The Effect of Nanoclay on Rheological Properties and Storage Stability of SBS-Modified Bitumen

Abstract

Linear and branched grades of styrene-butadiene-styrene (SBS) triblock copolymer are commonly used for modifying physical, mechanical, and rheological properties of bitumen. Because bitumen and SBS are incompatible, SBS-modified bitumen is not storage stable at elevated temperatures. Incompatibility of branched SBS is greater than linear SBS. To obtain greater compatibility between SBS and bitumen, organophilic montmorillonite/SBS-modified bitumen mixtures, prepared by melt intercalated blending, were used. Results showed that the presence of nanoclay could improve the storage stability, aging, and high-temperature performance of polymer-modified bitumen (PMB) significantly. Of course, this effect can be seen by proper dispersion of organophilic montmorillonite (OMMT) in SBS and obtaining a homogenous blend, which is calleed an exfoliated structure. The structure of OMMT/SBS/bitumen blend was characterized by X-ray diffraction (XRD).     

Trend Analysis of Water Inflow Into the Dam Reservoirs Under Future Conditions Predicted By Dynamic NAR and NARX Models

Nowadays, the use of artificial intelligence is extended to various scientific and engineering fields including water management and planning. This study investigates the performance of dynamic artificial neural network (ANN) models in prediction of water inflow into the Sefidruod dam reservoir (Iran). For this purpose, first, the discharge time series of tributaries of the Sefidruod dam were analyzed for trends for a 47 year time period (1967 to 2014) using parametric regression and non-parametric Mann–Kendall tests considering independence, short-term, and long-term persistence assumptions. Also, the homogeneity of the data was investigated using three statistical tests including Cumulative Deviations, Worsley's Likelihood Ratio, and Bayesian inference. Then, the inflow discharges into the reservoir of Sefidruod dam from GhezelOzan and Shahroud tributaries were simulated using dynamic Nonlinear Auto-Regressive (NAR) and Nonlinear Auto-Regressive with exogenous input (NARX) models. Further, water inflow values of both rivers were predicted for the next 5 years in future using dynamic NAR and NARX models. Finally, the simulated results were tested for trends. Obtained results showed a significant decreasing trend in both rivers. Results also showed a continuous downward trend for the following 5-year period predicted by NAR and NARX models. In addition, it was found that the results obtained by the NARX model were less accurate compared to those by the NAR model.

     

Flue Gas Desulfurization by a Powder‐Particle Spouted Bed

The powder‐particle spouted bed process is one of the semi‐dry processes that have been developed for flue gas desulfurization. In this study, which is designed for SO₂ removal by a powder‐particle spouted bed, the reaction term is included in one‐dimensional and streamtube models that were presented previously for spouted beds. Hydrated lime is used as the sorbent in this process. The predictions of the models are compared with some published experimental data and it is found that the developed models are valid. The results of two models are compared with each other and their various properties are evaluated. The effects of different operating conditions on SO₂ removal efficiency are also investigated and preferred operating conditions are discussed.     

Implementation of IEEE 802.16e Standard on Xilinx ZC706: A C-RAN Prototype

Wireless Personal Communications - In this paper, we propose an architecture to implement IEEE 802.16e transmitter and receiver physical (PHY) layer on field programmable gate arrays. Several...     

Synthesis and properties of novel polyurethane‐urea insulating coatings from hydroxyl‐terminated prepolymers and blocked isocyanate curing agent

A novel series of one‐pack solvent borne polyurethane‐urea insulating coatings was prepared from hydroxyl‐terminated prepolymers (HTP) and blocked isocyanate curing agent (BIC). HTP was prepared from poly z(tetramethylene ether)glycol (PTMEG) with excess amount of toluene diisocyanate (TDI) and subsequent reaction of NCO‐terminated polyurethane with tris(hydroxymethyl‐aminomethane) (TRIS). BIC was prepared from the reaction of trimethylol propane, TDI, and N‐methyl aniline. HTP, BIC, and final products were characterized by conventional methods, and the curing condition was optimized via gel content measurements. Crosslink density of samples was determined via equilibrium swelling method, using Flory‐Rehner equations. Thermal, mechanical, and electrical properties as well as the chemical resistance of prepared coatings were evaluated and compared with commercially available formulations. Effects of structural parameters on physical, electrical, mechanical, and dynamic mechanical (DMTA) properties of the polyurethane‐urea coatings were investigated. The investigation of results showed superior electrical and mechanical properties of prepared green coating as a tailor‐made electrical insulator for metals. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

A New Approach Towards Procurement of Software Models Via Distributed Business Models

