arXiv subjects

Kamran Karimi

Publications and source records attributed to Kamran Karimi.

At least 19 recordsLinked to original sources

arXiv2023

Serrated plastic flow in slowly-deforming complex concentrated alloys: universal signatures of dislocation avalanches

Under plastic flow, multi-element high/medium-entropy alloys (HEAs/MEAs) commonly exhibit complex intermittent and collective dislocation dynamics owing to inherent lattice distortion and atomic-level chemical complexities. Using atomistic simulations, we report on an avalanche study of slowly-driven model face-centered cubic (fcc) NiCoCrFeMn and NiCoCr chemically complex alloys aiming for microstructural/topological characterization of associated dislocation avalanches. The results of our avalanche simulations reveal a close correspondence between the observed serration features in the stress response of the deforming HEA/MEA and the incurred slip patterns within the bulk crystal. We show that such correlations become quite pronounced within the rate-independent (quasi-static) regime exhibiting scale-free statistics and critical scaling features as universal signatures of dislocation avalanches.

cond-mat.mtrl-sci↗

arXiv2023

Tuning brittleness in multi-component metallic glasses through chemical disorder aging

Shear localization in slowly-driven bulk metallic glasses (BMGs) is typically accompanied by a sharp drop in the bulk stress response as a signature of the plastic yielding transition. It is also observed that the sharpness of this elastic-plastic dynamical transition depends on the extent of local chemical and microstructural orders, as well as the glass preparation protocol ( ie. thermal annealing). Here, we investigate sheared multi-element BMGs in molecular dynamics (MD) simulations, and demonstrate that glass aging, implemented through a hybrid Monte-Carlo(MC)-MD process, sharpens the elastic-plastic transition through a distinct crossover, seen in strain patterns that gradually shift from diffuse features in as-quenched samples to localized (yet system-spanning) patterns in well-annealed glasses. This effect of glass aging on the elastic-plastic transition is found to be correlated to the inherent interplay between aging-induced icosahedra ordering and co-operative formation of shear transformation zones. The observed crossover is quantified through a measure of the age-dependent susceptibility to plastic rearrangements, exhibiting strong (anti-)correlations to local ordering features, and the corresponding spatial correlation length grows with the aging timescale.

cond-mat.soft↗

arXiv2023

Multiscale modeling of kinetic sluggishness in equiatomic NiCoCr and NiCoCrFeMn single-phase solid solutions

Complex, concentrated, multi-component alloys have been shown to display outstanding thermo-mechanical properties, that have been typically attributed to sluggish diffusion, entropic, and lattice distortion effects. Here, we investigate two metal alloys with such exemplary properties, the equiatomic, single-phase, face-centered-cubic (FCC) alloys NiCoCr and NiCoCrFeMn, and we compare their microstructural kinetics to the behaviors in a pure-Ni FCC metal. We perform long-time, kinetic Monte Carlo (kMC) simulations, and we analyze in detail the kinetics of atomic vacancies. We find that vacancies in both concentrated alloys exhibit subdiffusive thermally driven dynamics, in direct contrast to the diffusive dynamics of pure Ni. Subdiffusive dynamics shall be attributed to dynamical sluggishness, that is modeled by a fractional Brownian random walk. Furthermore, we analyze the statistics of waiting times, and we interpret long power-law-distributed rest periods as a direct consequence of barriers' energy-scales and lattice distortions.

cond-mat.mtrl-sci↗

arXiv2022

Prediction of steel nanohardness by using graph neural networks on surface polycrystallinity maps

As a bulk mechanical property, nanoscale hardness in polycrystalline metals is strongly dependent on microstructural features that are believed to be heavily influenced from complex features of polycrystallinity -- namely, individual grain orientations and neighboring grain properties. We train a graph neural network (GNN) model, with each grain center location being a graph node, to assess the predictability of micromechanical responses of nano-indented low-carbon 310S stainless steel (alloyed with Ni and Cr) surfaces, solely based on surface polycrystallinity, captured by electron backscatter diffraction maps. The grain size distribution ranges between $1-100~μ$m, with mean grain size at $18~μ$m. The GNN model is trained on a set of nanomechanical load-displacement curves, obtained from nanoindentation tests and is subsequently used to make predictions of nano-hardness at various depths, with sole input being the grain locations and orientations. Model training is based on a sub-standard set of $\sim10^2$ hardness measurements, leading to an overall satisfactory performance. We explore model performance and its dependence on various structural/topological grain-level descriptors, such as the grain size and number of nearest neighbors. Analogous GNN model frameworks may be utilized for quick, inexpensive hardness estimates, for guidance to detailed nanoindentation experiments, akin to cartography tool developments in the world exploration era.

cond-mat.mtrl-sci↗

arXiv2022

Dislocation plasticity in equiatomic NiCoCr alloys: The effect of short-range order

