Fire safety of steel wall systems using enhanced plasterboards

Fire safety design is important to eliminate the loss of property and lives during fire events. Gypsum plasterboard is widely used as a fire safety material in the building industry all over the world. It contains gypsum (CaSO4.2H2O) and Calcium Carbonate (CaCO3) and most importantly free and chemically bound water in its crystal structure. The dehydration of the gypsum and the decomposition of Calcium Carbonate absorb heat, which gives the gypsum plasterboard fire resistant qualities. Currently plasterboard manufacturers use additives such as vermiculite to overcome shrinkage of gypsum core and glass fibre to bridge shrinkage cracks and enhance the integrity of board during calcination and after the loss of paper facings in fires. Past research has also attempted to reduce the thermal conductivity of plasterboards using fillers. However, no research has been undertaken to enhance the specific heat of plasterboard and the points of dehydration using chemical additives and fillers. Hence detailed experimental studies of powdered samples of plasterboard mixed with chemical additives and fillers in varying proportions were conducted. These tests showed the enhancement of specific heat of plasterboard. Numerical models were also developed to investigate the thermal performance of enhanced plasterboards under standard fire conditions. The results showed that the use of these enhanced plasterboards in steel wall systems can significantly improve their fire performance. This paper presents the details of this research and the results that can be used to enhance the fire safety of steel wall systems commonly used in buildings.

Prediction of age at menopause from assessment of ovarian reserve may be improved by using body mass index and smoking status

Objective: Menopause is the consequence of exhaustion of the ovarian follicular pool. AMH, an indirect hormonal marker of ovarian reserve, has been recently proposed as a predictor for age at menopause. Since BMI and smoking status are relevant independent factors associated with age at menopause we evaluated whether a model including all three of these variables could improve AMH-based prediction of age at menopause. Methods: In the present cohort study, participants were 375 eumenorrheic women aged 19–44 years and a sample of 2,635 Italian menopausal women. AMH values were obtained from the eumenorrheic women. Results: Regression analysis of the AMH data showed that a quadratic function of age provided a good description of these data plotted on a logarithmic scale, with a distribution of residual deviates that was not normal but showed significant leftskewness. Under the hypothesis that menopause can be predicted by AMH dropping below a critical threshold, a model predicting menopausal age was constructed from the AMH regression model and applied to the data on menopause. With the AMH threshold dependent on the covariates BMI and smoking status, the effects of these covariates were shown to be highly significant. Conclusions: In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMH-based prediction of age at menopause.

Towards the development of a best practice index for the disclosure of organisations' climate change-related corporate governance practices

The aim of this study is to develop a disclosure guide for climate-change-related corporate governance (CCCG) practices. Drawing from existing climate change policy guidelines together with content analysis of leading Australian companies’ disclosure practices, we develop a best practice index for the disclosure of CCCG practises. The best practice index is further informed, validated and refined by the contribution of experts from a range of stakeholder groups. Our index represents the most comprehensive list generated to date, utilising experts’ opinions, in relation to CCCG disclosure practices. This CCCG disclosure index would be useful for companies seeking to provide information in relation their CCCG practices

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

Synthesis, structural analysis, and thermal decomposition studies of [(NH3)2BH2]B3H8

Boron–nitrogen containing compounds with high hydrogen contents as represented by ammonia borane (NH3BH3) have recently attracted intense interest for potential hydrogen storage applications. One such compound is [(NH3)2BH2]B3H8 with a capacity of 18.2 wt% H. Two safe and efficient synthetic routes to [(NH3)2BH2]B3H8 have been developed for the first time since it was discovered 50 years ago. The new synthetic routes avoid a dangerous starting chemical, tetraborane (B4H10), and afford a high yield. Single crystal X-ray diffraction analysis reveals N–Hδ+Hδ−–B dihydrogen interactions in the [(NH3)2BH2]B3H8·18-crown-6 adduct. Extended strong dihydrogen bonds were observed in pure [(NH3)2BH2]B3H8 through crystal structure solution based upon powder X-ray analysis. Pyrolysis of [(NH3)2BH2]B3H8 leads to the formation of hydrogen gas together with appreciable amounts of volatile boranes below 160 °C.

