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Femtosecond laser with pulse duration of 35 fs is used to introduce optical breakdown in water and ethanol. The initial dynamics of the laser-introduced break down is investigated with a time resolved shadow imaging method. The motion of the shock wave front at 600 ps, 4 ns, 12 ns, 16 ns, and 20 ns are observed. Experimental results indicate that under the same laser energy, the initial velocity of the shock wave generated in ethanol is slightly lower than that in water. This is mainly determined by liquid properties (viscosity coefficient, density, molecular weight, breakdown threshold). The evolution of the shock wave also indicates that the velocity decreases with time, and the decrease in ethanol is faster than that in water. [ABSTRACT FROM AUTHOR]

Femtosecond laser with pulse duration of 35 fs is used to introduce optical breakdown in water and ethanol. The initial dynamics of the laser-introduced break down is investigated with a time resolved shadow imaging method. The motion of the shock wave front at 600 ps, 4 ns, 12 ns, 16 ns, and 20 ns are observed. Experimental results indicate that under the same laser energy, the initial velocity of the shock wave generated in ethanol is slightly lower than that in water. This is mainly determined by liquid properties (viscosity coefficient, density, molecular weight, breakdown threshold). The evolution of the shock wave also indicates that the velocity decreases with time, and the decrease in ethanol is faster than that in water.

Abstract The velocity of laser-induced shock waves affects the efficiency and efficacy of laser-based processes. The ability to accurately estimate shock wave velocity is critical for optimizing experimental combinations, creating laser-based systems, and assuring desired results. Traditional approaches to predict shock wave velocity involve empirical equations and analytical models based on simplified assumptions. However, these methods often lack accuracy and fail to capture the complex dynamics of laser-matter interactions. To overcome these limitations, we used a combination of an artificial neural network and a genetic algorithm to predict shock wave velocity. In this method, the neural network structure is dynamically designed. The optimization method does this by modifying the neural network's weights and figuring out the network's structure on our behalf. Based on the findings, our suggested technique worked very well; it surpassed other comparison methods by achieving the lowest average errors in terms of RMSE and MAE, which are 4.38 and 3.74, respectively. Moreover, the analysis has shown that our proposed method has a high level of reliability in predicting impulsive wave velocity using a neural network.

The measurement process of ground shock wave overpressure is influenced by complex field conditions, leading to notable errors in peak measurements. This study introduces a novel pressure measurement model that utilizes the Rankine−Hugoniot relation and an equilateral ternary array. The research delves into examining the influence of three key parameters (array size, shock wave incidence angle, and velocity) on the precision of pressure measurement through detailed simulations. The accuracy is compared with that of a dual-sensor array under the same conditions. Static explosion tests were conducted using bare charges of 0.3 kg and 3 kg TNT to verify the numerical simulation results. The findings indicate that the equilateral ternary array shock wave pressure measurement method demonstrates a strong anti-interference capability. It effectively reduces the peak overpressure error measured directly by the shock wave pressure sensor from 17.73% to 1.25% in the test environment. Furthermore, this method allows for velocity-based measurement of shock wave overpressure peaks in all propagation direction, with a maximum measurement error of 3.59% for shock wave overpressure peaks ≤ 9.08 MPa. [ABSTRACT FROM AUTHOR]

The variation of shock-wave velocity with time induced by a millisecond-nanosecond combined pulse laser (CPL) on silicon is investigated. The convolution neural network (CNN) is used to predict the shock-wave velocity induced by a single ns laser and CPL with a ns laser energy density of 6, 12 and 24 J/cm2, ms laser energy density of 0 and 226.13 J/cm2, and pulse delay of 0, 0.4 and 0.8 ms. The four-layer CNN model was applied, ns laser energy density, ms laser energy density, pulse delay and time were set as the input parameter, while the shock-wave velocity was set as the output parameter. The correlation coefficient (R2), mean absolute error (MAE) and root mean square error (RMSE) of the CNN model on the test data set was 0.9865, 3.54 and 3.01, respectively. This indicated that the CNN model shows a high reliability in the prediction of CPL-induced shock-wave velocity with limited experimental data. [ABSTRACT FROM AUTHOR]

The variation of shock-wave velocity with time induced by a millisecond-nanosecond combined pulse laser (CPL) on silicon is investigated. The convolution neural network (CNN) is used to predict the shock-wave velocity induced by a single ns laser and CPL with a ns laser energy density of 6, 12 and 24 J/cm2, ms laser energy density of 0 and 226.13 J/cm2, and pulse delay of 0, 0.4 and 0.8 ms. The four-layer CNN model was applied, ns laser energy density, ms laser energy density, pulse delay and time were set as the input parameter, while the shock-wave velocity was set as the output parameter. The correlation coefficient (R2), mean absolute error (MAE) and root mean square error (RMSE) of the CNN model on the test data set was 0.9865, 3.54 and 3.01, respectively. This indicated that the CNN model shows a high reliability in the prediction of CPL-induced shock-wave velocity with limited experimental data.

