Prediction of flow stress of 7017 aluminium alloy under high strain rate compression at elevated temperatures

An artificial neural network(ANN) constitutive model and JohnsoneC ook(Je C) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar(SHPB) experiments at various temperatures. A neural network configuration consists of both training and validation, which is effectively employed to predict flow stress. Temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on Johnsone Cook(Je C) model and neural network model was performed. It was observed that the developed neural network model could predict flow stress under various strain rates and temperatures. The experimental stressestrain data obtained from high strain rate compression tests using SHPB over a range of temperatures(25 e300 C), strains(0.05e0.3) and strain rates(1500e4500 s 1) were employed to formulate JeC model to predict the flow stress behaviour of 7017 aluminium alloy under high strain rate loading. The JeC model and the back-propagation ANN model were developed to predict the flow stress of 7017 aluminium alloy under high strain rates, and their predictability was evaluated in terms of correlation coefficient(R) and average absolute relative error(AARE). R and AARE for the J-C model are found to be 0.8461 and 10.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. The predictions of ANN model are observed to be in consistent with the experimental data for all strain rates and temperatures.     

Determination of penetration depth at high velocity impact using finite element method and artificial neural network tools

Determination of ballistic performance of an armor solution is a complicated task and evolved significantly with the application of finite element methods(FEM) in this research field.The traditional armor design studies performed with FEM requires sophisticated procedures and intensive computational effort,therefore simpler and accurate numerical approaches are always worthwhile to decrease armor development time.This study aims to apply a hybrid method using FEM simulation and artificial neural network(ANN) analysis to approximate ballistic limit thickness for armor steels.To achieve this objective,a predictive model based on the artificial neural networks is developed to determine ballistic resistance of high hardness armor steels against 7.62 mm armor piercing ammunition.In this methodology,the FEM simulations are used to create training cases for Multilayer Perceptron(MLP) three layer networks.In order to validate FE simulation methodology,ballistic shot tests on 20 mm thickness target were performed according to standard Stanag 4569.Afterwards,the successfully trained ANN(s) is used to predict the ballistic limit thickness of 500 HB high hardness steel armor.Results show that even with limited number of data,FEM-ANN approach can be used to predict ballistic penetration depth with adequate accuracy.     

Phenomenological modelling of flow behaviour of 20MnMoNi55 reactor pressure vessel steel at cryogenic temperature with different strain rates

In the present study a phenomenological constitutive model is developed to describe the flow behaviour of 20MnMoNi55 low carbon reactor pressure vessel (RPV) steel at sub-zero temperature under different strain rates. A set of uniaxial tensile tests is done with the variation of strain rates and temperature ranging from 10⁻⁴ s⁻¹ to 10⁻¹ s⁻¹ and -80 °C to −140 °C respectively. From the experimental data, family of flow curves at different temperatures and strain rates are generated and fitted exponentially. The strain rate and temperature dependence of the coefficients of the exponential flow curves are extracted from these curves and characterised through a general phenomenological constitutive coupled equation. The coefficients of this coupled equation are optimised using genetic algorithm. Finite element simulation of tensile tests at different strain rates and temperatures are done using this coupled equation in material model of Abaqus FEA software and validated with experimental results. The novelties of proposed model are: (a) it can predict precisely the flow behaviour of tensile tests (b) it is a simple form of equation where fitting parameters are both function of strain rate ratio and temperature ratio, (c) it has ability to characterize flow behaviour with decreasing subzero temperatures and increasing strain rates.     

Effect of bending temperatures on the microstructure and springback of a TRIP steel sheet

Transformation-induced plasticity (TRIP) steel possesses high strength and formability, enabling the use of a thinner gauge material and allowing for the fabrication of complex shapes. In this research, we measured the effect of bending temperatures on the microstructure and air-bending springback angle of TRIP steel at temperatures from 25 to 600 °C. Real-time in situ X-ray diffraction and scanning electron microscopy were used for pre- and postbending analysis. As the prebending temperature increased from 25 °C to 600 °C, the retained austenite (RA) volume fraction decreased, and the RA transformed to bainite at temperatures above 400 °C. The springback angle was positively correlated with the prebending RA volume fraction, with the smallest springback angle achieved at 400 °C. Additionally, the springback angle was positively correlated with the bending angle, because the RA transformation ratio contributed to increased strain hardening. Further microstructure analysis revealed that the RA became elongated in the tension direction as the bending temperatures increased.     

