Experimental characterisation of porcine subcutaneous adipose tissue under blunt impact up to irreversible deformation

A deeper understanding of the mechanical characteristics of adipose tissue under large deformation is important for the analysis of blunt force trauma, as adipose tissue alters the stresses and strains that are transferred to subjacent tissues. Hence, results from drop tower tests of subcutaneous adipose tissue are presented (i) to characterise adipose tissue behaviour up to irreversible deformation, (ii) to relate this to the microstructural configuration, (iii) to quantify this deformation and (iv) to provide an analytical basis for computational modelling of adipose tissue under blunt impact. The drop tower experiments are performed exemplarily on porcine subcutaneous adipose tissue specimens for three different impact velocities and two impactor geometries. An approach based on photogrammetry is used to derive 3D representations of the deformation patterns directly after the impact. Median values for maximum impactor acceleration for tests with a flat cylindrical impactor geometry at impact velocities of 886~mm/s, 1253~mm/s and 2426~mm/s amount to 61.1~g, 121.6~g and 264.2~g, respectively, whereas thickness reduction of the specimens after impact amount to 16.7%, 30.5% and 39.3%, respectively. The according values for tests with a spherically shaped impactor at an impact velocity of 1253~mm/s are 184.2~g and 78.7%. Based on these results, it is hypothesised that, in the initial phase of a blunt impact, adipose tissue behaviour is mainly governed by the behaviour of the lipid inside the adipocytes, whereas for further loading, contribution of the extracellular collagen fibre network becomes more dominant

Characterization of Plasticity and Fracture Behavior of Aluminum 6061-T4 Sheet for Deep Drawing Simulation

A hybrid experimental-numerical approach to characterize plasticity and ductile fracture properties of aluminum 6061-T4 sheet is presented. The anisotropic elasto-plastic behavior is characterized by a Barlat89 model and the ductile fracture behavior by a GISSMO model in combination with the Xue-Wierzbicki model. We discuss then the validation procedure and the results related to a deep-drawing case where the simulation is carried out in a commercial FE-solver LS-DYNA. The drawing depth at fracture, as an exemplary result, shows a very good agreement between simulation and experiment

Mechanical characterisation and crashworthiness performance of additively manufactured polymer-based honeycomb structures under in-plane quasi-static loading

ABSTRACTAdditive manufacturing technology is suitable for producing energy-absorbing devices with tunable mechanical properties and improved crashworthiness performance. In this study, the mechanical properties and macrostructural crushing behaviour of five additively manufactured polymer-based honeycomb structures (HS) are investigated. Subjected to in-plane loading, the experimental results of the HS are compared with numerical findings and theoretical predictions. Results indicate that deformation modes and overall crushing performance are influenced by utilising different parent materials. The polymer HS made from polyethylene terephthalate glycol gives the best overall crushing performance over the other polymers and polymer-fibre reinforcement HS. However, the crush force efficiency of HS made from polylactic acid is the least promising. The polymer-fibre reinforced HS outperforms some of the pure polymer-based ones in terms of specific energy absorption and shows a characteristic lightweight advantage. Hence, spotting it as a promising energy absorber utilised for crashworthiness application especially where ultra-lightweight property is highly desired

Deformation Clustering Methods for Topologically Optimized Structures under Crash Load based on Displacement Time Series

Multi-objective Topology Optimization has been receiving more and more attention in structural design recently. It attempts to maximize several performance objectives by redistributing the material in a design space for a given set of boundary conditions and constraints, yielding many Paretooptimal solutions. However, the high number of solutions makes it difficult to identify preferred designs. Therefore, an automatic way of summarizing solutions is needed for selecting interesting designs according to certain criteria, such as crashworthiness, deformation, and stress state. One approach for summarization is to cluster similar designs and obtain design representatives based on a suitable metric. For example, with Euclidean distance of the objective functions as the metric, design groups with similar performance can be identified and only the representative designs from different clusters may be analyzed. However, previous research has not dealt with the deformation-related time-series data of structures with different topologies. Since the non-linear dynamic behavior of designs is important in various fields such as vehicular crashworthiness, a clustering method based on time-dependent behavior of structures is proposed here. To compare the time-series displacement data of selected nodes in the structure and to create similarity matrices of those datasets, euclidean metrics and Dynamic Time Warping (DTW) are introduced. This is combined with clustering techniques such as k-medoids and Ordering Points To Identify the Clustering Structure (OPTICS), and we investigate the use of unsupervised learning methods to identify and group similar designs using the time series of nodal displacement data. In the first part, we create simple time-series datasets using a mass-spring system to validate the proposed methods. Each dataset has predefined clusters of data with distinct behavior such as different periods or modes. Then, we demonstrate that the combination of metrics for comparison of time series (Euclidean and DTW) and the clustering method (k-medoids and OPTICS) can identify the clusters of similar behavior accurately. In the second part, we apply these methods to a more realistic, engineering dataset of nodal displacement time series describing the crash behavior of topologically-optimized designs. We identify similar structures and obtain representative designs from each cluster. This reveals that the suggested method is useful in analyzing dynamic crash behavior and supports the designers in selecting representative structures based on deformation data at the early stages of the design process

