Discontinuous finite-element quadrature sets based on icosahedron for the discrete ordinates method

Dai, Ni,Zhang, Bin,Chen, Yixue Korean Nuclear Society 2020 Nuclear Engineering and Technology Vol.52 No.6

The discrete ordinates method (S_N) is one of the major shielding calculation method, which is suitable for solving deep-penetration transport problems. Our objective is to explore the available quadrature sets and to improve the accuracy in shielding problems involving strong anisotropy. The linear discontinuous finite-element (LDFE) quadrature sets based on the icosahedron (in short, ICLDFE quadrature sets) are developed by defining projected points on the surfaces of the icosahedron. Weights are then introduced in the integration of the discontinuous finite-element basis functions in the relevant angular regions. The multivariate secant method is used to optimize the discrete directions and their corresponding weights. The numerical integration of polynomials in the direction cosines and the Kobayashi benchmark are used to analyze and verify the properties of these new quadrature sets. Results show that the ICLDFE quadrature sets can exactly integrate the zero-order and first-order of the spherical harmonic functions over one-twentieth of the spherical surface. As for the Kobayashi benchmark problem, the maximum relative error between the fifth-order ICLDFE quadrature sets and references is only -0.55%. The ICLDFE quadrature sets provide better integration precision of the spherical harmonic functions in local discrete angle domains and higher accuracy for simple shielding problems.

An hp-angular adaptivity with the discrete ordinates method for Boltzmann transport equation

Dai Ni,Zhang Bin,Wang Xinyu,Lu Daogang,Chen Yixue 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.2

This paper describes an hp-angular adaptivity algorithm in the discrete ordinates method for Boltzmann transport applications with strong angular effects. This adaptivity uses discontinuous finite element quadrature sets with different degrees, which updates both angular mesh and the degree of the underlying discontinuous finite element basis functions, allowing different angular local refinement to be applied in space. The regular and goal-based error metrics are considered in this algorithm to locate some regions to be refined. A mapping algorithm derived by moment conservation is developed to pass the angular solution between spatial regions with different quadrature sets. The proposed method is applied to some test problems that demonstrate the ability of this hp-angular adaptivity to resolve complex fluxes with relatively few angular unknowns. Results illustrate that a reduction to approximately 1/50 in quadrature ordinates for a given accuracy compared with uniform angular discretization. This method therefore offers a highly efficient angular adaptivity for investigating difficult particle transport problems.

Calculation of Deflection and Stress of Assembled Concrete Composite Beams under Shrinkage and Creep and Its Application in Member Design Optimization

Yan Fang,Jianghong Mao,Yixue Zhang,Weiliang Jin,Diwei Tang,Jun Zhang 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.9

There are a large number of concrete bonding interfaces in assembled concrete structures. Moreover, the problems of deformation and coordination at the interfaces lead to weak bonding under shrinkage and creep. The theoretical methods and analytical solutions for the long-term performance of composite structures in recent literatures are relatively complicated for the review or optimization in the design stage. Hence, a method for calculating the mid-span deflection of and the cross-sectional stress on composite beams under shrinkage and creep was developed based on the average curvature method. The calculation method was then verified by the experiments and the numerical simulations. Further, factors affecting the deflection of and the stress on the assembled concrete composite beams, including the loading age, the reinforcement ratio, the section dimensions, and the surface area in contact with the atmosphere were analyzed by using the developed method. The results revealed that the adjustment of the section dimensions and the loading time is the effective optimization approach. A framework for review or optimization of composite concrete beams based on the sensitivity analysis is proposed and a case study is carried out. The results of this work can helpfully be used to control the risk of additional deflections or cracking during the long-term operation of buildings.

