Investigation of wood pellets self-heating kinetics and thermal runaway phenomena using lab scale experiments

The phenomena of spontaneous combustion and thermal runaway in wood pellets storage were investigated using lab-scale experiments in the temperature range of 100–200 °C. The critical temperatures were determined for four sizes of reactors. The kinetic parameters of the self-heating were determined using three methods, the Frank-Kamenetskii's method, crossing point method, and numerical curve fitting method. Mean values of activation energy (E) of 78.7 ±0.8 kJ/mol and self-heating rate constant (∆ _rhA) of (4.22 ±2.5) × 10 ⁶ kJ/(kg s) were obtained for four type of wood pellets (made from whitewood) samples from different pellet producers in British Columbia. Finally, a two-dimensional numerical model was developed to predict the temperature development during self-heating and the critical temperature for known sizes of reactors.     

Silver nanoparticle films by flowing gas atmospheric pulsed laser deposition and application to surface-enhanced Raman spectroscopy

For the fast uptake into industrial applications, the further development of robust methods of nanomaterials, which are inexpensive and simultaneously technologically feasible, is one of the major key factors. A newly introduced atmospheric pulsed laser deposition method, based on a flowing gas approach, was used for plasmonic metal nanoparticle (NP) film of silver. Contrary to vacuum, in this method, the ambient air restricts expansion of the ablation plume within 1 to 3 mm above the target surface. These sets constrain on the formation of NP film close to the ablation spot. For deposition on a widely spaced surface, ablation material was entrained in a flow of argon, supplied at ~32 ms⁻¹, and effectively delivered to the substrate at ~20 ms⁻¹. The films produced were crystalline and particulate in nature, showing spectral plasmonic feature of surface plasmon resonance in the visible region. The film was directly tested in surface-enhanced Raman spectroscopy for chemical detection of crystal violet; the film with large particulates and aggregated crystallites was well-performed, showing enhanced Raman signals and detection sensitivity. Certainly, flowing gas atmospheric pulsed laser deposition seems a fast alternative to vacuum-pulsed laser deposition but needs further investigations to bring it in the industry for applications in sensor, catalysis, solar cell, and coating technology.     

A Comparative Assessment of Artificial Neural Network,Generalized Regression Neural Network,Least-Square Support Vector Regression,and K-Nearest Neighbor Regression for Monthly Streamflow Forecasting in Linear and Nonlinear Conditions

Monthly forecasting of streamflow is of particular importance in water resources management especially in the provision of rule curves for dams. In this paper, the performance of four data-driven models with different structures including Artificial Neural Network (ANN), Generalized Regression Neural Network (GRNN), Least Square-Support Vector Regression (LS-SVR), and K-Nearest Neighbor Regression (KNN) are evaluated in order to forecast monthly inflow to Karkheh dam, Iran, in linear and non-linear conditions while the optimized values of the model parameters are determined in the same condition via the Leave-One-Out Cross Validation (LOOCV) method. Results show that the performance of the models is different in linear and nonlinear conditions; the cumulative ranking of the models according to the three assessment criteria including NSE, RMSE and R² indicates that ANN performs best in linear conditions while LS-SVR, GRNN and KNN are in the next ranks, respectively. But in nonlinear conditions, the best performance belongs to LS-SVR, followed by KNN, ANN, and GRNN models.     

A regression modelling approach for optimizing segmentation scale parameters to extract buildings of different sizes

Multiresolution segmentation (MRS) is one of the most commonly used image segmentation algorithms in the remote-sensing community. This algorithm has three user-defined parameters: scale, shape, and compactness. The scale parameter (SP) is the most crucial one in determining the average size of the image segments generated. Since setting this parameter typically requires a trial-and-error process, automatically estimating it can expedite the segmentation process. However, most of automatic approaches are still iterative and can lead to a time-consuming process. In this article, we propose a new, non-iterative framework for estimating the SP with an emphasis on extracting individual urban buildings. The basis of the proposed method is to investigate the feasibility of associating the size of urban buildings with a corresponding ‘optimal’ (or at least reasonable) SP using an explicit mathematical equation. Using the proposed method, these two variables are related to each other by constructing a mathematical (regression) model. In this framework, the independent variables were chosen to be the typical size of buildings in a given urban area and the spatial resolution of the image under consideration; and the dependent variable was chosen to be the corresponding optimal SP. To assess the potential of the proposed approach, two regression models that yielded explicit equations (i.e. degree-2 polynomial (DP), and regression tree (RT)) were employed. In addition, as a sophisticated and versatile nonlinear model, support vector regression (SVR) was utilized to further measure the performances of DP and RT models compared with it. According to the comparisons, the DP model was selected as a representative of the proposed approach. In the end, to evaluate the proposed methodology, we also compared the results derived from the DP model with those derived from the Estimation of Scale Parameter (ESP) tool. Based on our experiments, not only did the DP model produce acceptable results, but also it outperformed ESP tool in this study for extracting individual urban buildings.     

