Strain Rate Response Research Articles

The finite element method-based pattern recognition approach for the classification of patient-specific gunshot injury.

Violence related injuries and deaths mostly caused by firearms are a major problem throughout the world. Understanding the factors that control the extent of hard-soft tissue wound patterns using computer imaging techniques, numerical methods, and machine learning algorithms may help physicians to diagnose and treat those injuries more properly. Here, we investigate the use of computational results coupled with the pattern recognition algorithms to develop an approach for forensic applications. Initially, computer tomography (CT) images of the patient whose leg was shot by a 9 × 19 parabellum bullet are used to construct the FE models of that patient's femoral bone and the surrounding soft tissues. Then, Hounsfield units-based material properties are assigned to elements of the bone. To simulate the full range of loading conditions encountered in ballistic events, a constitutive model that captures the strain-rate dependent response is implemented. The entrance pathway vector of the bullet is directed in accordance with the patient's wound and the simulations are deployed for the cases having various inlet velocities such as 150, 200, 250, 300, and 350 m/s. Once the FE results for each case are obtained, they are processed with supervised machine learning algorithms to classify the wound and inlet velocity correspondence. The results demonstrate that they can be diagnosed with a percent accuracy of 97.3, 97.5, and 98.3 for the decision tree (DT), k-nearest neighbors (kNN) and support vector machine (SVM) classifier, respectively. This approach may provide a useful framework in classifying the wound type, predicting the bullet impact velocity and its firing distance.

Porosity and pore structure control in cellular geopolymer using rheology and surface tension modifiers

Cellular geopolymer is produced by aerating Alkali-activated Fly ash (AAF) binder paste using Aluminum powder. The cellular structure created in the geopolymer depends on the AAF binder paste rheology and the surface tension of the activating solution. The constant strain rate rheological behavior of AAF binder paste varies between Maxwell flow and yield type depending on the activating solution content. Aeration with a stable bubble structure is achieved in an AAF binder paste with a yield-type constant strain-rate response. AAF binder pastes which exhibit a Maxwell-flow type constant strain rate response cannot retain bubbles in suspension. Addition of clay transforms the constant strain rate rheological behavior of the AAF binder paste from Maxwell-flow to yield type response producing a stable aerated paste. Increasing the clay content in the AAF binder paste increases its yield stress. The total porosity in the cellular geopolymer is controlled by the size and quantity of aluminum powder. Equivalent total porosity is achieved with a lower dosage of finer aluminum powder. Yield stress and surface tension have opposing influences on the pore size without influencing the total porosity. Increasing the yield stress of the AAF binder paste by adding clay produces an increase in the mean pore diameter. Adding surfactant to the AAF binder paste decreases the mean pore diameter in the cellular geopolymer. The porosity and the mean pore diameter in the cellular geopolymer can be controlled with the use of clay, and surfactant and by regulating the content and fineness of the aluminum powder.

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates.

A constitutive model for automobile steel with high elongation needs to be established to predict the dynamic deformation behavior under hydroforming applications. In order to clarify the confusing discrepancy in the essential parameters of the classical Cowper-Symonds (C-S) model, a series of automobile structural steels have been employed to investigate the strain rate response by conducting tensile dynamic deformation. Metallographic microscopy and orientation distribution functions were used to characterize the microstructure and texture components of the steels. The microstructure observation discloses that the matrix of all steels is mainly of ferrite and the texture constituent provides a framework for steel to withstand external deformation. The C-S model can be applied to simulate the dynamic deformation with satisfied expectations. It is concluded that the essential parameters D and p in the model show a specific relationship with the steel grade, and the parameter D is proportional to the steel grade and related to material anisotropy, while the parameter p is inversely proportional to the steel grade and has close links with the grain boundary characteristics.

