Calculation Of Velocity Research Articles

Self-supervised learning waveform inversion for seismic forward prospecting in tunnels: A case study in Pearl River Delta Water Resources Allocation Project in China

Tunnel and underground engineering construction often encounter unfavorable geology, leading to disasters such as water and mud inrushes and landslides. To prevent geologic hazards, it is important to look ahead and predict the location and distribution of adverse geology ahead of the tunnel face. This process is known as seismic forward prospecting in tunnels, and it typically requires an accurate calculation of velocity. Seismic waveform inversion methods based on deep learning have demonstrated potential in estimating velocity from synthetic seismic data. However, the superiority of these methods over traditional ones on field data is still an area of active research. Here, the Pearl River Delta Water Resources Allocation Project in China is used as an example to develop a self-supervised learning waveform inversion method for building a reliable velocity distribution in front of the tunnel. By introducing the background velocity as large-scale information and implementing multiscale loss functions, the previous self-supervised learning inversion method on synthetic data is improved. In addition, the corresponding network-based workflow for field data is developed. To demonstrate the effectiveness of our method, a comparison is conducted with practical tunneling exposure, for which the low-velocity zone corresponds with the fault-fractured zones and the water-flowing zones. This indicates that the results obtained from our method can be used as geologic guidance for safe tunneling practices. In the end, the applicability and disadvantages of our deep-learning inversion method for seismic forward prospecting in tunnels are discussed.

A muon high-resolution pseudorange measurement method: Application to muon navigation in confined spaces

Confined spaces such as polar regions, deep earth and deep ocean are crucial navigation scenarios where traditional navigation techniques have difficulty in obtaining external signals for positioning. The cosmic ray muons, which carry the spatial and energetic information, are easy to penetrate these confined spaces. Therefore, the unique muon characteristic provides a new perspective to estimate detector position, which can be considered using in confined spaces navigation. In this paper, a well-developed theory of muon navigation is established by combining a muon pseudorange measurement method. Moreover, an Equivalent Velocity Calculation Model (EVCM) and a Muon Sequence Matching Technology (MSMT) are proposed. The first model corrects flight pseudorange error caused by the relativistic energy loss and the second technology compensates the random error in pseudorange measurement. Further, a series of simulations are performed to analyze the muon events number which can be received by detector in different scenarios with the variations of zenith angle, detector area, varied detector plates gap, and muon flight distance. Meanwhile, the simulation results demonstrate that the muon navigation update rate every 10 minutes can reach 5.989 in confined spaces at 100 m, and further pseudorange error analysis indicates that the meter-level positioning accuracy can be acquired. Finally, we construct a muon coincidence measurement scheme and verify that the laws of the muon positioning system for high-energy muons are consistent with the simulation results.

Visualization and characterization of agricultural sprays using machine learning based digital inline holography

Accurate characterization of agricultural sprays is crucial to predict in-field performance of liquid applied crop protection products. In this paper, we introduce a robust and efficient machine learning (ML) based Digital In-line Holography (DIH) algorithm to accurately characterize the droplet field for a wide range of commonly used agricultural spray nozzles. Compared to non-ML based DIH processing, the ML-based algorithm enhances accuracy, generalizability, and processing speed. The ML-based approach employs two neural networks: a modified U-Net to obtain the 3D droplet field from the numerically reconstructed optical field, followed by a VGG16 classifier to reduce false positives from the U-Net prediction. The modified U-Net is trained using holograms generated using a single spray nozzle (XR11003) at three different spray locations; center, half-span, and the spray edge to create training data with different number densities and droplet size ranges. VGG16 is trained using the minimum intensity projection of the droplet 3D point spread function (PSF). Data augmentation is used to increase the efficiency of classification and make the algorithm generalizable for different measurement settings. The model is validated using National Institute of Standards and Technology (NIST) traceable glass beads and six different agricultural spray nozzles representing various spray characteristics. The principal results demonstrate a high accuracy rate, with over 90% droplet extraction and less than 5% false positives, regardless of droplet number density and size. Compared to traditional spray measurement techniques, the new ML-based DIH methodology offers a significant leap forward in spatial resolution and generalizability. We show that the proposed ML-based algorithm can extract the real cumulative volume distribution of the NIST beads, where the LD system measurements are biased towards droplets moving at slower speeds. Additionally, the ML-based DIH approach enables the estimation of mass and momentum flux at different locations and the calculation of relative velocities of droplet pairs, which are difficult to obtain using conventional spray characterization techniques.

