Ultraminiaturized High-Speed Permanent-Magnet Generators for Milliwatt-Level Power Generation

This paper presents the design, fabrication, and characterization of millimeter-scale rotary electromagnetic generators. The axial-flux synchronous machines consist of a three-phase microfabricated surface-wound copper coil and a multipole permanent-magnet (PM) rotor measuring 2 mm in diameter. Several machines with various geometries and numbers of magnetic poles and turns per pole are designed and compared. Moreover, the use of different PM materials is investigated. Multipole magnetic rotors are modeled using finite element analysis to analyze magnetic field distributions. In operation, the rotor is spun above the microfabricated stator coils using an off-the-shelf air-driven turbine. As a result of design choices, the generators present different levels of operating frequency and electrical output power. The four-pole six-turn/pole NdFeB generator exhibits up to 6.6 $hbox{mW}_{rm rms}$ of ac electrical power across a resistive load at a rotational speed of 392 000 r/min. This milliwatt-scale power generation indicates the feasibility of such ultrasmall machines for low-power applications.$hfill$ [2008-0078]      

Magnetic induction machines integrated into bulk-micromachined silicon

This paper presents the design, fabrication, and characterization of laminated, magnetic induction machines intended for high-speed, high-temperature, high-power-density, silicon-based microengine power generation systems. Innovative fabrication techniques were used to embed electroplated materials (Cu, Ni/sub 80/Fe/sub 20/, Co/sub 65/Fe/sub 18/Ni/sub 17/) within bulk-micromachined and fusion-bonded silicon to form the machine structures. The induction machines were characterized in motoring mode using tethered rotors, and exhibited a maximum measured torque of 2.5 /spl mu/N/spl middot/m.     

Array Decompositions for Nonuniform Computational Environments

Two-dimensional arrays are useful in a large variety of scientific and engineering applications. Parallelization of these applications requires the decomposition of array elements among different machines. Several data-decomposition techniques have been studied in the literature for machines with uniform computational power. In this paper, we develop new methods for decomposing arrays into a cluster of machines with nonuniform computational power. Simulation results show that our methods provide superior decomposition over naive schemes.     

Hybrid simulation of electrical machines in combination with power electronics

The dynamical behaviour of electrical machines can be investigated by purely digital simulation methods. However, if the machines are loaded or driven by power electronics(eg rectifier bridges) a full hybrid approach has many advantages. This article describes how electrical machines which operate in combination with power electronics can be simulated. The method is suitable for investigating any interaction between the electrical machine and the power convertor. This study deals with two applications of electrical machines affected by power convertors namely a rectifier loaded synchronous machine and a thyristor controlled induction motor(phase control).     

Self-similarity of parallel machines

Self-similarity is a property of physical systems that describes how to scale parameters such that dissimilar systems appear to be similar. Computer systems are self-similar if certain ratios of computational forces, also known as computational intensities, are equal. Two machines with different computational power, different network bandwidth and different inter-processor latency behave the same way if they have the same ratios of forces. For the parallel conjugate gradient algorithm studied in this paper, two machines are self-similar if and only if the ratio of one force describing latency effects to another force describing bandwidth effects is the same for both machines. For the two machines studied in this paper, this ratio, which we call the mixing coefficient, is invariant as problem size and processor count change. The two machines have the same mixing coefficient and belong to the same equivalence class.     

A heuristic training-based least squares support vector machines for power system stabilization by SMES

This paper presents the application of least squares support vector machines (LS-SVMs) to design of an adaptive damping controller for superconducting magnetic energy storage (SMES). To accelerate LS-SVMs training and testing, a large amount of training data set of a multi-machine power system is reduced by the measurement of similarity among samples. In addition, the redundant data in the training set can be significantly discarded. The LS-SVM for SMES controllers are trained using the optimal LS-SVM parameters optimized by a particle swarm optimization and the reduced data. The LS-SVM control signals can be adapted by various operating conditions and different disturbances. Simulation results in a two-area four-machine power system demonstrate that the proposed LS-SVM for SMES controller is robust to various disturbances under a wide range of operating conditions in comparison to the conventional SMES.     

