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At least 937 records · Page 52

Influence of ordered L1 2 precipitation on strain-rate dependent mechanical behavior in a eutectic high entropy alloy

Recent studies indicate that eutectic high-entropy alloys can simultaneously possess high strength and high ductility, which have potential industrial applications. The present study focuses on Al 0.7 CoCrFeNi, a lamellar dual-phase ( fcc + B2) precipitation-strengthenable eutectic high entropy alloy. This alloy exhibits an fcc + B2 (B2 with bcc nano-precipitates) microstructure resulting in a combination of the soft and ductile fcc phase together with hard B2 phase. Low temperature annealing leads to the precipitation of ordered L1 2 intermetallic precipitates within the fcc resulting in enhanced strength. The strengthening contribution due to fine scale L1 2 is modeled using Orowan dislocation bowing and by-pass mechanism. The alloy was tested under quasi-static (strain-rate = 10 –3 s –1 ) tensile loading and dynamic (strain-rate = 10 3 s –1 ) compressive loading. Due to the fine lamellar microstructure with a large number of fcc - bcc interfaces, the alloy show relatively high flow-stresses, ~1400 MPa under quasi-static loading and in excess of 1800 MPa under dynamic loading. Interestingly, the coherent nano-scale L1 2 precipitate caused a significant rise in the yield strength, without affecting the strain rate sensitivity (SRS) significantly. These lamellar structures had higher work hardening due to their capability for easily storing higher dislocation densities. The back-stresses from the coherent L1 2 precipitate were insufficient to cause improvement in twin nucleation, owing to elevated twinning stress under quasi-static testing. However, under dynamic testing high density of twins were observed.

36 MATERIALS SCIENCE↗

Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

Abstract Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.

54 ENVIRONMENTAL SCIENCES↗

Global tropical cyclone precipitation scaling with sea surface temperature

Understanding the relationship between tropical cyclone (TC) precipitation and sea surface temperature (SST) is essential for both TC hazard forecasting and projecting how these hazards will change in the future due to climate change. This work untangles how global TC precipitation is impacted by present-day SST variability (known as apparent scaling) and by long-term changes in SST caused by climate change (known as climate scaling). A variety of datasets are used including precipitation and SST observations, realistic climate model simulations, and idealized climate model simulations. The apparent scaling rates depend on precipitation metric; examples shown here have ranges of 6.1 to 9.5% per K versus 5.9 to 9.8% per K for two different metrics. The climate scaling is estimated at about 5% per K, which is slightly less than the atmospheric moisture scaling based on thermodynamic principles of about 7% per K (i.e., the Clausius–Clapeyron scaling). The apparent scaling is greater than the climate scaling, which implies that the relationship between TC precipitation and present-day SST variability should not be used to project the long-term response of TC precipitation to climate change.

54 ENVIRONMENTAL SCIENCES↗

The disproportionate impact of enhanced evaporation from melting arctic sea ice on cold-season land precipitation trends

Diminishing Arctic sea ice has led to enhanced evaporation from the Arctic marginal seas (AMS), which is expected to alter precipitation over land. In this work, AMS evaporation is numerically tracked to quantify its contribution to cold-season (October–March) precipitation over land in the Northern Hemisphere during 1980–2021. Results show a significant 32% increase in AMS moisture contribution to land precipitation, corresponding to a 16% increase per million square km loss of sea ice area. Especially over the high-latitude land, despite the fractional contribution of AMS to precipitation being relatively low (8%), the augmented AMS evaporation contributed disproportionately (42%) to the observed upward trend in precipitation. Notably, northern East Siberia exhibited a substantial rise in both the amount and fraction of extreme snowfall sourced from the AMS. Our findings underscore the importance of the progressively ice-free Arctic as an important contributor to the escalating levels of cold-season precipitation and snowfall over northern high-latitude land.

