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At least 91 records · Page 5

Upstream surface roughness and terrain are strong drivers of contrast in tornado potential between North and South America

Central North America is the global hotspot for tornadoes, fueled by elevated terrain of the Rockies to the west and a source of warm, moist air from equatorward oceans. This conventional wisdom argues that central South America, with the Andes to the west and Amazon basin to the north, should have a “tornado alley” at least as active as central North America. Central South America has frequent severe thunderstorms yet relatively few tornadoes. Here, we show that conventional wisdom is missing an important ingredient specific to tornadoes: a smooth, flat ocean-like upstream surface. Using global climate model experiments, we show that central South American tornado potential substantially increases if its equatorward land surface is smoothed and flattened to be ocean-like. Similarly, we show that central North American tornado potential substantially decreases if its equatorward ocean surface is roughened to values comparable to forested land. A rough upstream surface suppresses the formation of tornadic environments principally by weakening the poleward low-level winds, characterized by a weakened low-level jet east of the mountain range. Results are shown to be robust for any midlatitude landmass using idealized experiments with a simplified continent and mountain range. Our findings indicate that large-scale upstream surface roughness is likely a first-order driver of the strong contrast in tornado potential between North and South America.

54 ENVIRONMENTAL SCIENCES↗

Corrosion Research Survey: Corrosion-Surface Roughness Correlation on Carbon and Stainless Steels

Concerning the SAVY 4000 container LANL inspection acceptance of Ra (surface roughness) and its correlation to subsequent surface corrosion, a problem statement has been identified. The problem statement is as follows: When the 316L container has been subjected to accommodating materials producing high wattage, along with materials that eventually produce HCL (hydrochloric acid) will a higher or lower Ra on the inner surface of the SAVY 4000 container influence the rate or the amount of corrosion? In an effort to address this concern, a literature review covering more fundamental studies that examine the influence of roughness on corrosion in metals are surveyed. The scope is kept relevant to the less dynamic storage conditions that a SAVY container may be exposed to.

36 MATERIALS SCIENCE↗

Surface Roughness Calculations of Additively Manufactured Cylinders via X-Ray Computed Tomography

X-ray Computed Tomography (X-ray CT) is an analytical technique used in materials science to non–destructively characterize features in variety of materials like polymers, metals, composites, and explosives. It also has the capability of imaging additively manufactured, machined and assembled parts and processes. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations as a result of different stimuli, and assess accuracy of material production. This study will focus on parts manufactured via metal additive manufacturing (AM). Although, AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties. The analysis of 3D printed objects has a strength in analysis in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e. foams) due to stochastic structures. For this study, the print accuracy of several 3D printed cylinders will be assessed via X-ray CT to determine optimal printing parameters for parts with less defects and stronger mechanical properties. This will be accomplished by having the original STL file serve as the baseline surface to compute difference in the CT rendering to calculate surface roughness for each cylinders.

36 MATERIALS SCIENCE↗

Electrode roughness dependent electrodeposition of sodium at the nanoscale

Na metal is an attractive anode material for rechargeable Na ion batteries, however, the dendritic growth of Na can cause serious safety issues. Along with modifications of solid-electrolyte interphase (SEI), engineering the electrode has been reported to be effective in suppressing Na dendritic growth, likely by reducing localized current density accumulation. However, fundamental understanding of Na growth at the nanoscale is still limited. Here, we report an in-situ study of Na electrodeposition in electrochemical liquid cells with the electrodes in different surface roughness, e.g., flat or sharp curvature. Real time observation using transmission electron microscopy (TEM) reveals the Na electrodeposition with remarkable details. Relatively large Na grains (in the micrometer scale) are achieved on the flat electrode surface. The local SEI thickness variations impact the growth rate, thus the morphology of individual grains. In contrast, small Na grains (in tens of nanometers) grow explosively on the electrode at the point with sharp curvature. The newly formed Na grains preferentially deposit at the base of existing grains close to the electrode. Further studies using continuum-based computational modeling suggest that the growth mode of an alkali metal (e.g. Na) is strongly influenced by the transport properties of SEI. Our direct observation of Na deposition in combination with the theoretical modeling provides insights for comprehensive understanding of electrode roughness and SEI effects on Na electrochemical deposition.

