Advances and Future Perspectives

Agharafeie , R., Ramos, J. R. C., Mendes, J. M., & Oliveira, R. M. F. (2023). From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives. Fermentation, 9(10), 1-22. [922]. https://doi.org/10.20944/preprints202310.0107.v1, https://doi.org/10.3390/fermentation9100922--- This work was supported by the Associate Laboratory for Green Chemistry - LAQV which is financed by national funds from FCT/MCTES (UIDB/50006/2020 and UIDP/50006/2020). This work received funding from the European Union’s Horizon 2020 research and innovation program under the grant agreement no. 101099487- BioLaMer-HORIZON-EIC-2022-PATHFINDEROPEN-01 (BioLaMer)Deep learning is emerging in many industrial sectors in hand with big data analytics to streamline production. In the biomanufacturing sector, big data infrastructure is lagging comparatively to other industries. A promising approach is to combine Deep Neural Networks (DNN) with prior knowledge in Hybrid Neural Network (HNN) workflows that are less dependent on the quality and quantity of data. This paper reviews published articles over the past 30 years on the topic of HNN applications to bioprocesses. It revealed that HNNs were applied to various bioprocesses, including microbial cultures, animal cells cultures, mixed microbial cultures, and enzyme biocatalysis. HNNs were mainly applied for process analysis, process monitoring, development of software sensors, open- and closed-loop control, batch-to-batch control, model predictive control, intensified design of experiments, quality-by-design, and recently for the development of digital twins. Most previous HNN studies combined shallow Feedforward Neural Networks (FFNNs) with physical laws, such as macroscopic material balance equations, following the semiparametric design principle. Only recently, deep HNNs based on deep FFNNs, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM) networks and Physics Informed Neural Networks (PINNs) have been reported. The biopharma sector is currently a major driver but applications to biologics quality attributes, new modalities, and downstream processing are significant research gaps.publishersversionpublishe

Novel strategies for process control based on hybrid semi-parametric mathematical systems

Tese de doutoramento. Engenharia Química. Universidade do Porto. Faculdade de Engenharia. 201

Using traditional modelling approaches for a MBR system to investigate alternate approaches based on system identification procedures for improved design and control of a wastewater treatment process.

The specific research work described in this thesis forms part of a much larger research project that was funded by the Technology Programme of the UK Government. This larger project considered improving the design and efficiency of membrane bioreactor (MBR) plant by using modelling, simulation and laboratory methods. This research work uses phenomenological mechanistic models based on MBR filtration and biochemical processes to measure the effectiveness of alternative behavioural models based upon input-output system identification methods. Both model types are calibrated and validated using similar plant layouts and data sets derived for this purpose. Results prove that although both approaches have their advantages, they also have specific disadvantages as well. In conclusion, the MBR plant designer and/or operator who wishes to use good quality, calibrated models to gain a better understanding of their process, should carefully consider which model type is selected based upon on what their initial modelling objectives are (e.g. using either a physically mechanistic model or an input-output behaviourial model). Each situation usually proves unique. In this regard, this research work creates a "Model Conceptualisation Procedure" for a typical MBR which can be used by future researchers as a theoretical framework which underpins any newly created model type. There has been insufficient work completed to date on using a times series input-output approach in the model development of a wastewater treatment plant, so only general conclusions can be made from this research work. However, it can be stated that this novel approach seems to be applicable for a membrane filtration model if care it taken to select appropriate input-output model structures, such as those suggested in the "Model Conceptualisation Procedure". In the case of the development of a MBR biological model, it is thought that a conventional Activated Sludge model produced by the IWA could be coupled to a input-output model structure as suggested by this report to give a hybrid model structure that may have the advantages of both model types. Further research work is needed in this area. Future work that should follow on from this research study should focus on whether these input-output models could be used for predictive control purposes, whether an integrated model could be created, and whether a benchmark could be created for the three main MBR configurations.Technology Programme of the TSB (Technology Strategy Board) TP/3/DSM/6/I/1512

Model-based strategies for computer-aided operation of recombinant E. coli fermentation