Water quantities for public and private use in Pompeii

The water-supply system in Pompeii delivered water to both public and private water users. Aqueduct water was distributed in three main water pipelines. The aqueduct water was led up to fill lead containers on top of a number of water towers, and from there it continued downhill from one tower to the next located at a lower level. All top containers also had connections to small individual lead water pipes to public and private users in the different districts of the city. However, it still remains unclear how and with what efficiency aqueduct water could reach all users, some of them at a far distance from the water towers, in a system based on gravity flow. In this study the focus is to explain the water flow in the small water pipes from the top containers to public and private users. The study presents a calculation method based on Bernoulli’s equation for fluid mechanics. The simplified form of the equation is the result of an adaption to Pompeii’s conditions and has been used for the calculation of water velocity and the water quantity in water pipes when three geometrical variables are known, the head, the length of the pipe and the diameter of the pipe. The calculations of the water quantities in small water pipes have shown that less than half of the total incoming water quantity to the city was supplied for public use in the street fountains and the public baths, and that at least half was supplied for private use. This means that the water supply for some private users must have been considered from the beginning. The calculation method has only resulted in estimations, but the equation presented is exact and deserves to be used in the future as more exact values of the three geometrical variables are measured.

Six‐Component Earthquake Synchronous Observations Across Taiwan Strait: Phase Velocity and Source Location

AbstractWith the development of rotational seismometers, especially the high‐sensitivity optical seismometers, rotational motions have shown increasing benefits for calculation of dispersion curves, estimation of back azimuth and many other applications. Here we present the six‐component observations of 2019 Hualien mww6.1 earthquake simultaneously on both sides of Taiwan Strait. Seismograms and time‐frequency spectrums show that the attenuations for rotations are more significant than translations. Calculations of the surface wave phase velocity are performed for both stations through single‐station records, indicating a distinct difference owning to the instrument installation conditions and site effect. Comparison of theoretical dispersion curves is consistently in trends with estimations, and reveals the influence of higher‐mode surface waves. For the first time, we locate the source of a earthquake through intersection of two stations' back azimuths estimated through rotational methods. Results of comparing to translational polarization verify that rotational observation can distinctly reduce the deviation of source location.

Abundance, distribution and deposition of PM2.5-bound iron in northern China during 2021 dust and dust storm periods

