Rough Conditions Research Articles

Collaborative Production Planning Based on an Intelligent Unmanned Mining System for Open-Pit Mines in the Industry 4.0 Era

Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model’s potential to transform open-pit mining operations by using intelligent planning.

Experimental study on the static rolling friction coefficient of a flat-roller-flat configuration considering surface roughness

The friction-based seismic isolation technology is widely used in structural engineering. Despite the advantages and disadvantages of different types of isolated bearings, the coefficient of friction is a crucial factor that affects the seismic performance and stability of the isolation systems. In this study, a test apparatus with a flat-roller-flat configuration is developed to measure the static rolling friction coefficient (SRFC) of roller shafts. The SRFC under different conditions of normal load, material properties, geometry characteristics, and surface roughness are experimentally studied. The SRFC of the aluminum roller shafts ranges between 0.0020 and 0.0150, while that of the acrylic roller shaft ranges between 0.0028 and 0.0177, under low normal load level. The SRFCs of the roller shafts are positively correlated with the normal load and negatively correlated with their diameters. The surface roughness of the bottom plate significantly affects the SRFC. More precisely, the larger the surface roughness, the larger the SRFC. A theoretical model based on the elastic hysteresis theory is also proposed to predicted the SRFC. It is assumed that the elastic hysteresis loss coefficient (EHLC) is linearly correlated with the surface roughness of the bottom plate. Compared with the experimental results, the values predicted theoretically are within the error of 25 % for 85 % cases.

Three-dimensional modelling of artificial caves for geomechanical analysis

Abstract. Accurate cave surveying is crucial for understanding their genesis, current state, and potential hazards, especially in challenging environments marked by limited accessibility and poor visibility. This study applies geomatics techniques, including Terrestrial Laser Scanning (TLS), SLAM-based Mobile Mapping Systems (MMS), and digital photogrammetry, to create three-dimensional models of artificial caves in Gravina in Puglia, Apulia region, southern Italy. The research aims to assess these methodologies' accuracy, reliability, and performance for structural monitoring and hazard assessment. Despite challenges such as rough conditions, limited accessibility and poor visibility, the study reveals promising insights into the capabilities of these techniques for efficient surveying in complex underground environments. While highlighting the potential of MMS for cost-effective and rapid data acquisition, digital photogrammetry using spherical cameras also emerges as a viable alternative, offering comprehensive data collection capabilities with minimal capture time. Further research is warranted to optimize these techniques for enhanced hazard assessment and structural monitoring in challenging underground environments.

Film Cooling Performances Under Various Upstream Roughness Conditions: Experimental Investigations and Similarity Hypothesis

Abstract Roughness caused by deposition, erosion, and additive manufacturing can significantly affect gas turbine efficiency. Previous research has often examined film cooling performance under limited roughness configurations, resulting in inconclusive findings. In this study, film cooling performances under various upstream roughness conditions were investigated to simulate the roughness-affected film cooling performance of the suction side and the endwall. Three roughness heights (k/D = 0.1, 0.2, and 0.4) and shapes (ks/k = 0.17, 0.67, and 1.95) were selected to cover a wide range of surface roughness characteristics. Three blowing ratios were examined (M = 0.5, 1.0, and 1.5). The weakly roughened surfaces showed improved cooling effectiveness as k/D increased. Meanwhile, the moderately and severely roughened surfaces showed a decrease in cooling effectiveness with increasing k/D at M = 0.5 and 1.0 but an increase at M = 1.5. Cases with shallower and higher roughness elements at M = 1.5 outperformed the smooth plate. Subsequently, a similarity hypothesis for film cooling effectiveness was proposed. At all blowing ratios, the scaled cooling effectiveness profiles converged around the smooth plate results for ks/D < 0.391, encompassing common turbine roughness scales, including irregularly roughened surfaces. Deviations emerged at ks/D = 0.782, and they were correlated with the deteriorated regions observed at various blowing ratios. Ensemble-averaged scaled cooling effectiveness exponentially grew with increasing roughness scale for all blowing ratios, and empirical expressions based on smooth plate result and roughness scale were proposed.

