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Threshold verifiable multi‐secret sharing based on elliptic curves and Chinese remainder theorem
(2019)
The use of complex reaction schemes is accompanied by high computational cost in 3D CFD simulations but is particularly important to predict pollutant emissions in internal combustion engine simulations. One solution to tackle this problem is to solve the chemistry prior the CFD run and store the chemistry information in look-up tables. The approach presented combines pre-tabulated progress variable-based source terms for auto-ignition as well as soot and NOx source terms for emission predictions. The method is coupled to the 3D CFD code CONVERGE v2.4 via user-coding and tested over various speed and load passenger-car Diesel engine conditions. This work includes the comparison between the combustion progress variable (CPV) model and the online chemistry solver in CONVERGE 2.4. Both models are compared by means of combustion and emission parameters. A detailed n-decane/α-methyl-naphthalene mechanism, comprising 189 species, is used for both online and tabulated chemistry simulations. The two chemistry solvers show very good agreement between each other and equally predict trends derived experimentally by means of engine performance parameters as well as soot and NOx engine-out emissions. The CPV model shows a factor 8 speed-up in run-time compared to the online chemistry solver without compromising the accuracy of the solution.
The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low. This work presents a novel methodology to couple the stochastic reactor model and the Non-dominated Sorting Genetic Algorithm. First, the stochastic reactor model is calibrated for 10 low, medium and high load operating points at various engine speeds. Second, each operating point is optimized to find the lowest fuel consumption and specific NOx emissions. The optimization input parameters are the temperature at intake valve closure, the compression ratio, the start of injection, the injection pressure and exhaust gas recirculation rate. Additionally, it is ensured that the maximum peak cylinder pressure and turbine inlet temperature are not exceeded. This enables a safe operation of the engine and exhaust aftertreatment system under the optimized conditions. Subsequently, a reliability analysis is performed to estimate the effect of off-nominal conditions on the objectives and constraints. The novel multi-objective optimization methodology has proven to deliver reasonable results. The zero-dimensional stochastic reactor model with tabulated chemistry is a fast running physics-based model that allow to run large optimization problems in a short amount of time. The combination with the reliability analysis also strengthens the confidence in the simulation-based optimized engine operation parameters.
Our society faces a carbon dilemma whereby there is an imbalance between our need for carbon and the dark side of its utilization. Unlike electricity, heat and mobility sectors where a transition towards renewable energy sources is possible, the chemical industry has no alternative to carbon sources for its production. This paper carried out a case analysis of the German chemical industry. The objective is to identify challenges posed by the human dimension for its carbon transition from a dependence on imported carbon resources towards cleaner and sustainable production using domestic primary and secondary carbon feedstock alternatives. Findings from a representative survey study carried out in Germany in October 2017 showed widespread public misconceptions regarding what are carbon sources and a lack of mental associations regarding the use of domestic biomass, coal, waste and CO2 as feedstock alternatives for chemical production. Furthermore, significant regional difference in support/resistance for coal-to-chemicals as a carbon transition route is also observed. This paper represents a first effort to bridge the gap between transition and circular economy research to facilitate the early identification of human-related barriers to a carbon transition for the chemical industry.
Electroencephalographic (EEG) source imaging depends upon sophisticated signal processing algorithms for data cleaning, source separation, and localization. Typically, these problems are addressed separately using a variety of heuristics, making it difficult to systematize a methodology for extracting robust EEG source estimates on a wide range of experimental paradigms. In this paper, we propose a unifying Bayesian framework in which these apparently dissimilar problems can be understood and solved in a principled manner using a single algorithm. We explicitly model the effect of non-brain sources by augmenting the lead field matrix with a dictionary of stereotypical artifact scalp projections. We propose to populate the artifact dictionary with non-brain scalp projections obtained by running Independent Component Analysis (ICA) on an EEG database. Within a parametric empirical Bayes (PEB) framework, we use an anatomical brain atlas to parameterize a source prior distribution that encourages sparsity in the number of cortical regions. We show that, in our inversion algorithm, PEB+ (PEB with the addition of artifact modeling), the sparsity prior has the property of inducing the segregation of the cortical activity into a few maximally independent components with known anatomical support. Artifacts produced by electrooculographic and electromyographic activity as well as single-channel spikes are also segregated into their respective components. Of theoretical relevance, we use our framework to point out the connections between Infomax ICA and distributed source imaging. We use real data to demonstrate that PEB+ outperforms Infomax for source separation on short segments of data and, unlike the popular Artifact Subspace Removal algorithm, it can reduce artifacts without significantly distorting clean epochs. Finally, we analyze mobile brain/body imaging data to characterize the brain dynamics supporting heading computation during full-body rotations. In this example, we run PEB+ followed by the spectral analysis of the activity in the retrosplenial cortex, largely replicating the findings of previous experimental literature.
