International Journal of Protective Structures

This paper is focused on the study of innovative bi-stable supports to improve the impact performance of point-fixed glass panels, for typical use in facades. To mitigate the effects of impact and reduce potential risk for people, the introduction of innovative, bi-stable, mitigation devices between the fixing system and the primary building structure is addressed. The proposed dissipative system is able to control and minimise the input force which is transmitted to the primary building, controlling the damage around the supports and preventing the detachment of the glass panels. Based on LS-Dyna Finite-Element (FE) models, the proposed protection system is designed to have a snap-through behaviour under impact. The performance of the system is quantified for two different glazing systems, which are numerically investigated under various impact configurations.

In the near field, the air blast peak overpressure from cylindrical charges may vary by several times with angles at the same scaled distance. We propose an estimation equation for the peak overpressure from cylindrical charges, which can predict the peak overpressure from cylindrical charges at any positions in the near field. The estimation equation is in the form of piecewise function which contains three variables of length-to-diameter ratio, angle and scaled distance, and the applicability of our estimation equation is verified by experiment and simulation. After preliminary verification, the application range of length-to-diameter ratio of cylindrical charge is 1 / 4 ∼ 10 and that of scaled distance is 0.4 ∼ 2   m / k g 1 / 3 . The estimation equation can be rapidly applied to the assessment of near-field target damage and protection against air blast from cylindrical charges, which is a significant supplement to the traditional empirical equations for spherical charge.

Machine learning (ML) methods are becoming more prominent in blast engineering applications, with their adaptability to new scenarios and rapid computation times providing key benefits when compared to empirical methods and physics-based approaches, respectively. However, ML approaches commonly used for blast analyses are regularly provided with inputs relating to domain-specific parameters, restricting their use beyond the initial problem set and reducing their generality. This article presents the ‘Direction-encoded Neural Network’ (DeNN); a novel way to structure an Artificial Neural Network (ANN) to predict blast loading in obstructed environments. Each point of interest (POI) is represented by the proximity to its surroundings and the shortest travel path of the blast wave in order to prime the network to learn the underlying physics of the problem. Furthermore, a bespoke wave reflection equation creates a zone of influence around each point so that obstacles are only captured in the network’s inputs if they would alter the path of the wave. It is shown that the DeNN can predict peak overpressures with mean absolute errors ∼5 kPa for unseen, complex domains of any shape or size, when compared to the results from physics-based numerical models with ∼30 times the solution time of the DeNN. The network is used to develop maps of likely human injury following detonation of a high explosive in an internal environment, with eardrum rupture levels being correctly predicted for over 93% of unseen test points. It is therefore highly suited for use in probabilistic, risk-based analyses which are currently impractical due to excessive computational cost.

Shock absorbers have been widely used in the automotive and aeronautical industries for many years. Inspired on these devices, the paper presents an analytical and numerical assessment of a high performance protective system for building structures against blast loads, which is composed of a shielding element connected to the main structure, at the floor levels, through ductile Energy Absorbing Connectors (EACs). The EACs exploit the external tube inversion mechanism to absorb a significant part of the imparted kinetic energy from the blast wave. While the system prototype has been developed in laboratory, it was characterized and tested in a full-scale blast testing campaign. A validated finite element model was used next to analyze its performance in a more demanding design scenario. The introduction of EACs notably reduces the peak horizontal loads and the kinetic energy transferred to the protected structure, being expected a significant reduction of the stresses in the supporting vertical elements, in addition to the protection of structural and non-structural members. These results encourage further studies of the presented protective system that can be potentially employed for a large variety of blast threat scenarios, especially when increasing the stand-off is not a possible/viable option and sensitive facilities have to be protected.

Mathematical analysis of blast pressures has typically involved the empirical fitting of parametric models, which assumes a specific function shape. In reality, the true shape of the blast pressure is unknown and may lack a parametric form, particularly in the negative phase following arrival of the secondary shock. In this work, we develop a non-parametric (NP) representation that makes few assumptions and relies on the observed experimental data to fit a unique and previously unknown model. This differs from traditional approaches by not arbitrarily selecting a single, restrictive class of functions and estimating a minimal set of parameters, but rather estimating the underlying function class for which the blast pressure is generated; learning the model directly from the observed data. The method was applied to experimental blast measurements and the NP estimates matched the experimental data with a high degree of accuracy, both qualitatively and quantitatively. The NP approach was shown to significantly outperform other commonly used approaches, near-perfectly track the entire pressure and specific impulse history and predicting experimental peak specific impulse to within ±0.5% in all cases (compared to ±5.0% for a trained artificial neural network (ANN) and ±7.5% for the UFC semi-empirical approach). The NP approach predicts experimental net specific impulses (positive and negative phases combined) with a maximum variation of 2.7%, compared to maximum variations of −116% and 55% for the UFC and ANN approaches, respectively. Since the framework is probabilistic in nature, it can naturally account for random noise in sensor measurements, which are typically more pronounced in blast experiments than many other machine learning applications.

