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.     

On the use of the RMR system for estimation of rock mass deformation modulus

Estimation of rock mass deformation modulus is the subject of many studies in rock engineering research work. Although numerous predictive models have been developed for the estimation of the deformation modulus, they cannot be generalized for other sites because of inadequate accuracy. Furthermore, it is very valuable that the predictive models involve some accessible input parameters. The rock mass rating (RMR) is a well-known geomechanical parameter, which is usually determined to describe the quality of rock mass in rock engineering projects. In this study, five parameter ratings of the RMR classification system are used to predict the deformation modulus of rock mass in the abutment of the Gotvand earth dam. Statistical analysis and an artificial neural network are employed to present two new predictive models. Finally, probabilistic analysis is used to predict the rock mass deformation modulus, which overcomes the low accuracy caused by the inherent uncertainty in prediction. The results indicated that the parameter ratings used in the RMR classification system can predict the rock mass deformation modulus with a satisfactory correlation. However, the parameters don’t have the same influence on the rock mass deformability with the joint condition and the groundwater as the major and minor influencing parameters, respectively.     

Design and manufacture of high-filling-efficiency microfluidic devices

In this study, we proposed an efficient method for mass production of high-filling-efficiency microfluidic devices. Precision machining was the main process of device fabrication. The commercially available SolidWorks software was adopted for structure design. Unigraphics software was then used to simulate the machining process. The simulated tooling file was then loaded into a CNC milling machine for mold production. The fabricated metal mold was used for pouring polydimethylsiloxane (PDMS) to obtain high-filling-efficiency microfluidic structures. Finally, plasma-assisted packaging was conducted to tightly bind the PDMS microfluidic structure to the glass substrate. Experimental results showed that the additional semicircular filling structure and expended fill-entry structure can efficiently enhance filling efficiency of the microchannel device. The incubation well array can be completely filled at a relatively short filling time. The proposed highly efficient filling microfluidic device possesses advantages, such as feasibility for mass production and cost effectiveness.