Current Issue : July - September Volume : 2017 Issue Number : 3 Articles : 6 Articles
A developed microstructure-based internal state variable (ISV) plasticity damage model is for the first time used for simulating\npenetration mechanics of aluminum to find out its penetration properties. The ISV damage model tries to explain the interplay\nbetween physics at different length scales that governs the failure and damage mechanisms of materials by linking the macroscopic\nfailure and damage behavior of the materials with their micromechanical performance, such as void nucleation, growth, and\ncoalescence.Within the continuum modeling framework, microstructural features of materials are represented using a set of ISVs,\nand rate equations are employed to depict damage history and evolution of the materials. For experimental calibration of this\ndamage model, compression, tension, and torsion straining conditions are considered to distinguish damage evolutions under\ndifferent stress states. To demonstrate the reliability of the presented ISV model, that model is applied for studying penetration\nmechanics of aluminum and the numerical results are validated by comparing with simulation results yielded from the Johnson-\nCook model as well as analytical results calculated from an existing theoretical model....
Soft compliant grasping is essential in delicate manipulation tasks typically\nrequired in manufacturing and/or medical applications to prevent stress\nconcentration at the point of contact. In comparison with their rigid counterparts,\nthe intrinsic compliance of soft grippers offers simpler control and planning of the\ngrasping action, especially where robots are faced with a number of objects varying\nin shape and size. However, quantitative analysis is rarely utilized in the design and\nfabrication of soft grippers, due to the fact that significant and complex deformation\noccurs once the soft gripper is in contact with external objects. In this paper,\nwe demonstrate the design of a soft gripper using our novel bimorph-like pneumatic\nbending actuators. The gripper was modelled through finite element analysis to\nreflect its gripping capability during interaction with certain targeted objects. The\nproposed systematic design and analytical model was validated via experiments.\nThe system�s gripping capability was evaluated with objects of different weight and\ndimension. In addition, compliance testing has proved that the proposed soft gripper\nis able to grip objects of 60 g from the side, without causing exceeding concentration\nstress on the targeted object....
In this paper, broken rotor bar (BRB) fault is investigated by utilizing the Motor Current Signature Analysis (MCSA) method. In\nindustrial environment, induction motor is very symmetrical, and it may have obvious electrical signal components at different fault\nfrequencies due to their manufacturing errors, inappropriate motor installation, and other influencing factors.The misalignment\nexperiments revealed that improper motor installation could lead to an unexpected frequency peak, which will affect the motor\nfault diagnosis process. Furthermore,manufacturing and operating noisy environment could also disturb themotor fault diagnosis\nprocess. This paper presents efficient supervised Artificial Neural Network (ANN) learning technique that is able to identify fault\ntype when situation of diagnosis is uncertain. Significant features are taken out from the electric current which are based on\nthe different frequency points and associated amplitude values with fault type. The simulation results showed that the proposed\ntechnique was able to diagnose the target fault type. The ANN architecture worked well with selecting of significant number\nof feature data sets. It seemed that, to the results, accuracy in fault detection with features vector has been achieved through\nclassification performance and confusion error percentage is acceptable between healthy and faulty condition of motor....
The important gradients of stress arising in rough mechanical contacts due to interaction at the asperity level are responsible for\ndamage mechanisms like rolling contact fatigue, wear, or crack propagation. The deterministic approach to this process requires\ncomputationally effective numerical solutions, capable of handling very fine meshes that capture the particular features of the\ninvestigated contacting surface.The spatial discretization needs to be supported by temporal sampling of the simulation window\nwhen time-dependent viscoelastic constitutive laws are considered in the description of the material response. Moreover, when\nreal surface microtopography is considered, steep slopes inevitably lead to localized plastic deformation at the tip of the asperities\nthat are first brought into contact. A computer model for the rough contact of linear viscoelastic materials, capable of handling\ndeterministic contact geometry, complex viscoelastic models, and arbitrary loading histories, is advanced in this paper. Plasticity is\nconsidered in a simplified manner that preserves the information regarding the contact area and the pressure distribution without\ncomputing the residual strains and stresses. The model is expected to predict the contact behavior of deterministic rough surfaces\nas resulting from practical engineering applications, thus assisting the design of durable machine elements using elastomers or\nrubbers....
The paper presents a nonlinear unknown input observer (NUIO) based on singular value decomposition aided reduced dimension\nCubature Kalman filter (SVDRDCKF) for a special class of nonlinear systems, the nonlinearity of which is only caused by part of its\nstates. Firstly, the algorithmof general NUIO is discussed and the unknown input observer based on singular value decomposition\naidedCubatureKalman filter (SVDCKF) given.Thena special nonlinear systemmodel with unknown input is introduced. Based on\nthe proposed model and the corresponding NUIO, the equivalent integral form with partial sampling and all sampling of the state\nvector in Cubature Kalman filter is analyzed. Finally the nonlinear unknown input observer based on singular value decomposition\naided reduced dimension Cubature Kalman filter is obtained. Simulation results show that the proposed algorithm can meet the\nrequirements of the system and ismore important to increase the calculating efficiency a lot, although it has a decline in the accuracy\nof the filter....
Simulation of numerical reservoir models with thousands and millions of grid blocks may consume a significant amount of time\nand effort, even when high performance processors are used. In cases where the simulation runs are required for sensitivity analysis,\ndynamic control, and optimization, the act needs to be repeated several times by continuously changing parameters. This makes it\neven more time-consuming. Currently, proxy models that are based on response surface are being used to lessen the time required\nfor running simulations during sensitivity analysis and optimization. Proxy models are lighter mathematical models that run faster\nand perform in place of heavier models that require large computations. Nevertheless, to acquire data for modeling and validation\nand develop the proxy model itself, hundreds of simulation runs are required. In this paper, a system identification based proxy\nmodel that requires only a single simulation run and a properly designed excitation signal was proposed and evaluated using a\nbenchmark case study. The results show that, with proper design of excitation signal and proper selection of model structure,\nsystem identification based proxy models are found to be practical and efficient alternatives for mimicking the performance of\nnumerical reservoir models. The resulting proxy models have potential applications for dynamic well control and optimization....
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