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Identification of complex systems often face structural modelling errors and limited or low quality data, which hinder statistical characterisations. An alternative is the set-membership approach, where errors are assumed unknown-but-bounded. Set-membership estimation aims to find a feasible parameter set (FPS), which produces model outputs that fit within given error bounds. Most algorithms are limited to linear models, small number of parameters, or to discrete approximation of the FPS. These limitations hinder parameter estimation for relatively complex systems. We present an efficient sampling-based set-membership algorithm with low computational complexity that improves the coverage of a discrete approximation of the FPS, characterised by hyperspheres from a Voronoi diagram of the parameter space. Additionally, we suggest a measure for set-membership accuracy based on deviations between the given error bounds and the feasible model output set. Our algorithm provides a balance between accuracy and computational complexity, and a tool to investigate practical identifiability.

This thesis presents the development of mathematical models of water and nutrient balances in aquaponic systems, aimed at improving our understanding of this production method towards an efficient use of resources.Our current food production systems have large social and environmental impacts, which are commonly externalized in the context of industrial production and global trade. Aquaponics is an option for sustainable food production that combines aquatic species (aquaculture) with soilless plants (hydroponics). The main challenge in aquaponics consists of balancing optimal conditions for multiple species: aquatic organisms, plants and beneficial micro-organisms. To facilitate achieving this balance, decoupled aquaponic systems have been proposed, consisting of two separate recirculating water loops. In this way, the production loop for fish operates independently from the production loop for plants, each with their own optimal conditions. Nutrient-rich water from the fish loop can be supplied to the plants continuously or at selected times, reducing fertilizer requirements. Similarly, water from the plants loop can be recovered and supplied to the fish, reducing fresh water demand.Managing water and nutrient exchange in aquaponic systems requires continuous information about the concentrations of chemical elements (nutrients). Some nutrients, like nitrogen and phosphorus, are excreted in abundance by fish and can be used by plants. Other nutrients, like calcium and sodium, are also present in fish water, but they can easily reach harmful levels for plants. Sensors to continuously monitor these concentrations are costly and thus uncommon in commercial applications. Therefore, mathematical models combined with available measurements (semi-physical models), are suitable to support management and control of aquaponic systems.Mathematical models for aquaculture and hydroponic systems are widely available in literature. However, they do not describe the dynamics of nutrients. Furthermore, measurements of nutrients in the components of aquaponic systems are not always available and typically show large uncertainties.In this context, further elaborated in Chapter 1 - General introduction, the objective of this thesis was to investigate the dynamics of water and nutrient balances in decoupled aquaponic systems and their uncertainties. The research questions formulated for this purpose aim at identifying the main challenges and opportunities in closing water and nutrient cycles, and in modelling nutrient balances under uncertainties. Chapters 2 and 3 present system-level studies. Chapters 4 and 5 focus on mathematical modelling under uncertainty, applied to biological production systems.Chapter 2 presents a model-based study coupling a recirculating aquaculture system (RAS) for tilapia with a nutrient film technique (NFT) hydroponic system for tomato. The simulation results show that fish can provide 26% of the nitrogen requirements for plants. Furthermore, it is shown that variations in nitrate concentrations in the fish loop, can be decreased by 35%, using a water management strategy that sends water from fish to plants based on amounts proportional to the fish feed.Chapter 3 presents a model-based study supported by a demonstration aquaponic system in Abtshagen, Germany. The model helped identifying imbalances in the system design. It predicted excess concentrations of total suspended solids (TSS) for fish, and excess sodium, calcium, magnesium, and ammonium for plants. The model was used to develop an improved management strategy, preventing excess TSS, sodium, and ammonium, decreasing fertilizer requirements, and achieving water efficiencies similar to commercial aquaculture and hydroponic systems.Chapter 4 presents an algorithm proposed for the calibration of mathematical models applied to biological production systems. The algorithm is based on the set-membership approach, which is a suitable alternative to statistical methods in the presence of limited and uncertain experimental data. The algorithm uses Voronoi tessellation, a novel method that characterises the feasible parameter space with (hyper)spheres, quantifying deviations from experimental data.Chapter 5 studied the dynamics and uncertainties fish growth and excretion of macronutrients. A model was developed and calibrated using the Voronoi set-membership algorithm. Uncertainty propagation was assessed using Monte Carlo simulations. The model prediction explained 84% of the literature data variability for fish growth, 75% for digestive system content, and 28% for ammonia excretion rate. The uncertainty assessment helped identifying suitable experimental conditions for future research.Chapter 6 - General discussion, reflects on the research questions, explaining the limitations identified in each research chapter, and suggestions for future research.From a system design perspective, closing water and nutrient cycles requires a comprehensive quantitative analysis, using indicators that reflect the trade-offs occurring when trying to balancing optimal conditions between the fish and plant loops. A list of suggested indicators for future research is provided. From a system operation perspective, several specific problems and proposed solutions were identified. Solids should be removed from fish water by combining mechanical filtration and sedimentation, to better regulate water exchange from fish to plants, and to stabilize nutrient concentrations for plants. Water storage between fish and plant loops should be aerated to prevent nitrogen loss via denitrification. Fish feed should be selected based on the mineral concentrations in local fresh water, to prevent excess of nutrients harmful for plants, which decrease the potential for nutrient reuse.There is high multidisciplinarity involved in model development of aquaponic systems. Studies with a gradual increase in complexity are thus suggested. Future research on nutrient balances, for example, could consider the chemical form of nutrients and their bioavailability for fish and plants. Mathematical models of aquaponic systems and their components should consider simultaneously multiple variables with multiple time scales.The discussion is extended to the more general field of modelling biological production systems, providing a framework for the development of mathematical models under uncertainty, combining set-membership calibration with uncertainty propagation assessment, to identify critical variables for future experimental measurements.Finally, the discussion is brought back to the general socio-economic context. It is suggested to investigate whether the risks of aquaponics are most sensitive to the fish production loop. If that is the case, financial incentives for production should focus on the expansion of existing aquaculture farms to include hydroponic production. Furthermore, it is necessary to improve communication between researchers and producers.

