Seismic capacity of building constructed in slip formed load bearing wall panels

Constructing buildings using slip formed load bearing wall panels is becoming increasingly popular in Sri Lanka due to several advantages; low cost, environmental friendliness and rapid construction technique. These wall panels are already successfully implemented in many low rise buildings. However, the seismic capacities of these buildings have not been properly studied. Few seismic activities reported in Sri Lanka have not caused severe structural damage, but predictions can not be made as to whether this will continue to be the case in the future. This highlights the need to study the seismic capacity of buildings constructed in slip formed load bearing wall panels. This paper presents a study of the seismic capacity of the existing medium rise building.

Variation in leaf structure of the invasive Madeira vine (Anredera cordifolia, Basellaceae) at different light levels

Madeira vine (Anredera cordifolia (Ten.) Steenis) is a climber in the angiosperm family Basellaceae. It is native to South America and has naturalised in Australia. It is regarded as a serious environmental weed because of the structural damage it causes to native vegetation. The present study, for the first time, documents anatomical and morphological traits of the leaves of A. cordifolia and considers their implications for its ecology and physiology. Plants were grown under three different light levels, and anatomical and morphological leaf characters were compared among light levels, among cohorts, and with documented traits of the related species, Basella alba L. Stomata were present on both the adaxial and abaxial sides of the leaf, with significantly more stomata on the abaxial side and under high light. This may account for the ability of this species to fix large amounts of carbon and rapidly respond to light gaps. The leaves had very narrow veins and no sclerenchyma, suggesting a low construction cost that is associated with invasive plants. There was no significant difference in any of the traits among different cohorts, which agrees with the claim that A. cordifolia primarily propagates vegetatively. The anatomy and morphology of A. cordifolia was similar to that of B. alba.

Social media and journalism during times of crisis

Around lunchtime on 22 February 2011, the New Zealand city of Christchurch – the country’s second largest city – was hit by a magnitude 6.3 earthquake. Built on a geological faultline, like Los Angeles and Tokyo, Christchurch is no stranger to tremors; indeed, it had experienced a magnitude 7.1 quake just months before, in September 2010, and technically, this new earthquake was no more than an aftershock of the earlier tremor. That earlier quake had caused significant structural damage, but no fatalities, but the February earthquake was different: with its epicentre located no more than ten kilometres from the Christchurch city centre, at a depth of only five kilometres, it proved considerably more destructive – and it affected buildings whose structural integrity had already been severely compromised by the September quake, in the middle of a weekday when schools and city offices would have been fully occupied. While the full death toll has yet to be determined, it is estimated at close to 200.

A novel route in bone tissue engineering : magnetic biomimetic scaffolds

In recent years, interest in tissue engineering and its solutions has increased considerably. In particular, scaffolds have become fundamental tools in bone graft substitution and are used in combination with a variety of bio-agents. However, a long-standing problem in the use of these conventional scaffolds lies in the impossibility of re-loading the scaffold with the bio-agents after implantation. This work introduces the magnetic scaffold as a conceptually new solution. The magnetic scaffold is able, via magnetic driving, to attract and take up in vivo growth factors, stem cells or other bio-agents bound to magnetic particles. The authors succeeded in developing a simple and inexpensive technique able to transform standard commercial scaffolds made of hydroxyapatite and collagen in magnetic scaffolds. This innovative process involves dip-coating of the scaffolds in aqueous ferrofluids containing iron oxide nanoparticles coated with various biopolymers. After dip-coating, the nanoparticles are integrated into the structure of the scaffolds, providing the latter with magnetization values as high as 15 emu g�1 at 10 kOe. These values are suitable for generating magnetic gradients, enabling magnetic guiding in the vicinity and inside the scaffold. The magnetic scaffolds do not suffer from any structural damage during the process, maintaining their specific porosity and shape. Moreover, they do not release magnetic particles under a constant flow of simulated body fluids over a period of 8 days. Finally, preliminary studies indicate the ability of the magnetic scaffolds to support adhesion and proliferation of human bone marrow stem cells in vitro. Hence, this new type of scaffold is a valuable candidate for tissue engineering applications, featuring a novel magnetic guiding option.

