Modelling of guided wave propagation with spectral element: application in structural engineering

Among many structural health monitoring (SHM) methods, guided wave (GW) based method has been found as an effective and efficient way to detect incipient damages. In comparison with other widely used SHM methods, it can propagate in a relatively long range and be sensitive to small damages. Proper use of this technique requires good knowledge of the effects of damage on the wave characteristics. This needs accurate and computationally efficient modeling of guide wave propagation in structures. A number of different numerical computational techniques have been developed for the analysis of wave propagation in a structure. Among them, Spectral Element Method (SEM) has been proposed as an efficient simulation technique. This paper will focus on the application of GW method and SEM in structural health monitoring. The GW experiments on several typical structures will be introduced first. Then, the modeling techniques by using SEM are discussed. © (2014) Trans Tech Publications, Switzerland.

Development and applications of an experimental database for structural engineering education

A great number of research organisations in Japan have been conducting structural steel experiments for many years, particularly seismic tests of steel structures like cyclic-loading and pseudo-dynamic tests, in order to determine their seismic performances. However, the original test data gained by most research organisations are not well stored in an appropriate manner for distribution and possible usage by others. With the rapid development of information networks, structural engineers and researchers are able to exchange various types of test data through the Internet. In this paper, the authors present the development of a distributed collaborative database system for structural steel experiments. The database is made available on the Internet, and the use of Java language enables efficient interactive retrieval. The potential applications of the developed database system for structural engineering education are validated for the retrieval of experimental data and seismic numerical analysis.

Molecular dynamics simulations of highly concentrated salt solutions : structural and transport effects in polymer electrolytes

Structural, thermodynamic and transport properties have been calculated in concentrated non-aqueous NaI solutions using molecular dynamics simulations. Although the solvent has been represented by a simplistic Stockmayer fluid (spherical particles with point dipoles), the general trends observed are still a useful indication of the behavior of real non-aqueous electrolyte systems. Results indicate that in low dielectric media, significant ion pairing and clustering occurs. Contact ion pairs become more prominent at higher temperatures, independent of the dielectric strength of the solvent. Thermodynamic analysis shows that this temperature behavior is predominantly entropically driven. Calculation of ionic diffusivities and conductivities in the NaI/ether system confirms the clustered nature of the salt, with the conductivities significantly lower than those predicted from the Nernst-Einstein relation. In systems where the solvent-ion interactions increase relative to ion-ion interactions (lower charge or higher solvent dipole moment), less clustering is observed and the transport properties indicate independent motion of the ions, with higher calculated conductivities. The solvent in this system is the most mobile species, in comparison with the polymer electrolytes where the solvent is practically immobile.

An introduction to compressive sensing and its potential applications in structural engineering

The Shannon/Nyquist sampling theorem specifies that to avoid losing information when capturing a signal, one must sample at least two times faster than the signal bandwidth. In order to capture and represent compressible signals at a rate significantly below the Nyquist rate, a new method, called compressive sensing (CS), is therefore proposed. CS theory asserts that one can recover certain signals from far fewer samples or measurements than traditional methods use. It employs non-adaptive linear projections that preserve the structure of the sparse signal; the signal is then reconstructed from these projections using an optimization process. It is believed that CS has far reaching implications, while most publications concentrate on signal processing fields (especially for images). In this paper, we provide a concise introduction of CS and then discuss some of its potential applications in structural engineering. The recorded vibration time history of a steel beam and the wave propagation result on a steel rebar are studied in detail. CS is adopted to reconstruct the time histories by using only parts of the signals. The results under different conditions are compared, which confirm that CS will be a promising tool for structural engineering.

Damage identification of civil infrastructure in the time domain using FEM calibrated ARMAX model

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. First, a high quality finite element model is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then developed and calibrated. The calibrated ARMAX model can be used to identify damage in different scenarios through model updating process using clonal selection algorithm (CSA). The identification results demonstrate the performance of the proposed methodology, which has the potential to be used for damage identification in practices.

Comparisons of seismic rock slope stability assessments between the Hoek-Brown and Mohr-Coulomb failure criteria

Current investigations have shown that earthquakes can trigger significant damages of equipment, property infrastructure and environment. This is a persistent cause of economic loss for any country, especially for the loss of life. The conventional method for slope stability design is to utilize limit equilibrium method (LEM) in conjunction with the pseudo-static (PS) approach. However, the LEM has a significant drawback which is to determine the slip surface before factor of safety calculation. The numerical upper and lower bound limit analysis method employed in this paper can avoid this limitation. In this study, the presented slope stability evaluations considering earthquake effects based on the finite difference method will be discussed and compared with the results from the numerical limit analysis methods.

FEM calibrated ARMAX model updating method for time domain damage identification

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. To do this, a finite element model of a steel pipe laid on the soil is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then built and calibrated. The calibrated ARMAX model is used to identify different damage scenarios through model updating process using clonal selection algorithm (CSA). The results demonstrate the application potential of the proposed method in identifying the pipeline conditions. To further verify its performance, laboratory tests of a steel pipe laid on the soil with and without soil support (free span damage) are carried out. The identification results of pipe-soil system show that the proposed method is capable of identifying damagein a complex structural system. Therefore, it can be applied to identifying pipeline conditions.

Finite element model updating using estimation of distribution algorithm

Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable.

Organisational downsizing and knowledge sharing

Organisational downsizing has proven a popular strategic intervention in the new globalised competitive business environment. Yet surprisingly little research has been conducted in the knowledge management domain to help scholars and managers better understand the effects of downsizing on organisational knowledge sharing. This paper reports some of the key findings from an interpretive investigation of organisational knowledge sharing in a division of large Australian organisation where downsizing had recently taken place. The findings reveal structural and cultural effects stemming from downsizing, and shows how these effects influenced knowledge sharing. The paper provides sets of knowledge-based impacts of downsizing on (1) organisational structure and (2) organisational culture at the case organisation. Important implications for knowledge management research and practice are discussed.

Damage identification scheme based on compressive sensing

Civil infrastructures are critical to every nation, due to their substantial investment, long service period, and enormous negative impacts after failure. However, they inevitably deteriorate during their service lives. Therefore, methods capable of assessing conditions and identifying damage in a structure timely and accurately have drawn increasing attention. Recently, compressive sensing (CS), a significant breakthrough in signal processing, has been proposed to capture and represent compressible signals at a rate significantly below the traditional Nyquist rate. Due to its sound theoretical background and notable influence, this methodology has been successfully applied in many research areas. In order to explore its application in structural damage identification, a new CS-based damage identification scheme is proposed in this paper, by regarding damage identification problems as pattern classification problems. The time domain structural responses are transferred to the frequency domain as sparse representation, and then the numerical simulated data under various damage scenarios will be used to train a feature matrix as input information. This matrix can be used for damage identification through an optimization process. This will be one of the first few applications of this advanced technique to structural engineering areas. In order to demonstrate its effectiveness, numerical simulation results on a complex pipe soil interaction model are used to train the parameters and then to identify the simulated pipe degradation damage and free-spanning damage. To further demonstrate the method, vibration tests of a steel pipe laid on the ground are carried out. The measured acceleration time histories are used for damage identification. Both numerical and experimental verification results confirm that the proposed damage identification scheme will be a promising tool for structural health monitoring.