Stable encoding of finite-state machines in discrete-time recurrent neural nets with sigmoid units

There has been a lot of interest in the use of discrete-time recurrent neural nets (DTRNN) to learn finite-state tasks, with interesting results regarding the induction of simple finite-state machines from input-output strings. Parallel work has studied the computational power of DTRNN in connection with finite-state computation. This article describes a simple strategy to devise stable encodings of finite-state machines in computationally capable discrete-time recurrent neural architectures with sigmoid units and gives a detailed presentation on how this strategy may be applied to encode a general class of finite-state machines in a variety of commonly used first- and second-order recurrent neural networks. Unlike previous work that either imposed some restrictions to state values or used a detailed analysis based on fixed-point attractors, our approach applies to any positive, bounded, strictly growing, continuous activation function and uses simple bounding criteria based on a study of the conditions under which a proposed encoding scheme guarantees that the DTRNN is actually behaving as a finite-state machine.     

Data analytics for energy-efficient clouds: design,implementation and evaluation

ABSTRACT

The success of Cloud Computing and the resulting ever growing of large data centers is causing a huge rise in electrical power consumption by hardware facilities and cooling systems. This results in an increment of operational costs of data centres, that is becoming a crucial issue to deal with. Consolidation of virtual machines (VM) is one of the key strategies used to reduce the power consumption of Cloud servers. For this reason, it is extensively studied. Consolidation has the goal of allocating virtual machines on a few physical servers as possible while satisfying the Service Level Agreement established with users. Nevertheless, the effectiveness of a consolidation strategy strongly depends on the forecast of the VM resource needs. Predictive data mining models can be exploited for this purpose. This paper describes the design and development of a system for energy-aware allocation of virtual machines, driven by predictive data mining models. In particular, migrations are driven by the forecast of the future computational needs (CPU, RAM) of each virtual machine, in order to efficiently allocate those on the available servers. The experimental evaluation, performed on real-world Cloud data traces, reports a comparison of performance achieved by exploiting several classification models and shows good benefits in terms of energy saving.     

Generation of discontinuous gaits for quadruped walking vehicles

Discontinuous gaits for walking machines have not yet been properly studied. Research has focused on the investigation, comprehension, and mathematical formulation of natural gaits. These gaits feature the fact that the body is in constant motion. The results have been significant, but they seem more adequate for animals than machines. On the other hand, discontinuous gaits, executed by animals under extreme conditions, exhibit excellent attributes for implementation in walking machines. This article presents a comparative study of continuous and discontinuous gaits with regard to their maximum achievable velocity and stability. Other aspects such as implementation in real machines, power requirements, and control under terrain difficulties are mentioned briefly. An elemental discontinuous gait is stated, and some variations on deriving crab and turning gaits are performed. Different methods for enlarging the achievable crab angle and improving stability are discussed for discontinuous crab gaits. A similar study is also done for turning gaits. (c) 1995 John Wiley & Sons, Inc.     

Energy profile of rollback-recovery strategies in high performance computing

Extreme-scale computing is set to provide the infrastructure for the advances and breakthroughs that will solve some of the hardest problems in science and engineering. However, resilience and energy concerns loom as two of the major challenges for machines at that scale. The number of components that will be assembled in the supercomputers plays a fundamental role in these challenges. First, a large number of parts will substantially increase the failure rate of the system compared to the failure frequency of current machines. Second, those components have to fit within the power envelope of the installation and keep the energy consumption within operational margins. Extreme-scale machines will have to incorporate fault tolerance mechanisms and honor the energy and power restrictions. Therefore, it is essential to understand how fault tolerance and energy consumption interplay. This paper presents a comparative evaluation and analysis of energy consumption of three different rollback-recovery protocols: checkpoint/restart, message logging and parallel recovery. Our experimental evaluation shows parallel recovery has the minimum execution time and energy consumption. Additionally, we present an analytical model that projects parallel recovery can reduce energy consumption more than 37% compared to checkpoint/restart at extreme scale.     

