Standoff Distance Research Articles

Single-Shot Standoff Hyperspectral Raman Imaging of a Chemical Warfare Agent Simulant.

We demonstrate single-shot standoff hyperspectral Raman imaging of liquid diisopropyl methylphosphonate at a standoff distance of 1 m using two different techniques: multi-bandpass filter imaging (MBFI) and fiber-bundle imaging spectroscopy (FBIS). We find that MBFI has good spatial resolution, but poor spectral resolution, due to the limitations of commercially available bandpass filters. On the other hand, we find FBIS to have excellent spectral resolution, but limited spatial resolution due to the relatively small number of fibers in a bundle. For FBIS, we also determine, for a 1 m standoff distance, a minimum pump fluence of 10 mJ/cm to obtain good single-shot spectra.

A Study of Cavitation Erosion in Artificial Submerged Water Jets

The artificially submerged cavitation water jet is effectively utilized by ejecting a high-pressure water stream into a low-pressure water stream through concentric nozzles and utilizing the cavitation phenomenon generated by the shear layer formed between the two streams. In this study, we investigated the cavitation characteristics of artificially submerged cavitation water jets by combining numerical simulations and erosion experiments. The results indicate that an appropriate standoff distance can generate more cavitation clouds on the workpiece surface, and the erosion characteristics of the artificially submerged cavitation water jet are most pronounced at a dimensionless standoff distance of SD = 30. The shear effect formed between the two jets plays a crucial role in generating initial cavitation bubbles within the flow field of the artificially submerged cavitation water jet. Moreover, increasing the convergent angle between the two jets can significantly enhance the cavitation effect between them and lead to a more substantial cavitation effect. Simultaneously, increasing the pressure of the high-pressure inner nozzle also contributes to enhancing the cavitation effect of the artificially submerged cavitation water jet.

Machinability study on abrasive waterjet drilling of YSZ-coated inconel 718 superalloy: optimization and modelling by machine learning

The purpose of this research is to ascertain the optimal abrasive waterjet drilling parameters for making holes on Inconel 718 superalloy coated with yttrium-stabilized zirconia, namely waterjet pressure (JP), standoff distance (SD), abrasive flow rate (FR), and angle of impact (AI). The study explores the predictive modeling of the entry diameter (DN) and exit diameter (DX) of the drilled holes using an amalgamation of experimental analysis, response optimization and machine learning approaches. Eight different ML techniques are used to predict DN and DX. Better values of DN = 1.31352 mm and DX = 1.00515 mm are obtained through Random Forest for the setting of JP = 175 MPa, FR = 250 g min−1, SD = 1.45455 mm, and AI = 0.909091 deg. Further, the tuning of hyperparameters of Random Forest algorithm is performed to study the improvement in measuring DN and DX. The least value of total absolute error = 0.468 is observed while finding the DN and DX using Random Forest algorithm than the traditional response optimization method with reference to the confirmation test results. The work provides important insights for enhancing the machinability of YSZ-coated Inconel 718 superalloy utilizing the AWJ drilling process by bridging the gap between manufacturing research, machine learning, and real-world applications.

Simulation of the Effect of Particle-bubble Size Ratio on the Collapsing Dynamics of a Cavitation Bubble Near a Particle

Abstract The synergistic effect of cavitation bubbles and sediment particles on material damage is a significant problem in fluid machinery. The dynamic behavior of a cavitation bubble near a spherical particle were simulated in this study using the Volume of Fluid (VOF) method. The effects of the particle-bubble size ratio δ on the bubble profiles, the collapse time, the micro-jets and the pressure at the particle surface have been investigated under the conditions of three values of stand-off distance γ. The results show that (1) the bubble collapse time rises as the particle-bubble size ratio δ increases; (2) the peak values of the maximum jet velocity and the maximum pressure exerting on the particle appear at γ = 1.0 and δ = 1.2, which are 165.3 m/s and 10.46 MPa, respectively; (3) the influence on the particle caused by the micro-jets cannot be ignored when the stand-off distance is less than 1.5.

