Standoff Distance Research Articles

Surface Roughness Analysis in AWJM for Enhanced Workpiece Quality

Abrasive Water Jet Machining is a distinctive manufacturing process that effectively removes material from a workpiece by employing a high-pressure stream of water combined with abrasive particles. The final quality of the machined surface is directly influenced by various process parameters, such as the traverse speed, hydraulic pressure, stand-off distance, abrasive flow rate, and the specific type of abrasive used. In recent times, extensive research has been undertaken to enhance the performance of AWJM, with a specific focus on critical performance measures like surface roughness. This paper presents the latest advancements in AWJM research, with particular attention given to enhancing performance measures, implementing process monitoring and control, and optimizing process variables for applications involving high-carbon steel.

The relative position of pyrolysis onset and flame front location for downward flame spread

The interaction of solid and gas phase phenomena in downward flame spread is studied under buoyant conditions. Phosphor thermometry (PT) was used to determine the spatiotemporally resolved surface temperatures both ahead and beneath the flame while CH* chemiluminescence allowed for the quantification of the flame location relative to the fuel surface. The combination of these measurements allowed for the superposition of the flame front location and the surface temperature distribution. The standoff distance (∼1.1 mm) and preheated distance along the surface (∼3.5 mm) were quantified. The application of PT allowed for the continued measurement of surface temperatures in the pyrolyzing region beneath the flame, where the surface temperature was found to remain relatively constant between 300 and 350 °C. The combination of measurements allowed for the calculation of the gas-phase heat flux distribution ahead of the flame front using a point-source approximation, which compared well with previous studies. PT and CH* measurements were used to expand previous work to quantify the thermal gradients through the solid both ahead of and behind the flame front. Surface temperature measurements were coupled with thermogravimetric analysis (TGA) and a simple pyrolysis model to determine that the onset of pyrolysis occurs approximately 1 mm ahead of the flame front. This approach was also used to illustrate that pyrolysis gases were generated in sufficient volume to result in a flammable mixture at the leading edge of the flame. This study highlights the benefit of optical diagnostic techniques in exploring the controlling mechanisms of flame spread, and provides insight into the interaction of solid and gas-phase phenomena in downward flame spread.

Viscoelastic vapor bubble collapse near solid walls and corresponding shock wave formation

This study investigates the influence of viscoelasticity on the collapse of aspherical vapor bubbles near a solid boundary through numerical simulations. A fully compressible three-dimensional finite volume method is employed, incorporating a single-fluid homogeneous mixture cavitation model and the simplified linear Phan-Thien Tanner viscoelastic constitutive model. The collapse dynamics, liquid jetting, shock wave formation, and associated pressure impact are analyzed, and the viscous and viscoelastic stress fields are presented. A comparison of viscoelastic to Newtonian dynamics reveals significant differences in collapse behavior and shock wave formation due to viscoelasticity. Viscoelasticity can induce jet piercing, which is not observed in the Newtonian collapse, and increases vapor re-evaporation after the first collapse. The effect of changing the initial standoff distance is examined for both viscoelastic and Newtonian fluids, where a second jet formation is present only for the viscoelastic collapse, and the second collapse's intensity is increased due to increased vapor production during rebound. Additionally, the variation of elasticity in the viscoelastic case demonstrates a correlation between the amount of vapor produced during rebound and the relaxation time for the investigated cases.

Material removal rate in AJM of zirconia ceramic using silicon carbide abrasive: Investigation, modelling, and optimization

This research focuses on material removal rate in abrasive jet machining (AJM) of zirconia ceramic under varying process conditions (grain size of silicon carbide abrasive, air pressure, stand-off-distance). Combined approach of orthogonal array, and response surface methodology are respectively, applied for assessment, predictive modelling as well as response optimization. The influence of air pressure emerged as the most critical factor in enhancing MRR during AJM of zirconia ceramic. At elevated pressures, the surface morphology exhibits characteristic deep chipping and larger crater marks. The proposed predictive model for MRR utilizing the regression method proves effective, demonstrating adequacy, statistical significance, and probabilistic validation, indicated by its high R2-value (0.995), P-value below 0.05 (0.016), and substantial AD-test P-value (0.327). By employing DFA to solve the response optimization problem, optimal MRR (0.0000619 gm/min) for AJM of zirconia ceramic is achieved at abrasive grain size of 750 μm, air pressure of 7 kgf/cm2, and stand-off distance of 2 mm.