Assessing the impact of vortex generators on the dynamic stall behaviour of a thick airfoil

Modern slender wind turbine blades use thick inboard airfoils and thicker trailing edges prone to flow separation. The increasing size of these flexible blades amplifies the importance of considering unsteady aerodynamics during the design phase. Environmental conditions result in Leading Edge Erosion (LER), further complicating the sectional unsteady aerodynamic behaviour. Although vortex generators are a well-studied method for passive separation control under steady conditions, their influence on unsteady aerodynamics for clean and rough blade sections is an area that requires further exploration. While some numerical studies exist, reliable experimental data is lacking in the literature. This work presents experimental results on the dynamic stall behaviour of a DU97W300 airfoil, a typical thick root section. The investigation covers both clean and rough conditions, both with and without VGs, to create an understanding of how VGs impact dynamic stall. Moreover, various VG array configurations are used to study the parametric dependence of dynamic stall phenomena on the VG array parameters.

Analyses of non-clean surface compressor blade cascades’ aerodynamic performance deterioration

Abstract The efficiency and dependability of the engine are directly impacted by the compressor’s performance, which is a crucial part of gas turbines. The blade cascade is significantly influenced by surface roughness in terms of flow characteristics and aerodynamic performance. In this study, the NACA65-410 airfoil is selected as the research object to investigate the variations in blade cascade performance and flow characteristics under different inflow and roughness conditions. The results show that the smooth surface blade cascade performs optimally when the Reynolds number increases from 120,000 to 200,000. As the angle of attack increases from -5° to 8°, the blade cascade performance deteriorates, and the degree of performance degradation increases with the increase in angle of attack. For the roughened blade cascade surface, the performance initially improves and then decreases as the equivalent sand grain density increases, and there exists a critical equivalent sand grain density that maximizes the blade cascade performance. When the Reynolds number is 120,000, the critical equivalent sand grain density is 225 μm, and when the Reynolds number is 160,000, the critical equivalent sand grain density is 111 μm. Based on the findings of this study, the degradation pattern of blade cascade performance can be predicted, and it can be utilized to enhance the overall performance of the compressor.

Impact of random nanoscale roughness on gas-scattering dynamics.

The impact of nanoscale wall roughness on rarefied gas transport is widely acknowledged, yet the associated scattering dynamics largely remain elusive. In this paper, we develop a scattering kernel for surfaces having nanoscale roughness that distinctly characterizes the two major types of interactions between gas molecules and rough surfaces. Namely these are (a) the weak perturbations arising from the thermal motion of wall atoms, essentially gas-phonon collisions, which are captured by the well-established Cercignani-Lampis model, and (b) the hard collisions owing to the irregularities of the rough, static potential energy surface, which are generally described by the fully diffuse model. Drawing an analogy between wave-surface and gas-surface scattering, a pseudo Debye-Waller factor is incorporated into the modeling as a weighting coefficient to allow the transition between smooth and rough surface conditions. The proposed scattering kernel is validated through high-fidelity molecular dynamics simulations that are performed for systems with varying roughness, temperature, and gas-surface combinations. The results indicate that the model well captures the scattering dynamics of gas molecular beams impinging on surfaces at different velocities, specifically for the accommodation coefficients and reflection patterns. Additionally, in flow and heat transport cases, it accurately predicts macroscopic quantities such as velocity slip and temperature jumps across the range of tested conditions.

