Dynamic Behavior Of Materials Research Articles

A Method for Dynamic Kolsky Bar Compression at High Temperatures: Application to Ti-6Al-4V

Abstract An experimental apparatus for measuring the dynamic behavior of materials subjected to strain rates on the order of 10 $$^3$$ 3 s $$^{-1}$$ - 1 and temperatures up to 800°C with a unique triple actuation system is developed in this work. This system is based on the traditional Kolsky (or split-Hopkinson pressure) bar design, with the addition of an external furnace used to heat the specimen to the desired temperature. A synchronized triple pneumatic actuation system is used to control the motion and timing of the the sample, incident, and transmitted bars. The cold contact time (CCT), or the time during which the heated sample is in contact with the room temperature bars before compression, is measured experimentally and carefully controlled to minimize the development of a temperature gradient across the sample and avoid heating of the bars. Experiments are performed in conjunction with ultra high speed imaging and 2D digital image correlation (DIC), as well as high speed thermal imaging. To verify the viability of the proposed system, experiments were conducted on Ti-6Al-4V (wt.%) at temperatures from 25°C up to and 800°C at an average strain rate of approximately 1200 s $$^{-1}$$ - 1 .

Experimental investigation under laser-driven shocks of the dynamic behavior of materials for beam-intercepting devices in particle accelerators

Experimental investigation under laser-driven shocks of the dynamic behavior of materials for beam-intercepting devices in particle accelerators

Three-dimensional mesoscopic investigation on the dynamic compressive behavior of coral sand concrete with reinforced granite coarse aggregate (GCA)

In the construction of island and reef engineering, coral concrete shows a good application prospect due to its abundant raw materials. However, the porous and fragile mechanical characteristics of coral reefs limit their use as coarse aggregate in the preparation of coral concrete materials. This study utilized hard and dense granite as the coarse aggregate and regarded coral sand concrete as a two-phase composite material consisting of spherical granite coarse aggregate (GCA) and coral mortar. It investigated the enhancement effect of granite on coral concrete from a microscopic perspective. Five 3D mesoscopic models with different GCA contents and randomly distributed aggregates were established to reveal the variation patterns and failure mechanisms of coral sand concrete under impact loading with GCA. The findings demonstrate that the K&C model can effectively simulate the dynamic compression behavior of coral mortar and granite materials. Under the action of a half-sine incident wave, the dynamic compressive strength of the samples increases with the increase in GCA, demonstrating that the addition of GCA can effectively enhance the impact resistance of coral sand concrete. As the content of GCA increases, the sensitivity of the samples to the loading wave amplitude also increases accordingly.

Dynamic Behavior and Energy Absorption of Typical Porous Materials under Impacts.

Porous materials are known for their excellent energy absorption capability and, thus, are widely used in anti-impact applications. However, how the pore shape and size impact the failure mechanism and overall behavior of the porous materials under impact loading is still unclear or limitedly touched. Instead of using homogeneous solids for the porous material model, pores with various shapes and sizes were implanted in a solid to establish the porous materials that have true porous structures, which permits exploration of the local failure mechanism. The results revealed that differently shaped holes have two different dominant deformation modes. And due to their different local stress distributions, they enter the plastic phase earlier and, thus, have higher specific energy absorption. Meanwhile, the model changes from hardening to a quasi-zero stiffness model as the hole size increases. The application of this work can be extended into the field of impact resistance.

Interfacial dynamics mediate surface binding events on supramolecular nanostructures

The dynamic behavior of biological materials is central to their functionality, suggesting that interfacial dynamics could also mediate the activity of chemical events at the surfaces of synthetic materials. Here, we investigate the influence of surface flexibility and hydration on heavy metal remediation by nanostructures self-assembled from small molecules that are decorated with surface-bound chelators in water. We find that incorporating short oligo(ethylene glycol) spacers between the surface and interior domain of self-assembled nanostructures can drastically increase the conformational mobility of surface-bound lead-chelating moieties and promote interaction with surrounding water. In turn, we find the binding affinities of chelators tethered to the most flexible surfaces are more than ten times greater than the least flexible surfaces. Accordingly, nanostructures composed of amphiphiles that give rise to the most dynamic surfaces are capable of remediating thousands of liters of 50 ppb Pb2+-contaminated water with single grams of material. These findings establish interfacial dynamics as a critical design parameter for functional self-assembled nanostructures.

