Multiscale metabolic modeling of C4 plants: connecting nonlinear genome-scale models to leaf-scale metabolism in developing maize leaves

C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve the efficiency of carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and oxygen levels and reaction rates are key to their physiology but cannot be handled with standard techniques of constraint-based metabolic modeling. We demonstrate that incorporating these relationships as constraints on reaction rates and solving the resulting nonlinear optimization problem yields realistic predictions of the response of C4 systems to environmental and biochemical perturbations. Using a new genome-scale reconstruction of maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll and bundle sheath cells in 15 segments of the developing maize leaf, interacting via metabolite exchange, and use RNA-seq and enzyme activity measurements to predict spatial variation in metabolic state by a novel method that optimizes correlation between fluxes and expression data. Though such correlations are known to be weak in general, here the predicted fluxes achieve high correlation with the data, successfully capture the experimentally observed base-to-tip transition between carbon-importing tissue and carbon-exporting tissue, and include a nonzero growth rate, in contrast to prior results from similar methods in other systems. We suggest that developmental gradients may be particularly suited to the inference of metabolic fluxes from expression data.Comment: 57 pages, 14 figures; submitted to PLoS Computational Biology; source code available at http://github.com/ebogart/fluxtools and http://github.com/ebogart/multiscale_c4_sourc

Diseño para operabilidad: Una revisión de enfoques y estrategias de solución

In the last decades the chemical engineering scientific research community has largely addressed the design-foroperability problem. Such an interest responds to the fact that the operability quality of a process is determined by design, becoming evident the convenience of considering operability issues in early design stages rather than later when the impact of modifications is less effective and more expensive. The necessity of integrating design and operability is dictated by the increasing complexity of the processes as result of progressively stringent economic, quality, safety and environmental constraints. Although the design-for-operability problem concerns to practically every technical discipline, it has achieved a particular identity within the chemical engineering field due to the economic magnitude of the involved processes. The work on design and analysis for operability in chemical engineering is really vast and a complete review in terms of papers is beyond the scope of this contribution. Instead, two major approaches will be addressed and those papers that in our belief had the most significance to the development of the field will be described in some detail.En las últimas décadas, la comunidad científica de ingeniería química ha abordado intensamente el problema de diseño-para-operabilidad. Tal interés responde al hecho de que la calidad operativa de un proceso esta determinada por diseño, resultando evidente la conveniencia de considerar aspectos operativos en las etapas tempranas del diseño y no luego, cuando el impacto de las modificaciones es menos efectivo y más costoso. La necesidad de integrar diseño y operabilidad esta dictada por la creciente complejidad de los procesos como resultado de las cada vez mayores restricciones económicas, de calidad de seguridad y medioambientales. Aunque el problema de diseño para operabilidad concierne a prácticamente toda disciplina, ha adquirido una identidad particular dentro de la ingeniería química debido a la magnitud económica de los procesos involucrados. El trabajo sobre diseño y análisis para operabilidad es realmente vasto y una revisión completa en términos de artículos supera los alcances de este trabajo. En su lugar, se discutirán los dos enfoques principales y aquellos artículos que en nuestra opinión han tenido mayor impacto para el desarrollo de la disciplina serán descriptos con cierto detalle.Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Applied novel software development methodology for process engineering application