Effect of Hydrogen Charging on the Mechanical Properties of High-Strength Copper-Base Alloys, Austenitic Stainless Steel AISI 321, Inconel 625 and Ferritic Steel 1.4511

Hydrogen embrittlement (HE) poses the risk of premature failure for many metals, especially high-strength steels. Due to the utilization of hydrogen as an environmentally friendly energy source, efforts are made to improve the resistance to HE at elevated pressures and temperatures. In addition, applications in hydrogen environments might require specific material properties in terms of thermal and electrical conductivity, magnetic properties as well as corrosion resistance. In the present study, three high-strength Cu-base alloys (Alloy 25, PerforMet® and ToughMet® 3) as well as austenitic stainless AISI 321, Ni-base alloy IN 625 and ferritic steel 1.4511 are charged in pressurized hydrogen and subsequently tested by means of Slow Strain Rate Testing (SSRT). The results show that high-strength Cu-base alloys exhibit a great resistance to HE and could prove to be suitable for materials for a variety of hydrogen applications with rough conditions such as high pressure, elevated temperature and corrosive environments.

Rolling Mechanism of Launch Vehicle during the Prelaunch Phase in Sea Launch

During the sea launch of a launch vehicle in low sea state, a rolling phenomenon of the launch vehicle has been observed. In rough sea conditions, launch may failure. This study utilizes dimensionality reduction-driven spatial system projection methods and virtual prototype modeling technology to reveal that the launch vehicle’s rolling is caused by differences in the motion paths of the center of mass. Additionally, during the prelaunch stage, the variation in the trajectory of the launch vehicle’s center of mass caused by the rolling and pitching motions of the transportation vessel has a significant impact on the roll motion of the launch vehicle. The motion in other degrees of freedom has minimal influence on the launch vehicle’s rolling. The minimum rocket rolling occurs when the dynamic coefficient of friction of the launchpad–launch vehicle contact is 0.05, and the dynamic coefficient of friction of the adapters and guideways is 0.4. The conclusions provide a theoretical foundation for optimizing the sea launch system and enhancing the reliability of sea launch in rough sea conditions.

Genetic characterization and clinicopathological features of <em>Escherichia coli</em> in neonatal septicemic calves

Due to severe diarrhea associated with calf scour and septicemia, colibacillosis is one of the leading causes of neonatal mortality in calves. This study investigated the clinical and hematological manifestations as well as the genetic composition of Shiga toxin-producing E. coli (STEC) strains in septicemic neonatal calves. In this study, 47 fecal specimens were collected from diarrheic calves aged between one and three weeks on dairy farms that are unorganized around Basra, Iraq, while twenty age-matched calves were tested as controls. Of the 47 tested samples, 28 fecal samples were tentatively identified as STEC, with a prevalence of 60%. STEC-affected calves had variable rectal temperatures ranging from subnormal to fever, tachycardia, hyperpnea, diarrhea, partial or complete cessation of suckling, mucous membrane congestion, depression, incoordination and rough hair coat conditions. Significant changes were observed in the hemogram and the leukogram during the analysis of blood samples from calves with diarrhea. Molecular analysis of fecal samples demonstrated that local STEC isolates are more closely related to other strains obtained from both human and animal samples worldwide. Based on the results of the current study, we can conclude that the septicemic calves were likely infected by human or environmental resources and could play a major role in further spreading STEC infection.

Investigation of lubricant viscosity and third-particle contribution to contact behavior in dry and lubricated three-body contact conditions

The generation of third particles and change in viscosity lead to the gradual degradation of the performance of the machine interface. The generation of third particles may come from wear debris or environmental particles, which form a three-body contact system at the contact interface. The viscosity of the lubricant will also change with the long-term operation of the components. This paper uses a three-body lubrication model to study the influence and interaction of lubricant viscosity change and the presence of third particles on the contact characteristics, including the real contact area, the particle contact area ratio, the solid load percentage, the film thickness, and the evolution of the lubrication regime. The results show that when the interface is in a three-body mixed lubrication regime, the dimensionless total real contact area increases with the increase in particle size and density at the same lubricant viscosity, while the trend is the opposite in dry contact and boundary lubrication interfaces. When viscosity decreases, a three-body contact interface is more prone to entering boundary lubrication than a two-body contact interface, resulting in surface damage. Regardless of surface roughness, particle size, and dry or lubricated contact conditions, the turning point of the contact area (TPCA) phenomenon is usually when the ratio of particle size to surface roughness is 0.8–1.3. Under the same ratio of particle size to surface roughness, the critical load of the TPCA phenomenon increases with the increase in third-particle size and surface roughness, but decreases with the increase in lubricant viscosity and particle density.

