Modeling of the radiation transfer under partial frequency redistribution

A model is developed of the resonance radiation transfer under partial redistribution over frequencies. The media’s condition is described via the rate population balance equations for the two-level atom. The spectral intensity of the scattered radiation is calculated according to the stationary transfer equation. The light scattering by the atoms is modeled by a linear combination of the angle-averaged redistribution functions, R _II and R _III. The obtained integro-differential equation system is solved numerically taking into account the radiation transfer in a cylindrical gas containing volume. The influence is investigated of the partial frequency redistribution on the sodium atom resonance line (λ = 589 nm) profile as well as on the efficient vapor afterglow duration depending on its optical thickness.     

Nonlinear glucose–insulin control considering delays—Part II: Control algorithm

The closed loop control of blood glucose levels in a nonlinear glucose–insulin regulatory system is considered in this paper. Based on the subcutaneous glucose sensor readings, a control algorithm is designed and implemented. A mathematical model characterizing the ultradian oscillatory nature of the glucose–insulin regulatory system of diabetic patients is considered and an estimation based model predictive control scheme with physiological and actuator constraints is implemented. An in silico preclinical testing is done to corroborate the control algorithm using the UVa/Padova virtual patient software.     

PID controller design of TITO system based on ideal decoupler

The proposed method for designing multivariable controller is based on ideal decoupler D(s) and PID controller optimization under constraints on the robustness and sensitivity to measurement noise. The high closed-loop system performance and robustness are obtained using the same controller in all loops. The method is effective despite the values and positions of the right half plane zeros and dead-times in the process transfer function matrix G_p(s). The validity of the proposed multivariable control system design and tuning method is confirmed using a test batch consisting of Two-Input Two-Output (TITO) stable, integrating and unstable processes, and one Three-Input Three-Output (TITO) stable process.     

On Generalized Reduced Gradient method with multi-start and self-optimizing control structure for gas lift allocation optimization

In most of the gas lifted oil fields, multiple oil wells share lift gas from a common gas distribution source. The lift gas should be distributed optimally among the wells to maximize total oil production. In this paper, a nonlinear dynamic model of the oil field is developed from first principles modeling. One of the objectives of this paper is to solve the optimal lift gas distribution problem using the Generalized Reduced Gradient (GRG) method. In addition, multi-start search routine is developed to ensure that the local optimal solution is closer to the global solution. Sensitivity of the optimal solution to changes in oil field parameters like reservoir pressure, Productivity Indices (PI), total lift gas supply (input disturbance) and separator pressure is studied. It is shown that the available lift gas is distributed among the wells according to the PI values of the wells and the optimal values are highly sensitive to the changes in PI values. A self-optimizing control structure using simple controllers is designed which is capable of keeping the oil field in optimal operating conditions without having to re-optimize the whole process when the input disturbance occur in the system. The simulation results show that the outcome of optimization is increased total oil production which leads to increased profit.     

A comparison of receiver-initiated and sender-initiated adaptive load sharing

Load sharing in a locally distributed system is the process of transparently distributing work submitted to the system by its users. By directing work away from nodes that are heavily loaded to nodes that are lightly loaded, system performance can be improved substantially.Adaptive load sharing policies make transfer decisions using information about the current system state. Control over the maintenance of this information and the initiation of load sharing actions may be centralized in a ‘server’ node or distributed among the system nodes participating in load sharing.The goal of this paper is to compare two strategies for adaptive load sharing with distributed control. In sender-initiated strategies, congested nodes search for lightly loaded nodes to which work may be transferred. In receiver-initiated strategies, the situation is reversed: lightly loaded nodes search for congested nodes from which work may be transferred. We show that sender-initiated strategies outperform receiver-initiated strategies at light to moderate system loads, and that receiver-initiated strategies are preferable at high system loads only if the costs of task transfer under the two strategies are comparable. (There are reasons to believe that the costs will be greater under receiver-initiated strategies, making sender-initiated strategies uniformly preferable.)     

H∞-Control of a continuous crystallizer

Robustly stabilizing control of an open loop oscillatory crystallization process is considered. The crystallizer is described by a population balance model. From this distributed parameter model an irrational transfer function is obtained which has infinitely many poles and thus represents the infinite-dimensional nature of the system. An infinite-dimensional H_∞ controller synthesis method is applied to solve the weighted mixed sensitivity problem for this transfer function. This procedure results in an irrational controller. For practical implementation, the controller needs to be approximated by a rational transfer function. The effectiveness of the controller is demonstrated in simulations.     

Building a Knowledge Brokering System using social network analysis: A case study of the Korean financial industry

The importance of knowledge is increasing in our global and knowledge-based society. As a part of knowledge management, successful knowledge transfer can improve an organization’s competitive advantages and increase an organization’s valuable knowledge assets. However, knowledge transfer is complex and a lot of factors exist that affect successful knowledge transfer such as context, social networks, and IT/IS. This paper aims at the role of the knowledge broker which is to be a link between knowledge seekers and knowledge experts. In this context, this research implemented a Knowledge Brokering System – called K-broker system – as a prototype system to improve knowledge transfer in an organization based on an analysis of users’ social network. The K-broker system can provide a ‘single view’ screen for identifying knowledge experts and has no bottlenecks in contrast with a human knowledge broker and can provide a permanent communication channel between knowledge seekers and knowledge experts.     

