Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

中国古生教授学会微体古生物学分会举行代表大会和学术年会

中国古生教授学会微体古生物学分会举行代表大会和学术年会中国古竽物学会微体古物学分会第五次会员代表大分暨第六次不术年会于１９９６年１月２４日到３０日在福州市召开。来自全国地质、石油、煤炭的和产、科研和大学的１００多位代表参加了这次大会和学术研讨。大会共...     

Simulations of multimode bolometric interferometers

We describe a procedure for the numerical modelling of astronomical interferometers, with particular relevance to far-infrared and submillimetre wavelengths. The scheme is based on identifying a set of modes that carry power from the sky to the detector. The procedure is extremely general, and can be used to model scalar or vector fields, in any state of coherence and polarization, the only limitation being that the propagation of a coherent field through the system be described by an integral transform, a constraint that is in practise always met.
We present simulations of ideal, multimode two-dimensional interferometers, and show that the modal theory reproduces the correct behaviour of both Michelson and Fizeau interferometers. We calculate simulated visibility data for a multimode bolometric Michelson interferometer, with a synthesized source, and produce a dirty map, recovering the original source with the usual artefacts associated with interferometers.     

Wavelet Analysis of Space Solar Telescope Images

The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

An efficient technique for pre-selecting low-redshift damped Lyα systems

The number of z ∼ 1 damped Lyα systems (DLAs, log  N (H  i ) ≥ 20.3) per unit redshift is approximately 0.1, making them relatively rare objects. Large, blind QSO surveys for low-redshift DLAs are therefore an expensive prospect for space-borne ultraviolet telescopes. Increasing the efficiency of these surveys by pre-selecting DLA candidates based on the equivalent widths (EWs) of metal absorption lines has previously been a successful strategy. However, the success rate of DLA identification is still only ∼35 per cent when simple EW cut-offs are applied, the majority of systems having 19.0 < log  N (H  i ) < 20.3. Here, we propose a new way to pre-select DLA candidates. Our technique requires high-to-moderate-resolution spectroscopy of the Mg  ii λ2796 transition, which is easily accessible from the ground for 0.2 ≲ z ≲ 2.4. We define the D -index, the ratio of the line equivalent width to velocity spread, and measure this quantity for 19 DLAs and eight sub-DLAs in archival spectra obtained with echelle spectrographs. For the majority of absorbers, there is a clear distinction between the D -index of DLAs compared with sub-DLAs (Kolmogorov–Smirnov probability = 0.8 per cent). Based on this pilot data sample, we find that the D -index can select DLAs with a success rate of up to 90 per cent, an increase in selection efficiency by a factor of 2.5 compared with a simple EW cut. We test the applicability of the D -index at lower resolution and find that it remains a good discriminant of DLAs for full width at half-maximum (FWHM) ≲ 1.5 Å. However, the recommended D -index cut-off between DLAs and sub-DLAs decreases with poorer resolution and we tabulate the appropriate D -index values that should be used with spectra of different resolutions.