This paper reveals that apart from changes of system structure vital system properties such as stabilizability and compensatability may be lost temporarily due to the stochastic nature of system parameters. To that end new system properties called temporal mean-square stabilizability (tms-stabilizability) and temporal mean-square compensatability (tms-compensatability) for time-varying linear discrete-time systems with white stochastic parameters (multiplicative white noise) are developed. When controlling such systems by means of (optimal) state feedback, tms-stabilizability identifies intervals where mean-square stability (ms-stability) is lost temporarily. This is vital knowledge to both control engineers and system scientists. Similarly, tms-compensatability identifies intervals where ms-stability is lost temporarily in case of full-order (optimal) output feedback. Tests explicit in the system matrices are provided to determine each temporal system property. These tests compute measures of the associated temporal system properties. Relations among the new system properties as well as relations with associated existing system properties are investigated and established. Examples illustrating principal applications and practical importance are provided.

Multiple shifted images (MSIs) have been widely applied to many super-resolution mapping (SRM) approaches to improve the accuracy of fine-scale land-cover maps. Most SRM methods with MSIs involve two processes: subpixel sharpening and class allocation. Complementary information from the MSIs has been successfully adopted to produce soft attribute values of subpixels during the subpixel sharpening process. Such information, however, is not used in the second process of class allocation. In this paper, a new class-allocation algorithm, named 'hybrid constraints of pure and mixed pixels' (HCPMP), is proposed to allocate land-cover classes to subpixels using MSIs. HCPMP first determines the classes of subpixels that overlap with the pure pixels of auxiliary images in MSIs, after which the remaining subpixels are classified using information derived from the mixed pixels of the base image in MSIs. An artificial image and two remote sensing images were used to evaluate the performance of the proposed HCPMP algorithm. The experimental results demonstrate that HCPMP successfully applied MSIs to produce SRM maps that are visually closer to the reference images and that have greater accuracy than five existing class-allocation algorithms. Especially, it can produce more accurate SRM maps for high-resolution land-cover classes than low-resolution cases. The algorithm takes slightly less runtime than class allocation using linear optimization techniques. Hence, HCPMP provides a valuable new solution for class allocation in SRM using auxiliary data from MSIs.

The selective catalytic production of C4-tetritols (erythritol and threitol) from C5-sugars is an attractive route for the conversion of non-digestible sugars to C4-building blocks from agro residues. Here we show that an unprecedented high selectivity of 20–25% C4-tertritols can be achieved under mild conditions (138 °C, 6 bar H2, and 24 h) in the aqueous conversion of xylose over a 5 wt% Ru/C catalyst. A mechanistic study revealed that the dominant reaction mechanism for C5-sugar conversion involves a formal decarbonylation step leading to the initial formation of the desired C4-tetritols. Subsequently the formed C4-tetritols undergo further terminal C–C scissions to glycerol and ethylene glycol. Remarkably, potentially competing reactions like internal C–C chain scission (fragmentation) or hydrodeoxygenation (HDO) do not occur to any significant extent under the applied conditions.

Energy requirements for resource transport of algae cultivation are unknown. This work describes the quantitative analysis of energy requirements for water and CO2 transport. Algae cultivation models were combined with the quantitative logistic decision model 'BeWhere' for the regions Benelux (Northwest Europe), southern France and Sahara. For photobioreactors, the energy consumed for transport of water and CO2 turns out to be a small percentage of the energy contained in the algae biomass (0.1-3.6%). For raceway ponds the share for transport is higher (0.7-38.5%). The energy consumption for transport is the lowest in the Benelux due to good availability of both water and CO2. Analysing transport logistics is still important, despite the low energy consumption for transport. The results demonstrate that resource requirements, resource distribution and availability and transport networks have a profound effect on the location choices for algae cultivation.

A first principles microfiltration model based on shear-induced diffusion is compared to experiments performed on the clarification of beer. After performing an identifiability and sensitivity analysis, the model parameters are estimated using global minimization of the sum of least squares. The model is compared to different series of experiments, where either crossflow or permeate flux is varied. This study is concluded with a parameter study on the scaling of the filtration time with various model parameters. We have found that the filtration time primarily depends on two dimensionless numbers, namely the normalized critical distance for cake layer formation, and the dimensionless time required to plug all pores in the selective layer. We have found that there is an optimal setting of these parameters, rendering a maximal amount of filtrated beer in one cycle.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO 2 concentration, and the maximum amount of CO 2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO 2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO 2 were used as control variables. Standard optimization settings were defined in order to compare the grower’s strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO 2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO 2 were reduced by 28% and 10% respectively. We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.

This paper discusses a new tubular PhotoBioReactor (PBR) called twisted tubular PBR . The geometry of a twisted tubular PBR induces swirl mixing to guarantee good exposure of microalgae to Light-Dark (LD) cycles and to the nutrients and dissolved CO 2 . The paper analyses the energy uptake for fluid transport through the twisted tubular PBR. The analysis is based on a comparison between the twisted tubular PBR and other tubular PBRs that have swirl mixing generation. Four types of tubular PBRs are simulated using Computational Fluid Dynamics (CFD); these results are used to evaluate energy consumption and mixing conditions. Swirl number is used to evaluate mixing conditions and swirl flow. On the other hand, microalgae particles performing undulatory motion are evaluated with Discrete Fourier Transform (DFT). Characteristics of the microalgae frequency in the swirl mixing depend on average flow velocity. Results show that the new twisted tubular PBR demands less energy for pumping than the other tubular PBRs that have swirl motion; providing an important step towards the construction of a highly efficient tubular PBR.

The analyses of algae biorefinery performance are commonly based on fixed performance data for each processing step. In this work, we demonstrate a model-based combinatorial approach to derive the design-specific upstream energy consumption and biodiesel yield in the production of biodiesel from microalgae. Process models based on mass and energy balances and conversion relationships are presented for several possible process units in the algae processing train. They allow incorporating the effects of throughput capacity and process conditions, which is not possible in the data-based approach. Therefore, the effect of choices in the design on the overall performance can be quantified. The process models are organised in a superstructure to evaluate all combinations of routings. First, this is done for selected fixed design conditions, which is followed by optimisation of the process conditions for each route by maximising the net energy ratio (NER), based on upstream energy consumption and biodiesel yield. A scenario based on current energy production and state-of-the art techniques for algae processing is considered. The optimised process conditions yield NER values which are up to about 30% higher than those for fixed process conditions. In addition, the approach allows a quantitative bottleneck analysis for each process route. The model-based approach proves to be a versatile tool to guide the design of efficient microalgae processing systems.