Intervertebral staple grading system with micro-CT

Introduction Intervertebral stapling is a leading method of fusionless scoliosis treatment which attempts to control growth by applying pressure to the convex side of a scoliotic curve in accordance with the Hueter-Volkmann principle. In addition to that, staples have the potential to damage surrounding bone during insertion and subsequent loading. The aim of this study was to assess the extent of bony structural damage including epiphyseal injury as a result of intervertebral stapling using an in vitro bovine model. Materials and Methods Thoracic spines from 6-8 week old calves were dissected and divided into motion segments including levels T4-T11 (n=14). Each segment was potted in polymethylemethacrylate. An Instron Biaxial materials testing machine with a custom made jig was used for testing. The segments were tested in flexion/extension, lateral bending and axial rotation at 37⁰C and 100% humidity, using moment control to a maximum 1.75 Nm with a loading rate of 0.3 Nm per second for 10 cycles. The segments were initially tested uninstrumented with data collected from the tenth load cycle. Next an anterolateral 4-prong Shape Memory Alloy (SMA) staple (Medtronic Sofamor Danek, USA) was inserted into each segment. Biomechanical testing was repeated as before. The staples were cut in half with a diamond saw and carefully removed. Micro-CT scans were performed and sagittal, transverse and coronal reformatted images were produced using ImageJ (NIH, USA).The specimens were divided into 3 grades (0, 1 and 2) according to the number of epiphyses damaged by the staple prongs. Results: There were 9 (65%) segments with grade 1 staple insertions and 5 (35%) segments with grade 2 insertions. There were no grade 0 staples. Grade 2 spines had a higher stiffness level than grade 1 spines, in all axes of movement, by 28% (p=0.004). This was most noted in flexion/extension with an increase of 49% (p=0.042), followed by non-significant change in lateral bending 19% (p=0.129) and axial rotation 8% (p=0.456) stiffness. The cross sectional area of bone destruction from the prongs was only 0.4% larger in the grade 2 group compared to the grade 1 group (p=0.961). Conclusion Intervertebral staples cause epiphyseal damage. There is a difference in stiffness between grade 1 and grade 2 staple insertion segments in flexion/extension only. There is no difference in the cross section of bone destruction as a result of prong insertion and segment motion.

Post-fire mechanical properties of cold-formed steels

Cold-formed steel members have been widely used in residential, industrial and commercial buildings as primary load-bearing and non-load bearing structural elements. These buildings must be properly evaluated after a fire event to assess the nature and extent of structural damage. If the general appearance of the structure is satisfactory after a fire event then the question that has to be answered is how the structural capacity of cold-formed steel members in these buildings has been affected. Elevated temperatures during a fire event affect the structural performance of cold-formed steel members even after cooling down to ambient temperature due to the possible detrimental changes in their mechanical properties. However, the post-fire behaviour of cold-formed steel members has not been investigated in the past and hence there is a need to investigate the post-fire mechanical properties of cold-formed steels. Therefore an experimental study was undertaken at the Queensland University of Technology to understand the residual mechanical properties of cold-formed steels after fire events. Tensile coupon tests were conducted on three different steel grades and thicknesses to obtain their stress-strain curves and relevant mechanical properties after cooling them down from different elevated temperatures. It was found that the post-fire mechanical properties of cold-formed steels are different to the original ambient temperature mechanical properties. Hence a new set of equations is proposed to predict the reduced mechanical properties of cold-formed steels after a fire event.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Structural health monitoring of bridges using acoustic emission technology

Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Evaluation of strain energy based damage indices for flexural crack detection of RC beams

Vibration Based Damage Identification Techniques which use modal data or their functions, have received significant research interest in recent years due to their ability to detect damage in structures and hence contribute towards the safety of the structures. In this context, Strain Energy Based Damage Indices (SEDIs), based on modal strain energy, have been successful in localising damage in structuers made of homogeneous materials such as steel. However, their application to reinforced concrete (RC) structures needs further investigation due to the significant difference in the prominent damage type, the flexural crack. The work reported in this paper is an integral part of a comprehensive research program to develop and apply effective strain energy based damage indices to assess damage in reinforced concrete flexural members. This research program established (i) a suitable flexural crack simulation technique, (ii) four improved SEDI's and (iii) programmable sequentional steps to minimise effects of noise. This paper evaluates and ranks the four newly developed SEDIs and existing seven SEDIs for their ability to detect and localise flexural cracks in RC beams. Based on the results of the evaluations, it recommends the SEDIs for use with single and multiple vibration modes.

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.