25 ENERGY STORAGE↗

Experimental and computational investigation of interactive flow induced oscillations of two tandem rough cylinders at 3×10 4 ≤Re≤1.2×10 5

The interactive flow induced oscillations (FIO) of two adjacent, elastically mounted, rigid, tandem, locally-rough cylinders in transverse flow direction are analyzed utilizing two-dimensional Unsteady Reynolds-Averaged Navier-Stokes (2-D URANS) equations and verified experimentally in the proximity-wake region. Three sets of experiments and simulations (K = 600N/m, ζ = 0.14; K = 600N/m, ζ = 0.26; K = 1,200N/m, ζ = 0.26; K is spring stiffness, ζ is damping ratio) of two tandem cylinders with turbulence stimulation are tested and simulated for Reynolds number in the range of 30,000 = Re ≤ 120,000. The reduced velocity range is U* = 2.48–14.22, the mass ratio is m* = 1.343, and the center-to-center in-flow spacing to diameter ratio is d/D = 2.57. The characteristics of amplitude response, frequency response, lift force, and interactive wake patterns are presented and discussed. The trends of the amplitude and frequency responses from numerical simulations are in good agreement with experimental results. The main conclusions of Reynolds number effect on interactive flow induced oscillations are: (1) Five significant flow patterns between two tandem locally-rough cylinders for different Reynolds numbers are observed through analyzing the complex but stable interactions between vortices and cylinders. (2) In the initial and upper VIV branches, the downstream cylinder's FIO is seriously interfered by the wake of the upstream cylinder. (3) The downstream cylinder is strongly impinged by the vortices shed from the upstream cylinder resulting in nearly 180O out-of-phase oscillations in transition from VIV to galloping and in-phase oscillations in galloping.

42 ENGINEERING↗

Stochastic modal velocity field in rough-wall turbulence

Stochastically generated instantaneous velocity profiles are used to reproduce the outer region of rough-wall turbulent boundary layers in a range of Reynolds numbers extending from the wind tunnel to field conditions. Each profile consists in a sequence of steps, defined by the modal velocities and representing uniform momentum zones (UMZs), separated by velocity jumps representing the internal shear layers. Height-dependent UMZ is described by a minimal set of attributes: thickness, mid-height elevation, and streamwise (modal) and vertical velocities. These are informed by experimental observations and reproducing the statistical behaviour of rough-wall turbulence and attached eddy scaling, consistent with the corresponding experimental datasets. Sets of independently generated profiles are reorganized in the streamwise direction to form a spatially consistent modal velocity field, starting from any randomly selected profile. The operation allows one to stretch or compress the velocity field in space, increases the size of the domain and adjusts the size of the largest emerging structures to the Reynolds number of the simulated flow. By imposing the autocorrelation function of the modal velocity field to be anchored on the experimental measurements, we obtain a physically based spatial resolution, which is employed in the computation of the velocity spectrum, and second-order structure functions. The results reproduce the Kolmogorov inertial range extending from the UMZ and their attached-eddy vertical organization to the very-large-scale motions (VLSMs) introduced with the reordering process. The dynamic role of VLSM is confirmed in the –u'w' co-spectra and in their vertical derivative, representing a scale-dependent pressure gradient contribution.