Thermal-elastic stresses and the criticality of the continental crust

Heating or cooling can lead to high stresses in rocks due to the different thermal-elastic properties of minerals. In the upper 4 km of the crust, such internal stresses might cause fracturing. Yet it is unclear if thermal elasticity contributes significantly to critical stresses and failure deeper in Earth's continental crust, where ductile creep causes stress relaxation. We combined a heating experiment conducted in a Synchrotron microtomograph (Advanced Photon Source, USA) with numerical simulations to calculate the grain-scale stress field in granite generated by slow burial. We find that deviatoric stresses >100 MPa can be stored during burial, with relaxation times from 100's to 1000's ka, even in the ductile crust. Hence, grain-scale thermal-elastic stresses may serve as nuclei for instabilities, thus rendering the continental crust close to criticality.

Connecting across continents : collaborative learning in a Web 2.0 world

Purpose – The article aims to review a university course, offered to students in both Australia and Germany, to encourage them to learn about designing, implementing, marketing and evaluating information programs and services in order to build active and engaged communities. The concepts and processes of Web 2.0 technologies come together in the learning activities, with students establishing their own personal learning networks (PLNs). Design/methodology/approach – The case study examines the principles of learning and teaching that underpin the course and presents the students' own experiences of the challenges they faced as they explored the interactive, participative and collaborative dimensions of the web. Findings – The online format of the course and the philosophy of learning through play provided students with a safe and supportive environment for them to move outside of their comfort zones, to be creative, to experiment and to develop their professional personas. Reflection on learning was a key component that stressed the value of reflective practice in assisting library and information science (LIS) professionals to adapt confidently to the rapidly changing work environment. Originality/value – This study provides insights into the opportunities for LIS courses to work across geographical boundaries, to allow students to critically appraise library practice in different contexts and to become active participants in wider professional networks.

Creative city index [Report]

The CCI Creative City Index (CCI-CCI) is a new approach to the measurement and ranking of creative global cities. It is constructed over eight principal dimensions, each with multiple distinct elements. Some of these dimensions are familiar from other global city indexes, such as the MORI or GaWC indexes, which account for the size of creative industries, the scale of cultural amenities, or the flows of creative people and global connectedness. In addition to these indicators, the CCI-CCI contributes several new dimensions. These measure the demand side of creative participation, the attention economy, user-created content, and the productivity of socially networked consumers. Global creative cities can often seem alike, in respect of per-capita measures of factors such as public spending on cultural amenities, or the number of hotels and restaurants. This is to be expected when people and capital are relatively free to move, and where economic and political institutions are broadly comparable. However, we find that different cities can register far larger differences at the level of consumer-co-creation and especially digital creative ‘microproductivity’. To explain this finding, we review the logic and rationale of creative and global city index construction and present a review of previous and contemporary indexes. We set out the case for our new model of a creative city index by showing why greater attention to consumer co-creation and microproductivity are important, as well as examining how these factors have been previously overlooked. We show how we have CCI-CCI Creative City Index measured these additional factors and indicate the effect they have on creative and global city indexes. We then present the findings from a pilot study of six cities, two Australian, two German and two from the UK, to indicate how the new index is calculated and applied. Our results indicate much greater variance arising from the new arguments between cities.

Creative city index 2012 - Data sources, calculation methods and tools [Report spreadsheet]

Spreadsheet for Creative City Index 2012

3D thermal mapping of building interiors using an RGB-D and thermal camera

The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

Desalination by a solar thermal membrane distillation process

A solar thermal membrane distillation pilot plant was operated for over 70 days in field conditions. The pilot plant incorporated a single spiral wound permeate gap membrane distillation style of module. All energy used to operate the unit was supplied by solar hot water collectors and photovoltaic panels. The process was able to produce a distillate stream of product water with a conductivity less than 10 µS/cm. Feed water concentration varied from 2,400 µS/cm to 106,000 µS/cm. The process is expected to find application in the production of drinking water for remote island and arid regions without the consumption of electrical energy.