Brain Strain Rate Response: Addressing Computational Ambiguity and Experimental Data for Model Validation

Brain Strain Rate Response: Addressing Computational Ambiguity and Experimental Data for Model Validation

High Temperature and Strain-Rate Response of Al-Sic Metal Matrix Composites

High Temperature and Strain-Rate Response of Al-Sic Metal Matrix Composites

Dynamic Characterization of Additively Manufactured Polylactide (PLA)

Additively manufactured materials have excellent properties with wide applications in many industries. For designing components exposed to extreme loading situations, it is essential to characterize the high strain rate response of 3D printed (fused deposition modelling) materials. In this study, uniaxial quasi-static and dynamic compressive tests were carried out at various strain rates (10−2 s−1 and 200 s−1 to 1800 s−1) for 3D printed PLA. Strain rate dependent compressive response of Polylactide acid (PLA) disk specimens 3D printed at 0°, 45° and 90° orientations was obtained using the Split Hopkinson bar technique. The results show that the compressive strength increases with corresponding strain rates for 0° and 45° print orientations. PLA printed at 0° has higher compressive strength compared to 45° and 90° orientations under quasi-static as well as high strain rate loading. Toughness was observed to increase with strain rate in all three orientations. A simple modification to the Johnson-Cook model is proposed, which accounts for the effects of print orientation, porosity and strain softening behavior.

Spectro‐Microscopic Characterization of Elastomers Subjected to Laser‐Induced Shock Waves

AbstractThe core of this research is separated into three domains, the ultrahigh strain rate response of elastomeric polymers, laser‐induced shock waves , and terahertz time‐domain spectroscopy (THz‐TDS). Elastomers, e.g., polyurea, constitute an advance class of materials suitable for many applications, specifically in high impact loading scenarios, thus, a laser‐induced shock wave (LSW) experimental technique is used to investigate the mechanical response of shock‐loaded polyurea. LSW can submit samples to a strain rate exceeding 106 s−1 at low strains, enabling determination of material intrinsic failure modes. The large deformation induced during shock loading may alter the macromolecule structure, which can only be detected spectroscopically. Therefore, this research incorporated terahertz bulk spectroscopy to detect and report molecular conformational changes. Microscopy techniques were also used to elucidate changes in the microscale properties, morphology, and topography. The interpretation of the results explicated brittle failure in terms of partial and total spallation and, remarkably, ductile failure leading to plastic deformation, including plastic bulging and adiabatic shearing, not previously associated with LSW technique. Furthermore, spectral changes found in the terahertz regime substantiated the validity of terahertz spectroscopy in elucidating the underlying mechanism associated with the impact mitigating properties of dynamically loaded polyurea.

Kinematic Boundary Conditions Favouring Subduction Initiation at Passive Margins Over Subduction at Mid-oceanic Ridges

We perform numerical modelling to simulate the shortening of an oceanic basin and the adjacent continental margins in order to discuss the relationship between compressional stresses acting on the lithosphere and the time dependent strength of the mid-oceanic ridges within the frame of subduction initiation. We focus on the role of stress regulating mechanisms by testing the stress–strain-rate response to convergence rate, and the thermo-tectonic age of oceanic and continental lithospheres. We find that, upon compression, subduction initiation at passive margin is favoured for thermally thin (Palaeozoic or younger) continental lithospheres (<160 km) over cratons (>180 km), and for oceanic basins younger than 60 Myr (after rifting). The results also highlight the importance of convergence rate that controls stress distribution and magnitudes in the oceanic lithosphere. Slow convergence (<0.9 cm/yr) favours strengthening of the ridge and build-up of stress at the ocean-continent transition allowing for subduction initiation at passive margins over subduction at mid-oceanic ridges. The results allow for identifying geodynamic processes that fit conditions for subduction nucleation at passive margins, which is relevant for the unique case of the Alps. We speculate that the slow Africa–Europe convergence between 130 and 85 Ma contributes to the strengthening of the mid-oceanic ridge, leading to subduction initiation at passive margin 60–70 Myr after rifting and passive margin formation.

