Simulation and optimization of dynamic flux balance analysis models using an interior point method reformulation

This work presents a novel, differentiable, way of solving dynamic Flux Balance Analysis (dFBA) problems by embedding flux balance analysis of metabolic network models within lumped bulk kinetics for biochemical processes. The proposed methodology utilizes transformation of the bounds of the embedded linear programming problem of flux balance analysis via a logarithmic barrier (interior point) approach. By exploiting the first-order optimality conditions of the interior-point problem, and with further transformations, the approach results in a system of implicit ordinary differential equations. Results from four case studies, show that the CPU and wall-times obtained using the proposed method are competitive with existing state-of-the-art approaches for solving dFBA simulations, for problem sizes up to genome-scale. The differentiability of the proposed approach allows, using existing commercial packages, its application to the optimal control of dFBA problems at a genome-scale size, thus outperforming existing formulations as shown by two dynamic optimization case studies.• R. Conejeros would like to thank CONICYT’s research grant FONDECYT 1151295 for funding this research. • F. Scott gratefully acknowledges financial support from CONICYT (Proyectos REDES ETAPA INICIAL, Convocatoria 2017, REDI170254)

A new formulation for symbolic regression to identify physico-chemical laws from experimental data

A modification to the mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed with the aim of identification of physical models from noisy experimental data. In the proposed formulation, a binary tree in which equations are represented as directed, acyclic graphs, is fully constructed for a pre-defined number of layers. The introduced modification results in the reduction in the number of required binary variables and removal of redundancy due to possible symmetry of the tree formulation. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the numbers of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was proven to be successful in identifying the correct physical models describing the relationship between shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of chemical reactions. Future work will focus on addressing the limitations of the present formulation and solver to enable extension of target problems to larger, more complex physical models.EPSRC EP/R009902/

Logical effort based design exploration of 64-bit adders using a mixed dynamic-CMOS/threshold-logic approach

Copyright © 2004 IEEEThis paper presents the design exploration of CMOS 64-bit adders designed using threshold logic gates based on systematic transistor level delay estimation using Logical Effort (LE). The adders are hybrid designs consisting of domino and the recently proposed Charge Recycling Threshold Logic (CRTL). The delay evaluation is based LE modeling of the delay of the domino and CRTL gates. From the initial estimations, we select the 8-bit sparse carry look-ahead/carry-select scheme. Simulations indicate a delay of less than 5 FO4, which is 1.1 FO4 or 17% faster than the nearest domino design.Peter Celinski, Said Al-Sarawi, Derek Abbott, Sorin Cotofana and Stamatis Vassiliadi

From pre-storm activity to magnetic storms: a transition described in terms of fractal dynamics

International audienceWe show that distinct changes in scaling parameters of the Dst index time series occur as an intense magnetic storm approaches, revealing a gradual reduction in complexity. The remarkable acceleration of energy release ? manifested in the increase in susceptibility ? couples to the transition from anti-persistent (negative feedback) to persistent (positive feedback) behavior and indicates that the occurence of an intense magnetic storm is imminent. The main driver of the Dst index, the VBSouth electric field component, does not reveal a similar transition to persistency prior to the storm. This indicates that while the magnetosphere is mostly driven by the solar wind the critical feature of persistency in the magnetosphere is the result of a combination of solar wind and internal magnetospheric activity rather than solar wind variations alone. Our results suggest that the development of an intense magnetic storm can be studied in terms of "intermittent criticality" that is of a more general character than the classical self-organized criticality phenomena, implying the predictability of the magnetosphere

Analysis of the cyanobacterial hydrogen photoproduction process via model identification and process simulation