42 ENGINEERING↗

The importance of sub-meter-scale snow roughness on conductive heat flux of Arctic sea ice

Abstract The conductive heat flux through the snow and ice is a critical component of the mass and energy budgets in the Arctic sea ice system. We use high horizontal resolution (3–15 cm) measurements of snow topography to explore the impacts of sub-meter-scale snow surface roughness on heat flux as simulated by the Finite Element method. Simulating horizontal heat flux in a variable snow cover modestly increases the total simulated heat flux. With horizontal heat flux, as opposed to simple 1D-vertical heat flux modeling, the simulated heat flux is 10% greater than that for uniform snow with the same mean snow thickness for a 31.5 × 21 m region of sea ice (the largest region we studied). Vertical-only (1D) heat flux simulates just a 6% increase for the same region. However, this is highly dependent on observation resolution. Had we measured the snow cover at 1 m horizontal spacing or greater, simulating horizontal heat flux would not have changed the net heat flux from that simulated with vertical-only heat flux. These findings suggest that measuring and modeling snow roughness at sub-meter horizontal scales may be necessary to accurately represent horizontal heat flux on level Arctic sea ice.

Geology↗

Hydrogen Diffusion in Slit Pores: Role of Temperature, Pressure, Confinement, and Roughness

Diffusion of hydrogen (H 2 ) is important to understand the leakage risk and transport behavior for H 2 geologic storage. We applied molecular dynamics simulations to investigate the influencing factors of H2 diffusion in the slit pores of calcite, hematite, and quartz, owing to their abundance. It is revealed that the H2 self-diffusion coefficient increases with the temperature, regardless of the type of pore minerals. The diffusion of H 2 in the 20 nm slit pores falls into the bulk diffusion regime when the pressure is 10 MPa. The self-diffusion of H 2 decreases with pressure in all three types of slit pores, following a power law model with the exponents ranging from -0.825 to -0.964. Furthermore, the impact of confinement on H 2 diffusion is more pronounced for the slit pores with stronger interactions with H 2 -like calcite. The role of surface roughness in H 2 diffusion depends on the slit aperture. The rough surface enhances H 2 diffusion in the larger slit pores due to the enlarged effective pore space, whereas it weakens H 2 diffusion in the small slit pores due to stronger adsorption. These findings will fill the knowledge gap on the coupling effect of different factors influencing H 2 diffusion.

08 HYDROGEN↗

Two-Phase Fluid Flow Properties of Rough Fractures With Heterogeneous Wettability: Analysis With Lattice Boltzmann Simulations

Fractures are conduits for fluid flow in low-permeability geological formations. Multiphase flow properties of fractures are important in natural processes and in engineering applications such as the evaluation of the sealing capacity of caprocks and productivity of hydrocarbon-bearing tight rocks. Investigations of flow and transport through fractures typically focus on the effects of fracture geometric and mechanical factors such as aperture, roughness, and compressibility. The wettability of the fracture surfaces and its influence on microscale interfacial phenomena and macroscale effective transport properties are seldom studied. In this study, we investigated the effect of heterogeneous wetting properties on the displacement of water by supercritical CO2 through a series of lattice Boltzmann method simulations. The results show the evolution of the CO2 plume within a fracture is controlled by both the roughness of the aperture field and the wetting distribution. We combined these factors into a capillary pressure map that can be related to the macroscopic flow behavior of the fracture. We observed that heterogeneous wetting distributions promote the residual trapping of water where lower capillary pressures allowed for isolated water pockets in higher capillary pressure zones. Analysis of fracture unsteady relative permeability shows the effect of wetting on permeability evolution and provides support for the viscous-coupling relative permeability model. Finally, analysis of the steady-state relative permeability and saturation demonstrates a strong correlation between permeability and the standard deviation of the capillary pressure field. Thus, characterizing the distribution of wetting properties of fractures is crucial to understanding multiphase fracture flow and transport properties.

