Ageneric predictive information system for resource planning and optimisation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe purpose of this research work is to demonstrate the feasibility of creating a quick response decision platform for middle management in industry. It utilises the strengths of current, but more importantly creates a leap forward in the theory and practice of Supervisory and Data Acquisition (SCADA) systems and Discrete Event Simulation and Modelling (DESM). The proposed research platform uses real-time data and creates an automatic platform for real-time and predictive system analysis, giving current and ahead of time information on the performance of the system in an efficient manner. Data acquisition as the backend connection of data integration system to the shop floor faces both hardware and software challenges for coping with large scale real-time data collection. Limited scope of SCADA systems does not make them suitable candidates for this. Cost effectiveness, complexity, and efficiency-orientation of proprietary solutions leave space for more challenge. A Flexible Data Input Layer Architecture (FDILA) is proposed to address generic data integration platform so a multitude of data sources can be connected to the data processing unit. The efficiency of the proposed integration architecture lies in decentralising and distributing services between different layers. A novel Sensitivity Analysis (SA) method called EvenTracker is proposed as an effective tool to measure the importance and priority of inputs to the system. The EvenTracker method is introduced to deal with the complexity systems in real-time. The approach takes advantage of event-based definition of data involved in process flow. The underpinning logic behind EvenTracker SA method is capturing the cause-effect relationships between triggers (input variables) and events (output variables) at a specified period of time determined by an expert. The approach does not require estimating data distribution of any kind. Neither the performance model requires execution beyond the real-time. The proposed EvenTracker sensitivity analysis method has the lowest computational complexity compared with other popular sensitivity analysis methods. For proof of concept, a three tier data integration system was designed and developed by using National Instruments’ LabVIEW programming language, Rockwell Automation’s Arena simulation and modelling software, and OPC data communication software. A laboratory-based conveyor system with 29 sensors was installed to simulate a typical shop floor production line. In addition, EvenTracker SA method has been implemented on the data extracted from 28 sensors of one manufacturing line in a real factory. The experiment has resulted 14% of the input variables to be unimportant for evaluation of model outputs. The method proved a time efficiency gain of 52% on the analysis of filtered system when unimportant input variables were not sampled anymore. The EvenTracker SA method compared to Entropy-based SA technique, as the only other method that can be used for real-time purposes, is quicker, more accurate and less computationally burdensome. Additionally, theoretic estimation of computational complexity of SA methods based on both structural complexity and energy-time analysis resulted in favour of the efficiency of the proposed EvenTracker SA method. Both laboratory and factory-based experiments demonstrated flexibility and efficiency of the proposed solution.The Engineering and Physical Sciences Research Council

Combination of WENO and Explicit Runge–Kutta Methods for Wind Transport in the Meso-NH Model

This paper investigates the use of the weighted essentially nonoscillatory (WENO) space discretization methods of third and fifth order for momentum transport in the Meso-NH meteorological model, and their association with explicit Runge–Kutta (ERK) methods, with the specific purpose of finding an optimal combination in terms of wall-clock time to solution. A linear stability analysis using von Neumann theory is first conducted that considers six different ERK time integration methods. A new graphical representation of linear stability is proposed, which allows a first discrimination between the ERK methods. The theoretical analysis is then completed by tests on numerical problems of increasing complexity (linear advection of high wind gradient, orographic waves, density current, large eddy simulation of fog, and windstorm simulation), using a fourth-order-centered scheme as a reference basis. The five-stage third-order and fourth-order ERK combinations appear as the time integration methods of choice for coupling with WENO schemes in terms of stability. An explicit time-splitting method added to the ERK temporal scheme for WENO improves the stability properties slightly more. When the spatial discretizations are compared, WENO schemes present the main advantage of maintaining stable, nonoscillatory transitions with sharp discontinuities, but WENO third order is excessively damping, while WENO fifth order provides better accuracy. Finally, WENO fifth order combined with the ERK method makes the whole physics of the model 3 times faster compared to the classical fourth-order centered scheme associated with the leapfrog temporal scheme

