Thermal performance of magnesium oxide wall board using numerical modelling

Fire resistance of light-gauge steel frame (LSF) walls can be enhanced by lining them with single or multiple layers of wall boards. This research is focused on the thermal per-formance of Magnesium Oxide (MgO) wall boards in comparison to the conventional gypsum plasterboards exposed to standard fire on one side. Thermal properties of MgO board and gypsum plasterboard were measured first and then used in the finite element heat transfer models of the two types of panels. The measured thermal property results show that MgO board will perform better than the gypsum plasterboards due to its higher specific heat values at elevated temperatures. However, MgO board loses 50% of its ini-tial mass at about 500 °C compared to 16% for gypsum plasterboard. The developed finite element models were validated using the fire test results of gypsum plasterboards and then used to study the thermal performance of MgO board panels. Finite element analysis re-sults show that when MgO board panels are exposed to standard fire on one side the rate of temperature rise on the ambient side is significantly reduced compared to gypsum plas-terboard. This has the potential to improve the overall thermal performance of MgO board lined LSF walls and their fire resistance levels (FRL). However, full scale fire tests are needed to confirm this. This paper presents the details of this investigation and the results.

Material characterisation and numerical modelling of gypsum plasterboards in fire

The fire resistance characteristic of LSF wall systems mainly depends on the protective linings in use, commonly gypsum plasterboards. However, unclassified boards with varying composition and more notably with ambiguous thermal properties are increasingly becoming available in the market. Therefore a study was undertaken with an aim to set minimum standards for fire protective boards used in LSF wall applications. This paper presents the details of this study based on material characterisation and finite element thermal modelling of the most commonly used fire protective board, gypsum plasterboards, to address these critical issues related to fire safety design. In the material characterisation phase of this study, thermal properties of three different gypsum plasterboards manufactured in Australia were measured, analysed and compared. Subsequently, it proposes a thermal property based “k-factor” capable of giving an overall measure of the fire performance of boards, so that it can be used in appropriately classifying fire protective boards. As it is not known how this factor relates to the overall fire performance of LSF wall systems, numerical models were also developed and used to simulate the performance of LSF walls exposed to the standard fire. Finally, a correlation between time-temperature profiles from numerical analyses and calculated k-factors was established.

Dynamics of Finnish starlings in 1951-2005 : from monitoring to population modelling

Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

Contribution of geophysical surveys to groundwater modelling of a porous aquifer in semiarid Niger: An overview

Subsurface geophysical surveys were carried out using a large range of methods in an unconfined sandstone aquifer in semiarid south-western Niger for improving both the conceptual model of water flow through the unsaturated zone and the parameterization of numerical a groundwater model of the aquifer. Methods included: electromagnetic mapping, electrical resistivity tomography (ERT), resistivity logging, time domain electromagnetic sounding (TDEM), and magnetic resonance sounding (MRS). Analyses of electrical conductivities, complemented by geochemical measurements, allowed us to identify preferential pathways for infiltration and drainage beneath gullies and alluvial fans. The mean water content estimated by MRS (13%) was used for computing the regional groundwater recharge from long-term change in the water table. The ranges in permeability and water content obtained with MRS allowed a reduction of the degree of freedom of aquifer parameters used in groundwater modelling.

Reproducibility of scratch assays is affected by the initial degree of confluence: Experiments, modelling and model selection

Scratch assays are difficult to reproduce. Here we identify a previously overlooked source of variability which could partially explain this difficulty. We analyse a suite of scratch assays in which we vary the initial degree of confluence (initial cell density). Our results indicate that the rate of re-colonisation is very sensitive to the initial density. To quantify the relative roles of cell migration and proliferation, we calibrate the solution of the Fisher–Kolmogorov model to cell density profiles to provide estimates of the cell diffusivity, D, and the cell proliferation rate, λ. This procedure indicates that the estimates of D and λ are very sensitive to the initial density. This dependence suggests that the Fisher–Kolmogorov model does not accurately represent the details of the collective cell spreading process, since this model assumes that D and λ are constants that ought to be independent of the initial density. Since higher initial cell density leads to enhanced spreading, we also calibrate the solution of the Porous–Fisher model to the data as this model assumes that the cell flux is an increasing function of the cell density. Estimates of D and λ associated with the Porous–Fisher model are less sensitive to the initial density, suggesting that the Porous–Fisher model provides a better description of the experiments.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Modelling heterogeneity of concrete using 2D lattice network for concrete fracture and comparison with AE study

