Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Modeling and analysis of a novel variable-speed cage induction generator

This paper introduces a novel cage induction generator and presents a mathematical model, through which its behavior can be accurately predicted. The proposed generator system employs a three-phase cage induction machine and generates single-phase and constant-frequency electricity at varying rotor speeds without an intermediate inverter stage. The technique uses any one of the three stator phases of the machine as the excitation winding and the remaining two phases, which are connected in series, as the power winding. The two-series-connected-and-one-isolated (TSCAOI) phase winding configuration magnetically decouples the two sets of windings, enabling independent control. Electricity is generated through the power winding at both sub- and super-synchronous speeds with appropriate excitation to the isolated single winding at any frequency of generation. A dynamic mathematical model, which accurately predicts the behavior of the proposed generator, is also presented and implemented in MATLAB/Simulink. Experimental results of a 2-kW prototype generator under various operating conditions are presented, together with theoretical results, to demonstrate the viability of the TSCAOI power generation. The proposed generator is simple and capable of both storage and retrieval of energy through its excitation winding and is expected to be suitable for applications, such as small wind turbines and microhydro systems.

Five-level current-source inverters with buck-boost and inductive-current balancing capabilities

This paper presents new five-level current-source inverters (CSIs) with voltage/current buck-boost capability, unlike existing five-level CSIs where only voltage-boost operation is supported. The proposed inverters attain self-inductive-current-balancing per switching cycle at their dc front ends without having to include additional balancing hardware or complex control manipulation. The inverters can conveniently be controlled by using the well-established phase-shifted carrier modulation scheme with only two additional linear references and a mapping logic table needed. Existing modulators can therefore be conveniently retrofitted for controlling the presented inverters. By appropriately coordinating the inverter gating signals, their implementations can be realized by using the least number of components without degrading performance. These enhanced features of the inverters have already been verified in simulation and experimentally using a scaled-down laboratory platform.

Contact with existing adipose tissue is inductive for adipogenesis in matrigel

The effect of adipose tissue on inductive adipogenesis within Matrigel (BD Biosciences) was assessed by using a murine chamber model containing a vascular pedicle. Three-chamber configurations that varied in the access to an adipose tissue source were used, including sealed- and open-chamber groups that had no access and limited access, respectively, to the surrounding adipose tissue, and a sealed-chamber group in which adipose tissue was placed as an autograft. All groups showed neovascularization, but varied in the amount of adipogenesis seen in direct relation to their access to preexisting adipose tissue: open chambers showed strong adipogenesis, whereas the sealed chambers had little or no adipose tissue; adipogenesis was restored in the autograft chamber group that contained 2- to 5-mg fat autografts. These showed significantly more adipogenesis than the sealed chambers with no autograft (p < 0.01). Autografts with 1 mg of fat were capable of producing adipogenesis but did so less consistently than the larger autografts. These findings have important implications for adipose tissue engineering strategies and for understanding de novo production of adipose tissue.

Graphene and carbon nanotubes from arc plasmas : experiment and plasma modeling

Graphene and carbon nanotubes are the most promising nanomaterials for application in various modern nanodevices. The successful production of the nanotubes and graphene in a single process was achieved by using a magnetically enhanced arc discharge in helium atmosphere between carbon and metal electrodes. A 3-D fluid model has been used to investigate the discharge parameters.

Mathematical modeling of the cancer cell’s control circuitry : paving the way to individualized therapeutic strategies

Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cells finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as ‘ultrasensitivity’ and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating ‘simple’ signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how ‘control-oriented’ models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.

Degradation modeling and monitoring of machines using operation-specific hidden Markov models

In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

A simulation modeling approach to understanding information technology value cocreation

The business value of information technology (IT) is increasingly being cocreated by multiple parties, opening opportunities for new research initiatives. Previous studies on IT value cocreation mainly focus on analyzing sources of cocreated IT value, yet inadequately accommodating the influence of competition relationships in IT value cocreation activities. To fill the gap, this in-progress paper suggests an agent-based modeling (also simulation) approach to investigating potential influences of the dynamic interplay between cooperation and competition relationships in IT value cocreation settings. In particular, the research proposes a high-level conceptual framework to position general IT value cocreation processes. A relational network view is offered, aiming at decomposing and systemizing several typical cooperation and competition scenarios in practical IT value cocreation settings. The application of a simulation approach to analytical insights and to theory building is illustrated.

Controller synthesis of a bidirectional inductive power interface for electric vehicles

Bidirectional Inductive Power Transfer (IPT) systems are preferred for Vehicle-to-Grid (V2G) applications. Typically, bidirectional IPT systems consist of high order resonant networks, and therefore, the control of bidirectional IPT systems has always been a difficulty. To date several different controllers have been reported, but these have been designed using steady-state models, which invariably, are incapable of providing an accurate insight into the dynamic behaviour of the system A dynamic state-space model of a bidirectional IPT system has been reported. However, currently this model has not been used to optimise the design of controllers. Therefore, this paper proposes an optimised controller based on the dynamic model. To verify the operation of the proposed controller simulated results of the optimised controller and simulated results of another controller are compared. Results indicate that the proposed controller is capable of accurately and stably controlling the power flow in a bidirectional IPT system.

A matrix converter based Inductive Power Transfer system

Typical Inductive Power Transfer (IPT) systems employ two power conversion stages to generate a high frequency current from low frequency utility supply. This paper proposes a matrix converter based IPT system that facilitates the generation of high frequency current through a single power conversion stage. The proposed matrix converter topology transforms a 3-phase low frequency voltage system to a high frequency single phase voltage which in turn powers a series compensated IPT system. A comprehensive mathematical model is developed to investigate the behavior of the proposed IPT topology. Theoretical results are presented in comparison to simulations, which are performed in Matlab/ Simulink, to demonstrate the applicability of the proposed concept and the validity of the developed model.