Machine Learning Centered Energy Optimization In Cloud Computing: A Review

The rapid growth of cloud computing has led to a significant increase in energy consumption, which is a major concern for the environment and economy. To address this issue, researchers have proposed various techniques to improve the energy efficiency of cloud computing, including the use of machine learning (ML) algorithms. This research provides a comprehensive review of energy efficiency in cloud computing using ML techniques and extensively compares different ML approaches in terms of the learning model adopted, ML tools used, model strengths and limitations, datasets used, evaluation metrics and performance. The review categorizes existing approaches into Virtual Machine (VM) selection, VM placement, VM migration, and consolidation methods. This review highlights that among the array of ML models, Deep Reinforcement Learning, TensorFlow as a platform, and CloudSim for dataset generation are the most widely adopted in the literature and emerge as the best choices for constructing ML-driven models that optimize energy consumption in cloud computing

An Improved Linear Tetrahedral Element for Plasticity

A stabilized, nodally integrated linear tetrahedral is formulated and analyzed. It is well known that linear tetrahedral elements perform poorly in problems with plasticity, nearly incompressible materials, and acute bending. For a variety of reasons, linear tetrahedral elements are preferable to quadratic tetrahedral elements in most nonlinear problems. Whereas, mixed methods work well for linear hexahedral elements, they don't for linear tetrahedrals. On the other hand, automatic mesh generation is typically not feasible for building many 3D hexahedral meshes. A stabilized, nodally integrated linear tetrahedral is developed and shown to perform very well in problems with plasticity, nearly incompressible materials and acute bending. Furthermore, the formulation is analytically and numerically shown to be stable and optimally convergent. The element is demonstrated to perform well in several standard linear and nonlinear benchmarks

The Influence of Quadrature Errors on Isogeometric Mortar Methods

Mortar methods have recently been shown to be well suited for isogeometric analysis. We review the recent mathematical analysis and then investigate the variational crime introduced by quadrature formulas for the coupling integrals. Motivated by finite element observations, we consider a quadrature rule purely based on the slave mesh as well as a method using quadrature rules based on the slave mesh and on the master mesh, resulting in a non-symmetric saddle point problem. While in the first case reduced convergence rates can be observed, in the second case the influence of the variational crime is less significant

Superplastic forming using NIKE3D

The superplastic forming process requires careful control of strain rates in order to avoid strain localizations. A load scheduler was developed and implemented into the nonlinear finite element code NIKE3D to provide strain rate control during forming simulation and process schedule output. Often the sheets being formed in SPF are very thin such that less expensive membrane elements can be used as opposed to shell elements. A large strain membrane element was implemented into NIKE3D to assist in SPF process modeling

Energy and momentum conserving algorithms for rigid body contact

Energy-momentum conserving methods are developed for rigid body dynamics with contact. Because these methods are unconditionally stable, they are not time step dependent and, hence, are well suited for incorporation into structural mechanics finite element codes. Both penalty and Lagrange multiplier methods are developed herein and are the extension of the energy-momentum conserving integration schemes for rigid bodies given by Simo and Wong [1]

Conserving algorithms for frictionless and full stick friction dynamic contact problems using the direct elimination method

This is the peer reviewed version of the following article: [Agelet de Saracibar C, Di Capua D. Conserving algorithms for frictionless and full stick friction dynamic contact problems using the direct elimination method. Int J Numer Methods Eng. 2018;113:910–937. https://doi.org/10.1002/nme.5693], which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/nme.5693. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this paper, conserving time-stepping algorithms for frictionless and full stick friction dynamic contact problems are presented. Time integration algorithms for frictionless and full stick friction dynamic contact problems have been designed in order to preserve the conservation of key discrete properties satisfied at the continuum level. Energy and energy-momentum preserving algorithms for frictionless and full stick friction dynamic contact problems, respectively, have been designed and implemented within the framework of the direct elimination method, avoiding the drawbacks linked to the use of penalty-based or Lagrange multipliers methods. An assessment of the performance of the resulting formulation is shown in a number of selected and representative numerical examples, under full stick friction and slip frictionless contact conditions. Conservation of key discrete properties exhibited by the time stepping algorithm is shown.Peer ReviewedPostprint (author's final draft

A New Stabilized Nodal Integration Approach

A new stabilized nodal integration scheme is proposed and implemented. In this work, focus is on the natural neighbor meshless interpolation schemes. The approach is a modification of the stabilized conforming nodal integration (SCNI) scheme and is shown to perform well in several benchmark problems

Orbital HP-Clouds for Solving Schrödinger Equation in Quantum Mechanics

Solving Schroedinger equation in quantum mechanics presents a challenging task in numerical methods due to the high order behavior and high dimension characteristics in the wave functions, in addition to the highly coupled nature between wave functions. This work introduces orbital and polynomial enrichment functions to the partition of unity for solution of Schroedinger equation under the framework of HP-Clouds. An intrinsic enrichment of orbital function and extrinsic enrichment of monomial functions are proposed. Due to the employment of higher order basis functions, a higher order stabilized conforming nodal integration is developed. The proposed methods are implemented using the density functional theory for solution of Schroedinger equation. Analysis of several single and multi-electron/nucleus structures demonstrates the effectiveness of the proposed method

A stabilized assumed deformation gradient finite element formulation for strongly coupled poromechanical simulations at finite strain

An adaptively stabilized finite element scheme is proposed for a strongly coupled hydro-mechanical problem in fluid-infiltrating porous solids at finite strain. We first present the derivation of the poromechanics model via mixture theory in large deformation. By exploiting assumed deformation gradient techniques, we develop a numerical procedure capable of simultaneously curing the multiple-locking phenomena related to shear failure, incompressibility imposed by pore fluid, and/or incompressible solid skeleton and produce solutions that satisfy the inf-sup condition. The template-based generic programming and automatic differentiation (AD) techniques used to implement the stabilized model are also highlighted. Finally, numerical examples are given to show the versatility and efficiency of this model