A hybrid approach to detect crack parameters using measured natural frequencies in thin walled angle section steel beams

Present study outlines a hybrid approach using Finite Element Method (FEM)–Response Surface Method (RSM)–Genetic Algorithm (GA) to predict the crack parameters, namely crack position and crack depth ratio with the help of only the measured natural frequencies of cracked thin walled beams. Numerical experimental trials of cracked beams have been conducted based on design of experiment (DOE) approach using an improved Finite element model. The improvement has been achieved by consideration of warping stiffness in cracked angle section beam. Thereafter, regression analysis has been conducted to construct Response Surface Function (RSF). Optimum crack parameters were then calculated using GA by minimizing an objective function which has been formed as the root mean square (RMS) of the residuals between RSFs and measured frequencies. Results of the study indicate that, the proposed approach performs with excellent accuracy and it does not require the response of an uncracked beam as benchmark information.     

Evaluation of solar temperature field under different wind speeds for Shanghai 65 m radio telescope

The Shanghai 65 m radio telescope is currently the largest full range rotatable radio telescope in Asia. Gravity, wind and temperature are the three main factors which may have a bad effect on the reflector’s surface precision. To study the effect of the thermal deformation caused by daily non-uniform temperature fields on the surface precision of the main reflector, both the temperature field and its effect were studied in detail for two typical days (January 15th and July 15th). The method to simulate temperature fields was studied initially, considering heat conduction, solar radiation, shadowing, air convection, sky radiation and ground radiation. Then, an integral parametric thermal finite element model (FEM) of the telescope was established using the ANSYS thermal analysis module. Finally, the effect of non-uniform temperature fields on the surface precision of the main reflector was estimated in terms of the Root Mean Square (RMS) deformation based on temperature transient analysis. The proposed methods and conclusions drawn can provide valuable information for thermal design, thermal monitoring and thermal control of the Shanghai 65 m radio telescope and other similar giant antenna structures.     

Structural optimization of hollow-section steel trusses by differential evolution algorithm

This paper deals with the weight minimization of planar steel trusses by adopting a differential evolution-based algorithm. Square hollow sections are considered. The design optimization refers to size, shape and topology. The design variables are represented by the geometrical dimensions of the cross sections of the different components of the truss, directly involving the size of the structure, and by some geometrical parameters affecting the outer shape of the truss. The topology is included in the optimization search in a particular way, since the designer at different runs of the algorithm can change the number of bays keeping constant the total length of the truss, to successively choose the best optimal solution. The minimum weight optimum design is posed as a single-objective optimization problem subject to constraints formulated in accordance with the current Eurocode 3. The optimal solution is obtained by a Differential Evolutionary (DE) algorithm. In the DE algorithm, a particular combination of mutation and crossover operators is adopted in order to achieve the best solutions and a specific way for dealing with constraints is introduced. The effectiveness of the proposed approach is shown with reference to two case-studies. The analysis results prove the versatility of the optimizer algorithm with regard to the three optimization categories of sizing, shape, topology as well as its high computational performances and its efficacy for practical applications. In particular useful practical indications concerning the geometrical dimensions of the various involved structural elements can be deduced by the optimal solutions: in a truss girder the cross section of the top chord should be bigger than the one of the bottom chord as well as diagonals should be characterized by smaller cross sections with respect to the top and bottom chords in order to simultaneously optimize the weight and ensure an optimal structural behaviour.     

ESMRMB 2017, 34th Annual Scientific Meeting,Barcelona, ES,October 19–October 21: Abstracts,Thursday

Objective

Current magnetic resonance imaging (MRI) axon diameter measurements rely on the pulsed gradient spin-echo sequence, which is unable to provide diffusion times short enough to measure small axon diameters. This study combines the AxCaliber axon diameter fitting method with data generated from Monte Carlo simulations of oscillating gradient spin-echo sequences (OGSE) to infer micron-sized axon diameters, in order to determine the feasibility of using MRI to infer smaller axon diameters in brain tissue.

Materials and methods

Monte Carlo computer simulation data were synthesized from tissue geometries of cylinders of different diameters using a range of gradient frequencies in the cosine OGSE sequence . Data were fitted to the AxCaliber method modified to allow the new pulse sequence. Intra- and extra-axonal water were studied separately and together.

Results

The simulations revealed the extra-axonal model to be problematic. Rather than change the model, we found that restricting the range of gradient frequencies such that the measured apparent diffusion coefficient was constant over that range resulted in more accurate fitted diameters. Thus a careful selection of frequency ranges is needed for the AxCaliber method to correctly model extra-axonal water, or adaptations to the method are needed. This restriction helped reduce the necessary gradient strengths for measurements that could be performed with parameters feasible for a Bruker BG6 gradient set. For these experiments, the simulations inferred diameters as small as 0.5 μm on square-packed and randomly packed cylinders. The accuracy of the inferred diameters was found to be dependent on the signal-to-noise ratio (SNR), with smaller diameters more affected by noise, although all diameter distributions were distinguishable from one another for all SNRs tested.

