scholarly journals Iterative Design of Dynamic Experiments in Modeling for Optimization of Innovative Bioprocesses

2009 ◽  
Vol 4 (2) ◽  
Author(s):  
Mariano Cristaldi ◽  
Ricardo Grau ◽  
Ernesto Martinez
Keyword(s):  
Data Gathering ◽  
Parametric Uncertainty ◽  
Coli Strain ◽  
Operating Conditions ◽  
Batch Bioreactor ◽  
Dynamic Experiments ◽  
Speed Up ◽  
Interleukin 11 ◽  
Experimental Runs ◽  
Sampling Times

Finding optimal operating conditions fast with a scarce budget of experimental runs is a key problem to speed up the development and scaling up of innovative bioprocesses. In this paper, a novel iterative methodology for the model-based design of dynamic experiments in modeling for optimization is developed and successfully applied to the optimization of a fed-batch bioreactor related to the production of r-interleukin-11 (rIL-11) whose DNA sequence has been cloned in an Escherichia coli strain. At each iteration, the proposed methodology resorts to a library of tendency models to increasingly bias bioreactor operating conditions towards an optimum. By selecting the ‘most informative’ tendency model in the sequel, the next dynamic experiment is defined by re-optimizing the input policy and calculating optimal sampling times. Model selection is based on minimizing an error measure which distinguishes between parametric and structural uncertainty to selectively bias data gathering towards improved operating conditions. The parametric uncertainty of tendency models is iteratively reduced using Global Sensitivity Analysis (GSA) to pinpoint which parameters are keys for estimating the objective function. Results obtained after just a few iterations are very promising.

scholarly journals Tryptophan Production Maximization in a Fed-Batch Bioreactor with Modified E. coli Cells, by Optimizing Its Operating Policy Based on an Extended Structured Cell Kinetic Model

2021 ◽  
Vol 8 (12) ◽  
pp. 210
Author(s):  
Gheorghe Maria ◽  
Laura Renea
Keyword(s):  
Cell Model ◽  
Genetically Modify ◽  
Optimal Operation ◽  
Coli Strain ◽  
Operating Conditions ◽  
Model Complexity ◽  
State Variables ◽  
Fed Batch ◽  
E Coli ◽  
Batch Bioreactor

Hybrid kinetic models, linking structured cell metabolic processes to the dynamics of macroscopic variables of the bioreactor, are more and more used in engineering evaluations to derive more precise predictions of the process dynamics under variable operating conditions. Depending on the cell model complexity, such a math tool can be used to evaluate the metabolic fluxes in relation to the bioreactor operating conditions, thus suggesting ways to genetically modify the microorganism for certain purposes. Even if development of such an extended dynamic model requires more experimental and computational efforts, its use is advantageous. The approached probative example refers to a model simulating the dynamics of nanoscale variables from several pathways of the central carbon metabolism (CCM) of E. coli cells, linked to the macroscopic state variables of a fed-batch bioreactor (FBR) used for the tryptophan (TRP) production. The used E. coli strain was modified to replace the PTS system for glucose (GLC) uptake with a more efficient one. The study presents multiple elements of novelty: (i) the experimentally validated modular model itself, and (ii) its efficiency in computationally deriving an optimal operation policy of the FBR.

Enhanced Reactor Performance with Pressure and Vacuum Swing Reaction

2004 ◽  
Vol 2 (1) ◽  
Author(s):  
Vincent G Gomes
Keyword(s):  
Method Of Lines ◽  
Fixed Bed ◽  
Downstream Processing ◽  
Operating Conditions ◽  
Reactor Performance ◽  
Orthogonal Collocation ◽  
The Method Of Lines ◽  
Dynamic Experiments ◽  
Product Separation ◽  
Pressure Swing

Product separation and regeneration of sorbent was accomplished in a novel pressure swing reactor through pressurisation, adsorption, blowdown and purge steps. The switching from sorption to reaction to regeneration was tested in a two bed sorption/reaction apparatus. Models developed for the mass and momentum transfer in the catalyst bed and sorber, were solved using orthogonal collocation within the method of lines. The effects of operating conditions and cycle configurations on performance were assessed. The results from dynamic experiments with propene metathesis to produce ethene and 2-butene in a fixed-bed catalytic reactor were in agreement with model predictions. Both pressure and vacuum swing demonstrated that conversion and product quality can be enhanced by periodic cycling with greater separation obtained with vacuum swing. The separation of products help reduce the downstream processing costs of exit mixtures, enable reactant utilisation by recycling and improve product handling at subsequent stages. The efficacy of the periodic separating reactor in terms of conversion, product purity and recovery were investigated.

scholarly journals BAYESIAN OPTIMIZATION OF CRYSTALLIZATION PROCESSES TO GUARANTEE END-USE PRODUCT PROPERTIES

2020 ◽  
Vol 50 (2) ◽  
pp. 109-114
Author(s):  
Martin Francisco Luna ◽  
Ernesto Carlos Martinez
Keyword(s):  
Crystal Size ◽  
Process Development ◽  
Operating Conditions ◽  
Bayesian Optimization ◽  
Dissolution Profile ◽  
Bayesian Optimization Algorithm ◽  
Probability Of Success ◽  
End Use ◽  
One Class Classification ◽  
Experimental Runs