Tese de Doutoramento em Engenharia Química e BiológicaThe main objectives of this thesis were the development of model-based strategies for improving the performance of a high-cell density recombinant Escherichia coli fed-batch fermentation. The construction of a mathematical model framework as well as the derivation of optimal and adaptive control laws were used to accomplish these tasks. An on-line data acquisition system was also developed for an accurate characterization of the process and for the implementation of the control algorithms. The mathematical model of the process is composed of mass balance equations to the most relevant state variables of the process. Kinetic equations are based on the three possible metabolic pathways of the microorganism: glucose oxidation, fermentation of glucose and acetate oxidation. A genetic algorithm was used to derive the kinetic structure and to estimate both yield and kinetic coefficients of the model, minimizing the normalized quadratic differences between simulated and real values of the state variables. After parameter estimation, a sensitivity function analysis was applied to evaluate the influence of the various parameters on model behavior. Sensitivity functions revealed the sensitivity of the state variables to variations in each model parameter. Thus, essential parameters were selected and the model could be re-written in a simplified version that could also describe accurately experimental data. A system for the on-line monitoring of the major state variables was also developed. Glucose and acetate concentrations were measured with a developed Flow Injection Analysis system, while the carbon dioxide and oxygen transfer rates were calculated from data obtained with exhaust gas analysis. The fermentation culture weight was also continuously assessed with a balance, allowing the use of more precise mass-based concentrations, while environmental variables like pH, dissolved oxygen and temperatures were controlled and assessed via a Digital Control Unit. The graphical programming environment LabVIEW was used to acquire and integrate these variables in a supervisory computer, allowing the performance of integrated monitoring and control of the process. A model-based adaptive linearizing control law was derived for the regulation of acetate concentration during fermentations. The non-linear model was subjected to transformations in order to obtain a linear behavior for the control loop when a non-linear control is applied. The implementation of the control law was performed through a C script embedded in the supervisory LabVIEW program. Finally, two optimization techniques for the maximization of biomass concentration were compared: a first order gradient method and a stochastic method based on the biological principle of natural evolution, using a genetic algorithm. The former method revealed less efficient concerning to the computed maximum, and dependence on good initial values.A presente tese teve como principais objectivos o desenvolvimento de estratégias baseadas em modelos para melhorar o desempenho da fermentação em modo semi-continuo em altas densidades celulares de Escherichia coil recombinada. Para o efeito, foi construído um modelo matemático representativo do processo e a partir deste foram desenvolvidos algoritmos de controlo óptimo e adaptativo. De forma a possibilitar a implementação de leis de controlo em linha e a caracterização do processo fermentativo, foi desenvolvido um sistema informático de aquisição e envio de dados. O modelo matemático representativo do processo em estudo foi elaborado tendo por base as equações dinâmicas de balanço mássico para as variáveis de estado mais relevantes, contemplando as três possíveis vias metabólicas do microrganismo. A estrutura cinética, bem como os parâmetros do modelo foram determinados por recurso a uma abordagem sistemática tendo por base a minimização das diferenças quadráticas entra dados reais e dados simulados, com recurso a uma ferramenta de optimização estocástica denominada de Algoritmos Genéticos. Após a etapa de identificação do modelo matemático, foram calculadas as sensibilidades relativas ao longo do tempo das variáveis de estado do modelo relativamente aos vários parâmetros determinados. Os resultados desta análise de sensibilidade possibilitaram avaliar a relevância de cada um dos parâmetros em causa, permitindo propor uma estrutura de modelo menos complexa, por exclusão dos parâmetros menos importantes. O sistema elaborado para a aquisição e envio em linha de dados da fermentação inclui um sistema de FIA (Flow Injection Analysis) desenvolvido para a medição das concentrações de acetato e glucose, uma unidade de controlo digital que controla as variáveis físicas mais relevantes para o processo, e um equipamento de Espectrometria de Massas para analisar as correntes gasosas de entrada e saída do fermentador. O sistema dispõe ainda de duas balanças, uma das quais para a aferição em linha do peso do caldo de fermentação, permitindo o use de concentrações mássicas que proporcionam resultados mais exactos. A aquisição e integração destas variáveis medidas são, efectuadas através de um software de supervisão elaborado no ambiente de programação gráfico LabVIEW. Adicionalmente, foi elaborada uma lei de controlo adaptativo linearizante para a regulação da concentração de acetato no meio de fermentação. A síntese da lei de controlo não linear foi efectuada por técnicas de geometria diferencial com linearização do sistema por retroacção de estado. A adaptação foi feita tendo por base a estimação de parâmetros variáveis no tempo, nos quais se concentram as incertezas do modelo. A implementação ao processo real da referida lei de controlo foi efectuada por recurso a um programa elaborado em C incluindo no programa supervisor elaborado em LabVIEW. Finalmente, para a optimização da quantidade de biomassa formada no final da fermentação por manipulação do caudal de alimentação, foram estudadas duas ferramentas de optimização: um método de gradiente e uma ferramenta baseada em Algoritmos Genéticos. Esta última revelou-se mais eficaz tanto na convergência para o valor óptimo, como na estimativa inicial fornecida.Fundação para a Ciência e a Tecnologia (FCT) – PRAXIS XXI/16961/98.União Europeia - Fundo Social Europeu (FSE) – III Quadro Comunitário de Apoio (QCA III).Fundação Calouste Gulbenkian (FCQ) - Educação e Bolsas.Agência de Inovação (ADI) - PROTEXPRESS

