Showing papers by "Ryerson University published in 2014"
TL;DR: In this paper, the authors present a non-technical introduction to the basic concepts and issues of PLS-SEM, bearing the needs of potential users in mind, and illustrate the analysis of mediating effects.
988 citations
TL;DR: In this paper, the authors present a literature review of model predictive control (MPC) for HVAC systems, with an emphasis on the theory and applications of MPC for heating, ventilation and air conditioning (HVAC) systems.
899 citations
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TL;DR: A systematic procedure for PLS-SEM results evaluation is presented and applied to an annotated example, and the analysis of mediating effects, which researchers are increasingly testing in their models.
Abstract: Structural equation modeling (SEM) has become a mainstream method in many fields of business research, but its use in family business research remains in its infancy. This lag in SEM’s application holds especially true for partial least squares SEM (PLS-SEM), an alternative to covariance-based SEM, which provides researchers with more flexibility in terms of data requirements, model complexity and relationship specification. This article draws attention to PLS-SEM as an opportunity to advance the development and testing of theory in family business research by providing a non-technical introduction into the basic concepts and issues of PLS-SEM, bearing the needs of potential users in mind. To this end, a systematic procedure for PLS-SEM results evaluation is presented and applied to an annotated example. The article also illustrates the analysis of mediating effects, which researchers are increasingly testing in their models.
658 citations
501 citations
TL;DR: In this article, the authors present a comprehensive study on Smart Grid and the role of Advanced Metering Infrastructure (AMI) in SG, which is not a single technology; rather it is a combination of different areas of engineering, communication and management.
487 citations
27 Oct 2014
TL;DR: In this paper, the authors discuss common recommender systems techniques and their associated trade-offs in order to assist customers in this scenario, and discuss about common recommendation systems techniques that have been employed.
Abstract: Internet is speeding up and modifying the manner in which daily tasks such as online shopping, paying utility bills, watching new movies, communicating, etc., are accomplished. As an example, in older shopping methods, products were mass produced for a single market and audience but that approach is no longer viable. Markets based on long product and development cycles can no longer survive. To stay competitive, markets need to provide different products and services to different customers with different needs. The shift to online shopping has made it incumbent on producers and retailers to customize for customers' needs while providing more options than were possible before. This, however, poses a problem for customers who must now analyze every offering in order to determine what they actually need and will benefit from. To aid customers in this scenario, we discuss about common recommender systems techniques that have been employed and their associated trade-offs.
338 citations
TL;DR: A review of the methods used to model the heating, ventilation, and air conditioning (HVAC) systems can be found in this article, where major data driven, physics based, and grey box modeling techniques reported in the recent literature are reviewed.
308 citations
TL;DR: The adsorption characteristics of heavy metals of organic-inorganic hybrid polymers, including different kinds of functional groups, selectivity of them for heavy metals, effect of pH and synthesis conditions on Adsorption capacity, are studied.
Abstract: Over the past decades, organic-inorganic hybrid polymers have been applied in different fields, including the adsorption of pollutants from wastewater and solid-state separations. In this review, firstly, these compounds are classified. These compounds are prepared by sol-gel method, self-assembly process (mesopores), assembling of nanobuilding blocks (e.g., layered or core-shell compounds) and as interpenetrating networks and hierarchically structures. Lastly, the adsorption characteristics of heavy metals of these materials, including different kinds of functional groups, selectivity of them for heavy metals, effect of pH and synthesis conditions on adsorption capacity, are studied.
306 citations
TL;DR: In this paper, a new medium voltage power converter topology using a diode rectifier, three-level boost (TLB) converter, and neutral-point-clamped (NPC) inverter is proposed for a high-power permanent magnet synchronous generator-based wind energy conversion system.
Abstract: In this paper, a new medium voltage power converter topology using a diode rectifier, three-level boost (TLB) converter, and neutral-point-clamped (NPC) inverter is proposed for a high-power permanent magnet synchronous generator-based wind energy conversion system. The generator-side TLB converter performs the maximum power point tracking and balancing of dc-link capacitor voltages, while the grid-side NPC inverter regulates the net dc-bus voltage and reactive power to the grid. A significant improvement in the grid power quality is accomplished as the NPC inverter no longer controls the dc-link neutral point voltage. A model predictive strategy is proposed to control the complete system where the discrete-time models of the proposed power electronic converters are used to predict the future behavior of control variables. These predictions are evaluated using two independent cost functions, and the switching states which minimize these cost functions are selected and applied to the generator- and grid-side converters directly. In order to comply with the high-power application, the switching frequencies of the TLB converter and NPC inverter are minimized and maintained below 1.5 and 1 kHz, respectively. The proposed topology and control strategy are verified through MATLAB simulations on a 3-MW/3000-V/577-A system and dSPACE DS1103-based experiments on 3.6-kW/208-V/10-A prototype.