EXPERIENCES AND TENDENCIES TO DECENTRALIZE THE CAPABILITIES OF THE ECONOMIC POLICY AT THE EUROPEAN UNION LEVEL

Romania's integration in the European Union implies, apart the complex process of policy transfer, the learning of new modes to make policies characteristic to a multi-level governance and partnership culture. Of the different levels of governance of the European model, the regional level ("regional governance") most faithfully reflects, in our opinion, the complexity of reconfiguring the role of state in economy, at the beginning of this new millennium, in the European Union space and presents the highest practical importance for Romania, as a new Member State of the European Union, for, at the regional level, the structures are more flexible and the good practices are more rapidly assimilable. The selection of the best regional growth and development economic policies, the choosing of the objectives out of a series of competing options, the calibration in time and space of powers, roles, capabilities, and responsibilities and the encouragement of the win-win solutions call upon the choice and combination of some appropriate and efficient instruments. Representative for the new context, the regional growth and development policy must integrate, in Romania too, more knowledge, more creativity, new combinations of capabilities and new fields of expertise. This paper presents preliminary research results afferent to the post-doctoral research project: "Growth and regional development economic policies. Challenges for Romania in the context of economic-financial crisis and European model integration", carried out in the project "Economic scientific research, reliance of human welfare and development in European context", the Romanian Academy, "Costin C. Kiriţescu" National Institute for Economic Research, project financed for the 2010-2013 period from the European Social Fund (EFS) and implemented by the Romanian Academy, "Costin C. Kiriţescu" National Institute for Economic Research, in the period of time 1 December 2010 - 30 November 2012, coordinator: Professor Dr. Valeriu Ioan Franc. The question we intend to answer, in the present phase of our research, based on the comparative analysis of the decentralisation systems of several Member States of European Union, respectively on the analysis of the regional disparities existing at the European Union level and of the effects of the economic integration, is - to what extent the capabilities of the regional policy should rather be concentrated in the hands of regional authorities or of the European Union than to be left individually to the Member States which should conceive their own regional policy? What we intend in this paper, based on the analysis of some experiences to decentralize the capabilities of economic policy at the European Union level, is to identify the regional implications of the interconnection of decentralization, centralization, respectively supra-nationalization tendencies and, implicitly, the analysis of the way to reconfigure the role of state in economy at the regional level, in the context of integration in the European model. The examination of the way to reconfigure the role of state in economy at regional level requires the review of the allocative, distributive, and regulating roles of the state from a regional perspective, the analysis, on one side, of the decentralization of economic policy capabilities from the national level to the regional level (for example, national level: pure public goods supply, for instance, national defence and the centralization of fiscal policy capabilities in order to achieve macroeconomic stability and revenue redistribution; regional level: mixed public goods supply, for instance, waste collection and community policy), on the other hand, the centralization/decentralization of regional capabilities at the European Union level.European integration, role of state in economy, decentralization, regional governance, regional growth and development policy

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1

Interpolatory tensorial reduced order models for parametric dynamical systems

The paper introduces a reduced order model (ROM) for numerical integration of a dynamical system which depends on multiple parameters. The ROM is a projection of the dynamical system on a low dimensional space that is both problem-dependent and parameter-specific. The ROM exploits compressed tensor formats to find a low rank representation for a sample of high-fidelity snapshots of the system state. This tensorial representation provides ROM with an orthogonal basis in a universal space of all snapshots and encodes information about the state variation in parameter domain. During the online phase and for any incoming parameter, this information is used to find a reduced basis that spans a parameter-specific subspace in the universal space. The computational cost of the online phase then depends only on tensor compression ranks, but not on space or time resolution of high-fidelity computations. Moreover, certain compressed tensor formats enable to avoid the adverse effect of parameter space dimension on the online costs (known as the curse of dimension). The analysis of the approach includes an estimate for the representation power of the acquired ROM basis. We illustrate the performance and prediction properties of the ROM with several numerical experiments, where tensorial ROM's complexity and accuracy is compared to those of conventional POD-ROM

