Abstract: A toy track and brick adapter for toy tracks and bricks comprising a base having a top surface and a bottom surface with indentations in the bottom surface of the base for receiving building blocks. A first arm assembly and a second arm assembly mounted to the top surface generally perpendicular to the base distally disposed in a parallel relationship to grip toy tracks. Roadway retention lips are attached to the arm assemblies which in conjunction with the tension springs hold the toy track in place within the toy track and brick adapter. Also attached to the roadway retention lips are pull-tab accessory brackets configured to releasably connect a variety of useful, functional educational accessories such as side railings, overhead signs, stoplights, traffic controls, signs and the like to increase the versatility and constructive play value of the various toy systems.

Abstract: A toy track and brick adapter for toy tracks and bricks comprising a base having a top surface and a bottom surface with indentations in the bottom surface of the base for receiving building blocks. A first arm assembly and a second arm assembly mounted to the top surface generally perpendicular to the base distally disposed in a parallel relationship to grip toy tracks. Roadway retention lips are attached to the arm assemblies which in conjunction with the tension springs hold the toy track in place within the toy track and brick adapter. Also attached to the roadway retention lips are pull-tab accessory brackets configured to releasably connect a variety of useful, functional educational accessories such as side railings, overhead signs, stoplights, traffic controls, signs and the like to increase the versatility and constructive play value of the various toy systems.

Abstract: A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.

Abstract: A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.

Abstract: A knowledge management system and methods for crude oil refining are provided. The knowledge management system and methods enable information, such as crude oil characterizations, the experiences of processing crude oils in the refinery, problems encountered during the processing of crude oil in the refinery, and the treatments applied by personnel of the refinery to counteract those problems, to be captured, organized, and disseminated. The knowledge management system and methods for crude oil refining further provide a basis for running analytical models and other decision support applications to assess risks and financial impacts; thus, allowing users to make informed decisions for crude selection and treatment planning.