Wastewater Treatment and Reuse Technologies

This edited volume is a collection of 12 publications from esteemed research groups around the globe. The articles belong to the following broad categories: biological treatment process parameters, sludge management and disinfection, removal of trace organic contaminants, removal of heavy metals, and synthesis and fouling control of membranes for wastewater treatment

Recent Advances on The Enhanced Thermal Conductivity of Graphene Nanoplatelets Composites: A Short Review

Graphene nanoplatelets (GNPs) have attracted significant attention in the field of thermal management materials due to their unique morphology and remarkable thermal conductive properties. In addition, their impressive thermal properties make them interesting nanofillers for producing multifunctional composite materials with a multitude range of applications. This work specifically reviews the recent advances of the application of GNPs as nanofillers for the development of enhanced thermal conductivity of various materials or composites. In this review, the insight on the improved thermal conductivity of the composites bestowed by the GNPs with comprehensive comparison are briefly discussed. This review might unlock windows of opportunities and paves the way towards the production of enhanced materials for thermal applications including electronics, aerospace devices, batteries, and structural reinforcement

Optimal scheduling, design, operation and control of reverse osmosis desalination. Prediction of RO membrane performance under different design and operating conditions, synthesis of RO networks using MINLP optimization framework involving fouling, boron removal, variable seawater temperature and variable fresh water demand.

An accurate model for RO process has significant importance in the simulation and optimization proposes. A steady state model of RO process is developed based on solution diffusion theory to describe the permeation through membrane and thin film approach is used to describe the concentration polarization. The model is validated against the operation data reported in the literature. For the sake of clear understanding of the interaction of feed temperature and salinity on the design and operation of RO based desalination systems, simultaneous optimization of design and operation of RO network is investigated based on two-stage RO superstructure via MINLP approach. Different cases with several feed concentrations and seasonal variation of seawater temperature are presented. Also, the possibility of flexible scheduling in terms of the number of membrane modules required in operation in high and low temperature seasons is investigated A simultaneous modelling and optimization method for RO system including boron removal is then presented. A superstructure of the RO network is developed based on double pass RO network (two-stage seawater pass and one-stage brackish water pass). The MINLP problem based on the superstructure is used to find out an optimal RO network which will minimize the total annualized cost while fulfilling a given boron content limit. The effect of pH on boron rejection is investigated at deferent seawater temperatures. The optimal operation policy of RO system is then studied in this work considering variations in freshwater demand and with changing seawater temperature throughout the day. A storage tank is added to the RO layout to provide additional operational flexibility and to ensure the availability of freshwater at all times. Two optimization problems are solved incorporating two seawater temperature profiles, representing summer and winter seasons. The possibility of flexible scheduling of cleaning and maintenance of membrane modules is investigated. Then, the optimal design and operation of RO process is studied in the presence of membrane fouling and including several operational variations such as variable seawater temperature. The cleaning schedule of single stage RO process is formulated as MINLP problem using spiral wound modules. NNs based correlation has been developed based on the actual fouling data which can be used for estimating the permeability decline factors. The correlation based on actual data to predict the annual seawater temperature profile is also incorporated in the model. The proposed optimization procedure identified simultaneously the optimal maintenance schedule of RO network including its design parameters and operating policy. The steady state model of RO process is used to study the sensitivity of different operating and design parameters on the plant performance. A non-linear optimization problem is formulated to minimize specific energy consumption at fixed product flow rate and quality while optimizing the design and operating parameters. Then the MINLP formulation is used to find the optimal designs of RO layout for brackish water desalination. A variable fouling profile along the membrane stages is introduced to see how the network design and operation of the RO system are to be adjusted Finally, a preliminary control strategy for RO process is developed based on PID control algorithm and a first order transfer function (presented in the Appendix).Government gran