Experimental and modeling investigation of dynamic interfacial tension of asphaltenic-acidic crude oil/aqueous phase containing different ions

In this way,after experimental measurement of interfacial tension,different models including mono-exponential decay,dynamic adsorption models and empirical equation are used to correlate this time-dependent behavior of interfacial tension(IFT).During the modeling approach,the induction,adsorption,equilibrium,and meso-equilibrium times as well as diffusivity of surface active components known as natural surfactant including asphaltene and resin from crude oil to the interface are obtained.In addition,the surface excess concentration of surface active components at the interface and Gibbs adsorption isotherm are utilized to analyze the measured dynamic IFTs.Finally,the mechanisms of crude oil/aqueous solution IFT including(a)the activity of surface-active components and(b)surface excess concentration of them at fluid/fluid interface are proposed and discussed in details.     

Magnetic nanocomposite of multi-walled carbon nanotube as effective adsorbent for methyl violet removal from aqueous solutions: Response surface modeling and kinetic study

Magnetic nanocomposite of multi-walled carbon nanotube (m-MWCNT) was synthesized for adsorptive removal of methyl violet (MV) from aqueous solutions. The experiments were conducted using a central composite design (CCD) with the variables of adsorbent dosage (0.4-1.2 g/L), solution pH (3-9), contact time (10-42 min) and ionic strength (0.02-0.1mol L^?1). Regression analysis showed good fit of the experimental data to a quadratic response surface model whose statistical significance was verified by analysis of variance. By applying the desirability functions, optimum conditions of the process were predicted as adsorbent dosage of 0.99g/L, pH=4.92, contact time of 40.98 minutes and ionic strength of 0.04 mol L^?1 to achieve MV removal percentage of 101.19. Experimental removal efficiency of 99.51% indicated that CCD along with the desirability functions can be effectively applied for optimizing MV removal by m-MWCNT. Based on the study, the adsorption process followed Langmuir isotherm model and pseudo-second-order kinetic model could realistically describe the dye adsorption onto m-MWCNT.     

An OWA‐Based Ranking Approach for University Books Recommendation

Generally the book recommendation approaches are personalized in nature, that is, they utilize the users’ purchasing behavior to recommend them the book similar to their preferences. The main problem with the personalized recommendation is its knowledge requirement about users’ past preferences. As a result, these techniques fail in producing appropriate recommendation for a new user whose preferences are not known. The personalized recommendation also needs extra space to store the users’ preferences. In this paper, a framework to recommend books to university students for their studies is presented. In order to answer which books are to be included in the syllabus, a specialized way of recommendation, where recommendations from experts of the subjects at different universities are considered, is presented. We have suggested a ranked recommendation approach for books, which employ Ordered Weighted Aggregation (OWA), a fuzzy‐based aggregation, to aggregate the several ranking of the top universities. On the one hand, it does not need user prior preferences, and on the other hand, it eases the complexities of personalized recommendation to huge number of users and replaces it with a single ranked recommendation. The experimental results are compared with the existing positional aggregation algorithm that demonstrates significant improvement in the results with respect to various performance metrics.     

Dynamic Resource Allocation for Multimedia Document Retrieval over High Speed LANs

The emergence of gigabit local area networks (G-LANs) has spurred a tremendous interest in supporting networked multimedia applications over a LAN. In this paper, we propose a mechanism for dynamically allocating network resources in asynchronous LANs. Presentation of multimedia objects with required play-out quality requires Quality of Service (QoS) guarantees by the underlying networking infrastructure. Existing asynchronous LANs, such as Ethernet, do not support the notion of QoS due to their asynchronous media access protocol. For such networks, we propose a dynamic bandwidth management scheme that uses the concept of Time Division Multiple Access (TDMA). Significant performance improvement is observed through experimental results. In particular, the transmission rates for multimedia hosts improve significantly with low jitter variations in media streams. We also propose a framework for graceful degradation of play-out quality of multimedia objects in case the LAN's total capacity is not sufficient to meet the overall demand.