Ensemble transform Kalman-Bucy filters

Two recent works have adapted the Kalman-Bucy filter into an ensemble setting. In the first formulation, BR10, the full ensemble is updated in the analysis step as the solution of single set of ODEs in pseudo-BGR09, the ensemble of perturbations is updated by the solution of an ordinary differential equation (ODE) in pseudo-time, while the mean is updated as in the standard KF. In the second formulation, BR10, the full ensemble is updated in the analysis step as the solution of single set of ODEs in pseudo-time. Neither requires matrix inversions except for the frequently diagonal observation error covariance. We analyze the behavior of the ODEs involved in these formulations. We demonstrate that they stiffen for large magnitudes of the ratio of background to observational error covariance, and that using the integration scheme proposed in both BGR09 and BR10 can lead to failure. An integration scheme that is both stable and is not computationally expensive is proposed. We develop transform-based alternatives for these Bucy-type approaches so that the integrations are computed in ensemble space where the variables are weights (of dimension equal to the ensemble size) rather than model variables. Finally, the performance of our ensemble transform Kalman-Bucy implementations is evaluated using three models: the 3-variable Lorenz 1963 model, the 40-variable Lorenz 1996 model, and a medium complexity atmospheric general circulation model (AGCM) known as SPEEDY. The results from all three models are encouraging and warrant further exploration of these assimilation techniques

Space Network Devices Developed

The NASA Glenn Research Center through a contract with Spectrum Astro, Inc., has been developing space network hardware as an enabling technology using open systems interconnect (OSI) standards for space-based communications applications. The OSI standard is a well-recognized layered reference model that specifies how data should be sent node to node in a communications network. Because of this research and technology development, a space-qualifiable Ethernet-based network interface card (similar to the type found in a networked personal computer) and the associated four-port hub were designed and developed to flight specifications. During this research and development, there also have been many lessons learned for determining approaches for migrating existing spacecraft architectures to an OSI-network-based platform. Industry has recognized the benefits of targeting hardware developed around OSI standards such as Transmission Control Protocol/Internet Protocol (TCP/IP) or similar protocols for use in future generations of space communication systems. Some of these tangible benefits include overall reductions in mission schedule and cost and in system complexity. This development also brings us a step closer to the realization of a principal investigator on a terrestrial Internet site being able to interact with space platform assets in near real time. To develop this hardware, Spectrum Astro first conducted a technology analysis of alternatives study. For this analysis, they looked at the features of three protocol specifications: Ethernet (IEEE 802.3), Firewire (IEEE 1394), and Spacewire (IEEE 1355). A thorough analysis was performed on the basis of criteria such as current protocol performance and suitability for future space applications. Spectrum Astro also projected future influences such as cost, hardware and software availability, throughput performance, and integration procedures for current and transitive space architectures. After a thorough analysis, Ethernet was chosen because it was seen as the best longer term fit because of the prevalent commercial market; the current and projected availability of hardware, software, and development tools; and the ease of architecture integration

Model-Based Engineering for the support of Models of Computation: The Cometa Approach

The development of Real-Time Embedded Systems (RTES) increasingly requires the integration of several parts with different purposes. Consequently, the heterogeneous appearance of such systems creates a need to manage their growing complexity mainly due to the difficulty to interconnect the different parts composing them. Model-Based Engineering (MBE) has significantly participated in recent decades to find solutions in terms of methodologies and technical support tailored to the design of RTES. Indeed, several models are used to represent different aspects of the system. However, the interconnection of different modeling paradigms is still a difficult challenge. The handling of such problems requires a clear definition of the execution and interconnection semantics of the different models composing the system. Indeed, the abstraction of the execution semantics of machines or Models of Computation (MoC) can highlight properties for the whole system’s execution. In this paper, we propose an approach that captures these semantics at the earliest modeling phases with the aim of exhibiting properties that ease the design space exploration and performance analysis of systems. Our approach extends the Modeling and Analysis of Real-Time Embedded Systems profile (MARTE) by providing means to express communication semantics of models. We also review existing approaches for defining such execution semantics