Technological progress demands accurate measurements of rapidly changing pressures. This, in turn, requires the use of dynamically calibrated pressure meters. The shock tube enables the dynamic characterization by applying an almost ideal pressure step change to the pressure sensor under calibration. This paper evaluates the effect of the dynamic response of a side-wall pressure measurement system on the detection of shock wave passage times over the side-wall pressure sensors installed along the shock tube. Furthermore, it evaluates this effect on the reference pressure step signal determined at the end-wall of the driven section using a time-of-flight method. To determine the errors in the detection of the shock front passage times over the centers of the side-wall sensors, a physical model for simulating the dynamic response of the complete measurement chain to the passage of the shock wave was developed. Due to the fact that the use of the physical model requires information about the effective diameter of the pressure sensor, special attention was paid to determining the effective diameter of the side-wall pressure sensors installed along the shock tube. The results show that the relative systematic errors in the pressure step amplitude at the end-wall of the shock tube due to the errors in the detection of the shock front passage times over the side-wall pressure sensors are less than 0.0003%. On the other hand, the systematic errors in the phase lag of the end-wall pressure signal in the calibration frequency range appropriate for high-frequency dynamic pressure applications are up to a few tens of degrees. Since the target phase measurement uncertainty of the pressure sensors used in high-frequency dynamic pressure applications is only a few degrees, the corrections for the systematic errors in the detection of the shock front passage times over the side-wall pressure sensors with the use of the developed physical dynamic model are, therefore, necessary when performing dynamic calibrations of pressure sensors with a shock tube. [ABSTRACT FROM AUTHOR]

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Detonation metrology is essential for the development of energetic materials, to characterize existing explosives, and to characterize materials behavior under high pressures. The optical active method (OAM), based on PMMA optical fibers (250 μm diameter) and their radiation transmission loss when shocked, was used to characterize the detonation wave (DW) and shock wave (SW) in inert barriers and applied to measure the detonation pressure in condensed explosives. The detonation velocity and detonation pressure of a PBX based on PETN (86 % PETN, 14 % Sylgard), known as Seismoplast were measured. The OAM with protected optical probes (POP) was used to determine the mean detonation velocity (7337 m s−1), whereas the OAM with bare optical probes (BOP) was used to measure the induced shock velocities generated by Seismoplast on different thicknesses of PMMA (1–9 mm), aluminum and copper (1–7 mm). Based on the shock velocities at the interfaces between the explosive and the inert barriers, the CJ pressure of Seismoplast was determined as 21.2 GPa. [ABSTRACT FROM AUTHOR]

This paper presents the measurement method and results applicable to the pressure pulses and thermal effects generated by an explosion of an unguided thermobaric rocket missile warhead. The determination results include the shock wave pressure and velocity, the TNT equivalents of the thermobaric warheads, and the personnel strike radii of the shock wave. An estimation of the temperature increase rates at the shock wave front was also undertaken.

Time-resolved visualisation of shock wave motion within a powered resonant tube (PRT) is presented for the regurgitant mode of operation. Shock position and velocity are measured as functions of both time and space from ultra-high-speed schlieren visualisations. The shock wave velocity is seen to vary across the resonator length for both the incident and reflected waves. Three mechanisms are explored as explanations for the variation in velocity: change in local fluid velocity, variation in shock strength and variations in local temperature. For the incident wave, local fluid velocity and shock strength are extracted from the data and both are demonstrated to contribute to the observed variation, with a non-trivial remainder likely explained by variation in temperature. [ABSTRACT FROM AUTHOR]

Three heat integrated air separation columns (HIASCs) with different purities (low purity, moderate purity and high purity) are presented, and the open-loop dynamic behaviors are studied. A shock wave velocity is derived for HIASC, and based on that a nonlinear wave model of the HIASC is further established. Combined with the proposed wave model, a novel model predictive control scheme (SWMPC) is carried out, which is compared with a conventional model predictive control scheme (MPC). The comparison simulation results show that SWMPC can work better than MPC, especially for the high-purity HIASC. [ABSTRACT FROM AUTHOR]