Roughness Coefficient Research Articles

Experimental Study of Energy Evolution at a Discontinuity in Rock under Cyclic Loading and Unloading.

Energy is often dissipated and released in the process of rock deformation and failure. To study the energy evolution of rock discontinuities under cyclic loading and unloading, cement mortar was used as rock material and a CSS-1950 rock biaxial rheological testing machine was used to conduct graded cyclic loading and unloading tests on Barton’s standard profile line discontinuities with different joint roughness coefficients (JRCs). According to the deformation characteristics of the rock discontinuity sample, the change of internal energy is calculated and analyzed. The experimental results show that under the same cyclic stress, the samples harden with the increase in the number of cycles. With the increase of cyclic stress, the dissipated energy density of each stage gradually exceeds the elastic energy density and occupies a dominant position and increases rapidly as failure becomes imminent. In the process of increasing the shear stress step-by-step, the elastic energy ratio shows a downward trend, but the dissipated energy is contrary to it. The energy dissipation ratio can be used to characterize the internal damage of the sample under load. In the initial stage of fractional loading, the sample is in the extrusion compaction stage, and the energy dissipation ratio remains quasi-constant; then the fracture develops steadily, the damage inside the sample intensifies, and the energy dissipation ratio increases linearly (albeit at a low rate). When the energy storage limit is reached, the growth rate of energy dissipation ratio increases and changes when the stress level reaches a certain threshold. The increase of the roughness of rock discontinuity samples will improve their energy storage capacity to a certain extent.

Experimental Investigation and Performance Optimization during Machining of Hastelloy C-276 Using Green Lubricants.

Smart manufacturing is the demand of industry 4.0, in which the mass production of difficult-to-cut materials is of great concern to fulfil the goal of sustainable machining. Presently, the machining of superalloy is of upmost interest because of its wide application. However, the limited data on the turning of Hastelloy C-276 highlights its challenges during processing. Hence, the machining performance of superalloy considering surface quality, thermal aspects and chip reduction coefficient was examined with minimum quantity lubrication of several oils to address the sustainable development goal (SDG-12). The output responses were optimized through response surface methodology along with analysis of variance. The research exhibited that the output responses were dominated by cutting speed and feed rate having a percentage benefaction of 24.26% and 60%, respectively, whilst the depth of cut and lubricant type have an influence of 10–12%. No major difference in temperature range was reported during the different lubrication conditions. However, a substantial variation in surface roughness and the chip reduction coefficient was revealed. The percentage error evaluated in surface roughness, temperature and chip reduction coefficient was less than 5%, along with an overall desirability of 0.88, describing the usefulness of the model used. The SEM micrograph indicated a loss of coating, nose and flank wear during all lubrication conditions. Lastly, incorporating a circular economy has reduced the economic, ecological and environmental burden.

Prediction of PM2.5 concentrations using soft computing techniques for the megacity Delhi, India

Over the past few years, the concentration of fine particulate matter (PM2.5) in Delhi’s atmosphere has progressively increased, resulting in smog episodes and affecting people’s health. Therefore, accurate and reliable forecasting of PM2.5 concentration is essential to guide effective precautions before and during extreme pollution events. In this work, soft computing techniques, including Artificial Neural Network and Gaussian Process Regression are employed to predict PM2.5 concentrations in Delhi. Four models, namely, multi-layer feed-forward neural network (MLFFNN), General regression neural network, Gaussian process regression with ARD squared exponential kernel (GPARD_sqexp) and Gaussian process regression with ARD rational quadratic kernel (GPARD_rat_quad) are built using meteorological and air quality data corresponding to a two-year period (2015–2016). The results of the study suggested that MLFFNN showed the best prediction performance among the four models, with testing correlation coefficient (R) 0.949, Root mean square error 30.193, Nash–Sutcliffe efficiency index 0.892 and Mean absolute error 18.388. Moreover, sensitivity analysis performed to understand the importance of different input variables reported that PM10, wind speed, air quality index and aerodynamic roughness coefficient (Z0) are the most critical parameters influencing MLFFNN model forecasts. On the whole, the work has demonstrated that the artificial neural network model is more capable of dealing with PM2.5 forecasting in Delhi urban area than the Gaussian process regression model.