Tuning the reactivity of Al–Ni by fine coating of halogen-containing energetic composites

In this paper, various core-shell structured Al–Ni@ECs composites have been prepared by a spray-drying technique. The involved ECs refer to the energetic composites (ECs) of ammonium perchlorate/nitrocellulose (AP/NC, NA) and polyvinylidene fluoride/hexanitrohexaazaisowurtzitane (PVDF/CL-20, PC). Two Al–Ni mixtures were prepared at atomic ratios of 1:1 and 1:3 and named as Al/Ni and Al/3Ni, respectively. The thermal reactivity and combustion behaviors of Al–Ni@ECs composites have been comprehensively investigated. Results showed that the reactivity and combustion performance of Al–Ni could be enhanced by introducing both NA and PC energetic composites. Among which the Al/Ni@NA composite exhibited higher reactivity and improved combustion performance. The measured flame propagation rate (v = 20.6 mm/s), average combustion wave temperature (T_max = 1567.0 °C) and maximum temperature rise rate (γ_t = 1633.6 °C/s) of Al/Ni@NA are higher than that of the Al/Ni (v = 15.8 mm/s, T_max = 858.0 °C, and γ_t = 143.5 °C/s). The enhancement in combustion properties could be due to presence of the acidic gaseous products from ECs, which could etch the Al₂O₃ shell on the surface of Al particles, and make the inner active Al to be easier transported, so that an intimate and faster intermetallic reaction between Al and Ni would be realized. Furthermore, the morphologies and chemical compositions of the condensed combustion products (CCPs) of Al–Ni@ECs composites were found to be different depending on the types of ECs. The compositions of CCPs are dominated with the Al–Ni intermetallics, combining with a trace amount of Al₅O₆N and Al₂O₃.     

Low velocity impact studies of E-glass/epoxy composite laminates at different thicknesses and temperatures

Low velocity impact experiments were carried out on E-glass/epoxy composite laminates having varying thicknesses at sub zero and elevated temperatures using hemi spherical steel impactor of 16 mm diameter with impact energies in the rage of 50–150 J. The performance of the laminates was assessed in terms of energy absorption, maximum displacement, peak force and failure behaviour. Results indicated that the effect of temperature on energy absorption of the laminate is negligible although the laminates are embrittling at sub zero temperatures. However it has influence on failure behaviour and displacement. Peak force has increased linearly with increase in laminate thickness from 5 to 10 mm. However it got reduced by 25% when temperature was increased from −20 °C to 100 °C. Based on experimental results, laminate perforation energies were predicted using curve fitting equations. Statistical analysis was carried out using Taguchi method to identify the global effects of various parameters on laminate performance and confirmed that the laminate thickness has significant influence as compared to temperature, for the studied range.     

Development of multi-physics numerical simulation model to investigate thermo-mechanical fatigue crack propagation in an autofrettaged gun barrel

In this research, a detailed multi-physics study has been carried out by numerically simulating a solid fractured gun barrel for 20 thermo-mechanical cycles. The numerical model is based on thermal effects, mechanical stress fields and fatigue crack mechanics. Elastic-plastic material data of modified AISI 4340 at temperatures ranging from 25 to 1200 °C and at strain rates of 4, 16, 32 and 48 s⁻¹ was acquired from high-temperature compression tests. This was used as material property data in the simulation model. The boundary conditions applied are kept similar to the working gun barrel during continuous firing. A methodology has been provided to define thermo-mechanically active surface-to-surface type interface between the crack faces for a better approximation of stresses at the crack tip. Comparison of results from non-autofrettaged and autofrettaged simulation models provide useful information about the evolution of strains and stresses in the barrel at different points under combined thermo-mechanical loading cycles in both cases. The effect of thermal fatigue under already induced compressive yield due to autofrettage and the progressive degradation of the accumulated stresses due to thermo-mechanical cyclic loads on the internal surface of the gun barrel (mimicking the continuous firing scenario) has been analyzed. Comparison between energy release rate at tips of varying crack lengths due to cyclic thermo-mechanical loading in the non-autofrettaged and autofrettaged gun has been carried out.     

