Petri‐net based integer programs for synthesizing optimal material‐transfer procedures in pipeline networks

Abstract

Transferring materials through the pipeline network is a basic operation in almost every batch chemical plant. Traditionally, the tasks for conjecturing the needed operation steps are carried out manually on an ad hoc basis. This approach is often time‐consuming for industrial processes and, furthermore, the resulting recipe may be error‐prone. The aim of this paper is thus to develop a systematic strategy to generate the optimal operating procedures with Petri‐net based integer programs. Specifically, the shortest material‐transfer routes are selected on the basis of Petri‐net representation of the path structure in pipeline network. The equipment models are then incorporated into this path model to create a complete system model. An integer program can therefore be constructed accordingly to identify the detailed operation steps. Finally, a realistic example is presented at the end of this paper to demonstrate the effectiveness and correctness of the proposed approach.     

A grey‐based approach for distribution network reconfiguration

Abstract

This work presents a new concept for selecting restoration plans in power distribution systems using the Grey Relational Analysis (GRA) and the Analytical Hierarchy Process (AHP) approach. The GRA is used to analyze the preference ranking of each restoration plan, and the AHP is adopted to deal with assessing the weighting values of each objective function in a rational way. The proposed decision analysis framework can be applied to assist distribution system operators to make right decisions during a power system restoration process. The effectiveness of the proposed method is demonstrated through a numerical example. The test results show that the proposed method can rank each restoration plan in a quantitative way and obtain a preferable restoration plan correctly.     

A label‐based information flow control model for object‐oriented systems

Abstract

This paper proposes a label‐based information flow control model to prevent information leakage within object‐oriented systems. It offers the features of: (a) adapting to dynamic object state change, (b) adapting to dynamic role change, (c) preventing indirect information leakage, (d) detailing the control granularity to variables, (e) allowing purpose‐oriented method invocation, (f) controlling method invocation through argument sensitivity, (g) allowing declassification, and (h) allowing only trusted sources to write a variable.     

Robustness of reduced‐order observer‐based feedback control for discrete two‐time‐scale systems

Abstract

A design method to achieve robust stability and performance criteria for discrete two‐time‐scale systems controlled by low‐order observer‐based compensators is proposed. Sufficient conditions for stability and performance robustness are established by an easy extension of the small gain theorem. The theoretical analysis is illustrated by a numerical example.     

A nonintrusive distributed reduced-order modeling framework for nonlinear structural mechanics—Application to elastoviscoplastic computations

In this work, we propose a framework that constructs reduced-order models for nonlinear structural mechanics in a nonintrusive fashion and can handle large-scale simulations. Three steps are carried out: (i) the production of high-fidelity solutions by commercial software, (ii) the offline stage of the model reduction, and (iii) the online stage where the reduced-order model is exploited. The nonintrusivity assumes that only the displacement field solution is known, and the proposed framework carries out operations on these simulation data during the offline phase. The compatibility with a new commercial code only needs the implementation of a routine converting the discretized solution into our in-house data format. The nonintrusive capabilities of the framework are demonstrated on numerical experiments using commercial versions of Z-set and Ansys Mechanical. The nonlinear constitutive equations are evaluated by using an external plugin. The large-scale simulations are handled using domain decomposition and parallel computing with distributed memory. The features and performances of the framework are evaluated on two numerical applications involving elastoviscoplastic materials: the second one involves a model of high-pressure blade, where the framework is used to extrapolate cyclic loadings in 6.5 hours, whereas the reference high-fidelity computation would take 9.5 days.     

A new scheme for ID‐based cryptosystems and signatures

Abstract

This paper proposes a new ID‐based cryptographic scheme for implementing public‐key cryptosystems and signatures. Instead of generating and publishing a public key for each user, the ID‐based scheme permits each user to choose his name or network address as his public key. This eliminates the need of a large public‐file and the exchange of private or public keys. The major advantage of the ID‐based cryptosystems is that the number of users can be exteneded to t*L users without decreasing the system security when users conspire, where L is the number of the system's secrets and t is the number of factors in p ‐ 1.     

Passivity‐based adaptive position control for an induction motor

Abstract

This paper presents a passivity‐based composite adaptive control scheme for the position control of an induction motor. First, the dynamics of the induction motor are proved to be state strictly passive by the passivity theorem. Then, a composite adaptive estimation algorithm is designed to control the position of the induction motor and the global stability of the overall position control system is proved based on passivity instead of Lyapunov‐type arguments. The approach is robust with regard to variations of motor mechanical parameters and external load disturbances. Experimental results are provided to show that good position tracking capability can be obtained without knowledge of the rotor flux.     