In this research, the ballistic performance of ceramic-polyurea-aluminum composite targets under the impact of flat-nose projectile was investigated for different thicknesses. The relevant experiments were designed based on the thickness of the layers and the effect of their configuration was explored. Experimental tests were carried out using two types of gas gun devices with different calibers. Residual velocity of the projectile was extracted using ls-dyna software for all targets and compared with the experimental data and after validation, the ballistic limit velocity was extracted. Taguchi method was used to design experiments and optimization and ballistic limit velocity, surface density, and strength-to-weight ratio were considered as objective functions. Moreover, the residual velocity of the projectile, damage mechanism of layers, the diameter of the hole at the back layer, central displacement of the back layer, absorbed energy, and changes in the projectile velocity were also investigated. Based on the numerical results, ceramic had the greatest effect on reducing the velocity of the projectile (approximately between 55 and 65%). Strength-to-weight ratio and armor weight were considered as two objective functions in the optimization. The effect of each of the armor materials on the target functions was investigated. According to the results, ceramic had the greatest effect on increasing the strength-to-weight ratio (about 83.88%), and polyurea had the least effect (about 14.09%) on increasing the total weight of the armor.

An experimental and numerical study has been performed to explore the performance of one-way pretensioned concrete plates against impact loading. The impact resistance, experimental results and damage within the pretensioned concrete have been compared with the non-pretensioned concrete. The plate specimens of concrete grades M40 and M60 have been pretensioned to prestress level 10 and 20% of the compressive strength of the concrete. While, all the tendons employed in the non-pretensioned concrete were kept unstressed. The plates were struck at the mid-span by a steel mass (242.85 kg) dropped from 0.5 to 1.0 m heights. The numerical simulations have been executed using explicit finite element code considering the Holmquist–Johnson–Cook (HJC) and the metal plasticity model for concrete and steel, correspondingly. The performance of the plates is governed by the grade of concrete, impact energy and level of the prestress within the concrete. The induced prestress within the concrete enhanced the stiffness and, consequently, the impact resistance of the pretensioned concrete plates. The pretensioned concrete hence witnessed increased impact force and reduced deflection by 18.1% and 11.0%, correspondingly, compared to the non-pretensioned concrete. The splitting and punching crack within the plates became pronounced once the drop height increased from 0.5 m to 1.0 m. The simulations have estimated the peak impact force and reaction within 19.7% and 15.5% deviation, respectively. The displacement and energy absorption have been calculated using an analytical methodology closely correlated with the actual results within 18% and 14% deviation, respectively. Further, the simulations performed on two-way pretensioned concrete have shown improved performance of the plates witnessing no splitting crack and uniform crack distribution compared to one-way pretensioned concrete.

Light weight cellular structures have gained extensive attention in the impact energy absorption applications owing to their superior specific strength and excellent crashworthiness characteristics. The main objective of the present research work is to utilize this benefit to tailor and to improve the structural design and material type of cellular structures for crashworthiness applications. Cubic structures with four different types of design patterns such as concave, convex, hyperbola, and hexagon were proposed and fabricated through three-dimensional (3D) printing technique. Four polymeric filament materials such as Poly lactic acid (PLA), Acrylonitrile butadiene styrene (ABS), PLA mixed carbon fiber (PLA/CF), and Polyethylene terephthalate glycol (PETG), mixed carbon fiber (PETG/CF) were utilized. Accordingly, the compression tests were performed on the fabricated cellular cubic structures under quasi-static loading to examine the effect of design pattern, and material types on the compressive behavior and energy absorbing characteristics. The results revealed that the convex design pattern of 3D printed PETG/CF cubic structure showed the significant energy absorbing characteristics compared to the other three design patterns. It is emphasized that the proposed 3D printed cubic cellular structures have great prospective to substitute the traditional energy absorbing structures in automotive vehicles and high speed trains.