In this paper, numerical modelling of fracture in concrete using two-dimensional lattice model is presented and also a few issues related to lattice modelling technique applicable to concrete fracture are reviewed. A comparison is made with acoustic emission (AE) events with the number of fractured elements. To implement the heterogeneity of the plain concrete, two methods namely, by generating grain structure of the concrete using Fuller's distribution and the concrete material properties are randomly distributed following Gaussian distribution are used. In the first method, the modelling of the concrete at meso level is carried out following the existing methods available in literature. The shape of the aggregates present in the concrete are assumed as perfect spheres and shape of the same in two-dimensional lattice network is circular. A three-point bend (TPB) specimen is tested in the experiment under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the fracture process in the same TPB specimen is modelled using regular triangular 2D lattice network. Load versus crack mouth opening isplacement (CMOD) plots thus obtained by using both the methods are compared with experimental results. It was observed that the number of fractured elements increases near the peak load and beyond the peak load. That is once the crack starts to propagate. AE hits also increase rapidly beyond the peak load. It is compulsory here to mention that although the lattice modelling of concrete fracture used in this present study is very similar to those already available in literature, the present work brings out certain finer details which are not available explicitly in the earlier works.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Modelling, calibrating, and validating car following and lane changing behaviour

Car following (CF) and lane changing (LC) are two primary driving tasks observed in traffic flow, and are thus vital components of traffic flow theories, traffic operation and control. Over the past decades a large number of CF models have been developed in an attempt to describe CF behaviour under a wide range of traffic conditions. Although CF has been widely studied for many years, LC did not receive much attention until recently. Over the last decade, researchers have slowly but surely realized the critical role that LC plays in traffic operations and traffic safety; this realization has motivated significant attempts to model LC decision-making and its impact on traffic. Despite notable progresses in modelling CF and LC, our knowledge on these two important issues remains incomplete because of issues related to data, model calibration and validation, human factors, just to name a few. Thus, this special issue will focus on latest developments in modelling, calibrating, and validating two primary vehicular interactions observed in traffic flow: CF and LC.

Water balance modelling in a tropical watershed under deciduous forest (Mule Hole, India): Regolith matric storage buffers the groundwater recharge process

Accurate estimations of water balance are needed in semi-arid and sub-humid tropical regions, where water resources are scarce compared to water demand. Evapotranspiration plays a major role in this context, and the difficulty to quantify it precisely leads to major uncertainties in the groundwater recharge assessment, especially in forested catchments. In this paper, we propose to assess the importance of deep unsaturated regolith and water uptake by deep tree roots on the groundwater recharge process by using a lumped conceptual model (COMFORT). The model is calibrated using a 5 year hydrological monitoring of an experimental watershed under dry deciduous forest in South India (Mule Hole watershed). The model was able to simulate the stream discharge as well as the contrasted behaviour of groundwater table along the hillslope. Water balance simulated for a 32 year climatic time series displayed a large year-to-year variability, with alternance of dry and wet phases with a time period of approximately 14 years. On an average, input by the rainfall was 1090 mm year(-1) and the evapotranspiration was about 900 mm year(-1) out of which 100 mm year(-1) was uptake from the deep saprolite horizons. The stream flow was 100 mm year(-1) while the groundwater underflow was 80 mm year(-1). The simulation results suggest that (i) deciduous trees can uptake a significant amount of water from the deep regolith, (ii) this uptake, combined with the spatial variability of regolith depth, can account for the variable lag time between drainage events and groundwater rise observed for the different piezometers and (iii) water table response to recharge is buffered due to the long vertical travel time through the deep vadose zone, which constitutes a major water reservoir. This study stresses the importance of long term observations for the understanding of hydrological processes in tropical forested ecosystems. (C) 2009 Elsevier B.V. All rights reserved.