277 citations
TL;DR: Wang et al. as mentioned in this paper proposed a curb-based method for road surface extraction from mobile laser scanning (MLS) point clouds, which first partitions the raw MLS data into a set of profiles according to vehicle trajectory data, and then extracts small height jumps caused by curbs in the profiles via slope and elevation difference thresholds.
Abstract: A mobile laser scanning (MLS) system allows direct collection of accurate 3D point information in unprecedented detail at highway speeds and at less than traditional survey costs, which serves the fast growing demands of transportation-related road surveying including road surface geometry and road environment. As one type of road feature in traffic management systems, road markings on paved roadways have important functions in providing guidance and information to drivers and pedestrians. This paper presents a stepwise procedure to recognize road markings from MLS point clouds. To improve computational efficiency, we first propose a curb-based method for road surface extraction. This method first partitions the raw MLS data into a set of profiles according to vehicle trajectory data, and then extracts small height jumps caused by curbs in the profiles via slope and elevation-difference thresholds. Next, points belonging to the extracted road surface are interpolated into a geo-referenced intensity image using an extended inverse-distance-weighted (IDW) approach. Finally, we dynamically segment the geo-referenced intensity image into road-marking candidates with multiple thresholds that correspond to different ranges determined by point-density appropriate normality. A morphological closing operation with a linear structuring element is finally used to refine the road-marking candidates by removing noise and improving completeness. This road-marking extraction algorithm is comprehensively discussed in the analysis of parameter sensitivity and overall performance. An experimental study performed on a set of road markings with ground-truth shows that the proposed algorithm provides a promising solution to the road-marking extraction from MLS data.
246 citations
TL;DR: Metal-organic frameworks are a new class of microporous materials that possess framework flexibility, large surface areas, “tailor-made” framework functionalities, and tunable pore sizes that empower MOFs superior performances and broader application spectra than those of zeolites and phosphine-based molecular sieves.
Abstract: Metal-organic frameworks (MOFs) are a new class of microporous materials that possess framework flexibility, large surface areas, “tailor-made” framework functionalities, and tunable pore sizes. These features empower MOFs superior performances and broader application spectra than those of zeolites and phosphine-based molecular sieves. In parallel with designing new structures and new chemistry of MOFs, the observation of unique breathing behaviors upon adsorption of gases or solvents stimulates their potential applications as host materials in gas storage for renewable energy. This has attracted intense research energy to understand the causes at the atomic level, using in situ X-ray diffraction, calorimetry, Fourier transform infrared spectroscopy, and molecular dynamics simulations. This article is developed in the following order: first to introduce the definition of MOFs and the observation of their framework flexibility. Second, synthesis routes of MOFs are summarized with the emphasis on the hydrothermal synthesis, owing to the environmental-benign and economically availability of water. Third, MOFs exhibiting breathing behaviors are summarized, followed by rationales from thermodynamic viewpoint. Subsequently, effects of various functionalities on breathing behaviors are appraised, including using post-synthetic modification routes. Finally, possible framework spatial requirements of MOFs for yielding breathing behaviors are highlighted as the design strategies for new syntheses.
TL;DR: In this article, a longitudinal data set (from 1997 to 2005) of newly established Canadian small and medium-sized enterprises (SMEs) was analyzed and it was shown that no single strategy is superior per se but that internationalization strategy moderates the relative importance of resources to SMEs' survival in the export market.
Abstract: Does “born-global” internationalization enhance or threaten a firm’s chances for survival in the export market? Despite the ongoing debate about born-global firms, we know little about what drives their survival in the export market. In particular, different theories yield conflicting predictions regarding whether born-global internationalization is superior or inferior to born-regional internationalization or gradual internationalization. Analyzing a longitudinal data set (from 1997 to 2005) of 1959 newly established Canadian small- and medium-sized enterprises (SMEs), we show that no single strategy is superior per se but that internationalization strategy moderates the relative importance of resources to SMEs’ survival abroad. Although resources are important for the survival of all SMEs, the relative importance of slack resources and innovation resources are most important for born-global firms followed by born-regional firms, and are the least important for gradual internationalizers.