A problem in loose housing systems for laying hens is the laying of eggs on the floor; these eggs need manual collection. This job is heavy and time-consuming and automated collection is desired. For collection using a robot, a collection path is required. A novel path planning algorithm is introduced for non-uniform repetitive area coverage (NURAC) paths and evaluated based on information about floor egg distribution probability. Firstly, a spatial map was developed that describes the potential for floor eggs at each location in a poultry house. Next, paths for floor egg collection are planned with a dynamic programming approach that covers the house floor area and frequently revisits locations with a high potential on floor eggs. These paths are compared with the paths used for floor egg collection by a farmer and evaluated with help of a simulated set of floor eggs. With respect to the average time eggs are present on the floor, paths planned for a robot are compared to two collection rounds of a farmer. With respect to the structure of the path and the number of visits to locations with a high potential, the robot paths outperform the farmer. Although optimality of the path is not guaranteed, the presented results are promising for the use of a robot to collect floor eggs, and will result in a reduction of the demand for manual labour. Extending the floor egg model with feedback information could further improve the results.

Step changes in the organic loading rate (OLR) through variations in the influent chemical oxygen demand (CODin) concentration or in the hydraulic retention time (HRT) at constant COD/SO4 2- ratio (0.67) were applied to create sulfide responses for the design of a sulfide control in sulfate reducing bioreactors. The sulfide was measured using a sulfide ion selective electrode (pS) and the values obtained were used to calculate proportional-integral-derivative (PID) controller parameters.Step changes in the organic loading rate (OLR) through variations in the influent chemical oxygen demand (CODin) concentration or in the hydraulic retention time (HRT) at constant COD/SO42- ratio (0.67) were applied to create sulfide responses for the design of a sulfide control in sulfate reducing bioreactors. The sulfide was measured using a sulfide ion selective electrode (pS) and the values obtained were used to calculate proportional-integral -derivative (PID) controller parameters. The experiments were performed in an inverse fluidized bed bioreactor with automated operation using the LabVIEW software version 2009 (R). A rapid response and high sulfide increment was obtained through a stepwise increase in the CODin, concentration, while a stepwise decrease to the HRT exhibited a slower response with smaller sulfide increment. Irrespective of the way the OLR was decreased, the PS response showed a time-varying behavior due to sulfide accumulation (HRT change) or utilization of substrate sources that were not accounted for (CODin change). The pS electrode response, however, showed to be informative for applications in sulfate reducing bioreactors. Nevertheless, the recorded pS values need to be corrected for pH variations and high sulfide concentrations (>200 mg/L). (C) 2013 Elsevier Ltd. All rights reserved.

Microalgae gained much interest from industry as promising sustainable feedstock for the production of food, feed, bulk chemicals, and biofuels. Pilot scale research on microalgae is needed to bridge the gap between laboratory scale research and commercial applications. The AlgaePARC (Algae Production And Research Center) pilot facility was constructed to bridge this gap. The objective of this pilot center is to compare and improve photobioreactors and operational strategies under outdoor conditions. The pilot plant facility consists of four production systems (raceway pond, horizontal tubular reactor, vertically stacked tubular reactor and flat panels) and allows comparison of performance of these systems under identical climatological conditions. This paper describes the development of this pilot facility, decisions made during the building process and discusses the production systems including technical specifications, measurements and supporting facilities.

An increasing number of wastewater treatment plants require post-treatment to remove residual nitrogen and phosphorus. This study investigated various harvesting regimes that would achieve consistent low effluent concentrations of nitrogen and phosphorus in a phototrophic biofilm reactor. Experiments were performed in a vertical biofilm reactor under continuous artificial lighting and employing artificial wastewater. Under similar conditions, experiments were performed in near-horizontal flow lanes with biofilms of variable thickness. It was possible to maintain low nitrogen and phosphorus concentrations in the effluent of the vertical biofilm reactor by regularly harvesting half of the biofilm. The average areal biomass production rate achieved a 7 g dry weight m-2 day-1 for all different harvesting frequencies tested (every 2, 4, or 7 days), corresponding to the different biofilm thicknesses. Apparently, the biomass productivity is similar for a wide range of biofilm thicknesses. The biofilm could not be maintained for more than 2 weeks as, after this period, it spontaneously detached from the carrier material. Contrary to the expectations, the biomass production doubled when the biofilm thickness was increased from 130 µm to 2 mm. This increased production was explained by the lower density and looser structure of the 2 mm biofilm. It was concluded that, concerning biomass production and labor requirement, the optimum harvesting frequency is once per week.

In this work, the Flory Huggins Free Volume theory is used to interpret the sorption isotherms of broccoli from its composition and using physical properties of the components. This theory considers the mixing properties of water, biopolymers and solutes and has the potential to describe the sorption isotherms for varying product moisture content, composition and temperature. The required physical properties of the pure components in food became available in recent years and allow now the prediction of the sorption isotherms with this theory. Sorption isotherm experiments have been performed for broccoli florets and stalks, at two temperatures. Experimental data shows that the Flory Huggins Free Volume (FHFV) theory represents the sorption isotherm of fresh and blanched broccoli samples accurately. The results also show that blanching affects the sorption isotherm due to the change of composition via leaching solutes and the change of interaction parameter due to protein denaturation. © 2013 Springer Science+Business Media New York.

