Undeformed Structure Research Articles

Large deformation theory in geomechanics - influence of kinematic nonlinearity on the results of some characteristic geotechnical calculations

The geotechnical engineering calculations are usually carried out according to the small deformation and displacement theory (infinitesimal strain theory) i.e. firstorder theory. A linear relationship between componental displacements and deformations is adopted. The well-known conditions for equilibrium are defined for an undeformed system i.e. undeformed structure. Therefore, the geometric and static linearity assumptions are usually valid in geotechnical engineering calculations. These linearities are collectively referred to as kinematic linearity. In other words, engineers believe that results of quite satisfactory accuracy are obtained if only material nonlinearity is taken into account in the engineering calculations, regardless of the type of geotechnical problem being analysed. Therefore, it is not necessary to apply the large (finite) deformation theory with the assumption of material nonlinearity. The main aim of this paper is to verify the previous statement in the case of some characteristic problems of Geotechnics. In the first part of this paper, the large deformation theory, which is mostly unknown to the wider professional public, is briefly presented. After that, simple numerical analyses of some characteristic problems of Geotechnics were carried out in the well-known software FLAC 2D software with the aim of comparing the results obtained for the cases of kinematic linearity and kinematic nonlinearity. The obtained results point to the fact that kinematic nonlinearity should not always be ignored in the usual geotechnical engineering calculations. Therefore, engineers are urged to be careful.

Hypersonic Fluid–Thermal–Structural Interaction of Cone–Slice–Ramp: Computations with Experimental Validation

The paper presents an investigation of fluid–thermal–structural interaction (FTSI) on a complex geometry in hypersonic flows. The objective is to assess high-fidelity numerical tools for FTSI by validating two numerical frameworks against wind-tunnel data. We choose a cone–slice–ramp geometry with a wedge angle of 30 deg subjected to a laminar inflow at Mach 8. First, the time-averaged and the time-resolved laminar flow solutions are validated and highlight the mean flow features and their unsteady characteristics, including low-frequency bubble breathing and shear-layer flapping at a higher frequency. The numerical analysis reveals the presence of upstream and downstream legs of streamwise vortices. Next, FTSI analysis is performed at a tractable computational cost by decomposing the numerical frameworks into a quasi-steady FTSI (QS-FTSI) analysis and a transient fluid–structure interaction (FSI) analysis based on the disparity of the characteristic timescales. The QS-FTSI results highlight the shear-layer reattachment as the dominant source heating the structure, with nonuniform spanwise variations due to the streamwise vortices. The temperature increase drives the decrease in the structural modal frequencies. The FSI analysis was performed for an unheated, undeformed structure and a nominal heated and deformed structure. The average error in the predicted FSI frequency of the unheated panel is 2.65% in comparison to the experimental data; however, this value increases to 7.42% for the heated panel. The frequency peaks are associated with the structural mode shapes via dynamic mode decomposition analysis and show a close resemblance to natural modes, indicating weak FSI coupling. The FTSI study concludes that for a cone–slice–ramp configuration under the present inflow conditions, the interaction mostly occurs in a one-way coupled manner, where the flowfield drives the thermal and structural response of the panel.

3D concrete printing: Lattice modeling of structural failure considering damage and deformed geometry

This research studies the impact of localized damage and deformed printing geometry on the structural failure of plastic collapse for 3D concrete printing (3DCP) using the lattice model. Two different approaches are utilized for buildability quantification: the (previously developed) load-unload method, which updates and relaxes the printing system after each analysis step and repeatedly applies the gravitational loading to the undeformed structure; and the incremental method, which keeps the load after each analysis step and applies the incremental loading to the deformed printing system. The former can consider the material yielding but cannot capture accurately the structural deformation during printing process. Compared to the load-unload method, the incremental method can not only consider deformed printing geometry but can also simulate the non-proportional loading conditions and disequilibrium force occurring during 3D printing. In this study, computational uniaxial compression tests are first conducted to compare two algorithms. The numerical results indicate the consideration of nonequilibrium force and deformed geometry affects the peak load and crack information for fracture analysis. Subsequently, the incremental method is incorporated into the lattice model to quantify buildability of 3DCP. The predictions are compared with previously published numerical results obtained using the load-unload method. The lattice model based on incremental method reproduces correct failure mode; better quantitative agreement about critical printing height also can be obtained. These numerical analyses demonstrate that the incremental solution is an approximate method for buildability quantification since it can account for the nonequilibrium force induced by the deformed printing geometry and localized damage.

