Proceedings of the Seventh International Conference Formal Approaches to South Slavic and Balkan languages

Proceedings of the Seventh International Conference Formal Approaches to South Slavic and Balkan Languages publishes 17 papers that were presented at the conference organised in Dubrovnik, Croatia, 4-6 Octobre 2010

Power System Simulation, Control and Optimization

This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence

Information Preserving Processing of Noisy Handwritten Document Images

Many pre-processing techniques that normalize artifacts and clean noise induce anomalies due to discretization of the document image. Important information that could be used at later stages may be lost. A proposed composite-model framework takes into account pre-printed information, user-added data, and digitization characteristics. Its benefits are demonstrated by experiments with statistically significant results. Separating pre-printed ruling lines from user-added handwriting shows how ruling lines impact people\u27s handwriting and how they can be exploited for identifying writers. Ruling line detection based on multi-line linear regression reduces the mean error of counting them from 0.10 to 0.03, 6.70 to 0.06, and 0.13 to 0.02, com- pared to an HMM-based approach on three standard test datasets, thereby reducing human correction time by 50%, 83%, and 72% on average. On 61 page images from 16 rule-form templates, the precision and recall of form cell recognition are increased by 2.7% and 3.7%, compared to a cross-matrix approach. Compensating for and exploiting ruling lines during feature extraction rather than pre-processing raises the writer identification accuracy from 61.2% to 67.7% on a 61-writer noisy Arabic dataset. Similarly, counteracting page-wise skew by subtracting it or transforming contours in a continuous coordinate system during feature extraction improves the writer identification accuracy. An implementation study of contour-hinge features reveals that utilizing the full probabilistic probability distribution function matrix improves the writer identification accuracy from 74.9% to 79.5%

Advances in Character Recognition

This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

Between syntax and morphology

Synopsis: This volume collects novel contributions to comparative generative linguistics that “rethink” existing approaches to an extensive range of phenomena, domains, and architectural questions in linguistic theory. At the heart of the contributions is the tension between descriptive and explanatory adequacy which has long animated generative linguistics and which continues to grow thanks to the increasing amount and diversity of data available to us. The chapters address research questions in comparative morphosyntax, including the modelling of syntactic categories, relative clauses, and demonstrative systems. Many of these contributions show the influence of research by Ian Roberts and collaborators and give the reader a sense of the lively nature of current discussion of topics in morphosyntax and morphosyntactic variation. This book is complemented by volume I available at https://langsci-press.org/catalog/book/275 and volume III available at https://langsci-press.org/catalog/book/277