Chemical processes are nonlinear continuous/discrete dynamic systems that are subject to considerable uncertainties and variations during their design and operation. These systems are designed to operate at an economically optimal steady-state. However, minor changes in process parameters’ values might cause deviations and elicit dynamic responses from processes. Controllability—defined as the ability of holding a process within a specified operating regime and the controllability assessment of each given process system—should be taken into account during the system design phase. This emphasises the necessity of effective software tools that could assist process engineers in their controllability evaluation. Although there are few multipurpose tools available for this task, developing software tools for controllability analysis is a tedious and sophisticated undertaking. It involves elaboration from multiple disciplines, and the requirements of controllability assessments are so vast that it is almost impossible to create general software that covers all controllability measures and cases. This thesis aims to systematically tackle the challenge of developing practical and high-quality software tools for controllability problems while reducing the required time and effort, regardless of the size and scale of the controllability problem. Domain-specific language (DSL) methodology is proposed for this purpose. DSLs are programming languages designed to address the programming problems of a specific domain. Therefore, well-designed DSLs are simple, easy to use and capable of solving any problem defined in their domains. Based on DSL methodology, this study proposes a four-element framework to partition the software system into decoupled elements, and discusses the design and implementation steps of each element as well as communication between elements. The superiority of the developed methodology based on DSL is compared with traditional programming techniques for controllability assessment of various case studies. Essentially, the major advantage of the proposed methodology is the performance of the software product. Performance measures used in this study are total time to develop (TD) the software tool and its modifiability. Total time and effort to implement and use the result products presents up to five times improvement. Moreover, the result product’s modifiability is assessed by applying modifications, which also demonstrates up to five times improvement. All measures are tested on continuous stirred-tank reaction (CSTR) and forced-circulation evaporator (FCE) case studies. In conclusion, this study significantly contributes to two fields. The first is DSL, since this thesis studies different types of DSLs and evaluates their applications in the controllability analysis. The second is the controllability evaluation, since this study examines a new methodology for software development in controllability assessment

Closed Loop Simulation of Decentralized Control using RGA for Uncertain Binary Distillation Column

This paper presents the results of closed loop simulation for decentralized control of uncertain distillation column. The RGA (Relative Gain Array) RGA analysis will be used as the basis for selecting the configuration of the decentralized control system. PI controller obtained was then tuned with optimization methods. The simulation results show that the RGA analysis requires accurate range for uncertain systems. In addition, closed-loop simulation results confirm the RGA analysis

Mp Tuning for Internal Model Control 2x2 Multi Input Multi Output (MIMO) System

IMC is a type of model based control that compensates time delay in the process. The controller tuning is quite simple in case of no-error in the model, otherwise it will be a difficult matter. Mp tuning has been considered a tuning for uncertain processes. To extend  IMC to MIMO system, a new method  based on Maximum Peak (Mp) is developed . The present study proposes Maximum Peak  (Mp) tuning for IMC in 2x2  multi input and multi output (MIMO) system. Three particular 2x2 model of distillation colomn are being studied, the best configuration is analyzed by Relative Gain Array (RGA) and Average Dynamic Gain Array (ADGA) method. The tuning method  consists of two main steps: Firstly, determine the worst case of the model uncertainty. Secondly, specify the parameter of set point controller using maximum peak (Mp) criteria.  The effectiveness of Mp tuning for IMC in MIMO system  is  evaluated and compared to Biggest Log Modulus Tuning (BLT) for MIMO-PI Controller, Skogestad Tuning, and Rivera Tuning. Evaluation and comparison  have been done through simulation and the results are satisying

Comparative Analysis of Decoupling Control Methodologies and H¥ Multivariable Robust Control for Variable-Speed, Variable-PitchWind Turbines: Application to a Lab-Scale Wind Turbine

This work is focused on the improvement of variable-speed variable-pitch wind turbine performance by means of its control structure. This kind of systems can be considered as multivariable nonlinear processes subjected to undesired interactions between variables and presenting different dynamics at different operational zones. This interaction level and the dynamics uncertainties complicate the control system design. The aim of this work is developing multivariable controllers that cope with such problems. The study shows the applicability of different decoupling methodologies and provides a comparison with a H¥ controller, which is an appropriate strategy to cope with uncertainties. The methodologies have been tested in simulation and verified experimentally in a lab-scale wind turbine. It is demonstrated that the wind turbine presents more interaction at the transition zone. Then, this operational point is used as the nominal one for the controller designs. At this point, decoupling controllers obtain perfect decoupling while the H¥ control presents important interaction in the generated power loop. On the other hand, they are slightly surpassed by the robust design at other points, where perfect decoupling is not achieved. However, decoupling controllers are easier to design and implement, and specifically dynamic simplified decoupling achieve the best global response. Then, it is concluded that the proposed methodologies can be considered for implantation in industrial wind turbines to improve their performance