There is a growing consensus concerning the negative consequences of inappropriate workload on employee’s health and the safety of persons. In a simulator study, we focused on air traffic controllers during arrival management tasks. Our aim was to find out if the number of aircraft or the occurrence of an exceptional event added load to the subjectively experienced workload. The workload was assessed using the NASA-TLX, instantaneous self-assessment (ISA) questionnaire, and expert ratings. Our sample consisted of 21 subjects. According to standard ANOVA procedures, controllers’ subjective ratings showed a high-significant discrimination between the different air traffic demands but only a weak-significant discrimination between sessions with and without
event. In particular, we were not able to obtain a significant interaction effect between traffic volume and event. However, the examination of between-subject factors could reveal additional information about controller’s rating behavior. We currently conclude that while the effect of the number of aircraft was evident, the impact of an exceptional event
remained doubtful.
Laminar burning velocities of ethanol-water-air mixtures have been determined using the heat flux method. Aqueous ethanol contained 0–40% of water by mole fraction. Laminar premixed flat flames were stabilized on a perforated burner under adiabatic conditions for the equivalence ratio range from 0.7 to 1.4. Burning velocity measurements were performed for the initial gas temperature of 358 K and at atmospheric pressure. The results for ethanol-air flames are in good agreement with the previous data obtained using the same heat flux method. The present and literature experimental data were compared against predictions using four different kinetic models. All models show uniform behaviour over the range of ethanol dilution by water covered in the present study. However, model predictions significantly diverge from the experimental data obtained in spherical flames. To quantify the effect of dilution on the laminar burning velocity, an empirical dimensionless correlation has been derived from the experimental data and predictions of the models tested. Further numerical analyses were performed to identify the effects of water addition on laminar burning velocities. Results suggested that water strongly interacts with the H2/O2 and C1 oxidation/recombination routes.
The present study describes the utilization of a reaction mechanism generator for the development of chemical kinetic models. The aim of the investigation is twofold. The in-house developed mechanism generator is updated with reaction classes reported in the literature, and the effect of the lower hydrocarbon chemistry, that is, base chemistry, on the generation process is assessed. For this purpose, the algorithm is implemented on two different base chemistry mechanisms, that have previously been validated against a different range of hydrocarbons, that is, the mechanisms of the groups coauthoring the study. n-Hexane has been used as a modeling target due to its important role in combustion studies as a surrogate for engine and aviation applications. The steps of the generation process are given in detail as this is the first time the current algorithm is utilized. The two generated mechanisms are compared against speciation data, ignition delay times, and flame velocities from the literature. The overall agreement of the generated mechanisms is satisfying; discrepancies exist in the negative temperature coefficient regime. Reaction path analysis and sensitivity analysis were performed, revealing the reactions that cause the different mechanism performance. Among others, the study reveals that the generated schemes pose a fast and adequate alternative to literature mechanisms; it is however evident that the latter may include more detailed reaction paths and are therefore superior in terms of validation.
This essay provides a conceptual contribution to the understanding of solidarity rights and their relevance in an increasingly interconnected world, focusing on the common heritage of humanity. The analysis lies at the intersection of human rights with international heritage law, two areas that have developed along different historical trajectories. Recently policymakers and scholars have emphasized their interrelationships, suggesting that heritage is a human right, that human rights provide a framework for heritage protection, and that human rights themselves are a common heritage of humanity. Yet less attention has been given to the fact that the common heritage of humanity is also a principle of international law. As a legal formulation of the stewardship philosophy known in many religions and cultures, the common heritage of humanity embodies altruistic, equalitarian, and moral ideals. It is at the same time a controversial principle, because it introduces humanity as subject of law and triggers duties of solidarity and commitments that challenge state sovereignty. Drawing on the common heritage of humanity as principle of law in different historical and legal contexts, this essay explores its potential to illustrate the underlying message of solidarity rights and the implications of solidarity rights.