Robust prediction of force chains in jammed solids using graph neural networks

Force chains are quasi-linear self-organised structures carrying large stresses and are ubiquitous in jammed amorphous materials like granular materials, foams or even cell assemblies. Predicting where they will form upon deformation is crucial to describe the properties of such materials, but remains an open question. Here we demonstrate that graph neural networks (GNN) can accurately predict the location of force chains in both frictionless and frictional materials from the undeformed structure, without any additional information. The GNN prediction accuracy also proves to be robust to changes in packing fraction, mixture composition, amount of deformation, friction coefficient, system size, and the form of the interaction potential. By analysing the structure of the force chains, we identify the key features that affect prediction accuracy. Our results and methodology will be of interest for granular matter and disordered systems, e.g. in cases where direct force chain visualisation or force measurements are impossible.

Ratcheting and strain ranges in the shakedown state with stress stiffening using the Simplified Theory of Plastic Zones

The behavior of elastic-plastic structures under cyclic loading can be determined by incremental elastic-plastic analyses where a given load histogram is analysed cycle-by-cycle until shakedown is achieved. Many cycles may be required for this, if a ratchet mechanism is causing plastic strains to accumulate in each cycle until either elastic or plastic shakedown is achieved. The complexity of the elastic-plastic response of a structure is further increased if geometric effects are present. It may be very costly to get the accumulated strains and strain ranges in the state of shakedown by incremental analyses so that simplified or direct methods have been developed as an alternative. The Simplified Theory of Plastic Zones (STPZ) has proven itself for estimating the required quantities in the state of elastic and plastic shakedown within the framework of the 1st order theory, i.e., if the equilibrium conditions are satisfied for the undeformed structure. It is shown in this paper, how the STPZ can be expanded to capture 2nd order effects introduced by the equilibrium of the deformed structure. Some examples are used to demonstrate its applicability and the quality of the results, but also its limitations with respect to determining the accumulated strains and elastic-plastic strain ranges.

Predicting the location of shear band initiation in a metallic glass

We report atomistic simulation results which indicate that the location of shear banding in a metallic glass (MG) can be ascertained with reasonably high accuracy solely from the undeformed static structure. Correlation is observed between the location of the initiation of shear bands in a simulated MG and the initial distribution of the density of fertile sites (DFS) for stress-driven shear transformations identified a priori based on a deep learning model devised in our recent work [Fan and Ma, Nat. Commun. 12, 1506 (2021)]. In addition, we demonstrated that one can judge whether a glass is brittle or ductile solely based upon its initial DFS distribution. These validate that shear bands in MG arise from non-linear instabilities, and that the as-quenched glass structure contains inhomogeneities that influence these instabilities. This work also reveals an important subtlety regarding the non-deterministic nature of athermal quasistatic shear simulations.

Predicting the failure of two-dimensional silica glasses

Being able to predict the failure of materials based on structural information is a fundamental issue with enormous practical and industrial relevance for the monitoring of devices and components. Thanks to recent advances in deep learning, accurate failure predictions are becoming possible even for strongly disordered solids, but the sheer number of parameters used in the process renders a physical interpretation of the results impossible. Here we address this issue and use machine learning methods to predict the failure of simulated two dimensional silica glasses from their initial undeformed structure. We then exploit Gradient-weighted Class Activation Mapping (Grad-CAM) to build attention maps associated with the predictions, and we demonstrate that these maps are amenable to physical interpretation in terms of topological defects and local potential energies. We show that our predictions can be transferred to samples with different shape or size than those used in training, as well as to experimental images. Our strategy illustrates how artificial neural networks trained with numerical simulation results can provide interpretable predictions of the behavior of experimentally measured structures.