54 ENVIRONMENTAL SCIENCES↗

Bimodality in simulated precipitation frequency distributions and its relationship with convective parameterizations

Abstract Bimodality in precipitation frequency distributions is often evident in atmospheric models, but rarely in observations. This study i) proposes a metric to objectively quantify the bimodality in precipitation distributions, ii) evaluates model simulations contributed to the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5), phase 6 (CMIP6), and the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project by comparing them to satellite-based and reanalysis precipitation products, and iii) investigates possible origins of bimodal precipitation distributions. Our results reveal that about 83% (20 out of 24) of CMIP5 and 70% (21 out of 30) of CMIP6 models used in this study exhibit bimodal distributions. The few DYAMOND models that use a deep convective parameterization also show bimodal distributions, while most DYAMOND models do not. Predictably, the bimodality originates from the separation of precipitation process between resolved grid-scale and parameterized subgrid-scale. However, in a larger number of models bimodality arises from the parameterized subgrid-scale convective precipitation alone.

54 ENVIRONMENTAL SCIENCES↗

Dual-precipitates enhance fatigue resistance in an additively manufactured high-entropy alloy

To accomplish the intense desire of high-strength materials for enhanced energy-efficiency, recent research applies a combined strategy of additive-manufacturing and precipitation-strengthening in high entropy alloys. In a context, Al 0.2 Co 1.5 CrFeNi 1.5 Ti 0.3 nanoprecipitation-strengthened system was developed, demonstrating very convincing strength and toughness. Moreover, additive-manufacturing facilitated additional strength by well-decorated cell-boundaries with blocky L2 1 precipitates and homogeneously distributed L1 2 precipitates. However, fatigue research of this alloy remained unexplored despite being the main precursor for structural applications. In this study low-cycle fatigue behavior of this alloy in both as-built and precipitation-strengthened (aged) conditions has been explored, combined with in-situ neutron diffraction investigation. Findings revealed a substantial cyclic-stress profile and a notable fatigue-life below ±0.50% strain-amplitude, exceeding 10 5 cycles at ±0.30% strain-amplitude. These demonstrate the potential to carry higher payloads with marked engineering-reliability. Residual-stress estimation revealed strain-compatibility between the matrix and L1 2 precipitate, indicating a crack-initiation immune interface. A comparative examination of dislocation character revealed shifting towards pure edge-character in aged alloy indicates precipitates promoted planar-slip during deformation.

36 MATERIALS SCIENCE↗

Group precipitation and age hardening of nanostructured Fe-based alloys with ultra-high strengths

The precipitation of nanoparticles plays a key role in determining the properties of many structural materials, and the understanding of their formation and stabilization mechanisms has been a long standing interest in the material field. However, the critical issues involving the group precipitation of various nanoparticles and their cooperative hardening mechanism remain elusive in the newly discovered Fe-based alloys with nanostructures. Here we quantitatively elucidate the nucleation mechanism, evolution kinetics and hardening effects of the group-precipitated nanoparticles in the Fe-Cu-Ni-Al-based alloys by atom probe tomography together with both first-principles and thermodynamic calculations. Our results provide the compelling evidence for two interesting but complex group precipitation pathways of nanoparticles, i.e., the Cu-rich and NiAl-based precipitations. Lastly, the co-existence of the two precipitation pathways plays a key role in age hardening kinetics and ultimately enhances the hardening response, as compared to the single particle type of strengthening, therefore providing an effective new approach for strengthening materials for structural applications.

36 MATERIALS SCIENCE↗

Modelling the evolution of complex conductivity during calcite precipitation on glass beads

When pH and alkalinity increase, calcite frequently precipitates and hence modifies the petrophysical properties of porous media. The complex conductivity method can be used to directly monitor calcite precipitation in porous media because it is sensitive to the evolution of the mineralogy, pore structure and its connectivity. Here, we have developed a mechanistic grain polarization model considering the electrochemical polarization of the Stern and diffuse layers surrounding calcite particles. Our complex conductivity model depends on the surface charge density of the Stern layer and on the electrical potential at the onset of the diffuse layer, which are computed using a basic Stern model of the calcite/water interface. The complex conductivity measurements of Wu et al. on a column packed with glass beads where calcite precipitation occurs are reproduced by our surface complexation and complex conductivity models. The evolution of the size and shape of calcite particles during the calcite precipitation experiment is estimated by our complex conductivity model. At the early stage of the calcite precipitation experiment, modelled particles sizes increase and calcite particles flatten with time because calcite crystals nucleate at the surface of glass beads and grow into larger calcite grains. Finally, at the later stage of the calcite precipitation experiment, modelled sizes and cementation exponents of calcite particles decrease with time because large calcite grains aggregate over multiple glass beads and only small calcite crystals polarize.