Conclusion

The results of this study indicate the feasibility of using MRI with OGSE on preclinical scanners to infer small axon diameters.

     

Fitting interrelated datasets: metabolite diffusion and general lineshapes

Objective

Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented.

Materials and methods

Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra. This was implemented together with a simultaneous spectral and diffusion model fitting in the previously described Fitting Tool for Arrays of Interrelated Datasets (FiTAID), where prior knowledge conditions and restraints can be enforced in two dimensions.

Results

The benefit in terms of increased accuracy and precision of parameters is illustrated with examples from Monte Carlo simulations, in vitro and in vivo human brain scans for one- and two-dimensional datasets from 2-D separation, inversion recovery and diffusion-weighted spectroscopy (DWS). For DWS, it was found that acquisitions could be substantially shortened.

Conclusion

It is shown that inclusion of a measured lineshape into modeling of interrelated MR spectra is beneficial and can be combined also with simultaneous spectral and diffusion modeling.

     

Sensitive magnetic field sensor using 2D magnetic photonic crystal slab waveguide based on BIG/GGG structure

A kind of magnetic field sensor (MFS) using a two-dimensional (2D) magnetic photonic crystal (MPC) slab waveguide as the sensing structure is proposed and investigated numerically. The slab structure is based on bismuth iron garnet (BIG), a well-known magnetic material with effective magnetooptical (MO) properties, sandwiched with gadolinium gallium garnet (GGG) as substrate. The complete photonic bandgap (PBG) of the 2D MPC is simulated and optimized for realization of polarization-independent waveguides. The simulation results show that the width and position of the complete PBG depend on the thickness of the BIG slab and the radius of the air holes used in the design. By reducing the lightwave propagation losses and enhancing the mode conversion ratio, increased sensitivity is obtained. Based on the Faraday effect, a good linear relationship is observed between the normalized output light intensity and the magnetic field strength as the gyrotropy parameter g is varied from 0.13 to 0.19, a g-range used as the sensor dynamic range. The remarkable enhancement in sensing performance due to the MO effect makes the designed device suitable for magnetic field sensing. The results are discussed to provide a basis for investigation of 2D MPC slab waveguides based on the same structure, which are of particular interest for development of highly sensitive MFSs.     

基于剩余使用年限的结构生命周期性能设计方法

基于概率理论结构设计的基本目的是使结构在预定的使用期内满足设计所预期的结构可靠性,包括安全性、适用性、耐久性。影响结构可靠性的荷载效应(直接或间接作用引起的结构的各种内力)与结构抗力(指结构承受荷载和变形的能力)因受到各种因素的影响,都是随时间或空间而变动的随机函数。在目前的超高层建筑结构的设计过程中,有关是否需要考虑作用及抗力的时变性能以及如何考虑的规定十分笼统。为了更加明确考虑时变性能在结构设计中的影响,在引入剩余使用年限的基础上提出了基于剩余使用年限的结构生命周期性能设计方法。并以一个超高层建筑为例,阐述了其具体应用,为今后工程中基于时变性能的结构设计提供参考。     

Flow Behavior of SUS304 Stainless Steel Under a Wide Range of Forming Temperatures and Strain Rates

To determine the flow behavior of SUS304 stainless steel under different conditions, axisymmetric compression tests were conducted over a wide range of forming temperatures (25 °C to 400 °C) and strain rates (10⁻³ to 10 s⁻¹). Flow curves were obtained for different forming conditions to study the influence of the forming temperature and strain rate on the flow behavior. Moreover, electron backscatter diffraction analysis, X-ray diffraction analysis, transmission electron microscopy, and Feritscope were used to study the microstructure evolution of SUS304 stainless steel under different conditions for determining the underlying reasons for the variations in flow behavior. The experimental results indicated that the flow stress decreased with increasing the forming temperature. With increasing strain rate at 25 °C to 200 °C, the flow stress first increased and then decreased; however, the strain rate had little effect on the flow stress at 300 °C and 400 °C. By analyzing the variation in the phase transformation inside compressed SUS304 stainless steel samples under different forming conditions, the key factors affecting the flow behavior of stainless steel were identified. Finally, by examining the variation in the martensite content and the dislocation density, the dominant deformation mechanism under different forming conditions was determined.

     

数据融合技术在变压器状态评估中的应用

电力变压器是电力系统及变电站的最至关重要的设备之一。对电力系统进行运行维护时,监测并预报变压器运行状态并且能够有效地监测并判断变压器的故障情况具有非常现实的意义。基于设备状态信息融合技术,分析了D-S证据理论的基本原理、组合规则和决策过程。通过具体的实例论述了诊断方法的具体可行性,比较了单一诊断方法(只经神经网络判断的结果)与信息融合技术的正确率,并指出信息融合技术的发展优势和可实现性。