Time-Dependent Compression Behavior of Sands under Oedometric Conditions

A set of experimental data on the time-dependent oedometric compression behavior of sands is presented. The investigation focuses on the behavior of a clean quartz sand with respect to creep, strain-rate response, stress relaxation, and strain and strain rate history. The influence of different fine contents up to 25% by weight on creep, strain rate response, and stress relaxation are studied. The tests were conducted under vertical effective stress levels up to 7,500 kPa with specimens of medium dense and very dense relative density. The tests show a stress and density dependent creep behavior regardless of the fine content. Creep of sands with more than 14% by weight fine content can be described by a constant Cα/Cc ratio, whereas clean sand shows varying ratios. The response of the soils upon sudden changes in loading strain rate changes from clean sand, which exhibits only a temporary response of the stress-strain behavior, to the sands with more than 14% by weight fine content, which have a permanent response of the stress-strain behavior with continued straining. Stress relaxation tests show decreasing normalized stress relaxation σ/σ0 with increasing vertical effective stress. The behavior is independent of the density. It is described by the oedometric swelling index κ0. The tests on the influence of strain rate history show that the creep behavior of the sands is not dependent on it in the time scales studied.

Neural Network Parameter Identification Based Constitutive Modeling of Superelastic Shape Memory Alloys

AbstractSuperelastic shape memory alloys (SMAs) are two‐phase polycrystal materials with hysteretic energy dissipation and deformation recovery capabilities. This feature opens numerous application possibilities, particularly using SMA wires in structural vibration control. However, vibrations, such as wind and earthquake induced, may occur in high rate regimes with alternating amplitudes. Experiments show that the thermodynamically coupled SMA behavior is highly sensitive to strain rate and amplitude. Accordingly, the prediction accuracy of the constitutive models depends notably on their thermodynamic parameters, such as latent heat, heat transfer coefficient and specific heat. The identification of these parameters requires extensive experiments. To circumvent this challenge, this study proposes for SMA wires a machine learning based parameter identification procedure using artificial neural networks (ANNs). In this approach, a recently improved uniaxial macroscopic constitutive SMA model is utilized as a forward physics based model to compute all possible responses in an expected parameter space. With the generated data, a multilayer ANN is trained as a data based inverse model. The Latin hypercube sampling and the backpropagation learning algorithms are applied. After training, the data based model is able to identify suitable thermodynamic parameters from SMA stress responses. With the identified parameters, the constitutive model replicates the strain rate and amplitude dependent SMA response effects. The experimental results are matched by the model with high accuracy.

Large eddy simulation of premixed turbulent combustion using a non-adiabatic, strain-sensitive flamelet approach

In this study, a novel strained, non-adiabatic flamelet generated manifold (FGM) model is developed based on a counterflow premixed flame. The different levels of strain and heat loss are introduced into the flamelets by varying the stagnation point strain rate and burnt temperature of the counterflow configuration. The strain rate response of these flamelets is found to exhibit different extinction patterns for different ranges of burnt temperature. A priori studies are performed to compare the phase-space flame structures of the strained and unstrained flamelets. It is found that the strained flamelet degenerates towards the unstrained flamelet with burnt temperature decreasing. A bifurcation burnt temperature is further defined that separates the two types of flamelet quenching that are driven by strain and heat loss. An appropriate set of tabulation parameters is chosen that preserves the uniqueness of mapping between the manifold and the populated flamelets. The external boundaries of the tabulations are defined, where the proposed model degenerates into the conventional unstrained/non-adiabatic FGM manifold. Internal tabulation boundaries are defined to distinguish different combustion modes among stable combustion, strain-induced quenching, and heat-loss-induced quenching. The model is validated using large eddy simulation (LES) of a confined turbulent premixed jet flame. The proposed FGM model vastly increases accuracy of predictions when both strain and heat loss effects are included. Without accounting for these effects, there are discrepancies in the prediction of flame height and temperature as compared with experimental data. An analysis of the dominant physical process (strain, heat loss) that contributes to the evolution of the turbulent flame is performed.