Dust storms have the ability to transport and deposit contaminants and nutrients, such as iron (Fe), to downwind regions through atmospheric processes. However, there is a lack of reported data on the high-resolution variations and deposition of particulate iron in multiple locations during dust storms. This study aimed to address this gap by employing standardized analytical methods to measure the concentrations of PM10, PM2.5, and PM2.5-associated Fe in Taiyuan, Beijing, Tianjin, Ji'nan, and the Bohai Bay of China during the dusty events of 2021. A total of 13 blowing sand or dust storms were recorded, with average PM10 and PM2.5 concentrations of 262 ± 322 and 85 ± 652, 171 ± 403 and 53 ± 448, 153 ± 211 and 57 ± 315, and 207 ± 249 and 63 ± 301 μg/m3 at the above-mentioned sites, respectively. These elevated concentrations were attributed to stronger winds in northern China and severe wind erosion in the sand source areas. During these events, the average concentrations of PM2.5-bound Fe reached 2730.2 ± 4587.9, 2030.2 ± 3877.9, 1342.1 ± 2251.4, and 1785.1 ± 2536.6 ng/m3 in Taiyuan, Beijing, Tianjin, and Ji'nan, respectively, with the highest concentrations recorded as 48.8, 48.0, 29.2, and 22.7 μg/m3. A significant positive correlation was observed between Fe and Si in PM2.5 in the four cities, with higher Fe/Si slopes recorded in or near the source regions, while the homogenized Fe/Si values were observed after long-distance transport. The mean dry deposition fluxes (FFe) of PM2.5-bound Fe were calculated as 0.34 ± 0.64, 0.31 ± 0.91, 0.21 ± 0.56, and 0.17 ± 0.28 mg/m2/d for Taiyuan, Beijing, Tianjin, and Ji'nan, respectively, based on both hourly observation data and model-based calculations of dry deposition velocities. It is worth noting that FFe decreased from west to east in China, consistent with a previous study that showed a decrease in dust deposition rates with increasing transport distances. Peaks in FFe corresponded to the highest concentrations of PM2.5-associated Fe, indicating that these concentrations played a significant role in Fe. Furthermore, the atmospheric deposition of dissolved Fe from blowing sand or dust storm events was found to contribute to carbon fixation in the Bohai region of China, providing a range of 7.8 × 104–3.9 × 106 mol. This research provides valuable insights into the quantitative relationship between atmospheric deposition and marine productivity during dust events.

TRANSPORT CHARACTERISTICS OF ELECTRONS IN NITROUS OXIDE (N2O) UNDER THE INFLUENCE OF CROSSED ELECTRIC AND MAGNETIC DC FIELDS

Monte Carlo (MC) calculations of transport and rate coefficients of an electron swarm moving in nitrous oxide (N2O) under the influence of DC crossed electric and magnetic orthogonal fields are present- ed. The set of cross sections for e-/N2O scattering obtained in our previous investigations was used as the initial parameter. Calculations of mean energy, drift velocity, diffusion coefficients and rate coefficients for elastic and individual inelastic processes were performed for five different values of the reduced magnetic field (B/N = 100 Hx, 200 Hx, 500 Hx, 1000 Hx and 2000 Hx, 1Hx = 10-27 Tm3), where for each of these values, the value of the reduced electric field (E/N) ranged from 50 Td to 2000 Td (1Td = 10-21Vm2). The ratio of cyclotron to total collision frequency in these cases is less than one for all values of B/N (except for the highest one when it is slightly greater than one), so we may claim that our swarm is in a collision-domi- nated regime. The cooling effect of the swarm is observable, i.e. there is a decrease in its mean energy as the magnetic field increases, as well as a decrease in the drift velocity component in the electric field direction. Electron diffusion is slightly anisotropic for the higher values of B/N.

Lead Green's functions from quadratic eigenvalue problems without mode velocity calculations.

In quantum transport calculations, the proper handling of incoming and outgoing modes for retarded Green's functions is achieved via the lead self-energies. Computationally efficient and accurate methods to calculate the self-energies are thus very important. Here we present an alternative method for calculating lead self-energies which improves on a standard approach to solving quadratic eigenvalue problems that arise in quantum transport modeling. The method is based on a perturbative analysis of the generalized Schur decomposition to determine the relevant set of eigenvalues for transmitting modes. This allows us to circumvent finding the velocities of the modes (left- or right-moving) that are needed in order to calculate the lead Green's function from translationally invariant Green's functions. This saves computational time irrespective of the value of the imaginary part added to the energy. We compare our method with two existing methods-a popular iterative method and a standard eigenvalue method that explicitly calculates the velocities of the propagating modes. Our comparison shows that both eigenvalue methods are more robust than the iterative method. Furthermore, the comparison also shows that above a small threshold of propagating modes, the standard eigenvalue method requires extra computation time over our perturbation method. This excess of computation time grows linearly with the number of propagating modes.