Deep learning-based prediction of CME-driven shock standoff distances in metric type II radio emissions

Deep learning-based prediction of CME-driven shock standoff distances in metric type II radio emissions

Dynamics of a cavitation bubble confined in a thin liquid layer at null Kelvin impulse

In this work, we experimentally and numerically investigate cavitation bubble dynamics in a thin liquid layer surrounded by gas. We focus on configurations featuring strongly confined bubbles at dimensionless bubble-free surface stand-off distances D* below unity. Additionally, we impose the condition of null Kelvin impulse, subjecting a bubble to the oppositely equal influence of two opposing free surfaces, resulting in the formation of two convergent water jets. We observe a diverse spectrum of jetting phenomena, including broad jets, mushroom-capped jets, and cylindrical jets. These jets become progressively thinner and faster with lower D* values, reaching radii as small as 3% of the maximal bubble radius and speeds up to 150 m/s. Numerical results reveal a linear relationship between the jet impact velocity and the local curvature at the bubble region proximal to the free surface. This suggests that the magnitude of bubble deformation during its growth phase is the primary factor influencing the observed fivefold increase in the jet impact velocity in the parameter space considered. Our findings show that bubble collapse intensity is progressively dampened with increased confinement of its environment. As D* decreases beyond a critical value, the liquid layer separating the bubble and ambient air thins, leading to the onset of interfacial shape instabilities, its breakdown, and bubble atomization. Furthermore, we compare bubbles at zero Kelvin impulse to corresponding anisotropic scenarios with a single free surface, revealing that the dynamics of axial jets until the time of impact is primarily influenced by the proximal free surface. The impact of convergent axial jets at null Kelvin impulse results in local pressure transients up to 100 MPa and triggers the formation of a fast and thin annular outflow in the form of a liquid sheet, affected by the Rayleigh–Plateau and flapping shape instability.

Sandstone breaking performances and mechanisms of swirling abrasive waterjet during radial jet drilling process

Radial jet drilling (RJD) is one of the emerging hydrocarbon drilling technologies. And, the swirling abrasive waterjet (SAWJ) is expected to drill larger diameter laterals during RJD. Here, the performances and mechanisms of SAWJ breaking sandstone were studied by laboratory experiments. Results showed that the SAWJ could drill a smooth (surface roughness was 0.043 mm) & large (diameter was in 52.0–73.0 mm) circular hole on sandstone. The hole depth/volume increased as the jetting pressure, abrasive mass concentration and exposure time increased. Conversely, they decreased as the standoff distance increased. The optimal parameter combination under our experimental conditions was 30 MPa, 0 mm, 12% and 1 min. The SAWJ sandstone breaking mechanism were the erosion of cements, the integrally peeled off and broken of crystal grain. Failure mode of sandstone was mainly the tensile fracture. The key findings will provide guidance for the application of SAWJ in RJD technology.

Bulge-Free and Homogeneous Metal Line Jet Printing with StarJet Technology.

The technology to jet print metal lines with precise shape fidelity on diverse substrates is gaining higher interest across multiple research fields. It finds applications in additively manufactured flexible electronics, environmentally friendly and sustainable electronics, sensor devices for medical applications, and fabricating electrodes for solar cells. This paper provides an experimental investigation to deepen insights into the non-contact printing of solder lines using StarJet technology, eliminating the need for surface activation, substrate heating, curing, or post-processing. Moreover, it employs bulk metal instead of conventional inks or pastes, leading to cost-effective production and enhanced conductivity. The effect of molten metal temperature, substrate temperature, standoff distance, and printing velocity was investigated on polymer foils (i.e., PET sheets). Robust printing parameters were derived to print uniform, bulge-free, bulk metal lines suitable for additive manufacturing applications. The applicability of the derived parameters was extended to 3D-printed PLA, TPU, PA-GF, and PETG substrates having a much higher surface roughness. Additionally, a high aspect ratio of approx. 16:1 wall structure has been demonstrated by printing multiple metal lines on top of each other. While challenges persist, this study contributes to advancing additively manufactured electronic devices, highlighting the capabilities of StarJet metal jet-printing technology.