Desalination by capacitive deionization (CDI) is an emerging technology for the energy- and cost-efficient removal of ions from water by electrosorption in charged porous carbon electrodes. A variety of carbon materials, including activated carbons, templated carbons, carbon aerogels, and carbon nanotubes, have been studied as electrode materials for CDI. Using carbide-derived carbons (CDCs) with precisely tailored pore size distributions (PSD) of micro- and mesopores, we studied experimentally and theoretically the effect of pore architecture on salt electrosorption capacity and salt removal rate. Of the reported CDC-materials, ordered mesoporous silicon carbide-derived carbon (OM SiC-CDC), with a bimodal distribution of pore sizes at 1 and 4 nm, shows the highest salt electrosorption capacity per unit mass, namely 15.0 mg of NaCl per 1 g of porous carbon in both electrodes at a cell voltage of 1.2 V (12.8 mg per 1 g of total electrode mass). We present a method to quantify the influence of each pore size increment on desalination performance in CDI by correlating the PSD with desalination performance. We obtain a high correlation when assuming the ion adsorption capacity to increase sharply for pore sizes below one nanometer, in line with previous observations for CDI and for electrical double layer capacitors, but in contrast to the commonly held view about CDI that mesopores are required to avoid electrical double layer overlap. To quantify the dynamics of CDI, we develop a two-dimensional porous electrode modified Donnan model. For two of the tested materials, both containing a fair degree of mesopores (while the total electrode porosity is ∼95 vol%), the model describes data for the accumulation rate of charge (current) and salt accumulation very well, and also accurately reproduces the effect of an increase in electrode thickness. However, for TiC-CDC with hardly any mesopores, and with a lower total porosity, the current is underestimated. Calculation results show that a material with higher electrode porosity is not necessarily responding faster, as more porosity also implies longer transport pathways across the electrode. Our work highlights that a direct prediction of CDI performance both for equilibrium and dynamics can be achieved based on the PSD and knowledge of the geometrical structure of the electrodes.

Acoustic separation is a relatively new method for recovering valuable particulate matter from suspensions. This separation method is mainly used in medical technology, but may well be applicable as water purification and material recovery technique. The key question then is what separation efficiency can be reached and whether this can be realised in an energy-efficient way. In the current study, a commercially available acoustic separator, named BioSep, which employs ultrasound enhanced sedimentation, was used. With the aim to achieve a high separation efficiency with minimal energy consumption, a model-based open-loop switching control strategy was designed for the BioSep, using a numerical–experimental approach. Firstly, a dynamic BioSep model structure was derived from mass balances and its system properties were studied. Then, the unknown system parameters were estimated from steady state and dynamic experimental data and subsequently, the switching times of the control input were determined. The model with switching control outputs was then validated by experiments. Finally, the control strategy was implemented in the experimental setup and tested using suspended potato starch. Results showed that the optimal control strategy reached a mass separation efficiency of 96%, which was an improvement of 4% with respect to the initial settings, while using less energy.

Microalgae productivity in tubular photobioreactors depends on algae species, location, tube diameter, biomass concentration, distance between tubes and for vertically stacked systems, the number of horizontal tubes per stack. A simulation model for horizontal and vertically stacked horizontal tubular reactors was made to quantify the effect of these decision variables on production yield. The model uses reactor dimensions, dynamic sunlight patterns over the day and year, and growth characteristics of algae species as inputs. Scenario studies were done to study the effect of decision variables on reactor performance in The Netherlands, France and Algeria. Results indicate that the areal biomass productivity in vertically stacked photobioreactors is 25–70% higher than in plain horizontal systems. Reactor design is location specific because light conditions differ. In The Netherlands, the best horizontal distance between tubes is 0.05 m for horizontal and 0.25 m for vertical systems. For France and Algeria, the best horizontal distance between vertical systems is 0.20 m and 0.15 m respectively. System performance can be improved further by using light reflection materials on the ground surface. Improving the transparency properties of tube material does not significantly affect areal productivity.

In a past study the authors drew attention to the fact that time-varying discrete-time linear systems may be temporarily uncontrollable and unreconstructable and that this is vital knowledge for both control engineers and system scientists. Describing and detecting the temporal loss of controllability and reconstructability requires considering discrete-time systems with variable dimensions and the j-step, k-step Kalman decomposition. In this study for linear discrete-time systems with variable dimensions measures of temporal and one-step stabilisability and detectability are developed. These measures indicate to what extent the temporal loss of controllability and reconstructability may lead to temporal instability of the closed-loop system when designing a static state or dynamic output feedback controller. The measures are calculated by solving specific linear quadratic cheap control problems by means of standard linear quadratic control algorithms. The importance of our developments for control system design is illustrated by means of two numerical examples.

Ammonia nitrogen is one of the most common inhibitors in the anaerobic digestion of complex wastes containing high concentrations of ammonia like animal manures, blackwater and waste oil from gastronomy. The inhibiting effect of ammonia on methanogenesis has been well established. In contrast, the knowledge on the effect of ammonia on organic matter hydrolysis is rather limited. This study focuses on evaluating the effect of ammonia on the hydrolysis of carbohydrates and lipids, which are commonly found in biomass. Batch digestion of tributyrin and cellulose at varying ammonia concentrations were performed, using biomass adapted to 4.9 g NH 4 + –N.l −1 . From this experimental study it was concluded that total ammonia nitrogen in the range of 2.4–7.8 g NH 4 + –N.l −1 (283–957 mg NH 3 –N.l −1 ) does not inhibit the hydrolysis of tributyrin or cellulose. This result is further confirmed by mathematical analysis of the estimated variation of the first-order hydrolysis constant as a function of the total ammonia concentration.

Algorithms for optimal reduced-order dynamic output feedback control of linear discrete-time systems with white stochastic parameters are U-D factored in this paper. U-D factorisation enhances computational accuracy, stability and possibly efficiency. Since U-D factorisation of algorithms for optimal full-order output feedback controller design was recently published by us, this paper focusses on the U-D factorisation of the optimal oblique projection matrix that becomes part of the solution as a result of order-reduction. The equations producing the solution are known as the optimal projection equations which for discrete-time systems have been strengthened in the past. The U-D factored strengthened discrete-time optimal projection equations are presented in this paper by means of a transformation that has to be applied recursively until convergence. The U-D factored and conventional algorithms are compared through a series of examples.

Worldwide there is a wide variety of greenhouse types en cultivated crops, and consequently control options and control solutions differ. Yet, there are common characteristics that must be considered in every control solution. A versatile framework for greenhouse climate control aiming at economic optimal control is presented. The framework is based on time-scale decomposition. Factors to determine the feasibility of the approach are discussed, as well as options to overcome some of the challenges and issues. The expectation is that with expansion and professionalization of the greenhouse industry the scope for optimal control will become wider.