A solution algorithm for finding the best and the worst fuzzy compromise solutions of fuzzy rough linear programming problem with triangular fuzzy rough number coefficients

A solution algorithm for finding the best and the worst fuzzy compromise solutions of fuzzy rough linear programming problem with triangular fuzzy rough number coefficients

Joint roughness profiling using photogrammetry

We propose an automated camera setup for photogrammetric roughness analysis in the laboratory environment. The developed fast and low-cost automation setup can be very useful for tedious and laborsome manual field logging practices. The photographs are processed in MATLAB to obtain disparity maps. Coding routines for stereo photogrammetry and digital measurements are written in MATLAB. Secondly, 6 effecting factors (projecting an image onto core face, depth of field, brightness, camera-to-object to baseline distance ratio, projected image size, and occlusion) influencing noise in roughness depth maps computed by employing stereo photogrammetry are investigated. After deciding the best values that allow the lowest amount of noise, depth maps of 6 core faces are computed. Using the 3D point cloud generated, roughness profile measurements are made. Then, 8 profile measurements are made for each core face, both manually and digitally. The accuracy of the disparity maps has been verified by comparing 48 joint roughness coefficient (JRC) measurements made manually using a profile gauge. It was proved that surface roughness can be measured very fast in millimetric accuracy with an average root mean square error (RMSE) of 3.50 and mean absolute error (MAE) of 3.02 by the help of the proposed set-up and calibration.

Modelling and analysis of longitudinal-vertical coupling dynamics for the tracked vehicle on uneven roads

In this paper, a longitudinal-vertical coupling dynamic model of a tracked vehicle under uneven road conditions is established. The torsion suspension forces and torques generated by the torsion bar springs and torsion shock absorbers are considered in the present model. The tracked vehicle’s longitudinal acceleration and velocity change at the same time as the vehicle heaves under the excitation of uneven road terrain. The vehicle’s longitudinal-vertical coupling dynamics are explained elementarily by analysing the longitudinal and vertical dynamics of a road wheel based on the road wheel force model. From the coupling tracked vehicle model, the dynamic responses of the vehicle in the vertical and pitch directions as well as the longitudinal direction are investigated. The vehicle dynamics characteristics are compared with those obtained by Recurdyn simulation. The results indicate that the proposed dynamic model performs well in predicting the dynamic characteristics of the tracked vehicle on uneven roads. By means of the coupling dynamic model, the influences of vehicle speed and road conditions on the vehicle’s longitudinal dynamics are further studied. It has been found that both a higher velocity and a larger roughness coefficient will lead to a negative longitudinal acceleration with larger absolute value.

Empirical roughness coefficients for moderate floods in an open conduit cave: Fullers stream canyon, Culverson Creek Cave System, West Virginia

Open conduit modeling of cave stream floods can yield useful information about water velocities and shear stresses, which can in turn be used to estimate sediment transport capabilities. All such calculations require roughness coefficients for estimating energy losses and a priori knowledge of either discharge or flow depths to set model boundary conditions. However, the difficulties associated with observing in-cave floods generally preclude measuring discharge; roughness coefficients must be assumed based on channel properties. To overcome these challenges, we monitored stream flow depths in Fullers Cave, Greenbrier County, West Virginia using pressure transducers, and simultaneously measured stage and discharge in a karst window immediately upstream of the cave. Five pressure transducers were deployed opportunistically along a 93-meter-long reach in a 10+ meter high canyon averaging 1.5 to 3 meters wide. Stage-discharge relationships were determined for the karst window using an electromagnetic flow meter for floods with peak discharges of 1.66 m3 s-1 or less. The collected data was used to obtain the empirical Manning’s n roughness values, head losses, and energy gradients. Calculated floodwater velocities are comparable to values obtained from scallops on passage walls. Major energy losses were observed where breakdown partially occludes the passage. At peak flow, Manning n values average 0.053 for reaches typified as cobble-floored canyons, but n was 0.069 in the breakdown reach. Roughness values declined exponentially with increasing discharge, but friction slopes calculated using head losses show more complex relationships with discharge. Notably, n values back calculated using bed gradients differ from those calculated using measured head losses by as little as 12%, so the use of bed gradients in roughness estimations will generally yield reasonable approximations of flow conditions. Fullers Cave experiences significantly larger open conduit floods than we observed, so additional work is needed to estimate roughness coefficients for higher discharges. Our empirical roughness coefficients can be applied to similar cave passages in other caves and contexts, including modeling slot canyon-like channels, and our methods demonstrate a technique for measuring hard to obtain data. The addition of data for open conduit conduits significantly expands the range of environments that can be modeled using empirical data beyond pipe-full caves. Applications include studying flooding, sediment transport, and bedrock erosion process. All of these topics will be addressed in Fullers in the future.