Integrated electromagnetic microactuators with a large driving force

This paper describes a high power electromagnetic microactuator fabrication method that combines the hard magnetic Fe/Pt process, Ni/Fe permalloy magnetic circuit design, bulk micromachining, and excimer laser ablation. The hard magnetic material Fe/Pt is deposited under low temperature less than 350°C by sputter onto a suspension diaphragm to produce a perpendicular magnetic anisotropic field. The magnetic circuit with closed loop design is applied to concentrate the magnetic flux and increase the magnetic force. The magnetic field induced by the planar coil and Ni/Fe permalloy enhances the interaction with Fe/Pt to induce attractive and repulsive displacement, provide large output force, and operate at high frequency. This high power electromagnetic microactuator is demonstrated with minimum dimensions with a magnetic force two times greater than conventional magnetic micro-actuators.     

Effects of a magnetic field environment on quantum cloning of qubits

No cloning distinguishes the quantum cryptography. Buzek and Hillery have developed a universal quantum cloning machine that allows providing two copies of an arbitrary qubit state with the same accuracy independently of the input-state. The fidelity has been used as a criterion to characterize the cloning. It was found that this parameter can achieve 0.85 for special subsets of quantum states, i.e, equatorial qubits. In the present paper, we investigate the effects of a magnetic field environment as a perturbation of the cloning process. The quantum copying machines studied consist of UQCM-BH and UQCM-PC. Results have been discussed using both the fidelity and the relative entropy. Much attention has been paid to the magnetic field-related decoherence of ancillary qubits before preparation. An attempt to explain the impact of this decoherence on the performance of copying machines will be presented.     

Combining a maintenance center M/M/c/m queue into the economic production quantity model with stochastic machine breakdowns and repair

This article considers a production system in which “m” identical machines produce nonidentical products at production rates. Products made by each machine are on the other hand consumed at a specific demand rate. Machines may be affected by unwanted breakdowns. Machines break down according to a Poisson distribution with equal rates and the failed machines are sent to maintenance center for repair which is consisted of “c” servers or servicemen. However, Number of machines is greater than number of servicemen (m > c). Hence, if the number of failed machines is greater than that of servicemen, the machines have to be put in a queue. Machines are put in one queue with the order of queue being FCFS. The queue has a typical M/M/c/m system. If machines are broken down during production, shortage will occur. This problem has been considered to obtain a single production cycle for the machines and an optimum number of the servers such that costs are minimized. For this purpose, distribution of waiting time for machines in repair center is calculated and a cost function is formed. Steepest descent and direct search methods are applied in this work to obtain optimal production cycle and maintenance servers, respectively. The proposed methods are studied using a comprehensive example.     

Combining a maintenance center M/M/c/m queue into the economic production quantity model with stochastic machine breakdowns and repair

This article considers a production system in which “m” identical machines produce nonidentical products at production rates. Products made by each machine are on the other hand consumed at a specific demand rate. Machines may be affected by unwanted breakdowns. Machines break down according to a Poisson distribution with equal rates and the failed machines are sent to maintenance center for repair which is consisted of “c” servers or servicemen. However, Number of machines is greater than number of servicemen (m > c). Hence, if the number of failed machines is greater than that of servicemen, the machines have to be put in a queue. Machines are put in one queue with the order of queue being FCFS. The queue has a typical M/M/c/m system. If machines are broken down during production, shortage will occur. This problem has been considered to obtain a single production cycle for the machines and an optimum number of the servers such that costs are minimized. For this purpose, distribution of waiting time for machines in repair center is calculated and a cost function is formed. Steepest descent and direct search methods are applied in this work to obtain optimal production cycle and maintenance servers, respectively. The proposed methods are studied using a comprehensive example.     

