Shock Propagation Research Articles

Lie symmetry method to discuss the optimal system of Lie subalgebras and similarity solutions for shock propagation in a perfectly conducting dusty gas with magnetic field in rotating medium

In this paper, the similarity solutions for the shock wave propagation in a perfectly conducting dusty gas under the effect of axial or azimuthal magnetic field in the case of rotating medium by using Lie symmetry method have been discussed. The optimal system of one-dimensional Lie subalgebras related to the hyperbolic system of nonlinear partial differential equations had been constructed by using general invariant function and general adjoint transformation matrix. The optimal system is the collection of inequivalent optimal classes, which provides crucial information regarding different types of the similarity solutions. On the basis of the optimal system, we have discussed all possible similarity solutions for inequivalent optimal classes individually. Also, we have found that the similarity solutions exist in two cases for power law shock path and in one case with exponential law shock path. The shock wave decay is due to an increment in the physical parameter such as shock Cowling number or non-idealness parameter or adiabatic exponent or rotational parameter. For smaller value of the ratio of density of solid particles to initial species density of the gas i.e. [Formula: see text], the shock strength decreases with an increment in the mass fraction of solid particles in the mixture [Formula: see text], but the shock strength decreases as [Formula: see text] increases for [Formula: see text]. Also, the shock strength increases with an increment in [Formula: see text] at constant [Formula: see text]. It is observed that the shock wave is stronger in the presence of axial magnetic field as compared to azimuthal magnetic field.

Insights into spatio-temporal dynamics during shock–droplet flame interaction

This study comprehensively investigates the response of a combusting droplet during its interaction with a high-speed transient flow imposed by a coaxially propagating blast wave. The blast wave is generated using a specially designed miniature shock generator that produces blast waves using the wire-explosion technique, facilitating a wide range of Mach numbers (1.03 < Ms < 1.8). The experiments are performed in two configurations: open field and focused blast wave. The charging voltage and the configuration determine the Mach number (Ms) and flow characteristics. The flame is found to exhibit two major response patterns: partial extinction followed by reignition and full extinction. Increasing the Mach number (Ms > 1.1) makes the droplet flame more vulnerable to extinction. Additionally, the flame exhibits stretching and shedding, followed by reignition at lower Mach numbers (Ms < 1.06). In all cases, the flame base lifts off in response to the imposed flow, and the advection of the flame base interacting with the flame tip results in flame extinction. The entire interaction occurs in two stages: (i) interaction with the blast wave and the decaying velocity profile associated with it, and (ii) interaction with the induced flow behind the blast wave as a result of the entrainment (delayed response). Alongside the flame's response, the droplet also interacts with the flow imposed by the blast wave, exhibiting different response modes including pure deformation, Rayleigh–Taylor piercing bag breakup and shear-induced stripping.

Study on solid powder fuel transport characteristics and mixing degree in scramjet combustor

Abstract The powder scramjet engine is considered the best engine for hypersonic weapons because of its advantages of easy adjustment, flame stability, and high efficiency. However, due to the extremely short residence time of particle fuel in the combustion chamber under high Mach conditions, there is a risk of fuel mixing. Based on the existing combustion chamber models of scramjet engines, this paper proposes a new solid fuel blending enhancement structure by combining shock generator structure and transverse jet and compares the performance and mass transfer characteristics of different shock generators. The CFD method is used to solve the RANS formula to simulate the particle transfer process, and the SST k-ω model is used to calculate the complex turbulence. It was found that when the reverse shock generator was used, the mixing degree of solid particles was higher.

Inactivation of MS-2 virus in water by rotational generator of hydraulic shock

This study investigates the effect of hydraulic shock waves on inactivation of MS-2 bacteriophage, a norovirus surrogate. A falling circular jet of water spiked with the MS-2 (∼1000 PFU/mL) was repeatedly impacted by a rotating blade, resulting in occurrence of hydraulic shock waves within the liquid region adjacent to the impact. The proof-of-concept rotational generator of hydraulic shock treating 9 L of water spiked with viruses was able to achieve 3 logs reduction of viral plaque count within 80–100 liquid passes at moderate blade impact velocities (namely, 70 and 88 m/s) despite the water temperature not exceeding 40 °C and no detectible cavitation. Within the first 20 liquid passes, most MS-2 capsid proteins were degraded, with their concentration reduced from 22 μg/mL to only 7.3 μg/mL. Due to the lack of further capsid protein destruction, additional reduction in MS-2 plaque count in subsequent 80 passes is indicative of damage inflicted to the viral recognition receptors. All this suggests that shockwaves of moderate amplitude (few tens of MPa) alone are sufficient for effective viral inactivation. Considering this and the device's good scalability potential, rotational hydraulic shock generators could prove effective in treating virus-contaminated waters.

