903 resultados para Dynamic strain aging (DSA)
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This review gives a brief description of the historical development followed by the origin and the principle of operation of strain gauges. The features of an ideal strain gauge for measurement purposes and the general classes of strain gauges are given. The remaning part is devoted to an important development in strain gauge technology, namely thin film strain gauges. After highlighting the advantages of thin film strain gauges, a review of current data is given. Detailed description of metallic thin film strain gauges is provided and avaliable information on alloy semiconductor and cermet films for their possible use as strain gauge elements has also been included. The importance of ion implantation in tailoring the properties of strain gauges is highlighted. 33 ref.--AA
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The growth of characteristic length scales associated with dynamic heterogeneity in glass-forming liquids is investigated in an extensive computational study of a four-point, time-dependent structure factor defined from spatial correlations of mobility, for a model liquid for system sizes extending up to 351 232 particles, in constant-energy and constant-temperature ensembles. Our estimates for dynamic correlation lengths and susceptibilities are consistent with previous results from finite size scaling. We find scaling exponents that are inconsistent with predictions from inhomogeneous mode coupling theory and a recent simulation confirmation of these predictions.
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CMPs enable simultaneous execution of multiple applications on the same platforms that share cache resources. Diversity in the cache access patterns of these simultaneously executing applications can potentially trigger inter-application interference, leading to cache pollution. Whereas a large cache can ameliorate this problem, the issues of larger power consumption with increasing cache size, amplified at sub-100nm technologies, makes this solution prohibitive. In this paper in order to address the issues relating to power-aware performance of caches, we propose a caching structure that addresses the following: 1. Definition of application-specific cache partitions as an aggregation of caching units (molecules). The parameters of each molecule namely size, associativity and line size are chosen so that the power consumed by it and access time are optimal for the given technology. 2. Application-Specific resizing of cache partitions with variable and adaptive associativity per cache line, way size and variable line size. 3. A replacement policy that is transparent to the partition in terms of size, heterogeneity in associativity and line size. Through simulation studies we establish the superiority of molecular cache (caches built as aggregations of molecules) that offers a 29% power advantage over that of an equivalently performing traditional cache.
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We present a study of the piezoresistivity in nanostructured. polycrystalline films of La0.67Ca0.33MnO3 and La0.67Sr0.33MnO3 grown on oxidized Si (100) substrates. We have observed that the hole doped rare-earth manganites, which are well known for being colossal magnetoresistive (CMR) show change in its resistance under uniaxial strain even at room temperature. The piezoresistance was measured at room temperature by bending the Si cantilevers (on which the film is grown) in flexural mode both with compressive and tensile strain. The resistance of the film increases with tensile strain and decreases with compressive strain. A large gauge factor of 15-20 is seen in these films at room temperature.
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Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.
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Most of the structural elements like beams, cables etc. are flexible and should be modeled as distributed parameter systems (DPS) to represent the reality better. For large structures, the usual approach of 'modal representation' is not an accurate representation. Moreover, for excessive vibrations (possibly due to strong wind, earthquake etc.), external power source (controller) is needed to suppress it, as the natural damping of these structures is usually small. In this paper, we propose to use a recently developed optinial dynamic inversion technique to design a set of discrete controllers for this purpose. We assume that the control force to the structure is applied through finite number of actuators, which are located at predefined locations in the spatial domain. The method used in this paper determines control forces directly from the partial differential equation (PDE) model of the system. The formulation has better practical significance, both because it leads to a closed form solution of the controller (hence avoids computational issues) as well as because a set of discrete actuators along the spatial domain can be implemented with relative ease (as compared to a continuous actuator).
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Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.
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In order to bring insight into the emerging concept of relationship communication, concepts from two research traditions will be combined in this paper. Based on those concepts a new model, the dynamic relationship communication model, will be presented. Instead of a company perspective focusing on the integration of outgoing messages such as advertising, public relations and sales activities, it is suggested that the focus should be on factors integrated by the receiver. Such factors can be historical, future, external and internal factors. Thus, the model put a strong focus on the receiver in the communication process. The dynamic communication model is illustrated empirically using it as a tool on 78 short stories about communication. The empirical findings show that relationship communication occurs in some cases; in some cases it does not occur. The model is a useful tool in displaying relationship communication and how it differs from other communication. The importance of the time dimension, historical and future factors, in relationship communications is discussed. The possibility of reducing communications costs by the notion of relationship communication is discussed in managerial implications.
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using two types of organic ligands having similar chemical structure but different physical properties and varying their dynamic population at the surface of zinc blende seed nanocrystals, self-assembled zinc blende semicircular-shaped bent nanowires of CdS are synthesized via a colloidal synthetic approach. It is found that the hydrophobic tail interaction of long-chain ligands puts strain on these thin nanowires (< 2 nm diameter) and bend them to some extent, forming strained nanowires.
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In this letter we characterize strain in Si1-xGex based heterojunction bipolar transistors and modulation doped field effect transistors grown by rapid thermal chemical vapor deposition exploiting the phenomenon of strain-induced birefringence. The technique used is multiple angle of incidence ellipsometry at a wavelength of 670 nm to measure the ordinary and extraordinary refractive indices of the Si1-xGex films. We report measurements on thin fully strained films (with thicknesses less than the critical thickness) with Ge concentration varying from 9% to 40% with an accuracy of the order of 1 part in 10(4) and propose an empirical relation between the difference in the ordinary and extraordinary refractive indices (deltan) and the Ge concentration (x) given by deltan(x)=0.18x-0.12x(2). (C) 2000 American Institute of Physics. [S0003-6951(00)03948-6].
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Direct injection of genomic DNA from salt tolerant cv. Pokkali into developing floral tillers on IR20 produced transgenic seeds similar to Pokkali in husk colour and which germinated well in 0.2 M NaCl and had a 4-6-fold higher proline content.
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An application of Artificial Neural Networks for predicting the stress-strain response of jointed rocks under different confining pressures is presented in this paper. Rocks of different compressive strength with different joint properties (frequency, orientation and strength of joints) are considered in this study. The database for training the neural network is formed from the results of triaxial compression tests on different intact and jointed rocks with different joint properties tested at different confining pressures reported by various researchers in the literature. The network was trained using a three-layered network with the feed-forward back propagation algorithm.About 85% of the data was used for training and the remaining 15% was used for testing the network. Results from the analyses demonstrated that the neural network approach is effective in capturing the stress-strain behaviour of intact rocks and the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different jointed rocks, whose intact strength varies from 11.32 MPa to 123 MPa, spacing of joints varies from 10 cm to 100 cm. and confining pressures range from 0 to 13.8 MPa. (C) 2010 Elsevier Ltd. All rights reserved.
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Strain and temperature sensitivities of a type I Bragg grating inscribed in a germania doped silica fiber, fabricated under normal conditions and zero strain, are compared with that of a Bragg grating inscribed under pre-strained condition. The results obtained reveal that the strain and temperature sensitivities of the two gratings are different. Based on these results, we demonstrate a technique which enables discrimination of strain and temperature in a Fiber Bragg Grating (FBG) with a linear response. The present technique allows for an easy implementation of the sensor by providing a direct access to the grating region in the fiber and demands only a simple interrogation system.