A CTPN‐based scheduler for a flexible manufacturing cell

Abstract

This paper first presents hierarchical scheduling and control architecture for a flexible manufacturing cell (FMC) that is currently set up at the Mechanical Industrial Research Laboratories of the Industrial Technology Research Institute at Hsinchu, Taiwan. With this architecture, we focus on the scheduling problem of the FMC and present a scheduling mechanism based on a colored timed Petri net (CTPN) model. The CTPN model has three functions in the proposed mechanism: the first one is to formally describe pallet flows and resource constraints in the FMC by the event‐condition relation; the second one is to analyze conflict points among the pallet flows; the third one is to evaluate the used dispatching rules concerned with the selection of machine routings, the selection of work‐in‐process pallets in inter‐medium buffers and the assignment of the commonly used material‐handling device. Using the CTPN‐based scheduler, an appropriate combination of dispatching rules for each given batch can be selected to fit given criteria, e.g. minimum batch completion time, maximum resource utilization or minimum tardiness, etc. Moreover, real‐time status of the FMC can be represented in the mechanism for obtaining the on‐line scheduling effect.     

A job‐plan based performance evaluation for construction value engineering study

Abstract

Value Engineering can reduce costs and enhance the value of projects. Currently, the acceptance rate of Value Engineering Study (VES) recommendations and total potential savings are considered the principal performance indicators of a VES. In reality the success of a VES depends on numerous interrelated factors not easy for a VES team to control. However, a study team can ensure the success of a VES by fully implementing a VES job plan. Thus, realizing a job plan is a principal contribution toward insuring the success of the VES. This study presents a novel model that is able to evaluate the performance of a VES for a construction project. Two questionnaires, distributed to VE experts, were used to collect data needed for this research. Factor analysis, AHP, and SWAM were applied to build the VES performance evaluation model which consists of six evaluation groups and thirty‐two evaluation items. A real‐life VES for a construction project was then analyzed using the proposed model to demonstrate its usefulness in performance assessment. Defects of the VES were identified and suggestions were provided for the particular VES. The proposed model can be used by VES teams for self‐diagnosis, improvement, and motivation in achieving enhanced performance.     

A novel grey‐based feature ranking method for feature subset selection

Abstract

In this paper, a novel grey‐based feature ranking method for feature subset selection is proposed. The classification effectiveness of each attribute of a specific classification problem is proposed and then each attribute can be ranked. Features with higher classification effectiveness are more important and relevant and thus considered as the final feature subset for pattern classification. Experiments performed on various application domains are reported to demonstrate the performance of the proposed approach. The proposed approach yields better performance than other existing feature subset selection methods and is helpful for improving the classification accuracy in pattern classification.     

Delay‐dependent H∞ observer‐based control for uncertain neutral systems via LMI optimization approach

Abstract

In this paper, the delay‐dependent H∞ observer‐based control for a class of uncertain neutral systems with time‐varying delays is considered. The linear matrix inequality (LMI) optimization approach is used to design the H∞ robust control with disturbance attenuation. The control and observer gains are given from the LMI feasible solutions. Some numerical examples are given to illustrate the use of the main result.     

Subspace‐based techniques for 2‐d DOA estimation with uniform circular array under local scattering

Abstract

In mobile communication systems, local scatterers in the vicinity of the sources cause angular spreading of radiating signals as seen from a base station antenna array. Thus, the base station antenna array is typically situated on the roof of a high building away from potential multipath reflectors. The uniform circular array (UCA) geometry provides 360° azimuthal coverage and also provides information on source elevation angles. We consider the problem of two‐dimensional (azimuth and elevation) direction‐of‐arrival (DOA) estimation with UCA. In the multipath scenario, the base station antenna can receive many coherent signals that cause the array manifold to be different from the conventional array manifold model. Herein, parameters of the spatial signature in the presence of local scattering are presented which apply to UCA. Then, we present a fast searching technique to improve the efficiency of the MUSIC algorithm for two‐dimensional DOA estimation. The fast signal subspace‐based estimation method utilizes the ESPRIT algorithm and then adopts sequential one‐dimensional searching to save computational cost. Several simulation results are included for illustration and comparison.     

A simple model‐based nonlinear control strategy for feedback linearizable nonlinear processes

Abstract

In this paper we propose a simple and novel model‐based nonlinear control strategy for feedback linearizable nonlinear processes. The nonlinear controller, called NLC, has a forward static nonlinear element and, if the relative degree of the process is greater than unity, a linear dynamic feedback path. The nonlinear static element is a modified hyperbolic function which involves two tunable parameters used to adjust the linear gain and saturation level of the NLC. The NLC parameters are determined to achieve a desired tracking transfer function of the form (K_cs + 1)/(1 + ?s) ^r+1 where K_c and ? are parameters relating to NLC controller settings and r the system's relative degree. The effectiveness and applicability of the proposed nonlinear control strategy are demonstrated through the controls of nonlinear chemical processes. Extensive simulation results show that the proposed nonlinear control strategy is a robust model‐based approach for the nonlinear control of dynamic processes.     