Nowadays the distributive nature of many modern enterprises leads business strategists to look forward to new solutions which could take over this new requirement. The ever-increasing surge of e-business trend is another driving force for dealing with new distributed environment in addition to the serious need for core software components. On the other hand, the major role of these information systems in survival of business while tight competition exists is a facet which reveals another requirement focused on the robust relationship of business and the system(s) maintaining it. In this paper we aim to introduce a new approach to procure software models by means of the underlying business model. Since the introduction of UML as the latest OMG standard modeling language in 1997, a few researches have been done to use UML as a tool for business modeling. Unfortunately, recent trends are still immature and confronted with shortages and deficiencies. BSUP, which stands for Business to Software Unified Process, is our new approach to fulfill such a goal by means of a proprietary extension of UML. In this work, while analyzing the issues causing problems in the existing methods, we show how BSUP successfully resolves a few of such problems. Issues such as distributed processes, uncertainty in values and associations, ambiguity in the model, lack of precisely defined semantics and etc. may successfully be addressed and resolved. The BSUP is an ongoing work currently being evaluated in Paxan Corp,¹ a mid-scale industrial environment and a leading manufacturer of cosmetics and detergent products in the region. So far a few encouraging benefits have been revealed as briefly discussed within this paper.     

The incorporation and release of ungeremine,an antifungal Amaryllidaceae alkaloid,in poly(lactic acid)/poly(ethylene glycol) nanofibers

Ungeremine (UNG) is an alkaloid typically isolated from Pancratium maritimum or synthesized by the oxidation of lycorine. This antifungal alkaloid was incorporated into electrospun nanofibers based on blends of poly(lactic acid) (PLA) and poly(ethylene glycol) (PEG). The effect of the UNG on the structure, morphology, and thermal properties of the fibers was evaluated, and the release of the alkaloid from the fibers was quantified. Studies on the release of the UNG for the nanofibers show that the release rate is related to the amount and distribution of the PEG in the nanofiber matrix. Initial burst release of the antifungal alkaloid is related to the PEG in the nanofibers, where after a sustained release occurs indicating that the UNG is present in both the PLA and PEG domains in the nanofibers.     

Intelligent islanding detection of a synchronous distributed generation using governor signal clustering

Detection of intentional and unintentional islanding of distributed generation units is one of the major protection issues of the distribution networks. Regarding the safety and reliable operation of a modern distribution network, an expert diagnosis apparatus is required to distinguish network cut off from variety of normal occurrences. Automatic load-frequency controller (ALFC) is an indispensable component of the synchronous generators. Simulation results show that input signal of the governor includes somewhat singular characteristics for each possible phenomenon or disturbance. Therefore, a new method based on Self-Organizing Map (SOM) neural network is proposed using input signal to the governor to cluster various occurrences into islanding and non-islanding categories. Simulation results presented in this paper shows that the input signal of the governor employed by a SOM can cluster a majority of occurrences of the system and distinguishes the islanding phenomenon with high confidence.     

Artificial Neural Network and Support Vector Machine Models for Inflow Prediction of Dam Reservoir (Case Study: Zayandehroud Dam Reservoir)

Inflow prediction of reservoirs is of considerable importance due to its application in water resources management related to downstream water release planning and flood protection. Therefore, in this research, different new input patterns for predicting inflow to Zayandehroud dam reservoir is proposed employing artificial neural network (ANN) and support vector machine (SVM) models. Nine different models with different patterns of input data such as inflow to the dam reservoir considering time duration lags, time index, and monthly rainfall of Ghaleh-Shahrokh station have been proposed to predict the inflow to the dam reservoir. Comparison of the results indicates that the ninth proposed model has the least error for inflow prediction in which the results of SVM model outperform those of ANN model. That is, the least error has been obtained using the ninth SVM (ANN) model with correlation coefficient (R) values of 0.8962 (0.89296), 0.9303 (0.92983) and 0.9622 (0.95333) and root mean squared error (RMSE) values of 47.9346 (48.5441), 42.69093 (43.748) and 23.56193 (28.5125) for training, validation and test data, respectively.

     

A new analytical modeling for the determination of thermodynamic quantities of refrigerants

A new analytical fundamental equation of state (EOS) is presented for fluids. The equation is explicit in the effective molecular potentials and allows calculation of all thermodynamic properties over the whole fluid surface (gas, liquid, supercritical and gas–liquid phase transition). Outside the critical area (± 0.05T_c), it is valid in a vast range of temperature and pressure (0.8T_c to 7.5T_c and up to 120P_c,). The EOS is applicable for a variety of refrigerants such as C₃H₂F₄ (HFO-1234ze (E)), hydrofluorocarbons (HFCs) including C₃F₈ (R218), C₃H₂F₆ (R236ea), C₃H₂F₆ (R236fa), C₃H₃F₅ (R245ca), C₃HF₇, C₄F₈ (RC318), C₄F₁₀, C₅F₁₂, natural refrigerants including NH₃, CO₂, hydrocarbons, monatomic gases and some other fluids. Calculations of second derivatives properties of fluids are sensitive tests of EOS behavior. Therefore, estimation of the thermodynamic properties including Joule-Thomson coefficient, μ_JT, and speed of sound, w, has been considered.