58 GEOSCIENCES↗

Intermittent Criticality Multi‐Scale Processes Leading to Large Slip Events on Rough Laboratory Faults

Abstract We discuss data of three laboratory stick‐slip experiments on Westerly Granite samples performed at elevated confining pressure and constant displacement rate on rough fracture surfaces. The experiments produced complex slip patterns including fast and slow ruptures with large and small fault slips, as well as failure events on the fault surface producing acoustic emission bursts without externally‐detectable stress drop. Preparatory processes leading to large slips were tracked with an ensemble of ten seismo‐mechanical and statistical parameters characterizing local and global damage and stress evolution, localization and clustering processes, as well as event interactions. We decompose complex spatio‐temporal trends in the lab‐quake characteristics and identify persistent effects of evolving fault roughness and damage at different length scales, and local stress evolution approaching large events. The observed trends highlight labquake localization processes on different spatial and temporal scales. The preparatory process of large slip events includes smaller events marked by confined bursts of acoustic emission activity that collectively prepare the fault surface for a system‐wide failure by conditioning the large‐scale stress field. Our results are consistent overall with an evolving process of intermittent criticality leading to large failure events, and may contribute to improved forecasting of large natural earthquakes.

Geochemistry & Geophysics↗

Controlling Deformation in Al/Ti: How Interface Roughness and Orientation Drive Bimetal Mechanics

The microstructural characteristics and morphology of interfaces in metals can be crucial in governing the initiation of plasticity and early deformation mechanisms under extreme conditions. During high-strain-rate deformation, these interfaces significantly affect dislocation nucleation, twinning, and other mechanisms that directly impact material strength and failure. Despite their importance, a substantial knowledge gap remains between the observed macroscopic material behavior and the underlying role of bimetal interfaces in plasticity initiation. Here, to address this gap, large-scale molecular dynamics simulations are performed on Al/Ti bimetal structures to examine the effect of interface characteristics on the onset of plasticity under uniaxial compression. Specifically, this study investigates how interface roughness (flat vs waveform interfaces) modifies the initiation of plastic events in the microstructure. Atomistic simulations indicate that interface roughness (a microscopic behavior) reduces the stress required for dislocation nucleation, thereby reducing the peak stress relative to a flat interface. For the square interface, the step height strongly influences plasticity initiation by setting the separation of locally flat regions. Varying the interface rotation relative to the loading direction (macroscopic behavior) reveals that the peak stress for both flat and waveform interfaces initially decreases and then increases with rotation, accompanied by a shift in dominant mechanisms—from Al twinning (flat) to interface sliding and Ti-dominated phase transformation and twinning at lower angles. The change in the stress-strain slope during initial compression reflects how rotation alters the resolved shear stress and activates different slip systems. Overall, the study provides valuable insights into the role of bimetal interfaces in controlling plasticity initiation and early deformation pathways for Al/Ti under extreme loading conditions.

36 MATERIALS SCIENCE↗

Mediation of Colloidal Encounter Dynamics by Surface Roughness

Rigorous understanding on the self-assembly of colloidal nanocrystals is crucial to develop tailored nanostructured materials for energy storage, sensing, and optical fields. Despite extensive studies on the self-assembly, a mechanistic understanding of self-assembly under an external field still remains an ongoing challenge. Here, in this work, we used optical tweezers that impose an external attractive force field, resulting in the self-assembly of alpha-phase sodium yttrium fluoride nanocrystals. The dynamic force that is strongly dependent on the surface roughness of the nanocrystals is shown to be a decisive factor for a direct contact between the nanocrystals, manifested by the roughness-dependent hydrodynamic resistivity and Langevin dynamic simulations. Our study provides direct evidence that the role of dynamics is equally important in understanding the self-assembly, which has been rarely observed in the self-assembly in contrast with many studies on the equilibrium forces. These results may have further impact in other fields, such as having explanatory power for the probability of nonclassical crystal growth or the structure of viral spike proteins that affect the probability of viruses binding with cells.