BDST modelling of sodium ion exchange column behaviour with strong acid cation resin in relation to coal seam water treatment

Reverse osmosis is the dominant technology utilized for desalination of saline water produced during the extraction of coal seam gas. Alternatively, ion exchange is of interest due to potential cost advantages. However, there is limited information regarding the column performance of strong acid cation resin for removal of sodium ions from both model and actual coal seam water samples. In particular, the impact of bed depth, flow rate, and regeneration was not clear. Consequently, this study applied Bed Depth Service Time (BDST) models to reveal that increasing sodium ion concentration and flow rates diminished the time required for breakthrough to occur. The loading of sodium ions on fresh resin was calculated to be ca. 71.1 g Na/kg resin. Difficulties in regeneration of the resin using hydrochloric acid solutions were discovered, with 86% recovery of exchange sites observed. The maximum concentration of sodium ions in the regenerant brine was found to be 47,400 mg/L under the conditions employed. The volume of regenerant waste formed was 6.2% of the total volume of water treated. A coal seam water sample was found to load the resin with only 53.5 g Na/kg resin, which was consistent with not only the co-presence of more favoured ions such as calcium, magnesium, barium and strontium, but also inefficient regeneration of the resin prior to the coal seam water test.

Analytical modelling of integrated solar drying system

The drying of fruit and vegetables is a subject of great importance. Dried fruit and vegetables have gained commercial importance, and their growth on a commercial scale has become an important sector of the agricultural industry. However, food drying is one of the most energy intensive processes of the major industrial process and accounts for up to 15 % of all industrial energy usage. Due to increasingly high electricity prices and environmental concern, a dryer using traditional energy sources is not a feasible option anymore. Therefore, an alternative/renewable energy source is needed. In this regard, an integrated solar drying system that includes highly efficient double-pass counter flow v-groove solar collector, conical-shaped rock-bed thermal storage, auxiliary heater, the centrifugal fan and the drying chamber has been designed and constructed. Mathematical model for all the individual components as well as an integrated model combining all components of the drying system has been developed. Mathematical equations were solved using MATLAB program. This paper presents the analytical model and key finding of the simulation.

Modelling conical rock-bed solar thermal storage tank

An important application of solar thermal storage is for power generation or process heating. Low-temperature thermal storage in a packed rock bed is considered the best option for thermal storage for solar drying applications. In this chapter, mathematical formulations for conical have been developed. The model equations are solved numerically for charging/discharging cycles utilizing MATLAB. Results were compared with rock-bed storage with standard straight tank. From the simulated results, the temperature distribution was found to be more uniform in the truncated conical rock-bed storage. Also, the pressure drop over a long period of time in the conical thermal storage was as low as 25 Pa. Hence, the amount of power required from a centrifugal fan would be significantly lower. The flow of air inside the tank is simulated in SolidWorks software. From flow simulation, 3D modelling of flow is obtained to capture the actual scenario inside the tank.

Mathematical modelling of rock-bed solar thermal storage tank

An important application of thermal storage is solar energy for power generation or process heating. Low temperature thermal storage in a packed rock bed is considered best option for thermal storage for solar drying applications. In this paper, mathematical formulations for conical and cylindrical rock bed storage tanks have been developed. The model equations are solved numerically for charging/discharging cycles. From the simulated results, it was observed that for the same aspect ratio between the diameter and the length of the thermal storages, the conical thermal storage had better performance. The temperature distribution was found to be more uniform in the truncated conical shape rock bed storage. Also, the pressure drop over long period of time in the conical thermal storage was lower than that of the cylindrical thermal storage. Hence, the amount of power required from a centrifugal fan was lower.