Solar wind entry into Mercury’s magnetosphere: Simulation results for the second swingby of BepiColombo

Context. We use a global 3D hybrid plasma model to investigate the interaction between Mercury’s magnetosphere and the solar wind for the second BepiColombo swingby, evaluate magnetospheric regions, and study the typical energy profile of protons. Aims. The objective of this study is to gain a better understanding of solar wind entry and analyze simulated plasma data along a trajectory using BepiColombo swingby 2 conditions, with the goal of enhancing our comprehension of measurement data and potentially providing forecasts for future swingbys. Methods. To model Mercury’s plasma environment, we used the hybrid code AIKEF and developed a method to extract the particle (ion) data in order to compute the proton energy spectrum along the trajectory of BepiColombo during its second Mercury swingby on June 23, 2022. We evaluate magnetopause and bow shock stand-off distances under average upstream solar wind conditions with the Interplanetary Magnetic Field (IMF) condition derived from the BepiColombo magnetic field measurements during the second Mercury swingby. Results. We found that the magnetosheath on the quasi-perpendicular (dusk) side of the bow shock is thicker than that on the quasi-parallel (dawn) side, where a foreshock is formed. Multiple plasma populations can be extracted from our modeled energy spectra that assist in identifying magnetospheric regions. We observed protons of solar wind origin entering Mercury’s magnetosphere. Their energies range from a few electron volts in the magnetosphere up to 10 keV in the magnetosheath.

Investigation of high enthalpy thermochemical nonequilibrium flow over spheres

The hypersonic high enthalpy nitrogen flows over spheres are investigated by high-fidelity state-to-state (StS) modeling. The objective of the study is to understand the nonequilibrium behaviors in the shock layer, including the stagnation line features, surface heat transfer rate, and near-wall properties inside the thermal boundary layer. Two cases with the freestream total enthalpies of 16.5 and 15.5 MJ/kg are considered, and the numerical results are compared with the experimental data. The StS model yields an accurate prediction of the shock stand-off distance with the experiment rather than an underestimation by the traditional two-temperature model. Both the StS and two-temperature models provide general agreement of the stagnation point heat flux with the experiment. In comparison, the heat flux obtained by the StS model is lower than the two-temperature model. Note that our work finds distinctive behaviors of near-wall properties. The vibrational energy is not accommodated with the sphere surface and is in thermal nonequilibrium with the translational energy, with evidence showing that the vibrational temperature is much higher than the wall temperature and the translational temperature. The values of vibrational temperature in the immediate vicinity of the stagnation point are 9.3 and 10.0 times the wall temperature for the cases with total enthalpies of 16.5 and 15.5 MJ/kg, respectively. Moreover, the vibration temperature demonstrates a nonmonotonic variation trend with a local minimum, which can be explained by the nonequilibrium distributions of vibrational energy states due to vibrational-translational energy transfer and molecular recombination.

Numerical study of gas–surface interface effects due to transpiration in a hypersonic flow over a blunt body

This paper investigates the impact of transpiration on a hypersonic flow over a cylinder, considering different degrees of rarefaction. The study analyzes the interaction between freestream argon gas flow at Mach 5 and transpiring argon gas at the fluid–solid interface at a velocity of 10 m/s. Freestream Knudsen numbers considered are 0.002, 0.01, 0.05, and 0.25, spanning from a continuum to rarefied regime. Flow simulations utilize the open-source direct simulation Monte Carlo solver, Stochastic PArallel Rarefied-gas Time-accurate Analyzer. The influence of transpiration on flow and surface properties is examined by comparing non-transpiration and transpiration cases. At all regimes, transpiration increases the normal shock stand-off distance, while a comparison of flow properties along the stagnation line reveals a reduction in the velocity and an increase in the post-shock temperature with transpiration. Surface heat flux comparison indicates that transpiring gas reduces heat flux on the cylinder's upstream-facing front surface at all Knudsen numbers. However, at Kn∞ = 0.25, a shift occurs, and surface heat flux starts increasing locally from the top/bottom point on the cylinder surface through the rear face of the cylinder. Furthermore, a test for the validity of the continuum-based blowing correction correlation function reveals the failure of the empirical model, even in the continuum regime at Kn∞ = 0.002, casting doubt on its applicability to vehicles with curvilinear blunt-body shapes. Additionally, a sensitivity analysis demonstrates that transpiring gas with a number density an order of magnitude higher than the freestream reduces stagnation peak heat flux by nearly 30%, while transpiring gas with a temperature two times higher than the freestream shows a ∼13% reduction.