Kevlar fabric reinforced polybenzoxazine composites filled with silane treated microcrystalline cellulose in the interlayers: The next generation of multi-layered armor panels

The design of astonishing combinations of benzoxazine resins with various fillers is nowadays of great interest for high quality products, especially in ballistic armors. The objective of this study is to investigate a new hybrid material prepared as multi-layered composite plate by hand lay-up technique. Different composites were manufactured from Kevlar fabrics reinforced polybenzoxazine, which was filled with silane treated microcrystalline cellulose (MCC Si) at various amounts in the interlayers. The developed materials were tested for their flexural, dynamic mechanical and ballistic performance. The aim was to highlight the effect of adding different amounts of MCC Si on the behavior of the different plates. Compared to the baseline, the dynamic mechanical and bending tests revealed an obvious decrease of the glass transition of 21 °C and a notable increase in storage modulus and flexural strength of about 180 %and17%, respectively, upon adding 1% MMC Si as filler. Similarly, the ballistic test exhibited an enhancement in kinetic energy absorption for which the composite supplemented with 1% MCC Si had the maximal energy absorption of 166.60 J. These results indicated that the developed panels, with interesting mechanical and ballistic features, are suitable to be employed as raw materials to produce body armor.     

Data-driven prediction of plate velocities and plate deformation of explosive reactive armor

Explosive reactive armor (ERA) is currently being actively developed as a protective system for mobile devices against ballistic threats such as kinetic energy penetrators and shaped-charge jets. Considering mobility, the aim is to design a protection system with a minimal amount of required mass. The efficiency of an ERA is sensitive to the impact position and the timing of the detonation. Therefore, different designs have to be tested for several impact scenarios to identify the best design. Since analytical models are not predicting the behavior of the ERA accurately enough and experiments, as well as numerical simulations, are too time-consuming, a data-driven model to estimate the displacements and deformation of plates of an ERA system is proposed here. The ground truth for the artificial neural network (ANN) is numerical simulation results that are validated with experiments. The ANN approximates the plate positions for different materials, plate sizes, and detonation point positions with sufficient accuracy in real-time. In a future investigation, the results from the model can be used to estimate the interaction of the ERA with a given threat. Then, a measure for the effectiveness of an ERA can be calculated. Finally, an optimal ERA can be designed and analyzed for any possible impact scenario in negligible time.     

An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R² = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R² = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R² = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.     

基于独立分量分析和神经网络的钢结构损伤识别方法

为了有效剔除钢结构振动信号中的噪声,提取用于损伤识别的特征量,采用独立分量分析方法分离统计独立信号,同时得到表征结构损伤状态的混合矩阵,然后将混合矩阵作为特征量输入至神经网络进行训练,最后将训练好的神经网络作为分类器进行结构损伤识别.在冲击载荷作用下,针对钢框架结构模型进行了不同损伤部位的振动实验,结果表明:基于独立分量分析和神经网络的损伤识别方法具有较高的识别率和可重复性,而且实现简单,在结构损伤识别领域具有较大的应用潜力.     

Numerical investigation of the failure mechanism of cubic concrete specimens in SHPB tests