Book of abstracts of the 10th International Chemical and Biological Engineering Conference: CHEMPOR 2008

This book contains the extended abstracts presented at the 10th International Chemical and Biological Engineering Conference - CHEMPOR 2008, held in Braga, Portugal, over 3 days, from the 4th to the 6th of September, 2008. Previous editions took place in Lisboa (1975, 1889, 1998), Braga (1978), Póvoa de Varzim (1981), Coimbra (1985, 2005), Porto (1993), and Aveiro (2001). The conference was jointly organized by the University of Minho, “Ordem dos Engenheiros”, and the IBB - Institute for Biotechnology and Bioengineering with the usual support of the “Sociedade Portuguesa de Química” and, by the first time, of the “Sociedade Portuguesa de Biotecnologia”. Thirty years elapsed since CHEMPOR was held at the University of Minho, organized by T.R. Bott, D. Allen, A. Bridgwater, J.J.B. Romero, L.J.S. Soares and J.D.R.S. Pinheiro. We are fortunate to have Profs. Bott, Soares and Pinheiro in the Honor Committee of this 10th edition, under the high Patronage of his Excellency the President of the Portuguese Republic, Prof. Aníbal Cavaco Silva. The opening ceremony will confer Prof. Bott with a “Long Term Achievement” award acknowledging the important contribution Prof. Bott brought along more than 30 years to the development of the Chemical Engineering science, to the launch of CHEMPOR series and specially to the University of Minho. Prof. Bott’s inaugural lecture will address the importance of effective energy management in processing operations, particularly in the effectiveness of heat recovery and the associated reduction in greenhouse gas emission from combustion processes. The CHEMPOR series traditionally brings together both young and established researchers and end users to discuss recent developments in different areas of Chemical Engineering. The scope of this edition is broadening out by including the Biological Engineering research. One of the major core areas of the conference program is life quality, due to the importance that Chemical and Biological Engineering plays in this area. “Integration of Life Sciences & Engineering” and “Sustainable Process-Product Development through Green Chemistry” are two of the leading themes with papers addressing such important issues. This is complemented with additional leading themes including “Advancing the Chemical and Biological Engineering Fundamentals”, “Multi-Scale and/or Multi-Disciplinary Approach to Process-Product Innovation”, “Systematic Methods and Tools for Managing the Complexity”, and “Educating Chemical and Biological Engineers for Coming Challenges” which define the extended abstracts arrangements along this book. A total of 516 extended abstracts are included in the book, consisting of 7 invited lecturers, 15 keynote, 105 short oral presentations given in 5 parallel sessions, along with 6 slots for viewing 389 poster presentations. Full papers are jointly included in the companion Proceedings in CD-ROM. All papers have been reviewed and we are grateful to the members of scientific and organizing committees for their evaluations. It was an intensive task since 610 submitted abstracts from 45 countries were received. It has been an honor for us to contribute to setting up CHEMPOR 2008 during almost two years. We wish to thank the authors who have contributed to yield a high scientific standard to the program. We are thankful to the sponsors who have contributed decisively to this event. We also extend our gratefulness to all those who, through their dedicated efforts, have assisted us in this task. On behalf of the Scientific and Organizing Committees we wish you that together with an interesting reading, the scientific program and the social moments organized will be memorable for all.Fundação para a Ciência e a Tecnologia (FCT