Comparative Assessment of Different Image Velocimetry Techniques for Measuring River Velocities Using Unmanned Aerial Vehicle Imagery

The accurate measurement of river velocity is essential due to its multifaceted significance. In response to this demand, remote measurement techniques have emerged, including large-scale particle image velocimetry (LSPIV), which can be implemented through cameras or unmanned aerial vehicles (UAVs). This study conducted water surface velocity measurements in the Xihu River, situated in Miaoli County, Taiwan. These measurements were subjected to analysis using five distinct algorithms (PIVlab, Fudaa-LSPIV, OpenPIV, KLT-IV, and STIV) and were compared with surface velocity radar (SVR) results. In the quest for identifying the optimal parameter configuration, it was found that an IA size of 32 pixels × 32 pixels, an image acquisition frequency of 12 frames per second (fps), and a pixel size of 20.5 mm/pixel consistently yielded the lowest values for mean error (ME) and root mean squared error (RMSE) in the performance of Fudaa-LSPIV. Among these algorithms, Fudaa-LSPIV consistently demonstrated the lowest mean error (ME) and root mean squared error (RMSE) values. Additionally, it exhibited the highest coefficient of determination (R2 = 0.8053). Subsequent investigations employing Fudaa-LSPIV delved into the impact of various water surface velocity calculation parameters. These experiments revealed that alterations in the size of the interrogation area (IA), image acquisition frequency, and pixel size significantly influenced water surface velocity. This parameter set was subsequently employed in an experiment exploring the incorporation of artificial particles in image velocimetry analysis. The results indicated that the introduction of artificial particles had a discernible impact on the calculation of surface water velocity. Inclusion of these artificial particles enhanced the capability of Fudaa-LSPIV to detect patterns on the water surface.

Research on radial velocity and airspace position calculations of target in airborne active radar simulation

The detection of the target in the airborne active radar simulation is simplified to the calculations of the radial velocity, the maximum detecting range of the airborne active radar corresponding to the RCS, and the airspace position of the target. However, the coordinate transformations related to the calculations of the radial velocity and the airspace position are usually bewildering due to the different referenced coordinate systems. This paper introduces the radial velocity and airspace position calculations of the target in the airborne active radar simulation to illuminate the transformation process containing the specific rotation matrices, suggesting the unifying transformation to the north-up-east (NUE) rectangular coordinate system of the aircraft for both the radial velocity calculation and airspace position calculation of the target.

Investigation of a low frequency coherent mode in Wendelstein 7-X with island divertor

During the island divertor operation of W7-X, especially in standard magnetic configuration (with 5/5 island chain in the scrape-off-layer (SOL)), quasi-periodic electromagnetic oscillation is observed. It appears in the frequency range of 1 kHz–2 kHz, therefore it is called the low frequency mode (LFM) within this paper. It is observed by multiple diagnostics, amongst them, a poloidal correlation reflectometer allowing radial localization of the LFM. The LFM is localized in the SOL and shows an obvious modulation effect on the plasma perpendicular velocity ( V⊥ ). Furthermore, broadband turbulence is observed in the fluctuation spectra of the electron density and the magnetic field and the perpendicular correlation length of turbulence eddies are modulated. The calculation of the poloidal flow velocity and its oscillation allows us to study the effect of the LFM on the flow. Cross correlation analysis shows that the perpendicular flow oscillation and the turbulence modulation are closely correlated. The application of external control coils to adjust the island size and position result in a strong modification of the magnetic topology at the plasma edge which affects the appearance, amplitude and frequency of the LFM. Bi-coherence analysis indicates that nonlinear interactions among turbulence components is a possible mechanism for the generation of the LFM.

