Health monitoring of short-and medium-spen bridges using an improved modal strain energy method

Increasing the importance and use of infrastructures such as bridges, demands more effective structural health monitoring (SHM) systems. SHM has well addressed the damage detection issues through several methods such as modal strain energy (MSE). Many of the available MSE methods either have been validated for limited type of structures such as beams or their performance is not satisfactory. Therefore, it requires a further improvement and validation of them for different types of structures. In this study, an MSE method was mathematically improved to precisely quantify the structural damage at an early stage of formation. Initially, the MSE equation was accurately formulated considering the damaged stiffness and then it was used for derivation of a more accurate sensitivity matrix. Verification of the improved method was done through two plane structures: a steel truss bridge and a concrete frame bridge models that demonstrate the framework of a short- and medium-span of bridge samples. Two damage scenarios including single- and multiple-damage were considered to occur in each structure. Then, for each structure, both intact and damaged, modal analysis was performed using STRAND7. Effects of up to 5 per cent noise were also comprised. The simulated mode shapes and natural frequencies derived were then imported to a MATLAB code. The results indicate that the improved method converges fast and performs well in agreement with numerical assumptions with few computational cycles. In presence of some noise level, it performs quite well too. The findings of this study can be numerically extended to 2D infrastructures particularly short- and medium-span bridges to detect the damage and quantify it more accurately. The method is capable of providing a proper SHM that facilitates timely maintenance of bridges to minimise the possible loss of lives and properties.

A simple method for EPID-based in vivo dosimetry for radiotherapy treatments of head-and-neck cancers

This study used a homogeneous water-equivalent model of an electronic portal imaging device (EPID), contoured as a structure in a radiotherapy treatment plan, to produce reference dose images for comparison with in vivo EPID dosimetry images. Head and neck treatments were chosen as the focus of this study, due to the heterogeneous anatomies involved and the consequent difficulty of rapidly obtaining reliable reference dose images by other means. A phantom approximating the size and heterogeneity of a typical neck, with a maximum radiological thickness of 8.5 cm, was constructed for use in this study. This phantom was CT scanned and a simple treatment including five square test fields and one off-axis IMRT field was planned. In order to allow the treatment planning system to calculate dose in a model EPID positioned a distance downstream from the phantom to achieve a source-to-detector distance (SDD) of 150 cm, the CT images were padded with air and the phantom’s “body” contour was extended to encompass the EPID contour. Comparison of dose images obtained from treatment planning calculations and experimental irradiations showed good agreement, with more than 90% of points in all fields passing a gamma evaluation, at γ (3%, 3mm )Similar agreement was achieved when the phantom was over-written with air in the treatment plan and removed from the experimental beam, suggesting that water EPID model at 150 cm SDD is capable of providing accurate reference images for comparison with clinical IMRT treatment images, for patient anatomies with radiological thicknesses ranging from 0 up to approximately 9 cm. This methodology therefore has the potential to be used for in vivo dosimetry during treatments to tissues in the neck as well as the oral and nasal cavities, in the head-and-neck region.

Ozonolysis of phospholipid double bonds during electrospray ionization : A new tool for structure determination

Phospholipids are the key structural component of cell membranes, and recent advances in electrospray ionization mass spectrometry provide for the fast and efficient analysis of these compounds in biological extracts.1-3 The application of electrospray ionization tandem mass spectrometry (ESI-MS/MS) to phospholipid analysis has demonstrated several key advantages over the more traditional chromatographic methods, including speed and greater structural information.4 For example, the ESI-MS/MS spectrum of a typical phospholipidsparticularly in negative ion modesreadily identifies the carbon chain length and the degree of unsaturation of each of the fatty acids esterified to the parent molecule.5 A critical limitation of conventional ESI-MS/MS analysis, however, is the inability to uniquely identify the position of double bonds within the fatty acid chains. This is especially problematic given the importance of double bond position in determining the biological function of lipid classes.6 Previous attempts to identify double bond position in intact phospholipids using mass spectrometry employ either MS3 or offline chemical derivatization.7-11 The former method requires specialized instrumentation and is rarely applied, while the latter methods suffer from complications inherent in sample handling prior to analysis. In this communication we outline a novel on-line approach for the identification of double bond position in intact phospholipids. In our method, the double bond(s) present in unsaturated phospholipids are cleaved by ozonolysis within the ion source of a conventional ESI mass spectrometer to give two chemically induced fragment ions that may be used to unambiguously assign the position of the double bond. This is achieved by using oxygen as the electrospray nebulizing gas in combination with high electrospray voltages to initiate the formation of an ozoneproducing.

Damping structure selection in nonlinear ship manoeuvring models

This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.

