Processes

3373 KiB

Open AccessArticle

Hybrid Dynamic Optimization Methods for Systems Biology with Efficient Sensitivities

by Nicholas R. Lewis, John D. Hedengren and Eric L. Haseltine

Processes 2015, 3(3), 701-729; https://doi.org/10.3390/pr3030701 - 21 Sep 2015

Cited by 10 | Viewed by 9305

In recent years, model optimization in the field of computational biology has become a prominent area for development of pharmaceutical drugs. The increased amount of experimental data leads to the increase in complexity of proposed models. With increased complexity comes a necessity for [...] Read more.

In recent years, model optimization in the field of computational biology has become a prominent area for development of pharmaceutical drugs. The increased amount of experimental data leads to the increase in complexity of proposed models. With increased complexity comes a necessity for computational algorithms that are able to handle the large datasets that are used to fit model parameters. In this study the ability of simultaneous, hybrid simultaneous, and sequential algorithms are tested on two models representative of computational systems biology. The first case models the cells affected by a virus in a population and serves as a benchmark model for the proposed hybrid algorithm. The second model is the ErbB model and shows the ability of the hybrid sequential and simultaneous method to solve large-scale biological models. Post-processing analysis reveals insights into the model formulation that are important for understanding the specific parameter optimization. A parameter sensitivity analysis reveals shortcomings and difficulties in the ErbB model parameter optimization due to the model formulation rather than the solver capacity. Suggested methods are model reformulation to improve input-to-output model linearity, sensitivity ranking, and choice of solver. Full article

(This article belongs to the Special Issue Algorithms and Applications in Dynamic Optimization)

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101 KiB

Open AccessCorrection

Song, H.-S., et al. Mathematical Modeling of Microbial Community Dynamics: A Methodological Review. Processes 2014, 2, 711–752

by Hyun-Seob Song, William R. Cannon, Alexander S. Beliaev and Allan Konopka

Processes 2015, 3(3), 699-700; https://doi.org/10.3390/pr3030699 - 14 Sep 2015

Cited by 4 | Viewed by 5238

Abstract

The authors wish to make the following correction to this paper [1]. Due to mislabeling, replace: [...] Full article

(This article belongs to the Special Issue Microbial Community Modeling: Prediction of Microbial Interactions and Community Dynamics)

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390 KiB

Open AccessArticle

A Techno-Economic Comparison between Two Methanol-to-Propylene Processes

by Sarah Jasper and Mahmoud M. El-Halwagi

Processes 2015, 3(3), 684-698; https://doi.org/10.3390/pr3030684 - 11 Sep 2015

Cited by 61 | Viewed by 24298 | Correction

Abstract

The significant increase in natural/shale gas production in the US is causing major changes in the chemical and petrochemical markets. These changes include the increased supply of methanol and the decreased supply of propylene. As such, there are promising opportunities for methanol-to-propylene processes [...] Read more.

The significant increase in natural/shale gas production in the US is causing major changes in the chemical and petrochemical markets. These changes include the increased supply of methanol and the decreased supply of propylene. As such, there are promising opportunities for methanol-to-propylene processes in the US. This paper provides a top-level techno-economic analysis of two pathways: methanol to olefins (MTO) and methanol to propylene (MTP). Base-case scenarios are simulated using ASPEN Plus to obtain the key mass and energy balances as well as design data. For each process, two scenarios are considered for the feedstock: buying methanol versus making it from natural gas. The return on investment (ROI) is calculated for both processes under broad ranges of the prices of natural gas, methanol, and products. In addition to the techno-economic analysis, the CO₂ emissions are evaluated and compared. Full article

(This article belongs to the Special Issue Sustainable Products and Processes)

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880 KiB

Open AccessArticle

Conceptual Design of an Operator Training Simulator for a Bio-Ethanol Plant

by Inga Gerlach, Volker C. Hass and Carl-Fredrik Mandenius

Processes 2015, 3(3), 664-683; https://doi.org/10.3390/pr3030664 - 09 Sep 2015

Cited by 12 | Viewed by 10835

Abstract

Conceptual design methodology for the configuration and procedural training with an operating training simulator (OTS) in a large-scale plant for commercial bio-ethanol production is described. The aim of the study is to show how the methodology provides a powerful way for finding the [...] Read more.

Conceptual design methodology for the configuration and procedural training with an operating training simulator (OTS) in a large-scale plant for commercial bio-ethanol production is described. The aim of the study is to show how the methodology provides a powerful way for finding the best configuration and training structure of the OTS before constructing and implementing the software of the OTS. The OTS principle, i.e., to use a computer-based virtual representation of the real process plant intended for efficient training of process operators, has long since been applied in aviation and process industries for more efficient and flawless operations. By using the conceptual design methodology (sometimes referred to as bio-mechatronics) a variety of OTS configurations with this capacity was generated. The systematic approach of for targeting the users’ (i.e., the plant management and process operators) needs resulted in better understanding and efficiency in training of hands-on skills in operating the plant. The training included general standard operating procedures for running the plant under normal operation conditions with different starch materials, handling of typical frequent disturbances as well as acting in situations not described in the standard operation procedures and applying trouble-shooting. Full article

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687 KiB

Open AccessReview

Design of Sustainable Biofuel Processes and Supply Chains: Challenges and Opportunities

by George G. Zaimes, Nemi Vora, Shauhrat S. Chopra, Amy E. Landis and Vikas Khanna

Processes 2015, 3(3), 634-663; https://doi.org/10.3390/pr3030634 - 20 Aug 2015

Cited by 35 | Viewed by 16433

Abstract

The current methodological approach for developing sustainable biofuel processes and supply chains is flawed. Life cycle principles are often retrospectively incorporated in the design phase resulting in incremental environmental improvement rather than selection of fuel pathways that minimize environmental impacts across the life [...] Read more.