Felsted, Robert G. [Univ. of Washington, Seattle, ↗

Modeling of Cube Array Roughness: RANS, Large Eddy Simulation, and Direct Numerical Simulation

Abstract Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using direct numerical simulation (DNS) and large eddy simulation (LES), the ability of sublayer-resolved Reynolds-averaged Navier–Stokes (RANS) to predict the bulk flow phenomena of these systems is relatively unexplored, especially at low and high packing densities. Here, RANS simulations are conducted on six different packing densities of cubes in aligned and staggered configurations. The packing densities investigated span from what would classically be defined as isolated, up to those in the d-type roughness regime, filling in the gap in the present literature. Three different sublayer-resolved turbulence closure models were tested for each case: a low Reynolds number k–ϵ model, the Menter k–ω SST model, and a full Reynolds stress model. Comparisons of the velocity fields, secondary flow features, and drag coefficients are made between the RANS results and existing LES and DNS results. There is a significant degree of variability in the performance of the various RANS models across all comparison metrics. However, the Reynolds stress model demonstrated the best accuracy in terms of the mean velocity profile as well as drag partition across the range of packing densities.

Engineering↗

Role of humidity and surface roughness on direct wafer bonding

Bodies made from elastically stiff material usually bind very weakly unless the surfaces are flat and extremely smooth. In direct wafer bonding flat surfaces bind by capillary bridges and by the van der Waals interaction, which act between all solid objects. Here we study the dependency of the work of adhesion on the humidity and surface roughness in hydrophilic direct wafer bonding. We show that the long-wavelength roughness (usually denoted waviness) has a negligible influence on the strength of wafer bonding (the work of adhesion) from the menisci that form from capillary condensation of water vapor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Application of artificial intelligence methods in the international roughness index prediction of rigid and composite pavements: a systematic review

The International Roughness Index (IRI) is a widely adopted metric for quantifying pavement roughness, directly influencing vehicle safety, ride comfort, and overall roadway performance. In recent years, the use of Machine Learning (ML) models for IRI prediction has gained momentum, with the goal of improving the allocation of maintenance and rehabilitation resources by enabling accurate assessments of pavement conditions. Most prior reviews, however, have concentrated on flexible pavements, leaving a notable gap regarding rigid and composite pavements. To address this gap, the present study conducts a systematic review of Artificial Intelligence (AI) methods applied to IRI prediction for rigid and composite pavements. Literature published between 2004 and 2025 is synthesized to highlight prevailing trends, methodological contributions, and directions for future research. Particular attention is given to the types of models employed, the datasets used for training and validation, and the role of input variables and data-processing strategies. Across the included studies, ensemble learning methods (especially gradient boosting variants such as XGBoost), artificial neural networks, and hybrid architectures frequently achieved high predictive skill, with several models reporting test-set coefficients of determination approaching 0.9–0.96, indicating strong potential for capturing the influence of traffic, pavement structure, and climatic factors. Since these results are obtained from heterogeneous datasets and evaluation protocols, they are interpreted qualitatively rather than as strict cross-study rankings. Analysis of input variables revealed that pavement age and initial IRI were included in 91% (21 of 23) and 78% (18 of 23) of studies, respectively. Climatic variables such as the freezing index appeared in 57% (13 of 23), while traffic-related factors were considered in 65% (15 of 23). The findings underscore the importance of standardized, high-quality datasets, such as those from the Long-Term Pavement Performance (LTPP) program, along with data consistency, model interpretability, computational efficiency, and replicability in enhancing IRI prediction. Future research should focus on incorporating input variable selection techniques to identify the most influential predictors, thereby improving accuracy and robustness. Integrating these approaches with advanced non-linear data-driven models, coupled with robust hyperparameter optimization, holds considerable promise for strengthening the reliability of IRI prediction and supporting resilient pavement management strategies.