Modelling standoff distances to prevent escalation in shooting attacks to tanks storing hazardous materials

Modelling standoff distances to prevent escalation in shooting attacks to tanks storing hazardous materials

Numerical Simulation of Icebreaking by Underwater-Explosion Bubbles and Compressed-Gas Bubbles Based on the ALE Method

Icebreaking by using underwater explosion bubbles and compressed high-pressure gas bubbles has gradually become an effective icebreaking method. In order to compare the damaging effect of these two methods on the ice body, a fluid–structure coupling model was established based on the arbitrary Lagrangian–Eulerian (ALE) method and a series of calculations were carried out. The morphological changes of underwater explosion bubbles and compressed gas bubbles at the same energy under the free surface; the changes of flow load near the rigid wall; and the damage caused to the ice plate were studied and compared. The damage effect of the ice plate was analyzed by detecting the number of failure elements of the ice plate, and the optimum standoff distance was found. For an ice plate with a radius of 0.19 m and a thickness of 0.15 m, the optimum standoff distance of the compressed gas bubbles with 120 J is 0.03 m, and the optimum standoff distance of the TNT with 120 J is 0.02875 m. The similarities and differences of the two sources of bubbles on ice plate damage were summarized.

Prediction of the Response of Masonry Walls under Blast Loading Using Artificial Neural Networks

A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex due to the potential opening and sliding of the mortar joint interfaces between the masonry stones. To capture this response, advanced computational models can be developed requiring a significant amount of resources and computational effort. The article uses an advanced non-linear finite element model to capture the failure response of masonry walls under blast loads, introducing unilateral contact-friction laws between stones and damage mechanics laws for the stones. Parametric finite simulations are automatically conducted using commercial finite element software linked with MATLAB R2019a and Python. A dataset is then created and used to train an artificial neural network. The trained neural network is able to predict the out-of-plane response of the masonry wall for random properties of the blast load (standoff distance and weight). The results indicate that the accuracy of the proposed framework is satisfactory. A comparison of the computational time needed for a single finite element simulation and for a prediction of the out-of-plane response of the wall by the trained neural network highlights the benefits of the proposed machine learning approach in terms of computational time and resources. Therefore, the proposed approach can be used to substitute time consuming explicit dynamic finite element simulations and used as a reliable tool in the fast prediction of the masonry response under blast actions.

Heat transfer enhancement in multijet micropin fin heat sink

The thermal performance of tiny heat sinks with liquid cooling is being studied in order to solve the issue of electronics cooling. Increasing thermal performance while lowering pressure drop and maintaining a constant substrate temperature is a difficult task. The purpose of this study is to harvest the useful features of combination of microjet and micropin fins and explore the influence of geometrical features on fluid structures and heat transfer. To comprehend and assess the performance of a multijet heat sink with a micropin fin, three-dimensional numerical simulation is used in this inquiry. The three parameters under consideration are, the ratio of the jet diameter to the pin fin diameter (α), which ranges from 1.5 to 6.0; the ratio of the jet diameter to the jet standoff distance (β), which ranges from 0.75 to 1.5; and the pin fin pitch is determined by the ratio of the pin fin diameter to the pitch length (λ), which ranges from 0.1 to 0.8. The grid independence test is done to ensure accuracy in numerical results. The numerical scheme is validated by comparing numerical results with that of experimental results from literature. The results obtained from numerical simulation are analyzed. It has been found that improving heat transfer is not just caused by expanding the contact surface area; fluid structure vortex generation also affects overall thermal performance. Better overall performance is produced at lower values of α, β and higher values of λ. The ideal design parameters are α = 1.99, β = 1.431, and λ = 0.699, according to the optimization of geometrical parameters using a radial basis neural network surrogate model and particle swarm optimization. The jet Reynolds number is found to have no significant impact on the overall performance.

