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.

Correlation between conductivity or diffusivity and activation energy in amorphous solids

There exist many investigations of ionic transport in a variety of glasses. These studies exhibit strong correlation between ionic conductivity and activation energy: Typically, it is found that higher conductivity is associated with lower activation energies and vice versa. Although there are explanations for this at a phenomenological level, there is no consistent physical picture to explain the correlation between conductivity and activation energy. We have carried out molecular dynamics simulation as a function of the size of the impurity atom or diffusant (both neutral and charged) in a host amorphous matrix. We find that there is a maximum in self-diffusivity as a function of the size of the impurity atom suggesting that there is an appropriate size for which the diffusivity is maximum. The activation energy is found to be the lowest for this size of the impurity. A similar maximum has been previously found in other condensed phases, such as confined fluids and dense liquids, and has its origin in the levitation effect. The implications of this result for understanding ionic conductivity in glasses are discussed. Our results suggest that there is a relation between microscopic structure of the amorphous solid, diffusivity or conductivity, and activation energy. The nature of this relationship is discussed in terms of the levitation parameter showing that diffusivity is maximum when the size of the neck or doorway radius is comparable with the size of the diffusant. Our computational results here are in excellent agreement with independent experimental results of Nascimento et al. [Braz. J. Phys. 35, 626 (2005)] that structural features of the glass are important in determining the ionic conductivity.

Correlation, Coding, and Cooperation in Wireless Sensor Networks

We consider a single-hop data-gathering sensor network, consisting of a set of sensor nodes that transmit data periodically to a base-station. We are interested in maximizing the lifetime of this network. With our definition of network lifetime and the assumption that the radio transmission energy consumption forms the most significant portion of the total energy consumption at a sensor node, we attempt to enhance the network lifetime by reducing the transmission energy budget of sensor nodes by exploiting three system-level opportunities. We pose the problem of maximizing lifetime as a max-min optimization problem subject to the constraint of successful data collection and limited energy supply at each node. This turns out to be an extremely difficult optimization to solve. To reduce the complexity of this problem, we allow the sensor nodes and the base-station to interactively communicate with each other and employ instantaneous decoding at the base-station. The chief contribution of the paper is to show that the computational complexity of our problem is determined by the complex interplay of various system-level opportunities and challenges.

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.

Low correlation sequences over AM-PSK and QAM alphabets

A construction for a family of sequences over the 8-ary AM-PSK constellation that has maximum nontrivial correlation magnitude bounded as theta(max) less than or similar to root N is presented here. The famfly is asymptotically optimal with respect to the Welch bound on maximum magnitude of correlation. The 8-ary AM-PSK constellation is a subset of the 16-QAM constellation. We also construct two families of sequences over 16-QAM with theta(max) less than or similar to root 2 root N. These families are constructed by interleaving sets of sequences. A construction for a famBy of low-correlation sequences over QAM alphabet of size 2(2m) is presented with maximum nontrivial normalized correlation parameter bounded above by less than or similar to a root N, where N is the period of the sequences in the family and where a ranges from 1.61 in the case of 16-QAM modulation to 2.76 for large m. When used in a CDMA setting, the family will permit each user to modulate the code sequence with 2m bits of data. Interestingly, the construction permits users on the reverse link of the CDMA channel to communicate using varying data rates by switching between sequence famflies; associated to different values of the parameter m. Other features of the sequence families are improved Euclidean distance between different data symbols in comparison with PSK signaling and compatibility of the QAM sequence families with sequences belonging to the large quaternary sequence families {S(p)}.

Modelling of solute transport in a mild heterogeneous porous medium using stochastic finite element method: Effects of random source conditions

Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.

Testing against changing correlation

A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

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.

ZnO nanocrystalline thin films: a correlation of microstructural, optoelectronic properties

The compositional, structural, microstructural, dc electrical conductivity and optical properties of undoped zinc oxide films prepared by the sol-gel process using a spin-coating technique were investigated. The ZnO films were obtained by 5 cycle spin-coated and dried zinc oxide films followed by annealing in air at 600 A degrees C. The films deposited on the platinum coated silicon substrate were crystallized in a hexagonal wurtzite form. The energy-dispersive X-ray (EDX) spectrometry shows Zn and O elements in the products with an approximate molar ratio. TEM image of ZnO thin film shows that a grain of about 60-80 nm in size is really an aggregate of many small crystallites of around 10-20 nm. Electron diffraction pattern shows that the ZnO films exhibited hexagonal structure. The SEM micrograph showed that the films consist in nanocrystalline grains randomly distributed with voids in different regions. The dc conductivity found in the range of 10(-5)-10(-6) (Omega cm)(-1). The optical study showed that the spectra for all samples give the transparency in the visible range.