Bitumen-water interfacial tension modeling by using subtractive clustering method

Calculation of interfacial tension during bitumen production is a crucial issue in heavy crude oil history. Upon variation in pressure, temperature and phases composition, interfacial tension between bitumen and water change. In this work a sophisticated method called subtractive clustering was utilized to predict dynamic interfacial tension between bitumen and water. The subtractive clustering method is composed of optimized fuzzy logic algorithm. A data bank which is collected from open-source literature, is used to create a reliable model. Then the prediction accuracy of the measured dynamic interfacial tension using subtractive clustering have been examined. Results state that the comparison of measured interfacial tension and predicted interfacial tension indicate acceptable accuracy of proposed model. Also more than 90 percent of data points have less than 3 percent absolute error.     

Marital psychological and physical aggression and children's mental and physical health: Direct, mediated, and moderated effects.

Relations between marital aggression (psychological and physical) and children's health were examined. Children's emotional insecurity was assessed as a mediator of these relations, with distinctions made between marital aggression against mothers and fathers and ethnicity (African American or European American), socioeconomic status, and child gender examined as moderators of effects. Participants were 251 community-recruited families, with multiple reporters of each construct. Aggression against either parent yielded similar effects for children. Children's emotional insecurity mediated the relation between marital aggression and children's internalizing, externalizing, and posttraumatic stress disorder symptoms. No differences were found in these pathways for African American and European American families or as a function of socioeconomic status or child gender. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Applying FCM-ANFIS algorithm as a novel computational method for prediction of viscosity of bitumen and heavy alkane mixture

Recently the studies expressed that the noticeable number of oil reservoirs in all over the world are heavy oil and bitumen reservoirs. So the importance of enhancement of oil recovery (EOR) processes for heavy oil and bitumen reservoirs is highlighted. The Dilution of the reservoir fluid by solvents such as tetradecane is one of well-known methods for these types of reservoirs which effects oil recovery by decreasing viscosity. In the present study, Fuzzy c-means (FCM) algorithm was coupled with Adaptive neuro-fuzzy inference system (ANFIS) to predict viscosity of bitumen and tetradecane in terms of temperature, pressure and weight percent of tetradecane. The coefficients of determination for training and testing steps were calculated such as 0.9914 and 0.9613. The comparison of results and experimental data expressed that FCM-ANFIS algorithm has great potential for estimation of viscosity of bitumen and tetradecane.     

Interrelations and moderators of longitudinal links between marital satisfaction and depressive symptoms among couples in established relationships.

Extending research based on newlywed couples, this study investigated longitudinal associations between marital satisfaction and depressive symptoms in a community sample of 296 couples in established relationships (M = 13.25 years, SD = 5.98) with children (M age = 11.05 years, SD = 2.31). Support was found for reciprocal relations between marital satisfaction and depressive symptoms in couples with established relationships. Further extending previous work, the study showed that relationship length and hostile marital conflict were significant moderators of these linkages. Husbands in longer term relationships were more vulnerable to depressive symptoms in the context of marital problems compared with husbands in shorter term relationships. At higher levels of marital conflict, the negative relationship between marital satisfaction and depressive symptoms was strengthened. Reflecting an unexpected finding, increased conflict buffered spouses from marital dissatisfaction in the context of depressive symptoms. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A cloud service composition method using a trust‐based clustering algorithm and honeybee mating optimization algorithm

One of the most critical issues in using service‐oriented technologies is the combination of services, which has become an important challenge in the present. There are some significant challenges in the service composition, most notable is the quality of service (QoS), which is more challenging due to changing circumstances in dynamic service environments. Also, trust value in the case of selection of more reliable services is another challenge in the service composition. Due to NP‐hard complexity of service composition, many metaheuristic algorithms have been used so far. Therefore, in this paper, the honeybee mating optimization algorithm as one of the powerful metaheuristic algorithms is used for achieving the desired goals. To improve the QoS, inspirations from the mating stages of the honeybee, the interactions between honeybees and queen bee mating and the selection of the new queen from the relevant optimization algorithm have been used. To address the trust challenge, a trust‐based clustering algorithm has also been used. The simulation results using C# language have shown that the proposed method in small scale problem acts better than particle swarm optimization algorithm, genetic algorithm, and discrete gbest‐guided artificial bee colony algorithm. With the clustering and reduction of the search space, the response time is improved; also, more trusted services are selected. The results of the simulation on a large‐scale problem have indicated that the proposed method is exhibited worse performance than the average results of previous works in computation time.     

Applying Grid partitioning based Fuzzy inference system as novel algorithm to predict Asphaltene precipitation

Asphaltene precipitation is one of challenging problems in petroleum and chemical engineering so the importance of investigation of Asphaltene precipitation is clear. The asphaltene deposition effects on wellbore plugging, wettability alteration and facility damages. In order to solve these problems, a novel investigation based on Grid partitioning based Fuzzy inference system algorithm to predict precipitated asphaltene in terms of dilution ratio, temperature and carbon number of precipitant was developed. The predicting algorithm performance was evaluated statistically and graphically. The coefficients of determination (R²) for training and testing phases 0.9973 and 0.9900 respectively which confirm the great accuracy and high potential of predicting algorithm for estimation of precipitated asphaltene so this algorithm can be used as high accurate and simple software for prediction of asphaltene behavior in crude oil.