Analyzing recrystallization behavior of heterogeneous structures single-phase Al alloys

In this research, mixed structures are created so that they have regions where dislocations accumulate and a region that is, to some extent, free from dislocations. These heterogeneous structures that bring together both soft and hard domains in a single sample are presumed to produce a fine recrystallized grain and recovered large grain structures if they are subsequently heated, leading to limited recrystallization. In the present work, the 3D Potts model has been modified to tailor and model complex problems such as heterogeneous structure recrystallization. This is done by introducing a limited fraction of nucleating grains to the structure where the highest geometrically necessary dislocation density distributions develop in the rolled layers at early simulation time as well as by controlling structure evolution in the undeformed structure layer using grain boundary energy criteria. Additionally, the designed microstructures were investigated using electron backscatter diffraction measurements and an in-situ heating stage performed on material with various degrees of deformation.

Analyzing Recrystallization Behavior of Heterogeneous Structures Single-Phase Al Alloys

In this research, mixed structures are created so that they have regions where dislocations accumulate and a region that is, to some extent, free from dislocations. These heterogeneous structures that bring together both soft and hard domains in a single sample are presumed to produce a fine recrystallized grain and recovered large grain structures if they are subsequently heated, leading to limited recrystallization. In the present work, the 3D Potts model has been modified to tailor and model complex problems such as heterogeneous structure recrystallization. This is done by introducing a limited fraction of nucleating grains to the structure where the highest geometrically necessary dislocation density distributions develop in the rolled layers at early simulation time as well as by controlling structure evolution in the undeformed structure layer using grain boundary energy criteria. Additionally, the designed microstructures were investigated using electron backscatter diffraction measurements and an in-situ heating stage performed on material with various degrees of deformation.

Caracterização físico-hídrica de solos arenosos através da curva de retenção de água, índice S e distribuição de poros por tamanho

Solos arenosos representam um desafio para a produção agrícola. Assim, o objetivo deste estudo foi caracterizar o comportamento físico-hídrico de três classes de solos arenosos através da curva de retenção de água, índice S e distribuição de poros por tamanho no geombiente dos Tabuleiros Costeiros de Arez, no estado do Rio Grande do Norte. Amostras de solo com estrutura indeformada foram coletadas nos horizontes superficiais e subsuperficiais de três perfis de solos para caracterização físico-hídrica através dos seguintes atributos: Curva de retenção de água no solo, capacidade de água disponível às plantas, potencial matricial no ponto de inflexão, umidade no ponto de inflexão, água prontamente disponível, índice de vazios, capacidade de campo relativa (CCr), distribuição de poros por tamanho, carbono orgânico total e textura do solo. Tanto em superfície quanto em subsuperfície o teor de água disponível nos solos foi influenciado positivamente pelo conteúdo de carbono orgânico e, em subsuperfície pelo aumento do teor de argila e pelo percentual de areia fina. A distribuição de poros por tamanho se apresentou de forma regular, característica de solos arenosos, com predomínio de macroporos e mesoporos, exceto para os horizontes subsuperficiais do solo no terço inferior com caráter fragipânico, onde predominou micro e criptoporos. O índice S reduziu em profundidade e os valores de CCr ficaram abaixo de 0,6, indicando uma baixa capacidade de retenção de água no solo, independentemente da posição deles na paisagem. Embora, os solos no terço inferior tenham apresentado maiores teores de água disponível.