Experimental and Numerical Study on the Blast Resistant Performance of Geopolymer Concrete

Geopolymer, with its notable benefit of low carbon dioxide emissions, holds the potential to substantially curtail environmental pollution. According to the existing related research on geopolymer materials, it is obvious that it has great development potential in many engineering application fields, and it is a new generation of green and environmentally friendly recycled materials. Nowadays, there is a growing concern regarding explosion protection. Explosions near buildings can cause catastrophic damages on the building external and internal structure, and the most important thing is that can cause injuries and loss of life to the occupants of these buildings. This study investigates the mechanical performance of the fiber-reinforced geopolymer concrete under explosive testing. Furthermore, the finite element analysis models have been established through LS-DYNA software to simulate the explosive testing using Structure-Arbitrary Lagrangian Eulerian Method (S-ALE). The model is used to assess the dynamic mechanical behavior of geopolymer materials.

Simulating the near-field dynamic plume behavior of disposed fine sediments

Projections of the effects of fine sediment disposals, relevant for managed estuaries and tidally influenced coastal areas, are typically based on numerical far-field models. For an accurate consideration of the disposal itself, near-field models are often needed. The open source near-field model, PROVER-M, simulates the relevant processes of the physics based, dynamic behavior of disposed fine sediments in coastal waters and is applied in this study. First, new small scale laboratory experiments of instantaneous disposals are presented, documenting the dynamic behavior of fine material disposed in shallow waters. Second, results of the PROVER-M model are shown for disposals in three different settings: (1) a field-scaled study complementary to the laboratory set-up, (2) a parametric study of sequentially varied model input and (3) a far-field model coupling for estimation of the PROVER-M impact. By comparing results of the laboratory experiments to the PROVER-M model, the physical behavior of PROVER-M is successfully validated. The impact of the ambient setting and dredged material parameters is evaluated by the PROVER-M simulations, where the results show non-linear, complex interdependencies of the input parameters on disposal properties in dependence of ambient site conditions and material composition. In this context, limits of the model application are assessed and critically discussed. Finally, an exemplary coupling to a far-field model based on a real set of disposals in the tidally influenced Weser estuary (Germany) illustrates the potential impact of PROVER-M for assessing far-field suspended sediment concentration (SSC), with increased maximum SSC values of up to 10%.

Radial Inertia Effect of Ultra-Soft Materials from Hopkinson Bar and Solution Methodologies.

The split-Hopkinson pressure bar technique is widely used to determine the dynamic mechanical behavior of materials. However, spike-like stress features appear in the initial stress behavior of ultra-soft materials tested with a split-Hopkinson bar. These features are not intrinsic characteristics of the materials. Potential causes were investigated through experiments and numerical simulations. It was found that the spike feature represents derived stress resulting from the radial inertia effect during dynamic loading. In this work, we propose and experimentally verify effective methods to reduce this effect. The influences of density, strain acceleration, ratio between inner and outer diameter, and Poisson's ratio on the radial inertia effect were investigated. The spike stress was found to change linearly with density and strain acceleration but decrease significantly when the inner/outer diameter ratio was below 0.3, after which it remained nearly constant. A parabolic stress distribution was observed along the radial direction due to the Poisson effect, especially when the ratio exceeded 0.3, leading to higher spike stress. Finally, suggestions were proposed as experimental guidance when testing ultra-soft materials.

Recursive and batch Bayesian estimation of exponential non-viscous damping systems

Non-viscous damping systems include a convolutional integral and a kernel function in their equation of motion to incorporate time-hysteresis damping effects, which are present in dynamical behavior of most engineering materials yet are absent in commonly used viscous damping models. When an exponential kernel function is adopted by the non-viscous model, the unique damping characteristic is realized by an additional model parameter known as the relaxation parameter. The objective of this paper is to investigate various aspects of estimation problems on exponential non-viscous damping systems through recursive and batch Bayesian time-domain frameworks, with a focus on how the relaxation parameter introduces additional complexity in estimation problems compared to viscous damping systems. Two well-established algorithms are employed: the unscented Kalman filter (UKF) for recursive Bayesian estimation and the transitional Markov Chain Monte Carlo (TMCMC) for batch Bayesian estimation. We first analyze the complexity of estimation problems in SDOF viscous and non-viscous damping systems. The TMCMC algorithm offers a quantitative analysis that reveals greater uncertainty and stronger parameter correlation in non-viscous damping systems compared to viscous damping systems. Subsequently, the same SDOF systems are utilized to study recursive Bayesian estimation via UKF such as the effects of measurement data type, discretization, and initial conditions. Based on the results of the TMCMC algorithm, we study the dependence of UKF performance on the initial condition for various SDOF non-viscous damping systems with different levels of non-viscosity. In the end, a laboratory experiment compares the estimation results between viscous and non-viscous damping systems using both TMCMC and UKF.

