Explosive Behavior Research Articles

Theoretical and experimental studies on thermostatic explosion behavior of typical melting and casting explosive 2,4-dinitroanisole (DNAN)

With the advantages of 2,4-dinitroanisole based melt-cast explosives (DNAN-based MCEs), such as low sensitivity, low shrinkage rate, and environmental friendliness, their use as a replacement for trinitrotoluene (TNT) for fabrication of melt-cast explosives has received considerable attention. Therefore, it is significant to explore the thermal safety performance of DNAN-based MCEs (DNAN/HMX/Al 30/40/30) to provide references for their production, storage, and transportation. A combination of DSC and ARC was employed to investigate the thermostatic explosion behavior of DNAN/HMX/Al MCEs in this study. As a result, it was shown that two calorimetry methods could produce different thermodynamic explosion behavior parameters, contributing to the differences in the mass and heat transfer properties. Then a calibration model considering the mass, shape, and heat convection was developed for thermostatic explosion behavior prediction, which can explain the predicted deviations reasonably. At last, the new method has been verified by slow cooking-off experiments that the SADT calculated by the kinetic parameters of the ARC test is more in line with the actual situation of DNAN-based MCE.

Predicting Crude Oil Future Price Using Traditional and Artificial Intelligence-Based Model: Comparative Analysis

Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.

Command filter-based adaptive fuzzy switching event-triggered control for non-affine nonlinear systems with actuator faults

This paper considers a problem of command filter-based adaptive fuzzy switching event-triggered control for non-affine nonlinear systems with actuator faults. First, a state observer is given to estimate unmeasurable state. Secondly, an error transformation equation is designed to constrain output tracking error, and the feasibility condition of tracking error is not required. Then, a finite time fault-tolerant control scheme is constructed based on command filter and backstepping technologies, which can compensate completely the effects of actuator faults and trigger errors, and there is no differential explosion, singularity phenomenon and Zeno behavior. Besides, a switching event-triggered algorithm is designed to reduce the triggering number under the premise of ensuring the tracking performance. Finally, the proposed algorithm is applied to an one-link manipulator to verify the availability.

Explosion and vented explosion behaviors of low-concentration gas in large-scale pipes

The extraction, transmission, and use of low-concentration gas in coal mines are often challenged by potential accidents due to proximity to the combustion and explosion concentration limit. Water sealing of fire barriers and explosion venting devices guarantee the safe transmission of low-concentration gas. The propagation and venting of gas explosion under different concentrations are experimentally investigated in a DN500 mm pipe explosion propagation test system. The water sealing of fire barrier vented explosion field evolution of methane-air mixture at the stoichiometric concentration (9.5 vol%) is examined through Fluent numerical simulation to reveal the water sealing of fire barrier further vented explosion pattern of gas transmission pipelines under low concentrations. The explosion overpressure and flame propagation of low-concentration gas in pipes are observed and correlated. Based on their coupling relationship, the design basis for the installation location of the explosion venting device is derived. The vented explosion characteristics of low-concentration gas during pipe transmission are summarized, proving that this explosion venting technique enhances both the explosion venting device and explosion parameters. Our observations and analysis can offer useful clues to underground gas explosion and prevention in coal mines.

The influence of melt composition, liquidus temperature and solidus temperature on vapour explosions in melt droplet impingement experiments

For the investigation of vapour explosions, droplet impingement experiments were performed with the binary system Pb–Sn and the pseudo-binary system PbS–Cu2S. The experiments were performed with a melt at 600 °C (Pb–Sn) or 700 °C (PbS–Cu2S) and a water bath at ambient temperature and pressure. A hydrophone and a high-speed camera were used to study the interaction and from this data, the explosion probability and intensity were determined.The explosion probability had a single minimum around 70 wt% Sn, close to the eutectic composition. Moreover, the explosion probability increased approximately linearly with changing composition towards the pure melts, and was similar for pure tin and pure lead. On the other hand, the explosion intensity was comparable for tin and the eutectic alloy while clearly lower for lead. Almost all intermediate alloys had a reduced explosion intensity.Based on the variation in composition, the effects of the liquidus or solidus temperature and the liquidus-solidus gap on the explosion behaviour were also investigated. The explosion probability in both systems increased with increasing liquidus temperature. Also, the maximum explosion intensity in the Pb–Sn system increased with increasing liquidus temperature. Both could be related to easier triggering due to (partial) solidification. On the other hand, the explosion intensity was found to decrease with increasing gap between liquidus and solidus temperature, as was also found in literature. No significant trends for the explosion intensity were found for experiments with PbS–Cu2S.

