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.

New rational interpolation functions for finite element analysis of rotating beams

A rotating beam finite element in which the interpolating shape functions are obtained by satisfying the governing static homogenous differential equation of Euler–Bernoulli rotating beams is developed in this work. The shape functions turn out to be rational functions which also depend on rotation speed and element position along the beam and account for the centrifugal stiffening effect. These rational functions yield the Hermite cubic when rotation speed becomes zero. The new element is applied for static and dynamic analysis of rotating beams. In the static case, a cantilever beam having a tip load is considered, with a radially varying axial force. It is found that this new element gives a very good approximation of the tip deflection to the analytical series solution value, as compared to the classical finite element given by the Hermite cubic shape functions. In the dynamic analysis, the new element is applied for uniform, and tapered rotating beams with cantilever and hinged boundary conditions to determine the natural frequencies, and the results compare very well with the published results given in the literature.

Investigations on the influence of graphite filler on dry sliding wear and abrasive wear behaviour of carbon fabric reinforced epoxy composites

In this experimental study, the dry sliding wear and two-body abrasive wear behaviour of graphite filled carbon fabric reinforced epoxy composites were investigated. Carbon fabric reinforced epoxy composite was used as a reference material. Sliding wear experiments were conducted using a pin-on-disc wear tester under dry contact condition. Mass loss was determined as a function of sliding velocity for loads of 25, 50, 75, and 100 N at a constant sliding distance of 6000 m. Two-body abrasive wear experiments were performed under multi-pass condition using silicon carbide (SiC) of 150 and 320 grit abrasive papers. The effects of abrading distance and different loads have been studied. Abrasive wear volume and specific wear rate as a function of applied normal load and abrading distance were also determined. The results show that in dry sliding wear situations, for increased load and sliding velocity, higher wear loss was recorded. The excellent wear characteristics were obtained with carbon-epoxy containing graphite as filler. Especially, 10 wt.% of graphite in carbon-epoxy gave a low wear rate. A graphite surface film formed on the counterface was confirmed to be effective in improving the wear characteristics of graphite filled carbon-epoxy composites. In case of two-body abrasive wear, the wear volume increases with increasing load/abrading distance. Experimental results showed the type of counterface (hardened steel disc and SiC paper) material greatly influences the wear behaviour of the composites. Wear mechanisms of the composites were investigated using scanning electron microscopy. Wear of carbon-epoxy composite was found to be mainly due to a microcracking and fiber fracture mechanisms. It was found that the microcracking mechanism had been caused by progressive surface damage. Further, it was also noticed that carbon-epoxy composite wear is reduced to a greater extent by addition of the graphite filler, in which wear was dominated by microplowing/microcutting mechanisms instead of microcracking.

Optimisation techniques for planning automatic under frequency load shedding in New Zealand’s power system

Electricity generation is vital in developed countries to power the many mechanical and electrical devices that people require. Unfortunately electricity generation is costly. Though electricity can be generated it cannot be stored efficiently. Electricity generation is also difficult to manage because exact demand is unknown from one instant to the next. A number of services are required to manage fluctuations in electricity demand, and to protect the system when frequency falls too low. A current approach is called automatic under frequency load shedding (AUFLS). This article proposes new methods for optimising AUFLS in New Zealand’s power system. The core ideas were developed during the 2015 Maths and Industry Study Group (MISG) in Brisbane, Australia. The problem has been motivated by Transpower Limited, a company that manages New Zealand’s power system and transports bulk electricity from where it is generated to where it is needed. The approaches developed in this article can be used in electrical power systems anywhere in the world.

The Pandolf load carriage equation is a poor predictor of metabolic rate while wearing explosive ordnance disposal protective clothing

This investigation aimed to quantify metabolic rate when wearing an explosive ordnance disposal (EOD) ensemble (~33kg) during standing and locomotion; and determine whether the Pandolf load carriage equation accurately predicts metabolic rate when wearing an EOD ensemble during standing and locomotion. Ten males completed 8 trials with metabolic rate measured through indirect calorimetry. Walking in EOD at 2.5, 4.0 and 5.5km·h−1 was significantly (p < 0.05) greater than matched trials without the EOD ensemble by 49% (127W), 65% (213W) and 78% (345W), respectively. Mean bias (95% limits of agreement) between predicted and measured metabolism during standing, 2.5, 4 and 5.5km·h−1 were 47W (19 to 75W); −111W (−172 to −49W); −122W (−189 to −54W) and −158W (−245 to −72W), respectively. The Pandolf equation significantly underestimated measured metabolic rate during locomotion. These findings have practical implications for EOD technicians during training and operation and should be considered when developing maximum workload duration models and work-rest schedules.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

Can active learning principles be applied to the bioscience assessments of nursing students? A review of the literature