Mechanical Behavior of Axonal Actin, Spectrin, and Their Periodic Structure: A Brief Review

Actin and spectrin are important constituents of axonal cytoskeleton. Periodic actin-spectrin structures are found in dendrites, initial segment of axon, and main axon. Actin-spectrin periodicity has been hypothesized to be manipulating the axon stability and mechanical behavior. Several experimental and computational studies have been performed focusing on the mechanical behavior of actin, spectrin, and actin-spectrin network. However, most of the actin studies focus on typical long F-actin and do not provide quantitative comparison between the mechanical behavior of short and long actin filaments. Also, most of the spectrin studies focus on erythrocytic spectrin and do not shed light on the behavior of structurally different axonal spectrin. Only a few studies have highlighted forced unfolding of axonal spectrin which are relevant to brain injury scenario. A comprehensive, strain rate dependent mechanical study is still absent in the literature. Moreover, the current opinions regarding periodic actin-spectrin network structure in axon are disputed due to conflicting results on actin ring organization—as argued by recent super-resolution microscopy studies. This review summarizes the ongoing limitations in this regard and provides insights on possible approaches to address them. This study will invoke further investigation into relevant high strain rate response of actin, spectrin, and actin-spectrin network—shedding light into brain pathology scenario such as traumatic brain injury (TBI).Graphic Abstract

Modelling of temperature and strain rate dependent behaviour of pearlitic steel in block braked railway wheels

Block braked railway wheels are subjected to thermal and rolling contact loading. The thermal loading results in high temperatures and thermal stresses which cause slow time dependent processes such as creep, relaxation and static recovery of the wheel material. At the same time, the rolling contact loading implies a very fast mechanical load application. This paper is focused on material modeling of pearlitic steel for a wide range of loading rates at elevated temperatures. The starting point is a viscoplasticity model including nonlinear isotropic and kinematic hardening. The Delobelle overstress function is employed to capture strain rate dependent response of the material. The model also includes static recovery of the hardening to capture slower viscous (diffusion dominated) behaviour of the material. Experiments for the pearlitic wheel steel ER7 in terms of cyclic strain-controlled uniaxial tests with hold-time, uniaxial ratchetting tests including rapid cycles and biaxial cyclic tests with tension/compression and torsion are used to calibrate the material model. These experiments were performed under isothermal conditions at different temperatures. In the ratchetting tests, higher loading rates are obtained and these have been used to calibrate the high strain rate response of the viscoplasticity model. The paper is concluded with a numerical example of a block braked wheel where the importance of accounting for the viscoplasticity in modelling is highlighted.

Fracture Hits and Hydraulic-Fracture Geometry Characterization Using Low-Frequency Distributed Acoustic Sensing Strain Data

The propagation process and geometry of hydraulic fractures depend on complex interactions among the induced fractures and the pre-existing rock fabric, the heterogeneous rock properties, and the stress state. Accurate characterization of the resulting complex hydraulic-fracture geometry remains challenging. Fiber-optic-based distributed acoustic sensing (DAS) measurements have been used for monitoring hydraulic fracturing in adjacent treatment wells. DAS requires an optical fiber attached to the wellbore to transmit the laser energy into the reservoir. Each section of the fiber scatters a small portion of the laser energy back to a surface sensing unit, which uses interferometry techniques to determine strain changes along with the fiber. DAS data in offset wells fall in the low-frequency bands, which has been proven to be a powerful attribute for the characterization of the geometry of hydraulic fractures. Numerous recently published field examples demonstrate the potential of low-frequency DAS (LF-DAS) data for the detailed characterization of the hydraulic fracture geometry. Understanding the fracture-induced rock deformation associated with LF-DAS signals would be beneficial for the better interpretation of real-time data. However, interpretation of LF-DAS measurement is challenging due to the complexity of the subsurface conditions, in addition to potential unanticipated completion issues such as perforation failure, stage isolation failure, etc. All current research efforts focus on the qualitative interpretation of field data.In this study, we quantified the hydraulic fracture propagation process and described the fracture geometry by developing a geomechanical forward model and a Green’s function-based inversion model for the LF-DAS data interpretation, substantially enhancing the value of the LF-DAS data in the process. The work has a significant transformative potential, involving a tool package with developed forward and inversion models that can provide crucial insights for the optimization of hydraulic-fracturing treatments and reservoir development. Methodology The tool package can be used directly in the field to interpret LF-DAS data and monitor hydraulic fracture propagation. Raw data from the field measurement can be automatically processed. The geomechanics forward model we developed can quantify and analyze the strain-rate response from the LF-DAS measurements based on the 3D displacement discontinuity method. Fracture hits are detected by calculating three 1D features along the channel (location) axis, i.e., the maximum strain rate, the summation of strain rates, and the summation of strain-rate amplitudes. Channels with fracture hits usually exhibit significant peak values of these three features. We proposed general guide-lines for fracture-hit detection based on the quantitative analysis of strain/strain-rate responses during the multistage fracturing treatment. The details of the forward model can be found in Liu et al. (SPE 202482, 204457, AMRA-2020-1426). Additionally, we developed a novel Green’s function-based inversion model to qualify fracture width and height based on the determined fracture hits. The strain field that is estimated from the integration of the strain rates measured by the LF-DAS data along the offset monitoring well is related to the fracture widths through a geomechanics Green’s function. The resulting linear system of equations is solved by the least-square method. Details can be found in Liu et al. (SPE 204158, 205379, 204225).

