18,337 research outputs found
Application of symbolic computations to the constitutive modeling of structural materials
In applications involving elevated temperatures, the derivation of mathematical expressions (constitutive equations) describing the material behavior can be quite time consuming, involved and error-prone. Therefore intelligent application of symbolic systems to faciliate this tedious process can be of significant benefit. Presented here is a problem oriented, self contained symbolic expert system, named SDICE, which is capable of efficiently deriving potential based constitutive models in analytical form. This package, running under DOE MACSYMA, has the following features: (1) potential differentiation (chain rule), (2) tensor computations (utilizing index notation) including both algebraic and calculus; (3) efficient solution of sparse systems of equations; (4) automatic expression substitution and simplification; (5) back substitution of invariant and tensorial relations; (6) the ability to form the Jacobian and Hessian matrix; and (7) a relational data base. Limited aspects of invariant theory were also incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet pre-defined order and simplify expressions so as to limit expression growth. Results are displayed, when applicable, utilizing index notation. SDICE was designed to aid and complement the human constitutive model developer. A number of examples are utilized to illustrate the various features contained within SDICE. It is expected that this symbolic package can and will provide a significant incentive to the development of new constitutive theories
Computer simulation of the mathematical modeling involved in constitutive equation development: Via symbolic computations
Development of new material models for describing the high temperature constitutive behavior of real materials represents an important area of research in engineering disciplines. Derivation of mathematical expressions (constitutive equations) which describe this high temperature material behavior can be quite time consuming, involved and error prone; thus intelligent application of symbolic systems to facilitate this tedious process can be of significant benefit. A computerized procedure (SDICE) capable of efficiently deriving potential based constitutive models, in analytical form is presented. This package, running under MACSYMA, has the following features: partial differentiation, tensor computations, automatic grouping and labeling of common factors, expression substitution and simplification, back substitution of invariant and tensorial relations and a relational data base. Also limited aspects of invariant theory were incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). Finally not only calculation of flow and/or evolutionary laws were accomplished but also the determination of history independent nonphysical coefficients in terms of physically measurable parameters, e.g., Young's modulus, was achieved. The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet predefined order and simplify expressions so as to limit expression growth. Results are displayed when applicable utilizing index notation
Research on automatic grinding platform for rare earth ingot casting
Aiming at the problems of low grinding efficiency and difficulty in ensuring grinding uniformity of rare earth metal ingots, a rare earth metal ingot grinding system was designed. Based on Creo software and ANSYS/Workbench software, the kinematics analysis, modal analysis and transient dynamics analysis were carried out on the walking mechanism and flipping mechanism of automatic displacement platform of grinding system. The results show that the rare earth metal ingot grinding system has good stability and is beneficial to improving the grinding quality
Research on automatic grinding platform for rare earth ingot casting
Aiming at the problems of low grinding efficiency and difficulty in ensuring grinding uniformity of rare earth metal ingots, a rare earth metal ingot grinding system was designed. Based on Creo software and ANSYS/Workbench software, the kinematics analysis, modal analysis and transient dynamics analysis were carried out on the walking mechanism and flipping mechanism of automatic displacement platform of grinding system. The results show that the rare earth metal ingot grinding system has good stability and is beneficial to improving the grinding quality
Imbalanced Deep Learning by Minority Class Incremental Rectification
Model learning from class imbalanced training data is a long-standing and
significant challenge for machine learning. In particular, existing deep
learning methods consider mostly either class balanced data or moderately
imbalanced data in model training, and ignore the challenge of learning from
significantly imbalanced training data. To address this problem, we formulate a
class imbalanced deep learning model based on batch-wise incremental minority
(sparsely sampled) class rectification by hard sample mining in majority
(frequently sampled) classes during model training. This model is designed to
minimise the dominant effect of majority classes by discovering sparsely
sampled boundaries of minority classes in an iterative batch-wise learning
process. To that end, we introduce a Class Rectification Loss (CRL) function
that can be deployed readily in deep network architectures. Extensive
experimental evaluations are conducted on three imbalanced person attribute
benchmark datasets (CelebA, X-Domain, DeepFashion) and one balanced object
category benchmark dataset (CIFAR-100). These experimental results demonstrate
the performance advantages and model scalability of the proposed batch-wise
incremental minority class rectification model over the existing
state-of-the-art models for addressing the problem of imbalanced data learning.Comment: Accepted for IEEE Trans. Pattern Analysis and Machine Intelligenc
Suppressing longitudinal double-layer oscillations by using elliptically polarized laser pulses in the hole-boring radiation pressure acceleration regime
It is shown that well collimated mono-energetic ion beams with a large
particle number can be generated in the hole-boring radiation pressure
acceleration regime by using an elliptically polarized laser pulse with
appropriate theoretically determined laser polarization ratio. Due to the
effect, the double-layer charge separation region is
imbued with hot electrons that prevent ion pileup, thus suppressing the
double-layer oscillations. The proposed mechanism is well confirmed by
Particle-in-Cell simulations, and after suppressing the longitudinal
double-layer oscillations, the ion beams driven by the elliptically polarized
lasers own much better energy spectrum than those by circularly polarized
lasers.Comment: 6 pages, 5 figures, Phys. Plasmas (2013) accepte
Flexible constant force grinding of rare earth metal ingot
The rare earth metal ingots obtained by molten salt electrolysis method have oxide layers, salt layers, and other impurities on the surface, which require polishing processing. However, currently, manual polishing processing has problems such as low processing efficiency and resource waste. By designing a flexible end effector and adopting a parallel fuzzy Proportion Integration Differentiation (PID) control strategy for constant force control of the end effector, automation and high efficiency of rare earth metal ingot grinding are achieved
Flexible constant force grinding of rare earth metal ingot
The rare earth metal ingots obtained by molten salt electrolysis method have oxide layers, salt layers, and other impurities on the surface, which require polishing processing. However, currently, manual polishing processing has problems such as low processing efficiency and resource waste. By designing a flexible end effector and adopting a parallel fuzzy Proportion Integration Differentiation (PID) control strategy for constant force control of the end effector, automation and high efficiency of rare earth metal ingot grinding are achieved
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