Assessing Cavitation Erosion on Solid Surfaces Using a Cavitation Jet Apparatus

This study is dedicated to the examination of cavitation-induced erosion, a critical factor in optimizing the efficiency of hydraulic systems, including hydropower plants and pumping systems. To accomplish this, we conducted a sensitivity analysis utilizing a cavitation jet apparatus (CJA) and an experimental configuration that featured a vertical cylindrical test tank, a submerged nozzle, and an aluminum sample (specifically, alloy 6351 T6). The study maintained a consistent standoff distance of 5 cm and an orifice diameter of 2 × 10-3 m. Two distinct nozzle geometries were tested to assess their influence on cavitation erosion. The outcomes revealed that the 20° conical sharped-edges nozzle resulted in the highest erosion rates, while the commercial nozzle (MEG 2510) caused comparatively less erosion. By standardizing the test duration to 1200 seconds and using a cavitation index of 0.14, the researchers avoided overlapping pits. In summary, the CJA, with these adjustments, demonstrated its effectiveness as a tool for evaluating the resistance of solid surfaces to cavitation.

A forecasting model for optimizing abrasive water jet machining (AWJM) parameters based on the adaptive neuro-fuzzy inference system and meta-heuristic algorithms

Innovative materials have been steadily produced in the machining process, and it has stimulated substantial attention among researchers to assess the ideal parameters for the processing of these materials. In the manufacturing industry, conventional and modern or unconventional machining retains their imprint in delivering quality products. One of the most frequently used contemporary machining processes is abrasive water jet machining (AWJM) for cutting materials. The optimization of parameters, however, is essential to manufacturing high-quality products quickly and affordably. This study focused on optimizing the machining parameters of AWJM using the Adaptive Neuro-Fuzzy Inference System (ANFIS) by encrypting the evolutionary algorithms, including the reptile search algorithm (RSA), beetle antennae search (BAS), and particle swarm optimization (PSO). As a result of the developed methods, the surface roughness of titanium alloy (Ti–6Al–4V) during AWJM machining is predicted by considering inputs such as standoff distance, abrasive flow rate, and traverse speed, which affect the surface roughness. Based on a comparison of the prediction accuracy of the proposed methods, it was found that the combined ANFIS and RSA outperforms the others. In the simulation results, ANFIS-RSA (Adaptive Neuro-Fuzzy Inference System and Reptile Search Algorithm) yielded the most accurate estimates of surface roughness based on the RMSE (0.1241), MAE (0.0961), MAPE (0.0201), and R2 (0.9781) values. In particular, the analysis findings demonstrated that the combination of ANFIS and RSA was the most effective approach for predicting surface roughness on titanium alloy during AWJ machining.

Application of the Taguchi method to areal roughness-based surface topography control by waterjet treatments

Pure waterjet surface treatment without abrasive particles has a promising application in the biomedical field, because it induces compressive residual stresses on a metal surface and never leaves the tiny hard particles. In this work, the influence of operation pressure, standoff distance and the number of paths of the waterjet on the surface topography as well as the hardness was studied using the Taguchi method. The results showed that the most essential parameter is the operation pressure. By tuning the operation pressure from 100 to 300 MPa, the surface of Ti6Al4V specimens can be smoothed, roughened or damaged; when the surface layer is eroded, the new-born surface exhibits a clear stochastic nature accompanied by microvoids. The standoff distance benefits finer controlling the height parameters, whilst the number of paths affects the waviness. The hardening effect generated by the waterjet impingement extends to a few hundred-micron depth of the specimens, and the peak value of microhardness was found at a depth of 70 μm, which is an increase by greater than 20 %. The roughness parameters of Arithmetical mean height (Sa), Skewness (Ssk), Auto-correlation length (Sal), and Developed interfacial area ratio (Sdr) as a set are recommended to characterize the biomaterial's surface. The present research results promote the application of waterjet treatment in the field of fine-tuning biomaterial surface morphology.