Numerical and experimental study on effect of induction heating parameters on the coating of Zn layer on mild steel

The objective of the study is to determine the most effective induction heating parameters for melting pure zinc selectively over the mild steel substrate surface. The numerical simulation on effect of induction heating parameters on the mild steel substrate is studied using COMSOL Multiphysics 5.6 software. The optimised effective parameters are used for the experimental analysis for the validation. Variables such as coil configuration, stand-off distance (SOD), coil current and frequency were systematically changed, and optimal settings were chosen on the basis of time temperature contour curve and the heating rate within the material. Results of the numerical analysis portrayed that a pancake coil geometrical configuration, SOD of 2 mm, coil current of 300 A and alternating frequency of 300 kHz were found as the optimum set of parameters for the effective surface repair. An experimental investigation was carried out by depositing a thin layer of zinc on mild steel substrate using the optimized parameters. The surface integrity of the coated specimen was examined through the high-resolution optical microscopy, X-ray diffraction and electron back scattered diffraction (EBSD) techniques. The hardness property of the coated specimen was examined with a Vickers microhardness tester. The microstructure analysis and hardness measurement showed that consistent coating is achieved without affecting the base metal/substrate properties. The experimental results very much coincide with the numerical simulation.

Influence of Post-Heat Treatment on the Characteristics of FeCrBMnSi Coating on Stainless Steel 304 Substrate Prepared by Twin Wire Arc Spray (TWAS) Method at Various Stand-off Distance

Influence of Post-Heat Treatment on the Characteristics of FeCrBMnSi Coating on Stainless Steel 304 Substrate Prepared by Twin Wire Arc Spray (TWAS) Method at Various Stand-off Distance

Analytical assessment of hetero-/homogeneous combustion of magnesium particle: Fully explicit formulas for flame characteristics

In this study, by proposing a comprehensive multi-step model, the combustion of magnesium particles in O2-He, O2-Ar, and O2-N2 is scrutinized. In the current model, both the heterogeneous and homogeneous combustions are considered and the process is divided into four stages solid, liquid, and gas combustion and melting. Moreover, the diffusions of oxygen and unreacted magnesium to droplet and infinity together with surface exothermic reaction are considered. The governing equations are analytically solved and then, the formulas are extracted for combustion time and temperature, flame standoff distance, and evaporation rate as the functions of particle diameter, ambient temperature and pressure, oxygen mass fraction, type of inert gas, and Lewis numbers. For 120 µm particle and oxygen content of 0.05, time contributions of homogeneous and heterogeneous combustions are 85.8% and 14.2%, respectively. The burning time has drastic changes at ambient pressures below l atm, so that the burning time variations relative to the pressure in the environments less than 1 atm and greater than it are equal to 1200–1550 and 70–90 ms/atm, respectively. When the oxygen mass fraction is less than 0.29, combustion in helium-oxygen ends earlier than that in O2-Ar and O2-N2, but for the mass fraction greater than 0.35, it has the longest burning time.

A study of streamline geometries in subsonic and supersonic regions of compressible flow fields

The geometrical properties of streamlines, such as the curvatures, directions and positions, are studied in steady inviscid compressible flow fields via differential geometry theories and conservation laws. The influences of the streamline geometries on the flow speeds and pressures are also identified and discussed. By transforming the streamlines to fill the domain and satisfy the boundary conditions, a unified geometry-based solver, the streamline transformation method, is proposed for both subsonic and supersonic regions. The governing equations and boundary conditions along streamlines and shock waves are also derived. This method is verified by numerical results of three typical flow fields, including the subsonic channel flow, the supersonic downstream of attached shock waves and especially the subsonic/supersonic downstream of detached bow shock waves. Both two-dimensional planar and axisymmetric flow fields are considered. Compared with the results from computational fluid dynamics, good agreements are achieved by this method, while fewer computational resources, by an order of magnitude, are consumed. Features of these flow fields are also analysed from a geometrical perspective, such as flow speeds and pressures deviated by the wall curvatures, and three-dimensional effects in the after-shock flow fields. For a hyperbolic-shaped bow shock wave, the stand-off distances and the transitions from subsonic to supersonic regions are also discussed. As indicated by the accuracy, efficiency and applicability in a wide range of flow speeds, the streamline transformation method would be a potential candidate for the theoretical analysis and inverse design of high-speed flow fields, especially where the subsonic regions exist downstream of strong shock waves.