42 ENGINEERING↗

Surface Roughness Effects on Heat Transfer in Additively Manufactured sCO 2 Cycle Heat Exchangers

An experimental study was performed to consider the impact of surface roughness on heat transfer and pressure drop to supercritical carbon dioxide (sCO 2 ) in additively manufactured channels. All tests were performed in the Heat Exchange and Experimental Testing (HEET) rig at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia. Four test articles were considered. The first was a hydrodynamically smooth, drawn tube. The other three were additively manufactured channels with square and rectangular cross sections, which were characterized by sand-grain roughness to hydraulic diameter ratios spanning 0.0029 to 0.0073. Friction factors were determined by measuring the tube mass flow rate and pressure drop. The tube side heat transfer coefficient was measured using the Wilson plot technique. It was found that the friction factor results were 8% greater than the Colebrook correlation. Greater deviation was observed between the heat transfer results and the correlations. The Gnielinski correlation overpredicted the experimental points by nominally 30% and the Norris correlation overpredicting the experimental points by nominally 25%. A thermal performance factor was formed from the friction factor augmentation and Nusselt number augmentation results. These results indicated a 10% improvement in heat duty for a heat exchanger constructed utilizing a tube with ϵ/D_h =0.0073 relative to a heat exchanger utilizing a smooth, conventional tube.

36 MATERIALS SCIENCE↗

Reducing roughness and improving efficiency of MAPbI3 perovskite solar cells made by high-throughput photonic curing

For perovskite solar cells (PSCs) to be commercially viable, the slow and energy-insufficient thermal annealing step must be eliminated. Among the photo-irradiation methods proposed to replace thermal annealing, photonic curing is the fastest conversion method. Photonic curing delivers short (20 μs to 100 ms) but intense light pulses from a broadband (200-1500 nm) xenon flash lamp, making it the only method to convert perovskite under 20 ms. This processing time can be extrapolated to a roll-to-roll web speed of 40 m/min based on laboratory processing conditions. However, most reported PSCs made by photonic curing under 1 second have inferior performance (~10% PCE). Although SEM images show dense and pinhole-free perovskite films, AFM images indicate secondary wavy features of 500 nm-wide ridge and 80 nm-deep trenches on photonically cured perovskite films, the existence of which correlates with poor device performance. We suggest that this morphology feature is produced by volatile solvent evaporation during the fast photonic curing process. Two approaches have been made to remedy this issue: (1) adding CH2I2 as the third solvent in the conventional DMF-DMSO system and (2) applying a controlled air-blowing step before photonic curing to remove excess solvent further. Combining these two approaches produces photonically- cured perovskite films with a comparable film roughness and device performance. Alkyl halide additives have been reported to enhance PSC performance by modulated solvent-solute interactions and C-X (X = Cl, Br, and I) cleavage. Photonic curing can cleave CH2I2, producing disassociated iodide ions to replenish iodine loss induced by photonic curing, which is confirmed by EDX. As a co-solvent, the high boiling point of CH2I2 can also make the solvent less volatile, reducing surface roughness in photonically cured perovskite films. Additionally, photonically-cured perovskite films have longer PL lifetimes and a higher recombination resistance compared to thermally-annealed counterparts. As a result, we demonstrate that photonic curing is a suitable method to replace thermal annealing in high-throughput PSC fabrication.

14 SOLAR ENERGY↗

Uncertainty Quantification of Fatigue Behavior of Rough AM Surfaces and Microstructures to Enable Hydrogen Gas Turbine

Modifying fossil-fueled industrial gas turbines to utilize low or zero-carbon fuels, such as hydrogen or hydrogen-natural gas blends, is a complex endeavor. The successful implementation of this technology hinges on three key design criteria: (1) developing new fuel injectors capable of efficiently burning alternative fuels, (2) ensuring manufacturability to meet cost and time-to-market goals, and (3) achieving component durability in the demanding environment of an operating gas turbine. Additive manufacturing (AM) accelerates product development, yet concerns persist regarding the durability of parts with rough AM surfaces. A fully experimental approach to quantify the fatigue performance of rough AM microstructures is both costly and labor-intensive. To address this, ORNL and Solar Turbines Incorporated (Solar) employed a crystal plasticity finite element (CPFE) model to identify the factors influencing AM surface fatigue behavior. These CPFE findings, combined with targeted experimental data, were used to develop a computationally efficient surrogate model suitable for assessing the lifespan of gas turbine engine components.

08 HYDROGEN↗