Equiatomic NiCoCr solid solutions have been recently shown to display exceptional mechanical properties, that have been suggested to be linked to nanostructural short-range order (SRO) features that may arise from thermal treatments, such as annealing or/and aging. Here, we use hybrid Monte Carlo-Molecular Dynamics simulations to gain further insights of thermal effects on the SRO formation as well as the edge dislocation plasticity mechanisms of equiatomic NiCoCr face-centered cubic solid solution. For that purpose, we utilize two well-known NiCoCr interatomic potentials, one of which displays well documented SRO, believed to be linked to experimental evidence and labeled as the Li-Sheng-Ma potential, while the other (Farkas-Caro) does not. We use these two potentials to discern short range ordering (from inherent randomness in random solid solutions) and understand how SROs influence dislocation depinning dynamics in various thermal annealing scenarios. In this context, we used robust, scale-dependent metrics to infer a characteristic SRO size in the Li-Sheng-Ma case by probing local concentration fluctuations which otherwise indicate uncorrelated patterns in the Farkas-Caro case in a close agreement with random alloys. Using relevant order parameters, we also report on the drastic increase of chemical ordering within the stacking fault region. More importantly, we find that the Li-Sheng-Ma potential leads to excellent edge dislocation depinning strength with low stacking fault width. Our findings indicate an enhanced roughening mechanism due to the SROs-misfit synergy that leads to significant improvements in dislocation glide resistance. We argue that the improvements in alloy strength have their atomistic origins in the interplay between nanoscopic SROs and atomic-level misfit properties.

cond-mat.mtrl-sci↗

arXiv2022

Yielding in multi-component metallic glasses: Universal signatures of elastic modulus heterogeneities

Sheared multi-component bulk metallic glasses are characterized by both chemical and structural disorder that define their properties. We investigate the behavior of the local, microstructural elastic modulus across the plastic yielding transition in six Ni-based multi-component glasses, that are characterized by compositional features commonly associated with solid solution formability. We find that elastic modulus fluctuations display consistent percolation characteristics pointing towards universal behavior across chemical compositions and overall yielding sharpness characteristics. Elastic heterogeneity grows upon shearing via the percolation of elastically soft clusters within an otherwise rigid amorphous matrix, confirming prior investigations in granular media and colloidal glasses. We find clear signatures of percolation transition with spanning clusters that are universally characterized by scale-free characteristics and critical scaling exponents. The spatial correlation length and mean cluster size tend to diverge prior to yielding, with associated critical exponents that exhibit fairly weak dependence on compositional variations as well as macroscopic stress-strain curve details.

cond-mat.mtrl-sci↗

arXiv2021

Shear banding instability in \remove{high entropy} multi-component metallic glasses: Interplay of composition and short-range order}

The shear-banding instability in quasi-statically driven bulk metallic glasses emerges from collective dynamics, mediated by shear transformation zones and associated non-local elastic interactions. It is also phenomenologically known that sharp structural features of shear bands are typically correlated to the sharpness of the plastic yielding transition, being predominant in commonly studied alloys composed of multiple different elements, that have very different atomic radii. However, in the opposite limit \remove{of high-entropy multicomponent alloys,} where elements' radii are relatively similar, plastic yielding of bulk metallic glasses is highly dependent on compositional and ordering features. In particular, a known mechanism at play involves the formation of short-range order dominated by icosahedra-based clusters. Here, we report on atomistic simulations of multi-component metallic glasses with different chemical compositions showing that the degree of strain localization is largely controlled by the interplay between composition-driven icosahedra-ordering and collectively-driven shear transformation zones. By altering compositions, strain localization ranges from diffuse homogenized patterns to singular crack-like features. We quantify the dynamical yielding transition by measuring the atoms' susceptibility to plastic rearrangements, strongly correlated to the local atomic structure. We find that the abundance of short-range ordering of icosahedra within rearranging zones increases glassy materials' capacity to delocalize strain. The kind of plastic yielding can be often qualitatively inferred by the commonly used compositional descriptor that characterizes element associations, the misfit parameter $δ_a$, and also by uncommon ones, such as shear-band width and shear-band dynamics' correlation parameters.