Effect of N2 and CO2 on explosion behavior of hydrogen-air mixtures in non-premixed state

In this paper, the suppression effects of non-premixed inert gas (N2, CO2) on hydrogen-air explosion behaviors are experimentally studied. The effects of N2 and CO2 addition on flame propagation, explosion pressure and flame length are analyzed. The results show that N2 and CO2 can effectively reduce the explosion hazard in non-premixed state. The mixing process of non-premixed gases leads to the development of turbulent flame, but the suppression of inert gas on explosion exceeds the promotion of turbulent flame. Under the action of N2 and CO2, the energy of the flame decreases, and the front contour becomes blurred. When the fuel zone is only set at the ignition end, with the suppression of N2 and CO2, the maximum explosion pressure is reduced by 35.1% and 50.6%, respectively. It is worth noting that the high-frequency periodic oscillation and pressure soaring appear in the pressure histories, which are attributed to the rapid phase transition of water. Furthermore, the two inert gases can significantly reduce the chemical reaction rate and heat release rate during the explosion, which is reflected in the decrease of the maximum flame length. It is found that N2 and CO2 have different explosion suppression effects and mechanisms, but CO2 has better suppression performance on hydrogen-air explosion.

Do Bubbles in the Bitcoin Market Impact Stock Markets? Evidence From 10 Major Stock Markets

In this paper, we examine the effect of explosive behaviors in the Bitcoin market on the top 10 largest stock markets of developed and emerging countries. The daily dataset, including the Dow Jones Industrial Index (DJIA), Nasdaq (NSQ), Shanghai Composite Index (SSE), Nikkei 225 (N225), Hang Seng Index (HSI), Shenzhen Composite Index (SZSE), Euronext Amsterdam Index (AEX), London Stock Exchange (LSE), Toronto Stock Exchange (TSX), and Bombay Stock Exchange (BSE), spans July 21, 2010, to December 9, 2022. We first investigate the existence of explosive price behaviors using the bubble detection test of Phillips and Shi and the results provide evidence of multiple bubble episodes, coinciding with the monetary policy actions of the FED and ECB. Then, we address the question of whether the explosive behaviors detected affect the variance of equity returns by employing a GARCH model. The impact is negative, albeit its magnitude and significance vary among stock indices.

Investigation on the explosion dynamics of large-format lithium-ion pouch cells

Explosion is the most extreme case of thermal runaway of lithium-ion (Li-ion) batteries. In this study, explosion dynamics of large-format Li-ion cells are investigated experimentally and numerically. Overcharge-to-explosion tests are conducted on 40 Ah Li-ion cells with Li[Ni0.8Co0.1Mn0.1]O2 cathode. Based on the explosion physics, shockwave and detonation models are used to characterize the shock effect of the cell explosion and evaluate the explosion equivalent. Von Neumann peak is observed on the pressure curves, and the shockwave velocity is supersonic at this time; the unwrinkled spherical flame phenomenon observed in the experiment indicates that it is detonation. Additionally, a geometric model is established based on the real testing scenario, and the explosion behavior is numerically studied. The characteristics of the explosion dynamics process are interpreted and the propagation mechanism of the shockwave are revealed; the deflagration to detonation transition (DDT) phenomenon in this process is caused by the formation of “hot spots”, and the explosion of the cells eventually turns into stable combustion. This study fills the gap in the research on thermal runaway of Li-ion cells, especially in the extreme cases of fire and explosion, and provide useful guidance for battery safety.

Identifying Common and Idiosyncratic Explosive Behaviors in the Large Dimensional Factor Model with an Application to U.S. State-Level House Prices