Manifestations of catastrophic Turkish earthquakes February 6, 2023 in Kryvbas

We analyzed the impact of powerful Turkish earthquakes that occurred on February 6, 2023, including a magnitude 7.8 Mw earthquake at 01:17:36 (UTC) in Kahramanmarash—Gaziantep, a magnitude 6.7/6.3 Mw earthquake at 01:28:21 (UTC), and a magnitude 7.5 Mw earthquake at 10:24:50 in Ekinoz—Kahramanmarash, on the territory of Ukraine, particularly in the city of Kryvyi Rih.The study involved the examination of algorithms for processing data recorded at seismic stations belonging to the S.I. Subbotin Institute of Geophysics of the National Academy of Sciences of Ukraine and the Main Center for Special Control of t he State Space Agency of Ukraine. The analysis of digital records from these Turkish earthquakes provided ground shaking intensity parameters at the recording points: Odesa and KryvyiRih had intensity levels below 3, Kremenchuk recorded 2, and Poltava and Kyiv registered 1. The resulting isoseismal map illustrates that the attenuation of wave intensity from the Turkish earthquakes depended on the geotectonic structure of the Ukrainian territory through which the seismic vibrations propagated.
 The monitoring of the water level in a deep well recorded changes in geodynamic (hydrodeformation) processes following the powerful Turkish earthquakes on February 6, 2023. We found the level of fault-fracture groundwater in the territory of Kryvbaswas affected bythe earthquakes. The calculation of the propagation velocity in the upper part of the lithosphere of the rock deformation front showed a value of ≈19.0 km/min (0.5 km/min).Concurrently, a decrease in the groundwater level by 2—3 cm was recorded, making it possible to conclude that after the earthquake, short-period stretchings of the earth’s crust occurred, both in the zone of the Kryvyi Rih—Kremenchutsky fault and over the Ukrainian Shield, in in general.
 The calculated amplitude-frequency characteristics for the geological environment on the territory of Kryvyi Rih revealed that the maximum acceleration of seismic vibrations on the free-soil surface increases relative to bedrock by about 4 times in the frequency range from 1.2 Hz to 1.75 Hz.

Design and Experimental Analysis of Straw Suction Unit on Straw Cover Weight Detection Machine

In response to the issues of high cost, limited detection accuracy, and significant measurement errors inherent in conventional manual techniques used to measure straw cover weight under the conservation tillage method, a dedicated straw cover weight detection machine was developed in the current study. This machine included a critical straw suction device that utilizes negative pressure to collect straw within a defined area. The efficiency of straw collection is affected by suction chamber structural parameters and transport pressure. With crushed corn straw as the research subject, the theoretical calculation of straw suspension velocity was used to determine the wind duct diameter, perform the initial design of the suction chamber structure, and select the appropriate fan. After conducting preliminary experiments, single-factor optimization tests, and orthogonal rotation experiments, we analyzed the flow field distribution patterns and identified the critical parameters for the straw cover weight suction unit. We found that the fan should operate at a speed of 2900 r/min, the diameter of the straw outlet should be 200 mm, the vertical height of the suction chamber should be 536 mm, and the bottom diameter of the suction chamber should be 800 mm. The optimization results were validated through simulation tests and bench tests, yielding an average near-ground airflow velocity of vj = 9.03 m/s and an average outlet airflow velocity of vo = 34.27 m/s, meeting the basic requirements of the suction unit. This study could provide a new approach and technical support for the automated detection of straw cover weight in conservation tillage areas.

Anisotropic mechanical behavior and thermal attributes of antiferromagnetic UX2(X=P, As, Sb) materials: A density functional and elasticity theories study

