On locally embedded two-scale solution for wall-bounded turbulent flows

Recent findings on wall-bounded turbulence have prompted a new impetus for modelling development to capture and resolve the Reynolds-number-dependent influence of outer flow on near-wall turbulence in terms of the ‘foot-printing’ of the large-scale coherent structures and the scale-interaction associated ‘modulation’. We develop a two-scale method to couple a locally embedded near-wall fine-mesh direct numerical simulation (DNS) block with a global coarser mesh domain. The influence of the large-scale structures on the local fine-mesh block is captured by a scale-dependent coarse–fine domain interface treatment. The coarse-mesh resolved disturbances are directly exchanged across the interface, while only the fine-mesh resolved fluctuations around the coarse-mesh resolved variables are subject to periodic conditions in the streamwise and spanwise directions. The global near-wall coarse-mesh region outside the local fine-mesh block is governed by the augmented flow governing equations with forcing source terms generated by upscaling the space–time-averaged fine-mesh solution. The validity and effectiveness of the method are examined for canonical incompressible channel flows at several Reynolds numbers. The mean statistics and energy spectra are in good agreement with the corresponding full DNS data. The results clearly illustrate the ‘foot-printing’ and ‘modulation’ in the local fine-mesh block. Noteworthy also is that neither spectral-gap nor scale-separation is assumed, and a smooth overlap between the global-domain and the local-domain energy spectra is observed. It is shown that the mesh-count scaling with Reynolds number is potentially reduced from $O(R{e^2})$ for the conventional fully wall-resolved large-eddy simulation (LES) to $O(Re)$ for the present locally embedded two-scale LES.

Impact of domain disorder on optoelectronic properties of layered semimetal MoTe2

We address the impact of crystal phase disorder on the generation of helicity-dependent photocurrents in layered MoTe2, which is one of the van der Waals materials to realize the topological type-II Weyl semimetal phase. Using scanning photocurrent microscopy, we spatially probe the phase transition and its hysteresis between the centrosymmetric, monoclinic 1T’ phase to the symmetry-broken, orthorhombic Td phase as a function of temperature. We find a highly disordered photocurrent response in the intermediate temperature regime. Moreover, we demonstrate that helicity-dependent and ultrafast photocurrents in MoTe2 arise most likely from a local breaking of the electronic symmetries. Our results highlight the prospects of local domain morphologies and ultrafast relaxation dynamics on the optoelectronic properties of low-dimensional van der Waals circuits.

Integrating generalized domain adaptation and Fisher discriminative learning: A unified framework for face recognition with single sample per person

In this paper, an enhanced discriminative feature learning (EDFL) method is proposed to address single sample per person (SSPP) face recognition. With a separate auxiliary dataset, EDFL integrates Fisher discriminative learning and domain adaptation into a unified framework. The separate auxiliary dataset and the gallery/probe dataset are from two different domains (named source and target domains respectively) and have different data distributions. EDFL is modeled to transfer the discriminative knowledge learned from the source domain to the target domain for classification. Since the gallery set with SSPP contains scarce number of samples, it is hard to accurately represent the data distribution of the target domain, which hinders the adaptation effect. To overcome this problem, the generalized domain adaption (GDA) method is proposed to realize good overall domain adaptation when one domain contains limited samples. GDA considers the both global and local domain adaptation effect at the same time. Further, to guarantee that the learned domain adaptation components are optimal for discriminative learning, the domain adaptation and Fisher discriminant model learning are unified into a single framework and an efficient algorithm is designed to optimize them. The effectiveness of the proposed approach is demonstrated by extensive evaluation and comparison with some state-of-the-art methods.

A local meshless analysis of dynamics problems / Uma análise local desordenada dos problemas dinâmicos

This paper is concerned with new formulations of local meshfree numerical method, for the solution of dynamic problems in linear elasticity, Integrated Local Mesh Free (ILMF) method. The key attribute of local numerical methods is the use of a modeling paradigm based on a node-by-node calculation, to generate the rows of the global system of equations of the body discretization. In the local domain, assigned to each node of a discretization, the work theorem is kinematically formulated, leading thus to an equation of mechanical equilibrium of the local node, that is used by local meshfree method as the starting point of the formulation. The main feature of this paper is the use of a linearly integrated local form of the work theorem. The linear reduced integration plays a key role in the behavior of local numerical methods, since it implies a reduction of the nodal stiffness which, in turn, leads to an increase of the solution accuracy. As a consequence, the derived meshfree and finite element numerical methods become fast and accurate, which is a feature of paramount importance, as far as computational efficiency of numerical methods is concerned. The cantilever beam was analyzed with this technique, in order to assess the accuracy and efficiency of the new local numerical method for dynamic problems with regular and irregular nodal configuration. The results obtained in this work are in perfect agreement with Mesh-Free Local Petrov-Galerkin (MLPG) and the Finite Element Method (FEM) solutions.