Goal-oriented multi-collision source algorithm for discrete ordinates transport calculation

Xinyu Wang,Bin Zhang,Yixue Chen 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.7

Discretization errors are extremely challenging conundrums of discrete ordinates calculations for radiation transport problems with void regions. In previous work, we have presented a multi-collision source method (MCS) to overcome discretization errors, but the efficiency needs to be improved. This paper proposes a goal-oriented algorithm for the MCS method to adaptively determine the partitioning of the geometry and dynamically change the angular quadrature in remaining iterations. The importance factor based on the adjoint transport calculation obtains the response function to get a problem-dependent, goal-oriented spatial decomposition. The difference in the scalar fluxes from one high-order quadrature set to a lower one provides the error estimation as a driving force behind the dynamic quadrature. The goal-oriented algorithm allows optimizing by using ray-tracing technology or high-order quadrature sets in the first few iterations and arranging the integration order of the remaining iterations from high to low. The algorithm has been implemented in the 3D transport code ARES and was tested on the Kobayashi benchmarks. The numerical results show a reduction in computation time on these problems for the same desired level of accuracy as compared to the standard ARES code, and it has clear advantages over the traditional MCS method in solving radiation transport problems with reflective boundary conditions

MGGC2.0: A preprocessing code for the multi-group cross section of the fast reactor with ultrafine group library

Hu Kui,Ma Xubo,Zhang Teng,Ma Xuan,Huang Zifeng,Chen Yixue 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.8

How to generate the precise broad group cross section is important for the fast reactor design. In this study, a fast reactor multi-group cross-section generation code MGGC2.0 are developed in-house for processing ultrafine group MATXS format library. Validation and verification are performed for MGGC2.0 code by applying the benchmarks of ICSBEP handbook, and the results of MGGC2.0 agree well with that of MCNP. The consistent PN method with critical buckling search is in good agreement that condensed with TWODANT flux and flux moment for the inner core and outer core region. For the radial blanket and reflector, two region approximation method has been applied in MGGC2.0 by using collision Probability Method neutron flux solver. The RBEC-M benchmark was used to verify the power distribution calculation, and the relative error of power distribution comparison with the reference are less than 0.8% in the fuel region and the maximum relative error is 5.58% in the reflector region. Therefore, the precise broad cross section can be generated by MGGC2.0 for fast reactor

A Method of Network Public Opinion Analysis Based on Quantum Particle Swarm Algorithm Optimization Least Square Vector Machine

Bo Li,BaoXing Bai,Changsheng Zhang,Yixue Jiang 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.8

Prediction of network public opinion is a complicated prediction featuring poor information, small samples and uncertainty. A prediction model of network public opinion based on grey support vector machine (SVM) is specified to increase prediction accuracy. First, network data are preprocessed by text clustering, hotpot extraction and data aggregation. Then a time series model GM(1,1) is established and SVM is used to modify prediction outcomes of GM(1,1). At last, simulation experiment is conducted to test performance of the model. Simulation results indicate that grey SVM improves the prediction accuracy of network public opinion compared with traditional prediction models. The predictions have certain practical values.

5G-Smart Diabetes: Toward Personalized Diabetes Diagnosis with Healthcare Big Data Clouds

Chen, Min,Yang, Jun,Zhou, Jiehan,Hao, Yixue,Zhang, Jing,Youn, Chan-Hyun Institute of Electrical and Electronics Engineers 2018 IEEE communications magazine Vol.56 No.4

<P>Recent advances in wireless networking and big data technologies, such as 5G networks, medical big data analytics, and the Internet of Things, along with recent developments in wearable computing and artificial intelligence, are enabling the development and implementation of innovative diabetes monitoring systems and applications. Due to the life-long and systematic harm suffered by diabetes patients, it is critical to design effective methods for the diagnosis and treatment of diabetes. Based on our comprehensive investigation, this article classifies those methods into Diabetes 1.0 and Diabetes 2.0, which exhibit deficiencies in terms of networking and intelligence. Thus, our goal is to design a sustainable, cost-effective, and intelligent diabetes diagnosis solution with personalized treatment. In this article, we first propose the 5G-Smart Diabetes system, which combines the state-of-the-art technologies such as wearable 2.0, machine learning, and big data to generate comprehensive sensing and analysis for patients suffering from diabetes. Then we present the data sharing mechanism and personalized data analysis model for 5G-Smart Diabetes. Finally, we build a 5G-Smart Diabetes testbed that includes smart clothing, smartphone, and big data clouds. The experimental results show that our system can effectively provide personalized diagnosis and treatment suggestions to patients.</P>