<p>Electrospun Scaffold with Sustained Antibacterial and Tissue-Matched Mechanical Properties for Potential Application as Functional Mesh</p>

IntroductionVarious materials and approaches have been used to reduce the mesh-induced inflammatory response and modify the mesh with tissue-matched mechanical properties, aiming to improve the repair of abdominal wall defects.Materials and MethodsIn this study, we fabricated a polycaprolactone (PCL)/silk fibroin (SF) mesh integrated with amoxicillin (AMX)-incorporating multiwalled carbon nanotubes (MWCNTs) via electrospinning, grafting and crosslinking, developing a sustainable antibiotic and flexible mesh. AMX was loaded into the hollow tubular MWCNTs by physical adsorption, and a nanofibrous structure was constructed by electrospinning PCL and SF (40:60 w/w). The AMX@MWCNTs were then chemically grafted onto the surfaces of the PCL/SF nanofibers by treating with 1-ethyl-3-(3-dimethyl aminopropyl) carbodiimide/N-hydroxysuccinimide (EDC/NHS) solution for simultaneous crosslinking and coating. The incorporation of AMX into the MWCNTs (AMX@MWCNTs) and the integration of the AMX@MWCNTs with the PCL/SF nanofibers were characterized. Then, the functional mesh was fabricated and fully evaluated in terms of antibacterial activity, mechanical properties and host response.ResultsOur results demonstrated that the PCL/SF nanofibrous structure was fabricated successfully by electrospinning. After integrating with AMX@MWCNT by grafting and crosslinking, the functional mesh showed undeformed structure, modified surface hydrophilicity and biocompatible interfaces, abdominal wall-matched mechanical properties, and a sustained-release antibiotic profile in E. coli growth inhibition compared to those of PCL/SF mesh in vitro. In a rat model with subcutaneous implantation, the functional mesh incited less mesh-induced inflammatory and foreign body responses than PCL/SF mesh within 14 days. The histological analysis revealed less infiltration of granulocytes and macrophages during this period, resulting in the loosely packed collagen deposition on the functional mesh and prominent collagen incorporation.DiscussionTherefore, this designed PCL/SF–AMX@MWCNT nanofibrous mesh, functionalized with antibacterial and tissue-matched mechanical properties, provides a promising alternative for the repair of abdominal wall defects.

Dynamic Evolution Equations for Cores of Linear Crystal Defects in Colliding Solids

A discrete model in a generalized rectangular-pulse space is proposed for dislocation cores in a crystal with its undeformed perfect structure taken as a Hilbert space of Schrodinger wave functions and with the core of a dislocation as a rigged Hilbert space of step functions of opposite sign separated by a time interval. The model suggests Vlasov equations for cation and electron distribution functions and equations for an intermittent field and their solutions. It is shown that the particle dispersion law is complex, and its real part is nonlinear and quadratic.

Effect of intercritical deformation on tensile performance of a low-carbon Si–Mn steel processed by quenching and bainitic partitioning

The effect of intercritical deformation on retained austenite and tensile performance of a low-carbon Si–Mn steel in modified quenching and bainitic partitioning processes was evaluated. The results showed that the intercritical deformation can play a positive role in stabilizing and refining the retained austenite, and possessed promising potential in balancing tensile strength and ductility of multiphase high-strength steels. The experimental low-carbon Si–Mn steel exhibited multiphase configuration comprising polygonal ferrite, granular bainite and granular structure after two different modified quenching and bainitic partitioning processes, and the bainitic ferrite laths got refined by intercritical deformation. The volume fraction of retained austenite in film-like and blocky morphology was increased from 11.5% to 13.9% due to applied intercritical deformation, and the larger amount of retained austenite provided the sufficient transformation-induced plasticity effect and resulted in enhanced work hardening degree; in response, enhanced ultimate tensile strength 1260 MPa and fracture elongation 22.1% were obtained, leading to increased product of strength and elongation in value of 27.7 GPa% compared to 20.8 GPa% of undeformed structure.

