Wen Zhou

National University of Defense Technology

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Joint Operational Situation Assessment and Firepower Allocation Method Based on Enhanced Potential Energy Model

Measurement Science and Technology (2024)

Yitai Xu Jianbo Yuan Wen Zhou Miao Yu

Abstract The assessment of battlefield situations and the allocation of firepower are pivotal prerequisites for conducting joint operational planning. In response to the challenges posed by multi-service joint operations, this paper presents a methodology based on enhanced operational potential energy model for the assessment of battlefield situations and the generation of optimal firepower allocation plan. We focuses on the three-fold factors influencing operational effectiveness: spatial, informational, and environmental factors, and completes the enhanced operational potential energy model by integrating the assessment of joint operational situations and the generation of optimal firepower allocation plans. Finally, the effectiveness of this methodology is demonstrated through operational simulations in a joint anti-ship combat scenario.

Firepower

10.1088/1361-6501/ad4c8d

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Effect of Al2o3-Mwcnts on Anti-Corrosion Behavior of Inorganic Phosphate Coating in High-Temperature Marine Environment

Chenyu Wang Wu Meiping Yiyao Wang Jianyu Wang Wen Zhou

Chemically bonded aluminum phosphate coating modified with Al2O3-MWCNTs was prepared for anti-corrosion in high-temperature marine environment. a-Al2O3 was successfully and conveniently coupled to the multi-walled carbon nanotubes by surface modification. Then the hybrid materials mixed with coating materials were applied on heat-resistant steel using high-pressure airless spraying. SEM, XRD, FT-IR spectrum, Raman spectrum and TGA were performed to prove the success of hybridization. Simultaneously, adhesion, electrochemical, and SEM experiments were conducted to characterize the protective performance of the coating under different ablation times. One noteworthy phenomenon showed by the thermogravimetric analysis results is that the initial decomposition temperature of Al2O3-MWCNTs was increased by 100 °C compared with pure MWCNTs, which provided a basis for the application of the ceramic coatings in oxidation-resistant environment at 600 °C. The results of adhesion experiments showed that the dry bonding force of the ceramic coating with Al2O3-MWCNTs added on the substrate /coating interface was 3 times higher than that of the pure coating. By adding Al2O3-MWCNTs, the coating had a denser mosaic structure on the outside a three-dimensional mesh structure on the inside, which provided outstanding shielding properties and more electron channels, and had the best surface quality after ablation at 600 ℃. Additionally, the Rct value was 34.7 kΩ/cm2 after 100 h of high temperature ablation, which is 345 times of that without added coating. In general, the results showed that the corrosion resistance of the coating with Al2O3-MWCNTs as the reinforcing phase was still maintained at a high level.

10.2139/ssrn.4431586

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A Phase Field Technique for Modeling and Predicting Flow Induced Crystallization Morphology of Semi-Crystalline Polymers

Polymers (2016)

Xiaodong Wang Jie Ouyang Wen Zhou Zhijun Liu

Flow induced crystallization of semi-crystalline polymers is an important issue in polymer science and engineering because the changes in morphology strongly affect the properties of polymer materials. In this study, a phase field technique considering polymer characteristics was established for modeling and predicting the resulting morphologies. The considered crystallization process can be divided into two stages, which are nucleation upon the flow induced structures and subsequent crystal growth after the cessation of flow. Accordingly, the proposed technique consists of two parts which are a flow induced nucleation model based on the calculated information of molecular orientation and stretch, and a phase field crystal growth model upon the oriented nuclei. Two-dimensional simulations are carried out to predict the crystallization morphology of isotactic polystyrene under an injection molding process. The results of these simulations demonstrate that flow affects crystallization morphology mainly by producing oriented nuclei. Specifically, the typical skin-core structures along the thickness direction can be successfully predicted. More importantly, the results reveal that flow plays a dominant part in generating oriented crystal morphologies compared to other parameters, such as anisotropy strength, crystallization temperature, and physical noise.

Crystal (programming language)

Polystyrene

Tacticity

Morphology

10.3390/polym8060230

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Citations (21)

Some Bayesian and multivariate analysis methods in statistical machine learning and applications

Wen Zhou

The local curvature characterizes a smooth function’s shape. For the purpose of sampling a target distribution, the local curvature of the corresponding probability density function is particularly informative. We propose an adaptive Markov Chain Monte Carlo (MCMC) algorithm based on the Metropolis-Hastings (MH) probability transition kernel and the local curvature of a target density. A bounded Gaussian calibration strategy for the proposed algorithm is motivated by the relationship between the acceptance rate and the tuning parameter of the proposal distribution in an MH algorithm for sampling a standard normal distribution. The proposed algorithm balances the expected acceptance rate against the mobility of the algorithm across the state space. Simulation studies demonstrate that the proposed algorithm provides good performance when sampling densities with highly variable local curvatures (such as mixture distributions). Theoretical convergence results are presented for the proposed algorithm.