Investigation of the ultrasound-induced collapse of air bubbles near soft materials

A numerical investigation into the ultrasound-induced collapse of air bubbles near soft materials, utilizing a novel multi-material diffuse interface method (DIM) model with block-structured adaptive mesh refinement is presented. The present work expands from a previous five-equation DIM by incorporating Eulerian hyperelasticity. The model is applicable to any arbitrary number of interacting fluid and solid material. A single conservation law for the elastic stretch tensor enables tracking the deformations for all the solid materials. A series of benchmark cases are conducted, and the solution is found to be in excellent agreement against theoretical data. Subsequently, the ultrasound-induced bubble-tissue flow interactions are examined. The bubble radius was found to play a crucial role in dictating the stresses experienced by the tissue, underscoring its significance in medical applications. The results reveal that soft tissues primarily experience tensile forces during these interactions, suggesting potential tensile-driven injuries that may occur in relevant treatments. Moreover, regions of maximal tensile forces align with tissue elongation areas. It is documented that while early bubble dynamics remain relatively unaffected by changes in shear modulus, at later stages of the penetration processes and the deformation shapes, exhibit notable variations. Lastly, it is demonstrated that decreasing standoff distances enhances the interaction between bubbles and tissue, thereby increasing the stress levels in the tissue, although the behavior of the bubble dynamics remains largely unchanged.

Optimal model-based control for automated robotized abrasive blasting system

In robotic abrasive blasting operations, achieving the required surface roughness and cleanliness relies heavily on manually pre-set operational parameters. These parameters, such as stand-off distance, blasting angle, inlet air pressure, abrasive flow rate, and particle size, are set based on operator experience. However, given that optimal values for these parameters vary depending on specific blasting conditions and surface requirements, the pre-set values often fail to deliver both the desired surface quality and productivity. To address these challenges, we propose a solution employing a set of proxy models and a model predictive control system to achieve optimal operational outputs. For energy efficiency and productivity maximization, we utilize computational fluid dynamics with a multiphase flow solver to determine the optimal stand-off and offset distances, thus controlling the blasting nozzle effectively. Additionally, we build a data-driven model to obtain the optimal reference set point of air pressure at the sensor location based on the desired surface roughness. Moreover, we develop a dynamic process model to link the inlet air pressure and abrasive flow rate to the air pressure at the sensor location, which facilitates the development of a model-based control system. By applying this comprehensive approach, we evaluate and optimize the control and operational parameters to achieve the desired surface roughness and productivity targets. To validate the effectiveness of our newly developed control system and models, extensive tests are conducted both virtually (in silico) and on-site. The results confirm the stability and accuracy of the control system. In on-site reliability tests, the automated blasting system successfully delivers the desired surface roughness with a relative error of less than 5 % and a remarkable 30–50 % improvement in productivity. Overall, our innovative control system and models offer a reliable and efficient solution for robotic abrasive blasting, ensuring consistent surface quality and productivity enhancements.

Optimization of Process Parameters to Minimize the Surface Roughness of Abrasive Water Jet Machined Jute/Epoxy Composites for Different Fiber Inclinations

Composites materials like jute/epoxy exhibit high hardness and are considered as difficult-to-machine materials. As a result, alternatives to conventional machining become essential to post-process the composites. Accordingly, due to its non-thermal nature, abrasive water jet machining has recently come to be seen as one of the most promising machining methods for composite materials. In the current study, the impact of machining parameters such as traverse speed (TS), standoff distance (SOD) and abrasive mass flow rate (MFR) on machined surface roughness (Ra) has been investigated. In addition, the optimum combination of process parameters to machine a jute fiber-reinforced polymer composite with minimum Ra is predicted. The experimental results are analyzed using Taguchi and Response Surface Methodology (RSM) approaches to determine the optimum set of process parameters to achieve the lowest roughness values. Without making any changes in the machining conditions, the optimum set of values is determined for two conditions by reinforcing the fiber with 45° inclination and 90° inclination. The results reflect the different optimum combinations for each fiber inclination. For 45° fiber inclination, to achieve the minimum Ra value, the predicted combination is TS = 30 mm/min, SOD = 2 mm and MFR = 0.35 kg/min. When the fiber inclination is 90°, the predicted optimum combination is TS = 25 mm/min, SOD = 2 mm, and MFR = 0.35 kg/min. It is evident from the results that the optimum combination will be changed according to the machining conditions as well as material properties. The results confirm the effect of fiber orientation on surface roughness. The specimen with 45° fiber inclination produces a lower Ra with an average of 4.116 µm, and the specimen with 90° fiber inclination generates a higher Ra with an average of 4.961 µm.