Construction of self-supported TiO2 nanotube arrays with hybrid point defect engineering: A bifunctional anode for Li+/Na+ storage

Point defect engineering has garnered widespread application for enhancing the dynamic behavior of anode materials and improving electrochemical performance. Herein, a hybrid point defect strategy is proposed in Ti-based oxide materials to achieve N doping induced oxygen vacancies (OVs) and subsequently accelerated electron mobility and perform better diffusion kinetics. This methodology culminates in the fabrication of self-supported nanotube arrays comprising N-doped OVs-rich TiO2 (denoted as N-TNTs). Density functional theory (DFT) calculations and electrochemical characterizations validate that, hybrid point defects lead to high electron mobility and perform better diffusion kinetics, as well as higher Li+/Na+ ions adsorption energy barrier and diffusion energy barrier, which in turn improves the rate performance and cycling stability. This research provides a forward-looking and feasible strategy for the application of point defect engineering in anode materials.

Neural networks for emergent behavior in biological microstructures

PurposeThis paper develops a neural network surrogate model based on a discrete lattice approach to investigate the influence of complex microstructures on the emergent behavior of biological networks.Design/methodology/approachThe adaptability of network-forming organisms, such as, slime molds, relies on fluid-to-solid state transitions and dynamic behaviors at the level of the discrete microstructure, which continuum modeling methods struggle to capture effectively. To address this challenge, we present an optimized approach that combines lattice spring modeling with machine learning to capture dynamic behavior and develop nonlinear constitutive relationships.FindingsThis integrated approach allows us to predict the dynamic response of biological materials with heterogeneous microstructures, overcoming the limitations of conventional trial-and-error lattice design. The study investigates the microstructural behavior of biological materials using a neural network-based surrogate model. The results indicate that our surrogate model is effective in capturing the behavior of discrete lattice microstructures in biological materials.Research limitations/implicationsThe combination of numerical simulations and machine learning endows simulations of the slime mold Physarum polycephalum with a more accurate description of its emergent behavior and offers a pathway for the development of more effective lattice structures across a wide range of applications.Originality/valueThe novelty of this research lies in integrating lattice spring modeling and machine learning to explore the dynamic behavior of biological materials. This combined approach surpasses conventional methods, providing a more holistic and accurate representation of emergent behaviors in organisms.

Multi-scale pore model construction and damage behavior analysis of SiCf/SiC composite tubes

SiCf/SiC composite materials are essential for spacecraft thermal protection, determining the safety of spacecraft. However, their complex structures and intricate fabrication processes have led to an unclear understanding of their failure mechanisms, limiting their application. In this study, circumferential compression experiments were conducted, and X-ray computed tomography (X-CT) was used to analyze the distribution characteristics of pore spaces. The experimental results indicate that damage manifests as secondary fracture phenomena based on temporal evolution characteristics. Specifically, after experiencing performance degradation of 24.73–60.96%, the material still maintained basic stability, exhibiting a performance recovery of 31.55–36.1% under the applied load until failure. To predict the dynamic damage behavior of materials at multiple scales, a multi-scale method combining statistical and microscopic approaches was proposed. A micro representative volume element (RVE) random fiber pore distribution model was established based on random processes and random medium theory. Finally, considering the CT data and the principle of minimum potential energy, a macroscopic finite element model of the micro-pores' structural characteristics in a three-dimensional wound tube was reconstructed. The results indicate that cracks initiate around pore defects and gradually propagate to form crack bands. The model closely matches the macroscopic damage and microscopic characteristics of the material. This work provides a new approach for the numerical simulation of pore defects in such materials.