TL;DR: This approach is a hybrid model of ensemble pruning that is based on k-means clustering and the framework of dynamic selection and circulating in combination with a sequential search method, and shows that D3C exhibits competitive performance against other high-performance methods, and experiments in multi-label datasets verify the feasibility of multi- label D2C.
29 Sep 2014
TL;DR: This work presents a novel approach for detecting objects and estimating their 3D pose in single images of cluttered scenes using a deformable parts-based model and demonstrates successful grasps using the detection and pose estimate with a PR2 robot.
Abstract: We present a novel approach for detecting objects and estimating their 3D pose in single images of cluttered scenes. Objects are given in terms of 3D models without accompanying texture cues. A deformable parts-based model is trained on clusters of silhouettes of similar poses and produces hypotheses about possible object locations at test time. Objects are simultaneously segmented and verified inside each hypothesis bounding region by selecting the set of superpixels whose collective shape matches the model silhouette. A final iteration on the 6-DOF object pose minimizes the distance between the selected image contours and the actual projection of the 3D model. We demonstrate successful grasps using our detection and pose estimate with a PR2 robot. Extensive evaluation with a novel ground truth dataset shows the considerable benefit of using shape-driven cues for detecting objects in heavily cluttered scenes.
TL;DR: This paper presents a review of different optimization methods for deployment and operation of renewable energy sources based generating units, and presents different types of linear and non-linear optimization algorithms used in renewableEnergy sources.
Abstract: Renewable energy technologies׳ systems are major components of the strategy to reduce harmful emissions and deal with depleting energy resources. It is necessary to deploy renewable energy sources in the best possible way such that cost is minimized and generation is maximized. In this paper, we present a review of different optimization methods for deployment and operation of renewable energy sources based generating units. Unlike other existing reviews, we carry out a general review of this research area, without limiting ourselves to any particular issue or geographic location. We examine this area with respect to different types of renewable energy sources, different modes of operations, types of objective functions for optimization and different geographical areas from which research publication are emanating. We present a general resource allocation problem and specify different possibilities for input, output, objective function and constraints. In addition, we review different objectives used in defining the optimization problems. We also present different types of linear and non-linear optimization algorithms used in renewable energy sources. Finally, we review optimization techniques for applications with respect to different end users.
TL;DR: A set of efficient closed-form AOA based self-localization algorithms using auxiliary variables based methods that achieve much higher localization accuracy than the triangulation method and avoid local minima and divergence in iterative ML estimators.
Abstract: Node self-localization is a key research topic for wireless sensor networks (WSNs). There are two main algorithms, the triangulation method and the maximum likelihood (ML) estimator, for angle of arrival (AOA) based self-localization. The ML estimator requires a good initialization close to the true location to avoid divergence, while the triangulation method cannot obtain the closed-form solution with high efficiency. In this paper, we develop a set of efficient closed-form AOA based self-localization algorithms using auxiliary variables based methods. First, we formulate the self-localization problem as a linear least squares problem using auxiliary variables. Based on its closed-form solution, a new auxiliary variables based pseudo-linear estimator (AVPLE) is developed. By analyzing its estimation error, we present a bias compensated AVPLE (BCAVPLE) to reduce the estimation error. Then we develop a novel BCAVPLE based weighted instrumental variable (BCAVPLE-WIV) estimator to achieve asymptotically unbiased estimation of locations and orientations of unknown nodes based on prior knowledge of the AOA noise variance. In the case that the AOA noise variance is unknown, a new AVPLE based WIV (AVPLE-WIV) estimator is developed to localize the unknown nodes. Also, we develop an autonomous coordinate rotation (ACR) method to overcome the tangent instability of the proposed algorithms when the orientation of the unknown node is near π/2. We also derive the Cramer-Rao lower bound (CRLB) of the ML estimator. Extensive simulations demonstrate that the new algorithms achieve much higher localization accuracy than the triangulation method and avoid local minima and divergence in iterative ML estimators.
TL;DR: In this article, a new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flowinterception; (2) stochastic demand as dynamic service requests; and (3) queueing delay.