Abstract This study applies the date-stamping methodologies for explosive behaviors proposed in the seminal work of Phillips, P. C. B., and J. Yu. (2011. “Dating the Timeline of Financial Bubbles during the Subprime Crisis.” Quantitative Economics 2 (3): 455–91), Phillips, P. C. B., S. Shi, and J. Yu. (2015a. “Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500.” International Economic Review 56 (4): 1043–78), and Phillips, P. C. B., S. Shi, and J. Yu. (2015b. “Testing for Multiple Bubbles: Limit Theory of Real Time Detectors.” International Economic Review 56 (4): 1079–134) to a large dimensional factor model. To this end, we compare two methods of identifying common and idiosyncratic components: the Panel Analysis of Nonstationarity in Idiosyncratic and Common Components (PANIC) method by Bai, J., and S. Ng. (2004. “A Panic Attack on Unit Roots and Cointegration.” Econometrica 72 (4): 1127–77) and the Cross-Sectional regression (CS) method by Yamamoto, Y., and T. Horie. (2022. “A Cross-Sectional Method for Right-Tailed PANIC Tests under a Moderately Local to Unity Framework.” Econometric Theory (forthcoming)). We show that, when the explosive behavior lies only in the common component, the origination and termination dates are precisely estimated by either method. However, when the explosive behaviors exist in idiosyncratic components, only the CS method can detect them. We apply our method to the U.S. state-level real house price indices. We find that the 2000s boom was driven by not only the national bubble factors but also local components, while the 2010s onward expansion is dominated by the effect of national components.

Effect of silica fume content in concrete blocks on laser-induced explosive spalling behavior

This experimental study investigated the effect of silica fume mixed in concrete blocks on laser-induced explosion behavior. We used a 5.3 kW fiber laser as a thermal source to induce explosive spalling on a concrete surface blended with and without silica fume. An analytical approach based on the difference in the removal rate and thermal behavior was used to determine the effect of silica fume on laser-induced explosive spalling. A scanner was employed to calculate the laser-scabbled volume of the concrete surface to derive the removal rate. The removal rate of the concrete mixed with silica fume was higher than that of without silica fume. Thermal images acquired during scabbling were used to qualitatively analyze the thermal response of laser-induced explosive spalling on the concrete surface. At the early stage of laser heating, an uneven spatial distribution of surface temperature appeared on the concrete blended with silica fume because of frequent explosive spalling within a small area. By contrast, the spalling frequency was relatively lower in laser-heated concrete without silica fume. Furthermore, we observed that a larger area was removed via a single explosive spalling event owing to its high porosity.

Bitcoin Forecasting Performance Measurement: A Comparative Study of Econometric, Machine Learning and Artificial Intelligence-Based Models

Bitcoin is a type of Cryptocurrency that relies on Blockchain technology and its growing popularity is leading to its acceptance as an alternative investment. However, the future value of Bitcoin is difficult to predict due to its significant volatility and speculative behavior. Considering this, the key objective of this research is to assess Bitcoins’ explosive behavior during 2013–2022 including the most volatile COVID-19 pandemic and Russia–Ukraine war period and to forecast its price by comparing the predictive abilities offive different econometric, machine learning and artificial Intelligence methods namely, ARIMA, Decision Tree, Random Forest, SVM, and Artificial Intelligence Long Short-Term Memory Network (AI-LSTM). The precision of such methodologies has been assessed using root mean square error (RMSE) and mean average per cent error (MAPE) values. The findings confirmed that the AI-LSTM model performs better than other forecast models in predicting Bitcoins’ opening price on the following working day. Therefore, Bitcoin traders, policymakers, and financial institutions can use the model effectively to better forecast the next day’s opening price.

The illusion of the metaverse and meta-economy

This paper provides (i) a review of the existing literature on the metaverse and (ii) an empirical assessment of the current state of the Web3 meta-economy, with the focus on economic governance and metaverse commerce. We have analysed the entire Web3 metaverse niche, i.e. both the 196 available metaverse fungible tokens and all the non-fungible token (NFT) transactions belonging to the metaverse marketplace. Our results showed that economic governance is based on metaverse tokens that cannot be defined as reliable virtual currencies due to their explosive behaviour, negative performance, and higher volatility compared to traditional alternatives. Paradoxically, fiat currencies and stablecoins could be more appropriate candidates for the payment infrastructure. Moreover, we also observed that NFT prices are affected by the cryptocurrency market, which highlights the risk of metaverse commerce. For future research, developers and scholars must assess the different alternatives and infrastructures that can make the metaverse a persistent reality with a proper virtual economy. However, at present, it seems that the hype has run far ahead of reality.

