A novel MINLP-based representation of the original complex model for predicting gasoline emissions

The Environmental Protection Agency (EPA) introduced Reformulated Gasoline (RFG) requirements as a measure to reduce emissions from gasoline-powered vehicles in certain geographic areas. As part of this effort, the EPA developed empirical models for predicting emissions as a function of gasoline properties and established statutory baseline emissions from a representative set of gasolines. All reformulated gasoline requires certification via this model, known as the Complex Model, and all refiners and importers calculate emissions performance reductions from the statutory baseline gasoline. The current representation of the Complex Model is extremely difficult to implement within refinery operations models or to use in combination with models for designer gasoline. RFG and boutique fuels are key driving forces in the North American refining industry.The RFG models introduce increasingly complex constraints with the major limitation that they are implicitly defined through a series of complicated disjunctions assembled by the EPA in the form of spreadsheets. This implicit and cumbersome representation of the emissions predictive models renders rigorous optimization and sensitivity analysis very difficult to address directly. In this paper, we discuss how the federal government requirements for reformulated gasoline can be restated as a set of mixed-integer nonlinear programming (MINLP) constraints with the aid of disjunctive programming techniques. We illustrate the use of this model with two simple example fuel blending problems.     

Application of a Three-dimensional Wind Driven Circulation Model to Assess the Locations of New Drinking Water Intakes in Lake Ontario

A 3D transport model is used to perform a comparative analysis of several potential drinking water intakes located along the northwest shore of Lake Ontario between Toronto and Oshawa. The model is specifically used to assess each intake under both long- and short-term transport of a potential pollutant release from the Pickering Nuclear Generating Station and potential and actual pollutant releases from local land sources respectively. A model based on a 500 m grid resolution is calibrated using data collected in the aftermath of the 1992 tritium spill at the Pickering Nuclear Generation Station and subsequently used to simulate long-term transport. A model based on a 100 m grid resolution is verified using drogue studies and used to simulate short-term transport events. Both models are used to assess pollutant levels at each of nine potential intake locations under different wind scenarios and pollutant releases. Field data for the study included water quality and flow measurements from local sewers and rivers, and estimates of pollutant levels from the local waste water treatment plants. This paper describes the model setup for both the long-term and short-term transport models, calibration using field data, long-term transport modeling, short-term transport modeling, and the comprehensive analysis approach used to evaluate the nine potential intake locations proposed. Results indicated that four intakes in particular outperformed other intake locations by maintaining bottom pollutant levels within governmental standards and warning times that exceeded 20 hours.     

Effects of mastication on the distribution of molecular weights and on the mechanical properties of native and commercial dental gutta percha (trans-polyisoprene)

Mastication of gutta percha (trans-polyisoprene) resulted in the selective scission of molecules, producing a narrower distribution of lower molecular weights. The mechanical properties of the samples also underwent a significant change due to mastication. The greater the content of incompatible substances (salts and oxides) in commercial gutta percha. the more substantial were these effects. The atmosphere (air, N₂, O₂) in which the experiments were conducted yielded significantly different results. The decrease in molecular weight was far greater in an O₂ atmosphere than under a current of nitrogen or air, owing to the combination of double bonds with O₂.     

Response surface methodology applied for Orange II photocatalytic degradation in TiO2 aqueous suspensions

BACKGROUND: Heterogeneous photocatalysis is influenced by a number of parameters involving synergistic effects; hence, an experimental strategy design that considers interactions between the main variables is needed. The response surface methodology was applied for the investigation of photodegradation of 20 mg L^?1 Orange II in aqueous solutions and for optimization of color removal efficiency. Preliminary studies were performed to identify the parameters to be selected for optimization. RESULTS: The input variables considered for experimental design were: solution initial pH, oxidizing agent (H₂O₂) initial concentration and UV‐A irradiation time. The multivariate experimental design allowed the development of a quadratic response surface model to be used for the prediction of color removal efficiency over the full range of the experimental region. Under the optimum conditions established in the region of experimentation (pH = 6.9, [H₂O₂]₀ = 183 mg L^?1 and t = 32 min), a 100% color removal efficiency was obtained in experiments. CONCLUSIONS: It was found that the variables considered have important effects on color removal efficiency. The results demonstrate that the use of experimental design strategy is indispensable for successful investigation and adequate modeling of the process because the interdependence of the reaction parameters cannot be neglected. Copyright © 2008 Society of Chemical Industry     

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and best cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.     

From Natural Methylation to Versatile Alkylations Using Halide Methyltransferases

Halide methyltransferases (HMTs) enable the enzymatic synthesis of S-adenosyl-l -methionine (SAM) from S-adenosyl-l -homocysteine (SAH) and methyl iodide. Characterisation of a range of naturally occurring HMTs and subsequent protein engineering led to HMT variants capable of synthesising ethyl, propyl, and allyl analogues of SAM. Notably, HMTs do not depend on chemical synthesis of methionine analogues, as required by methionine adenosyltransferases (MATs). However, at the moment MATs have a much broader substrate scope than the HMTs. Herein we provide an overview of the discovery and engineering of promiscuous HMTs and how these strategies will pave the way towards a toolbox of HMT variants for versatile chemo- and regioselective biocatalytic alkylations.     

ROSy+: 3D Object Pose Normalization Based on PCA and Reflective Object Symmetry with Application in 3D Object Retrieval

A novel pose normalization method based on 3D object reflective symmetry is presented. It is a general purpose global pose normalization method; in this paper it is used to enhance the performance of a 3D object retrieval pipeline. Initially, the axis-aligned minimum bounding box of a rigid 3D object is modified by requiring that the 3D object is also in minimum angular difference with respect to the normals to the faces of its bounding box. To estimate the modified axis-aligned bounding box, a set of predefined planes of symmetry are used and a combined spatial and angular distance, between the 3D object and its symmetric object, is calculated. By minimizing the combined distance, the 3D object fits inside its modified axis-aligned bounding box and alignment with the coordinate system is achieved. The proposed method is incorporated in a hybrid scheme, that serves as the alignment method in a 3D object retrieval system. The effectiveness of the 3D object retrieval system, using the hybrid pose normalization scheme, is evaluated in terms of retrieval accuracy and demonstrated using both quantitative and qualitative measures via an extensive consistent evaluation on standard benchmarks. The results clearly show performance boost against current approaches.