Cylindrical specimens are commonly used in Split Hopkinson pressure bar (SHPB) tests to study the uniaxial dynamic properties of concrete-like materials.In recent years,true tri-axial SHPB equipment has also been developed or is under development to investigate the material dynamic properties under tri-axial impact loads.For such tests,cubic specimens are needed.It is well understood that static material strength obtained from cylinder and cube specimens are different.Conversion factors are obtained and adopted in some guidelines to convert the material strength obtained from the two types of specimens.Previous uniaxial impact tests have also demonstrated that the failure mode and the strain rate effect of cubic specimens are very different from that of cylindrical ones.However,the mechanical background of these findings is unclear.As an extension of the previous laboratory study,this study performs numerical SHPB tests of cubic and cylindrical concrete specimens subjected to uniaxial impact load with the validated numerical model.The stress states of cubic specimens in relation to its failure mode under different strain rates is analyzed and compared with cylindrical specimens.The detailed analyses of the numerical simulation results show that the lateral inertial confinement of the cylindrical specimen is higher than that of the cubic specimen under the same strain rates.For cubic specimen,the corners are more severely damaged because of the lower lateral confinement and the occurrence of the tensile radial stress which is not observed in cylindrical specimens.These results explain why the dynamic material strengths obtained from the two types of specimens are different and are strain rate dependent.Based on the simulation results,an empirical formula of conversion factor as a function of strain rate is proposed,which supplements the traditional conversion factor for quasi-static material strength.It can be used for transforming the dynamic compressive strength from cylinders to cubes obtained from impact tests at different strain rates.     

The non-isothermal gravimetric method for study the thermal decomposition kinetic of HNBB and HNS explosives

The hexanitrostilben (HNS) is a thermally stable explosive that can be prepared from hexanitrobibenzyl (HNBB). Therefore, the investigation of thermal stability of HNBB can be important in the yield of preparation of HNS. The decomposition kinetic of HNBB and HNS are studied by non-isothermal gravimetric method. The TG/DTG curves in non-isothermal method are obtained in range of 25°C–400 °C at heating rates of 3 °C/min, 5 °C/min, 8 °C/min, 10 °C/min and 12 °C/min. The data of weight-temperature are used for calculation of activation energy (E_a) of thermal decomposition reactions by methods of Ozawa, Kissinger, Ozawa-Flynn-Wall (OFW) and Kissinger-Akahira-Sunose (KAS) as model-free methods and Strink's equation as model-fitting method. The compensation effect is used for prediction of mechanism and determination of pre-exponential factor (lnA) of the decomposition reaction. A reduction 60 kj/mol for the average of activation energy of thermal decomposition reaction of HNBB is obtained versus HNS. This result shows the lower thermal stability of HNBB in comparison to HNS. The Avrami equation (A_3/2) with function f(α) = 3/2(1-α)[-ln(1-α)]^1/3 indicates the predicted mechanism for thermal decomposition reaction both explosives.     

Experimental investigation of a cook-off temperature in a hot barrel

The experimental investigations of the effect of contact time/temperature on initiating the cook-off using 7.62 mm calibre cartridge cases (CC) were conducted previously. These cartridges were filled with commercial off-the-shelf (COTS) double based (DB) propellant (Bulls Eye) and were loaded in a hot chamber. The thermal explosion temperature is of great significance to both weapon designers and safety inspectors as it provides the operational limit and safe operating temperature. For CC under test, it was found that the cook-off temperatures of this propellant were encountered with the heat transfer profile of the simulated gun barrel between 151.4 °C and 153.4 °C, with a reaction occurring in less than 300 s after the round was chambered. Usefully, each experiment was found to be consistent and repeatable.     

The properties of Sn–Zn–Al–La fusible alloy for mitigation devices of solid propellant rocket motors

The Al and La elements are added to the Sn9Zn alloy to obtain the fusible alloy for the mitigation devices of solid propellant rocket motors. Differential scanning calorimetry (DSC), metallographic analysis, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), tensile testing and fracture analysis were used to study the effect of Al and La elements on the microstructure, melting characteristics, and mechanical properties of the Sn9Zn alloy. Whether the fusible diaphragm can effectively relieve pressure was investigated by the hydrostatic pressure at high-temperature test. Experimental results show that the melting point of the Sn9Zn-0.8Al0·2La and Sn9Zn–3Al0·2La fusible alloys can meet the predetermined working temperature of ventilation. The mechanical properties of those are more than 35% higher than that of the Sn9Zn alloy at −50 °C–70 °C, and the mechanical strength is reduced by 80% at 175 °C. It is proven by the hydrostatic pressure at high-temperature test that the fusible diaphragm can relieve pressure effectively and can be used for the design of the mitigation devices of solid propellant rocket motors.     