Material similarity of scaled models

When different strain hardening, strain-rate sensitive and temperature softening materials are used for scaled model and prototype, the traditional similarity laws of solid mechanics will be broken. Although research works in the last twenty years have developed the correction methods of initial conditions to compensate for the similarity distortion, their basic correction factors are practically impeded for their inherent non-direct (depending on unknown structural responses) and inexact (having significant similarity errors) defects. In this paper, a more complete framework of material similarity is developed. Based on the similarity analysis of thermo-visco-plastic constitutive equation, the material dimensionless numbers are suggested to represent the objective similarity of strain hardening, strain-rate sensitive and temperature softening effects. The universal direct and exact solution of the basic correction factors is further proved when the material numbers of the scaled model and the prototype are equal, which overcomes the previous inherent defects radically. And the simple and practical phase diagram of ‘material numbers - strain/strain-rate/temperature’ curves are proposed to design the optimum similitude materials. Three impacted structure are numerically verified: circular plate, crooked plate, and Taylor bar. The results show that the proposed material numbers control the similarity behavior of different materials. When the proposed direct and exact methods are used by the designed optimum similitude materials, the completely different materials can behave acceptable exact similarity of strain, strain-rate, temperature, stress and displacement responses in time and space fields.

High strain rate response of laminated glass interlayer materials

During a blast event, the polymeric interlayer of laminated glass used in windows and curtain walls plays an essential role in protecting buildings and occupants. In this research, the dynamic constitutive behavior of ultraviolet (UV) cured one-component acrylic resin (UVEKOL-S), Polyvinyl butyral (PVB), and virgin PVB extracted from heat strengthened laminated glass panes were investigated at an average strain rate of 30–40 s−1 using impact drop-weight apparatus. An analytical procedure was developed to simulate the drop weight device and calculate the drop height required for a certain strain rate. A new technique was used to investigate the mechanical properties of PVB, and UVEKOL-S before and after the breakage of the laminated glass, including each material energy absorption capacity. The results show that both PVB and UVEKOL-S, at strain rates of 30–40 s−1, had an initial rise in strength. However, after the maximum stress point, both materials followed a noticeable difference in their response to failure. Comparing the high-strain and static results showed that the dynamic loading significantly affects the material response and the energy absorption characteristics of the interlayer materials, and subsequently, the blast response of laminated glass panels. Sufficient data was obtained from the tests to evaluate alternative approaches to modeling PVB and UVEKOL-S materials in the blast event.