Thermal performance of load bearing cold-formed steel walls under fire conditions using numerical studies

Cold–formed Light gauge Steel Frame (LSF) wall systems are increasingly used in low-rise and multi-storey buildings and hence their fire safety has become important in the design of buildings. A composite LSF wall panel system was developed recently, where a thin insulation was sandwiched between two plasterboards to improve the fire performance of LSF walls. Many experimental and numerical studies have been undertaken to investigate the fire performance of non-load bearing LSF wall under standard conditions. However, only limited research has been undertaken to investigate the fire performance of load bearing LSF walls under standard and realistic design fire conditions. Therefore in this research, finite element thermal models of both the conventional load bearing LSF wall panels with cavity insulation and the innovative LSF composite wall panel were developed to simulate their thermal behaviour under standard and realistic design fire conditions. Suitable thermal properties were proposed for plasterboards and insulations based on laboratory tests and available literature. The developed models were then validated by comparing their results with available fire test results of load bearing LSF wall. This paper presents the details of the developed finite element models of load bearing LSF wall panels and the thermal analysis results. It shows that finite element models can be used to simulate the thermal behaviour of load bearing LSF walls with varying configurations of insulations and plasterboards. Failure times of load bearing LSF walls were also predicted based on the results from finite element thermal analyses. Finite element analysis results show that the use of cavity insulation was detrimental to the fire rating of LSF walls while the use of external insulation offered superior thermal protection to them. Effects of realistic design fire conditions are also presented in this paper.

Study of particulate matter removal mechanism by using non-thermal plasma technology

Numbers of diesel engines in both stationary and mobile applications are increasing nowadays. Diesel engines emit lower Hydrocarbon (HC) and Carbon monoxide (CO) than gasoline engines. However, they can produce more nitrogen oxides (NOx) and have higher particulate matter (PM). On the other hand, emissions standards are getting stringent day by day due to considerable concerns about unregulated pollutants and particularly ultrafine particles deleterious effect on human health. Non-thermal plasma (NTP) treatment of exhaust gas is known as a promising technology for both NOx and PM reduction by introducing plasma inside the exhaust gas. Vehicle exhaust gases undergo chemical changes when exposed to plasma. In this study, the PM removal mechanism using NTP by applying high voltage pulses of up to 20 kVpp with a repetition rate of 10 kHz are investigated. It is found that, voltage increase not necessarily has a positive effect on PM removal in diesel engine emissions.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.

The thermal decomposition of hydronium jarosite and ammoniojarosite

The thermal decomposition of hydronium jarosite and ammoniojarosite was studied using thermogravimetric analysis and mass spectrometry, in situ synchrotron X-ray diffraction and infrared emission spectroscopy. There was no evidence for the simultaneous loss of water and sulfur dioxide during the desulfonation stage as has previously been reported for hydronium jarosite. Conversely, all hydrogen atoms are lost during the dehydration and dehydroxylation stage from 270 to 400 °C and no water, hydroxyl groups or hydronium ions persist after 400 °C. The same can be said for ammoniojarosite. The first mass loss step during the decomposition of hydronium jarosite has been assigned to the loss of the hydronium ion via protonation of the surrounding hydroxyl groups to evolve two water molecules. For ammoniojarosite, this step corresponds to the protonation of a hydroxyl group by ammonium, so that ammonia and water are liberated simultaneously. Iron(II) sulfate was identified as a possible intermediate during the decomposition of ammoniojarosite (421–521 °C) due to a redox reaction between iron(III) and the liberated ammonia during decomposition. Iron(II) ions were also confirmed with the 1,10-phenanthroline test. Iron(III) sulfate and other commonly suggested intermediates for hydronium and ammoniojarosite decomposition are not major crystalline phases; if they are formed, then they most likely exist as an amorphous phase or a different low temperature phases than usual.