3D Visual Method of Variant Logic Construction for Random Sequence

As Internet security threats continue to evolve, in order to ensure information transmission security, various encrypt and decrypt has been used in channel coding and decoding of data communication. While cryptography requires a very high degree of apparent randomness, Random sequences play an important role in cryptography. Both CA (Cellular Automata) and RC4 contain pseudo‐random number generators and may have intrinsic properties respectively. In this paper, a 3D visualization model (3DVM) is proposed to display spatial characteristics of the random sequences from CA or RC4 keystream. Key components of this model and core mechanism are described. Every module and their I/O parameters are discussed respectively. A serial of logic function of CA are selected as examples to compare with some RC4 keystreams to show their intrinsic properties in three‐dimensional space. Visual results are briefly analyzed to explore their intrinsic properties including similarity and difference. The results provide support to explore the RC4 algorithm by using 3D dimensional visualization tools to organize its interactive properties as visual maps

The Effect of Turbulence Modeling on the Mixing Characteristics of Several Fuel Injectors at Hypervelocity Flow Conditions

CFD analysis is presented on the effects of turbulence modeling choices on the mixing characteristics and performance of three fuel injectors at hypervelocity flow conditions. The analyses were carried out with the VULCAN-CFD solver using Reynolds-Averaged Simulations (RAS). The hypervelocity flow conditions match the high Mach number flow of the experiments conducted as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The three injectors are the baseline configurations used in the experiments and represent three categories of injectors typically considered individually or in combination for fueling high-speed propulsive devices. The current work discusses the impact of the turbulence model and the turbulent Schmidt number on the mixing flow field behavior and the mixing performance as described by the one-dimensional values of the Mach number, total pressure recovery, and the mixing efficiency. Because planar laser induced fluorescence (PLIF) images are available from the EIMP experiments, the sensitivity of the synthetic LIF signal to turbulence modeling choices is also examined to determine whether PLIF can be extended beyond its intended qualitative visualization purpose and used to guide CFD turbulence model and parameter selections. It is found that the mixing performance, as quantified using mixing efficiency, exhibits a strong sensitivity to both turbulence model choice and turbulent Schmidt number value. However, the synthetic LIF signal only demonstrates a modest level of sensitivity, which suggests that PLIF is of limited use for guiding CFD turbulence model and parameter selections

Pressure drop evaluation based on two-phase flow observation in packed bed system

Two-phase pressure drop in the debris has been studied by many researchers concerning the debris cooling characteristics during a severe accident in a nuclear reactor. However, its flow regime transition of the two-phase flow in the debris has not been well understood, which strongly affects the interfacial drag and the pressure drop. Conventional models for gas-liquid two-phase flow pressure drop have not been established to evaluate interfacial drag accurately. In this study, high-speed imaging of a two-dimensional network model was performed to clarify the effect of flow patterns on interfacial drag and pressure drop. Usually, it would not be easy to visualize such two-phase flow behavior in a randomly packed bed due to the reflection/refraction of light and/or overlapping bubbles, even if the test section is made of transparent materials. Therefore, in this study, a test section, which simulates a two-dimensional network of porous structures, was fabricated to avoid overlapping bubbles. The two-phase flow pattern in the porous structure has been identified by high-speed imaging of the two-dimensional network model. The flow regime map based on the flow pattern visualization results is applied to the pressure drop evaluation and it could reduce the overestimation of experimental values. The experimental results suggested that the interfacial drag term should be modified in the gas-liquid two-phase flow pressure drop model

Interactive Visualization of Multidimensional Feature Spaces

Image similarity models characterize images as points in high-dimensional feature spaces. Each point is represented by a combination of distinct features, such as brightness, color histograms or texture characteristics of the image, etc. For the design and tuning of features, and thus the effectiveness of the image similarity model, it is important to understand the interrelations of individual features and the implications on the structure of the feature space. In this paper, we discuss an interactive visualization tool for the exploration of multidimensional feature spaces. Our tool uses a graph as an intermediate representation of the points in the feature space. A mass spring algorithm is used to layout the graph in a 2D space in which arrangements of similar images are attracted to each other and dissimilar images are repelled. The emphasis of the visualization tool is on interaction: users may influence the layout by interactively scaling dimensions of the feature space. In this way, the user can explore how a feature behaves in relation to other features