- Objectives To explore if active learning principles be applied to nursing bioscience assessments and will this influence student perception of confidence in applying theory to practice? - Design and Data Sources A review of the literature utilising searches of various databases including CINAHL, PUBMED, Google Scholar and Mosby's Journal Index. - Methods The literature search identified research from twenty-six original articles, two electronic books, one published book and one conference proceedings paper. - Results Bioscience has been identified as an area that nurses struggle to learn in tertiary institutions and then apply to clinical practice. A number of problems have been identified and explored that may contribute to this poor understanding and retention. University academics need to be knowledgeable of innovative teaching and assessing modalities that focus on enhancing student learning and address the integration issues associated with the theory practice gap. Increased bioscience education is associated with improved patient outcomes therefore by addressing this “bioscience problem” and improving the integration of bioscience in clinical practice there will subsequently be an improvement in health care outcomes. - Conclusion From the literature several themes were identified. First there are many problems with teaching nursing students bioscience education. These include class sizes, motivation, concentration, delivery mode, lecturer perspectives, student's previous knowledge, anxiety, and a lack of confidence. Among these influences the type of assessment employed by the educator has not been explored or identified as a contributor to student learning specifically in nursing bioscience instruction. Second that educating could be achieved more effectively if active learning principles were applied and the needs and expectations of the student were met. Lastly, assessment influences student retention and the student experience and as such assessment should be congruent with the subject content, align with the learning objectives and be used as a stimulus tool for learning.

Energy harvesting using ionic electro-active polymer thin films with Ag-based electrodes

In this paper we employ the phenomenon of bending deformation induced transport of cations via the polymer chains in the thickness direction of an electro-active polymer (EAP)-metal composite thin film for mechanical energy harvesting. While EAPs have been applied in the past in actuators and artificial muscles, promising applications of such materials in hydrodynamic and vibratory energy harvesting are reported in this paper. For this, functionalization of EAPs with metal electrodes is the key factor in improving the energy harvesting efficiency. Unlike Pt-based electrodes, Ag-based electrodes have been deposited on an EAP membrane made of Nafion. The developed ionic metal polymer composite (IPMC) membrane is subjected to a dynamic bending load, hydrodynamically, and evaluated for the voltage generated against an external electrical load. An increase of a few orders of magnitude has been observed in the harvested energy density and power density in air, deionized water and in electrolyte solutions with varying concentrations of sodium chloride (NaCl) as compared to Pt-based IPMC performances reported in the published literature. This will have potential applications in hydrodynamic and residual environmental energy harvesting to power sensors and actuators based on micro-andn nano-electro-mechanical systems (MEMS and NEMS) for biomedical,maerospace and oceanic applications.

Strength design of composite beam using gradient and particle swarm optimization

This work addresses the optimum design of a composite box-beam structure subject to strength constraints. Such box-beams are used as the main load carrying members of helicopter rotor blades. A computationally efficient analytical model for box-beam is used. Optimal ply orientation angles are sought which maximize the failure margins with respect to the applied loading. The Tsai-Wu-Hahn failure criterion is used to calculate the reserve factor for each wall and ply and the minimum reserve factor is maximized. Ply angles are used as design variables and various cases of initial starting design and loadings are investigated. Both gradient-based and particle swarm optimization (PSO) methods are used. It is found that the optimization approach leads to the design of a box-beam with greatly improved reserve factors which can be useful for helicopter rotor structures. While the PSO yields globally best designs, the gradient-based method can also be used with appropriate starting designs to obtain useful designs efficiently. (C) 2006 Elsevier Ltd. All rights reserved.

Influence lines for bending under a ring load of a free shell, a shell embedded in a soft medium and a shell containing a soft core

Theoretical expressions for stresses and displacements have been derived for bending under a ring load of a free shell, a shell embedded in a soft medium, and a shell containing a soft core. Numerical work has been done for typical cases with an Elliot 803 Digital Computer and influence lines are drawn therefrom.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Development and transient performance results of a single stage activated carbon - HFC 134a closed cycle adsorption cooling system

A laboratory model of a thermally driven adsorption refrigeration system with activated carbon as the adsorbent and 1,1,1,2-tetrafluoroethane (HFC 134a) as the refrigerant was developed. The single stage compression system has an ensemble of four adsorbers packed with Maxsorb II specimen of activated carbon that provide a near continuous flow which caters to a cooling load of up to 5W in the 5-18 degrees C region. The objective was to utilise the low grade thermal energy to drive a refrigeration system that can be used to cool some critical electronic components. The laboratory model was tested for it performance at various cooling loads with the heat source temperature from 73 to 93 degrees C. The pressure transients during heating and cooling phases were traced. The cyclic steady state and transient performance data are presented. (C) 2010 Elsevier Ltd. All rights reserved.