Graphene crumpling as a method of hydrogen storage: Simulation results

Various carbon nanostructures, including graphene, are very promising for application in hydrogen storage. One of the promising ways to increase the hydrogen storage capacity of graphene is crumpling. In this work, an increase of hydrogen binding energy to graphene with ripple is studied by first-principle calculations. It is shown that binding energy can be considerably increased for hydrogen atom attached outside the cavity of graphene ripple. Further, by molecular dynamics simulation, it is shown that physisorption of hydrogen in the cavities of crumpled graphene is also very promising if hydrostatic compression is applied to the structure. The volumetric density of hydrogen storage can be increased for 14% for the compressed crumpled graphene in comparison with undeformed structure. Results obtained by two simulation techniques showed that crumpled graphene can be considered as a very promising media for hydrogen storage both by chemisorption and physisorption.

A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses

When metallic glasses (MGs) are subjected to mechanical loads, the plastic response of atoms is non-uniform. However, the extent and manner in which atomic environment signatures present in the undeformed structure determine this plastic heterogeneity remain elusive. Here, we demonstrate that novel site environment features that characterize interstice distributions around atoms combined with machine learning (ML) can reliably identify plastic sites in several Cu-Zr compositions. Using only quenched structural information as input, the ML-based plastic probability estimates (“quench-in softness” metric) can identify plastic sites that could activate at high strains, losing predictive power only upon the formation of shear bands. Moreover, we reveal that a quench-in softness model trained on a single composition and quench rate substantially improves upon previous models in generalizing to different compositions and completely different MG systems (Ni62Nb38, Al90Sm10 and Fe80P20). Our work presents a general, data-centric framework that could potentially be used to address the structural origin of any site-specific property in MGs.

MICRO-CRYSTAL STRUCTURE OF 57Fe15Cr25Ni0.32Mn0.96Si AUSTENITE STEEL AFTER 850°C-5H TEMPERATURE-QUENCHING TREATMENTS FOR HIGH TEMPERATURE MATERIAL APPLICATIONS

MICRO-CRYSTAL STRUCTURE OF 57Fe15Cr25Ni0.32Mn0.96Si AUSTENITE STEEL AFTER 850°C-5H TEMPERATURE-QUENCHING TREATMENTS FOR HIGH TEMPERATURE MATERIAL APPLICATIONS. A serial austenite stainless steel, namely A2-type, has been synthesized by using casting technique at temperature more than 1250 °C in the induction furnace that used an electromagnetic inductive-thermal system. The steel is dedicated for structural component material in multi-purpose applications such as in high-temperature operating environments. So, the material must be resistant to mechanical loads, high temperature, corrosion and irradiation. In order to increase the strength of materials, temperature-quenching treatments are required in some cooling media. Mineral element was extracted from crude ores of Indonesian mines and commercial scrap materials, i.e: ferro scrap, ferro chrome, nickel, manganese, and ferro silicon; all of them in granular shape were prepared to alloy the steel. Titanium was not added to this austenite low carbon steel. The OES-chemical composition in %wt of the materials is 57%Fe, 15%Cr, 25%Ni, 0.34%C and less than 0.1% of impurities that comprised of: titanium, phosphor, copper, niobium and sulphur elements in the steel. X-ray diffraction pattern shows that ascast material had an fcc crystal structure with lattice parameter of 3.632 Å. Meanwhile, two of samples, i.e: annealing and oil quench, have strictly similar lattice parameter to that of air (normalizing) quench (3.580 Å). On the other hand, the lattice parameter of water quenched samples has a slightly lower lattice parameter than the ascast lattice , i.e. 3.587 Å. The peak shift of (111) and (200) -plane in the diffraction profile, is very significant, approximately 0.63 degrees between ascast sample and the last two samples. Ascast microstructure reveals that the austenite phase grains look large and describe an undeformed structure, with an average grain size of about 6 mm, while the annealed sample was larger. Air- and oil- quenched sample microstructures showed a fine grain which was very different to water quenched sample microstructure that showed a coarse grain. The viscousity (h) of the quenching medium had an important role in the formation of grain boundary, because the rate of decreasing temperature was heavily influenced by the diffusion of heat from the high to low temperature spaces.