The current methodological approach for developing sustainable biofuel processes and supply chains is flawed. Life cycle principles are often retrospectively incorporated in the design phase resulting in incremental environmental improvement rather than selection of fuel pathways that minimize environmental impacts across the life cycle. Further, designing sustainable biofuel supply chains requires joint consideration of economic, environmental, and social factors that span multiple spatial and temporal scales. However, traditional life cycle assessment (LCA) ignores economic aspects and the role of ecological goods and services in supply chains, and hence is limited in its ability for guiding decision-making among alternatives—often resulting in sub-optimal solutions. Simultaneously incorporating economic and environment objectives in the design and optimization of emerging biofuel supply chains requires a radical new paradigm. This work discusses key research opportunities and challenges in the design of emerging biofuel supply chains and provides a high-level overview of the current “state of the art” in environmental sustainability assessment of biofuel production. Additionally, a bibliometric analysis of over 20,000 biofuel research articles from 2000-to-present is performed to identify active topical areas of research in the biofuel literature, quantify the relative strength of connections between various biofuels research domains, and determine any potential research gaps. Full article

(This article belongs to the Special Issue Sustainable Products and Processes)

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349 KiB

Open AccessArticle

The Production of Vinyl Acetate Monomer as a Co-Product from the Non-Catalytic Cracking of Soybean Oil

by Benjamin Jones, Michael Linnen, Brian Tande and Wayne Seames

Processes 2015, 3(3), 619-633; https://doi.org/10.3390/pr3030619 - 14 Aug 2015

Cited by 8 | Viewed by 21395

Abstract

Valuable chemical by-products can increase the economic viability of renewable transportation fuel facilities while increasing the sustainability of the chemical and associated industries. A study was performed to demonstrate that commercial quality chemical products could be produced using the non-catalytic cracking of crop [...] Read more.

Valuable chemical by-products can increase the economic viability of renewable transportation fuel facilities while increasing the sustainability of the chemical and associated industries. A study was performed to demonstrate that commercial quality chemical products could be produced using the non-catalytic cracking of crop oils. Using this decomposition technique generates a significant concentration of C2−C10 fatty acids which can be isolated and purified as saleable co-products along with transportation fuels. A process scheme was developed and replicated in the laboratory to demonstrate this capability. Using this scheme, an acetic acid by-product was isolated and purified then reacted with ethylene derived from renewable ethanol to generate a sample of vinyl acetate monomer. This sample was assessed by a major chemical company and found to be of acceptable quality for commercial production of polyvinyl acetate and other products. Full article

(This article belongs to the Special Issue Sustainable Products and Processes)

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205 KiB

Open AccessReview

Systems Biology of the Fluxome

by Miguel A. Aon and Sonia Cortassa

Processes 2015, 3(3), 607-618; https://doi.org/10.3390/pr3030607 - 22 Jul 2015

Cited by 13 | Viewed by 8767

Abstract

The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. [...] Read more.

The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms. Full article

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3616 KiB

Open AccessArticle

Methods and Tools for Robust Optimal Control of Batch Chromatographic Separation Processes

by Anders Holmqvist, Christian Andersson, Fredrik Magnusson and Johan Åkesson

Processes 2015, 3(3), 568-606; https://doi.org/10.3390/pr3030568 - 16 Jul 2015

Cited by 10 | Viewed by 9553

Abstract

This contribution concerns the development of generic methods and tools for robust optimal control of high-pressure liquid chromatographic separation processes. The proposed methodology exploits a deterministic robust formulation, that employs a linearization of the uncertainty set, based on Lyapunov differential equations to generate [...] Read more.