Jetting enhancement from wall-proximal cavitation bubbles by a distant wall

An additional distant wall is known to highly alter the jetting scenarios of wall-proximal bubbles. Here, we combine high-speed photography and axisymmetric volume of fluid (VoF) simulations to quantitatively describe its role in enhancing the micro-jet dynamics within the directed jet regime (Zeng et al., J. Fluid Mech., vol. 896, 2020, A28). Upon a favourable agreement on the bubble and micro-jet dynamics, both experimental and simulation results indicate that the micro-jet velocity increases dramatically as $\eta$ decreases, where $\eta =H/R_{max}$ is the distance between two walls $H$ normalized by the maximum bubble radius $R_{max}$ . The mechanism is related to the collapsing flow, which is constrained by the distant wall into a reverse stagnation-point flow that builds up pressure near the bubble's top surface and accelerates it into micro-jets. We further derive an equation expressing the micro-jet velocity $U_{jet}=87.94\gamma ^{0.5}(1+(1/3)(\eta -\lambda ^{1.2})^{-2})$ , where ${\gamma =d/R_{max}}$ is the stand-off distance to the proximal wall with $d$ the distance between the initial bubble centre and the wall, $\lambda =R_{y,m}/R_{max}$ with $R_{y,m}$ the distance between the top surface and the proximal wall at the bubble's maximum expansion. Viscosity has a minimal impact on the jet velocity for small $\gamma$ , where the pressure buildup is predominantly influenced by geometry.

Experimental investigations with machine learning techniques for understanding of erosion wear in advanced aluminum nanocomposites

This article addresses the significant challenge of erosion wear in aluminum composites, particularly in industries such as automotive, aerospace and energy, where sustained material performance is crucial. The study focuses on the experimental investigation of erosive wear characteristics exhibited by advanced aluminum nanocomposites, utilizing an air jet erosion wear test apparatus. The erosion wear tests were conducted using diverse parameters, such as angles (30°, 45°, 60° and 90°), air pressures (1–4 bar) and a fixed 600-s duration, maintaining a constant sand particle feed rate of 2.0 (g/min) and utilizing stand-off distances of 10, 15 and 20 mm. Surface assessments were conducted using field emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS). The results revealed observable specimen wear, particularly at a 45° angle, with wear rates decreasing at higher impingement angles and reaching a minimum at 90°. Notably, the Al-4 wt.%TiC nanocomposites exhibited a 25% improvement in wear resistance compared to the base alloy. Further analysis of eroded surfaces through (FE-SEM) revealed a mechanism involving micro-cutting, plowing and grain pull-out, attributing wear primarily to plastic deformation and crack formation. Evaluating erosive wear results through six machine learning (ML) models demonstrated that gradient boosting regression emerged as the most accurate, achieving an R2 value of 0.97. This highlights the effectiveness of ML in predicting erosion wear rates and offers insights for improving aluminum composite materials in demanding industrial applications.