Fault detection using interval LPV models in an open-flow canal

This paper proposes a new method of fault detection using Linear Parameter Varying (LPV) interval models and its application to an open-flow canal. The use of such models is motivated because the parameters and transport delay in the canal transfer function model vary with the operating point. LPV models allow to consider these variations by characterizing the parameters/delay variation law with the operating point while intervals are used to bound the parameter/delay uncertainty. Additionally, a LPV parameter estimation algorithm that allows to estimate parameter/delay uncertainty intervals is also proposed. As an application case study, an open-flow canal system based on the Lunax dam-gallery system located in France is used to show the effectiveness of the proposed method to detect faults. The satisfactory results obtained allow to assess the effectiveness of the proposed approach.     

Design and experimental validation of an extended Kalman filter-based NOx concentration estimator in selective catalytic reduction system applications

This paper presents an extended Kalman filter (EKF) based approach of integrating NO_x and NH₃ sensors to estimate the NO_x concentrations in Diesel engine selective catalytic reduction (SCR) aftertreatment systems. NO_x sensors have been commonly used by vehicles for aftertreatment system control and onboard diagnostics (OBD) purposes. However, most currently available NO_x sensors are cross-sensitive to ammonia. Based on the experimental observations and physical inferences, the cross-sensitivity characteristics may change with temperature and is hard to be predicted by a model. This feature limits the applications of NO_x sensors on urea-SCR systems where ammonia is the reductant for NO_x conversions. Grounded in the insight into SCR dynamics and NO_x sensor properties, a novel approach of using an extended Kalman filter to estimate the actual exhaust gas NO_x concentration was proposed. The estimator was examined by NO_x measurements from a Horiba gas analyzer under different engine operating conditions. The experimental results show that the EKF-based approach can significantly improve the accuracy of NO_x concentration measurements from the original NO_x sensor readings.     

Semi-physical mean-value NOx model for diesel engine control

A semi-physical model has been developed to predict nitrogen oxide (NO_x) emissions produced by diesel engines. This model is suitable for online NO_x estimation and for model-based engine control. It is derived from a zero-dimensional thermodynamic model which was simplified by only retaining main phenomena contributing to NO_x formation. The crank angle evolution of the burned gas temperature, which has a strong impact on NO_x formation rate, is described by a semi-empirical model whose key variable is the maximum burned gas temperature. This variable presents a good correlation with the molar fraction of NO_x at the end of combustion and can be expressed as a function of the intake burned gas ratio and the start of combustion. The maximum burned gas temperature sub-model is then coupled to an averaged NO_x formation kinetic model (based on the Zeldovich mechanism) to form a mean-value model for NO_x computation. This latter model was validated using data sets recorded in two diesel engines for steady-state operating conditions as well as for several driving cycles including parametric variations of the engine calibration.     

Structural synthesis of multivariable controllers

In this paper the problem of achieving a desired transfer function matrix H_d(s) between external inputs and controlled outputs in a linear multivariable system by connecting proper, stabilizing controllers between measured outputs and control inputs is solved in both transfer function and state space settings. The class H_d of achievable transfer functions is directly and constructively characterized via the theory of transfer function valuations. For each H_d(s)ϵH_d, the class of synthesizing controllers is determined. Similar valuation conditions are given for the asymptotic tracking and disturbance rejection problem in which H_d(s) is only partially specified. These results extend and complement earlier results. The state space geometric solution of the problem of achieving a desired H_d(s) is obtained by formulating it as an equivalent output feedback disturbance rejection problem. A constructive solvability condition in terms of a pair of measurement and control invariant subspaces is given. This requires a nontrivial generalization of the notion of (C, A, B) pairs. An H_d(s) is shown to be admissible if and only if it induces an appropriate pair of invariant subspaces. The signal flow structure and certain factorizability conditions for a robust synthesis of the output feedback disturbance rejection problem are also given which extend earlier results on robust state feedback disturbance rejection. It is shown that every compensator corresponds to a state feedback control law implemented by an unknown input observer. The results of this paper are expected to be useful in the development of parameter optimization or other computer aided design algorithms where response specifications are to be traded against other design criteria such as sensitivity or stability margins since they explicitly characterize the algebraic variety H_d in which the response transfer function may lie.     

A hierarchical adaptive distributed algorithm for load balancing

Load balancing/sharing exploits the communication facility between the servers of a distributed system, by using the exchanging of status information and jobs between any two servers of the system in order to improve the overall performance.We propose an adaptive distributed hierarchical scheme, the Virtual Tree Algorithm (VTA), which creates a virtual binary tree structure over the actual network topology. It uses the difference-initiated (DI) technique for load balancing, which needs remote information for the transfer policy and no additional information for the location policy. We demonstrate that the introduced virtual construction keeps the exchanged messages to relatively low levels. To evaluate the performance of our policy, we present both theoretical and simulation results. By using simulation, we compare our results with one of the most representative, adaptive, symmetrical and efficient algorithms, the Variable Threshold (V_THR) algorithm.     

