Commonly used time steps in dissipative particle dynamics (DPD) simulations are too large and lead to systematic errors in the computed properties. The main source of errors is the inaccurate integration of the conser...
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Commonly used time steps in dissipative particle dynamics (DPD) simulations are too large and lead to systematic errors in the computed properties. The main source of errors is the inaccurate integration of the conservative force. This error can be reduced to some extent by constructing a smoother force without any abrupt change at the cut-off distance, but the improvement is marginal. Alternatively, we tried smooth forces that also lead to the same conclusion. It is possible to find combinations of parameters for the random and dissipative forces that make errors cancel, but the combinations will depend on the system's thermodynamic state and on the particular force model. The only safe procedure is to use small time steps, i.e. comparable with those used in MD simulations. Alternatively, an improved integration algorithm should be used for the conservative force.
Commonly used time steps in dissipative particle dynamics (DPD) simulations are too large and lead to systematic errors in the computed properties. The main source of errors is the inaccurate integration of the conser...
详细信息
Commonly used time steps in dissipative particle dynamics (DPD) simulations are too large and lead to systematic errors in the computed properties. The main source of errors is the inaccurate integration of the conservative force. This error can be reduced to some extent by constructing a smoother force without any abrupt change at the cut-off distance, but the improvement is marginal. Alternatively, we tried smooth forces that also lead to the same conclusion. It is possible to find combinations of parameters for the random and dissipative forces that make errors cancel, but the combinations will depend on the system's thermodynamic state and on the particular force model. The only safe procedure is to use small time steps, i.e. comparable with those used in MD simulations. Alternatively, an improved integration algorithm should be used for the conservative force.
The recent trend towards miniaturisation has pushed the development of non-classical continuum mechanics theories intended to explain the behaviour of materials at small scales. In particular, a wide range of observed...
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The recent trend towards miniaturisation has pushed the development of non-classical continuum mechanics theories intended to explain the behaviour of materials at small scales. In particular, a wide range of observed size dependent phenomena has been experimentally identified. Two issues arise in the numerical treatment of the theories. Firstly, in a displacement-based finite element approach the need appears for higher orders of continuity in the interpolation functions. Secondly, if non-linear-inelastic material response is expected the theories should be cast in rate form and the corresponding integration algorithms complete the implementation. In this paper we address both problems for the particular case of a Cosserat Couple Stress theory. We describe alternatives for the numerical treatment and then we extend the framework to the case of a rate independent inelastic - non-linear material behaviour. The equations are presented in its flow theory form together with integration algorithms.
The stock market, one of the most important trading platforms, has been subject to many market manipulation practices since its emergence. At present, the phenomenon of market manipulation has become an obstacle that ...
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The stock market, one of the most important trading platforms, has been subject to many market manipulation practices since its emergence. At present, the phenomenon of market manipulation has become an obstacle that restricts the development of the stock market. Based on the data fusion background, this paper conducts a study on the A-share listed companies publicly investigated and confirmed as market manipulation by CSRC in China from 2018-2022 as a manipulation sample under the perspective of fusion of data, model and decision, to provide theoretical support for regulators to identify market manipulation under the new trend. The results show that: ① Comparing with single financial data, different types of models respond to text indicators significantly differently. More than that, a reasonable addition of text dimensions can optimize the model performance; ② Comparing with a single base classifier, integrated models generally have better recognition performance. In addition, this effect can be deeply improved with the diversification of the base classifier.
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