Background Transcription of genes coding for xylanolytic and cellulolytic enzymes in Aspergillus niger is controlled by the transactivator XlnR. In this work we analyse and model the transcription dynamics in the XlnR regulon from time-course data of the messenger RNA levels for some XlnR target genes, obtained by reverse transcription quantitative PCR (RT-qPCR). Induction of transcription was achieved using low (1 mM) and high (50 mM) concentrations of D-xylose (Xyl). We investigated the wild type strain (Wt) and a mutant strain with partial loss-of-function of the carbon catabolite repressor CreA (Mt). Results An improved kinetic differential equation model based on two antagonistic Hill functions was proposed, and fitted to the time-course RT-qPCR data from the Wt and the Mt by numerical optimization of the parameters. We show that perturbing the XlnR regulon with Xyl in low and high concentrations results in different expression levels and transcription dynamics of the target genes. At least four distinct transcription profiles were observed, particularly for the usage of 50 mM Xyl. Higher transcript levels were observed for some genes after induction with 1 mM rather than 50 mM Xyl, especially in the Mt. Grouping the expression profiles of the investigated genes has improved our understanding of induction by Xyl and the according regulatory role of CreA. Conclusions The model explains for the higher expression levels at 1 mM versus 50 mM in both Wt and Mt. It does not yet fully encapsulate the effect of partial loss-of-function of CreA in the Mt. The model describes the dynamics in most of the data and elucidates the time-dynamics of the two major regulatory mechanisms: i) the activation by XlnR, and ii) the carbon catabolite repression by CreA. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0257-4) contains supplementary material, which is available to authorized users.

Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and experimental data can be used to acquire valid estimates of the material parameters. In our design application, a finite element (FE) model of an ultrasonic particle separator, driven by an ultrasonic transducer in thickness mode, is required. A limited set of material parameters for the piezoelectric transducer were obtained from the manufacturer, thus preserving prior physical knowledge to a large extent. The remaining unknown parameters were estimated from impedance analysis with a simple experimental setup combined with a numerical optimization routine using 2-D and 3-D FE models. Thus, a full set of physically interpretable material parameters was obtained for our specific purpose. The approach provides adequate accuracy of the estimates of the material parameters, near 1%. These parameter estimates will subsequently be applied in future design simulations, without the need to go through an entire series of characterization experiments. Finally, a sensitivity study showed that small variations of 1% in the main parameters caused changes near 1% in the eigenfrequency, but changes up to 7% in the admittance peak, thus influencing the efficiency of the system. Temperature will already cause these small variations in response; thus, a frequency control unit is required when actually manufacturing an efficient ultrasonic separation system.

Parameter estimation plays an important role in physical modelling, but can be problematic due to the complexity of spatiotemporal models that are used for analysis, control and design in industry. In this paper we aim to circumvent these problems by using a methodology that approximates a model, or a part of a model, by a first-order plus dead time (FOPDT) approximation, explicit in the physical parameters. The FOPDT model with its physical parameters can be calibrated and validated to experimental data via an Output Error identification. The methodology is illustrated by a model of a temperature-controlled food storage room using experimental data. The complex part of the model is reduced to an accurate first-order model that has predictive power with respect to physical parameter variations. Moreover, this methodology allows one to test model adjustments for phenomena that were not considered in the physical model, in a relatively easy way. (C) 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.

Now that more than half of the world's population lives in cities, improving urban resource cycles is crucial for sustainable urban development. Currently cities are highly dependent on external supplies of water, energy, nutrients, and other materials, while local possibilities of self-production of such resources are generally overlooked. This article describes a novel method, the urban harvest approach (UHA), its rationale, and the steps toward sustainable urban resource planning. The UHA is based on the urban metabolism concept. Herein, a city is regarded to have multiple potentials in the form of untapped primary and secondary (already used) resources that can be utilized. The UHA works on the principle that urban systems and their direct peri-urban surroundings can become self-sufficient by applying three strategies: minimizing demand, minimizing outputs, and multisourcing. An elaboration of the UHA for the resource “water” at the building scale is also presented in this article. A freestanding house in the Netherlands and a similar house in Australia were studied, with a focus on indoor consumption. Results showed a 40% demand reduction when water-saving technologies were implemented. In both cases, after demand minimization, local resources were sufficient to cover the demand by recycling grey water and harvesting rainwater. These findings confirm that a multimeasure implementation according to the three different strategies is needed to achieve sustainable urban water systems. The UHA helps to structure large influences of urban context on water and other resource cycles as an aid to urban planners and water managers in designing sustainable urban areas.

Physicochemical processes, such as the Lo-cat and Amine-Claus process, are commonly used to remove hydrogen sulfide from hydrocarbon gas streams such as landfill gas, natural gas, and synthesis gas. Biodesulfurization offers environmental advantages, but still requires optimization and more insight in the reaction pathways and kinetics. We carried out experiments with gas lift bioreactors inoculated with haloalkaliphilic sulfide-oxidizing bacteria. At oxygen-limiting levels, that is, below an O(2)/H(2)S mole ratio of 1, sulfide was oxidized to elemental sulfur and sulfate. We propose that the bacteria reduce NAD(+) without direct transfer of electrons to oxygen and that this is most likely the main route for oxidizing sulfide to elemental sulfur which is subsequently oxidized to sulfate in oxygen-limited bioreactors. We call this pathway the limited oxygen route (LOR). Biomass growth under these conditions is significantly lower than at higher oxygen levels. These findings emphasize the importance of accurate process control. This work also identifies a need for studies exploring similar pathways in other sulfide oxidizers such as Thiobacillus bacteria.