Abstract: A new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flow-interception; (2) stochastic demand as dynamic service requests; and (3) queueing delay. These features are essential to analyze battery-powered electric shared-ride taxis operating in a connected, centralized dispatch manner. The model and solution method are based on a bi-level, simulation–optimization framework that combines an upper level multiple-server allocation model with queueing delay and a lower level dispatch simulation based on earlier work by Jung and Jayakrishnan. The solution algorithm is tested on a fleet of 600 shared-taxis in Seoul, Korea, spanning 603 km2, a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark “naive” genetic algorithm that does not consider cyclic interactions between the taxi charging demand and the charger allocations with queue delay. Results show not only that the proposed model is capable of locating charging stations with stochastic dynamic itinerary-interception and queue delay, but that the bi-level solution method improves upon the benchmark algorithm in terms of realized queue delay, total time of operation of taxi service, and service request rejections. Furthermore, we show how much additional benefit in level of service is possible in the upper-bound scenario when the number of charging stations is unbounded.
TL;DR: In this paper, the authors propose that the hackathon has the potential to act in multiple ways, possibly as a backdoor to the traditional government procurement process, and as a form of civic engagement.
Abstract: At all levels, governments around the world are moving toward the provision of open data, that is, the direct provision to citizens, the private sector, and other third parties, of raw government datasets, controlled by a relatively permissible license. In tandem with this distribution of open data is the promotion of civic hackathons, or “app contests” by government. The civic hackathon is designed to offer prize money to developers as a way to spur innovative use of open data, more specifically the creation of commercial software applications that deliver services to citizens. Within this context, we propose that the civic hackathon has the potential to act in multiple ways, possibly as a backdoor to the traditional government procurement process, and as a form of civic engagement. We move beyond much of the hype of civic hackathons, critically framing an approach to understanding civic hackathons through these two lenses. Key questions for future research emphasize the emerging, and important, nature of this research path.
TL;DR: In this paper, the authors proposed a model based on the technology acceptance model, which posits that consumers will accept the mobile wallet when they perceive usefulness and discover features through informal learning and are concerned about trust.
TL;DR: This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010, and serves as a "call to action" for universities regarding the need to respond to emerging market needs in BI/BA, including “Big Data.”
Abstract: In December 2012, the AIS Special Interest Group on Decision Support, Knowledge and Data Management Systems (SIGDSS) and the Teradata University Network (TUN) cosponsored the Business Intelligence Congress 3 and conducted surveys to assess academia’s response to the growing market need for students with Business Intelligence (BI) and Business Analytics (BA) skill sets. This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010. The article also serves as a “call to action” for universities regarding the need to respond to emerging market needs in BI/BA, including “Big Data.” The IS field continues to be well positioned to be the leader in creating the next generation BI/BA workforce. To do so, we believe that IS leaders need to continuously refine BI/BA curriculum to keep pace with the turbulent BI/BA marketplace.
TL;DR: Food insecurity in North America is consistently more prevalent among households with a person living with diabetes, and similarly, diabetes is also more prevalent in food-insecure households.
Abstract: Access to sufficient, safe, and nutritious food not only affects the health of people who experience food insecurity, but also their ability to manage health conditions, such as diabetes. When people find it difficult to access sufficient food, tailoring their food selection to a diabetes regimen is even more difficult. Food insecurity in North America is consistently more prevalent among households with a person living with diabetes, and similarly, diabetes is also more prevalent in food-insecure households. Diabetes management can be stressful due to the many required responsibilities; when compounded with food insecurity, it becomes an even greater challenge. As a result, many food-insecure diabetics find themselves caught between competing priorities such as procuring food, prescribed medications and supplies for diabetes, and managing other living expenses, potentially worsening their condition and overall health. Healthcare providers should be aware and informed about the significant role that food security can play in the prevention and management of diabetes.
TL;DR: This paper provides a simple but integrated mathematical model for determining an optimal vendor–buyer inventory policy by accounting for quality inspection errors at the buyer's end and learning in production at the vendor’s end to minimize the joint annual cost incurred in the supply chain.
Abstract: It is imperative for contemporary businesses to proactively search for ways of continuously improving the performance of their supply chains. Supply chain coordination and integrated decision making across the supply chain among various supply chain partners are frequently employed towards this end. Such supply chain coordination strategies include the use of common cycle time, quantity discounts, optimal lot sizing, quality improvements and inspections, etc. An important issue lacking in the supply chain literature relates to the incorporation of such quintessential and omnipresent human factors as errors in quality inspections and production improvements due to learning. This paper provides a simple but integrated mathematical model for determining an optimal vendor–buyer inventory policy by accounting for quality inspection errors at the buyer’s end and learning in production at the vendor’s end. The objective is to minimize the joint annual cost incurred in the supply chain. A numerical example is presented to illustrate the application and the substance of the proposed model. We discuss how such integrated models can be used for justifying investments in such strategic and operational areas as relationship management, product design, process design, and personnel training. We also provide some very interesting and challenging future research directions.