Mesoscale modeling of dynamic compressive behavior of microcapsule-based self-healing concrete under impact loading

Microcapsule-based self-healing concrete (MSC) has been widely studied, with a focus on static behavior and self-healing effectiveness. However, the dynamic mechanical properties of MSC have rarely been studied. This study presents a mesoscale numerical investigation of the dynamic compressive behavior of MSC under impact loading. In mesoscale, MSC is regarded as a four-phase composite material mainly composed of coarse aggregates, interface transition zones, cement mortar, and microcapsules. A pseudo 3D numerical model is constructed by combining a slice of a detailed mesoscale model with a homogenous 3D model. The mesoscale MSC slice models with different mass fractions of microcapsules (0%, 2%, 5%, and 8%) are constructed. Different coarse aggregate shapes (i.e., circles, ellipses, and polygons) are considered. The uniaxial dynamic compressive behaviors of MSC materials under loads of different strain rates are numerically simulated and compared with those from split Hopkinson pressure bar tests previously done by the authors. The comparison results show that the present mesoscale model can accurately predict the compressive strength and failure mode of MSC. The effects of the microcapsules ratio and strain rate on the dynamic strength are studied. Results show that the MSC compressive strength decreases with the increase in microcapsules and increases with the increase in strain rate. The dynamic increase factor (DIF) of the specimen is jointly contributed by the material DIF, inertial constraints, and heterogeneity. Different aggregate shapes have little effect on the simulation results of MSC behavior. The obtained dynamic mechanical properties of MSC may assist in designing MSC to resist collisions or explosions.

A coupled FD-SPH method for shock-structure interaction and dynamic fracture propagation modeling

Shock wave propagation and their damage to solid structures, which involve complex multiphase and multiphysics phenomena, are difficult problems to address. In this paper, a three-dimensional graphics processing unit (GPU)-accelerated finite difference-smoothed particle hydrodynamics (FD-SPH) method was developed for the prediction of strongly compressible fluid flow and strong fluid-structure interactions. The conventional mesh-based finite difference method was used to simulate shock wave propagation, while the smoothed particle hydrodynamics method was employed to predict the dynamic behavior of solid materials. In addition, the immersed boundary method (IBM) was implemented in the GPU-accelerated FD-SPH solver for the boundary treatment of the interface between solid and fluid materials. Four numerical cases, namely shock-cylinder obstacle interaction, elastic panel deformation induced by shock wave propagation, the response of stainless steel tubes under internal blast loading, and the damage of blast loading on reinforced concrete slab, were conducted for verification of the GPU-accelerated FD-SPH solver. The numerical results were compared against the available experimental data, which shows that the GPU-accelerated FD-SPH solver is capable of capturing the shock wave propagation and its damage to structures very well.

Experimental and numerical studies of the effects of micro/nano carbon fibers in the dynamic behavior of cement-based grouting materials for reinforcement of sand layers

Geological hazards of sand layers pose a serious threat to engineering safety. Grouting reinforcement technology is widely used in such conditions due to its convenience, economy, and effectiveness. To explore the reinforcement effect of carbon fiber (CF) modified cement-based grouting materials on sand layers, grouting solidified bodies (GSB) with CF contents of 0.0%, 0.5%, 1.0%, and 1.5% are selected for Split Hopkinson Pressure Bar (SHPB) impact tests, scanning electron microscope (SEM) scanning, and numerical simulation experiments. The mechanical properties of specimens under dynamic impact conditions and the reinforcement mechanism of CF are studied. Results show that GSB is a strain-rate-dependent material. With the increase of impact rate, peak stress, incident energy, transmitted energy, and dissipated energy of specimens gradually increase, while the integrity of specimens decreases. The CF content remarkably affects the mechanical properties of specimens. When the impact rate is constant, with the increase of CF content, the peak stress and transmitted energy of specimens show a decreasing–increasing– decreasing trend, and the performance of CF-1.0% specimens is optimal. The cement matrix is the main energy storage and release medium, accounting for 97.66% of the energy. When damaged, the cement matrix is mainly fractured. At the microcrack tip, CF influences the direction of crack propagation, reducing the radius of crack propagation, and the main failure mode of CF is debonding. CF can substantially improve the mechanical properties of specimens and reduce the number of cracks. Compared with CF-0.0%-cementitious material (CM) specimens, the peak stress of CF-1.0%-CM specimens is increased by 19.98%. The magnitude of CF force is related to the angle between crack and CF. As the angle increases from 0° to 90°, the CF force gradually increases, reaching the maximum at 90°, with an increase of 133.82%. At this angle, the anti-cracking effect of CF is most substantial. The research results can provide technical support for sand layer grouting reinforcement technology.