Polarization curves are of paramount importance for the detection of toxic components in microbial fuel cell (MFC) based biosensors. In this study, polarization curves were made under non-toxic conditions and under toxic conditions after the addition of various concentrations of nickel, bentazon, sodiumdodecyl sulfate and potassium ferricyanide. The experimental polarization curves show that toxic components have an effect on the electrochemically active bacteria in the cell. (Extended) Butler Volmer Monod (BVM) models were used to describe the polarization curves of the MFC under nontoxic and toxic conditions. It was possible to properly fit the (extended) BVM models using linear regression techniques to the polarization curves and to distinguish between different types of kinetic inhibitions. For each of the toxic components, the value of the kinetic inhibition constant Ki was also estimated from the experimental data. The value of Ki indicates the sensitivity of the sensor for a specific component and thus can be used for the selection of the biosensor for a toxic component. © 2012 by the authors.

The nutritional requirements of stem cells have not been determined; in particular, the amino acid metabolism of stem cells is largely unknown. In this study, we investigated the amino acid metabolism of human mesenchymal stem cells (hMSCs), with focus on two questions: Which amino acids are consumed and/or secreted by hMSCs and at what rates? To answer these questions, hMSCs were cultured on tissue culture plastic and in a bioreactor, and their amino acid profile was analyzed. The results showed that the kinetics of hMSCs growth and amino acid metabolism were significantly higher for hMSCs in tissue culture plastic than in the bioreactor. Despite differences in culture conditions, 8 essential and 6 nonessential amino acids were consumed by hMSCs in both tissue culture plastic and bioreactor cultures. Glutamine was the most consumed amino acid with significantly higher rates than for any other amino acid. The metabolism of nonessential amino acids by hMSCs deviated significantly from that of other cell lines. The secretion of alanine, glycine, glutamate, and ornithine by hMSCs showed that there is a strong overflow metabolism that can be due to the high concentrations of amino acids provided in the medium. In addition, the data showed that there is a metabolic pattern for proliferating hMSCs, which can contribute to the design of medium without animal serum for stem cells. Further, this study shows how to implement amino acid rates and metabolic principles in three-dimensional stem cell biology.

Bioremoval of H2S from gas streams became popular in recent years because of high process efficiency and low operational costs. To expand the scope of these processes to gas streams containing volatile organic sulfur compounds, like thiols, it is necessary to provide new insights into their impact on overall biodesulfurization process. Published data on the effect of thiols on biodesulfurization processes are scarce. In this study, we investigated the effect of methanethiol on the selectivity for sulfur production in a bioreactor integrated with a gas absorber. This is the first time that the inhibition of biological sulfur formation by methanethiol is investigated. In our reactor system, inhibition of sulfur production started to occur at a methanethiol loading rate of 0.3 mmol L(-1) d(-1). The experimental results were also described by a mathematical model that includes recent findings on the mode of biomass inhibition by methanethiol. We also found that the negative effect of methanethiol can be mitigated by lowering the salinity of the bioreactor medium. Furthermore, we developed a novel approach to measure the biological activity by sulfide measurements using UV-spectrophotometry. On the basis of this measurement method, it is possible to accurately estimate the unknown kinetic parameters in the mathematical model.

This work aims at exploring the feasibility of a combined process bioflocculation to concentrate sewage organic matter and anaerobic fermentation to produce volatile fatty acids (VFA). Bioflocculation, using a high-loaded aerobic membrane bioreactor (HL-MBR), was operated at an HRT of 1 h and an SRT of 1 day. The HL-MBR process removed on average 83% of sewage COD, while only 10% of nitrogen and phosphorus was removed. During anaerobic fermentation of HL-MBR concentrate at an SRT of 5 days and 35 °C, specific VFA production rate of 282 mg VFA-COD/g VSS could be reached and consisted of 50% acetate, 40% propionate and 10% butyrate. More than 75% of sewage COD was diverted to the concentrate, but only 15% sewage COD was recovered as VFA, due to incomplete VSS degradation at the short treatment time applied. This shows that combined process for the VFA production is technologically feasible and needs further optimization.

Tubular photobioreactors (PBR) have great potential for microalgae cultivation due to its high productivity compared with open ponds. However, the energy uptake for fluid circulation and mixing is significant, impacting the operation and production costs. In this work, we investigate by CFD simulation the effect of wall turbulence promoters, i.e. profiles at the inner tube wall, at low flow velocities (0.1–0.3 m/s). The use of these wall turbulence promoters is compared to the mixing behaviour in standard tubular PBRs at flow velocity of 0.5 m/s. It was found that the wall turbulence promoters have at flow velocities of 0.2–0.25 m/s better mixing behaviour as in standard PBRs while the energy uptake is 60–80% lower.

Binnen Wageningen UR wordt op grote schaal samengewerkt met bedrijven. Dat helpt niet alleen het bedrijf zelf vooruit, maar ook de biobased economy in het algemeen. Prof. Dr. Harry Bitter: ‘De kennis over de eigenschappen van bijvoorbeeld bioplastics wordt alleen maar groter.’

Elevated emissions of sulfur dioxide, nitrogen oxides and ammonia in China have resulted in high levels of sulfur and nitrogen deposition, being contributors to soil acidification, especially in and near large cities. However, knowledge gaps still exist in the way that large cities shape spatial patterns of acid deposition. Here, we assessed the patterns of pH, sulfate, nitrate and ammonium in bulk precipitation and throughfall in southern China’s forests by synthesizing data from published literature. Concentrations and fluxes of sulfate, nitrate and ammonium in bulk precipitation and throughfall exhibited a power-law increase with a closer distance to the nearest large cities, and accordingly pH showed a logarithmic decline. Our findings indicate the occurrence of urban ‘acid islands’ with a critical radius of approximately 70¿km in southern China, receiving potential acid loads of more than 2 keq ha-1 yr-1. These urban acid islands covered an area of 0.70¿million km2, accounting for nearly 30% of the land area in southern China. Despite a significant capacity to neutralize acids in precipitation, our analysis highlights a substantial contribution of ammonium to potential acid load. Our results suggest a joint control on emissions of multiple acid precursors from urban areas in southern China