Uncertainties in dynamic response of buildings with non-linear base-isolators

Dynamic response of base-isolated buildings under uni-directional sinusoidal base excitation is numerically investigated considering uncertainties in the isolation and excitation parameters. The buildings are idealized as single degree of freedom (SDOF) system and multi-degrees of freedom (MDOF) system with one lateral degree of freedom at each floor level. The isolation system is modeled using two different mathematical models such as: (i) code-recommended equivalent linear elastic-viscous damping model and (ii) bi-linear hysteretic model. The uncertain parameters of the isolator considered are time period, damping ratio, and yield displacement. Moreover, the amplitude and frequency of the sinusoidal base excitation function are considered uncertain. The uncertainty propagation is investigated using generalized polynomial chaos (gPC) expansion technique. The unknown gPC expansion coefficients are obtained by non-intrusive sparse grid collocation scheme. Efficiency of the technique is compared with the sampling method of Monte Carlo (MC) simulation. The stochastic response quantities of interest considered are bearing displacement and top floor acceleration of the building. Effects of individual uncertain parameters on the building response are quantified using sensitivity analyses. Effect of various uncertainty levels of the input parameters on the dynamic response of the building is also investigated. The peak bearing displacement and top floor acceleration are more influenced by the amplitude and frequency of the sinusoidal base excitation function. The effective time period of the isolation system also produces a considerable influence. However, in the presence of similar uncertainty level in the time period, amplitude and frequency of the sinusoidal forcing function, the effect of uncertainties in the other parameters of the isolator (e.g., damping ratio and yield displacement) is comparatively less. Interestingly, the mean values of the response quantities are found to be higher than the deterministic values in several instances, indicating the need of conducting stochastic analysis. The gPC expansion technique presented here is found to be a computationally efficient yet accurate alternative to the MC simulation for numerically modeling the uncertainty propagation in the dynamic response analyses of the base-isolated buildings

Recent progress in 4D printed energy-absorbing metamaterials and structures

The emergence of 4D printing from additive manufacturing has opened new frontiers in crashworthiness application. Energy-absorbing structures with fixed geometrical shapes and irreversible deformation stages can be programmed such that after mild or extreme deformation, their initial shapes, properties and functionalities can be recovered with time when actuated by external stimuli. This survey delves into the recently-accelerated progress of shape memory/recovery energy-absorbing metamaterials (EAMM) and energy-absorbing smart/intelligent structures (EASS). First, the introduction gives some fundamental concepts of metamaterials and their application to energy-absorbing structures. Next, some common 3D printing technologies that have led to 4D printed EAMM and EASS are succinctly described. Shape memory materials, their functional properties and recovery process, are then discussed. Finally, various recoverable/reversible energy absorbers with their future challenges and perspectives, are presented. With well-tailored 4D printed EAMM and EASS, reusability with minimal maintenance and higher energy absorption capacity can be retained

Current trends in additively manufactured (3D printed) energy absorbing structures for crashworthiness application – a review

Inspired by the vast amounts of investigations carried out on three-dimensional (3D) printed structures and their recent accelerated developments, the present review paper comprehensively describes the current trends as well as promising findings of 3D printed energy absorbing structures (EAS) for crashworthiness application. Particular attention is paid to the mechanical behaviour and crushing performance of 3D printed EAS. The main 3D printing technological processes, their material feedstocks choices and unique structural designs, investigated recently, are discussed in detail. Deformation modes obtained by 3D printed EAS under different loading conditions are identified. Additionally, salient suggestions with future realisation of complex 3D printed EAS are provided. This review will serve as a springboard to propel the technological advancement of additively manufactured EAS incorporated into moving vehicles and utilised as protective devices. Hence, setting the goals to encourage novel research that guarantees the efficient protection of lives and valuables during mild and catastrophic impacts