Mappe V: Deutsche Künstler
(2019)
Sicherheitsbetrachtungen im Fall von stromstarken Erdfehlern in NOSPE-Netzen und bei Netzkopplung
(2019)
With the recent emergence of efficient zero-knowledge (ZK) proofs for general circuits, while efficient zero-knowledge proofs of algebraic statements have existed for decades, a natural challenge arose to combine algebraic and non-algebraic statements. Chase et al. (CRYPTO 2016) proposed an interactive ZK proof system for this cross-domain problem. As a use case they show that their system can be used to prove knowledge of a RSA/DSA signature on a message m with respect to a publicly known Pedersen commitment gmhr. One drawback of their system is that it requires interaction between the prover and the verifier.
This is due to the interactive nature of garbled circuits, which are used in their construction. Subsequently, Agrawal et al. (CRYPTO 2018) proposed an efficient non-interactive ZK (NIZK) proof system fo cross-domains based on SNARKs, which however require a trusted setup assumption. In this paper, we propose a NIZK proof system for cross domains that requires no trusted setup and is efficient both for the prover and the verifier.
Our system constitutes a combination of Schnorr based ZK proofs and ZK proofs for general circuits by Giacomelli et al. (USENIX 2016). The proof size and the running time of our system are comparable to the approach by Chase et al. Compared to Bulletproofs (SP 2018), a recent NIZK proofs system on committed inputs, our techniques achieve asymptotically better performance on prover and verifier, thus presenting a different trade-off between the proof size and the running time.
The neohypoplastic model [12] eliminates several shortcomings of the hypoplastic vW-HP model [17]. The most important improvements are presented here. The general form of the constitutive equation is slightly modified by two additional terms in brackets. The functions and are completely reformulated in order to deal with numerous problems of the old model: perpetuum mobile of the second kind, too small dilatancy during triaxial tension paths, poor predictions of peak stress and inconsistent behaviour of the model at the upper density limit. A new state variable similar to the one from the Sanisand model [3] is introduced. The hitherto used state variables: the stress and the void ratio are preserved, of course. Moreover, a new kind of nonlinearity is proposed: the rotation of the deviatoric stress response. The problems connected to the extension intergranular-strain extension are not discussed here.
This paper presents a novel and simplified approach to simulate the effects of the vibro-pile installation on the deformation of deep excavation shoring walls at high ground water levels. Although commonly-used finite element simulations provide acceptable predictions of the
wall displacements caused by underwater excavations, anchor installation, or pit dewatering processes, they could not explain the unexpected large wall movements measured in different excavations during the vibro-pile installation stage. Previous dynamic finite element …
Bei Shapies handelt es sich um Ministatuen von sich selbst, anderen Menschen oder (Haus)Tieren aus einem 3D-Drucker, auf der Basis eines hochauflösenden Körperscans. Im Unterschied zum Selfie hat das Shapie noch keine massenmediale Verbreitung erfahren, sodass auch die (wissenschaftliche) Literatur zu diesem Phänomen sehr überschaubar ist. Wir möchten daher mit unserem Aufsatz einen ersten Vorschlag zur Interpretation der Shapies leisten. Geleitet von dem Statement eines Shapie-Käufers: ‚Das eigene Ich in den Händen zu halten als naturgetreues Miniaturmodell – ist faszinierend‘, werden drei darin zum Ausdruck kommende Perspektiven fokussiert: (1) Shapies als naturgetreue Miniaturmodelle des eigenen Ichs; (2) Das eigene Ich in Händen halten und (3) das Shapie als Faszinosum.
Identität, Vulnerabilität und Selbstsorge – ein eudaimogenetischer Bezugsrahmen Sozialer Arbeit
(2019)
Der Beitrag von Juliane Noack Napoles formuliert einen anthropologisch-identitätstheoretisch motivierten Bezugsrahmen Sozialer Arbeit, der ausgehend von der Bestimmung des Menschen als verletzlichem und verletzungsmächtigem Wesen im gelingenden Leben als Fluchtpunkt mündet. In diesem Sinne wird zunächst ein Rahmen vorgestellt, der es ermöglicht, menschliche Vulnerabilitäten zu systematisieren, sodann dargelegt, was unter Vulnerabilität verstanden wird und in einem dritten Schritt versucht, Soziale Arbeit als Ermöglichung von Selbstsorge und gelingendem Leben – also eudaimogenetisch – zu denken.