Theory of one-tape linear-time Turing machines

A theory of one-tape two-way one-head off-line linear-time Turing machines is essentially different from its polynomial-time counterpart since these machines are closely related to finite state automata. This paper discusses structural-complexity issues of one-tape Turing machines of various types (deterministic, nondeterministic, reversible, alternating, probabilistic, counting, and quantum Turing machines) that halt in linear time, where the running time of a machine is defined as the length of any longest computation path. We explore structural properties of one-tape linear-time Turing machines and clarify how the machines’ resources affect their computational patterns and power.     

Future computer technology for large power system simulation

A true technological explosion has taken place in the computer hardware industry in the last few years. Words such as parallel processing, vector processors, array processors, pipelined machines, ‘number crunching’, and megaflops (Millions of FLoating-point OPerations per Second) are heard regularly. Computer manufacturers have responded to the needs of specific groups requiring, above all else, high speed arithmetic capability. The result is a host of new machines which are called in this paper ‘vector processors’. This paper will assess the applicability of vector processors to power flow and transient stability simulation programs and will indicate how these programs should be organized to run efficiently on these new machines. The approach taken will be to survey the entire class of vector processors available now and in the near future, to attempt to raise the reported low efficiency of sparsity-coded programs for large vector processors by reorganizing their sparse structure.     

The art of modeling and simulation of induction generator in wind generation applications using high-order model

Both fixed-speed squirrel-cage induction generators and variable-speed doubly fed induction generators are used in wind turbine generation technology. Modeling and simulation of induction machines using vector computing technique in Matlab/Simulink provides an efficient approach for further research on wind generation system integration and control. In this paper, the vector computing technique is applied in modeling and simulation of induction machines. Free acceleration of squirrel-cage induction generator, active power and reactive power control of DFIGs in a power system as well as inter-area oscillation damping control are demonstrated using the proposed model. The modeling approach in Matlab/Simulink makes controller design and simulation verification effective.     

Energy-aware capacity scaling in virtualized environments with performance guarantees

We investigate the trade-off between performance and power consumption in servers hosting virtual machines running IT services. The performance behavior of such servers is modeled through Generalized Processor Sharing (GPS) queues enhanced with a green speed-scaling mechanism that controls the processing capacity to use depending on the number of active virtual machines. When the number of virtual machines grows large, we show that the stochastic evolution of our model converges to a system of ordinary differential equations for which we derive a closed-form formula for its unique stationary point. This point is a function of the capacity and the shares that characterize the GPS mechanism. It allows us to show that speed-scaling mechanisms can provide large reduction in power consumption having only small performance degradation in terms of the delays experienced in the virtual machines. In addition, we derive the optimal choice for the shares of the GPS discipline, which turns out to be non-trivial. Finally, we show how our asymptotic analysis can be applied to the dimensioning and service partitioning in data-centers. Experimental results show that our asymptotic formulas are accurate even when the number of virtual machines is small.     

Common software for electromagnetic and heat fields analysis of electrical machines including the force calculation

The modern practice of electrical machines design has needed the discrete fields analysis to prevent the growth of local eddy currents, overheating, thermoelastic stresses and magnetic vibrations. The common package for solving electromagnetic and heating problems in any regions of electric machines was created and used in practice. All programs are realized on IBM PC/AT. Some interesting methodical tasks were investigated and solved in this work.     

On the power of alternation on reversal-bounded alternating Turing machines with a restriction

Whether or not there is a difference of the power among alternating Turing machines with a bounded number of alternations is one of the most important problems in the field of computer science. This paper presents the following result: Let R(n) be a space and reversal constructible function. Then, for any k 1, we obtain that the class of languages accepted by off-line 1-tape rσ_k machines running in reversal O(R(n)) is equal to the class of languages accepted by off-line 1-tape σ₁ machines running in reversal O(R(n)). An off-line 1-tape σ_k machine M is called an off-line 1-tape rσ_k machine if M always limits the non-blank part of the work-tape to at most O(R(n) log n) when making an alternation between universal and existential states during the computation.