Dynamic splitting behavior of microcapsule-based self-healing cementitious composites under SHPB impact loading

This study presents an experimental study on the dynamic splitting tensile performance of microcapsule-based self-healing cementitious composites and fiber-reinforced microcapsule cementitious composites. The research aims to determine the effect of microcapsule dosages, fiber types, and strain rates on the dynamic splitting tensile behavior of materials. A total of 99 specimens were subjected to the split Hopkinson pressure bar (SHPB) impact loading within the strain rates of 0.85–17.12 s−1. A high-speed camera was employed to capture the crack propagation process, and scanning electron microscopy (SEM) was used to characterize the corresponding microstructure. The results indicated that the splitting tensile performance of materials exhibits significant strain rate sensitivity. The addition of microcapsules increases the dynamic splitting tensile strength of the material, and the highest energy absorption capacity can be achieved with a 5 % microcapsule dosage. The incorporation of polyvinyl alcohol (PVA) and polyethylene (PE) fibers effectively enhances dynamic splitting tensile strength and energy absorption capacity, achieving optimal performance with the incorporation of PVA-PE hybrid fibers. Furthermore, the investigation of the dynamic increase factor (DIF) of the material indicates that fibers heighten the strain rate sensitivity of the material.

Special Issue “Dynamic Behavior of Brittle Materials”

Special Issue “Dynamic Behavior of Brittle Materials”

Influence of Interface Type on Dynamic Deformation Behavior of 3D-Printed Heterogeneous Titanium Alloy Materials.

Using the Split Hopkinson Pressure Bar technique, strain-limited dynamic compressive loading experiments were performed on TA1/TA15 heterostructure (HS) materials. The plastic deformation mechanisms, fracture forms, and energy absorption properties of an HS material with a metallurgical bonding interface (MB) and an HS material without a metallurgical bonding interface (NMB) are compared and analyzed. The results show that there is no significant difference between the two deformation mechanisms. The fracture forms are all "V-shaped" fractures within the TA1 part. The NMB was carried for 57 μs before failure and absorbed 441 J/cm3 of energy. The MB was carried for 72 μs before failure and absorbed 495 J/cm3 of energy. Microstructure observations show that there is a coordinated deformation effect near the MB interface compared to the NMB, with both TA1 and TA15 near the interface carrying stresses. This causes an enhancement of the MB load-bearing time and a 12% increase in energy absorption.

Effect of Cooling Rate on Dynamic Magnetic Hysteresis Loop Behaviors of Magnetic Materials by Using as a Model Mixed Spin (1, 3/2) Ising System Under an Oscillating Magnetic Field

Effect of Cooling Rate on Dynamic Magnetic Hysteresis Loop Behaviors of Magnetic Materials by Using as a Model Mixed Spin (1, 3/2) Ising System Under an Oscillating Magnetic Field

Dynamic behaviors of nickel coated carbon nanotubes reinforced ultra-high performance cementitious composites under high strain rate impact loading

Understanding the dynamic mechanical behaviors of materials is a prerequisite for reliably analyzing and predicting the dynamic response of structures, which is of great significance for transportation infrastructure and military engineering subjected to extreme loads, particularly dynamic loads at high strain rates. Nickel coated multi-walled carbon nanotubes (Ni-MWCNTs) show promise as a reinforcement to modify the dynamic mechanical behaviors of ultra-high performance cementitious composites (UHPCC). Because Ni-MWCNTs combine the high tensile strength and large aspect ratio characteristics of fibers with the nano effect of nanomaterials, as well as have excellent dispersibility due to the nickel plating on the CNTs’ surface, they effectively improve the dynamic mechanical properties of UHPCC under impact loading at high strain rates of about 100 s−1/300 s−1/500 s−1 and reduce the brittle damage degree of composites. The maximal increase in dynamic compressive strength and energy absorption capacity of UHPCC reaches 47.9% and 68.2%, respectively. This enhancement effect arises from that Ni-MWCNTs improve the microstructure and form multiple fine cracks, resulting in an increased energy consumption required for crack formation, propagation and coalescence. Additionally, the dynamic mechanical properties of Ni-MWCNTs reinforced UHPCC exhibit noticeable strain rate effects. Consequently, a strain rate-dependent logarithmic functional dynamic increase factor model and dynamic constitutive model of UHPCC filled with Ni-MWCNTs are modified herein for predicting and modeling the dynamic mechanical behaviors of composites.