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This paper deals with the theoretical comparison of biogas and energy yields of one-stage anaerobic digestion processes (OSAD) with biomethane production and two-stage anaerobic digestion processes (TSAD) producing biohydrogen and biomethane. The comparative study of the biogas yield from OSAD and TSAD systems is performed on the base on mathematical models obtained in our previous papers. The possible maximal yields of biohydrogen and biomethane are calculated by the static characteristics and extremum points of both systems. Simulation results suggest that in comparison to OSAD, the increase in biogas (biohydrogen and biomethgane) production of TSAD can reach to 75.18%. The energy produced from two-stage anaerobic digestion processes is 1.32 to 1.486 times greater than those from one-stage anaerobic digestion processes (depending of the inlet organics concentrations), which means TSAD is a better choice considering biogas and energy production.

In this paper, a new structure of extremum seeking algorithm is applied to the two-stage anaerobic digestion process to maximize the outflow rate of both hydrogen and methane. The model of the two-stage AD process is presented, which provides the characteristics of the total gas production rate. Based on the original Extremum Seeking Control (ESC), a novel Composed Recursive Model Free Controller (CRMFC) is added for maximum tracking for the gas production in the bioreactors. The proposed controller comprises a recursive model free stabilization term and a recursive time delay compensation term. Standard ESC, Newton-based ESC and Kalman filter (KF) based ESC are respectively combined with the new model-free controller to verify the proposed structure. Numerical simulations illustrate the performance of the proposed controller.

Anaerobic digestion is a biotechnological process, in which microorganisms degrade the complex organic matter to simpler components under anaerobic conditions to produce biogas and fertilizer. This process has many environmental benefits, such as green energy production, organic waste treatment, environmental protection and greenhouse gas emissions reduction. It has long been known that the two main communities of microorganisms (acidogenic and methanogenic) taking part in the anaerobic digestion differ in many aspects e.g. their optimal conditions for cell growth and development. Therefore, the anaerobic digestion in a single bioreactor (BR) (single-phase process) required selected optimal conditions, taking into account the slow-growing methanogens at the expense of fast-growing acidogens, which affects the efficiency of the whole process. This has led in recent years to development of two-stage anaerobic digestion, in which the processes are divided into a cascade of two separate BRs. It is known that this separation of the processes into two consecutive BRs leads to significantly higher energy yields for the two-phase system (H2 + CH4), compared to the traditional single-stage CH4 production process. The present paper aims to review the literature in the field of two-stage anaerobic digestion of organic wastes.

Anaerobic digestion (AD) is a biotechnological process, in which microorganisms degrade organic matter under anaerobic conditions to produce biogas. It has long been known that the two main species (acidogenic and methanogenic) in the community of microorganisms in AD differ in many aspects and the optimal conditions for their growth and development are different. Therefore, in AD in a single bioreactor (BR) (single-phase process), the optimal conditions are selected taking into account the slow-growing methanogens at the expense of fast-growing acidogens, which affects the efficiency of the whole process. This has led in recent years to the development of two-stage AD (TSAD), in which processes are divided into a cascade of two separate BRs. It is known that this division of the processes into two consecutive BRs leads to significantly higher energy yields for the two-phase system (H2 + CH4), compared to the traditional single-stage CH4 production process. In our previous studies different mathematical models of the TSAD have been developed. It was shown that in both BRs the input-output characteristics have a clear maximum, which allows the yields to increase significantly if operations are provided around the maximum points. However, in order to maintain the sustainability of the biogas plants work, it is necessary to introduce automatic control with sophisticated extremum seeking control (ESC) algorithms. This paper presents the pioneering research on ESC of AD process with production of hydrogen and methane. This research has been realized by the Department of Biotechnology at The Stephan Angeloff Institute of Microbiology (SAIM) and the French-Chinese Laboratory on Automatic Control and Signal Processing (LaFCAS), in collaboration with the Laboratory of Signals and Systems (L2S) at the French National Center of Scientific Research CNRS.

A study on the anaerobic digestion of wheat straw in a pilot scale bioreactor with an organic load of 2, 5, 7, 10 and 20 g/l and a process duration of 18 to 80 days was performed. The pilot bioreactor used has a computerized system for control and monitoring of various operational parameters – temperature, pH, biogas composition, etc. Total solids, total organics and volatile fatty acids were measured by standard methods and gas chromatography. Daily biogas yield and its main components (CH4, CO2, H2S) were analysed too. During the anaerobic digestion, different species of microorganisms have been isolated from the genera Bacillus, Pseudomonas, Enterococcus and Aeromonas, as well as the species Terribacillus halophilus. With a known pathogenic potential are described Pseudomonas sp., Enterococcus sp. and Aeromonas sp. Studies on the antimicrobial resistance of all isolated strains show resistance to ampicillin, amoxicillin, bacitracin, ceftriaxone, gentamicin and vancomycin. The cellulose degrading activity of some of the bacterial isolates, their pathogenic potential and antimicrobial resistance are discussed in detail in the light of the data on the mechanisms of proven resistance.

