Dissociation of polar oil components in low salinity water and its impact on crude oil–brine interfacial interactions and physical properties

Despite many efforts into the study of fluids interaction in low salinity water flooding, they are not probing the basics of transport phenomena between the involved phases. This work is aimed to bring new understanding of fluid–fluid interaction during low salinity water flooding through a series of organized experiments in which a crude oil sample with known properties was kept in contact with different brine solutions of various ionic strengths. Measuring brine pH, conductivity and crude oil viscosity and density for a period of 45 days illustrates the strong effect of the contact time and ionic strength on the dissociation of polar components and physical properties of the crude oil and brine. Besides, the interfacial tension (IFT) measurements show that the interfacial interactions are affected by several competitive interfacial processes. By decreasing the ionic strength of the brine, the solubility of naphthenic acids in the aqueous solution increases, and hence, the conductivity and the pH of the aqueous phase decrease. To verify this important finding, UV–Vis spectroscopy and 1H NMR analysis were also performed on aged brine samples. Notably, there is an ionic strength of brine in which the lowest IFT is observed, while the other physical properties are remained relatively unchanged.     

Preventing Cloud Network from Spamming Attacks Using Cloudflare and KNN

Cloud computing is one of the most attractive and cost-saving models, which provides online services to end-users. Cloud computing allows the user to access data directly from any node. But nowadays, cloud security is one of the biggest issues that arise. Different types of malware are wreaking havoc on the clouds. Attacks on the cloud server are happening from both internal and external sides. This paper has developed a tool to prevent the cloud server from spamming attacks. When an attacker attempts to use different spamming techniques on a cloud server, the attacker will be intercepted through two effective techniques: Cloudflare and K-nearest neighbors (KNN) classification. Cloudflare will block those IP addresses that the attacker will use and prevent spamming attacks. However, the KNN classifiers will determine which area the spammer belongs to. At the end of the article, various prevention techniques for securing cloud servers will be discussed, a comparison will be made with different papers, a conclusion will be drawn based on different results.     

Preparation of voltammetric biosensor for tryptophan using multi-walled carbon nanotubes

Multi-walled carbon nanotubes (MWCNTs) were grown by chemical vapor deposition. The effect of the composition of carbon paste electrode on its voltammograms was evaluated in basic solution with 5.0×10⁻⁵ M tryptophan (Trp). It was found that addition of MWCNTs to the carbon paste would generate the peak current of Trp because of its catalytic effect on the redox process. The pH strongly affects the peak potential of Trp. The best analytical response was obtained at pH 13.0. The anodic peak currents were proportional to Trp concentrations in the range of 1.0×10⁻⁹−1.0×10⁻⁴ M under the optimized experimental conditions. The detection limit was 2.2×10⁻¹⁰ M. The effect of potential scan rate on the peak potential and peak current of tryptophan was investigated. The correlation of the peak currents against v^1/2 (v is the scan rate) is linear, which is very similar to a diffusion-controlled process. The proposed biosensor was applied to the determination of Trp in pharmaceuticals formulations successfully.     

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.     

Application of a Model to Simulate the Wetting and Drying Processes of Woody Biomass in the Field

The variation of moisture content in the biomass materials would affect the quality during the utilization of these materials as solid biofuel. The ability to predict the time-dependent moisture contents of the biomass via modeling can help to devise a better way to store and manage these biomass materials. In this study, pieces of aspen stems were subject to cycles of wetting and drying in lab-scale tests. A lumped mathematical model for simulating the moisture changes during storage was developed and calibrated using the experimental data. With the available weather data (air temperature, relative humidity, solar radiation, wind speed, and precipitation) as inputs, the model was then applied to estimate the moisture content of aspen (Populus tremuloides) during one year of storage in the field. Results showed that, for both uncovered bales and covered bales, the predicted moisture contents and the profiles were in good agreement with the measured in-field results. This lumped model may be used as a first approximation, and applied to estimate the moisture content of aspen or similar woody biomass materials during relatively long-term field storage.     

Enhancing liquid micromixing using low‐frequency rotating nanoparticles

Magnetic nanofluid actuation by rotating magnetic fields was proposed as a high‐performance tool for liquid mixing with enhanced micromixing features. A comparative study was conducted to evaluate the mixing index in T‐type mixers of magnetic and nonmagnetic fluids subject to static (SMF), oscillating (OMF), and rotating (RMF) magnetic fields. RMF excitation unveiled superior mixing indices with strong dependences to magnetic field frequency and content of magnetic nanoparticles. The impact of magnetic field types on micromixing was further examined at low and moderate Re numbers using the Villermaux–Dushman reaction and IEM micromixing model. The IEM‐inferred micromixing times were remarkably shorter by nearly four orders of magnitude in comparison with OMF and SMF excitations, and without magnetic field. The proposed mixing strategy is foreseen to complement innovative microfluidic devices with valuable mixing tools and methods for the diagnosis of the coupling between transport and intrinsic kinetics. © 2016 American Institute of Chemical Engineers AIChE J, 63: 337–346, 2017     

THERMODYNAMICS OF MOISTURE SORPTION IN ALFALFA PELLETS

ABSTRACT

Experimental data on sorption isotherms of alfalfa pellets were used to determine the thermodynamic functions (differential heat of sorption, spreading pressure, net integral enthalpy and entropy) of the pellets. The thermodynamic functions were then utilized in modeling the specific heats of pellets as a function of moisture content. The estimated values of the thermodynamic functions at different moisture contents confirmed the results of an earlier study on the influence of moisture sorption on the physical integrity of the pellets. The changes in the thermodynamic properties and physical integrity were prominent when the moisture of the pellets were between 0.10 and 0.12 (mass fraction basis). Using the differential heat of sorption, it was determined that alfalfa pellets have higher affinity for moisture uptake when compared to wheat and lentils. The specific heat of the solids of alfalfa pellets had a parabolic relationship with moisture whereas the specific heat of water fraction increased linearly with moisture content of the pellets.     

Developing an Interactive Spatial Multi-Attribute Decision Support System for Assessing Water Resources Allocation Scenarios

Water Resources Management - In water resource management, assessing water resource allocation scenarios (WRASs) is an important multi-attribute decision making (MADM) problem. It involves...