TL;DR: The proposed approach uses the novel discrete-time model of the inverter and output LC filter in order to predict the variables to be controlled and its application to the load voltage control of two-level four-leg inverters.
Abstract: This paper presents a finite control set model predictive strategy and its application to the load voltage control of two-level four-leg inverters. The proposed approach uses the novel discrete-time model of the inverter and output LC filter in order to predict the variables to be controlled. These predictions are carried out for the 16 switching states of the inverter and are evaluated using a cost function. The switching state that forces the load voltages to be closest to their respective references is chosen and applied to the inverter. The behavior of the predictive controller has been investigated, and the changes to both inductive and capacitive filter parameters have been considered. In order to improve the reliability of the fourth leg as well as the overall inverter efficiency, a solution is proposed, which combines hardware and software reconfigurations. The feasibility of the proposed method is verified through simulation and experimental results considering single-/three-phase, balanced/unbalanced, and linear/nonlinear loads.
TL;DR: The patterns of face exposure revealed in the current study coincide with the known trajectory of perceptual narrowing seen later in infancy.
Abstract: Exposure to faces is known to shape and change the face processing system; however, no study has yet documented infants' natural daily first-hand exposure to faces. One- and three-month-old infants' visual experience was recorded through head-mounted cameras. The video recordings were coded for faces to determine: (1) How often are infants exposed to faces? (2) To what type of faces are they exposed? and (3) Do frequently encountered face types reflect infants' typical pattern of perceptual narrowing? As hypothesized, infants spent a large proportion of their time (25%) exposed to faces; these faces were primarily female (70%), own-race (96%), and adult-age (81%). Infants were exposed to more individual exemplars of female, own-race, and adult-age faces than to male, other-race, and child- or older-adult-age faces. Each exposure to own-race faces was longer than to other-race faces. There were no differences in exposure duration related to the gender or age of the face. Previous research has found that the face types frequently experienced by our participants are preferred over and more successfully recognized than other face types. The patterns of face exposure revealed in the current study coincide with the known trajectory of perceptual narrowing seen later in infancy.© 2013 The Authors. Developmental Psychobiology Published by Wiley Periodicals, Inc. Dev Psychobiol 56: 249–261, 2014.
TL;DR: Rigorous proof shows that the proposed control law ensures semiglobal stability and guarantees the attitude of a rigid spacecraft to track a time-varying reference attitude in finite time.
Abstract: This brief investigates the finite-time output feedback attitude control of a rigid spacecraft. First, a nonlinear observer is designed. Through geometric homogeneity and Lyapunov theories, it is shown that the proposed observer can achieve the semiglobal finite-time stability. Then, a finite-time output feedback controller is proposed based on the finite-time observer. Rigorous proof shows that the proposed control law ensures semiglobal stability and guarantees the attitude of a rigid spacecraft to track a time-varying reference attitude in finite time. Simulation results are presented to illustrate the performance of the proposed controller.
TL;DR: A predictive control scheme is proposed for the low-voltage ride-through (LVRT) enhancement of direct-driven permanent-magnet-synchronous-generator-based megawatt-level wind turbines to store the surplus energy during the grid voltage dips.
Abstract: In this paper, a predictive control scheme is proposed for the low-voltage ride-through (LVRT) enhancement of direct-driven permanent-magnet-synchronous-generator-based megawatt-level wind turbines. The proposed method uses the turbine-generator rotor inertia to store the surplus energy during the grid voltage dips. The power conversion system is realized using a three-phase diode-bridge rectifier, a three-level-boost converter, and a neutral-point-clamped (NPC) inverter. The wind turbine requirements, such as maximum power point tracking, net dc-bus voltage control, balancing of the dc capacitor voltages, and reactive power generation, are modeled as the reference control variables. The generator- and grid-side cost functions are defined to deal with these control objectives. During each sampling interval, the control goals are achieved based on the minimization of cost functions. The coordination of boost and NPC converters and the exchange of reference control variables during normal and LVRT operation are formulated such that the power converters operate in a safe mode while meeting the grid code requirements. Simulation and experimental results are presented to validate the proposed strategy.
