61 resultados para non-exhaustible energy


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Space plasmas provide abundant evidence of highly energetic particle population, resulting in a long-tailed non-Maxwellian distribution. Furthermore, the first stages in the evolution of plasmas produced during laser-matter interaction are dominated by nonthermal electrons, as confirmed by experimental observation and computer simulations. This phenomenon is efficiently modelled via a kappa-type distribution. We present an overview, from first principles, of the effect of superthermality on the characteristics of electrostatic plasma waves. We rely on a fluid model for ion-acoustic excitations, employing a kappa distribution function to model excess superthermality of the electron distribution. Focusing on nonlinear excitations (solitons), in the form of solitary waves (pulses), shocks and envelope solitons, and employing standard methodological tools of nonlinear plasmadynamical analysis, we discuss the role of excess superthermality in their propagation dynamics (existence laws, stability profile), geometric characteristics and stability. Numerical simulations are employed to confirm theoretical predictions, namely in terms of the stability of electrostatic pulses, as well as the modulational stability profile of bright- and dark-type envelope solitons.

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Boundary layer transition estimation and modelling is essential for the design of many engineering products across many industries. In this paper, the Reynolds-averaged Navier–Stokes are solved in conjunction with three additional transport equations to model and predict boundary layer transition. The transition model (referred to as the kTkT–kLkL–ωω model) is based on the kk–ωω framework with an additional transport equation to incorporate the effects low-frequency flow oscillations in the form of a laminar kinetic energy (kLkL). Firstly, a number of rectifications are made to the original kTkT–kLkL–ωω framework in order to ensure an appropriate response to the free-stream turbulence level and to improve near wall predictions. Additionally, the model is extended to incorporate the capability to model transition due to surface irregularities in the form of backward-facing steps with maximum non-dimensional step sizes of approximately 1.5 times the local displacement thickness of the boundary layer where the irregularity is located (i.e k/δ∗⪅1.5k/δ∗⪅1.5) at upstream turbulence intensities in the range 0.01<Tu(%)<0.80.01<Tu(%)<0.8. A novel function is proposed to incorporate transition sensitivity due to aft-facing steps. This paper details the rationale behind the development of this new function and demonstrates its suitability for transition onset estimation on a flat plate at zero pressure gradient.

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In future systems with relatively unreliable and unpredictable energy sources such as harvesters, the system power supply may become non-deterministic. For energy effective operations, Vdd is an important parameter in any meaningful system control mechanism. Reliable and accurate on-chip voltage sensors are therefore indispensible for the power and computation management of such systems. Existing voltage sensing methods are not suitable because they usually require a stable and known reference (voltage, current, time, frequency, etc.), which is difficult to obtain in this environment. This paper describes an autonomous reference-free voltage sensor designed using an asynchronous counter powered by the charge on a capacitor and a small controller. Unlike existing methods, the voltage information is directly generated as a digital code. The sensor, fabricated in the 180 nm technology node, was tested successfully through performing measurements over the voltage range from 1.8 V down to 0.8 V.

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Nonlinear phenomena play an essential role in the sound production process of many musical instruments. A common source of these effects is object collision, the numerical simulation of which is known to give rise to stability
issues. This paper presents a method to construct numerical schemes that conserve the total energy in simulations of one-mass systems involving collisions, with no conditions imposed on any of the physical or numerical parameters.
This facilitates the adaptation of numerical models to experimental data, and allows a more free parameter adjustment in sound synthesis explorations. The energy preservedness of the proposed method is tested and demonstrated though several examples, including a bouncing ball and a non-linear oscillator, and implications regarding the wider applicability are discussed.