계산 과학적 접근을 통한 지속가능한 공정의 최적 설계 및 산업에의 응용

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 화학생물공학부, 2018. 2. 이원보.Recently, in the field of chemical engineering, many types of research based on high-performance computing have been combined with computer-aided process systems engineering. Therefore, various techniques of computational science such as computational fluid dynamics, optimization methodology, and machine learning have been applied to the problems of chemical reactor modeling and process optimization. Notably, in this advance computational science approach, the scope of research extends to non-traditional fields such as reactive research according to the 3D shape of the reactor that has not been easily solved in the past and surrogate model based optimization using machine learning. In this thesis, various methods are proposed to obtain the maximum profit with minimum cost by making a breakthrough design. In parallel, there is a growing demand for sustainable chemical processes in chemical engineering. Conventional chemical processes are highly dependent on oil prices, and unless a diverse portfolio is designed, the sustainability of their chemical industries can be violated because of the oil controlling from the Middle East or US. In addition, these crude oil based chemical processes and power plants generate a great deal of CO2. Therefore, it is not necessary to capture these CO2 and make only meaningless storage but to reproduce it as a product that can be used and make it economical carbon capture, utilization, and storage (CCUS) technology. To solve this series of processes, the Gas-to-Liquid (GTL) process and CCUS are being researched and developed in various ways. In this thesis, I will discuss the process modeling, optimizing, and designing the reactor and process using CFD, mathematical programming, machine learning, deep learning, and derivative-free optimization techniques in computational science. First of all, the Fischer-Tropsch microchannel reactor and 3-phase carbonation reactor, which are the key reactor of two most important processes of the sustainable process, the gas-to-liquid process (GTL) and the carbon capture, utilization, and storage (CCUS), are modeled by CFD. Also, we propose an integration platform of CFD model and process simulator and conduct research from the point of view of combining with existing process engineering. With these advanced reactor model, we propose a multi-objective optimization methodology using a stochastic optimization algorithm, a genetic algorithm (GA) with e-constraint method for simultaneously maximizing C5+ productivity and minimizing the temperature rise of a Fischer-Tropsch microchannel reactor. The main mixed integer nonlinear programming (MINLP) optimization problem is decomposed into an external CFD reactor model function and internal optimization constraints. The methodology is applied to the catalyst packing zone division, which is divided and packed with a different dilution ratio to distribute the heat of reaction evenly. The best solutions of the proposed optimizer are reproducible with different crossover fractions and are more efficient than other traditional non-convex constraint local solvers. Based on the Pareto optimal solution of the final optimizer with 4 zones, discrete dilution increases C5+ productivity to 22% and decreases ∆Tmax to 63.2% compared to the single zone catalyst packing case. Finally, several Pareto optimal solutions and sub-optimal solutions are compared and the results are documented in terms of C5+ productivity and maximum temperature increase. In process scale optimization platform, a modified DIRECT algorithm with a sub-dividing step for considering hidden constraints is proposed. The effectiveness of the algorithm is exemplified by its application to a cryogenic mixed refrigerant process using a single mixed refrigerant for natural gas liquefaction and its comparison with a well-known stochastic algorithm (GA, PSO, SA), and model based search algorithm (SNOBFIT), local solver (GPS, GSS, MADS, active-set, interior-point, SQP), and other hidden constraint handling methods, including the barrier approach and the neighborhood assignment strategy. Optimal solution calculated by the proposed algorithms decreases the specific power required for natural gas liquefaction to 18.9% compared to the base case. In the same chapter, heat exchanger network synthesis (HENS) has progressed by using mathematical programming-based simultaneous methodology. Although various considerations such as non-isothermal mixing and bypass streams are applied to consider real world alternatives in modeling phase, many challenges are faced because of its properties within non-convex mixed-integer nonlinear programming (MINLP). We propose a modified superstructure, which contains a utility substage for use in considering multiple utilities in a simultaneous MINLP model. To improve model size and convergence, fixed utility locations according to temperature and series connections between utilities are suggested. The numbers of constraints, discrete, and continuous variables show that overall model size decreases compared with previous research. Thus, it is possible to expand the feasible search area for reaching the nearest global solution. The models effectiveness and applications are exemplified by several literature problems, where it is used to deduce a network superior to that of any other reported methodology. In the case of plant-wide scale systems, a non-linear surrogate model based on deep learning is proposed using a variational autoencoder with deep convolutional layers and a deep neural network with batch normalization (VAEDC-DNN) for real-time analysis of the probability of death (Pdeath). VAEDC can extract representation features of the Pdeath contour with complicated urban geometry in the latent space, and DNN maps the variable space into the latent space for the Pdeath image data. The chlorine gas leak accident in the Mipo complex (city of Ulsan, Republic of Korea) is used for verification of the model. The proposed model predicts the Pdeath image within a mean squared error of 0.00246, and compared with other models, it exhibits superior performance. Furthermore, through the smoothness of image transition in the variable space, it is confirmed that image generation is not overfitting by data memorization. Finally, a pilot scale (1.0 BPD) compact GTL process comprising of reforming section, CO2 separating section and Fischer -Tropsch (FT) synthesis section is presented. Systematic design procedure adopted for the design of a modular 0.5 BPD microchannel FT reactor block design consisting of 528 process channels is described. On average 98.27% CH4 conversion to syngas in reforming section comprising of a pre-reformer unit and a tri-reformer unit, CO2 separation rate of 36.75 % along with CO/H2 reduction from 2.67 to 2.08 in CO2 membrane separation section comprising of three membrane separators, for the entire plant operation duration of 450 hr demonstrated successful and stable operation of pre-processing sections of the present pilot-scale compact GTL process. Parallel operation of FT microchannel reactor and multitubular fixed bed type FT reactor proved failure for latter due to reaction runaway, while the former showed stable operation with high CO conversion of 83% and successful temperature control (at 220 oC, 230 oC and at 240 oC during the 139 hr operation), which demonstrated the appreciable performance of KOGAS-SNU novel microchannel FT reactor. Furthermore, a tank agitator carbonation reactor in which the reaction between calcium oxide and carbon dioxide takes place is studied to understanding that how 6 design variables (the number of impeller, impeller type, D/T, clearance, speed, baffle) affect to the solid dispersion using CFD simulation.CHAPTER 1. Introduction 17 1.1. Research motivation 17 1.1.1. Chronological stages of development of process design 19 1.1.2. Current status of process systems engineering with computational science approach 21 1.1.3. Introduction to the sustainable process 23 1.2. Research objectives 25 1.3. Outline of the thesis 26 1.4. Associated publications 29 CHAPTER 2. Study of the Novel Reactor Models using Computational Science 30 2.1. Introduction 30 2.2. Gas-to-Liquid (GTL) Fischer-Tropsch (FT) reactor model 32 2.2.1. 2D axisymmetric computational fluid dynamics (CFD) based Fischer-Tropsch microchannel reactor single-channel model 37 2.2.2. 3D CFD based Fischer-Tropsch microchannel reactor multi-channel model 52 2.3. Carbon Capture, Utilization, and Storage (CCUS) multiphase carbonation reactor model 75 2.3.1. Rigorous reaction kinetics for carbonation based CCUS reactor 77 2.3.2. Eulerian multiphase model for carbonation reactor 92 2.4. CFD-Process integrated platform for simultaneous process and reactor design 105 2.4.1. Introduction 105 2.4.2. Model formulation 106 2.4.3. Result and discussion 112 2.4.4. Conclusion 116 CHAPTER 3. Optimization for the Unit, Process, and Plant-wide Systems 117 3.1. Introduction 117 3.2. Reactor systems scale optimization 119 3.2.1. Multi-objective optimization of microchannel reactor for Fischer-Tropsch synthesis using computational fluid dynamics and genetic algorithm 119 3.3. Process systems scale optimization 152 3.3.1. A modified DIRECT algorithm for hidden constraints optimization problem 152 3.3.2. Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages 200 3.4. Plant-wide systems scale modeling and optimization 233 3.4.1. Toxic gas release modeling for real-time analysis using variational autoencoder with convolution neural networks 233 CHAPTER 4. Industrial Applications 276 4.1. Optimal Design and Operation of Fischer-Tropsch Microchannel Reactor for Pilot Scale Compact Gas-to-Liquid Process 276 4.1.1. Pilot scale compact GTL process 277 4.1.2. Microchannel FT reactor design 286 4.1.3. Pilot plant experiment 287 4.1.4. Result and discussion 291 4.1.5. Conclusion 304 4.2. Industrial scale (40 tonCO2/day) CCUS carbonation reactor geometry design optimization 306 4.2.1. Design procedure and simulation set-up 310 4.2.2. Result and Discussion 313 4.2.3. Conclusion 332 CHAPTER 5. Concluding Remarks 334 5.1. Summary of Contributions 334 5.2. Future Work 337 Nomenclature 340 Reference 346 Abstract in Korean (국문초록) 360Docto

Syntactic architecture and its consequences II

This volume collects novel contributions to comparative generative linguistics that “rethink” existing approaches to an extensive range of phenomena, domains, and architectural questions in linguistic theory. At the heart of the contributions is the tension between descriptive and explanatory adequacy which has long animated generative linguistics and which continues to grow thanks to the increasing amount and diversity of data available to us. The chapters address research questions in comparative morphosyntax, including the modelling of syntactic categories, relative clauses, and demonstrative systems. Many of these contributions show the influence of research by Ian Roberts and collaborators and give the reader a sense of the lively nature of current discussion of topics in morphosyntax and morphosyntactic variation. This book is complemented by volume I available at https://langsci-press.org/catalog/book/275 and volume III available at https://langsci-press.org/catalog/book/277