Reconstruction of rough rock joints: 2D profiles and 3D surfaces

The 3D reconstruction of rock joint surfaces is crucial for quantifying rock joints. Through the uniform discretization of 2D and 3D rock joints, it was determined that both the climbing angles along the shear direction and the projection lengths of the consecutive ascending/descending segments follow normal distributions . This statistical distribution of climbing angles and projection lengths provides an important reference for rock joint reconstruction, although hypothesis testing indicated that some joint profiles/surfaces do not follow normal distributions. A normal distribution-based method and a bubbling method were used to reconstruct the 2D joint profiles. The bubbling method demonstrated good applicability for the generation of 3D rock joint surfaces, especially because it included surfaces with different roughness in two orthogonal directions. Therefore, ten typical 3D rock joint surfaces were reconstructed using the bubbling method, where both the size of asperities (waviness or unevenness) and the joint roughness coefficient values were quantified. To reconstruct a joint surface with a certain roughness coefficient, scaling the elevation of a generated surface was demonstrated as an effective supplementary approach. • Rock joints were statistically analyzed via normal distributions owing to a uniform discretization operation. • The normal distribution-based method and the bubbling method were both suitable for reconstructing 2D joint profiles. • The bubbling method could generate 3D joint surfaces with different roughness in two orthogonal directions. • Rock joints with different joint roughness coefficients were reconstructed by scaling their elevation coordinates.

An experimental study of the hydrodynamics and contaminant transport in a Y‐shaped confluence with flexible submerged vegetation

AbstractVegetation greatly affects the flow characteristics and contaminant transport in river confluences. In this study, the flow characteristics and contaminant transport in the non‐vegetated/vegetated Y‐shaped confluence were explored systematically through a series of experiments. A total of 10 scenarios were designed to answer the three main research questions: what is the difference between the flow characteristics and contaminant transport in (1) asymmetrical and Y‐shaped confluences; (2) non‐vegetated/vegetated Y‐shaped confluences; (3) vegetated Y‐shaped confluences with different confluence ratios? The experimental results revealed that vegetation remarkably changes the internal flow structure in Y‐shaped confluences. Briefly, the velocity profile can be divided into three vertical layers within the vegetated system, but it remains nearly constant in the non‐vegetated channel. Vegetation changes the circulation location and reduces the intensity of the secondary current, weakening the strength of contaminant mixing. However, the turbulent kinetic energy within the vegetated system is larger than that in the non‐vegetated case, and it peaks at the top of the vegetation canopy. Under different confluence ratio cases, the overall fluctuation of the longitudinal dispersion coefficients along the cross‐sections in the mainstream was similar but increasing the confluence ratio causes the circulation to appear to advance and enhances its intensity. In addition, the vegetation density (200 item/m2) in this study render the manning roughness coefficient at 0.068, which is larger than that under lower vegetation density cases. The outcomes from this study are helpful for both environmental and river management applications.

Probabilistic data-driven framework for performance assessment of retaining walls against rockfalls