Elevated emissions of sulfur dioxide, nitrogen oxides and ammonia in China have resulted in high levels of sulfur and nitrogen deposition, being contributors to soil acidification, especially in and near large cities. However, knowledge gaps still exist in the way that large cities shape spatial patterns of acid deposition. Here, we assessed the patterns of pH, sulfate, nitrate and ammonium in bulk precipitation and throughfall in southern China’s forests by synthesizing data from published literature. Concentrations and fluxes of sulfate, nitrate and ammonium in bulk precipitation and throughfall exhibited a power-law increase with a closer distance to the nearest large cities, and accordingly pH showed a logarithmic decline. Our findings indicate the occurrence of urban ‘acid islands’ with a critical radius of approximately 70¿km in southern China, receiving potential acid loads of more than 2 keq ha-1 yr-1. These urban acid islands covered an area of 0.70¿million km2, accounting for nearly 30% of the land area in southern China. Despite a significant capacity to neutralize acids in precipitation, our analysis highlights a substantial contribution of ammonium to potential acid load. Our results suggest a joint control on emissions of multiple acid precursors from urban areas in southern China

Biogas, synthesis and natural gas streams often require treatment because of the presence of gaseous hydrogen sulphide (H2S). About 25 years ago, a biotechnological gas treatment process was developed as an alternative to the conventionally applied technologies. This process is known as the Thiopaq process and offers a number of advantages compared to the existing physical-chemical processes. Depending on the process conditions, H2S is oxidized to elemental bio-sulfur (90-94 mol%) and sulphate (6-10 mol%). In order to enable cost effective large scale applications, the selectivity for sulfur production should be increased to more than 97 mol%. Hence, a better understanding of the combined effect of abiotic and biological reaction kinetics and the relation to hydrodynamic characteristics is required. The first part of this PhD study focuses on biological reaction kinetics and biological pathways for sulphide oxidation that occur in the process at haloalkaline conditions. It was found that two different sulfide oxidizing enzyme systems are present in haloalkaline sulfide oxidizing bacteria. It has been hypothesized that the different enzymatic routes are determined by the process conditions. Both enzyme systems were taken into account to propose and validate a new physiological mathematical model that can handle multi-substrates and multi-products. In the second part of the thesis, this model was evaluated via a normalized sensitivity method and it was demonstrated that certain key parameters affect the activity of the biomass at different substrate levels. Furthermore, from CSTR simulations it has been demonstrated that non-linear effects are of importance when scaling up from lab-scale to full-scale industrial units. Finally, the developed kinetic models have been incorporated in a full-scale biodesulfurization model that includes the effects of turbulent flow regimes and mass transfer of oxygen. This enables us to better understand the overall process. Moreover, the model can also be used as a tool to design model-based control strategies which will lead to better overall process performance, i.e. maximize sulfur production and minimize chemical consumption rates.

An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the potential of advanced modelling and control to improve the production and quality of food. Significant improvements are demonstrated in this paper through simulation experiments. Optimal scheduling and control comprises a mixed integer non-linear programming problem (MINLP). By making some suitable assumptions that are approximately satisfied in practice, we manage to significantly simplify the problem by turning it into an ordinary non-linear programming problem (NLP) for which solution methods are readily available. The adaptive part of our scheduler and controller performs model parameter adaptations. These are also obtained by solving associated NLP problems. During cleaning stages in between membrane filtrations enough time is available to solve the NLP problems. This allows for real-time implementation.

Water and resource availability in sufficient quantity and quality for anthropogenic needs represents one of the main challenges in the coming decades. To prepare for upcoming challenges such as increased urbanization and climate change related consequences, innovative and improved resource management concepts are indispensable. In recent years we have developed and applied the Urban Harvest Approach (UHA). The UHA proposes to model and quantify the urban water cycle on different temporal and spatial scales. This approach allowed us to quantify the impact of the implementation of water saving measures and new water treatment concepts in cities. In this paper we will introduce the UHA and present for urban water cycles. Furthermore, we will show first results for an extension to energy cycles and highlight future research items (e.g., nutrients, water-energy-nexus). Key words | Resource cycles, Water management, Water-Energy Nexus, Decision-Support

In a modern greenhouse there are a number of alternative systems that can be deployed to control the climate, and the choice what to use and when is not easy for the grower. A novel management system is proposed, consisting of an energy input minimizing module, and a module to realise the determined input with the available equipment. The current paper describes the energy minimization part. A dynamic optimization tool based on optimal control theory was used to obtain time trajectories of the energy flux that minimizes total external energy input over the year, while maintaining greenhouse air temperature and humidity between grower defined bounds. By giving the grower the lead in defining the bounds, the method stays as closely as possible to the grower’s daily practice and experience, and no crop production models and market prices are needed. The underlying dynamic model of temperature and humidity, based on known physical principles and parameters, compared very well with unique, year round high frequent data from a commercial rose greenhouse. A relatively simple crop transpiration model was validated separately, with very good results. It was shown that over twelve selected days, distributed over the entire year, the energy saving potential as compared to the actual grower’s practice is substantial. This potential was related to the definition of lower and upper bounds, less natural ventilation at colder days, and more natural ventilation and less heating at warmer days. The prominent role of the bounds was clearly demonstrated. Relaxing the temperature and humidity bounds decreases the energy input to the greenhouse. While this is obvious, the quantification of the effect as demonstrated here is of great interest to growers, and is essential for the development of the second part of the system.

The answer lies right in front of us, but we refuse to see it. Both relativity and quantum theory, the two pillars of fundamental physics, are modified in this paper to make them also explain the physical phenomena they describe. With this explanation, all current inconsistencies between the two vanish. The modifications relate to the presence of a medium, which is in fact potential energy, in three-dimensional space. This medium acts as a reference system, in accordance with Mach’s principle. The speed of light, therefore, is not absolute but relative to the medium and thus to the observer. It is also dependent on medium density. Quantum waves are real scalar waves occurring in the potential energy medium, not probabilities of particles being present. Real scalar quantum waves in three-dimensional space make up the whole of physics representing manifest energy. Particles therefore do not exist; they are local manifestations of real scalar quantum waves. As a result, the Doppler effect and wave interference play a central role in physics. Moreover, the dependence of quantum wave velocity (speed of light) on medium density provides the energy exchange mechanism that is central to physics because all physical phenomena, including observation, concern energy exchange, or interaction. The conceptual simplicity of the model of physics proposed in this paper is shown to clarify a series of paradoxes and ill-understood phenomena at the fundamental level of physics such as wave-particle duality, the twins paradox, and the double slit experiment. As to entanglement, superposition, and nonlocality, the model implies that only weak versions of these properties exist.