Cold spray processing of AA2024/Al2O3 coating on magnesium AZ31B alloy: Process parameters optimization, microstructure and adhesive strength performance of coating

The automotive and aerospace sectors are progressively employing the magnesium (Mg) alloy of the grade AZ31B because of its excellent castability, low density, and high ratio of strength to weight. Nevertheless, the limited ability of AZ31B alloy to withstand corrosion limits their use in several fields of technology. In order to solve this problem, the AZ31B alloy is coated utilizing an AA2024/Al2O3 metal matrix composite (MMC) coating that is applied by the cold spray coating (CS) method. The primary goal of this work is the parametric optimization of CS process for maximizing adhesive strength of MMC-coated Mg-alloy substrate. Response surface methodology (RSM) is implemented to find the optimum CS parameters, including feed rate of powder – FRP (g/min), standoff distance of gun – SDG (mm) and processing temperature – TEMP (°C). The regression-based parametric adhesion strength prediction (ASP) model was formulated using the RSM and statistically validated using analysis of variance (ANOVA). Employing 3D surface of responses, the influence of CS parameters on the adhesion strength of an MMC-coating was assessed. The findings revealed that when the MMC-coating was cold sprayed on the Mg-alloy using FRP of 22 g/min, SDG of 12 mm, and TEMP of 520 °C, the maximum adhesion strength of MMC-coating was 70 MPa (actual). Given less than 2% error at 95% confidence, the parametric ASP model correctly predicted the adhesion strength of the MMC-coating. The ANOVA findings showed that FRP (g/min) had significant effect on adhesive strength of MMC-coating followed by SDG (mm) and TEMP (°C). The MMC-coating applied using the RSM optimized CS parameters showed 70.73% superior adhesive strength owing to the lower porosity formation of 2 vol% which offers greater interfacial area. The ASP equation was formulated using the “best fitting line” approach and validated using ANOVA for predicting the adhesive strength (MPa) from the porosity formation (vol%) in the MMC-coating.

Prediction and optimization kerf width in laser beam machining of titanium alloy using genetic algorithm tuned adaptive neuro-fuzzy inference system

In the power diode laser beam machining (DLBM) process, the kerf width (KW) and surface roughness (SR) are important factors in evaluating the cutting quality of the machined specimens. Apart from determining the influence of process parameters on these factors, it is also very important to adopt multi-response optimization approaches for them, in order to achieve better processing of specimens, especially for hard-to-cut materials. In this investigation, adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm tuned ANFIS (GA-ANFIS) were used to predict the KW on a titanium alloy workpiece during DLBM. Five machining process factors, namely power diode, standoff distance, feed rate, duty cycle, and frequency, were used for the development of the model due to their correlation with KW. As in some cases, traditional soft computing methods cannot achieve high accuracy; in this investigation, an endeavor was made to introduce the GA-assisted ANFIS technique to predict kerf width while machining grooves in a titanium alloy workpiece using the DLBM process based on experimental results of a total of 50 combinations of the process parameters. It was observed that FIS was tuned well using the ANN in the ANFIS model with an R2 value of 0.99 for the training data but only 0.94 value for the testing dataset. The predicting performance of the GA-ANFIS model was better with less value for error parameters (MSE, RMSE, MAE) and a higher R2 value of 0.98 across different folds. Comparison with other state-of-the-art models further indicated the superiority of the GA-ANFIS predictive model, as its performance was superior in terms of all metrics. Finally, the optimal process parameters for minimum KW and SR, from gray relational–based (GRB) multi-response optimization (MRO) approach, were found as 20 W (level 2) for laser power, 22 mm (level 5) for standoff distance, 300 mm/min (level 5) for feed rate, 85% (level 5) for duty cycle, and 18 kHz (level 3) for frequency.

Behavior of steel liner tray walls under external blast: Experimental testing and numerical simulations

Explosions produced in urban or industrial areas due to accidental or intentional detonation of explosives are low-probability but high-impact events. If standoff distance from buildings or other constructions is small, explosions can cause structural failures and serious injuries or deaths of occupants. Although heavy/stiff enclosure systems were long considered appropriate to protect buildings against explosive threats, lighter and flexible steel-based systems, which are increasingly used for modern buildings, may also provide satisfactory performance. The study presents the results of full-scale blast tests on liner tray walls attached to a steel frame building. Walls were tested against increasing blast charges until failure. Due to very high peak pressures and very short durations, the loading regime could be classified as impulsive. The ultimate strength is given by the failure of the end fasteners, after large bolt hole elongations coupled with the pull-through of the end fasteners. If the insulation and outer cladding are lost, the liner trays are directly exposed to blast and the seaming fasteners at overlapping sheets are prematurely lost. As a result, the wall panels work mostly independently, as one-way elements. On the contrary, if the outer cladding protects the seaming fasteners, the overlapping provides additional capacity due to membrane effect (two-way behavior). Numerical models were calibrated using test data and were further used to obtain more information about liner tray behavior under blast.