Research on the influences of confining pressure and strain rate on NEPE propellant: Experimental assessment and constitutive model

In order to study the influences of confining pressure and strain rate on the mechanical properties of the Nitrate Ester Plasticized Polyether (NEPE) propellant, uniaxial tensile tests were conducted using the self-made confining pressure system and material testing machine. The stress-strain responses of the NEPE propellant under different confining pressure conditions and strain rates were obtained and analyzed. The results show that confining pressure and strain rate have a remarkably influence on the mechanical responses of the NEPE propellant. As confining pressure increases (from 0 to 5.4 MPa), the maximum tensile stress and ultimate strain increase gradually. With the coupled effects of confining pressure and strain rate, the value of the maximum tensile stress and ultimate strain at 5.4 MPa and 0.0667 s⁻¹ is 2.03 times and 2.19 times of their values under 0 MPa and 0.00333 s⁻¹, respectively. Afterwards, the influence mechanism of confining pressure on the NEPE propellant was analyzed. Finally, based on the viscoelastic theory and continuous damage theory, a nonlinear constitutive model considering confining pressure and strain rate was developed. The damage was considered to be rate-dependent and pressure-dependent. The constitutive model was validated by comparing experimental data with predictions of the constitutive model. The whole maximum stress errors of the model predictions are lower than 4% and the corresponding strain errors are lower than 7%. The results show that confining pressure can suppress the damage initiation and evolution of the NEPE propellant and the nonlinear constitutive model can describe the mechanical responses of the NEPE propellant under various confining pressure conditions and strain rates. This research can lay a theoretical foundation for analyzing the structural integrity of propellant grain accurately under working pressure loading.     

一座小型建筑空调动态负荷的ANN预测研究

人工神经网络(Artificial Neural Network,简称ANN)是一种崭新非线性建模和预测方法,具有良好的非线性品质和极高的拟合精度。在前人研究的基础上,针对一座小型建筑物建立了其空调动态负荷预测的BP模型。为克服常规BP训练算法的缺陷,提出了一种改进的遗传搜索算法,结果证明是一种高效实用的算法。     

Effect of transverse compression on the residual tensile strength of ultrahigh molecular weight polyethylene (Dyneema® SK-76) yarns

Ballistic impact induces complex stress states on fiber-based armor systems. During impact fibers undergo multiaxial loading which includes axial tension, axial compression, transverse compression, and transverse shear. Transverse compression induced by the projectile leads to permanent deformation and fibrillation of fibers resulting in degradation of material tensile strength. Previous work (Sockalingam et al. Textile Res. J 2018) has shown a reduction of 20% in the tensile strength of Dyneema® SK76 single fibers subjected to 77% nominal transverse compressive strains. Experimental investigation of quasi-static transverse compression on Dyneema® SK-76 yarns, unconstrained in the lateral direction, indicate an average of 4% reduction in tensile strength of yarns compressed to 77% nominal strains. In this work we use finite element modeling techniques to understand the difference in residual tensile strength between single fibers and yarns observed in laterally unconstrained transverse compression experiments. Finite element study of the transverse compression response of single fibers and yarns indicate that local strains developed in fibers within the yarn are much lower than the local strains developed in single fibers subjected to a given nominal strain and may explain the less reduction in strength observed in yarns.     

Scale-up synthesis and characterization of 2,6-diamino-3,5-dinitropyrazine-1-oxide

2,6-diamino-3,5-dinitropyrazine-1-oxide (ANPZO), as an insensitive high explosive, with a high yield and excellent purity has been prepared at pilot plant scale by an improved method. The synthesized ANPZO is characterized by IR, laser granularity measurement, SEM and HPLC. The particle analysis revealed that the improved method could offer desired product with average particle size of 40 μm and high purity (>98.45%). The experimental parameters exhibited that the detonation velocity of the formulation based on ANPZO was higher than that of the corresponding TATB formulation. The DSC curve showed that the exothermic decomposition of the product occurred at the temperature between 300.5 °C and 360.4 °C. Furthermore, the sensitivity test suggests its safe nature towards mechanical stimulus.     

3D laser scanning strategy based on cascaded deep neural network

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s. The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.