Optimization of energy absorption performance of polymer honeycombs by density gradation

Density gradation has been analytically and experimentally proven to enhance the load-bearing and energy absorption efficiency of cellular solids. This paper focuses on the analytical optimization (by virtual experiments) of polymeric honeycomb structures made from thermoplastic polyurethane to achieve density-graded structures with combined desired mechanical properties. The global stress-strain curves of single-density honeycomb structures are used as input to an analytical model that enables the characterization of the constitutive response of density-graded hexagonal honeycombs with discrete and continuous gradations and for various gradients. The stress-strain outputs are used to calculate the specific energy absorption, efficiency, and ideality metrics for all density-graded structures. The analytical results are shown to be in good agreement with previous experimental measurements. Our findings suggest that the choice of an optimal gradient depends on the specific application and design criteria. For example, graded structures wherein low density layers are dominant are shown to outperform high density uniform honeycombs in terms of specific energy absorption capacity while possessing higher strength compared with low density uniform structures

Characterizing fiber-matrix debond and fiber interaction mechanisms by full-field measurements

An experimental approach is developed and utilized to characterize the fiber-matrix interfacial debonding mechanism and its effect on matrix cracking in unidirectional (UD) fiber composites. Local deformation response at the fiber-matrix interface is first studied by analyzing the strain fields developed in the vicinity of macro fibers in single-fiber samples. A practical approach for the identification of normal cohesive behavior at the fiber-matrix interface is presented and implemented in a finite element model that replicates the experimental findings. Fiber-to-fiber interaction, debond formation, and failure mechanisms in multiple fiber systems are then studied by varying the distance and angle between adjacent fibers in double-fiber samples. The experimental results indicate that the spacing and angular orientation between adjacent fibers affect the interface debond initiation and propagation, as well as subsequent matrix failure mechanisms. It is also shown that compared with fiber spacing, angular distance has a more significant effect on matrix cracking in UD composites under transverse tension. Results presented in this work provide an experimental-based quantitative insight into the mechanics of fiber-matrix interface using in-situ full-field measurements

Deformation Of Multifunctional Materials At Various Time And Length Scales: A DIC-Based Study

The focus in the present work is to explore and characterize the underlying deformation and failure mechanisms in multifunctional materials including woven composites and polymeric foams, using full-field measurements. Attention has been especially drawn towards the challenges associated with characterizing these materials at extreme length and time scales, and investigating the advantages of full-field measurements to resolve the existing limitations. Accordingly, the current limitations in the study of dynamic deformation response of low-impedance materials are identified. An approach based on the general stress equilibrium is presented and successfully implemented to include the concurrent effects of inertia and material compressibility into the analysis of direct impact response of various low impedance rigid closed-cell foams. The approach takes advantage of full-field measurement based on stereovision digital image correlation (3D-DIC) to measure the full-field acceleration and material density, later used to determine the distribution of inertia stresses developed in the material. The inertia stress is superimposed with the boundary-measured stress to give the local variation of stress in the dynamically deformed specimen. The rest of the work is dedicated to the characterization of orthogonally woven fiber reinforced composites, with emphasis on exploring the origin of deformation nonlinearity and orientation dependence of these materials when subjected to far-field loads. Attempts have been made to quantify the local deformations over fiber bundles and matrix-rich areas in woven composites with different reinforcements (glass fiber and carbon fiber) and different yarn dimensions. The full-field deformation captured through the use of 2D and 3D DIC at sub-millimeter scales is utilized to reveal the underlying load-bearing mechanisms, dominant failure modes and the origin of non-linearity in the global stress-strain response of the material subjected to in-plane axial tensile load. Results obtained through the application of full-field measurements are validated using post-mortem fracture surface study in the composites

In Situ Deformation Characterization of Density-Graded Foams in Quasi-Static and Impact Loading Conditions

Digital image correlation is utilized to characterize deformation and strain fields developed within the layers of density-graded multilayered foam structures subjected to uniaxial quasi-static and dynamic compression. Three-layered graded structures fabricated from rigid polyurethane foams with nominal densities of 160, 240, and 320 kg/m³ are subjected to both quasi-static and dynamic loading. The quasi-static measurements show that, irrespective of the loading direction, the densification initiates in the lowest density layer and propagates into other layers later once the first layer is fully densified. The deformation mechanisms are seen to be different in the case of dynamic loading conditions compared to the quasi-static loading. The deformation mechanism, in the case of dynamic loading, depends on the sample orientation relative to the direction of the applied load. In cases where the higher density layers are impacted, the propagation of the elastic and compaction waves leads to partial deformation of the lowest density layer. Sample deformation continues in all layers upon the reflection of the stress waves from the distal end of the sample. In cases where the lowest density layer is oriented towards the impact face, a completely different deformation response is observed. A detailed full-field analysis of strain and stress is performed. The mechanisms associated with the formation and propagation of stress waves from the impact ends to the distal ends of the samples are discussed

The impact of alkali-ion intercalation on redox chemistry and mechanical deformations: Case study on intercalation of Li, Na, and K ions into FePO4 cathode