Special oils for halal and safe cosmetics

Three types of non conventional oils were extracted, analyzed and tested for toxicity. Date palm kernel oil (DPKO), mango kernel oil (MKO) and Ramputan seed oil (RSO). Oil content for tow cultivars of dates Deglect Noor and Moshkan was 9.67% and 7.30%, respectively. The three varieties of mango were found to contain about 10% oil in average. The red yellow types of Ramputan were found to have 11 and 14% oil, respectively. The phenolic compounds in DPKO, MKO and RSO were 0.98, 0.88 and 0.78 mg/ml Gallic acid equivalent, respectively. Oils were analyzed for their fatty acid composition and they are rich in oleic acid C18:1 and showed the presence of (dodecanoic acid) lauric acid C12:0, which reported to appear some antimicrobial activities. All extracted oils, DPKO, MKO and RSO showed no toxic effect using prime shrimp bioassay. Since these oils are stable, melt at skin temperature, have good lubricity and are great source of essential fatty acids; they could be used as highly moisturizing, cleansing and nourishing oils because of high oleic acid content. They are ideal for use in such halal cosmetics such as Science, Engineering and Technology 75 skin care and massage, hair-care, soap and shampoo products

Modelling, Optimisation and Control of Anaerobic Co-digestion Processes

La digestión anaerobia es un proceso biológico que ocurre espontáneamente en la naturaleza. Sin embargo, el rendimiento de metanización varía mucho dependiendo del tipo de residuo y condiciones ambientales a las que los residuos están expuestos. La tesis “Modelling, Optimisation and Control of Anaerobic Co-digestion Processes” contribuye a la modelización, optimización y control de procesos de co-digestión con el objetivo de mejorar el rendimiento del proceso. Los fundamentos de la digestión anaerobia y co-digestión se presentan en el Capítulo 1, junto con una revisión bibliográfica sobre la modelización del proceso, centrándose principalmente en la descripción y aplicaciones del Anaerobic Digestion Model No. 1 (ADM1), y una revisión de las distintas estrategias de control que están disponibles en la actualidad. El Capítulo 2 describe detalladamente la planta piloto que se utilizó para realizar los ensayos experimentales del trabajo de investigación. En el Capítulo 3 se desarrolla y valida un método generalizado para incorporar diversos sustratos solubles fermentables en un modelo basado en ADM1. Las reacciones de fermentación de sustratos tales como el etanol, no incluidos originalmente en ADM1, se implementan como reacciones de fermentación equivalente de glucosa. Suponiendo que la acidogénesis es el paso más rápido en la digestión anaerobia, una descripción exacta de la estequiometría de la fermentación de sustratos solubles (etanol, glicerol...) y productos (acetato, butirato y propionato) no es necesaria siempre que se cumplan los balances de masa y de electrones, puesto que todos estos ácidos intermedios se convierten rápidamente en acetato, H2 y CO2 en sistemas metanogénicos. El tratamiento de residuos sólidos mediante digestión anaerobia es atractivo por su alto contenido en materia orgánica y al potencial de recuperación de energía. En el caso de sólidos, la etapa de desintegración-hidrólisis es el paso más lento del proceso. El Capítulo 4 presenta un nuevo enfoque para la modelización de las etapas de desintegración e hidrólisis de sustratos sólidos complejos. Éstos se suponen que están compuestos de una fracción fácilmente biodegradable y otra lentamente biodegradable. El modelo propuesto considera una desintegración desacoplada de estas dos fracciones para describir mejor la degradación de los residuos sólidos. La co-digestión puede mejorar el rendimiento de las plantas de biogás en términos de productividad de metano y estabilidad de la operación si se combinan adecuadamente los diferentes co-sustratos. El Capítulo 5 formula y valida un método de optimización basado en programación lineal que calcula la mejor mezcla de alimentación para sistemas de co-digestión, capaz de maximizar la producción de metano a cada velocidad de carga orgánica aplicada. La mezcla resultante está sujeta a un conjunto de restricciones fisicoquímicas, que se definen en base al conocimiento heurístico del proceso. Finalmente, el Capítulo 6 presenta una estrategia de control para co-digestión anaerobia. La mezcla óptima obtenida por programación lineal se alimenta a un digestor operando en continuo y un sistema de diagnosis evalúa el rendimiento del proceso. En función de los resultados de la diagnosis, la acción de control modifica las restricciones aplicadas en el cálculo de la alimentación. Esta acción de control permite calcular una nueva mezcla de sustratos y un nuevo TRH para el próximo período de operación. Como resultado, la estrategia funciona como un controlador en lazo cerrado que optimiza la mezcla de alimentación al digestor y posteriormente evalúa el rendimiento de operación con la mezcla alimentada