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Abstract To study the influence of pits on shock wave propagation and the propagation of shock waves within pits, numerical simulations were used to calculate the distribution of overpressure peak values at the bottom and rear of the pits at 5 depths and 5 explosion center distances. The results indicate that diffraction occurs when the explosion shock wave passes through the edge of the crater; The peak overpressure of the shock wave at the bottom of the pit exhibits a "spoon shaped" distribution, and the peak overpressure on the right side is significantly higher than that on the left side; There are two distinct boundary regions for the overpressure of the shock wave behind the crater due to the influence of the crater; The distance between the explosion centers has little effect on the distribution trend of the overpressure peak of the shock wave at the bottom and rear of the pit, mainly affecting the magnitude of the overpressure peak. The research results provide theoretical support for the analysis of the propagation law of explosion shock waves and guidance for the design of protective engineering structures, with significant engineering application value.

In actual combat, the attack of the warhead on the target is a dynamic process, and there is a significant difference in shock wave pressure between dynamic and static explosions of ammunition, while dynamic explosions are more in line with actual combat situations. Therefore, conducting research on the distribution law of dynamic explosion shock wave pressure in ammunition has more practical value for evaluating the damage power of ammunition and guiding its use. This study used the display explosion dynamics simulation software AUTODYN to conduct simulation analysis on the pressure distribution patterns of static and dynamic explosion shock waves, clarifying the differences in pressure distribution between dynamic and static explosions. Considering the factors that affect the distribution law of dynamic explosion shock wave pressure, a BP neural network based correlation prediction model for static and dynamic explosion shock wave pressure was constructed, and the prediction accuracy of the model was verified. The analysis results indicate that the pressure distribution of dynamic explosion shock waves has a significant velocity tendency; The prediction accuracy of the static and dynamic shock wave pressure correlation prediction model based on BP neural network is better than 90.7%. The research results have improved the accuracy of the calculation of dynamic explosion shock wave pressure in warheads, providing effective calculation methods and scientific data support for the calculation of dynamic explosion shock wave pressure and the evaluation of damage power. [ABSTRACT FROM AUTHOR]

The surface reflection pressure sensor installation flatness will directly lead to the change of the explosion shock wave pressure propagation and distribution law, affecting the test results accuracy, and the test data cannot accurately evaluate the ammunition explosion damage power. In this study, the numerical simulation model of the explosion shock wave pressure propagation and distribution law was established by using the explosive mechanics simulation software, and the pressure distribution law was studied when the sensors installation angles were 0°, 4°, 8°, 12°, −4°, −8°, and −12° respectively. Combined with analysis of the pressure peak value and the pressure evolution nephogram at different measuring points, it is clarified that the positive tilt angle of the sensor installation has an enhancing effect on the pressure peak, while the negative tilt angle has a attenuation effect on the pressure peak. Based on the calculation function formula of the surface reflected pressure peak value in the national defense engineering design code, the surface reflected pressure peak value correction function formula is established by introducing the sensor installation angle correction effect. This study results provide a theoretical basis for the design of ammunition explosion shock wave pressure engineering test scheme and the test data validity verification. [ABSTRACT FROM AUTHOR]

The impact of supercooled water droplets is the cause of aircraft icing, and the acquisition of impingement characteristics is the key to icing prediction and the design of ice protection systems. The introduction of water droplet collection efficiency is required to obtain the characteristics for the Lagrangian method. In this work, a traditional flow tube method, a local flow tube method, and a statistical method are established to calculate the local collection efficiency, based on Lagrangian droplet trajectories. Through the numerical simulations of the air–droplet flow field around an NACA 0012 airfoil, the accuracies of the three methods in regard to collection efficiency are verified. Then, these three methods are applied to obtain the results for water droplet trajectories and the collection efficiency of an S-shaped duct, a 2D engine cone section and an icing wind tunnel. The results show that the distributions of water droplet collection efficiency obtained by the three methods are consistent and the three methods are all feasible when the water droplets do not overlap or cross before hitting the aircraft surfaces. When the water droplets are shadowed by upstream surfaces or blown by air injection, the droplet trajectories might overlap or even cross, and the local collection efficiencies obtained by the traditional flow tube method, local flow tube method, and statistical method might differ. The statistical method is relatively accurate. However, not all the droplet impingement characteristics obtained by the three methods are different due to these effects, and the non-crossing of the droplet trajectories is not a necessary condition for the use of the flow tube method. The effects of trajectory crossings are analyzed and discussed in detail in different situations for the three methods. This work is helpful for understanding and accurately calculating the droplet impingement characteristics and is of great significance for simulations of the aircraft icing process and anti/de-icing range. [ABSTRACT FROM AUTHOR]

We study a periodic‐review multi‐supplier series inventory system in which the demand is restricted to partial sum uncertainty sets. We present and solve a robust rolling‐horizon model for the system. We propose an induction framework to characterize the closed‐form robust optimal solution of the problem. We show that the robust optimal policy combines the echelon base‐stock policy and a gap‐of‐echelon‐base‐stock policy for the uppermost stage and a modified echelon base‐stock policy for the other downstream stages. The policy structure is easy for the manager to understand and implement in practice. The policy parameters are directly determined by a sequence of nominal partial‐sum demands, and its computation is very effective. In addition, the policy does not rely on complete information about the demand distribution; its solution can be more robust than that of stochastic optimization methods, especially when demand is highly uncertain, and forecasting is difficult. Based on the structure of the robust optimal policy, we design two heuristic policies for the system and evaluate the policies' performance through an extensive numerical study using both synthetic and real data. [ABSTRACT FROM AUTHOR]