PIC simulation of a nonoscillatory perturbation on a subcritical fast magnetosonic shock wave

Abstract We use a two-dimensional particle-in-cell (PIC) simulation to study the propagation of subcritical fast magnetosonic shocks in electron-nitrogen plasma and their stability against an initial deformation. A slab of dense plasma launches two planar blast waves into a surrounding ambient plasma, which is permeated by a magnetic field that points out of the simulation box and is spatially uniform at the start of the simulation. One shock propagates into a spatially uniform ambient plasma. This reference shock has a Mach number of 1.75, and the heating of ions only along the shock normal compresses the ions that cross the shock to twice the upstream density. Drift instabilities lead to rapidly growing electron-cyclotron harmonic waves ahead of the location where the shock's density overshoot peaks, and to slowly growing lower-hybrid waves with a longer wavelength behind it. The second shock wave enters a perturbation layer that deforms it into a sine shape. Once the shock leaves the perturbation layer, the deformation is weakly damped and non-oscillatory, and the shock remains stable. Even without an external perturbation, and for the plasma parameters considered here, drift instabilities will cause ripples in the shock wave. These instabilities lead to a spatially and temporally varying compression of the plasma that crosses the shock.

Study of ablation and shock generation across three orders of magnitude of laser intensity with 100 ps laser pulses

The laser ablation and subsequent shock generation in solid targets plays an important role in a variety of research topics from equation of state models for materials to inertial confinement fusion. One of the long-standing issues is the knowledge of ablation depth in the picosecond time regime. We report on a direct technique for determining the ablation depth in aluminum using x-ray diffraction data from Linac Coherent Light Source at the Stanford Linear Accelerator Center. This technique gives a direct measurement of the shock wave propagation in the bulk target, enabling an ability to discern early timescale physics from late timescale effects not available in postmortem analysis. We find that the ablation depths only vary by 0.2 μm across three orders of magnitude of laser intensity, while the pressure increased by a factor of 10 following a square root dependence on laser pulse energy. We further observe that the ablation depth in this intensity range (1011–1013 W/cm2 in intensity, corresponding to 0.8–80 J/cm2 in fluence) cannot be modeled by a universal scaling law, given the complexity of the mechanisms governing laser ablation in this intensity regime.

Upstream propagation of shocks in supply chains: Evidence from earthquakes

AbstractWe investigate how natural disaster shocks to customers propagate upstream to suppliers’ investment. Using data from the major customers of Chinese listed firms and earthquake information during 2009–2019, we investigate the impact of customers’ earthquake exposure on corporate investment. We find that firms significantly reduce investment after their customers experience earthquakes, particularly for non‐state‐owned enterprises, firms with higher product uniqueness, firms in competitive industries, and firms in nondurable goods industries. Furthermore, our analysis highlights firms’ sales as one of the potential channels through which customers’ earthquake exposure influences firm investment. We also find that following an earthquake supplier firms reduce their transactions with the affected customers and develop alternative customers.

Dependence of green energy markets on big data and other fourth industrial revolution technologies

This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.

Shock Propagation Through a Square Injector: Investigation into Rotating-Detonation Engine Injector Dynamics

The rotating detonation engine is perhaps the most promising means to realize pressure-gain combustion in modern engines. The physical processes underpinning the dynamics of the combustion wave are complex, and a lack of understanding of these processes represents a significant barrier to practical implementation of the technology. A significant simplification of the RDE is considered through an abstracted experimental setup. The detonation wave is replaced with a nonreacting shock generated by a shock tube, and the annulus is unwrapped into a single linear channel. Both simplifications make direct visualization of the problem via schlieren imaging tractable. Several performance metrics are used to relate the fluid-dynamic behavior of the shock–injector interaction to the performance of a theoretical rotating detonation engine. The first such metric is “recovery time,” based on the time taken for the injector to return to a fully flowing state after the passage of a detonation wave. The second such metric not only considers the mass flow through the injector exit but also accounts for potential backflow into the injector nozzle that may occur for sufficiently strong waves. Finally, a reactant mass-deficit metric is used to characterize the reduction in mass injection due to the interaction with the wave.