In this work, we delve into the investigation of mechanical and thermal properties of antiferromagnetic UX2 (X=P, As, Sb), which are structured in the unique anti-Cu2Sb-type tetragonal form. The study’s principal findings revolve around the revelation of distinctive compressibility patterns and an observed preference for shear deformation in these compounds. These patterns are notably marked by a lower compressibility along the [100] direction than the [001] one, and the ease of shear deformation on the (100) plane compared to the (001) one. Intriguingly, our findings identify these compounds as residing on the brink of the brittle/ductile borderline as per Pugh’s ratio and Poisson’s ratio. Furthermore, the mechanical strength in these materials is significantly influenced by shear deformation, a fact indicated by the values of bulk and Young’s modulus. Among the UX2 (X=P, As, Sb) compounds, our analysis of the Debye temperature singles out UP2 as an outstanding performer due to its higher Debye temperature. A noteworthy aspect of this study is the quicker propagation of longitudinal waves over transverse waves, as indicated by the wave velocity and anisotropy calculations. We bring forth an enriched understanding of the anisotropic behavior of these materials in terms of bulk modulus, Young’s modulus, shear modulus, and Poisson’s ratio. The predicted high melting temperatures of the UX2 (X=P, As, Sb) compounds, coupled with the computed heat capacities aligning well with existing experimental data, point towards their potential applicability in high-temperature settings. Collectively, our study not only validates the methodologies employed but also brings to light fascinating new insights into the mechanical and thermal properties of these compounds, deepening our understanding of the intricate interplay between their atomic constitution and physical properties.

Numerical and experimental study on efficient optimization of variable cross-section battery thermal management systems using an improved flow resistance network model

Air-cooled systems are widely used for cooling of battery packs in electric vehicles. Optimization method combined with the flow resistance network (FRN) model is effective for system design. However, the local pressure loss of divergence and convergence ducts in the traditional FRN model is ignored, leading to large error when applying the model in systems with variable cross-section channels. In this study, the local loss coefficients of the contractive and diffusive channels are derived and the improved FRN model is developed for velocity calculation of variable cross-section air-cooled systems. The improved model is verified using computational fluid dynamics method. Based on the improved FRN model, the cross-section width distribution of the divergence duct is calculated from the given flow rate distribution. The shape of the divergence deflector is optimized by adjusting the flow rate distribution and using the improved model. The results indicate that the temperature difference of the battery cells decreases by more than 84% after the optimization, with the maximum temperature decreasing by more than 3.8 K. Furthermore, the optimized system performs better than those in the previous studies. Also, experiments are carried out to verify the effectiveness of the developed optimization method based on the improved FRN model.

Fluidized Bed Reactor Modeling and Simulation with Aspen Plus

Fluidized bed reactor is useful for heterogeneous (multiphase) reactions, separations, size enlargement, coating, and blending in chemical and pharmaceuticals industries. To develop a model and simulation of this reactor with advanced systems process engineering software (Aspen Plus). Aspen plus has the capability to simulate real factory performance, design improved plants, and intensify profitability in present plants. This modeling and simulation are applied Geldart B particle classification, GGC is used for particle size distribution function, Newton parameters for mass convergence, and Ergun equation is used for minimum fluidization velocity calculation and pressure drop through the fluidized bed reactor. Generally, most of the predictions model from Aspen plus is a reasonable agreement through the experimental results. Advantage of this investigation is used small quantity of bed particles and identified their melting point temperature is above 340°C. This fluidized bed reactor model and simulation is functional for aluminum hydroxide decomposition reaction. The feed 275 kg/hr of Al(OH)3is converted into 169.6 kg/hr of aluminum oxide (Al2O3) and 89.9 kg/hr of water. A total mass conversion percent is 94.4% of aluminum hydroxide.

РАСЧЕТ СКОРОСТИ ВОЗДУШНОГО ПОТОКА ИЗ ТУРБИНЫ С ИНТЕГРИРОВАННЫМ СОПЛОМ ЛАВАЛЯ НА ВЫХОДЕ ДЛЯ НАНЕСЕНИЯ МЕТАЛЛИЧЕСКОГО ПОКРЫТИЯ МЕТОДОМ ХОЛОДНОГО НАПЫЛЕНИЯ

The goal of this work was to test the practicability of using a device that provides airflow into the Laval nozzle channel to enable the application of metal coating by cold spraying. A turbine with an integrated Laval nozzle at the outlet was considered as a device to provide airflow into the Laval nozzle channel. The authors describe the equipment used in the calculations and the experimental study, the process of gasdynamic calculation of the output velocity of the airflow injected by the turbine impeller and the results of this calculation with precise indices. As a result, functional dependences of the indicators that provide the possibility of using the turbine as a source of airflow have been obtained, and a conclusion about the inexpediency of using a turbine with an integrated Laval nozzle at the outlet to provide the possibility of metal coating by cold spraying has been formed.