Gravity wave emission from jet systems in the differentially heated rotating annulus experiment
(2019)
We carry out a theoretical study of vibration-induced saturation of the Rayleigh-Taylor instability for an isolated liquid drop on the surface of a less dense finite-thickness carrier film. Without vibration, a heavy drop falls through the carrier film by forming a stretching liquid column until the bottom tip of the column reaches the solid substrate and the carrier film ruptures. We show that an externally applied vertical vibration prevents the rupture of the film and enables stable flotation of the drop. A hydrodynamic model is used to study the effect of inertia on the long-time dynamics of the drop. It is shown that rupture can only be prevented when the Reynolds number is nonzero.
Ergebnisse einer qualitativen Studie an der BTU Cottbus Senftenberg im Fachbereich Sozialer Arbeit über Social Entrepreneure in strukturarmen Regionen. Die Selbstständigen berichten über ihrer Gründungsmotivationen, ihre Erfahrungen und über ihre Probleme sowie Erfolge. Der tägliche Kampf im Sozialbereich mit seinen Herausforderungen und die Einstellungen und Haltungen der Social Entrepreneure zeigen unerwartete Ergebnisse auf.
The current economic and cultural domain and the society in general are subject to major changes that create an extremely competitive environment. All members of any organization are obliged to adapt to these changes in order to achieve competitive advantage for their organization. Experts give organizational culture great importance as
they believe that it is essential to achieve the organization's
success. This research examines the importance of a strong
organizational culture as a tool for managing, improving and enhancing the performance of the employees and the role of the HR in developing a positive organizational culture by using Nestlé Company in Egypt as a case study.
Food and beverages industry is facing major challenges in the years to come, as the world population is expected to grow, accompanied by a growing need for energy, feed and fuel. Much of the processing in the food industry is performed in small-scale decentralized plants, with relatively few possibilities of energy recovery. Innovation in areas such as process and product modeling, process intensification and process control enable the development of new manufacturing pathways, more efficient, versatile, selective and sustainable. Furthermore, the addition of Internet of Things elements and the way they connect to the physical process will ensure continuous communication between the various actors of the food value chain. This will enable the design of new compact, scalable, flexible, modular, and automated production equipment that will offer food manufacturers the ability to respond rapidly, economically, accurately and flexibly to the consumer demands.
Optimisation-based models are often employed for the design and operation of distributed energy systems (DES). A two-stage approach often involves the optimisation of the design of a distributed energy system for a specified location or scale, and the subsequent optimisation of the operational model based on the structure recommended by the design model. The structure includes what types of generation and storage technologies should be used in the operation, related capacities and sizes, and potential locations. Often, both design and operational models are deterministic in nature, as either past or fictitious data is fed into the models to minimise an objective function such as the total cost or environmental impact due to carbon emissions. Consequently, the operational models encounter challenges when real-time data is fed, as time-variant input variables such as electricity demand, heating demand and solar insolation can be deemed uncertain. These variables could have unexpected and significant impacts on the total costs involved with the operation of distributed energy systems, leading to sub-optimality or even infeasibilities. Identifying these input variables, quantifying their uncertainties (which are then described in the models), and evaluating the influence of these variables on the outputs can lead to the design of more robust models. Such models can then be used to design and operate optimal distributed energy systems.
This paper presents a novel methodology for using global sensitivity analysis (GSA) on an operational optimisation-based model of a distributed energy system. The operational model also utilises Model Predictive Control (MPC) rolling horizon concepts (as done by [1]) to determine hourly total operational costs. The paper also addresses how some challenges and limitations encountered in the operational model can be attributed to the deterministic design model on which the structure of the operational model has been based. Furthermore, the research explores how the design can be improved to support more robust operation. Another novel aspect of this paper highlights the use of the optimisation tool GAMS alongside SobolGSA, a global sensitivity analysis software [2]. This software uses the variance-based Sobol method to generate N samples and perform global sensitivity analysis, allowing users to understand how variations in the inputs can influence the outputs, whilst accounting for the different combinations of the uncertain parameters without varying one uncertain parameter at a time.