Numerical study on cavitation generation induced by the high-speed jet impact on the water surface

The complex interaction between shock waves and two-phase interfaces can generate cavitation. In this study, the cavitation induced by the high-speed jet impact on the water surface was investigated. The mixture fluid is modeled using the barotropic equation of state under the framework of the two-phase flow model, which can describe the mixture of air, water, and vapor with any proportion. Through constructing a 1D Riemann problem for the impact-induced cavitation phase transition, it indicates that the coupling effect of multiple rarefaction waves emitted from the two-phase interface is responsible for the cavitation phase transition inside the liquid. Then, a 3D (three-dimensional) simulation regarding the impact of a high-speed jet on the water surface was conducted and validated against previous experiments that captured the cavitation phase transition phenomenon in the central region after the jet impact. The 3D simulation results revealed the spatial structure and development process of shock waves in detail. The coupling effects of shock waves and two-phase interfaces generate a ring-shaped rarefaction wave, which develops radially inward and superimposes, resulting in the formation of acorn-shaped cavitation bubble nuclei inside the water. The 3D simulation can provide spatial shock/rarefaction wave structures and internal flow details that have never been obtained in experiments, such as shock generation and propagation, rarefaction wave generation and center convergence, and the internal structure of acorn-shaped cavitation nucleation. Furthermore, the influence of the jet velocity on the cavitation intensity was analyzed, and a quantitative relationship was provided.

Sustenance of hydrogen–oxygen cellular detonation with ozone additions in confined space

The sustenance of cellular detonation under weak confinement is studied through two-dimensional (2D) numerical simulations of hydrogen–oxygen mixtures surrounded by inert gas. The results show that in the weakly confined space, the cellular detonation with Chapman-Jouguet velocity can survive by increasing the width of the reactant layer and enhancing the reactivity of reactants, which ensures enough triple points and high reactivity in the reactant layer for detonation sustenance since transverse shocks cannot be regenerated and reinforced by boundary reflection. By adding ozone into the system and changing the width of the reactant layer, the relationship between induction length and detonation sustenance is established. It is found that the sustenance of cellular detonation in the weakly confined space is related to the ratio of the reactant layer width to the induction length. Ozone reactions can reduce the induction length and enhance reactivity, thereby promoting the generation of new transverse shocks and significantly improving the sustenance of cellular detonation in weakly confined space.

SN 2021wvw: A Core-collapse Supernova at the Subluminous, Slower, and Shorter End of Type IIPs

We present detailed multiband photometric and spectroscopic observations and analysis of a rare core-collapse supernova, SN 2021wvw, that includes photometric evolution up to 250 days and spectroscopic coverage up to 100 days postexplosion. A unique event that does not fit well within the general trends observed for Type IIP supernovae, SN 2021wvw shows an intermediate luminosity with a short plateau phase of just about 75 days, followed by a very sharp (∼10 days) transition to the tail phase. Even in the velocity space, it lies at a lower velocity compared to a larger Type II sample. The observed peak absolute magnitude is −16.1 mag in r-band, and the nickel mass is well constrained to 0.020 ± 0.006 M ⊙. Detailed hydrodynamical modeling using MESA+STELLA suggests a radially compact, low-metallicity, high-mass red supergiant progenitor (M ZAMS = 18 M ⊙), which exploded with ∼0.2 × 1051 erg s−1 leaving an ejecta mass of M ej ≈ 5 M ⊙. Significant late-time fallback during the shock propagation phase is also seen in progenitor+explosion models consistent with the light-curve properties. As the faintest short-plateau supernova characterized to date, this event adds to the growing diversity of transitional events between the canonical ∼100 days plateau Type IIP and stripped-envelope events.