A Combined Renormalization Group-Multiple Scale Method for Singularly Perturbed Problems

This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

Structure-controlled, vertical graphene-based, binder-free electrodes from plasma-reformed butter enhance supercapacitor performance

Vertical graphene nanosheets (VGNS) hold great promise for high-performance supercapacitors owing to their excellent electrical transport property, large surface area and in particular, an inherent three-dimensional, open network structure. However, it remains challenging to materialise the VGNS-based supercapacitors due to their poor specific capacitance, high temperature processing, poor binding to electrode support materials, uncontrollable microstructure, and non-cost effective way of fabrication. Here we use a single-step, fast, scalable, and environmentally-benign plasma-enabled method to fabricate VGNS using cheap and spreadable natural fatty precursor butter, and demonstrate the controllability over the degree of graphitization and the density of VGNS edge planes. Our VGNS employed as binder-free supercapacitor electrodes exhibit high specific capacitance up to 230 F g−1 at a scan rate of 10 mV s−1 and >99% capacitance retention after 1,500 charge-discharge cycles at a high current density, when the optimum combination of graphitic structure and edge plane effects is utilised. The energy storage performance can be further enhanced by forming stable hybrid MnO2/VGNS nano-architectures which synergistically combine the advantages from both VGNS and MnO2. This deterministic and plasma-unique way of fabricating VGNS may open a new avenue for producing functional nanomaterials for advanced energy storage devices.

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

A micro-level investigation of the solid displacement method for porosity determination of dried food

Porosity is one of the key parameters of the macroscopic structure of porous media, generally defined as the ratio of the free spaces occupied (by the volume of air) within the material to the total volume of the material. Porosity is determined by measuring skeletal volume and the envelope volume. Solid displacement method is one of the inexpensive and easy methods to determine the envelope volume of a sample with an irregular shape. In this method, generally glass beads are used as a solid due to their uniform size, compactness and fluidity properties. The smaller size of the glass beads means that they enter into the open pores which have a larger diameter than the glass beads. Although extensive research has been carried out on porosity determination using displacement method, no study exists which adequately reports micro-level observation of the sample during measurement. This study set out with the aim of assessing the accuracy of solid displacement method of bulk density measurement of dried foods by micro-level observation. Solid displacement method of porosity determination was conducted using a cylindrical vial (cylindrical plastic container) and 57 µm glass beads in order to measure the bulk density of apple slices at different moisture contents. A scanning electron microscope (SEM), a profilometer and ImageJ software were used to investigate the penetration of glass beads into the surface pores during the determination of the porosity of dried food. A helium pycnometer was used to measure the particle density of the sample. Results show that a significant number of pores were large enough to allow the glass beads to enter into the pores, thereby causing some erroneous results. It was also found that coating the dried sample with appropriate coating material prior to measurement can resolve this problem.

An improved modal strain energy method for structural damage detection, 2D simulation

Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.

An improved computational method in structural dynamics

Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.

Tailoring surface properties and structure of layered double hydroxides using silanes with different number of functional groups

Four silanes, trimethylchlorosilane (TMCS), dimethyldiethoxylsilane (DMDES), 3-aminopropyltriethoxysilane (APTES) and tetraethoxysilane (TEOS), were adopted to graft layered double hydroxides (LDH) via an induced hydrolysis silylation method (IHS). Fourier transform infrared spectra (FTIR) and 29Si MAS nuclear magnetic resonance spectra (29Si MAS NMR) indicated that APTES and TEOS can be grafted onto LDH surfaces via condensation with hydroxyl groups of LDH, while TMCS and DMDES could only be adsorbed on the LDH surface with a small quantity. A combination of X-ray diffraction patterns (XRD) and 29Si MAS NMR spectra showed that silanes were exclusively present in the external surface and had little influence on the long range order of LDH. The surfactant intercalation experiment indicated that the adsorbed and/or grafted silane could not fix the interlamellar spacing of the LDH. However, they will form crosslink between the particles and affect the further surfactant intercalation in the silylated samples. The replacement of water by ethanol in the tactoids and/or aggregations and the polysiloxane oligomers formed during silylation procedure can dramatically increase the value of BET surface area (SBET) and total pore volumes (Vp) of the products.

The molecular structure of chloritoid: A mid-infrared and near-infrared spectroscopic study

The mineral chloritoid collected from the argillite in the bottom of Yaopo Formation of Western Beijing was characterized by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. The MIR spectra showed all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and the influence of iron on the chloritoid structure. The NIR spectrum of the chloritoid showed combination (ν + δ)OH bands with the fundamental stretching (ν) and bending (δ) vibrations. Based on the chemical component data and the analysis result from the MIR and NIR spectra, the crystal structure of chloritoid from western hills of Beijing, China, can be illustrated. Therefore, the application of the technique across the entire infrared region is expected to become more routine and extend its usefulness, and the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for the unit cell structural analysis.

Versatile single-layer sodium phosphidostannate(II): Strain-tunable electronic structure, excellent mechanical flexibility, and an ideal gap for photovoltaics

Density functional theory (DFT) calculations were performed to study the structural, mechanical, electrical, optical properties, and strain effects in single-layer sodium phosphidostannate(II) (NaSnP). We find the exfoliation of single-layer NaSnP from bulk form is highly feasible because the cleavage energy is comparable to graphite and MoS2. In addition, the breaking strain of the NaSnP monolayer is comparable to other widely studied 2D materials, indicating excellent mechanical flexibility of 2D NaSnP. Using the hybrid functional method, the calculated band gap of single-layer NaSnP is close to the ideal band gap of solar cell materials (1.5 eV), demonstrating great potential in future photovoltaic application. Furthermore, strain effect study shows that a moderate compression (2%) can trigger indirect-to-direct gap transition, which would enhance the ability of light absorption for the NaSnP monolayer. With sufficient compression (8%), the single-layer NaSnP can be tuned from semiconductor to metal, suggesting great applications in nanoelectronic devices based on strain engineering techniques.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.