58 GEOSCIENCES↗

Elastically mediated interactions between grain boundaries and precipitates in two-phase coherent solids

In this work, we investigate analytically and numerically the interaction between grain boundaries and second phase precipitates in two-phase coherent solids in the presence of misfit strain. Our numerical study uses amplitude equations that describe the interaction of composition and stress [R. Spatschek and A. Karma, Phys. Rev. B 81, 214201 (2010)] and free-energies corresponding to two-dimensional hexagonal and three-dimensional BCC crystal structures that exhibit isotropic and anisotropic elastic properties, respectively. We consider two experimentally motivated geometries where (i) a lamellar precipitate nucleates along a planar grain boundary that is centered inside the precipitate, and (ii) a circular precipitate nucleates inside a grain at a finite distance to an initially planar grain boundary. For the first geometry, we find that the grain boundary becomes morphologically unstable due to the combination of long-range elastic interaction between the grain boundary and compositional domain boundaries, and shear-coupled grain boundary motion. We characterize this instability analytically by extending the linear stability analysis carried out recently [P.-A. Geslin, Y.-C. Xu, and A. Karma, Phys. Rev. Lett. 114, 105501 (2015)] to the more general case of elastic anisotropy. The analysis predicts that elastic anisotropy hinders but does not suppress the instability. Simulations also reveal that, in a well-developed nonlinear regime, this instability can lead to the break-up of low-angle grain boundaries when the misfit strain exceeds a threshold that depends on the grain boundary misorientation. For the second geometry, simulations show that the elastic interaction between an initially planar grain boundary and an adjacent circular precipitate causes the precipitate to migrate to and anchor at the grain boundary.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mesoscale convective clustering enhances tropical precipitation

In the tropics, extreme precipitation events are often caused by mesoscale systems of organized, spatially clustered deep cumulonimbi, posing a substantial risk to life and property. While the clustering of convective clouds has been thought to strengthen precipitation rate, no quantitative estimates of this hypothesized enhancement exist. In this study, after isolating the effects of mesoscale convective clustering on precipitation, we find that strongly clustered oceanic convection precipitates more intensely than weakly clustered convection. We further show that this enhancement is primarily attributable to an increase in convective precipitation rate when the environment is less than 70% saturated, with increases in the size of the rainy stratiform region being of equal or greater importance when the environment is closer to saturation. Our results suggest that a correct representation of mesoscale organized convective systems in numerical weather and climate models is needed for accurate predictions of extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗

A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns

Abstract Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950–2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a “base function” for evaluating a climate model’s potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model’s skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4’s representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗

Climatological Characteristics of Typical Daily Precipitation

Precipitation is often quantified by the amount that falls over a given period of time but not the rate at which most of it falls or the rate associated with the most frequent events. Here, three metrics are introduced to distill salient characteristics of typical daily precipitation accumulation based on the full distribution of rainfall: rain amount peak (the rain rate at which the most rain falls), rain frequency peak (the most frequent nonzero rain rate), and rain amount width (a measure of the variability of typical precipitation accumulation). These metrics are applied to two observational datasets to describe the climatology of typical daily precipitation accumulation: GPCP 1° daily (October 1996–October 2015) and TMPA 3B42 (January 1998–October 2015). Results show that the rain frequency peak is similar to total rainfall in terms of geographical pattern and seasonal cycle and varies inversely with rain amount width. In contrast, the rain amount peak varies distinctly, reaching maxima on the outer edges of the regions of high total precipitation, and with less seasonal variation. Despite that GPCP and TMPA 3B42 are both merged satellite–gauge precipitation products, they show substantial differences. In particular, the rain amount peak and rain amount width are uniformly greater in TMPA 3B42 compared to GPCP, and there are large discrepancies in their rain frequency distributions (peak and width). Issues relating to model evaluation are highlighted using CESM1 as an illustrative example and underscore the need for observational datasets incorporating measurements of light rain.