Rejection sampling

Metropolis–Hastings algorithm

Kernel (algebra)

Kernel density estimation

10.31274/etd-180810-1479

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Numerical simulation of polymer filling process by a combined finite element/discontinuous Galerkin/level set method

The Canadian Journal of Chemical Engineering (2018)

Puyang Gao Jie Ouyang Wen Zhou

Abstract The filling process in injection molding involves polymer melt and air with large density/viscosity ratios and the transient free surface. It is treated as a challenging viscoelastic‐Newtonian two‐phase flow problem especially on irregular domains. In this paper, the complex filling process for the irregular cavity is simulated using a combined finite element/discontinuous Galerkin/level set method with application to the socket with five inserts, which is rarely investigated. The rheological behaviour of the viscoelastic fluid is predicted according to the eXtended Pom‐Pom (XPP) constitutive model. The level set method proposed from prior literature is utilized to capture the moving interface because of its simplicity and efficiency. The hybrid continuous and discontinuous Galerkin method is utilized to solve the viscoelastic incompressible Navier‐Stokes equations. The second order Runge Kutta discontinuous Galerkin (RKDG) method is employed to deal with the XPP constitutive equation and the level set equation due to their hyperbolic natures. This combined algorithm is convenient to cope with the irregular cavity and avoid any stabilization terms. We first investigate the filling process of the rectangular cavity without and with a diamond insert and compare with other numerical and experimental results to illustrate the validity of the coupled method. Moreover, the cavity of the socket with five inserts is considered an application case. We analyze the influences of the inlet velocity and elasticity on physical quantities such as stresses, stretch, etc. The simulation results could provide some numerical predictions for the polymer industry.

Level set method

10.1002/cjce.23314

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Intelligent modeling of the hydrogen sulfide removal by deep eutectic solvents for the environmental protection

Separation and Purification Technology (2023)

Xuhao Li Wen Zhou Jiajun Liu Li Feng

UNIQUAC

Biogas

10.1016/j.seppur.2023.123621

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Citations (13)

Integration of Network Game and Opinion Dynamics in the Analysis and Management of Public Opinion Evolution

Yitai Xu Xiaofeng Liu Jiayi Luo Wen Zhou Miao Yu

Dynamics

10.2139/ssrn.4933829

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Integration of Network Game and Opinion Dynamics in the Analysis and Management of Public Opinion Evolution

Yitai Xu Xiaofeng Liu Jiayi Luo Wen Zhou Miao Yu

Dynamics

10.2139/ssrn.4934647

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Study on Hydrological Simulation of Jin River Based on SWAT-X Model

Applied Mechanics and Materials (2011)

Yu Fang Wen Zhou Ding Luo

Hydrological simulation is the basis of water resources management and utilization. In this study, Soil and Water Assessment Tool (SWAT) model was applied to Jin River Basin for hydrological simulation on ArcView3.3 platform. The basic database of Jin river Basin was built using ArcGis9.2. Based on the LH-OAT parameter sensitivity analysis, the sensitive parameters of runoff were identified, including CN2, Gwqmn, rchrg_dp, ESCO, sol_z, SLOPE, SOL_AWC, sol_k, Gwrevap, and then model parameters related to runoff were calibrated and validated using data observed in weifang, yifeng, shanggao and gaoan hydrological stations during 2001-2008. The simulation showed that the simulated values were reasonably comparable to the observed data (Re<20%, R 2 >0.7 and Nash-suttcliffe > 0.7), suggesting the validity of SWAT model in Jin River Basin.

SWAT model

10.4028/www.scientific.net/amm.84-85.238

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Ontology Learning by Clustering Based on Fuzzy Formal Concept Analysis

Proceedings - International Computer Software & Applications Conference (2007)

Wen Zhou Zongtian Liu Yan Zhao

Ontology is an important tool of knowledge representation, but its construction is a difficult and tedious task. Ontology constructed by formal concept analysis is quite complicated in terms of the number of concepts generated and can not deal with the vague and uncertain information in practice. A new method is developed to create fuzzy ontology by clustering on Fuzzy Formal Concept Analysis. In the end, experimental results on artificially generated datasets are produced which shows that the learning algorithm has excellent performance on the time-spatial complexity.

Ontology learning

Formal ontology

Representation

10.1109/compsac.2007.161

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Citations (22)