Testing for parameter change epochs in GARCH time series

Summary We develop a uniform test for detecting and dating the integrated or mildly explosive behaviour of a strictly stationary generalized autoregressive conditional heteroskedasticity (GARCH) process. Namely, we test the null hypothesis of a globally stable GARCH process with constant parameters against the alternative that there is an ‘abnormal’ period with changed parameter values. During this period, the parameter-value change may lead to an integrated or mildly explosive behaviour of the volatility process. It is assumed that both the magnitude and the timing of the breaks are unknown. We develop a double-supreme test for the existence of breaks, and then provide an algorithm to identify the periods of changes. Our theoretical results hold under mild moment assumptions on the innovations of the GARCH process. Technically, the existing properties for the quasi-maximum likelihood estimation in the GARCH model need to be reinvestigated to hold uniformly over all possible periods of change. The key results involve a uniform weak Bahadur representation for the estimated parameters, which leads to weak convergence of the test statistic to the supreme of a Gaussian process. Simulations in the Appendix show that the test has good size and power for reasonably long time series. We apply the test to the conventional early-warning indicators of both the financial market and a representative of the emerging Fintech market, i.e., the Bitcoin returns.

Detecting Episodes of Mildly Explosive Behavior in the Hurricane Resiliency Index to Examine Community Resilience to Hurricanes

Natural disasters such as hurricanes, earthquakes, and floods cause massive damage and losses around the world. Investigating their impact on affected communities and delineating them from nondisaster forces have major scientific and policy implications. To that end, a series of econometric tests were applied to the Hurricane Resiliency Index (HRI) for six selected study areas to identify and date-stamp periods of mildly explosive behavior (MEB). Evidence of MEB signals a structural break or nonlinearity in an otherwise stationary time series. The starting and ending points of multiple MEB episodes indicate the extent to which a community recovers toward normalcy. It is found that the recovery time associated with hurricanes is much shorter than that with economic recessions. The overall severity of MBE, when considering both duration and amplitude, is most pronounced when a major hurricane strikes dense populations. The findings also highlight that the compounding effect of economic recession and hurricane poses the most serious threat to a local economy. Finally, the Hurricane Resiliency Index is shown to outperform the Federal Reserve Bank of Dallas’s Metro Business-Cycle Index in capturing such behaviors.

Suppression characteristics of multi-layer metal wire mesh on premixed methane-air flame propagation

Metal wire mesh is widely used in the energy industry for its excellent protective properties as a fire stopping and explosion isolating material. In this study, the suppression characteristics of different layers of metal mesh on the dynamic behavior of premixed methane-air flame propagation were studied experimentally. A high-speed photographic schlieren system was used to photograph the explosion process to capture the changes in the microstructure of the flame, and high-frequency pressure sensors and micro-thermocouple measurements were used to capture the flame explosion pressure and temperature. The experimental results show that the suppression effectiveness of wire mesh is a reflection of the coupling of explosive flame propagation behavior and combustion state in the pipe. Increasing the number of mesh layers and mesh density can destroy the microstructure of the premixed methane-air flame front and hinder the progress of flame propagation. Increasing the number of wire mesh layers will delay the peak time of premixed flame propagation speed and reduce the peak speed values of flame propagation. Wire mesh has a pronounced attenuation effect on premixed flame temperature and explosion overpressure. The maximum flame temperature attenuation rate is 34.99%–60.95%, and the maximum explosion overpressure attenuation rate is 33.70%–74.02%. And the suppression effect is greatly enhanced as the increase of mesh layers.

Hogan-Weintraub Singularity and Explosive Behaviour in the Black-Derman-Toy Model

Hogan-Weintraub Singularity and Explosive Behaviour in the Black-Derman-Toy Model

Research on deflagration behavior of gas and gas-coal dust in a vertical pressure relief pipe-line system

Gas explosion and gas-coal dust explosion are serious disasters in coal mine production. To further study the hazards of gas explosion and gas and coal dust explosion under different conditions, experiments were done in this paper in a pipe-line system containing an explosion pipe-line and pressure relief pipe-line. Flame propagation behavior and overpressure dynamics of gas explosion and gas coal dust explosion were analyzed. Flame propagation behavior of gas explosion and gas-coal dust explosion are divided into three-stages: spherical flame, round-finger flame, and pointed-finger flame. Flame front position increases with time showing a class exponential growth trend. Flame front velocity has been increasing in the explosion pipe-line. When the flame rushes out of the PVC membrane and enters the pressure relief pipe-line, flame front velocity decreases slightly. The flame front velocity increases rapidly in the pressure relief pipe-line. With growing gas concentration, the peak overpressure in the explosion pipe-line rises at first, then decrease, and the peak overpressure in the pressure relief pipe-line keeps rising. Peak overpressures are obtained at gas concentrations of 9 vol.% and 13 vol.%, respectively. When gas concentrations are 7 vol.% and 9 vol.% in the reaction, the peak overpressures in the pressure relief pipe-line during gas explosion and gas-coal dust explosion are all lower than those in the explosion pipe-line. When gas concentrations are 11 vol.% and 13 vol.% in the reaction, the peak overpressures in the pressure relief pipe-line during the two types of explosions are higher than those in the explosion pipe-line.