Rockfall is a significant hazard to sites that are located at the foot of rock slopes. In such sites, there is a notable need to evaluate the potential for rockfall, estimate the extent of areas at risk, and design retaining structures to reduce the risk of rockfall-induced. This paper presents a probabilistic framework for predicting the formation and progression of rockfalls and for evaluating the performance of retaining walls under rockfalls. To this end, first a probabilistic model for the rock projectile motion on a slope is presented. The model accounts for prevailing uncertainties, i.e., the trigger points, rock shape, projectile path, and slope material properties, which include surface roughness, friction angle, and horizontal and normal coefficients of restitution. Next, Monte Carlo sampling is employed to propagate these uncertainties in the proposed model and generate a large dataset of rockfall realizations. The resulting dataset is subsequently utilized to develop an exceedance probability diagram of the rock endpoints, which is in turn used to estimate the location of the retaining wall for a target exceedance probability. Furthermore, the exceedance probability contours of the bounce height and the total kinetic energy of the rock in the projectile path are computed to produce the spatial variation of the exceedance probability at any desired location along the slope. Given the location of the retaining and the target exceedance probability, the probability contours are then employed to approximate the height and the structural capacity of the retaining wall to withstand the rock collision. Finally, a bivariate sensitivity analysis is performed to measure the performance of the retaining wall against the falling rocks and further evaluate the efficiency of the proposed probabilistic design.

A cluster-based drag model of rough sphere for the simulation of fast fluidization

The non-uniform flow caused by cluster greatly influences the performance in fast fluidization systems. Rough particles result in extra energy dissipation by particle rotation, which finally affects the cluster formation and evolution. In this study, the kinetic theory of rough sphere (KTRS) is employed and coupled with the cluster structure-dependent (CSD) drag model to consider the rotation effect on cluster formation, where the total granular temperature is introduced and the cluster-scale effect on the collision is incorporated. The effect of particle roughness on energy consumption is also discussed. The result demonstrates that the cluster-scale pressure plays an important role in the collision. The energy consumption is dependent on the particle roughness or tangential restitution coefficient. Meanwhile, the change of particle roughness also alters mesoscale parameters like cluster size and cluster solid concentration.

Evaluation of effective parameters of Manning roughness coefficients in HDPE culverts via kernel-based approaches

Abstract The prediction of Manning coefficients plays a prominent role in the estimation of head losses along culvert systems. Although the Manning coefficient is treated as a constant, previous studies showed the dependency of this coefficient on several parameters. This study aims to evaluate the effective parameters of the Manning roughness coefficient using intelligence approaches such as Gaussian process regression (GPR) and support vector machines (SVM), in which the input variables were considered as dimensionless and dimensional. In addition to the enhanced efficiency of the SVM approach compared to the GPR approach in model development with dimensionless input variables, the accuracy of model A(I) with input parameters of Fr (Froude) and y/D (the ratio of water depth to culvert diameter) and performance criteria of correlation coefficient (R) = 0.738, determination coefficient (DC) = 0.0962, root mean square errors (RMSE) = 0.0015 and R = 0.818, DC = 0.993 and RMSE = 0.0006 for GPR and SVM approaches were the highest. Thus, for the second category, a model with an input parameter of discharge (Q), hydraulic radius (RH), and culvert's slope (S0) showed good efficiency in predicting the Manning coefficient, in which the performance criteria of GPR and SVM approaches were (R = 0.719, DC = 0.949, RMSE = 0.0013) and (R = 0.742, DC = 0.991, RMSE = 0.007), respectively. Furthermore, developed OAT (one-at-a-time) sensitivity analysis revealed that relative depth y/D and Q are the most important parameters in the prediction of the Manning coefficient for models with dimensionless and dimensional input variables, respectively.

Seepage Characteristics Study of Single Rough Fracture Based on Numerical Simulation

Fracture seepage is an important aspect of groundwater research, but due to the closure of fractures and the randomness of wall surface roughness, it is a challenge to carry out relevant research. Numerical simulation serves as a good way to solve this problem. As such, the water flow in single fracture with different shapes and densities of roughness elements (various bulges/pits on fracture wall surfaces) on wall surface was simulated by Fluent software. The results show that, in wider rough fractures, the flow rate mainly depends on fracture aperture, while, in narrow and close rough fracture medium, the surface roughness of fracture wall is the main factor of head loss of seepage; there is a negative power exponential relation between the hydraulic gradient index and the average fracture aperture, i.e., with increase of rough fracture aperture, both the relative roughness of fracture and the influence of hydraulic gradient decrease; in symmetrical-uncoupled rough fractures, there is a super-cubic relation between the discharge per unit width and average aperture; the rough fracture permeability coefficient K is not a constant which is affected by the scale effect and the density of roughness elements. Results found provide further understanding of rough fracture seepage.