Optimization of cold spray process parameters to maximize adhesion and deposition efficiency of Ni+Al2O3 coatings

The paper considers the conducted study of the complex effect of low-pressure cold spraying parameters, namely the nozzle inlet temperature, stand-off distance, and powder feed rate on the adhesion and deposition efficiency of coatings from a Ni+Al2O3 powder on VT3-1 titanium alloy substrate. Based on predetermined information, the main levels and intervals of factor variation were selected. The dependence of the adhesion and deposition efficiency on the selected variables was approximated by a second-order polynomial. In accordance with the developed matrix of the experiment (central compositional design), a coating of the studied powder was deposited. The average value of these parameters was determined using standard methods for studying the adhesion strength (ASTM C603) and the deposition efficiency for thermal spray coatings. Based on the results of experimental data, regression equations were obtained for adhesion and deposition efficiency. For the purpose of checking the adequacy of the model, an analysis of variance was performed. It was confirmed that the obtained empirical dependences can be used to predict the adhesion and deposition efficiency of cold spraying of coatings from a Ni+Al2O3 powder on VT3-1 titanium alloy in the specified ranges of values of spraying parameters. Multi-factor optimization of the spraying parameters in order to obtain maximum values of adhesion strength and deposition efficiency was performed using the response surface methodology in the Stat-Ease 360 software. Three-dimensional and contour graphs of the dependence of the adhesion and deposition efficiency on the studied parameters were developed from the obtained empirical models. The optimal combination of parameters of low-pressure cold spraying, which ensures the maximum adhesion (34.78 MPa) and deposition efficiency (29.46%) of the Ni+Al2O3 coating mixture, is the nozzle inlet temperature—537 °C, stand-off distance—11 mm, and powder feed rate—0.6 g s−1.

Predictive model of back-wall overpressure behind a cantilever wall

To reduce the hazards posed by blast shock waves, important potential targets are usually shielded by cantilever walls. The main factor that indicates whether there is damage is the back-wall overpressure, and of concern here is predicting the back-wall overpressure behind a rigid cantilever wall. This was measured in full-scale blast experiments using 20 kg of trinitrotoluene (TNT) located on the ground, and the experimental data reveal how the cantilever wall mitigates the shock wave. A 3D numerical model was established to determine how the wall size influences the diffraction of the shock wave and the peaks and attenuation of the back-wall overpressure. Based on the numerical results and dimensional analysis, a model is proposed that provides an effective means of predicting the back-wall overpressure rapidly from the TNT equivalent, the standoff distance, and the height of the wall.

Three‐Dimensional Global Hybrid Simulations of Mercury's Disappearing Dayside Magnetosphere

AbstractAn important discovery of MESSENGER is the occurrence of dayside disappearing magnetosphere (DDM) events that occur when the solar wind dynamic pressure is extremely high and the interplanetary magnetic field (IMF) is both intense and southward. In this study, we investigate the DDM events at Mercury under extreme solar wind conditions using a three‐dimensional (3‐D) global hybrid simulation model. Our results show that when the solar wind dynamic pressure is 107 nPa and the magnitude of the purely southward IMF is 50 nT, most of the dayside magnetosphere disappears within 10 s after the interaction between the solar wind and the planetary magnetic field starts. During the DDM event, the ion flux is significantly enhanced at most of the planetary dayside surface and reaches its maximum value of about 1010 cm−2 s−1 at the low‐latitude surface, which is much larger than that under normal solar wind conditions. During the DDM events, the dayside bow shock mostly disappears for about 9 s and then reappears. Moreover, the time evolution of magnetopause standoff distance under different solar wind conditions is also studied. When the solar wind dynamic pressure exceeds 25 nPa and the IMF is purely southward, a part of the dayside magnetosphere disappears. Under the same IMF, the higher the solar wind dynamic pressure, the faster the magnetopause standoff distance reaches the planetary surface. When the solar wind conditions are normal (with a dynamic pressure of 8 nPa) or the IMF is purely northward, the dayside magnetosphere does not disappear. The results provide a clear physical image of DDM events from a 3‐D perspective.