One of the main issues that many industrial sectors such as oil refineries have been facing nowadays is their sole dependency on fossil fuel. Not only have price fluctuations affected the products, but their environmental impact is an ever present problem that should be addressed. This has led to the search for alternatives such as biomass based processes in order to reduce the dependency on fossil fuel.
Bio-refinery processes, fed by biomass, produce high value chemicals and materials with the advantage of reduced environmental drawbacks, such as CO2 emissions, when compared to the conventional refinery. For the benefit of both systems, an integration approach has been considered connecting bio-refining and conventional refining processes together.
In this work we focus on the production of long chain hydrocarbons while maintaining production of chemicals that already originate from biomass such as Acetone, Butanol and Ethanol (ABE). The ABE used for this process is obtained as a product of sugar fermentation using the bacteria genus Clostridium. Through the upgrading and conversion of ABE, the products obtained will then be incorporated in the proposed integration system, connecting the conventional oil refinery to this process. A reaction involving a complex reaction network towards upgrading ABE with the aim of producing valuable products using economically viable catalysts has been carried out. The vast majority of research in this area either involves the separation of ABE after fermentation to be used in the chemical/or transportation industry that incurs large costs, or noble metal catalysts are used to upgrade this feed, which would also not be economically viable. However, our research has surpassed the necessity of noble metals, leading to a significant cost decrease that also produces outstanding results. The catalysts required for this process were synthesised successfully through the wetness incipient method and characterised by XRD, Raman, BET, TPR and N2 Isotherm. The reaction consists of the self-condensation and cross condensation of the alcohols and acetone, respectively, using a variety of active metals on basic supports as catalysts, at high temperatures and pressure in a batch reactor.
The results have shown exceptional performance for the catalysts in terms of conversion and selectivity, having conversions as high as 90%. The catalysts have proven to yield a range of C3-C15 hydrocarbons identified to be of need in the chemical industry. In conclusion, our route has produced valuable chemicals proven to have a considerably higher market value than the simple alcohol reactants, useful for both the petrochemical and the transportation industries, through the use of novel and economically favourable catalysts.
A Novel Circulating Fluidised Bed Solar Receiver Design for Thermal Energy Conversion and Storage
(2019)
he middle east and northern Africa (MENA) regions rely heavily on fossil fuels as an energy source. The region consumes high amounts of energy for their air cooling and water desalination needs. For the GCC region this amounts to 60-70% of their energy consumption and has one of the highest carbon dioxide emissions per capita in the world.
The GCC countries are in an area of high direct normal irradiance from the sun and thus, investigating the use of solar power as an alternative energy source is valid. Concentrated Solar Power (CSP) technology is a promising energy capture technology that uses optical devices to concentrate the power of the sun on to a surface and in turn generates power by means of a thermal-to-electric conversion. CSP technology integrates Thermal Energy Storage (TES) materials to store heat and thus enable power production in the absence of sunlight, at night or in poor weather conditions. While CSP technology is a promising alternative energy source its high levelized cost of energy (LCOE) is a drawback to its widespread implementation. A major factor to the high LCOE is the use of molten salts as the TES material carrying with it, high capital costs and high operating and maintenance cost. This is due to molten salts being corrosive and having a low working temperature limiting its thermal-to-electric efficiency.
This contribution introduces a novel conceptual design of a circulating fluidised bed as the solar receiver for a CSP plant. The use of raw desert sand as an alternative TES material was investigated. An optimum heat transfer fluid (HTF) was selected from Carbon dioxide, Nitrogen, Argon and Air.
This work will also argue that these changes to current CSP plants will significantly reduce the LCOE. The results of this study show that the proposed design can allow up to six times higher mass flowrates of the heat transfer fluid to circulate the sand than current designs. Moreover, 1000 oC uniform outlet temperature was also achieved.
For this purpose, Carbon dioxide was found to be the optimum HTF, achieving the highest heat transfer rates. Thus, the new configuration of a fluidised bed receiver proves desert sand to be an effective alternative TES material leading to high thermal energy outputs per m2 and a substantial reduction in the LCOE for CSP technology.