Connectedness and Shock Propagation in South African Equity Sectors during Extreme Market Conditions

This study examined the connectedness and propagation of risk in the South African equity sectors during the Global Financial Crisis (GFC), the European Debt Crisis (EDC), the US–China trade war, and the COVID-19 pandemic. Daily returns of nine Johannesburg Stock Exchange (JSE) super sectors were examined from 3 January 2006 to 31 December 2021. Applying the connectedness matrix and time-varying parameter vector autoregressive (TVP-VAR) model, in full sample and sub-periods, the study showed that dynamic total connectedness of the super sectors is high in absolute form (62%). Furthermore, it was found that the highest volatility connectedness was during the EDC (68.83%) and during the COVID-19 pandemic (68.57%), followed by the GFC (63.16%) and lastly the US–China trade war (42.09%), respectively. This suggests that the tendency for a systemic risk is highest during the EDC, COVID-19, and GFC periods, and lowest during the US–China trade war. The financial sector was the primary net-transmitter of shocks during the COVID-19 period, while the automobile and parts sector was the strongest net-transmitter of shocks during the GFC, EDC, and US–China trade war. Similarly, the strongest net recipient of shocks during GFC, EDC, and COVID-19 is the chemical super sector. The study concludes that there is a significant volatility connectedness among JSE super sectors. In addition, the JSE super sectors exhibit time-varying connectedness during extreme events. Moreover, the net-transmitter and net-receiver of shock do not change significantly during different crisis periods. The policy implications of the findings are highlighted in the concluding section.

Crypto network

The empirical literature has studied linkages in the cryptocurrency market because knowing how shocks pass from one currency to another helps policymakers and practitioners better counter their propagation in these and related markets. This paper contributes to this literature by proposing a methodology based on Granger causality and network analysis. Using the daily log-returns of 22 cryptocurrencies over the period 2018–2023, I develop a VAR model to infer unidirectional or bidirectional Granger causality among cryptocurrencies. These relationships are then transformed into a directed network and several centrality measures are calculated. The centrality measures are also observed over the years to understand the dynamics of the cryptocurrency network. I find out that each one unit increase in eigencentrality is associated with a 0.22 percent increase in log-returns. Cryptocurrencies are nontrivially connected, and in this sample Cardano, Dogecoin, Gridcoin, and Neo are amongst the most central in the network throughout the period. Some cryptocurrencies, such as Dogecoin or Neo, show decreasing centrality over the years, while others, such as Gridcoin, Litecoin, Namecoin, or Ripple, gain centrality. These results support the idea that the cryptocurrency market is no longer exclusively associated with Bitcoin and lay the groundwork for further study of shock propagation in financial markets.

A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus

ABSTRACT Transmission channels from monetary shocks might be identified by studying the features of the production network. The main aim of this paper is to provide insights about the role of production network into the propagation of monetary policy shocks in G7 economies. Time-varying Bayesian vector-autoregressions were built to compute impulse response functions of output to monetary policy shocks in these countries. Panel Auto-Regressive Distributed Lag Bound Approach based on Mean-Group estimator was used to assess the long and short-run connections between production network structure and various shocks associated to monetary policy in the period 2000–2018 and during the Great Recession (2007–2009). The results show that upstreamness is more significant than downstremness in the period 2000–2018, while the financial sector significantly contributed to the spread of various monetary shocks during the Great Recession.

Quantile Connectedness Across Socially Responsible Equity Markets of The BRICT Nations

This paper investigates the shock linkages between the socially responsible equity indices of Brazil, Russia, India, China, and Türkiye, by using the quantile connectedness approach that is used by Chatziantoniou et al. (2021), to assess the median-based and tail connectivity, we will analyse daily time series data from April 4, 2018, to March 31, 2023. The outcomes of the static and dynamic analyses can be summarized as follows: for static quantile connectedness, Russia and India are net transmitters of shock at the tails, while China is a net receiver. China and Türkiye are net receivers, whereas Brazil, India, and Russia are net transmitters at the median quantile. Considering the dynamic quantile connectedness assessment, the findings indicate that the magnitude of connectedness significantly increases positive and negative shock connectedness. This suggests that during periods of extreme market volatility, socially responsible equity indices in BRICT nations experience more pronounced shock propagation. This suggests that socially responsible investments are susceptible to contagion and, as a result, provide restricted portfolio diversification advantages during periods of extreme market volatility. The analysis also indicates that there was a substantial rise in the overall dynamic connection during the COVID-19 pandemic and the Russia-Ukraine war.