Comparison of thermodynamic database models and APT data for strength modeling in high Nb content γ–γ′ Ni-base superalloys

In response to the increasing need for higher operating temperatures in advanced gas turbine engines, new alloying concepts are required to develop novel nickel-base superalloys with enhanced temperature capabilities. Recent studies have shown that polycrystalline Ni-base superalloys containing elevated levels of Nb additions exhibit superior properties at elevated temperatures when compared to existing commercial Ni-base superalloys. In order to design, develop and fully exploit this innovative class of superalloys, an understanding of how alloying elements partition to each phase is essential. Using atom probe tomography (APT), compositions of the constituent phases were measured in four high Nb content γ–γ′ Ni-base superalloys and the results were compared to thermodynamic database models from Thermo-Calc. Results were also used in predicting the solid solution strength behavior of the four alloys. The differences in phase composition predictions from thermodynamic models resulted in dissimilarities between the generated strength behavior curves and those from the experimental work.     

Application of genetic algorithm to the observer‐based controller design for neutral systems

Abstract

In this paper, the dynamic observer‐based controller design for a class of neutral systems with known and uncertain time delays is considered. Delay‐dependent and delay‐independent stabilizability criteria are proposed to guarantee the stability for the feedback control systems. Linear matrix inequality (LMI) and genetic algorithm (GA) are used to design the observer‐based control. Design procedure for the observer‐based control is provided. A numerical example is given to illustrate our results.     

A two‐layer cryptographic scheme for a service framework based on mobile agents

Abstract

In recent years, a new computation model, referred to as Service‐On‐Demand, has come into being gradually. This concept can be summarized as: the whole Net is a computer and one can have his/her tasks served using resources scattered around the Net. One technique that uses a similar concept is Web Service, which has been applied to many networks. However, Web Service is still confined to the Client‐Server paradigm and, in our opinion, does not wholly tally with the spirit of Service‐On‐Demand. Besides, there have not been many effective security schemes proposed for Web Services. This paper presents a mobile agent service framework, designed in reference to the service‐on‐demand concept, for the next generation of service‐based Internet applications. A two‐layer cryptographic security infrastructure is laid in the service framework to offer secured services. By separating the service functionality from its operating medium, the framework successfully prevents many security problems from happening. It also offers a most desirable benefit to both service providers and users. For service providers, deployment of a service is as easy as inserting a plug‐n‐play interface card and for service users, using a service is as easy as filling out a downloaded form. The main goal of this framework is to offer a total solution for providing secured services easily instead of doing difficult programming for services.     

Uncertain process–based reliability and maintenance modeling for systems under mutually dependent degradation and shock processes

For the systems that experience competing failure processes, an uncertain process–based degradation model is developed to describe the systems. The competing degradation process is composed of internal continuous degradation and external shocks, and the mutual dependence between them is considered. When the magnitude of the internal degradation exceeds the threshold, the soft failure occurs. While for the shock processes involving the randomness and the subjective information, we adopt the uncertain random renewal reward process to characterize it. Hard failure occurs when the damage of the shock process exceeds the strength threshold of the system. By using the belief reliability metric, the reliability of the degraded system is defined as the chance measure that neither soft failure nor hard failure occurs. And the effect of the degradation-shock dependence on the system reliability is performed by the parametric studies. Then the proposed degradation model is introduced into the preventive maintenance strategy to minimize the average maintenance cost. Using the microelectromechanical systems as an example, the effectiveness of the constructed degradation model and maintenance strategy is illustrated, and the proposed model can characterize the system degradation process in a superior way to the stochastic process model. These methods can be applied to other similar degraded systems and provide support for maintenance decisions.     

A novel combined molecular dynamics–micromechanics method for modeling of stiffness of graphene/epoxy nanocomposites with randomly distributed graphene

In this paper, by combining molecular dynamics and micromechanics methods, a new approach for prediction of the stiffness of the nanocomposites with randomly distributed nanoparticles in the macro level is presented. The molecular dynamics method is used to model the stiffness of the graphene/epoxy nanocomposites containing one layer of an aligned nano graphene embedded in epoxy resin. By considering the large sizes of the length and width of the nano graphene in comparison with its thickness and the shortcomings of the available hardware and software for simulation purposes, a new approach for modeling is also developed. This new approach, by using the moduli of different graphene sheets with different sizes embedded in a representative volume element, can predict the moduli of a real size graphene embedded in the matrix along the longitudinal, transverse and normal directions in the nano-scale. In order to consider the effect of the random distribution of graphene sheets in epoxy resin, a micromechanical approach is used. The results obtained by the molecular dynamics method are used by the micromechanics approach and the stiffness of graphene/epoxy nanocomposites with randomly distributed graphene in the macro-scale is predicted. An experimental program is conducted to evaluate the capability of the model. The result of the modeling is in a very good agreement with the experimental data.