cond-mat.mtrl-sci↗

arXiv2021

Sheared granular matter & the empirical relations of seismicity

The frictional instability associated with earthquake initiation and earthquake dynamics is believed to be mainly controlled by the dynamics of fragmented rocks within the fault gauge. Principal features of the emerging seismicity (e.g. intermittent dynamics and broad time and/or energy scales) have been replicated by simple experimental setups, which involve a slowly driven slider on top of granular matter, for example. Yet, these set-ups are often physically limited and might not allow one to determine the underlying nature of specific features and, hence, the universality and generality of the experimental observations. Here, we address this challenge by a numerical study of a spring-slider experiment based on two dimensional discrete element method simulations, which allows us to control the properties of the granular matter and of the surface of the slider, for example. Upon quasi-static loading, stick-slip-type behavior emerges which is contrasted by a stable sliding regime at finite driving rates, in agreement with experimental observations. Across large parameter ranges for damping, inter-particle friction, particle polydispersity etc. the earthquake-like dynamics associated with the former regime results in several robust scale-free statistical features also observed in experiments. At first sight these closely resemble the main empirical relations of tectonic seismicity at geological scales. Yet, we show that the correlations associated with tectonic aftershocks are absent such that the origin of the Omori-Utsu relation, the aftershock productivity relation, and Båth's relation in the simulations is fundamentally different from the case of tectonic seismicity. We argue that the same is true for previous lab experiments.

cond-mat.stat-mech↗

arXiv2019

Self-diffusion in plastic flow of amorphous solids

We report on a particle-based numerical study of sheared amorphous solids in the dense slow flow regime. In this framework, deformation and flow are accompanied by critical fluctuation patterns associated with the macroscopic plastic response and single particle kinematics. The former is commonly attributed to the collective slip patterns that relax internal stresses within the bulk material and give rise to an effective mechanical noise governing the latter particle-level process. In this work, the avalanche-type dynamics between plastic events is shown to have a strong relevance on the self-diffusion of tracer particles in the Fickian regime. As a consequence, strong size effects emerge in the effective diffusion coefficient that is rationalized in terms of avalanche size distributions and the relevant temporal occurrence.

cond-mat.soft↗

arXiv2018

From plastic flow to brittle fracture: role of microscopic friction in amorphous solids

Plasticity in soft amorphous materials typically involves collective deformation patterns that emerge upon intense shearing. The microscopic basis of amorphous plasticity has been commonly established through the notion of "Eshelby"-type events, localized abrupt rearrangements that induce flow in the surrounding material via non-local elastic-type interactions. This universal mechanism in flowing disordered solids has been proposed despite their diversity in terms of scales, microscopic constituents, or interactions. However, we argue that the presence of frictional interactions in granular solids alters the dynamics of flow by nucleating micro shear cracks that continually coalesce to build up system-spanning fracture-like formations on approach to failure. The plastic-to-brittle failure transition is uniquely controlled by the degree of frictional resistance which is in essence similar to the role of heterogeneities that separate the abrupt and smooth yielding regimes in glassy structures.

cond-mat.soft↗

arXiv2017

Correlation and shear bands in a plastically deformed granular medium

Recent experiments (Le Bouil et al., Phys. Rev. Lett., 2014, 112, 246001) have analyzed the statistics of local deformation in a granular solid undergoing plastic deformation. Experiments report strongly anisotropic correlation between events, with a characteristic angle that was interpreted using elasticity theory and the concept of Eshelby transformations with dilation; interestingly, the shear bands that characterize macroscopic failure occur at an angle that is different from the one observed in microscopic correlations. Here, we interpret this behavior using a mesoscale elastoplastic model of solid flow that incorporates a local Mohr-Coulomb failure criterion. We show that the angle observed in the microscopic correlations can be understood by combining the elastic interactions associated with Eshelby transformation with the local failure criterion. At large strains, we also induce permanent shear bands at an angle that is different from the one observed in the correlation pattern. We interpret this angle as the one that leads to the maximal instability of slip lines.

cond-mat.soft↗

arXiv2017

Anomalous Stress Fluctuations in Athermal Two Dimensional Amorphous Solids

We numerically study the local stress distribution within athermal, isotropically stressed, mechanically stable, packings of bidisperse frictionless disks above the jamming transition in two dimensions. Considering the Fourier transform of the local stress, we find evidence for algebraically increasing fluctuations in both isotropic and anisotropic components of the stress tensor at small wavenumbers, contrary to recent theoretical predictions. Such increasing fluctuations imply a lack of self-averaging of the stress on large length scales. The crossover to these increasing fluctuations defines a length scale $\ell_0$, however it appears that $\ell_0$ does not vary much with packing fraction $ϕ$, nor does $\ell_0$ seem to be diverging as $ϕ$ approaches the jamming $ϕ_J$. We also find similar large length scale fluctuations of stress in the inherent states of a quenched Lennard-Jones liquid, leading us to speculate that such fluctuations may be a general property of amorphous solids in two dimensions.

cond-mat.soft↗

arXiv2017

Inertia and universality of avalanche statistics: The case of slowly deformed amorphous solids