Fracture toughness and cracking behavior of frozen sandstone at different freezing temperatures

Fracture toughness and crack behavior of frozen rocks have an important guiding significance for engineering in cold regions, where the freezing temperature is one of the main factors that affect the mechanical properties of frozen rocks. Therefore, both mechanical properties (fracture toughness, compressive strength, and tensile strength) and pore phase composition of water-saturated sandstone at different freezing temperatures (0 °C, −2 °C, −4 °C, −6 °C, −8 °C, −10 °C, −12 °C, −15 °C, −20 °C) were tested in this paper. High-speed photography was used to capture the crack propagation process of the semi-circular bending (SCB) specimen. Also, morphological characteristics of the fracture surface under different freezing temperatures were analyzed. The results show the following: (1) The fracture toughness of saturated sandstone increases exponentially with the decrease of freezing temperature, reaching an increase of 402 % at −20 °C. (2) When the freezing temperature decreases from 0 °C to −8 °C, the crack growth rate increases rapidly. (3) The fracture surface roughness coefficient (Rs) of the SCB specimen shows a two-stage decreasing trend: a rapid decrease (0 °C to −8 °C), and a slow decrease (−8 °C to −20 °C). (4) The change of phase composition with freezing displayed two distinct stages: the unfrozen water content decreases rapidly and the ice content increases rapidly (0 °C to −4 °C) and then the unfrozen water content decreases slowly and the ice content increases slowly (−4 °C to −20 °C). Based on the above test results, we suggest that: (1) With the decrease of the freezing temperature, the pore phase composition changes significantly, resulting in enhanced mechanical properties of the rock. (2) The cementation and filling effect of pore ice reduce the dissipative energy in the process of crack expansion, increasing the brittleness index, so the crack growth rate of the SCB specimens increases rapidly.

Effects of Bed Materials to Flow Characteristics on Open Channel and Gradually Varied Flow Simulation Using Genetic Algorithm (GA)

Determination of accurate roughness coefficient was realized necessary for hydraulic parameters estimation in open channel flow. For the purpose this study was planned to carry out on experimental basis in hydraulic laboratory hall of campus itself. In this study, a combination between experimental and numerical models study were carried out to investigate the influence of bed roughness on flow characteristics. Experiments were conducted on six bed materials (Sand, Gravel, Cement plaster, Grass, Formica and cast iron (original bed of channel)) in three conditions. Firstly the discharge was varied at same tail water level. Secondly the depths were varied for same discharge and thirdly the depths were measured for different discharges for each bed material Results were analyzed and were graphically presented .The Manning roughness coefficient was estimated for each bed material using the experimental and discharge optimization technique. The percentages of errors between the observed and predicted were reported. Since the channel represents compound case having glass wall and different bed material, the roughness coefficient of each bed materials were predicted by optimization on genetic algorithm to the lotter’s modified equation in which the exponent alpha value varies from 1.28 to 1.76 The shear stress distribution was examined by first and second approximation theory on smooth rectangular channel on Knight et al (1984) model. It was compared with the experimental average shear stress and was found the first approximation theory over estimated to the experimental value whereas second approximation result was within the average relative error of 1.61% for bed. Side wall/bed stress ration was found of 0.61. Similarly gradually varied flow was simulated in python using optimal value of roughness coefficient.

Quantitative De Giorgi methods in kinetic theory

We consider hypoelliptic equations of kinetic Fokker-Planck type, also known as Kolmogorov or ultraparabolic equations, with rough coefficients in the drift-diffusion operator. We give novel short quantitative proofs of the De Giorgi intermediate-value Lemma as well as weak Harnack and Harnack inequalities. This implies H{o}lder continuity with quantitative estimates. The paper is self-contained.

