Comparison of Experiment and Simulation of the triple GEM-Based Fast Neutron Detector

A detector for fast neutrons based on a 10 × 10 cm^2 triple gas electron multiplier （GEM） device is developed and tested. A neutron converter, which is a high density polyethylene （HDPE） layer, is combined with the triple GEM detector cathode and placed inside the detector, in the path of the incident neutrons. The detector is tested by obtaining the energy deposition spectrum with an Am Be neutron source in the Institute of Modern Physics （IMP） at Lanzhou. In the present work we report the results of the tests and compare them with those of simulations. The transport of fast neutrons and their interactions with the different materials in the detector are simulated with the GEANT4 code, to understand the experimental results. The detector displays a clear response to the incident fast neutrons. However, an unexpected disagreement in the energy dependence of the response between the simulated and measured spectra is observed. The neutron sources used in our simulation include deuterium-tritium （DT, 14 MeV）, deuterium-deuterium （DD, 2.45 MeV）, and Am Be sources. The simulation results also show that among the secondary particles generated by the incident neutron, the main contributions to the total energy deposition are from recoil protons induced in hydrogen-rich HDPE or Kapton （GEM material）, and activation photons induced by neutron interaction with Ar atoms. Their contributions account for 90% of the total energy deposition. In addition, the dependence of neutron deposited energy spectrum on the composition of the gas mixture is presented.

APPLICATIONS OF FAST SIMULATED ANNEALING IN NEURAL NETWORKS

Fast simulated annealing is implemented into the learning process of neural network to replace the traditional back-propagation algorithm. The new procedure exhibits performance fast in learning and accurate in prediction compared to the traditional neural networks. Two numerical data sets were used to illustrate its use in chemistry.

Fast muon simulation in the JUNO central detector

The Jiangmen Underground Neutrino Observatory （JUNO） is a multi-purpose neutrino experiment designed to measure the neutrino mass hierarchy using a central detector （CD）, which contains 20 kton liquid scintillator （LS） surrounded by about 17000 photomultiplier tubes （PMTs）. Due to the large fiducial volume and huge number of PMTs, the simulation of a muon particle passing through the CD with the Geant4 toolkit becomes an extremely computation-intensive task. This paper presents a fast simulation implementation using a so-called voxel method： for scintillation photons generated in a certain LS voxel, the PMT＇s response is produced beforehand with Geant4 and then introduced into the simulation at runtime. This parameterisation method successfully speeds up the most CPU consuming process, the optical photon＇s propagation in the LS, by a factor of 50. In the paper, the comparison of physics performance between fast and full simulation is also given.

A rapid modeling method for urban microscale meteorology and its applications

This paper introduces a fast urban microscale meteorological model with a horizontal resolution of O(10)m,named URBAN(Urban Rapid&Building-Aware Neighborhood),which is capable of rapid assessment of meteorological fields over key urban areas,including wind speed,air temperature,humidity and thermal comfort index,with the execution time less than10 minutes consuming 1 CPU core.URBAN uses a fast wind diagnostic method to construct three-dimensional(3-D)wind fields surrounding complex building clusters with their geometry resolved explicitly.To enhance the accuracy of wind reconstruction and the continuity of the initial wind field around irregular buildings,we propose a new parameterization method based on stream functions,which can accurately characterize the influences of complex urban building clusters on the three-dimensional wind field.The model can provide various results for the meteorological service of large outdoor activities,including conventional meteorological elements(wind,temperature,humidity,radiation,etc.)and the Universal Thermal Comfort Index,which is derived from the relationship between physiological processes and environmental meteorological conditions.In this paper,URBAN is applied to develop an automatic analysis and forecast system of microscale meteorological elements over the central Beijing region in summer during a large outdoor event.By comparing with the half-hourly observations from three auto weather stations(AWSs)in the region,the root-mean-square errors(RMSEs)of the modeled 10-meter-height wind speed,2-meter-height air temperature and humidity are 0.98 m s^(-1),1.37℃and 7.37%,respectively.

Near-Surface Anisotropic Structure Characterization by Love Wave Inversion for Assessing Ground Conditions in Urban Areas

In many geophysical applications, neglecting of anisotropy is somehow an oversimplification. The mismatch between prediction based on isotropic theory and near-surface seismic observations indicates the need for the inclusion of medium anisotropy. In this paper, surface wave（Love wave） dispersion properties are used to estimate the anisotropic structure of the near-surface layered earth, which is modeled as media possess vertical transverse isotropy（VTI）, a reasonable assumption for near-surface sedimentary layers. Our approach utilizes multi-mode surface waves to estimate both the velocity structure and the anisotropy structure. This approach consists of three parts. First, the dispersion analysis is used to extract dispersion curves from real data. Second, the forward modeling is carried out based on the dispersion equation of Love wave in a multi-layered VTI medium. Dispersion curves of multi-modes, which are the numerical solutions of the dispersion equation, are obtained by a graphic-based method. Finally, the very fast simulated annealing（VFSA） algorithm is used to invert velocity structure and anisotropy structure simultaneously. Our approach is verified by the synthetic dispersion curve generated by a VTI medium model. The estimation of shear wave velocity and anisotropy structure of surface wave data acquired at Rentschler Field, an urban center site on sediments in the Connecticut River valley reveals a simple structure of the sediment layer over a bedrock half space. The results are verified by other inversion results based on different data set obtained on the same site. The consistency of inversion results shows the feasibility and efficiency of the approach.