Continuous Biochemical Processing: Investigating Novel Strategies to Produce Sustainable Fuels and Pharmaceuticals

Biochemical processing methods have been targeted as one of the potential renewable strategies for producing commodities currently dominated by the petrochemical industry. To design biochemical systems with the ability to compete with petrochemical facilities, inroads are needed to transition from traditional batch methods to continuous methods. Recent advancements in the areas of process systems and biochemical engineering have provided the tools necessary to study and design these continuous biochemical systems to maximize productivity and substrate utilization while reducing capital and operating costs. The first goal of this thesis is to propose a novel strategy for the continuous biochemical production of pharmaceuticals. The structural complexity of most pharmaceutical compounds makes chemical synthesis a difficult option, facilitating the need for their biological production. To this end, a continuous, multi-feed bioreactor system composed of multiple independently controlled feeds for substrate(s) and media is proposed to freely manipulate the bioreactor dilution rate and substrate concentrations. The optimal feed flow rates are determined through the solution to an optimal control problem where the kinetic models describing the time-variant system states are used as constraints. This new bioreactor paradigm is exemplified through the batch and continuous cultivation of β-carotene, a representative product of the mevalonate pathway, using Saccharomyces cerevisiae strain mutant SM14. The second goal of this thesis is to design continuous, biochemical processes capable of economically producing alternative liquid fuels. The large-scale, continuous production of ethanol via consolidated bioprocessing (CBP) is examined. Optimal process topologies for the CBP technology selected from a superstructure considering multiple biomass feeds, chosen from those available across the United States, and multiple prospective pretreatment technologies. Similarly, the production of butanol via acetone-butanol-ethanol (ABE) fermentation is explored using process intensification to improve process productivity and profitability. To overcome the inhibitory nature of the butanol product, the multi-feed bioreactor paradigm developed for pharmaceutical production is utilized with in situ gas stripping to simultaneously provide dilution effects and selectively remove the volatile ABE components. Optimal control and process synthesis techniques are utilized to determine the benefits of gas stripping and design a butanol production process guaranteed to be profitable

Algorithms for Imaging Atmospheric Cherenkov Telescopes

Imaging Atmospheric Cherenkov Telescopes (IACTs) are complex instruments for ground-based -ray astronomy and require sophisticated software for the handling of the measured data. In part one of this work, a modular and efficient software framework is presented that allows to run the complete chain from reading the raw data from the telescopes, over calibration, background reduction and reconstruction, to the sky maps. Several new methods and fast algorithms have been developed and are presented. Furthermore, it was found that the currently used file formats in IACT experiments are not optimal in terms of flexibility and I/O speed. Therefore, in part two a new file format was developed, which allows to store the camera and subsystem data in all its complexity. It offers fast lossy and lossless compression optimized for the high data rates of IACT experiments. Since many other scientific experiments also struggle with enormous data rates, the compression algorithm was further optimized and generalized, and is now able to efficiently compress the data of other experiments as well. Finally, for those who prefer to store their data as ASCII text, a fast I/O scheme is presented, including the necessary compression and conversion routines. Although the second part of this thesis is very technical, it might still be interesting for scientists designing an experiment with high data rates

Rival Penalized Competitive Learning Based Separator on Binary Sources Separation

This paper 1 presents an approach named Rival Penalized Competitive Learning based Binary Source Separator (RPCLBSS) , which has two major advantages: (1) fast in implementation, (2) able to automatically determine the number of binary sources, and (3) able to reduce the noise effects. Experiments have shown that RPCL-BSS algorithm can not only find out the correct number of sources quickly, but also be insensitive to Gaussian noise such that the source signals can be exactly recovered under the low-level noise interference. KEYWORDS: Rival Penalized Competitive Learning, Binary Source Separation, Number of Sources, Noise Interference 1. Introduction In recent years, many approaches have been proposed to solve Blind Source Separation (BSS) problems due to its attracting application on wireless communication [1], image processing [2] and so on. Typical examples include Informationmaximization (INFORMAX) [3] , Minimum Mutual Information (MMI) [4] and Learned Parametric Mixture (LPM..

International Conference on Continuous Optimization (ICCOPT) 2019 Conference Book

The Sixth International Conference on Continuous Optimization took place on the campus of the Technical University of Berlin, August 3-8, 2019. The ICCOPT is a flagship conference of the Mathematical Optimization Society (MOS), organized every three years. ICCOPT 2019 was hosted by the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin. It included a Summer School and a Conference with a series of plenary and semi-plenary talks, organized and contributed sessions, and poster sessions. This book comprises the full conference program. It contains, in particular, the scientific program in survey style as well as with all details, and information on the social program, the venue, special meetings, and more

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

Efficient local search for Pseudo Boolean Optimization

Algorithms and the Foundations of Software technolog