Verification of a multidestination selective repeat procedure

A multidestination protocol is a data transfer procedure from one transmitter to many rceivers. We specify and verify such a protocol, the Selective Repeat procedure. The communication medium assumed is a satellite broadcast channel shared by using a time division multiplexed technique.The Selective Repeat procedure is modeled as a parallel program in a Pascal-like language. Then, we show the correctness of the parallel program model using temporal logic. The correctness requires that the program model have two system properties: the safety and liveness properties. The safety property ensures that each receiver delivers the packets to the user in the same sequence as originally delivered to the transmitter. The liveness property ensures that each receiver delivers an infinite number of packets to the user if an infinite number of packets are waiting to be transmitted at the transmitter.     

RBF neural network inferential sensor for process emission monitoring

Inferential sensing, or soft sensing, gained popularity in recent years as an alternative to continuous emission monitoring systems because of its simplicity, reliability, and cost effectiveness as compared to analogous hardware sensors. In this paper we address the problem of NO_x emission using a model of furnace of an industrial boiler, and propose a neural network structure for high performance prediction of NO_x as well as O₂. The studied boiler is 160 MW, gas fired with natural gas, water-tube boiler, having two vertically aligned burners. The boiler model is a 3D problem that involves turbulence, combustion, radiation in addition to NO_x modeling. The 3D computational fluid dynamic model is developed using Fluent simulation package. The model provides calculations of the 3D temperature distribution as well as the rate of formation of the NO_x pollutant, enabling a better understanding on how and where NO_x are produced. The boiler was simulated under various operating conditions. The generated data is then used for initial development and assessment of neural network soft sensors for emission prediction based on the conventional process variable measurements. The performance of the proposed soft sensor is then evaluated using actual data from an industrial boiler. The developed soft sensor achieves comparable accuracy to the continuous emission monitor analyzer, however, with substantial reduction in the cost of equipment and maintenance.     

Formation of high-purity organic thin films by gas flow deposition and the effect of impurities on device characteristics

A gas flow deposition (GFD) system was developed to manufacture large-scale organic light-emitting diodes (OLEDs). A N,N′-di(1-naphthyl)-N,N′-diphenylbenzidine (α-NPD) thin film with a high purity of 99.97% was obtained using the GFD system. The film properties such as morphology, and electrical and optical characteristics were almost the same as those of films made by conventional vacuum thermal evaporation.     

Thermodynamics and kinetics of solution nitriding

In order to clarify the thermodynamics and kinetics of solution nitriding, the non-uniform nitrogen distribution formed by solution nitriding was investigated in austenitic (18Cr–10Ni) and ferritic (25Cr) stainless steels, and then it was simulated with DICTRA. The main issue for austenitic stainless steel is the surface reaction determined by the mass transfer from gas to solid, while that for ferritic stainless steel is the ferrite to austenite transformation and the austenite growth kinetics induced by nitrogen absorption. DICTRA simulations gave close agreement with the experimental results and demonstrated that solution nitriding is obviously controlled by mass transfer of nitrogen from gas to solid as well as diffusion in the solid, and austenite growth is controlled by nitrogen diffusion in austenite. In addition, the analysis suggests that nitrogen should have a stronger interaction with chromium than that treated in the thermodynamic database and austenite nucleation induced by nitrogen absorption takes place without any change in Cr composition.     

Bond graph based control and substructuring

A bond graph framework giving a unified treatment of both physical-model based control and hybrid experimental–numerical simulation (also known as real-time dynamic substructuring) is presented. The framework consists of two subsystems, one physical and one numerical, connected by a transfer system representing non-ideal actuators and sensors. Within this context, a two-stage design procedure is proposed: firstly, design and/or analysis of the numerical and physical subsystem interconnection as if the transfer system were not present; and secondly removal of as much as possible of the transfer system dynamics while having regard for the stability margins established in the first stage. The approach allows the use of engineering insight backed up by well-established control theory; a number of possibilities for each stage are given.The approach is illustrated using two laboratory systems: an experimental mass-spring-damper substructured system and swing up and hold control of an inverted pendulum. Experimental results are provided in the latter case.     

Level of interactivity and executive functions as predictors of learning in computer-based chemistry simulations

High school students’ learning outcomes was examined comparing exploratory vs. worked simulations. The effects of added icons and students’ executive functions were also examined. In Study 1, urban high school students (N = 84) were randomly assigned to one of four versions of a web-based simulation of kinetic molecular theory that varied in instructional format (exploratory vs. worked simulation) and representation (added icons vs. no added icons). Learning was assessed at two levels: comprehension and transfer. For transfer, a main effect was found for instructional format: the exploratory condition yielded greater levels of transfer than the worked simulation. Study 2 used the same conditions and a more complex simulation, the ideal gas law, with a similar sample of students (N = 67). For transfer, an interaction between instructional format and executive functions was found: Whereas students with higher levels of executive functions had better transfer with the exploratory condition, students with lower levels of executive functions had better transfer with the guided simulations. Results are discussed in relation to current theories of instructional design and learning.