This contribution concerns the development of generic methods and tools for robust optimal control of high-pressure liquid chromatographic separation processes. The proposed methodology exploits a deterministic robust formulation, that employs a linearization of the uncertainty set, based on Lyapunov differential equations to generate optimal elution trajectories in the presence of uncertainty. Computational tractability is obtained by casting the robust counterpart problem in the framework of bilevel optimal control where the upper level concerns forward simulation of the Lyapunov differential equation, and the nominal open-loop optimal control problem augmented with the robustified target component purity inequality constraint margin is considered in the lower level. The lower-level open-loop optimal control problem, constrained by spatially discretized partial differential equations, is transcribed into a finite dimensional nonlinear program using direct collocation, which is then solved by a primal-dual interior point method. The advantages of the robustification strategy are highlighted through the solution of a challenging ternary complex mixture separation problem for a hydrophobic interaction chromatography system. The study shows that penalizing the changes in the zero-order hold control gives optimal solutions with low sensitivity to uncertainty. A key result is that the robustified general elution trajectories outperformed the conventional linear trajectories both in terms of recovery yield and robustness. Full article

(This article belongs to the Special Issue Algorithms and Applications in Dynamic Optimization)

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739 KiB

Open AccessArticle

Multi-Period Dynamic Optimization for Large-Scale Differential-Algebraic Process Models under Uncertainty

by Ian D. Washington and Christopher L.E. Swartz

Processes 2015, 3(3), 541-567; https://doi.org/10.3390/pr3030541 - 14 Jul 2015

Cited by 1 | Viewed by 5273

Abstract

A technique for optimizing large-scale differential-algebraic process models under uncertainty using a parallel embedded model approach is developed in this article. A combined multi-period multiple-shooting discretization scheme is proposed, which creates a significant number of independent numerical integration tasks for each shooting interval [...] Read more.

A technique for optimizing large-scale differential-algebraic process models under uncertainty using a parallel embedded model approach is developed in this article. A combined multi-period multiple-shooting discretization scheme is proposed, which creates a significant number of independent numerical integration tasks for each shooting interval over all scenario/period realizations. Each independent integration task is able to be solved in parallel as part of the function evaluations within a gradient-based non-linear programming solver. The focus of this paper is on demonstrating potential computation performance improvement when the embedded differential-algebraic equation model solution of the multi-period discretization is implemented in parallel. We assess our parallel dynamic optimization approach on two case studies; the first is a benchmark literature problem, while the second is a large-scale air separation problem that considers a robust set-point transition under parametric uncertainty. Results indicate that focusing on the speed-up of the embedded model evaluation can significantly decrease the overall computation time; however, as the multi-period formulation grows with increased realizations, the computational burden quickly shifts to the internal computation performed within the non-linear programming algorithm. This highlights the need for further decomposition, structure exploitation and parallelization within the non-linear programming algorithm and is the subject for further investigation. Full article

(This article belongs to the Special Issue Algorithms and Applications in Dynamic Optimization)

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228 KiB

Open AccessEditorial

Special Issue on “Modeling and Analysis of Signal Transduction Networks” in the Journal Processes

by Juergen Hahn

Processes 2015, 3(3), 540; https://doi.org/10.3390/pr3030540 - 13 Jul 2015

Viewed by 3644

Abstract

Biological pathways, such as signaling networks, are a key component of the biological systems of each living cell. [...] Full article

(This article belongs to the Special Issue Modeling and Analysis of Signal Transduction Networks)

1271 KiB

Open AccessArticle

Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

by Daniel J. Garcia and Fengqi You

Processes 2015, 3(3), 514-539; https://doi.org/10.3390/pr3030514 - 13 Jul 2015

Cited by 26 | Viewed by 7488

Abstract

The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters [...] Read more.

The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water), and maximization of energy output per liter of water consumed (energy efficiency of water). A mixed integer, multiobjective nonlinear fractional programming (MINLFP) model is formulated. A mixed integer linear programing (MILP)-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP) subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline). A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers. Full article

(This article belongs to the Special Issue Sustainable Products and Processes)

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1412 KiB

Open AccessArticle

The Effects of Solvent and Added Bases on the Protection of Benzylamines with Carbon Dioxide

by Amy L. Ethier, Jackson R. Switzer, Amber C. Rumple, Wilmarie Medina-Ramos, Zhao Li, Jason Fisk, Bruce Holden, Leslie Gelbaum, Pamela Pollet, Charles A. Eckert and Charles L. Liotta

Processes 2015, 3(3), 497-513; https://doi.org/10.3390/pr3030497 - 25 Jun 2015

Cited by 16 | Viewed by 9112

Abstract

The introduction and removal of protecting groups is ubiquitous in multi-step synthetic schemes. From a green chemistry standpoint, however, alternative strategies that employ in situ and reversible protection and deprotection sequences would be attractive. The reversible reactions of CO₂ with amines could [...] Read more.

The introduction and removal of protecting groups is ubiquitous in multi-step synthetic schemes. From a green chemistry standpoint, however, alternative strategies that employ in situ and reversible protection and deprotection sequences would be attractive. The reversible reactions of CO₂ with amines could provide a possible vehicle for realizing this strategy. Herein, we present (1) the products of reaction of benzylamines with CO₂ in a variety of solvents with and without the presence of basic additives; (2) new adducts associated with CO₂ protected benzylamine in acetonitrile containing 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU); and (3) the intermolecular competitive acylation of benzylamine and benzyl alcohol and the intramolecular competitive acylation of (4-aminomethyl)phenyl) methanol with isopropenyl acetate in acetonitrile containing DBU in the absence and presence of CO₂. Full article

(This article belongs to the Special Issue Sustainable Products and Processes)

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Processes, Volume 3, Issue 3 (September 2015) – 12 articles , Pages 497-729

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