Batteries made of charge carriers from Earth-crust abundant materials (e.g., Na, K, and Mg) have received extensive attention as an alternative to Li-ion batteries for grid storage. However, a lack of understanding of the behavior of these larger ions in the electrode materials hinders the development of electrode structures suitable for these large ions. In this study, we investigate the impact of alkali ions (Li, Na, and K) on the redox chemistry and mechanical deformations of iron phosphate composite cathodes by using electrochemical techniques and in situ digital image correlation. Na-ion and Li-ion intercalation demonstrate a nearly linear correlation between electrochemical strains and the state of charge and discharge. The strain development shows nonlinear dependance on the state of charge and discharge for K ions. Strain rate calculations show that K ion intercalation results in a progressive increase in the strain rate for all cycles. Li and Na intercalation induce nearly constant strain rates with the exception of the first discharge cycle of Na intercalation. When the same amount of ions are inserted into the electrode, the electrode shows the lowest strain generation upon Li intercalation compared to larger alkali ions. Na and K ions induce similar volumetric changes in the electrode when the state of charge and discharge is around 30%. Although the electrode experiences larger absolute strain generation at the end of the discharge cycles upon Na intercalation, strain rates were found to be greater for K ions. Potential-dependent behaviors also demonstrate more sluggish redox reactions during K intercalation, compared to Li and Na. Our quantitative analysis suggests that the strain rate, rather than the absolute value of strain, is the critical factor in amorphization of the crystalline electrode

Design Optimization of a Pneumatic Soft Robotic Actuator Using Model-Based Optimization and Deep Reinforcement Learning

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape and layout of air chambers are optimized individually with the firefly algorithm and a deep reinforcement learning approach using both a model-based formulation and finite element analysis. The presented modeling approach extends the analytical formulations for tapered and thickened cantilever beams connected in a structure with virtual spring elements. The deep reinforcement learning-based approach is combined with both the model- and finite element-based environments to fully explore the design space and for comparison and cross-validation purposes. The two-chamber soft actuator was specifically designed to be integrated as a modular element into a soft robotic pad system used for pressure injury prevention, where local control of planar displacements can be advantageous to mitigate the risk of pressure injuries and blisters by minimizing shear forces at the skin-pad contact. A comparison of the results shows that designs achieved using the deep reinforcement based approach best decouples the horizontal and vertical motions, while producing the necessary displacement for the intended application. The results from optimizations were compared computationally and experimentally to the empirically obtained design in the existing literature to validate the optimized design and methodology

Tuning the Mechanical Behavior of Density-Graded Elastomeric Foam Structures via Interlayer Properties.

The concept of density-graded foams has been proposed to simultaneously enhance strain energy dissipation and the load-bearing capacities at a reduced structural weight. From a practical perspective, the fabrication of density-graded foams is often achieved by stacking different foam densities. Under such conditions, the adhesive interlayer significantly affects the mechanical performance and failure modes of the structure. This work investigates the role of different adhesive layers on the mechanical and energy absorption behaviors of graded flexible foams with distinct density layers. Three adhesive candidates with different chemical, physical, and mechanical characteristics are used to assemble density-graded polyurea foam structures. The mechanical load-bearing and energy absorption performances of the structures are evaluated under quasi-static and dynamic loading conditions. Mechanical tests are accompanied by digital image correlation (DIC) analyses to study the local strain fields developed in the vicinity of the interface. Experimental measurements are also supplemented by model predictions that reveal the interplay between the mechanical properties of an adhesive interlayer and the macroscale mechanical performance of the graded foam structures. The results obtained herein demonstrate that the deformation patterns and macroscale properties of graded foam composites can be tuned by selecting different bonding agents. It is also shown that the proper selection of an adhesive can be a practical way to address the strength-energy dissipation dichotomy in graded structures

Predictability of mechanical behavior of additively manufactured particulate composites using machine learning and data-driven approaches

Additive manufacturing and data analytics are independently flourishing research areas, where the latter can be leveraged to gain a great insight into the former. In this paper, the mechanical responses of additively manufactured samples using vat polymerization process with different weight ratios of magnetic microparticles were used to develop, train, and validate a neural network model. Samples with six different compositions, ranging from neat photopolymer to a composite of photopolymer with 4 wt.% of magnetic particles, were manufactured and mechanically tested at quasi-static strain rate and ambient environmental conditions. The experimental data were also synthesized using a data-driven approach based on shape-preserving piecewise interpolations while leveraging the concept of simple micromechanics rule of mixture. The overarching objective is to forecast the mechanical behavior of new compositions to eliminate or reduce the need for exhaustive post-manufacturing testing, resulting in an accelerated product development cycle. The ML model predictions were found to be in excellent agreement with the experimental data for prognostication of the mechanical behavior of physically tested samples with near-unity correlation coefficients. Furthermore, the ML model performed reasonably well in predicting the mechanical response of untested, newly formulated compositions of photopolymers and magnetic particles. On the other hand, the data-driven approach predictions suffered from processing artifacts, demonstrating the superiority of ML algorithms in handling this type of data. Overall, this analysis approach holds great potential in advancing the prospects of additive manufacturing and model-less mechanics of material analyses. A byproduct of the ML approach is using the results for quality assurance, accelerating the acceptance of additively manufactured parts into industrial deployments

Flexible planar metamaterials with tunable Poisson\u27s ratios

This research reports on the design, fabrication, and multiscale mechanical characterization of flexible, planar mechanical metamaterials with tailorable mechanical properties. The tunable mechanical behavior of the structures is realized through the introduction of orthogonal perforations with different geometric features. Various configurations of the perforations lead to a wide range of Poisson\u27s ratios (from −0.8 to 0.4), load-bearing properties, and energy absorption capacities. The correlations between the configuration of the perforations and the auxetic response of the structures are highlighted through computational and experimental characterizations performed at multiple length scales. It is demonstrated that the local in-plane rotation of the solid ligaments in a uniaxially loaded structure is the primary factor that contributes to its strain-dependent auxetic behavior at macroscopic scales. Confinement of these local rotations is then used as a practical strategy to activate a self-strengthening mechanism in the auxetic structures. It is further shown that the fabrication of planar flexible structures with controllable Poisson\u27s ratios is feasible through spatial adjustment of perforations in the structure. Finally, discussions are provided regarding the practical applications of these structures for a new generation of highly energy-absorbing protective equipment