A crystal plasticity finite element model embedding strain-rate sensitivities inherent to deformation mechanisms: Application to alloy AZ31

The fundamental power-law relationship representing the flow rule in crystal visco-plasticity ensures uniqueness in the selection of slip systems accommodating imposed plastic strain-rates. The power-law relationship also introduces an artificially high strain-rate sensitivity in crystal plasticity simulations, unless a high value of the power-law exponent is used. However, the use of high values for the exponent is limited by numerical tractability. This paper presents a numerical method implemented in a crystal plasticity finite element (CPFE) model for embedding any value of the power-law exponent reflecting the true material strain-rate sensitivity. Importantly, the method does not increase computation time involved in the simulations. The enhanced CPFE model is used to interpret and predict a complex strain-rate sensitive response and microstructural evolution of AZ31 Mg alloy. Measured values of strain-rate sensitivity for slip and twinning modes are used in the simulations. Calculations show that the model successfully captures the phenomena pertaining to the effect of changing applied strain-rate on the mechanical response including flow stress and evolution of texture and twinning for a broad range of strain-rates ranging from 10−3 s−1 to 103 s−1 and loading orientations in tension and compression. It is shown that such predictions are a consequence of not only relative amounts of slip and twinning activities driven by a set of accurately characterized hardening law parameters but also values of the strain-rate sensitivities inherent to individual deformation mechanisms. Besides, the model validates the measured strain-rate dependency of deformation mechanisms while accurately reproducing the mechanical data. Hence, the model can be used to verify and further refine or infer measured strain-rate sensitivity per deformation mechanism by reproducing experimental data.

Mechanical characterisation and modelling of a thermoreversible superamolecular polyurethane over a wide range of rates

Understanding the mechanical response of thermo-recoverable elastomers to applied deformation at different strain rates and temperatures is crucial for more effective exploitation of these reusable materials in industrial applications. The research presented in this paper aims to understand the thermal and mechanical responses of a healable, elastomeric supramolecular polyurethane, examining morphology, rheology and mechanical responses from low to high strain rates. In particular, measurement of the high strain rate response of low modulus, or low strength, materials is challenging, and the current paper addresses this by incorporating a modelling framework based on low-rate characterization. To support this research, significant characterization experiments have been performed, which also show, for the first time, the excellent reusability of the polymer. The structure of specimens with different thermal histories was characterized using nuclear magnetic resonance spectroscopy, gel permeation chromatography and small angle X-ray scattering. Differential scanning calorimetry and Rheometry were used to investigate thermomechanical performance during heating and cooling cycles, whilst large strain compression characterization was performed on a commercial screw-driven test frame, a hydraulic loading system and a split-Hopkinson pressure bar. To describe the mechanical response of the polymer, a viscoelastic softening model was developed and characterized. The model incorporates data from rheometry and dynamic mechanical analysis using the principle of time-temperature superposition in a Prony series, combined with a non-linear large strain response, and recovery. The model was able to describe low strain rate behaviour under monotonic and cyclic loading, as well as predicting the response to monotonic loading at medium-to-high strain rates from 40 to 1220 s−1. The paper therefore demonstrates the effectiveness of using the viscoelastic theory and its analytical model to calibrate and further predict the mechanical behaviour of polymers at different strain rates: this is particularly useful for low modulus materials for which high strain rate characterization is challenging.

Rheology control of alkali-activated fly ash with nano clay for cellular geopolymer application

An efficient method of production for cellular geopolymer from an alkali-activated fly ash (AAF) binder paste by controlling its rheological behavior is presented. The AAF binder paste exhibits a complex rheological behavior, which is influenced by the solids loading and the composition of the activating solution. The constant strain rate response of the AAF binder paste varies between a yield-type and Maxwell flow behavior. Entrained porosity created in the hardened geopolymer matrix with the use of Aluminum powder exhibits a dependence on the constant strain rate response of the AAF binder paste. A cellular structure is achieved in pastes which exhibit a yield-type behavior. The addition of nano-clay fundamentally alters the constant strain rate response of AAF binder pastes producing a yield-type response in suspensions that exhibit a Maxwell flow behavior. There is also an increase in the peak stress in the constant strain rate response with nano-clay. A stable cellular structure is produced in the AAF binder pastes which exhibit a Maxwell-flow type response with the addition of clay. Montmorillonite is more effective than Bentonite in enhancing the yield stress of the AAF binder pastes. The importance of identifying the yield stress of the AAF binder pastes for creating a stable cellular structure within the hardened geopolymer matrix is established. The cellular structure in the geopolymer matrix can be tailored with the rheology control of the AAF binder pastes using nano-clay.