As focus of humans has turned to renewable energy, the role of anaerobic digestion has started to become economically viable. Reducing the volume of agro-wastes for the generation of gaseous and liquid fractions with energy carriers and valuable products is an enormous challenge. A two-stage anaerobic digestion process consisting of hydrogenic stage followed by methanogenic stage was studied in a laboratory scale. Five simple nonlinear models of this continuous cascade process were studied in order to determine the optimal ratio of working volumes of bioreactors, in view of maximising energy production. This ratio was reported for all adopted models. The optimal ratio (maximal energy production criterion) depends of the adopted mathematical model. Static characteristics of both bioreactors were obtained using Symbolyc toolbox of Matlab. Numerical experiments concerning dynamics of the main variables of both bioreactors for these models using Simulink of Matlab are performed for different step changes of the dilution rate of the first bioreactor, together with the influence of the substrate (acetate) inhibition for one of the models. The value of the constant of inhibition plays an important role on the admissible interval of the dilution rate. The developed idea could serve for optimally designed experiments of anaerobic digestion for production of hydrogen and methane from lignocelluloses wastes (wheat straw) in two phase process.

This paper proposes a Kalman filter (KF) based Newton extremum seeking control (NESC) to maximize production rates of hydrogen and methane in anaerobic digestion process. The Kalman filtering algorithm is used to obtain more accurate gradient and Hessian estimates which makes possible to increase the convergence speed to the extremum and to eliminate input and output steady-state oscillations. The simulation examples demonstrate the performances of the proposed approach.

The aim of this study is to implement a mathematical model to simulate the dynamic behaviour of a two-stage anaerobic digestion process for simultaneous production of hydrogen and methane. The process is carried out in two connected continuously stirred bioreactors. The proposed model is developed by reducing the well known IWA Anaerobic Digester Model No 1 (ADM1). In the present study the original model concept was adapted and applied to replicate a two-stage process. The proposed model involves 13 ODEs for the 1st stage and 7 ODEs for the 2nd stage. The numerical coefficient values in the model are taken from specified literature and adapted to the case of wheat straw AD. Important input-output static characteristics and existence of maxima of the input-output static characteristics concerning the biohydrogen and biomethane production in function of the control variable (dilution rate) are presented. Supposing that both bioreactors are operating nearby these maxima the optimal ratio of the working volumes was obtained. Numerical simulations using a specially elaborated web-based software environment are presented to demonstrate the dynamic behavior of the model solutions.

Anaerobic digestion is a multi-step biotechnological process, in which H2 is not detected as it is consumed immediately e.g. by hydrogenotrophic methanogens to produce CH4 and CO2. Recently a two-stage AD concept consisting of hydrogenic process followed by methanogenic process was suggested. However, only few models of this process are known. In this study a mathematical model of a continuous process of AD with production of hydrogen and methane in a cascade of two bioreactors, including some intermediate products in the first bioreactor was developed and investigated.

This paper presents a newly created mathematical model of thermophilic anaerobic digestion of wheat straw carried out in a 2 dm3 bioreactor for methane production. Two batch processes, with 30 mL/dm3 and 35 mL/dm3 organic load, are carried out—one set for parameter identification and one set for model verification. The identification of model parameter values is based on dynamical experiments. It is fulfilled using two different techniques: deterministic sequential quadratic programming algorithm and metaheuristic genetic algorithm. Verification of the developed mathematical models is conducted based on the different data sets of the process. Both models predict the set of the experimental data for all considered process variables well. Genetic algorithm visually fits the data with a higher degree of accuracy, as confirmed by the numerical results for the objective function value.

At present, complex biological processes are used in many industrial areas [...]

Anaerobic microbial biodegradation of cellulose containing wastes generated during the long-term manned space missions is a key technological approach for resolving the problem of wastes accumulated onboard of the spacecraft. Herewith are presented data on the possibilities of structurally stable multispecies microbial consortia originating from methanogenic bioreactors to decompose different cellulose substrates – filter paper, medical gauze and vegetable mix as potential cellulose wastes during space missions. The rates of biodegradation processes carried out at mesophilic and thermophilic conditions are not only measured and compared but are providing new opportunities for development of technology for microbial biodegradation of cellulose-rich organic wastes. Moreover, the studies have shown that paper and gauze hydrolysis with the help of cellulolytic bacterial communities can be an effective component of utilization of cosmonaut hygiene items. Biodegradation of plant wastes by community of anaerobic bacteria is promising and applicable tool also under terrestrial conditions. Light microscopy of bacterial communities reveals the presence of Gram-positive spore forming bacilli (short and long forms, bipolar and dividing cells) and typical clostridia forms.