Towards Sustainable Industries: Industrial Symbiosis of an Oil Refinery and a Petrochemical Plant
(2019)
A common factor that can be seen in the history of all manufacturing and production sectors is that they all go through significant changes to keep them operating efficiently, thus a constant cycle of system development, obsolescence and advancement is formed. These sectors must be able to maintain the balance between the energy consumption and efficiency to keep the system optimised and preserve the opportunity to create value. Oil refineries are a prime example of one of these sectors that play an important role in our day-to-day lives. Due to an oil refineries’ major dependency on crude oil, the price fluctuation of which, has a profound impact on this industry. Thusly, this drives up prices and forcing a rise in the search for alternative solutions to tackle these efficacy and economic problems. Therefore, in this work, an integration approach has been considered based on the Industrial Symbiosis concept to connect an oil refinery with a petrochemical plant.
One main feature of the larger chemical industry that should be considered, is that they require careful management of material and energy to obtain valuable products. Of course, the processes key to the generation of the valuable products also produce fewer desirable chemicals, which have no value as waste products. Some of these waste materials can be used as feed-stock for other processes; turning probable costly chemical disposal into an economic boon. This “greener†approach opens avenues of improvement compatible with the idea of industrial symbiosis; where the waste from one process can be a feed-stock, useful for another. Taking this into account, a case study is presented involving the connection of an oil refinery with an ethylene production plant through material exchange and stream combination to benefit both plants.
As a result, we were able to improve not only product quality but the overall profit of both plants by a significant margin, while also decreasing dependency on outside sources for material supply.
In the context of Industry 4.0, engineering systems and manufacturing processes are becoming increasingly complex, combining the physical world of the processing units with the cyber world of the wireless sensing and communication networks, big data analytics, ubiquitous computing and other elements that the Industrial Internet of Things technologies. The fields of ontology, knowledge management and decision-making systems have matured significantly in the recent years and their integration with the cyber-physical system (CPS) facilitates and improves the effectiveness of decision-support systems (DSS) [1]. Yet, this comes with an increase in the system’s complexity and a need for deployment of intelligent systems for process systems engineering (PSE) applications, that should adapt to the continuously new requirements of Industry 4.0. Considering the large number of devices existent in a CPS, distributed methods are required to transfer the computational load from centralised to local (decentralised) controllers.
This has led to the motivation of applying multi-agent systems (MASs) methodologies as a solution to distributed control as a computational paradigm [2]. An agent can be defined as an entity placed in an environment that can sense different parameters used to make a decision based on the goals of the entity. A MAS is a computerised system composed of multiple interacting agents exploited to solve a problem. Their salient features, which include efficiency, low cost, flexibility, and reliability, make it an effective solution for solving tasks [3]. Usually, DSS adopt a rule-based or logic-based representation scheme [4].
For this reason, ontologies have attracted the attention of the PSE community as a convenient means for knowledge representation [1, 5]. An ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts, and it serves as a library of knowledge to efficiently build intelligent systems and as a shared vocabulary for communication between interacting human and/or software agents [6].
In this paper, a multi-agent cooperative-based model predictive control (MPC) system for monitoring and control of a chemical process is proposed. The system uses ontology to formally represent the system knowledge at process, communication and decision-making level. The application of the proposed framework is discussed for a chemical process that produces iso-octane. A cooperative MPC is implemented to achieve the control of the plant. This protocol is defined using a simple algorithm to reach an agreement regarding the state of a number of N agents [7]. The monitoring feature is defined by means of a MAS, consisting of follower agents (FAs), a coordinator agent (CA) and a monitor agent (MoA), that is integrated with the MPC. The MAS has two main tasks: a) decide optimal connectivity between the distributed MPCs for safer and better operation; and b) monitor the system and detect any deviation in the behaviour.
The addition of the MAS makes the cooperative MPC controller more efficient by taking advantage of the communication between the various elements of the CPS. Using the knowledge form the ontology and the agents’ sharing capabilities, the system can detect faster any deviation compared to standard operation. The framework can easily be adapted for other control approaches by very simple modifications in the structure and objectives. A practical demonstration in a pilot plant environment is envisaged for the future.