Assessment of Uncertainty in Grid-Based Rainfall-Runoff Model Based on Formal and Informal Likelihood Measures

Damage prevention from the local storms and typhoons in Korea, the development of a rainfall-runoff model reflecting local geological, meteorological and physical characteristics is necessary. The accuracy of the rainfall-runoff model is influenced by the various uncertainty factors that can occur in the modeling processes, including input data, model parameters, modeling simplification, and so on. Thus, the objectives of this study are (1) to estimate runoff for two rainfall events using Grid Rainfall-Runoff Model (GRM); (2) to quantify the uncertainty of the GRM model using the Generalized Likelihood Uncertainty Estimation (GLUE) method, and (3) to assess the uncertainty ranges of the GRM based on different likelihood functions. For this, two rainfall events were implemented to the GRM in the Cheongmicheon watershed, and informal likelihood functions (LNSE, LPBIAS, LRSR, and LLOG) based on the fitness indices (NSE, PBIAS, RSR, and Log-normal) were used for uncertainty analysis and quantification using GLUE method. As a result, the GRM parameters varied according to the different rainfall patterns even in the same watershed. In addition, among the GRM parameters, the CRC (Channel Roughness Coefficient) and CSHC (Correction factor for Soil Hydraulic Conductivity) characteristics are the most sensitive. Moreover, this study showed that the uncertainty range of the GRM model can be changed with the subjective selection of likelihood functions and thresholds. The GRM model is open source and has good accessibility. Especially, this open-source model allows various approaches to disaster prevention plans such as flood forecasting and flood insurance policies. In addition, if the parameter range of GRM is quantified and standardized at domestic watersheds, it is expected that the reliability of the rainfall-runoff simulation can be increased by the reduction of the uncertainty factors.

Fretting wear mechanical analysis of double rough surfaces based on energy method

A fretting wear model of a rough surface that conforms to the actual situation is established to accurately reveal the wear mechanism of the connection structure. In the ABAQUS software, the UMESHMOTION subroutine and the energy dissipation model are used to simulate the fretting wear of double rough surfaces. The new model, a single rough surface model, and a smooth model are compared to analyze their differences. In addition, the influence of surface roughness, material, and friction coefficient on the fretting wear of rough surfaces is systematically explored through finite element simulation. The results show that the model's reliability has been verified through Hertz's theory and experiments. The stress and wear of the contact surface are more realistically reflected by the double roughness model. Besides, with the increase of surface roughness and material rigidity and the decrease of friction coefficient, the wear of the double rough surface model becomes more severe. The research work provides a theoretical basis for the design and performance prediction of the connection structure.

Derivation, Validation, and Numerical Implementation of a Two-Dimensional Boulder Transport Formulation by Coastal Waves

Numerical computations for boulder transport have become a state-of-the-art tool for hindcasting the hydraulic processes associated with past storm wave and tsunami events. Since most previously developed two-dimensional formulations cater to boulders with symmetric outlines, they can consequently reproduce the transport distance and the velocity of boulders of cubic shape or similar structured geometries reasonably well. However, the formulations exhibit limitations when applied to rectangular- and flat-shaped boulders. The presently available formulations have difficulties reproducing the variations of frictional drag force due to the changes of the boulders’ contact time with the ground. We have developed an extended boulder transport formulation and derived a new empirical roughness coefficient by considering the shape of boulders that accounts for the changes of the boulders’ contact time with the ground. In comparison to other existing transport formulations, the present method provides superior accuracy of block velocity and transport distance in most cases — especially for boulders of rectangular geometry. Even by neglecting the full three-dimensional processes, numerical computations extended with the proposed boulder transport formulation can help explaining historic wave regimes, which were responsible for the transport of a variety of coastal boulders reported around the world.

A fractal friction model for nanoscale rough surface contact

In ultra-precision equipment, nanoscale rough surface contact widely exists, and the adhesion between interfaces has become a critical component in researching the friction phenomenon. However, adhesion is not considered in traditional friction models. In this study, the adhesion model between fractal contact surfaces is established by proposing the critical truncated area of adhesion, acut′, and a new friction model considering adhesion is established by combining with the traditional model. The present model shows that adhesion increases as the fractal dimension (D) increases or the surface roughness coefficient (G) decreases when contact occurs between nanoscale rough surfaces. The friction coefficient calculated based on the new model is larger than that of the traditional model, especially when G is small. In addition, a static friction force measurement system was built by using the reticle and vacuum chuck in the lithography system. The experimental system measured the maximum static friction between the chuck and the reticle under different normal loads, and the experimental results show that the new model proposed in this paper is more accurate in characterizing the static friction of nanoscale rough surfaces.