Suzhen Wang¹, Shanshan Geng¹, Zhanfeng Zhang¹, Anshan Ye², Keming Chen², Zhaosheng Xu², Huimin Luo², Gangshan Wu^3,*, Lina Xu⁴, Ning Cao⁵

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 739-757, 2019, DOI:10.32604/cmc.2019.06097

Abstract Spark is a distributed data processing framework based on memory. Memory allocation is a focus question of Spark research. A good memory allocation scheme can effectively improve the efficiency of task execution and memory resource utilization of the Spark. Aiming at the memory allocation problem in the Spark2.x version, this paper optimizes the memory allocation strategy by analyzing the Spark memory model, the existing cache replacement algorithms and the memory allocation methods, which is on the basis of minimizing the storage area and allocating the execution area according to the demand. It mainly including two parts: cache replacement optimization and… More >

S.H. Ju¹

CMES-Computer Modeling in Engineering & Sciences, Vol.64, No.1, pp. 91-109, 2010, DOI:10.3970/cmes.2010.064.091

Abstract This study develops an OpenMP scheme to parallel the preconditioned conjugate gradient methods (PCG) in shared memory computers. The proposed method is simple and systematic, so a minor change in traditional PCG methods may produce effective parallelism. At first, the global stiffness matrix is re-numbered in order to produce a parallel three-line form matrix, and a subroutine only needs to be called once in the finite element analysis. Several basic OpenMP commands are then added into the traditional incomplete Cholesky factorization (ILU) and symmetric successive over-relaxation (SSOR) codes to make the procedures of matrix multiplication, decomposition, forward substitution, and backward… More >

Liu Bingfei, Dui Guansuo, Zhu Yuping

The International Conference on Computational & Experimental Engineering and Sciences, Vol.17, No.3, pp. 73-74, 2011, DOI:10.3970/icces.2011.017.073

Abstract Several constitutive models with different yield functions for porous shape memory alloy (SMA) are compared with the experimental date. Different approaches such as upper bound theory and lower bound theory have been adopted and a new correction formula of the yield function is proposed in this work to study the behavior of porous SMAs. Numerical results are compared with the experimental date by Zhao et al (2005). It shows that the researches using upper bound and lower bound are nearly the same and the new correction formula is much closer to the experimental data than others. More >

L.Y. Wang, W. B. Song Z.D. Wang

The International Conference on Computational & Experimental Engineering and Sciences, Vol.17, No.1, pp. 13-14, 2011, DOI:10.3970/icces.2011.017.013

Abstract Shape memory epoxies and their composites have great potential applications in future deployable space structures industry. In this study six types of shape memory epoxies with different shape transition temperatures were synthesized by varying the curing agents and their contents. Thermal frozen/recovery test, DSC and DMA were performed to investigate their shape memory behaviors and thermomechanical properties. Further discussions about the testing results were presented with consideration of the microstructure. More >

Zhengfa Li, Weibin Song, Zhengdao Wang

The International Conference on Computational & Experimental Engineering and Sciences, Vol.17, No.1, pp. 11-12, 2011, DOI:10.3970/icces.2011.017.011

Abstract By using the high froze/recovery strains of shape memory polymers to meet the requirements of deployable space structures, the folding behavior of shape memory tape spring structures consisting of shape memory polymer and metal spring was analyzed. Firstly, numerical simulations were performed on the buckling modes and affecting factors under the equal- and opposite-sense bends. The results show that the folding deformations of such structure in the two cases are completely different. The equal-sense bending leads to the structure buckled abruptly, but gradual torsion buckling is received in the case of opposite-sense bending. The critical bending moments have big difference… More >

Hsin-Yu Chen, Nien-Ti Tsou^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.3, pp. 55-55, 2019, DOI:10.32604/icces.2019.05403

Abstract Shape memory alloys has been widely applied on actuators and medical devices. The transformation temperature and microstructural evolution play the crucial factors and dominate the behavior of shape memory alloys. In order to understand the influence of the composition of the Ni-Ti on the two factors, molecular dynamics (MD) is adopted to simulate the temperature-induced phase transformation in the current study. In addition, the results are post-processed by the martensite variant identification method. The method allows to reveal the detailed microstructural evolution and the volume fraction of each variant/phase in each case of the composition of Ni-Ti. Many features that… More >

K. Williams¹, T. Cagin^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.15, No.4, pp. 153-160, 2010, DOI:10.3970/icces.2010.015.153

Abstract Designing magnetic shape memory materials with practicable engineering applications requires a thorough understanding of their electronic, magnetic, and mechanical properties. Experimental and computational studies on such materials provide differing perspectives on the same problems, with theoretical approaches offering fundamental insight into complex experimental phenomena. Many recent computational approaches have focused on first-principles calculations, all of which have been successful in reproducing ground-state structures and properties such as lattice parameters, magnetic moments, electronic density of states, and phonon dispersion curves. With all of these successes, however, such methods fail to include the effects of finite temperatures, effects which are critical in… More >

Z.D. Wang¹, D.F Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.5, No.4, pp. 245-254, 2008, DOI:10.3970/icces.2008.005.245

Abstract The thermo-mechanical constitution of shape memory polymers (SMPs) is critical for predicting their deformation and recovery characteristics under different constraints. In this study, a new, physical-based, temperature and time-dependent constitutive model is proposed for simulating the thermomechanical response of SMPs. The deformation mechanisms of shape fix and shape recovery are analyzed. Different models are compared to compare strain and stress recovery responses with the experimental results. More >

Bashir S. Shariat^*, Sam Bakhtiari, Hong Yang, Yinong Liu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.1, pp. 21-21, 2019, DOI:10.32604/icces.2019.05559

Abstract Shape memory alloys (SMAs) are a unique collection of materials which can return to their initial configuration after being largely deformed. Near-equiatomic NiTi is the most widely used SMA due to its excellent shape memory properties and fabricability. One exceptional property of this alloy is superelasticity, which refers to the ability of the alloy to accommodate relatively large deformation typically up to 8% of tensile strain and return to the original undeformed shape upon unloading. As a result of this outstanding feature, superelastic NiTi have been increasingly used in different areas of engineering, such as in biomedical engineering and in… More >

Qiang Liu^1,*, Yanyun Zou^2,3, Xiaodong Liu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.3, pp. 617-637, 2019, DOI:10.32604/cmes.2019.06272

Abstract Haze-fog, which is an atmospheric aerosol caused by natural or man-made factors, seriously affects the physical and mental health of human beings. PM_2.5 (a particulate matter whose diameter is smaller than or equal to 2.5 microns) is the chief culprit causing aerosol. To forecast the condition of PM_2.5, this paper adopts the related the meteorological data and air pollutes data to predict the concentration of PM_2.5. Since the meteorological data and air pollutes data are typical time series data, it is reasonable to adopt a machine learning method called Single Hidden-Layer Long Short-Term Memory Neural Network (SSHL-LSTMNN) containing memory capability… More >