By means of a finite elements technique we solve numerically the dynamics of an amorphous solid under deformation in the quasistatic driving limit. We study the noise statistics of the stress-strain signal in the steady state plastic flow, focusing on systems with low internal dissipation. We analyze the distributions of avalanche sizes and durations and the density of shear transformations when varying the damping strength. In contrast to avalanches in the overdamped case, dominated by the yielding point universal exponents, inertial avalanches are controlled by a non-universal damping dependent feedback mechanism; eventually turning negligible the role of correlations. Still, some general properties of avalanches persist and new scaling relations can be proposed.

cond-mat.soft↗

arXiv2015

Rheology, diffusion, and velocity correlations in the bubble model

We present results on spatio-temporal correlations in the so-called mean drag version of the Durian bubble model in the limit of small, but finite, shearing rates, $\dotγ$. We study the rheology, diffusion, and spatial correlations of the instantaneous velocity field. The quasi-static (QS) effective diffusion co-efficient, $D_e$, shows an anomalous system size dependence indicative of organization of plastic slip into lines along the directions of maximum shearing. At higher rates, $D_e$ decays like $\dotγ^{-1/3}$. The instantaneous velocity fields have a spatial structure which is consistent with a set of spatially uncorrelated Eshelby transformations. The correlations are cut off beyond a length, $ξ$. $ξ\sim \dotγ^{-1/3}$ which explains the $D_e\sim\dotγ^{-1/3}$ behavior. The shear stress, $σ$, follows a similar rate dependence with $δσ=σ-σ_y\sim \dotγ^{1/3}$ where $σ_y$ is the yield stress observed in the QS regime.These results indicate that the form for the viscous dissipation can have a profound impact on the rheology, diffusion and spatial correlations in sheared soft glassy systems.

cond-mat.soft↗

arXiv2015

When In-Memory Computing is Slower than Heavy Disk Usage

Disk access latency and transfer times are often considered to have a major and detrimental impact on the running time of software. Developers are often advised to favour in-memory operations and minimise disk access. Furthermore, diskless computer architectures are being studied and designed to remove this bottleneck all together, to improve application performance in areas such as High Performance Computing, Big Data, and Business Intelligence. In this paper we use code inspired by real, production software, to show that in-memory operations are not always a guarantee for high performance, and may actually cause a considerable slow-down. We also show how small code changes can have dramatic effects on running times. We argue that a combination of system-level improvements and better developer awareness and coding practices are necessary to ensure in-memory computing can achieve its full potential.

cs.OH↗

arXiv2015

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

OpenCL, along with CUDA, is one of the main tools used to program GPGPUs. However, it allows running the same code on multi-core CPUs too, making it a rival for the long-established OpenMP. In this paper we compare OpenCL and OpenMP when developing and running compute-heavy code on a CPU. Both ease of programming and performance aspects are considered. Since, unlike a GPU, no memory copy operation is involved, our comparisons measure the code generation quality, as well as thread management efficiency of OpenCL and OpenMP. We evaluate the performance of these development tools under two conditions: a large number of short-running compute-heavy parallel code executions, when more thread management is performed, and a small number of long-running parallel code executions, when less thread management is required. The results show that OpenCL and OpenMP each win in one of the two conditions. We argue that while using OpenMP requires less setup, OpenCL can be a viable substitute for OpenMP from a performance point of view, especially when a high number of thread invocations is required. We also provide a number of potential pitfalls to watch for when moving from OpenMP to OpenCL.

cs.DC↗

arXiv2013

Accelerating a Cloud-Based Software GNSS Receiver

In this paper we discuss ways to reduce the execution time of a software Global Navigation Satellite System (GNSS) receiver that is meant for offline operation in a cloud environment. Client devices record satellite signals they receive, and send them to the cloud, to be processed by this software. The goal of this project is for each client request to be processed as fast as possible, but also to increase total system throughput by making sure as many requests as possible are processed within a unit of time. The characteristics of our application provided both opportunities and challenges for increasing performance. We describe the speedups we obtained by enabling the software to exploit multi-core CPUs and GPGPUs. We mention which techniques worked for us and which did not. To increase throughput, we describe how we control the resources allocated to each invocation of the software to process a client request, such that multiple copies of the application can run at the same time. We use the notion of effective running time to measure the system's throughput when running multiple instances at the same time, and show how we can determine when the system's computing resources have been saturated.

cs.PF↗

arXiv2012

Challenges of Upgrading a Virtual Appliance

A virtual appliance contains a target application, and the running environment necessary for running that application. Users run an appliance using a virtualization engine, freeing them from the need to make sure that the target application has access to all its dependencies. However, creating and managing a virtual appliance, versus a stand-alone application, requires special considerations. Upgrading a software system is a common requirement, and is more complicated when dealing with an appliance. This is because both the target application and the running environment must be upgraded, and there are often dependencies between these two components. In this paper we briefly discuss some important points to consider when upgrading an appliance. We then present a list of items that can help developers prevent problems during an upgrade effort.

cs.SE↗