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We study the interplay between forgetful and memory-keeping evolution enforced on a two-level system by a multi-spin environment whose elements are coupled to local bosonic baths. Contrarily to the expectation that any non-Markovian effect would be buried by the forgetful mechanism induced by the spin-bath coupling, one can actually induce a full Markovian-to-non-Markovian transition of the two-level system's dynamics, controllable by parameters such as the mismatch between the energy of the two-level system and of the spin environment. For a symmetric coupling, the amount of non-Markovianity surprisingly grows with the number of decoherence channels. DOI: 10.1103/PhysRevA.87.022317

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Hydro-entanglement is a versatile process for bonding non-woven fabrics by the use of fine, closely-spaced, high-velocity jets of water to rearrange and entangle arrays of fibres. The cost of the process mainly depends on the amount of energy consumed. Therefore, the economy of the process is highly affected by optimisation of the energy required. In this paper a parameter called critical pressure is introduced which is indicative of the energy level requirement. The results of extensive experimental work are reported and analysed to give a clear understanding of the effect of the web and fibre properties on the critical pressure in the hydro-entanglement process. Furthermore, different energy-transfer distribution schemes are tested on various fabrics. The optimum scheme which involves the lowest energy consumption and the best fabric properties is identified. © 2001 Published by Elsevier Science Ltd. All rights reserved.

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Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

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Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

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Linear wave theory models are commonly applied to predict the performance of bottom-hinged oscillating wave surge converters (OWSC) in operational sea states. To account for non-linear effects, the additional input of coefficients not included in the model itself becomes necessary. In ocean engineering it is
common practice to obtain damping coefficients of floating structures from free decay tests. This paper presents results obtained from experimental tank tests and numerical computational fluid dynamics simulations of OWSC’s. Agreement between numerical and experimental methods is found to be very good, with CFD providing more data points at small amplitude rotations.
Analysis of the obtained data reveals that linear quadratic-damping, as commonly used in time domain models, is not able to accurately model the occurring damping over the whole regime of rotation amplitudes. The authors
conclude that a hyperbolic function is most suitable to express the instantaneous damping ratio over the rotation amplitude and would be the best choice to be used in coefficient based time domain models.

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Collisions are an innate part of the function of many musical instruments. Due to the nonlinear nature of contact forces, special care has to be taken in the construction of numerical schemes for simulation and sound synthesis. Finite difference schemes and other time-stepping algorithms used for musical instrument modelling purposes are normally arrived at by discretising a Newtonian description of the system. However because impact forces are non-analytic functions of the phase space variables, algorithm stability can rarely be established this way. This paper presents a systematic approach to deriving energy conserving schemes for frictionless impact modelling. The proposed numerical formulations follow from discretising Hamilton׳s equations of motion, generally leading to an implicit system of nonlinear equations that can be solved with Newton׳s method. The approach is first outlined for point mass collisions and then extended to distributed settings, such as vibrating strings and beams colliding with rigid obstacles. Stability and other relevant properties of the proposed approach are discussed and further demonstrated with simulation examples. The methodology is exemplified through a case study on tanpura string vibration, with the results confirming the main findings of previous studies on the role of the bridge in sound generation with this type of string instrument.

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In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

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This document describes best practice and evidence based recommendations for the use of FDG-PET/CT for the purposes of radiotherapy target volume delineation (TVD) for curative intent treatment of non-small cell lung cancer (NSCLC). These recommendations have been written by an expert advisory group, convened by the International Atomic Energy Agency (IAEA) to facilitate a Coordinated Research Project (CRP) aiming to improve the applications of PET based radiation treatment planning (RTP) in low and middle income countries. These guidelines can be applied in routine clinical practice of radiotherapy TVD, for NSCLC patients treated with concurrent chemoradiation or radiotherapy alone, where FDG is used, and where a calibrated PET camera system equipped for RTP patient positioning is available. Recommendations are provided for PET and CT image visualization and interpretation, and for tumor delineation using planning CT with and without breathing motion compensation.

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Increasingly large amounts of data are stored in main memory of data center servers. However, DRAM-based memory is an important consumer of energy and is unlikely to scale in the future. Various byte-addressable non-volatile memory (NVM) technologies promise high density and near-zero static energy, however they suffer from increased latency and increased dynamic energy consumption.

This paper proposes to leverage a hybrid memory architecture, consisting of both DRAM and NVM, by novel, application-level data management policies that decide to place data on DRAM vs. NVM. We analyze modern column-oriented and key-value data stores and demonstrate the feasibility of application-level data management. Cycle-accurate simulation confirms that our methodology reduces the energy with least performance degradation as compared to the current state-of-the-art hardware or OS approaches. Moreover, we utilize our techniques to apportion DRAM and NVM memory sizes for these workloads.