Experimental Study of the Suppression Effect of N2/CO2 On the LPG Explosion Behavior in a Half-Open Duct with Large Aspect Ratios

ABSTRACT This work aims to investigate the effect of N2/CO2 on the explosion behavior of premixed liquefied petroleum gas (LPG)-air in a half-open duct. Experiments were performed in a duct (L/D = 47.5) with the ignition end closed and the other end open. Firstly, the optimal explosion concentration of LPG was determined using the stepwise approximation method, secondly, the effects of different volume fractions (VFs) of N2/CO2 on the pressure dynamic process, flame propagation velocity, and explosion severity of LPG-air explosion were analyzed, and finally the inerting effects of N2 and CO2 were compared using the control variable method. The results show that the explosion pressure and flame propagation velocity reach a maximum when the VF of LPG is 4.8% (without inert gas), and two pressure peaks (the first pressure peak (P 1 ) and the second pressure peak (P 2 )) are observed. When the VF of LPG is 4.8%, the maximum pressure and the average flame propagation velocity in the tube decrease and the explosion intensity inside and outside the duct was effectively mitigated as the VF of N2/CO2 increases, and the explosion is completely suppressed as the VF of inert gas reached 30%. P 2 is significantly suppressed, and the maximum explosion pressure (P max ) occurs at when the VF of N2/CO2 is above 15%. The suppression effects of CO2 are more remarkable at a lower VF (below 18%), those of N2 are more significant at a higher VF (above 18%), and P 1 also follows this rule. For a given volume fraction of inert gas, the suppression effect of N2/CO2 on the degree of explosion severity becomes more significant when approaching the optimal LPG explosion concentration (4.8%).

A viscoelastic–viscoplastic constitutive model for polymer bonded explosives under low impact loading

Viscoplastic work is very important to explosive ignition under impact loading. At present, a large number of constitutive models only consider the viscoelastic and damage behavior of explosives, ignoring the plastic effect under low impact loading. A new viscoelastic–viscoplastic (VE–VP) model was developed and studied to describe the dynamic mechanical behaviors of polymer-bonded explosives (PBXs). The total strain was assumed to be the sum of the viscoelastic (VE) and viscoplastic (VP) components. A generalized Maxwell model was used to determine the VE responses. A VP model was developed by using the classical J2 rate-dependent model with isotropic hardening. Viscoplastic flow was considered in hyperbolic sinusoidal form. The explicit algorithms of VE model were proposed and assessed by using two different integration methods. The accuracy and efficiency of these two methods are similar at high strain rates. The coupled algorithms of VE–VP model were developed by referring to the classical elasto-viscoplasticity (EVP) provided and using the expression of incremental relaxation modulus. The proposed model was implemented in the ABAQUS using a user-subroutine (VUMAT) to predict the response behaviors of PBX 9501 under low impact loading. Several numerical simulations illustrated the computational efficiency and the accuracy of the proposed methods. The model predictions were compared with experimental data, and reasonable agreement was obtained.

Reaction of African stocks markets to disequilibrium episodes of the COVID-19 infection: Evidence from the top hit African countries

The continued COVID-19 pandemic has had a significant impact on the global economy, with countries battling to contain the infection’s spread as it continues to affect nearly every country in the globe. We test for possible explosive behavior (excessive disequilibrium) in COVID-19 infection in the top African impacted economies, given the sensitivity and fragility of stock markets to shocks. The study identifies two (2) separate explosive occurrences in Algeria and Egypt using the Generalized Sup Augmented DickeyFuller (GSADF) test. Furthermore, the study examines the influence of the COVID-19 infection’s explosive behavior on the stock markets of the countries, taking into consideration the disequilibrium occurrences. The COVID-19 infection’s explosive behavior had a negative but insignificant effect on stock returns, leading to an increase in riskiness. This outcome could be explained by the fact that the explosive incidents were transitory and could only have had a momentary impact on stock market returns absorbable overtime. More so, it suggests that investors may have adjusted to the shock of the COVID-19 infection prior to the two explosive occurrences, and that the development of the COVID-19 vaccine reassures for a near halt to the pandemic.