Cyanothece sp. ATCC 51142 is considered a microorganism with the potential to generate sustainable hydrogen in the future. However, few kinetic models are capable of simulating different phases of Cyanothece sp. ATCC 51142 from growth to hydrogen production. In the present study four models are constructed to simulate Cyanothece sp. batch photoproduction process. A dynamic optimisation method is used to determine parameters in the models. It is found that although the piecewise models fit experimental data better, large deviation can be induced when they are used to simulate a process whose operating conditions are different from the current experiments. The modified models are eventually selected in the present study to simulate a two-stage continuous photoproduction process. The current simulation results show that a plug flow reactor (PFR) shows worse performance compared to a continuous stirred-tank reactor (CSTR) in the current operating conditions since it lowers the total hydrogen production. The finding is that nitrate and oxygen concentration change along the direction of culture movement in PFR, and hydrogen is only generated in the zone where both of them are low. The reactor area thereby is not well utilised. Additionally, as hydrogen production rate is primarily influenced by biomass concentration, which increases initially and decreases eventually along the direction of culture movement, the overall hydrogen production rate in a PFR may be lower than that in a CSTR. Finally, in this study fed-batch photoproduction processes are proposed containing only one photobioreactor based on the current simulation.Solar Hydrogen Project was funded by the UK Engineering and Physical Sciences Research Council (EPSRC), Project reference EP/F00270X/1. The author E.A. del Rio-Chanona funding by CONACyT Scholarship No. 522530 scholarship from the Secretariat of Public Education and the Mexican government.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0009250915000883#

Modelling of light and temperature influences on cyanobacterial growth and biohydrogen production

Dynamic simulation is a valuable tool to assist the scale-up and transition of biofuel production from laboratory scale to potential industrial implementation. In the present study two dynamic models are constructed, based on the Aiba equation, the improved Lambert–Beer's law and the Arrhenius equation. The aims are to simulate the effects of incident light intensity, light attenuation and temperature upon the photo-autotrophic growth and the hydrogen production of the nitrogen-fixing cyanobacterium Cyanothece sp. ATCC 51142. The results are based on experimental data derived from an experimental setup using two different geometries of laboratory scale photobioreactors: tubular and flat-plate. All of the model parameters are determined by an advanced parameter estimation methodology and subsequently verified by sensitivity analysis. The optimal temperature and light intensity facilitating biohydrogen production in the absence of light attenuation have been determined computationally to be 34 °C and 247 μmol m− 2 s− 1, respectively, whereas for cyanobacterial biomass production they are 37 °C and 261 μmol m− 2 s− 1, respectively. Biomass concentration higher than 0.8 g L− 1 is also demonstrated to significantly enhance the light attenuation effect, which in turn inducing photolimitation phenomena. At a higher biomass concentration (3.5 g L− 1), cyanobacteria are unable to activate photosynthesis to maintain their lives in a photo-autotrophic growth culture, and biohydrogen production is significantly inhibited due to the severe light attenuation.The author D. Zhang gratefully acknowledges the support from his family. The author P. Dechatiwongse is supported by a scholarship from the Royal Thai Government, Thailand, and his project, Solar Hydrogen Project, was funded by the UK Engineering and Physical Sciences Research Council (EPSRC), project reference EP/F00270X/1. Author E. A. del Rio-Chanona is funded by CONACyT scholarship No. 522530 from the Secretariat of Public Education and the Mexican government. The authors wish to thank Mr. Fabio Fiorelli for his invaluable advice and support during the preparation of this work.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.algal.2015.03.01

Optimal Operation Strategy for Biohydrogen Production

Hydrogen produced by microalgae is intensively researched as a potential alternative to conventional energy sources. Scaling-up of the process is still an open issue, and to this end, accurate dynamic modeling is very important. A challenge in the development of these highly nonlinear dynamic models is the estimation of the associated kinetic parameters. This work presents the estimation of the parameters of a revised Droop model for biohydrogen production by Cyanothece sp. ATCC 51142 in batch and fed-batch reactors. The latter reactor type results in an optimal control problem in which the influent concentration of nitrate is optimized which has never been considered previously. The kinetic model developed is demonstrated to predict experimental data to a high degree of accuracy. A key contribution of this work is the prediction that hydrogen productivity can achieve 3365 mL/L through an optimally controlled fed-batch process, corresponding to an increase of 116% over other recently published strategies.Author E. A. del Rio-Chanona would like to acknowledge CONACyT scholarship No. 522530 and the Secretariat of Public Education and the Mexican government for funding this project. Author P. Dechatiwongse is supported by a scholarship from the Royal Thai Government, Thailand. Solar Hydrogen Project was funded by the UK Engineering and Physical Sciences Research Council (EPSRC), project reference EP/F00270X/1.This is the author accepted manuscript. The final version is available from ACS via http://dx.doi.org/10.1021/acs.iecr.5b0061