Experimental studies of two-phase anaerobic digestion of corn steep liquor (a waste product from processing corn grain for starch extraction) were performed. For the first time, an automatic mode of operation was implemented in continuous processes with simultaneous production of hydrogen and methane using the developed computer system for monitoring and control of pilot bioreactors. The best results for daily biogas yield were obtained at an organic load of 20 g/L for hydrogen producing bioreactor, as the daily yield of biohydrogen is 0.74 dm3/L at a hydrogen concentration in biogas of 32.6% (0.24 dm3/L pure biohydrogen) and the daily biomethane yield in the methane producing bioreactor is 0.587 dm3/L at a methane concentration in biogas of 69% (0.4 dm3/L pure biomethane). The obtained energy is more than 40% compared to the traditional single-stage methane production process. A disadvantage is the need for additional purification from hydrogen sulfide of both gases before obtaining electricity and/or heat.

We propose a new mathematical model describing a biotechnological process of simultaneous production of hydrogen and methane by anaerobic digestion. The process is carried out in two connected continuously stirred bioreactors. The proposed model is developed by adapting and reducing the well known Anaerobic Digester Model No 1 (ADM1). Mathematical analysis of the model is carried out, involving existence and uniqueness of positive and uniformly bounded solutions, computation of equilibrium points, investigation of their local stability with respect to practically important input parameters. Existence of maxima of the input&ndash, output static characteristics with respect to hydrogen and methane is established. Numerical simulations using a specially elaborated web-based software environment are presented to demonstrate the dynamic behavior of the model solutions.

Mathematical models of a cascade of two continuously stirred anaerobic bioreactors for simultaneous hydrogen and methane production are presented and a stable extremum seeking control algorithm is applied to the system. The dilution rate of the first bioreactor is chosen as control action and the hydrogen and methane flow rates of both bioreactors, working in continuous mode, are the measured outputs to be maximized. The concentration of the inlet organics is accepted for disturbance. The control loop is represented by the extremum seeking controller, which finds the optimum control action and reacts to the disturbance. Simulation studies show the feasibility of this scheme

A mathematical model of a cascade of two continuously stirred anaerobic bioreactors is presented in this paper and the extremum seeking control is applied on it. The dilution rate of the first bioreactor is chosen as control action and the joint biogas flow rate both bioreactors is the measured output to be maximized. The concentration of inlet organics is accepted as the disturbance. The correction of the working volume of the second bioreactor is studied as the inner loop of the cascade control system. The outer control loop is represented by the extremum seeking controller, which finds the optimum control action and reacts to the disturbance. Computer simulation studies show the feasibility of this scheme.

The paper deals with the optimization of nonlinear systems by using Extremum Seeking Control (ESC) without any prior knowledge of the system model. An Extend Kalman Filter based Extremum Seeking Control (EKF based ESC) is proposed, which can make the amplitude of perturbation signal variable and ensure convergence to zero, i.e. without steady-state oscillation. The proposed ESC algorithm makes also possible to obtain more accurate gradient estimate and more rapid ESC convergence. The proposed EKF based ESC algorithm is applied to a fifth-order model of anaerobic digestion process and its performances are compared with the performances of the classical ESC algorithm. Key Words: ESC, EKF, steady state oscillation, anaerobic digestion processes

In the submitted work the noise characteristics of hail dropping strikes in urban environment are analyzed. In light of ground observations through crowd-sourcing mobile applications two hail storm recording spectra are compared. It is shown, that the low frequency component has strong influence on noise energy.

We propose a new mathematical model describing a biotechnological process of simultaneous production of hydrogen and methane by anaerobic digestion. The process is carried out in two connected continuously stirred bioreactors. The proposed model is developed by reducing the well known Anaerobic Digester Model No 1 (ADM1). The mathematical analysis of the model involves computation of equilibrium points, investigation of their local stability with respect to practically important input parameters, existence of maxima of the input-output static characteristics. Numerical simulations using a specially elaborated web-based software environment are presented to demonstrate the dynamic behavior of the model solutions.

Summary How is the progression of a virus influenced by properties intrinsic to individual cells? We address this question by studying the susceptibility of cells infected with two strains of the human respiratory syncytial virus (RSV-A and RSV-B) in an in vitro experiment. Spatial patterns of infected cells give us insight into how local conditions influence susceptibility to the virus. We observe a complicated attraction and repulsion behavior, a tendency for infected cells to lump together or remain apart. We develop a new spatial point process model to describe this behavior. Inference on spatial point processes is difficult because the likelihood functions of these models contain intractable normalizing constants; we adapt an MCMC algorithm called double Metropolis–Hastings to overcome this computational challenge. Our methods are computationally efficient even for large point patterns consisting of over 10,000 points. We illustrate the application of our model and inferential approach to simulated data examples and fit our model to various RSV experiments. Because our model parameters are easy to interpret, we are able to draw meaningful scientific conclusions from the fitted models.