We report on an efficient method to concentrate suspensions in a flow channel comprising sparse periodic arrays of obstacles. The obstacle spacings are a few times larger than the diameter of the particles. We perform up-scaled experiments, in which all particles flow along a few obstacle lines rotated with respect to the main flow direction. We found that for a diluted suspension a single line is sufficient to displace all particles into a concentrated stream. With visual high speed camera images particle–particle interactions were observed at increasing concentrations. Although one obstacle line was no longer enough to retain all particles, few additional obstacle lines facilitated good separation. This provides the insight that while the angle of the lines determines the primary separation, the number of lines is coupled to the maximum particle volume fraction that can be separated. With CFD simulations we showed that the flow resistance in these sparse arrays is very low and that the flow distribution across the outlets is easily controlled by the outlet tubing. These conclusions show the potential of sparse obstacle arrays for effective concentration of suspensions.

This study explored the potential of volatile fatty acids (VFA) production from sewage by a combined high-loaded membrane bioreactor and sequencing batch fermenter. VFA production was optimized with respect to SRT and alkaline pH (pH 8–10). Application of pH shock to a value of 9 at the start of a sequencing batch cycle, followed by a pH uncontrolled phase for 7 days, gave the highest VFA yield of 440 mg VFA-COD/g VSS. This yield was much higher than at fermentation without pH control or at a constant pH between 8 and 10. The high yield in the pH 9 shocked system could be explained by (1) a reduction of methanogenic activity, or (2) a high degree of solids degradation or (3) an enhanced protein hydrolysis and fermentation. VFA production can be further optimized by fine-tuning pH level and longer operation, possibly allowing enrichment of alkalophilic and alkali-tolerant fermenting microorganisms.

Voor veel toepassingen is biologische afbreekbaarheid niet gewenst.

We review models for bulk storage facilities.A comprehensive generally applicable model is still lacking.Simulations using computational fluid dynamics are the solution.Storage policies that focus on controlling the indoor climate have limitations.Sustainable quality control of the stored product itself is within reach. Storage of season-dependent agro-materials is a key process in providing food, feed and biomass throughout the whole year. We review the state of the art in physical modelling, simulation and control of ventilated bulk storage facilities, and in particular the storage of potatoes, from a state-space perspective. The basic physical relations that describe the dynamic behaviour of air and potatoes in a storage facility use laws of conservation of mass, energy and momentum and corresponding constitutive laws. However, a very complex physically based storage model is obtained if the macro climate in the air channels and the micro climate around the potato and all the interactions between air and potato are taken into consideration. Therefore, lumped, 1-D, 2-D and 3-D macro, and also some micro climate storage models were developed. These models basically focus on heat and moisture generation and transportation. The latest developments give more and more insight into the spatial distribution of the macro climate, using CFD simulation techniques. Traditionally, the indoor climate instead of the potato quality is controlled, to maintain a good product quality. However, quality control of the product can be realised if there is knowledge between the spatial distribution of temperature and moisture and the product quality. With the developments in CFD simulation, control algorithms and the state space framework, modelling and control of product quality is within reach.

International audience; Environmental impact is an essential aspect for the introduction of algae production systems. As information of large scale algae production is hardly available, process simulation is the only way to evaluate environmental sustainability in an early phase of process design. Simulation results allow the evaluation of production and design scenarios, and reveal the potential to improve the Life Cycle Performance of algae production systems. In this work, we discuss how choices in the process design of algae production systems (cultivation, biorefinery and the supply chain) advance LCA-results.

Binnen Wageningen UR wordt op grote schaal samengewerkt met bedrijven. Dat helpt niet alleen het bedrijf zelf vooruit, maar ook de biobased economy in het algemeen. Prof. Dr. Harry Bitter: ‘De kennis over de eigenschappen van bijvoorbeeld bioplastics wordt alleen maar groter.’

This study compares the thermodynamic performance of three industrial bread production chains: one that generates food waste, one that avoids food waste generation, and one that reworks food waste to produce new bread. The chemical exergy flows were found to be much larger than the physical exergy consumed in all the industrial bread chains studied. The par-baked brown bun production chain had the best thermodynamic performance because of the highest rational exergetic efficiency (71.2%), the lowest specific exergy losses (5.4 MJ/kg brown bun), and the almost lowest cumulative exergy losses (4768 MJ/1000 kg of dough processed). However, recycling of bread waste is also exergetically efficient when the total fermented surplus is utilizable. Clearly, preventing material losses (i.e. utilizing raw materials maximally) improves the exergetic efficiency of industrial bread chains. In addition, most of the physical (non-material related) exergy losses occurred at the baking, cooling and freezing steps. Consequently, any additional improvement in industrial bread production should focus on the design of thermodynamically efficient baking and cooling processes, and on the use of technologies throughout the chain that consume the lowest possible physical exergy.

In the sulphate-reducing process, bioprocess control can be used to regulate the competition between microbial groups, to optimize the input of the electron donor and/or to maximize or minimize the production of sulphide. As shown in this review, modelling and monitoring are important tools in the development and application of a bioprocess control strategy. Pre-eminent literature on modelling, monitoring and control of sulphate-reducing processes is reviewed. This paper firstly reviews existing mathematical models for sulphate reduction, focusing on models for biofilms, microbial competition, inhibition and bioreactor dynamics. Secondly, a summary of process monitoring strategies is presented. Special attention is given to in situ sensors for sulphate, sulphide and electron donor concentrations as well as for biomass activity and composition. Finally, the state of the art of the bioprocess control strategies in biological sulphate reduction processes is overviewed.

Harry Bitter, sinds twee jaar hoogleraar Biobased Chemistry & Technology aan de Wageningen Universiteit, pleit voor meer chemie en katalyse in het onderzoek naar biobased producten. ‘Mijn onderzoeksfocus ligt op hoe je de omzettingen van biomassa naar product zo optimaal mogelijk kunt uitvoeren. Voor mij zijn de reacties een vehikel om nieuwe, betere katalysatoren te ontwikkelen.’