Stress field measurements using quantitative schlieren

Quantitative schlieren analysis is extended here to optically transparent solids in quasi-static and dynamic experiments to measure stress distributions. The quasi-static experiments in polymethyl methacrylate (PMMA) compared refraction angles and stress gradients calculated from schlieren images to the analytical Flamant solution of a line load on a half-space. The quantitative schlieren measurements of the stress field in the thin sample with a load compared well to the analytical solution. The analysis method was then extended to explosive induced shock waves in PMMA. The explosive induced response of PMMA was experimentally studied using high-speed schlieren to visualize the shock propagation in conjunction with Photon Doppler Velocimetry (PDV) to record surface velocity histories. The stress state estimated from the schlieren images was compared to the stress calculated from the PDV measurements. High-speed imaging limitations caused the shock wave to not be fully resolved in the images, but was resolved in the PDV measurement. The stress state behind the shock calculated from the high-speed images followed a similar trend to the stress calculated from the PDV measurements.

Self-similar flow behind a shock wave in a gas under the effect of viscosity, heat conduction, and variable ambient density

Self-similar solutions have been investigated to describe the propagation of planar shock waves in a non-ideal gas generated by a piston under viscous stress and heat flux. The equation of state for non-ideal gas incorporates the correction in pressure and volume of the gas. The piston position and ambient density vary exponentially with time. Newton’s law of viscosity is used for the viscous stress and Fourier’s law of heat conduction is taken for heat flux. The viscosity coefficient is taken as constant whereas the thermal conductivity coefficient varies with temperature and density following the power law. The shock jump conditions have been derived for the viscous non-ideal gas using integral form of conservation laws. The shock Reynolds number Re s has been introduced to study the effect of viscosity on shock propagation in non-ideal gas. It is found that similarity solution exists only in an ideal gas under the condition that the ambient density exponent is equal to twice the shock position exponent. This study shows that shock Reynolds number Re s and heat conduction parameter Γ c can be used to control the variation of the flow variables and piston position significantly. The shock strength decreases with increase in the value of shock Reynolds number Re s but is independent of the heat conduction parameter Γ c . The pressure, density, and adiabatic compressibility have significant deviations from high to low viscous flow of ideal gas but the velocity and heat flux undergo negligible change. The results do not support the claim of negligible effect of viscosity in earlier studies and establish the impact of viscosity and heat flux on shock propagation in an ideal gas.

Characterization of Supernovae Interacting with Dense Circumstellar Matter with a Flat Density Profile

Interaction between supernova (SN) ejecta and dense circumstellar medium (CSM) with a flat density structure (ρ ∝ r −s , s < 1.5) was recently proposed as a possible mechanism behind interacting SNe that exhibit exceptionally long rise times exceeding 100 days. In such a configuration, the interaction luminosity keeps rising until the reverse shock propagates into the inner layers of the SN ejecta. We investigate the light curves of SNe interacting with a flatly distributed CSM in detail, incorporating the effects of photon diffusion inside the CSM into the model. We show that three physical processes—the shock breakout, the propagation of the reverse shock into the inner ejecta, and the departure of the shock from the dense CSM—predominantly determine the qualitative behavior of the light curves. Based on the presence and precedence of these processes, the light curves of SNe interacting with flatly distributed CSM can be classified into five distinct morphological classes. We also show that our model can qualitatively reproduce doubly peaked SNe whose peaks are a few tens of days apart, such as SN 2005bf and SN 2022xxf. Our results show that the density distribution of the CSM is an important property of CSM that contributes to the diversity in light curves of interacting SNe.

Comprehensive analysis of normal shock wave propagation in turbulent non-ideal gas flows with analytical and neural network methods

Shock wave propagation in gases through turbulent flow has wide-reaching implications for both theoretical research and practical applications, including aerospace engineering, propulsion systems, and industrial gas processes. The study of normal shock propagation in turbulent flow over non-ideal gas investigates the changes in pressure, density, and flow velocity across the shock wave. The Mach number is derived for the system and explored across various gas molecule quantities and turbulence intensities. This study analytically investigated the normal shock wave propagation in turbulent flow of adiabatic gases with modified Rankine–Hugoniot conditions. Artificial neural network (ANN) techniques are used to estimate the solutions for shock strength and Mach number training validation phases of back-propagated neural networks with the Levenberg–Marquardt algorithm. The results reveal that pressure ratio with density ratio increase for higher values of increase in the turbulence level as well as intermolecular forces. A reverse trend is observed in velocity coefficient after shock in the presence of adiabatic gas. The regression coefficient values obtained using the network model ranged from 0.999 99 to 1, indicating an almost perfect correlation. These findings demonstrate that the ANN can predict the Mach number with high accuracy.