Numerical modelling of load bearing light gauge steel frame wall systems exposed to realistic design fires

Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Conventionally the fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve in ISO834 [1]. However, modern commercial and residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the fire performance of LSF walls was undertaken using realistic design fire curves developed based on Eurocode parametric [2] and Barnett’s BFD [3] curves using both full scale fire tests and numerical studies. It included LSF walls without cavity insulation, and the recently developed externally insulated composite panel system. This paper presents the details of finite element models developed to simulate the full scale fire tests of LSF wall panels under realistic design fires. Finite element models of LSF walls exposed to realistic design fires were developed, and analysed under both transient and steady state fire conditions using the measured stud time-temperature curves. Transient state analyses were performed to simulate fire test conditions while steady state analyses were performed to obtain the load ratio versus time and failure temperature curves of LSF walls. Details of the developed finite element models and the results including the axial deformation and lateral deflection versus time curves, and the stud failure modes and times are presented in this paper. Comparison with fire test results demonstrate the ability of developed finite element models to predict the performance and fire resistance ratings of LSF walls under realistic design fires.

Rodent Scope: A User-Configurable Digital Wireless Telemetry System for Freely Behaving Animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

Fault detection of slow speed rolling element bearing with noise removal techniques

Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.

Human lens lipids differ markedly from those of commonly used experimental animals

Electrospray ionisation tandem mass spectrometry has allowed the unambiguous identification and quantification of individual lens phospholipids in human and six animal models. Using this approach ca. 100 unique phospholipids have been characterised. Parallel analysis of the same lens extracts by a novel direct-insertion electron-ionization technique found the cholesterol content of human lenses to be significantly higher (ca. 6 times) than lenses from the other animals. The most abundant phospholipids in all the lenses examined were choline-containing phospholipids. In rat, mouse, sheep, cow, pig and chicken, these were present largely as phosphatidylcholines, in contrast 66% of the total phospholipid in Homo sapiens was sphingomyelin, with the most abundant being dihydrosphingomyelins, in particular SM(d18:0/16:0) and SM(d18:0/24:1). The abundant glycerophospholipids within human lenses were found to be predominantly phosphatidylethanolamines and phosphatidylserines with surprisingly high concentrations of ether-linked alkyl chains identified in both classes. This study is the first to identify the phospholipid class (head-group) and assign the constituent fatty acid(s) for each lipid molecule and to quantify individual lens phospholipids using internal standards. These data clearly indicate marked differences in the membrane lipid composition of the human lens compared to commonly used animal models and thus predict a significant variation in the membrane properties of human lens fibre cells compared to those of other animals. © 2008 Elsevier B.V. All rights reserved.

Fire performance and design of load bearing light gauge steel frame wall systems exposed to realistic design fires

This paper presents the fire performance results of light gauge steel frame (LSF) walls lined with single and double plasterboards, and externally insulated with rock fibre insulation as obtained using a finite element analysis based parametric study. A validated numerical model was used to study the influence of various fire curves developed for a range of compartment characteristics. Data from the parametric study was utilized to develop a simplified method to predict the fire resistance ratings of LSF walls exposed to realistic design fire curves. Further, this paper also presents the details of suitable fire design rules based on current cold-formed steel standards and the modifications proposed by previous researchers. Of these the recently developed design rules by Gunalan and Mahendran [1] were investigated to determine their applicability to predict the axial compression strengths and fire resistance ratings (FRR) of LSF walls exposed to realistic design fires. Finally, the stud failure times obtained from fire design rules and finite element studies were compared for LSF walls lined with single and double plasterboards, and externally insulated with rock fibres under realistic design fire curves.

Fusiform activation to animals is driven by the process, not the stimulus

Previous studies have found that the lateral posterior fusiform gyri respond more robustly to pictures of animals than pictures of manmade objects and suggested that these regions encode the visual properties characteristic of animals. We suggest that such effects actually reflect processing demands arising when items with similar representations must be finely discriminated. In a positron emission tomography (PET) study of category verification with colored photographs of animals and vehicles, there was robust animal-specific activation in the lateral posterior fusiform gyri when stimuli were categorized at an intermediate level of specificity (e.g., dog or car). However, when the same photographs were categorized at a more specific level (e.g., Labrador or BMW), these regions responded equally strongly to animals and vehicles. We conclude that the lateral posterior fusiform does not encode domain-specific representations of animals or visual properties characteristic of animals. Instead, these regions are strongly activated whenever an item must be discriminated from many close visual or semantic competitors. Apparent category effects arise because, at an intermediate level of specificity, animals have more visual and semantic competitors than do artifacts.