Meteorology & Atmospheric Sciences↗

Clustering of Observed Diurnal Cycles of Precipitation over the United States for Evaluation of a WRF Multiphysics Regional Climate Ensemble

The diurnal cycle of precipitation during the summer season over the contiguous United States is examined in eight distinct regions. These were identified using cluster analysis applied to the diurnal cycle characteristics at 2141 rainfall gauges over the 10-yr period 1991–2000. Application of the clustering technique provides a physically meaningful way of identifying regions for comparison of model results with observations. The diurnal cycle for each region is specified in terms of 1) total precipitation, 2) frequency of precipitation occurrence, and 3) intensity of precipitation per occurrence on an hourly basis averaged over the 10-yr period. The amplitude and phase of each element of the diurnal cycle was obtained from harmonic analysis and has been compared with the results of a 24-member multiphysics ensemble of simulations produced by the Weather Research and Forecast (WRF) Model on a region-by-region basis. Three cumulus schemes, two radiation schemes, two microphysics schemes, and two planetary boundary layer schemes were included in the ensemble. Simulations of total precipitation showed reasonable agreement with observations in regions where the diurnal cycle is directly influenced by solar radiation, (e.g., the U.S. Southeast), but they were less successful in regions where other factors influence the diurnal cycle (e.g., the central United States). The diurnal cycle of precipitation frequency and intensity showed substantial biases in the simulations of all eight regions, namely, overestimation of occurrences and underestimation of intensities. Simulations were sensitive to the cumulus and radiation schemes but were largely insensitive to either microphysics or planetary boundary layer schemes.

Mooney, P. A.↗

Cold-Season Precipitation Sensitivity to Microphysical Parameterizations: Hydrologic Evaluations Leveraging Snow Lidar Datasets

Abstract Cloud microphysical processes are an important facet of atmospheric modeling, as they can control the initiation and rates of snowfall. Thus, parameterizations of these processes have important implications for modeling seasonal snow accumulation. We conduct experiments with the Weather Research and Forecasting (WRF V4.3.3) Model using three different microphysics parameterizations, including a sophisticated new scheme (ISHMAEL). Simulations are conducted for two cold seasons (2018 and 2019) centered on the Colorado Rockies’ ∼750-km 2 East River watershed. Precipitation efficiencies are quantified using a drying-ratio mass budget approach and point evaluations are performed against three NRCS SNOTEL stations. Precipitation and meteorological outputs from each are used to force a land surface model (Noah-MP) so that peak snow accumulation can be compared against airborne snow lidar products. We find that microphysical parameterization choice alone has a modest impact on total precipitation on the order of ±3% watershed-wide, and as high as 15% for certain regions, similar to other studies comparing the same parameterizations. Precipitation biases evaluated against SNOTEL are 15% ± 13%. WRF Noah-MP configurations produced snow water equivalents with good correlations with airborne lidar products at a 1-km spatial resolution: Pearson’s r values of 0.9, RMSEs between 8 and 17 cm, and percent biases of 3%–15%. Noah-MP with precipitation from the PRISM geostatistical precipitation product leads to a peak SWE underestimation of 32% in both years examined, and a weaker spatial correlation than the WRF configurations. We fall short of identifying a clearly superior microphysical parameterization but conclude that snow lidar is a valuable nontraditional indicator of model performance.

54 ENVIRONMENTAL SCIENCES↗

Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH{sub 4}{sup +} production during urea hydrolysis were incorporated in the model and captured critical changes in the major metal species. The electrical phase increases were potentially due to ion exchange processes that modified charge structure at mineral/water interfaces. Our study revealed the potential of geophysical monitoring for geochemical changes during urea hydrolysis and the advantages of combining multiple approaches to understand complex biogeochemical processes in the subsurface.

54 ENVIRONMENTAL SCIENCES↗

Extreme Precipitation and Runoff under Changing Climate in Southern Maine

The quantification of extreme precipitation events is vitally important for designing and engineering water and flood sensitive infrastructure. Since this kind of infrastructure is usually built to last much longer than 10, 50, or even 100 years, there is great need for statistically sound estimates of the intensity of 10-, 50-, 100-, and 500-year rainstorms and associated floods. The recent assessment indicated that the intensity of the most extreme precipitation events (or the heaviest 1% of all daily events) have increased in every region of the contiguous states since the 1950s (Melillo et al. 2014). The maximum change in precipitation intensity of extreme events occurred in the northeast region reaching 71%. The precipitation extremes can be characterized using intensity-duration-frequency analysis (IDF). However, the current IDFs in this region were developed around the assumption that climate condition remains stationary over the next 50 or 100 years. To better characterize the potential flood risk, this project will (1) develop precipitation IDFs on the basis of both historical observations and future climate projections from dynamic downscaling with Argonne National Laboratory’s (Argonne’s) regional climate model and (2) develop runoff IDFs using precipitation IDFs for the Casco Bay Watershed. IDF development also considers non-stationary distribution models and snowmelt effects that are not incorporated in the current IDFs.