Finite Element Simulation of Axisymmetric Elastic and Electroelastic Wave Propagation Using Local-Domain Wave Packet Enrichment

A local-domain wave packet enriched multiphysics finite element (FE) formulation is employed for accurately solving axisymmetric wave propagation problems in elastic and piezoelastic media, involving complex wave modes and sharp jumps at the wavefronts, which pose challenges to the conventional FE solutions. The conventional Lagrangian interpolations for the displacement and electric potential fields are enriched with the element-domain sinusoidal functions that satisfy the partition of unity condition. The extended Hamilton’s principle is employed to derive the coupled system of equations of motion which is solved using the simple Newmark-β direct time integration scheme without resorting to any remeshing near the wavefronts or post-processing. The performance of the enrichment is assessed for the axisymmetric problems of impact waves in elastic and piezoelectric cylinders and elastic half-space, bulk and Rayleigh waves in the semi-infinite elastic domain and ultrasonic Lamb wave actuation and propagation in plate-piezoelectric transducer system. The element shows significant improvement in the computational efficiency and accuracy over the conventional FE for all problems, including those involving multiple complex wave modes and sharp discontinuities in the fields at the wavefronts.

Bi-level Flow Based Anomalous Activity Identification System for IoT Devices

With the advanced technologies, IoT has widely emerged with data collection, processing, and communication as well in smart applications. The wireless medium in the IoT devices would broadcast the data, which makes them easily targeted by the attacks. In the local network, the normal communication attack is restricted to small local domain or local nodes. However, the attack present in IoT devices gets expanded to a large area that would cause destructive effects. The heterogeneity and distribution of IoT services/applications make the security of IoT a more challenging and complex one. This paper aims to propose a bi-level flow based anomalous activity identification system in IoT. Initially, the flow based features get extracted along with the statistical features like mean, median, variance, correlation, and correntropy. Subsequently, Bi-level classification is carried out in this work. In level 1, the presence of attack is detected and the level 2 classification classifies the type of attack. A decision tree is used for detecting the attacks by checking whether the network traffic is anomalous traffic or normal traffic. In level 2, an Optimized Neural network (NN) is used for categorizing the attacks in IoT with the knowledge of flow features and statistical features. To make the detection and classification more accurate, the weight of NN will be optimally tuned by a new Combined Whale SeaLion Algorithm (CWSA) that hybridizes the concepts of both SLnO and WOA. At last, the performance of the adopted method is computed over other traditional models in terms of accuracy, sensitivity, specificity, precision, FPR, FDR, FNR, NPV, F1-score, and MCC.

Atomic-resolution Probing of Anion Migration in Perovskites with In-situ (S)TEM

ABSTRACTPerovskites are promising functional materials for their optoelectronic properties and anion migration plays a key role in their functional performance [1-3]. By using in-situ (S)TEM mechanical and electrical testing in conjunction with 4D-STEM [4,5], we directly observed/probed anion migration in perovskites at atomic resolution (see Figure 1). Here, we studied the mechanism for the anion migration in perovskites such as (PbZr)TiO3 and BaTiO3, which is induced under the mechnaicl/electrical loading. To avoid the influence of the electron beam, we carried out the in-situ (S)TEM study at 60kv with low dose. And to avoid the possible strong size effect and the substrate (interface) influence, we prepared free-standing sub-micrometer single-crystalline structures to perform the experiments. Corresponding EDS and EELS examinations were performed to measure the local chemical change with applied stress and electrical currents. Our observations revealed the coexistence of multiple phase structures and hierarchical domain structures, as well as the greatly enhanced anion drifting and diffusion at the charged domain walls (Figure 2) and phase boundaries. The complex interaction between the local domain evolution and phase transition has been discussed. Based on above investigations, a model for anion migration in perovskire under mechanical/electrical loading has been presented.

CSR Initiatives and Practices: Empirical Evidence From Indian Metal and Mining Companies

This study investigates the corporate social responsibility (CSR) discourse on community and environment by Indian metal and mining (extractive) sector. Specifically, we examine the change in internal governance and external implementation mechanisms in response to affirmative CSR policy actions. Applying text network analysis technique on CSR related expenditures provided in the annual reports and CSR annexures (2014–2018), our study reveals that CSR discourse of extractive firms improved significantly and became more focused after the introduction of post-affirmative policy. CSR initiatives in the extractive sector are primarily focused toward local social development, with little emphasis on the environmental sustainability. Furthermore, companies have adopted two-tier governance structures for managing CSR. The top tier comprises board members who formulate the CSR programs, while the second tier has executives responsible for the implementation. Another tier of governance involving local domain experts is emerging. The three-tier implementation mechanisms give firms a tighter control on spending and enhance the effectiveness of initiatives. We present the results visually in the form of network graphs.

LEA-DNS: DNS Resolution Validity and Timeliness Guarantee Local Authentication Extension with Public Blockchain

While the Domain Name System (DNS) is an infrastructure of the current network, it still faces the problem of centralization and data authentication according to its concept and practice. Decentralized storage of domain names and user local verification using blockchain may be effective solutions. However, since the blockchain is an add-only type database, domain name changes will cause out of date records to still be correct when using the Simplified Payment Verification (SPV) mechanism locally. This paper mainly introduces Local Enhanced Authentication DNS (LEA-DNS), which allows domain names to be stored in public blockchain database to provide decentralization feature and is compatible with the existing DNS. It achieves the validity and timeliness of local domain name resolution results to ensure correct and up to date with the Merkle Mountain Range and RSA accumulator technologies. Experiments show that less than 3.052Kb is needed for each DNS request to be validated, while the validation time is negligible, and only 9.44Kb of data need to be stored locally by the web client. Its compatibility with the existing DNS system and the lightness of the validation protocols indicate that this is a system suitable for deployment widely.