An experimental based assessment of the deviation of the bearing characteristic frequencies

Slippage in the contact roller-races has always played a central role in the field of diagnostics of rolling element bearings. Due to this phenomenon, vibrations triggered by a localized damage are not strictly periodic and therefore not detectable by means of common spectral functions as power spectral density or discrete Fourier transform. Due to the strong second order cyclostationary component, characterizing these signals, techniques such as cyclic coherence, its integrated form and square envelope spectrum have proven to be effective in a wide range of applications. An expert user can easily identify a damage and its location within the bearing components by looking for particular patterns of peaks in the output of the selected cyclostationary tool. These peaks will be found in the neighborhood of specific frequencies, that can be calculated in advance as functions of the geometrical features of the bearing itself. Unfortunately the non-periodicity of the vibration signal is not the only consequence of the slippage: often it also involves a displacement of the damage characteristic peaks from the theoretically expected frequencies. This issue becomes particularly important in the attempt to develop highly automated algorithms for bearing damage recognition, and, in order to correctly set thresholds and tolerances, a quantitative description of the magnitude of the above mentioned deviations is needed. This paper is aimed at identifying the dependency of the deviations on the different operating conditions. This has been possible thanks to an extended experimental activity performed on a full scale bearing test rig, able to reproduce realistically the operating and environmental conditions typical of an industrial high power electric motor and gearbox. The importance of load will be investigated in detail for different bearing damages. Finally some guidelines on how to cope with such deviations will be given, accordingly to the expertise obtained in the experimental activity.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

A vibrational spectroscopic study of the copper bearing silicate mineral luddenite

The molecular structure of the copper–lead silicate mineral luddenite has been analysed using vibrational spectroscopy. The mineral is only one of many silicate minerals containing copper. The intense Raman band at 978 cm−1 is assigned to the ν1 (A1g) symmetric stretching vibration of Si5O14 units. Raman bands at 1122, 1148 and 1160 cm−1 are attributed to the ν3 SiO4 antisymmetric stretching vibrations. The bands in the 678–799 cm−1 are assigned to OSiO bending modes of the (SiO3)n chains. Raman bands at 3317 and 3329 cm−1 are attributed to water stretching bands. Bands at 3595 and 3629 cm−1 are associated with the stretching vibrations of hydroxyl units suggesting that hydroxyl units exist in the structure of luddenite.

Distribution of methylene chloride in human blood

Methylene chloride (dichloromethane) is widely used as a solvent for stripping of paint, as industrial cleaning agent, for coating of pills in the pharmaceutical industry, and in the decaffeination of coffee. There is “sufficient evidence for the carcinogenicity” of methylene chloride in animals and “inadequate evidence for its carcinogenity in humans”, according to IARC (IARC 1987; CEC 1990).

Species differences in acrylonitrile metabolism and toxicity between experimental animals and humans based on observations in human accidental poisonings

The high acute toxicity of acrylonitrile may be a result of its intrinsic biological reactivity or of its metabolite cyanide. Intravenous N-acetylcysteine has been recommended for treatment of accidental intoxications in acrylonitrile workers, but such recommendations vary internationally. Acrylonitrile is metabolized in humans and experimental animals via two competing pathways; the glutathione-dependent pathway is considered to represent an avenue of detoxication whilst the oxidative pathway leads to a genotoxic epoxide, cyanoethylene oxide, and to elimination of cyanide. Cases of acute acrylonitrile overexposure or intoxication have occurred within persons having industrial contact with acrylonitrile; the route of exposure was by inhalation and/or by skin contact. The combined observations lead to the conclusion of a much higher impact of the oxidative metabolism of acrylonitrile in humans than in rodents. This is confirmed by differences in the clinical picture of acute life-threatening intoxications in both species, as well as by differential efficacies of antidotes. A combination of N-acetylcysteine with sodium thiosulfate seems an appropriate measure for antidote therapy of acute acrylonitrile intoxications. Clinical observations also highlight the practical importance of human individual susceptibility differences. Furthermore, differential adduct monitoring, assessing protein adducts with different rates of decay, enables the development of more elaborated biological monitoring strategies for the surveillance of workers with potential acrylonitrile contact.

Experimental study of load-bearing cold-formed steel walls exposed to realistic design fires

This paper presents the details of full scale fire tests of LSF wall panels conducted using realistic fire time-temperature curves. Tests included eight LSF wall specimens of various configurations exposed to both parametric design and natural fire curves. Details of the fire test set-up, test procedure and the results including the measured time-temperature and deformation curves of LSF wall panels are presented along with wall stud failure modes and times. This paper also compares the structural and thermal behavioural characteristics of LSF wall studs with those based on the standard time-temperature curve. Finally, the stud failure times and temperatures are summarized for both standard and realistic design fire curves. This study provides the necessary test data to validate the numerical models of LSF wall panels and to undertake a detailed study into the structural and thermal performance of LSF wall panels exposed to realistic design fire curves.