Microscopic insights of phase-transition-induced vapor transport enhancement in porous media

Vapor transport in porous media, often associated with liquid-vapor phase change, is an fundamental process in many emerging underground energy storage and extraction processes (i.e., seasonal solar thermal aquifer storage, geothermal extraction, extraterrestrial in-situ water extraction). By jointly using experimental imaging and numerical modeling at the micro-scale, we conduct mechanistic pore scale investigation of capillarity-dominated phase change dynamics and its influence on vapor transport in partially saturated porous rock micromodel. Strongly linked to surface roughness and wettability condition, the capillarity hinders water vaporization from rock surface micro/nano-structures as observed under the environmental scanning electron microscope. By varying the contact angle of 0°, 60°, and 120°, the lattice Boltzmann simulation shows the wettability-dependent vaporization process of capillary-hold water, where pores with hydrophilic surfaces contains significantly more liquid water than that of the hydrophobic ones under the same temperature. When saturated vapor flows through rock porous patterns, capillarity further induces water condensation on the strongly water-wet surfaces. Water condensation, yet forming water bridges/islands and causing the blockage of vapor diffusion, enhances the vapor diffusion ability counterintuitively. The reduction of diffusion path is revealed as the main reason by assessing the local vapor pressure distribution before and after the pore filling by condensate. The findings support the debatable enhancement mechanisms postulated by Philip and de Vries. This work offers the insightful interfacial hydrodynamics of vapor transport in porous media and potentially provides operational guidance for geothermal applications and beyond.

Deformation of vegetated channel bed under ice-covered flow conditions

A common feature of cold regions is the presence of ice cover on water surface. In the presence of vegetation in the channel bed which is normally leafless in winter, interaction between river ice and vegetated channel bed becomes very complex. In the present study, the impacts of ice cover and submerged leafless vegetation on channel bed deformation and flow resistance have been investigated based on 144 experiments conducted in a large-scale outdoor flume. The independent variables associated with the maximum scour depth around vegetation elements have been assessed and equations have been developed. Results indicate that the most important variable affecting the maximum scour depth around vegetation under ice-covered flow conditions is the ratio of the ice cover roughness to the bed roughness (ni/nb). However, under open channel flow conditions, the flow Froude number is the most important variable influencing the maximum scour depth. The methods based on the law of the wall provide reliable Manning's coefficient for both smooth and rough ice covers in the presence of submerged vegetation in the channel bed. As the vegetation density increases, the size of scour holes becomes smaller. With the increase in vegetation density, the median grain size of the armour layer in scour holes decreases correspondingly. When vegetation elements are placed in a staggered configuration, the median grain size of the armour layer in scour holes is less than that of squared configuration of vegetation elements. Regardless of the roughness of ice cover on water surface and the grain size of sediment in the bed, the maximum depth of scour holes always occurs at the upstream front face of each vegetation element. Under the rough ice-covered flow condition, the maximum depth of scour holes is more than that under the smooth ice-covered and open flow conditions.

