Kyu Suk Hwang

Design of a Fully Thermally Coupled Distillation Column for Hexane Process Using a Semi-Rigorous Model

An industrial scale hexane process is designed for the implementation of a fully thermally coupled distillation column (FTCDC). A semi-rigorous material balance and Peng-Robinson equilibrium relation are utilized in the structural design. The operational design is conducted with a commercial design program, the HYSYS. The design outcome of the structural design indicates it to be comparable with the practical system of a conventional two-column arrangement in field operation, which shows the effectiveness of the design procedure implemented here. The procedure is good for the system of many components found from actual field applications. In addition, an investigation of the energy requirement of the FTCDC and a conventional system shows that an energy saving of 34.1% is available with the FTCDC.

A gene clustering method with masking cross-matching fragments using modified suffix tree clustering method

Multiple sequence alignment is a method for comparing two or more DNA or protein sequences. Most multiple sequence alignment methods rely on pairwise alignment and Smith-Waterman algorithm [Needleman and Wunsch, 1970; Smith and Waterman, 1981] to generate an alignment hierarchy. Therefore, as the number of sequences increases, the runtime increases exponentially. To resolve this problem, this paper presents a multiple sequence alignment method using a parallel processing suffix tree algorithm to search for common subsequences at one time without pairwise alignment. The cross-matched subsequences among the searched common subsequences may be generated and those cause inexact-matching. So the procedure of masking cross-matching pairs was suggested in this study. The proposed method, improved STC (Suffix Tree Clustering), is summarized as follows: (1) construction of suffix tree; (2) search and overlap of common subsequences; (3) grouping of subsequence pairs; (4) masking of cross-matching airs; and (5) clustering of gene sequences. The new method was successfully evaluated with 23 genes inMus musculus and 22 genes in three species, clustering nine and eight clusters, respectively.

Process identification for second-order plus dead time model using pulse input

A new method of process identification for a second-order plus dead time model is proposed and tested with two example systems. In the activation of the example processes for the identification, a rectangular pulse input is applied to open loop systems. The estimation of model parameters is conducted by minimizing sum of modeling errors with the least squares method. The estimation performance is examined by comparing the pulse responses from the example system and the estimated model. The performance comparison of the proposed method and two existing techniques indicates that satisfactory parameter estimation is available from the proposed procedure. In addition, the role of sampling time and the aspect ratio of input pulse is examined and the noise robustness of the estimation in noisy process is investigated.

Fenske and Kremser Group Methods in the Design of Fully Thermally Coupled Distillation Column

Abstract The design of fully thermally distillation column is more complex than conventional arrangements due to greater number of degrees of freedom. This paper introduces a new structure design method to determine the structure of column system. The method combines approximate group method and Fenske equation for minimum equilibrium stage which is applied to three column model. The usefulness of the design method is explored using different feed systems. This design procedure gives an optimum structure for a given ternary separation. The method provides an initial design from which thermodynamic efficiency and optimal internal flow distribution are examined.

Gene Sequences Clustering and Identifying Functional Domain Using a Suffix Tree Algorithm

Most multiple gene sequence alignment methods rely on conventions regarding the score of a multiple alignment by pairwise alignment. Therefore, as the number of sequences increases, the runtime of sequencing expands exponentially In order to solve the problem, this paper presents a multiple sequence alignment method using a linear-time suffix tree algorithm to cluster similar sequences at one time without pairwise alignment. After searching for common subsequences, cross-matching common subsequences were generated, and sometimes inexact matching was found. So, a procedure aimed at masking the inexact cross-matching pairs was suggested here. In addition, BLAST was combined with a clustering tool in order to annotate the clusters generated by suffix tree clustering. The performance of the proposed system, CLAGen, was successfully evaluated with 42 gene sequences in a TCA cycle (a citrate cycle) of bacteria, identifying 11 clusters

An automatic synthesis system for start-up operating procedures of boiler plants

As boiler plants which supply steam and heat into chemical plants become larger in scale and more complicated, accidents caused by the wrong understanding and erroneous operations are increasing. In this paper, we present a computer-aided system that should prevent such mistakes and synthesize operating procedures for start-up of steam boiler plants: 1) This system generates a goal tree by generalizing and classifying the operational situations hierarchically, and uses the relationship between an operation and a function to search for primitive operations in the lowest level of the goal tree. 2) It simulates changes in operational situations caused by the action of primitive operations with heuristic knowledge of transition relationships between operational situations. 3) It determines the priority of low-level operational situations and primitive operations by referring to the database on hazardous situations and properties. We have applied the developed system to a large-scale boiler plant to demonstrate its effectiveness.

Process Identification for an SOPDT Model Using Rectangular Pulse Input

A new method of process identification for a second-order-plus-dead-time model is proposed and tested with two example systems. In the activation of the example processes for the identification, a rectangular pulse input is applied to open loop systems. The model parameters are estimated by minimizing sum of modeling errors with the least squares method. The estimation performance is examined by comparing the output pulse responses from the example system and the estimated model. The performance comparison of the proposed method and two existing techniques indicates that satisfactory parameter estimation is available from the proposed procedure. In addition, the role of sampling time and the shape of input pulse is evaluated and it is found that the sampling time of less than 0.01 minute gives good estimation while the shape of input pulse does not affect the estimation performance. Finally, the robustness of the estimation in noisy process is proved from the investigation of the performance in the processes having various levels of noise.

An Operating Procedure Synthesis Method for Shutdown of Boiler Plants

Abstract A method is proposed which automatically synthesizes a safe operating procedure based on the knowledge of human operators that are generalized and classified hierarchically. The proposed method automatically generates and orders subgoals that must be achieved between the initial state and the goal state. It searches for the primitive operation device to achieve each subgoal subject to the operational constraints, and evaluates the safety of the operation. A case study of automatic synthesis of a boiler plant shutdown procedure shows the industrial applicability of the proposed method.