For pharmaceutical solid products, the issue of reproducibly obtaining their desired end-use properties depending on crystal size and form is the main problem to be addressed and solved in process development. Lacking a reliable first-principles model of a crystallization process, a Bayesian optimization algorithm is proposed. On this basis, a short sequence of experimental runs for pinpointing operating conditions that maximize the probability of successfully complying with end-use product properties is defined. Bayesian optimization can take advantage of the full information provided by the sequence of experiments made using a probabilistic model of the probability of success based on a one-class classification method. The proposed algorithm’s performance is tested in silico using the crystallization and formulation of an API product where success is about fulfilling a dissolution profile as required by the FDA. Results obtained demonstrate that the sequence of generated experiments allows pinpointing operating conditions for reproducible quality.

scholarly journals Development and assessment of speed-up algorithms for the reactive CFD–DEM simulation of fluidized bed reactors

2020 ◽  
Vol 5 (2) ◽  
pp. 278-288 ◽  
Author(s):  
Riccardo Uglietti ◽  
Mauro Bracconi ◽  
Matteo Maestri
Keyword(s):  
Fluidized Bed ◽  
Selection Procedure ◽  
Operating Conditions ◽  
Fluidized Bed Reactors ◽  
Effective Algorithm ◽  
Dem Simulation ◽  
Dem Simulations ◽  
Speed Up

PA and ISAT algorithms are developed to speed-up the CFD–DEM simulations of fluidized reactors. Also, a selection procedure of the most effective algorithm according to the operating conditions is developed, enabling the simulation of lab reactors.

scholarly journals Operating Time Division for a Bus Route Based on the Recovery of GPS Data

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jian Wang ◽  
Yang Cao
Keyword(s):  
Travel Time ◽  
Operating Time ◽  
Time Of Day ◽  
Operating Conditions ◽  
Gps Data ◽  
Recovery Method ◽  
Speed Up ◽  
Link Travel Time ◽  
Partition Method ◽  
Bus Travel Time

Bus travel time is an important source of data for time of day partition of the bus route. However, in practice, a bus driver may deliberately speed up or slow down on route so as to follow the predetermined timetable. The raw GPS data collected by the GPS device equipped on the bus, as a result, cannot reflect its real operating conditions. To address this concern, this study first develops a method to identify whether there is deliberate speed-up or slow-down movement of a bus. Building upon the relationships between the intersection delay, link travel time, and traffic flow, a recovery method is established for calculating the real bus travel time. Using the dwell time at each stop and the recovered travel time between each of them as the division indexes, a sequential clustering-based time of day partition method is proposed. The effectiveness of the developed method is demonstrated using the data of bus route 63 in Harbin, China. Results show that the partition method can help bus enterprises to design reasonable time of day intervals and significantly improve their level of service.

Test and Analysis of Exhaust Pollutants from Automobiles Based on GPS Technology

2010 ◽  
Vol 40-41 ◽  
pp. 675-681
Author(s):  
Ming Li Xian ◽  
Qing Huang Yong
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Operating Conditions ◽  
Vehicle Emission ◽  
Testing System ◽  
Time Data ◽  
Gps Technology ◽  
Urban Road ◽  
Real Time Data ◽  
Object Of Study

Taking the actual running vehicles on the urban roads of Ningpo City as the object of study, by using the brand-new on-vehicle automobile exhaust real-time testing system, and through actual testing by tracking the running vehicles and real-time data gathering, The paper analyzed urban road operating conditions, the vehicle emission situation on the actual roads, obtained the relations between the operating conditions, the speed and emissions and the law by which the automobile operating conditions affect the automobile exhausts.

scholarly journals Pengaruh sumber karbon terhadap produksi bioplastik polihidroksialkanoat (PHA) dengan ralstonia eutropha

2018 ◽  
Vol 9 (1) ◽  
pp. 28
Author(s):  
Martha Aznury ◽  
Tjandra Setiadi ◽  
Adi Pancoro
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Carbon Source ◽  
Fermentation Process ◽  
Volatile Fatty Acids ◽  
Ralstonia Eutropha ◽  
Operating Conditions ◽  
Batch Bioreactor ◽  
Pha Production ◽  
Fructose Fermentation