The mechanics of downstream blast wave attenuation caused by interaction with obstacles arranged into a pre-fractal shape based on the Sierpinski carpet was numerically investigated using a high-fidelity CFD solver. The blast mitigation was qualitatively and quantitatively assessed for four pre-fractal iterations at three different scaled distances (Z = 1.87, 2.24, 2.99 m/kg^1/3). Mitigation was seen to occur in zones associated with the location of destructive wave interference patterns in the downstream region. Crucially, these zones were found to widen spatially with increasing pre-fractal iteration, and strong shock-shock interactions that result in load amplification, commonly encountered in downstream regions of a solitary block-like obstacle, were not observed for the more fractal-like obstacles. The mechanisms of attenuation are explored in terms of wave impedance. It is found that pre-fractals reduce wave transmission in the downstream, increase reflection of the blast wave, and enhance trapping within the confines of the pre-fractal obstacle, dramatically changing the directionality and hence the strength of the transmitted wave. Reductions in peak pressure of up to 60% and peak specific impulse of up to 40% were recorded for the highest iteration pre-fractal, that is, obstacles that most closely represent a true fractal, thereby highlighting the effectiveness of such shapes for protective structure design for improved blast mitigation.

When an engineering structure regarding a rock is affected by dynamic loads (due to the occurrence of natural hazards, such as earthquakes and landslides, or man-made hazards, such as explosions or impacts), correct prediction of changes in the strength behavior and deformability of the rock relative to its static state is necessary for reducing the damages and costs. On the other hand, rocks are always influenced by environmental conditions, such as temperature changes due to fire and weather during their lifetime, which should be considered when using them. In these cases, the mechanical behavior of the rock can usually be determined under different loading and environmental conditions using stress–strain curves. This study investigates rocks’ dynamic strength and deformability behavior at different loading rates and temperatures. For this purpose, 30 travertine rock samples from the Torshab mine, located in the Markazi province of Iran, were first heated up to 100°C, 200°C, 400°C, 800°C, and 1000°C (six temperatures), and then subjected under the impact pressure with different loading rates from (five) 11 m/s to 15 m/s using the split Hopkinson pressure bar test. Comparing the obtained dynamic stress–strain curve shows that at a constant loading rate, increasing the temperature, especially at higher temperatures, reduces the dynamic strength and increases the rock’s deformability. Moreover, in all cases, at a constant temperature, increasing the loading rate, especially at higher rates, increases the rock’s dynamic strength and deformability.

Traditional protective structures are usually equipped with ventilation systems. Main components of the latter are passive air blast safety valves. Their purpose in case of an explosive event outside the structure is to significantly reduce the blast pressure leakage into the structure in order to protect human individuals as well as technical installations. Until now, the performance determination of such valves is mostly realized by means of experimental tests in a shock tube. Considering industrial and modern civil protection applications with their practical implementation, additional methods are required to gain further insights into the behaviour of different valve closing mechanisms and to support novel developments as well as error analysis. For this reason, a practice-oriented procedure is presented, with the aim to extend the assessment of the closing behaviour and blast pressure leakage of passive air blast safety valves and the structural behaviour by numerical simulations. In a first preliminary step, potential software solutions have been evaluated based on literature research and expert knowledge. After evaluation of the obtained results, two different software pairs (fluid dynamic as well as structural dynamic tools) have been tested by carrying out indirectly coupled numerical simulations. The software pair APOLLO Blastsimulator & LS-DYNA achieved satisfactory results with the indirect coupling, so that direct fully coupled FSI simulations were additionally performed. To cover a broad range of blast safety valve applications, two different suitable test cases have been considered. In comparison to the experimental results, good agreement was achieved when analysing the pressure–time history of the blast pressure leakage and the closing time of the safety valve. Furthermore, the latter was confirmed by high-speed camera registrations during blast loading.

The safety of both military personnel and equipment in unstable regions has for a long time been a major issue and concern. Protective shelters with multiple configurations have been widely used to meet safety requirements. Since military compounds are subjected to different types of threats, such as the detonation of improvised explosive devices (IED), a good understanding of the response of such shielding structures to blast waves is critical. A three-dimensional finite element (FE) model of a corner-entry ISO 20 ft container HESCO-Bastion survival shelter is developed, validated and tested under the external detonation of explosive charges. The FE model is validated against experimental data and used to investigate the protective performance of the shelter by considering several design-related parameters, such as charge location, roof extension, interior corridor dimensions and the effect of venting and its location. Results are discussed in terms of peak overpressure and maximum impulse at discrete locations around the container, and it is found that the shelter is the least efficient in mitigating the blast load propagation when the explosive material is at an angle of 45° to the entrance. Also, while the protective roof at the entrance plays a significant role in protecting the container from air-borne threats, it is observed that it contributes to higher pressure and impulse data within the shelter, for detonations at ground level, with impulse amplifications as high as 94% when fully covering the entrance area. Contrarily, varying the distance between the container and the HESCO-Bastions is found to have minimal impact on the impulse, while naturally decreasing the peak pressure for increasing distances. Venting (through openings) can lead to up to 95% reduction in the peak pressure, whilst not affecting the impulse.