Certain fundamental principles are common to all distilling systems. Modern distillation systems are multi-stage, continuous, countercurrent, vapor-liquid contacting systems that operate within the physical laws that state that different materials boil at different temperatures. Represented in Figure 1 is a typical distillation tower that could be employed to separate an ideal mixture. Such a s...

LabVIEW and SIMULINK are two most widely used graphical programming environments for designing digital signal processing and control systems. Unlike conventional text-based programming languages such as C, C++ and MATLAB, graphical programming involves block-based code developments, allowing a more efficient mechanism to build and analyze control systems. In this paper a LabVIEW environment has...

In this work, we analyze the control properties of thermally coupled reactive distillation sequences and thermally coupled extractive distillation sequences in comparison with conventional reactive and extractive distillation configurations. All sequences have been designed using a multi objective genetic algorithm with restrictions. We study the theoretical control properties of those schemes ...

Neural machine translation (NMT) offers a novel alternative formulation of translation that is potentially simpler than statistical approaches. However to reach competitive performance, NMT models need to be exceedingly large. In this paper we consider applying knowledge distillation approaches (Bucila et al., 2006; Hinton et al., 2015) that have proven successful for reducing the size of neura...

The paper considers the effect of feed plate location on the interactions in a seven plate binary distillation column. The mathematical model of the distillation column is deduced based on the equations of mass and energy balances for each stage, detailed model for both reboiler and condenser, and heat transfer equations. The Dynamic Relative Magnitude Criterion, DRMC is used to assess the inte...

Model distillation compresses a trained machine learning model, such as a neural network, into a smaller alternative such that it could be easily deployed in a resource limited setting. Unfortunately, this requires engineering two architectures: a student architecture smaller than the first teacher architecture but trained to emulate it. In this paper, we present a distillation strategy that pr...

Membrane distillation is an emerging water distillation technology that offers several advantages compared to conventional water desalination processes. Although progress has been made to model and understand the physics of the process, many studies are based on steady-state assumptions or are computationally not appropriate for real time control. This paper presents the derivation of a novel d...

It has been shown that entanglement distillation of Gaussian entangled states by means of local photon subtraction can be improved by local Gaussian transformations. Here we show that a similar effect can be expected for the distillation of an asymmetric Gaussian entangled state that is produced by a single squeezed beam. We show that for low initial entanglement, our largely simplified protoco...

Information distillation aims to analyze and interpret large volumes of speech and text archives in multiple languages and produce structured information of interest to the user. In this work, we investigate cross-lingual information distillation, where nonEnglish (source language) documents are searched for user queries that are in English (target language). We propose to perform distillation ...

The stringent quality requirement of petroleum products in highly competitive markets makes on-line controlling of distillation composition essential. In this paper, a novel method using sensitivity matrix analysis and kernel ridge regression to implement on-line estimation of distillation compositions is proposed. In the approach, the sensitivity matrix analysis is presented to select the most...