[en] An essential part of burnup analysis is to solve the burnup equations. The burnup equations can be regarded as a first-order linear system and solved by means of matrix exponential methods. Because of its large spectrum, it is difficult to compute the exponential of the burnup matrix. Conventional methods of computing the matrix exponential, such as the truncated Taylor expansion and the Pade approximation, are not applicable to burnup calculations. Recently the Chebyshev Rational Approximation Method (CRAM) has been applied to solve burnup matrix exponential and shown to be robust and accurate. However, the main defect of CRAM is that its coefficients are not easy to obtain. In this paper, an orthogonal polynomial expansion method, called Laguerre Polynomial Approximation Method (LPAM), is proposed to compute the matrix exponential in burnup calculations. The polynomial sequence of LPAM can be easily computed in any order and thus LPAM is quite convenient to be utilized into burnup codes. Two typical test cases with the decay and cross-section data taken from the standard ORIGEN 2.1 libraries are calculated for validation, against the reference results provided by CRAM of 14 order. Numerical results show that, LPAM is sufficiently accurate for burnup calculations. The influences of the parameters on the convergence of LPAM are also discussed. (authors)

[en] Monte Carlo simulations containing a large number of tallies generally suffer severe performance penalties due to a significant amount of run time spent in searching for and scoring individual tally bins. This paper describes the improved methods of handling large numbers of tallies, which have been implemented in the RMC Monte Carlo code. The calculation results demonstrate that the proposed methods can considerably improve the tally performance when massive tallies are treated. In the calculated case with 6 million of tally regions, only 10% of run time is increased in each active cycle against each inactive cycle. (authors)

[en] The applications of Monte Carlo method in reactor physics analysis is somewhat restricted due to the excessive memory demand in solving large-scale problems. Memory demand in MC simulation is analyzed firstly, it concerns geometry data, data of nuclear cross-sections, data of particles, and data of tallies. It appears that tally data is dominant in memory cost and should be focused on in solving the memory problem. Domain decomposition and tally data decomposition algorithms are separately designed and implemented in the reactor Monte Carlo code RMC. Basically, the domain decomposition algorithm is a strategy of 'divide and rule', which means problems are divided into different sub-domains to be dealt with separately and some rules are established to make sure the whole results are correct. Tally data decomposition consists in 2 parts: data partition and data communication. Two algorithms with differential communication synchronization mechanisms are proposed. Numerical tests have been executed to evaluate performance of the new algorithms. Domain decomposition algorithm shows potentials to speed up MC simulation as a space parallel method. As for tally data decomposition algorithms, memory size is greatly reduced

[en] A new Monte Carlo neutron transport code RMC has been being developed by Department of Engineering Physics, Tsinghua University, Beijing as a tool for reactor physics analysis on high-performance computing platforms. To meet the requirements of reactor analysis, RMC now has such functions as criticality calculation, fixed-source calculation, burnup calculation and kinetics simulations. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation, and temperature dependent cross sections processing are researched and implemented in RMC to improve the efficiency. Validation results of criticality calculation, burnup calculation, source convergence acceleration, tallies performance and parallel performance shown in this paper prove the capabilities of RMC in dealing with reactor analysis problems with good performances. (authors)

[en] Intelligent mechanical fault diagnosis is a crucial measure to ensure the safe operation of equipment. To solve the problem that network features is not fully utilized in the adversarial transfer learning, this paper develops a Wasserstein distance based deep multi-feature adversarial (WDDMA) transfer diagnosis approach under variable working conditions. Domain adaptation is realized by adapting multi-feature in adversarial training and reducing the Wasserstein distance between the two domains after the discriminator network. The multi-feature are adapted at the same time to improve the recognition ability of the transfer network to the target domain. Experimental datasets under variable working conditions support the value of our approach.

[en] In this paper, the inverse problem on source term identification in convection-diffusion equation is transformed into an optimization problem. To reduce the computational cost and improve computational accuracy for the optimization problem, a new algorithm, chaos real-coded hybrid-accelerating evolution algorithm (CRHAEA), is proposed, in which an initial population is generated by chaos mapping, and new chaos mutation and simplex evolution operation are used. With the shrinking of searching range, CRHAEA gradually directs to an optimal result with the excellent individuals obtained by real-coded evolution algorithm. Its convergence is analyzed. Its efficiency is demonstrated by 15 test functions. Numerical simulation shows that CRHAEA has some advantages over the real-coded accelerated evolution algorithm, the chaos algorithm and the pure random search algorithm

[en] A new Monte Carlo transport code RMC has been being developed by Department of Engineering Physics, Tsinghua University, Beijing as a tool for reactor core analysis on high-performance computing platforms. To meet the requirements of reactor analysis, RMC now has such functions as criticality calculation, fixed-source calculation, burnup calculation and kinetics simulations. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation, and temperature dependent cross sections processing are researched and implemented in RMC to improve the efficiency. Validation results of criticality calculation, burnup calculation, source convergence acceleration, tallies performance and parallel performance shown in this paper prove the capabilities of RMC in dealing with reactor analysis problems with good performances. (authors)

[en] This series of slides is divided into 3 parts. The first part is dedicated to the presentation of the Monte-Carlo computational performance benchmark (aims, specifications and results). This benchmark aims at performing a full-size Monte Carlo simulation of a PWR core with axial and pin-power distribution. Many different Monte Carlo codes have been used and their results have been compared in terms of computed values and processing speeds. It appears that local power values mostly agree quite well. The first part also includes the presentations of about 10 participants in which they detail their calculations. In the second part, an extension of the benchmark is proposed in order to simulate a more realistic reactor core (for instance non-uniform temperature) and to assess feedback coefficients due to change of some parameters. The third part deals with another benchmark, the BEAVRS benchmark (Benchmark for Evaluation And Validation of Reactor Simulations). BEAVRS is also a full-core PWR benchmark for Monte Carlo simulations

[en] China is ranked first by greenhouse area in the world; pesticide application using knapsack electric sprayers is the main tool used in these settings to prevent and control plant diseases and insect pests. This is the first report of an exposure assessment for 60 greenhouse operators to the insecticide clothianidin when applied with knapsack electric sprayers. The commercial clothianidin formulation used in the field trials was a 20% suspension concentrate. The assessment was based on the whole-body dosimetry method and a personal air sampler fitted with an XAD-2 resin tube located in the operator’s breathing zone to monitor dermal and inhalation exposure, respectively. During application, the total dermal unit exposure was 598.71 mg/kg. The leg was the largest exposure area, accounting for about 53% of total dermal exposure. Meanwhile, inhalation exposure was only 0.50 mg/kg. The margin of exposure was much greater than 100 in all cases, indicating that the risk is controllable with the use of protection equipment and comparable to that of the manual application of treated soil.