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.     

常村矿巷道前方地质构造MTRT法超前探测技术应用研究

MTRT技术作为一种先进的超前探测井下地质构造的物探方法,通过采用左帮、右帮、顶板三维观测系统,数据处理采用速度扫描和偏移成像技术,对巷道前方地质构造识别的准确度较高。通过在常村矿对MTRT技术的多次应用,并进行探掘对比资料分析,证实了该方法在实际探测中准确率较高,能为巷道掘进提供更有效的技术依据。     

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。     

吸附模式及固结变形对溶质运移规律的影响研究

目前关于溶质在变形土体中运移规律的研究相对较少,但是荷载作用又是实际工程中必须考虑的因素。基于比奥固结理论和溶质运移理论,建立渗流场、应力场和浓度场耦合的溶质运移模型,并采用有限差分法对溶质在变形土体中的运移规律进行研究。此外,许多学者在研究溶质运移规律时,多数情况下采用线性吸附模式,但是细粒土对金属离子、有机物或者高浓度溶质的吸附多表现出较强的非线性,因此研究了不同吸附模式作用下溶质的运移规律。研究结果表明,固结变形对溶质的运移过程具有持久性的阻滞作用,导致了溶质运移深度的减小;吸附模式对溶质运移规律没有本质的影响,但是吸附模式对溶质运移的快慢有较大影响,并且随着运移时间的增加,吸附模式对溶质运移快慢的影响不断增大。     

试论土木工程中建筑节能措施的应用

我国民用建筑节能措施的推广已经经历了将近20个年头,实践中却仍然存在很多问题。本文就对土木工程建筑中节能措施的重要性以及如何有效开展节能工作进行了分析。