Experimental Analysis of Kerf Characteristics of Carbon Fiber-Reinforced Polymer with Abrasive Water Jet Machining

<div>This research looks into how abrasive water jet machining (AWJM) can be used on carbon fiber-reinforced polymer (CFRP) materials, specifically how the kerf characteristics change with respect to change in process parameters. We carefully looked into four important process parameters: stand-off distance (SOD), water pressure (WP), traverse rate (TR), and abrasive mass flow rate (AMFR). The results showed that as SOD goes up, the kerf taper angle goes up because of jet dispersion, but as WP goes up, the angle goes down because jet kinetic energy goes up. The TR was directly related to the kerf taper angle, but it made the process less stable. The kerf drop angle was not greatly changed by AMFR. When it came to kerf top width, SOD made it wider, WP made it narrower, TR made it narrower, and AMFR made it a little wider. When the settings (SOD: 1 mm, WP: 210 MPa, TR: 150 mm/min, AMFR: 200 g/min) were optimized, the kerf taper angle and kerf top width were lowered. This improved the accuracy of the measurements and cut down on material waste in CFRP composite machining. These results make it clear how important parameter selection is in precision cutting.</div>

Effective optimization strategies for abrasive water jet machining of glass-carbon fiber reinforced composites: A comparative study of evolutionary optimization techniques

This study applied evolutionary optimization techniques and neural networks to predict optimum machining parameters of Abrasive Water Jet Machining (AWJM) for machining Glass-Carbon Fiber Reinforced Composite (GCFRC) materials. Several researchers have employed different optimization techniques; however, evolving computational capabilities further open avenues to optimize such parameters. Five evolutionary techniques, namely Artificial Neural Network (ANN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Nonlinear Least Square Error (LSE), were applied to minimize surface roughness (Ra) and maximize kerf width (Kw) and material removal rate (MRR). The output performance parameters (Ra, Kw, and MRR) were formulated as a linear mathematical function of machining parameters: tool feed rate (TFR), cutting speed rate (CSR), and stand-off distance (SOD). Though this study solves linear optimization problems, the proposed technique will be a strong tool for solving complex associations of machining and performance parameters in the future. A dataset of machining parameters and subsequent performance parameters was adopted from the available literature. The results indicated that the LSE method outperformed other techniques, yielding the lowest Root Mean Square Error (RMSE) in predicting Ra, Kw, and MRR, thus ensuring high machining accuracy. LSE technique reported relatively least RMSE values of 0.37 µm, 0.149Mm, and 237.23 mm3/min for Ra, Kw, and MRR, respectively. SA and PSO displayed identical and competitive RMSE values, slightly higher than LSE (up to 20 % higher). ANN and GA techniques were not effective relative to other considered techniques. LSE, SA, and PSO provide superior performance in optimizing AWJM parameters. The significant contribution of this research is the proposed optimization technique, offering a clear direction for solving complex associations between the performances and machining parameters of AWJM. This work also provides a foundation for future research to optimize such associations for other machining setups.

Experimental study on cavitation water jet cleaning of marine fouling

The accumulation of marine fouling on a ship’s hull can increase its fuel consumption, necessitating removal. The use of a cavitation water jet as an efficient method for cleaning marine fouling has been widely adopted. In the research, experiments are conducted on water jet cleaning of marine fouling to investigate the influence of water jet parameters on cleaning efficiency. The findings reveal that the surface damage to specimens was minimized when maintaining an erosion pressure of 16 MPa, employing a 25 mm standoff distance, and applying a 90° incidence angle. This research can provide theoretical guidance for subsequent optimization of cavitation water jet cleaning parameters.