Cylinder Liner Velocity Calculation under Dynamic Condition in the Pursuit of Liner Cavitation Investigation of an Internal Combustion Engine

<div>An analytical method for nonlinear three-dimensional (3D) multi-body flexible dynamic time-domain analysis for a single-cylinder internal combustion (IC) engine consisting of piston, connecting rod, crank pin, and liner is developed. This piston is modeled as a 3D piston that collides with the liner as in a real engine. The goal is to investigate the piston slap force and subsequent liner vibration. Liner vibrational velocity is directly responsible for pressure fluctuations in the coolant region resulting in bubble formation and subsequent collapse. If the bubble collapse is closer to the liner surface, cavitation erosion in the liner might occur. The mechanism of liner cavitation is briefly explained, which would take a full computational fluid dynamics (CFD) model to develop, which is out of scope for the present work. However, as a first step, the present method focused on a comprehensive and accurate estimation of the highest inward and outward liner velocities, which are directly related to the bubble formation and collapse, respectively. Sensitivity of liner velocity to different engine-operating conditions (warm and hot, with highest skirt temperatures of 178 and 130°C), piston pin bore offsets (thrust side, anti-thrust side directions in the amounts of 0.6 mm, and the nominal no offset case), and liner thicknesses are determined. Piston thermal growth is considered as part of the analysis resulting in interference condition between piston skirt and liner under the hot operating condition and low minimum clearance under the warm condition. Correlation of liner velocity contour plots with real engine liner cavitation erosion is presented. Analytical model showed a maximum liner inward velocity of 55 mm/s with no piston pin offset under nominal engine-operating configuration. A correlation has been found between location of this highest liner velocity and location of the actual cavitation erosion in the field.</div>

A Study of Flow in Open Orthogonal and Trapezoidal Channels with Gabion Walls

The turbulent characteristics of the flow in open channels with gabion walls are studied numerically. Two trapezoidal and one orthogonal channel are used along with four different heights: 100mm, 150mm, 200mm, and 250mm of sand roughness in the gabion walls. Calculations of velocity, pressure, turbulence kinetic energy and eddy viscosity show clearly that the presence of the roughness affect considerably the fluid motion. As expected, the rough elements affect the mean velocity inside the channel and near the walls. Near the solid walls, the velocity profile is significantly affected and sharply lower velocities are observed very close to the walls.

An Improved Parallel Particle Swarm Optimization

In the area of global optimization, a variety of techniques have been developed to find the global minimum. These techniques, in most cases, require a significant amount of computational resources and time to complete and therefore there is a need to develop parallel techniques. In addition, the wide spread of parallel architectures in recent years greatly facilitates the implementation of such techniques. Among the most widely used global optimization techniques is the particle swarm optimization technique. In this work, a series of modifications are proposed in the direction of efficient parallelization for particle swarm optimization. These modifications include an innovative velocity calculation mechanism that has also been successfully used in the serial version of the method, mechanisms for propagating the best particles between parallel computing units, but also a process termination mechanism, which has been properly configured for efficient execution in parallel computing environments. The proposed technique was applied to a multitude of computational problems from the relevant literature and the results were more than promising, since it was found that increasing the computational threads can significantly reduce the required number of function calls to find the global minimum. The proposed technique is at rate of 50–70% of the required number of function calls compared to other optimization techniques. This reduction is visible even if one to two parallel processing units are used. In addition, with the increase in parallel processing units, a drastic reduction in the number of calls is observed and therefore a reduction in the required computing time, which can reach up to 70%.