsh environment in a reactor. The O&M costs of Advanced Reactor (AR)’s are expected to constitute a significant fraction of the total cost as well, because of high temperature and radiation level in AR are likely to cause material fatigue and premature failure of sensors and components. The O&M costs in AR’s could be reduced through integration of advanced informatics of performance-related sensors into a digital twin designed for reactor monitoring. For example, machine learning (ML) could be employed for real-time validation and correction of performance-related sensors, and reducing the number of performance-related physical sensor units through virtual sensing. As part of the effort, we investigate real-time validation of thermal hydraulic sensors through one-step ahead forecasting of sensor values using long short-term memory (LSTM) recurrent neural networks (RNN). The sensors are installed in a flow loop containing a thermal mixing tee, which is a common experimental model to study thermal fatigue in a thermal hydraulic loop. In addition, nonlinear transients generated in a thermal mixing tee constitute a good challenge data set for training and validation of ML algorithms. Sensors in this study include thermocouples, flow meters, and optical fibers for distributed temperature sensing. In one experiment, measurement data sets were obtained for a loop was filled with water, and in another experiment, measurements were performed on a loop filled with liquid metal Galinstan. We have also conducted preliminary investigation of one-step ahead prediction of fiber optics-based distributed temperature sensing with LSTM networks. In predicting fiber-based temperature measurements, we treated each gauge pitch of the fiber as an independent sensor. Accuracy of one-step ahead forecasting was estimated by calculating root mean square error (RMSE) for the test segment of time series of each sensor. RMSE’s for temperature sensors in water loop were, for the most part, lower than for the same sensors in Galinstan loop. The RMSE’s for flow meters were similar for both loops. The RMSE’s for distributed temperature measured with the fiber optic sensor were similar to those of the point sensors. Results of this study demonstrated the capability of LSTM one-step ahead forecasting with RMSE comparable to uncertainty in sensor measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Pore-resolved investigation of turbulent open channel flow over a randomly packed permeable sediment bed

Pore-resolved direct numerical simulations are performed to investigate the interactions between streamflow turbulence and groundwater flow through a randomly packed porous sediment bed for three permeability Reynolds numbers, Re K = 2.56 , 5.17 and 8.94, representative of natural stream or river systems. Time–space averaging is used to quantify the Reynolds stress, form-induced stress, mean flow and shear penetration depths, and mixing length at the sediment–water interface (SWI). Here, the mean flow and shear penetration depths increase with Re K and are found to be nonlinear functions of non-dimensional permeability. The peaks and significant values of the Reynolds stresses, form-induced stresses, and pressure variations are shown to occur in the top layer of the bed, which is also confirmed by conducting simulations of just the top layer as roughness elements over an impermeable wall. The probability distribution functions (p.d.f.s) of normalized local bed stress are found to collapse for all Reynolds numbers, and their root-mean-square fluctuations are assumed to follow logarithmic correlations. The fluctuations in local bed stress and resultant drag and lift forces on sediment grains are mainly a result of the top layer; their p.d.f.s are symmetric with heavy tails, and can be well represented by a non-Gaussian model fit. The bed stress statistics and the pressure data at the SWI potentially can be used in providing better boundary conditions in modelling of incipient motion and reach-scale transport in the hyporheic zone.

turbulence simulation↗

Uncovering the active sites and demonstrating stable catalyst for the cost-effective conversion of ethanol to 1-butanol

We report the recent emergence of a robust renewable ethanol industry has provided a sustainable platform molecule toward the production of value-added chemicals and fuels; what is lacking now are viable conversion processes from ethanol that can displace the current production pathways from non-renewable pathways. Here in the work, we demonstrate the highly selective conversion of ethanol to higher alcohols over low copper loaded MgAl mixed oxide catalysts, with 50% improvement in higher alcohol yields over the current state of the art. At these copper concentrations, atomically dispersed Cu +1 were found to be stable even at highly reductive conditions and highly active towards higher alcohol products (e.g. butanol, hexanol) while suppressing side reaction pathways and leading to extended lifetimes of over 150 hours time on stream. Technoeconomic analysis conducted based on these experimental results demonstrate that this catalytic system is cost-competitive with the conventional process. This marks significant progress in the development of Guerbet coupling of ethanol as a viable renewable process and offers a pathway toward sustainable chemical and fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kondo effect in ferromagnetic quantum critical CeRh 6 ⁢Ge 4

The mechanism of a pressure-induced quantum critical point in the heavy fermion ferromagnet CeRh 6 ⁢Ge 4 has attracted interest, as ferromagnetic quantum criticality in a clean itinerant Ce compound is typically avoided. The localized versus itinerant character of the 4⁢𝑓 electrons is a key aspect for understanding this behavior. We investigated the electronic structure of the 4⁢𝑓 shell in CeRh 6 ⁢Ge 4 using core-level photoelectron and x-ray absorption spectroscopy, demonstrating the hybridization of Ce 4⁢𝑓 with the conduction electrons. Linearly polarized x-ray absorption reveals a temperature-dependent linear dichroism consistent with the crystal-electric-field sequence as inferred from the static susceptibility. This dichroism cannot be described by an ionic full-multiplet model alone, but is reproduced by including the Kondo effect within a single-impurity Anderson model in the noncrossing approximation. The Kondo effect mixes higher-lying crystal-field states into a resulting multiorbital ground state with 4⁢𝑓 occupancy, 𝑛 𝑓 ∼ 0.9. Deviations at low temperatures between the measured linear dichroism and calculated dichroism suggest an orbital-dependent Kondo effect. A scenario in which there is a multiorbital ground state and orbital-dependent Kondo hybridization should be a starting point for a model of pressure-induced criticality in CeRh 6 ⁢Ge 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