TL;DR: A historical database of experimental and theoretical works has been offered and major challenges, limitations, and technical hitches of performing experiments on ground (earth) condition has been selected, and cautiously deliberated.
TL;DR: Very large amounts of alcohol are produced globally that go unrecorded, and the primary harm from this kind of alcohol arises from the fact that it is typically much cheaper than licit alcohol, which may contribute to higher rates of chronic and irregular heavy drinking.
Abstract: BACKGROUND AND AIMS: Unrecorded alcohol constitutes about 30% of all alcohol consumed globally. The aims of this systematic review were to determine the epidemiology (occurrence, types, prevalence) of unrecorded alcohol consumption in different countries/regions, analyze the chemical composition of unrecorded alcohol, and examine health outcomes caused by the consumption of unrecorded alcohol, based on either epidemiology or toxicology. METHODS: A systematic search for, and qualitative analysis of, articles with empirical results on the different categories of unrecorded alcohol, based on PRISMA guidelines. RESULTS: Unrecorded alcohol was widespread in all regions of the world. Artisanal fermented beverages and spirits were the most common categories of unrecorded alcohol globally, and were available on all continents. In India, industrially produced spirits (country spirits) were most prevalent. In Russia and countries of the former Soviet Union, surrogate alcohols complemented artisanal spirits. Cross-border shopping was the most prevalent method of obtaining unrecorded alcohol in parts of Europe. Ethanol was the most harmful ingredient of unrecorded alcohol, and health consequences due to other ingredients found in unrecorded alcohol were scarce. However, since unrecorded alcohol is usually the least expensive form of alcohol available in many countries, it may contribute to higher rates of chronic and irregular heavy drinking. CONCLUSIONS: Very large amounts of alcohol are produced globally that go unrecorded. The primary harm from this kind of alcohol arises from the fact that it is typically much cheaper than licit alcohol. Language: en
TL;DR: A meta-analysis of research conducted for the same purpose since 1998 fails to replicate the moderating effect of friendship, and effect sizes are higher in studies conducted outside North America than in U.S.--and Canada-based studies.
Abstract: A central tenet of Bowlby's attachment theory is that early child-caregiver attachment is reflected in the quality of the child's interpersonal relationships throughout life. Schneider, Atkinson, and Tardif (2001) conducted a meta-analysis of studies conducted up to 1998 to corroborate that contention. They found a significant but small to moderate effect size (r = .20). Their finding that studies of friendship bonds had higher effect sizes than studies of other interpersonal relationships has important theoretical ramifications. The present brief report is a meta-analysis that covers research conducted for the same purpose since 1998. The sample consists of 44 studies with a total of 8505 participants. The overall effect size r of .19 (adjusted r = .12; 95% confidence interval, .08-.17) in the current study was similar in magnitude to the effect size reported in the 2001 meta-analysis, documenting consistency in the predictive power of attachment theory. However, we failed to replicate the moderating effect of friendship. One possible explanation for these findings is that the friendships of school-age children and adolescents no longer invoke very high levels of intimacy. Effect sizes are higher in studies conducted outside North America than in U.S.--and Canada-based studies.
TL;DR: In this article, the effect of temperature, pressure, pressure drop, dilution ratio, and mixture compositions on asphaltene precipitation and deposition is investigated. And the connectionist model is built based on experimental data covering wide ranges of process and thermodynamic conditions.
Abstract: Precipitation of asphaltene is considered as an undesired process during oil production via natural depletion and gas injection as it blocks the pore space and reduces the oil flow rate. In addition, it lessens the efficiency of the gas injection into oil reservoirs. This paper presents static and dynamic experiments conducted to investigate the effects of temperature, pressure, pressure drop, dilution ratio, and mixture compositions on asphaltene precipitation and deposition. Important technical aspects of asphaltene precipitation such as equation of state, analysis tools, and predictive methods are also discussed. Different methodologies to analyze asphaltene precipitation are reviewed, as well. Artificial neural networks (ANNs) joined with imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) are employed to approximate asphaltene precipitation and deposition with and without CO2 injection. The connectionist model is built based on experimental data covering wide ranges of process and thermodynamic conditions. A good match was obtained between the real data and the model predictions. Temperature and pressure drop have the highest influence on asphaltene deposition during dynamic tests. ICA-ANN attains more reliable outputs compared with PSO-ANN, the conventional ANN, and scaling models. In addition, high pressure microscopy (HPM) technique leads to more accurate results compared with quantitative methods when studying asphaltene precipitation.