Bioplastic Polyhidroxyalknoate (PHA) is a polyester type bioplastic with physicochemical properties resemble to those of polypropilen from petroleum. PHA production was investigated to determine the effect of carbon source on the fermentation process by Ralstonia eutropha. Specifically, Ralstonia eutropha was cultivated in a batch bioreactor to show the dynamics of P(3HB-co-3HV) copolymer production from glucose or fructose as C source. In adition, the effect of volatile fatty acids addition, as stimulator to the copolymer production, was also studied. The operating conditions in a 7 L bioreactor were at temperature 30 oC and pH 7.0. The concentration of carbon source glucose or fructose was 40 g/L, and after 20 hour fermentation, volatile fatty acids were added. With volatile fatty acids addition, the resulting fructose fermentation had PHA content of 32.78%, in which the HV percentage was 11.78%. Meanwhile, the fermentation of glucose, stimulated by volatile fatty acids, gave PHA as much as 20.19% with HV percentage of 8.71%. Therefore,, the Ralstonia eutropha fermentation of fructose as the carbon source gave a higher yield than glucose. Keywords: Volatil Fatty Acid, Fructose, Glucose, PHA, P(3HB-co-3HV), Ralstonia eutropha AbstrakBioplastik polihidroksialkanoat (PHA) adalah bioplastik dari kelompok poliester dengan sifat fisikokimia mirip dengan plastik polipropilen dari minyak bumi. Penelitian ini bertujuan untuk mempelajari pengaruh sumber karbon terhadap poduksi PHA yang dilakukan dengan proses fermentasi menggunakan Ralstonia eutropha. Ralstonia eutropha dikultivasi dalam bioreaktor batch untuk mempelajari dinamika produksi kopolimer P(3HB-co-3HV) dari sumber karbon glukosa atau fruktosa, serta mempelajari pengaruh sumber stimulator asam lemak volatil. Kondisi operasional fermentasi menggunakan bioreaktor 7 L adalah pada temperatur 30 oC dan pH 7. Konsentrasi sumber karbon glukosa atau fruktosa yang digunakan adalah 40 gr/L, dan setelah 20 jam fermentasi ditambahkan asam lemak volatil yang berfungsi sebagai stimulator dalam produksi P(3HB-co-3HV). Panen sel Ralstonia eutropha dilakukan setelah 60 jam. Hasil penelitian menunjukkan fermentasi Ralstonia eutropha dengan substrat fruktosa dan asam lemak volatil sebagai stimulator mempunyai kandungan PHA sebesar 32,78%, dengan kadar HV 11,78%. Pada pemberian substrat glukosa dan asam lemak volatil menunjukkan kandungan PHA sebesar 20,19%, dengan kadar HV 8.71%. Jadi fermentasi Ralstonia eutropha dengan menggunakan substrat fruktosa memberikan yield yang lebih tinggi dibandingkan menggunakan substrat glukosa.Kata Kunci: Asam lemak volatil, fruktosa, glukosa, PHA, P(3HB-co-3HV), Ralstonia eutropha

Investigation on the Internal Cooling of Two-Passage Channels With Parallel Ribs and Guide Vanes

2019 ◽  
Author(s):  
Ryoichi S. Amano ◽  
Mandana S. Saravani ◽  
Nicholas DiPasquale
Keyword(s):  
Heat Transfer ◽  
Guide Vane ◽  
Constant Heat Flux ◽  
Operating Conditions ◽  
Internal Cooling ◽  
Flux Boundary Condition ◽  
Guide Vanes ◽  
Flow And Heat Transfer ◽  
Speed Up ◽  
Dynamics Simulations

Abstract The present work investigates the effects of various guide vane designs on the heat transfer enhancement of rotating U-Duct configuration with parallel 45-deg ribs. The ribs were installed on the bottom wall of the channel which has a constant heat flux boundary condition. The channel has a square cross-section with a 5.08 cm (2 in) hydraulic diameter. The first and second passes are 514 mm and 460 mm, respectively. The range of Reynolds number for turbulent flow is up to 35,000. The channel rotates in various speed up to 600 rpm which brings the maximum rotation number of 0.75. Several computational fluid dynamics simulations are carried out for this study to understand the effect of guide vanes on flow and heat transfer in serpentine channels under various operating conditions.

scholarly journals A Learning-Based Framework for Circuit Path Level NBTI Degradation Prediction

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1976
Author(s):  
Aiguo Bu ◽  
Jie Li
Keyword(s):  
Timing Analysis ◽  
Operating Conditions ◽  
Negative Bias Temperature Instability ◽  
Worst Case ◽  
Learning Framework ◽  
Bias Temperature Instability ◽  
Minimal Loss ◽  
Complex Dependence ◽  
Speed Up ◽  
Tremendous Challenge

Negative bias temperature instability (NBTI) has become one of the major causes for temporal reliability degradation of nanoscale circuits. Due to its complex dependence on operating conditions, it is a tremendous challenge to the existing timing analysis flow. In order to get the accurate aged delay of the circuit, previous research mainly focused on the gate level or lower. This paper proposes a low-runtime and high-accuracy machining learning framework on the circuit path level firstly, which can be formulated as a multi-input–multioutput problem and solved using a linear regression model. A large number of worst-case path candidates from ISCAS’85, ISCAS’89, and ITC’99 benchmarks were used for training and inference in the experiment. The results show that our proposed approach achieves significant runtime speed-up with minimal loss of accuracy.

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