THE COMPLETED FORM OF ELASTIC MODEL FOR ANCF THIN PLATE ELEMENT AND ITS APPLICATION ON DYNAMIC MODELING OF THE LEAF SPRING1)

The absolute nodal coordinate formulation(ANCF) was widely used in the research of multi-body dynamics. But the thin plate element which designed for modeling thin shell structure couldn't be adopted for initial curved structure directly because of its deficiency of position vector gradient. Thin plate element was chosen for modelling the leaf spring to avoid the troublesome locking problem when using fully parameterized ANCF element. One explored the way to express the elastic force of existing thin plate element via common continuum mechanics system by adopting the unitized normal vector on the centroid plane as the added position vector gradient for thickness direction. So as to modify its elastic force formulation. The completed form of the element was given which could eliminated the introduced initial stress when describing initially curved leaf using the standard procedure which could only be performed on fully parameterized ANCF element. The modification for elastic force would not affect the element property. By setting undeformed structure which differs from initial one, the controlled initial stress could be introduced into the model for describing the assemble process. Numerical results were given to verify the validity of this modification. An initial curved double-leaf spring model was built. In order to specify the exact contact region, a cross element search strategy using a local material coordinate system built on the entire leaf was developed. Introduced a more precise calculation procedure for contact and friction force using penalty method and smooth Coulomb law. The rigid-flexible coupled leaf spring model combined with ANCF reference nodes was built, integrated with shackle, chassis and their mechanism movement.

Cell Evacology: Could it be a New Science

The sponge like protocol successfully introduced a fast, cheap and in house cell evacuation for nearly all the biological cells [1]. The original protocol describes bacterial cell evacuation from its cytoplasmic contents [1,2]. The protocol was optimized using Plackett-Burman design, which enables randomization for the variables included. Such randomization enables mapping the best cells’ evacuation experimental conditions, which give the best un-deformed 3D structure and un-deteriorated surface antigens [1,3]. Its main concept is to determine the minimum inhibition concentration (MIC) and the minimum growth concentration (MGC) of chemical compounds able to induce pores in the cell walls [1,3].

Sensitivity of Computational Rotor Dynamics Towards the Empirically Estimated Lubrication Gap Clearance of Foil Air Journal Bearings

AbstractThis contribution is concerned with the computational analysis of a rigid rotor supported by means of two self‐acting foil air journal bearings. Even though the overall equation system is thereby typically written in a nondimensional form, prior knowledge about realistic value ranges of occurring dimensionless numbers is required in order to parameterize and interpret such simulations correctly. Unlike all other quantities, the nominal lubrication gap clearance between the rotating journal and the undeformed foil structure is reported to be only poorly known. Thus, even in the light of an advanced understanding of the bearing rotor system's fundamental behavior, the quantitative reproduction and prediction of experimental results by means of computational analysis need to be viewed critically. In this study, the sensitivity of numerical results towards the assumed nominal lubrication gap clearance will be investigated. To this end, the stability of the system is considered and the characteristics of occasionally observed equilibrium points and limit cycles are addressed. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Topology optimization utilizing inverse motion based form finding

Topology optimization at finite strain setting using the concept of inverse motion based form finding is introduced. This novel procedure allows boundary conditions and shape of the structure in the operating, deformed, state to be prescribed. The outcome of the optimization algorithm will be the shape of the undeformed structure, i.e. the state in which the structure should be manufactured. The objective of the optimization considered is to find the stiffest structure for a given amount of material. The problem is regularized using a Helmholtz filter which is formulated in the deformed configuration. Both the elastic boundary value problem and the partial differential equation associated with the Helmholtz filter are solved using the finite element method. The optimization problem is solved using a sequence of convex separable approximations. The paper is closed by 2D as well as 3D numerical examples that clearly illustrates that the method is able to find optimal solutions for inverse motion finite strain topology optimization problems.