54 ENVIRONMENTAL SCIENCES↗

Impact of Dust-Cloud-Radiation-Precipitation Dynamical Feedback on Subseasonal-to-Seasonal Variability of the Asian Summer Monsoon in Global Variable-Resolution Simulations With MPAS-CAM5

In this study, we investigate the effects of increased dust emission from the Middle East deserts on subseasonal-to-seasonal (S₂S) variability of the Asian summer monsoon (ASM). Numerical experiments are performed using the Model for Prediction Across Scales (MPAS) coupled with the Community Atmosphere Model (CAM5) physics, with regional refinement at 30 km grid resolution over South Asia and the surrounding regions. Result shows that increased dust emission and transport from the Middle East/West Asia region induces a strong dust-cloud-radiation-precipitation-circulation feedback, resulting in a colder surface over the desert regions and the western Tibetan Plateau, but warmer and moister troposphere with enhanced cloudiness and precipitation over the Pakistan/Northwest India (PNWI) region. The latter changes are amplified by the dust aerosol induced Elevated Heat Pump (EHP) mechanism along the West Himalayas/Iranian Plateau foothill regions, most pronounced during May-June. During July-August, cloud radiation feedback further enhances the warming of the upper troposphere, and cooling of the land surface over the PNWI and adjacent regions over West Asia. The upper tropospheric heating and increased precipitation over PNWI spur a large-scale anomalous Rossby wavetrain and a northward displacement of the subtropical jetstream, manifesting in a contraction of the South Asian High and westward shift of the Western Pacific Subtropical High. As a result, the entire ASM precipitation-cloud system is displaced westward. Precipitation and cloudiness are intensified over northwest and western India and west Asia, but suppressed over southern and central East Asia. Analyses of the S₂S variability of the upper level vorticity balance suggests that heating by Middle East dust plays an important role in exciting, and anchoring a teleconnection pattern through interactions among dust-cloud radiation, precipitation heating over the PNWI, the development of an upper level Rossby wavetrain, and the northward shift of the boreal summer jetstream over Eurasia.

54 ENVIRONMENTAL SCIENCES↗

Response of Biological Soil Crust Diazotrophs to Season, Altered Summer Precipitation, and Year-Round Increased Temperature in an Arid Grassland of the Colorado Plateau, USA

Biological soil crusts (biocrusts), which supply significant amounts of fixed nitrogen into terrestrial ecosystems worldwide (~33 Tg y -1 ), are likely to respond to changes in temperature and precipitation associated with climate change. Using nifH gene-based surveys, we explored variation in the diazotrophic community of biocrusts of the Colorado Plateau, USA in response to season (autumn vs. spring), as well as field manipulations that increased the frequency of small volume precipitation events and year-round soil temperature. Abundance of nifH genes in biocrusts ranged from 3 × 10 6 to 1 × 108 g -1 soil, and nifH from heterocystous cyanobacteria closely related to Scytonema hyalinum, Spirirestis rafaelensis, and Nostoc commune comprised >98% of the total. Although there was no apparent seasonal effect on total nifH gene abundance in the biocrusts, T-RFLP analysis revealed a strong seasonal pattern in nifH composition. Spirirestis nifH abundance was estimated to oscillate 1 to >2 orders of magnitude between autumn (low) and spring (high). A year-round increase of soil temperature (2–3°C) had little effect on the diazotroph community structure over 2 years. Altered summer precipitation had little impact on diazotroph community structure over the first 1.5 years of the study, when natural background patterns across years and seasons superseded any treatment effects. However, after the second summer of treatments, nifH abundance was 2.6-fold lower in biocrusts receiving altered precipitation. Heterocystous cyanobacteria were apparently more resilient to altered precipitation than other cyanobacteria. The results demonstrate that diazotrophic community composition of biocrusts in this semi-arid grassland undergoes strong seasonal shifts and that the abundance of its dominant members decreased in response to more frequent, small volume precipitation events.

59 BASIC BIOLOGICAL SCIENCES↗