Синтез параметрически грубых систем управления с регуляторами и наблюдателями состояния на основе грамианных технологий

Automatic control systems based on regulators with state observers are effective means to control linear and linearized objects of a high degree of complexity. One of the key problems in the synthesis of modal systems is the development of parametrically rough (robust) systems that retain their performance, as well as the main quality indicators with possible variations of the parameters of both the control object and the controller itself. The synthesis of a robust system with a state observer is carried out by the modal control method based on the matrix model of the controlled object. To ensure the parametric robustness of the system, the authors have proposed a technique which based on the mathematical apparatus of Gramians of controllability and observability as well as on the similarity transformation of observer matrices. Computer simulation of the system with state controller and observer is carried out by means of the MatLab software. The authors have proposed a method to form an observer state structure that is optimal in the sense of parametric roughness of the system, which is based on the procedure of transforming the similarity of the object model. And the transformation matrix is formed by varying the singular numbers of the controllability and observability gramians. The proposed method allows us to obtain an observer structure with a certain ratio of controllability and observability that ensures the fulfillment of the condition of parametric roughness i.e., the absence of positive feedback in the control device. The results obtained make it possible to clearly demonstrate the high efficiency of using the Gramian method for the synthesis of control systems with state observers with low sensitivity to variations of the controller own parameters.

Hole Edge Metrology and Inspection by Edge Diffractometry

Abstract This article introduces a novel hole edge inspection and metrology technology by edge diffractometry, which occurs when light interacts with the hole edge. The proposed method allows for simultaneous characterization of hole part error and edge roughness conditions. Edge diffraction occurs as light bends at a sharp edge. Such a diffractive fringe pattern, the so-called interferogram, is directly related to edge geometry and roughness. Image-based diffractometry inspection technology was developed to capture the diffractive fringe patterns. The collected fringe patterns were analyzed through statistical feature extraction methods, and numerical results such as roundness index, concentricity, and via edge roughness (VER) were obtained. The results indicated that hole 1 had an average VER of 0.665 μm and a roundness index of 0.95, while hole 2 was measured an average VER of 0.753 μm and a roundness index of 0.96. Through-focus scanning optical microscopy (TSOM) was also utilized to perform three-dimensional characterization of hole features along the depth direction. As a result, the proposed method could characterize hole part error and evaluate its roughness conditions. This study showed the potential to be adapted for automatic optical inspection for advancing microelectronics and semiconductor packaging technology.

A three in one bottom-up framework for simultaneous semantic segmentation, instance segmentation and classification of multi-organ nuclei in digital cancer histology

Simultaneous segmentation and classification of nuclei in digital histology remains challenging. The highest achieved Panoptic Quality (PQ) remains low due to overlapping nuclei, higher staining and tissue variability, and rough clinical conditions. The generic deep-learning methods usually rely on end-to-end models, which fail to address these problems associated explicitly with digital histology. We resolve these issues using a dual attention-based model combined with post-processing in a bottom-up fashion. We use three attention decoder heads, which produce semantic segmentation, edge proposals, and classification maps. We use these outputs to apply post-processing, including controlled watershed and pixel grouping, to produce instance segmentation and classification. Our multi-stage approach utilizes edge proposals and semantic segmentations compared to direct segmentation and classification strategies followed by most generic state-of-the-art methods. Due to this, we demonstrate a significant performance improvement in producing high-quality instance segmentation and nuclei classification. We have achieved a 0.841 Dice score for semantic segmentation, 0.713 bPQ scores for instance segmentation, and 0.633 mPQ for nuclei classification. Furthermore, the framework is less complex compared to the state-of-the-art.

A long sequence time-series forecasting model for ship motion attitude based on informer

Influenced by marine environmental factors, a ship sailing at sea will experience six degrees of freedom oscillating motions. These oscillating motions pose safety risks to ship navigation and maritime operations. Especially in severe weather conditions, these oscillating motions have a significant impact on the takeoff and landing of carrier aircraft, as well as the launch of carrier missiles. Therefore, studying and forecasting the ship motion attitude in wind and waves holds immense significance. This paper presents a sparrow search algorithm (SSA) optimized Informer model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to forecast the long sequence time-series of ship motion attitude. Firstly, the ship motion attitude time series, as measured by the inertial navigation system, is decomposed using CEEMDAN to obtain several intrinsic mode functions (IMFs) and a residual. Then, the IMFs and residual are fed into SSA-Informer, where SSA is used to optimize the hyperparameter of Informer. Finally, the forecast values of IMFs and residual are superimposed and reconstructed to get the ship motion attitude forecasting result. The forecasting experiment under slight, moderate and rough sea conditions in the East China Sea shows that the proposed model achieves better performance and longer forecasting time compared with other popular methods.

A stereovision-based efficient measurement approach for surface flatness of concrete members

The surface flatness of concrete members is an important quality characteristic of buildings and civil infrastructure. Existing measurement methods such as the straightedge method, F-numbers method, and laser scanning method have various limitations such as inefficiency in engineering practices, low accuracy, and high costs. Therefore, this paper presents a novel stereovision-based system comprising two industrial cameras and one projector alongside optimized algorithms to efficiently measure the surface flatness of concrete member. The proposed system is highlighted by effective feature point extraction and matching algorithms, the innovative introduction of feature point extraction error to system measurement error evaluation, and enriched flatness indicators to comprehensively assess surface flatness of concrete members. The outputs of the system, namely, the contour maps as visual demonstrations and the flatness indicator results, can collectively reflect various roughness conditions with high speed and precision. Experiments at multiple levels have validated the proposed algorithms and measurement system, showing that it is capable for providing fast and accurate measures for the surface flatness of concrete members. Further research and developments are sought in system optimization and expanding its applications to other structural members and engineering practices.

Turbulent Fluxes and Evaporation/Sublimation Rates on Earth, Mars, Titan, and Exoplanets

AbstractTurbulent fluxes of heat, momentum, and humidity in the atmospheric boundary layer are pivotal to the evolution of geology, weather and climate, and the possibility of life. Here we extend recent advances in calculating these near‐surface turbulent fluxes in the Earth's atmospheric boundary layer to any terrestrial planetary body with an atmosphere. These improvements include: (a) incorporating Monin‐Obukhov similarity functions that encompass the entire range of atmospheric stability expected on terrestrial planetary bodies, (b) accounting for the additional shear associated with buoyant plumes under unstable conditions, (c) using surface renewal theory to calculate transfer rates within the interfacial layer adjacent to the surface, and (d) explicitly accounting for key humidity effects that become especially important when a volatile is more buoyant than the ambient gas (e.g., on Mars where H2O is lighter than CO2). We tested and validated our model using in situ data collected on Earth, Mars, and Titan under a wide range of atmospheric stability, pressure, and surface roughness conditions. The model shows up to 71% better agreement with measurements compared to methods commonly used on Mars for evaporation/sublimation. Compared to previous estimates for H2O ice on Mars, our model predicts up to 1.5–190x lower latent heat fluxes under stable atmospheric conditions (depending on the wind speed) and 1.78x higher latent heat fluxes under unstable conditions. Our results provide improved constraints on the stability of ice on Mars and will help determine whether ice can melt under present‐day conditions.

Optimization of insert roughness and pouring conditions to maximize bond strength of (Cp)Al-SS304 bimetallic castings using RSM-GA coupled technique

The integration of ferrous and non-ferrous materials represents a breakthrough in materials technology, enabling the fabrication of functionally graded lightweight components with enhanced properties. In this study, a Box-Behnken design of experiments was employed to investigate the effects of pouring temperature, insert temperature, insert thickness, and surface roughness on the bond strength of bimetallic components. Shear punch tests were conducted to assess the maximum loads before fracture, with the highest bond strength of 17.04 MPa achieved under specific processing conditions. The presence of intermetallic compounds, including Fe2Al5, FeAl2, and Fe4Al13, contributed to the observed increase in reaction layer thickness. Response surface methodology revealed concentric responses for pouring temperature and surface roughness with an optimal predicted bond strength of 18.02 MPa. Further optimization using Genetic Algorithm resulted in a maximum bond strength of 19.20 MPa. These findings demonstrate the potential for producing high-performance bimetallic components tailored for applications in various industries.