424 resultados para cyclic stability


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Methods which disperse single-walled carbon nanotubes (SWNTs) in water as `debundled', while maintaining their unique physical properties are highly useful. We present here a family of cationic cholesterol compounds (Chol(+)) {Cholest-5en-3 beta-oxyethyl pyridinium bromide (Chol-PB+), Cholest-5en-3 beta-oxyethyl N-methyl pyrrolidinium bromide (Chol-MPB+), Cholest-5en-3 beta-oxyethyl N-methyl morpholinium bromide (Chol-MMB+) and Cholest-5en-3 beta-oxyethyl diazabicyclo octanium bromide (Chol-DOB+)}. Each of these could be easily dispersed in water. The resulting cationic cholesterol (Chol(+)) suspensions solubilized single-walled carbon nanotubes (SWCNTs) by the non-specific physical adsorption of Chol(+) to form stable, transparent, dark aqueous suspensions at room temperature. Electron microscopy reveals the existence of highly segregated CNTs in these samples. Zeta potential measurements showed an increase in potential of cationic cholesterol aggregates on addition of CNTs. The CNT-Chol(+) suspensions were capable of forming stable complexes with genes (DNA) efficiently. The release of double-helical DNA from such CNT-Chol(+) complexes could be induced upon the addition of anionic micellar solution of SDS. Furthermore, the CNT-based DNA complexes containing cationic cholesterol aggregates showed higher stability in fetal bovine serum media at physiological conditions. Confocal studies confirm that CNT-Chol(+) formulations adhere to HeLa cell surfaces and get internalized more efficiently than the cationic cholesterol suspensions alone (devoid of any CNTs). These cationic cholesterol-CNT suspensions therefore appear to be a promising system for further use in biological applications.

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The study focuses on probabilistic assessment of the internal seismic stability of reinforced soil structures (RSS) subjected to earthquake loading in the framework of the pseudo-dynamic method. In the literature, the pseudo-static approach has been used to compute reliability indices against the tension and pullout failure modes, and the real dynamic nature of earthquake accelerations cannot be considered. The work presented in this paper makes use of the horizontal and vertical sinusoidal accelerations, amplification of vibrations, shear wave and primary wave velocities and time period. This approach is applied to quantify the influence of the backfill properties, geosynthetic reinforcement and characteristics of earthquake ground motions on reliability indices in relation to the tension and pullout failure modes. Seismic reliability indices at different levels of geosynthetic layers are determined for different magnitudes of seismic acceleration, soil amplification, shear wave and primary wave velocities. The results are compared with the pseudo-static method, and the significance of the present methodology for designing reinforced soil structures is discussed.

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For the analysis and design of pile foundation used for coastal structures the prediction of cyclic response, which is influenced by the nonlinear behavior, gap (pile soil separation) and degradation (reduction in strength) of soil becomes necessary. To study the effect of the above parameters a nonlinear cyclic load analysis program using finite element method is developed, incorporating the proposed gap and degradation model and adopting an incremental-iterative procedure. The pile is idealized using beam elements and the soil by number of elastoplastic sub-element springs at each node. The effect of gap and degradation on the load-deflection behavior. elasto-plastic sub-element and resistance of the soil at ground-line have been clearly depicted in this paper.

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Nonlinear analysis of batter piles in soft clay is performed using the finite element technique. As the batter piles are not only governed by lateral load but also axial load, the effect of P- Delta moment and geometric stiffness matrix is included in the analysis. For implementing the nonlinear soil behavior, reduction in soil strength (degradation), and formation of gap with number of load cycles, a numerical model is developed where a hyperbolic relation is adopted for the soil in static condition and hyperbolic relation considering degradation and gap for cyclic load condition. The numerical model is validated with published experimental results for cyclic lateral loading and the hysteresis loops are developed to predict the load-deflection behavior and soil resistance behavior during consecutive cycles of loading. This paper highlights the importance of a rigorous degradation model for subsequent cycles of loading on the pile-soil system by a hysteretic representation.

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The stability of slopes is a major problem in geotechnical engineering. Of the methods available for the analysis of soil slopes such as limit equilibrium methods, limit analysis and numerical methods such as FEM and FDM, limit equilibrium methods are popular and generally used, owing to their simplicity in formulation and in evaluating the overall factor of safety of slope. However limit equilibrium methods possess certain disadvantages. They do not consider whether the slope is an embankment or natural slope or an excavation and ignore the effect of incremental construction, initial stress, stress strain behavior etc. In the work reported in this paper, a comparative study of actual state of stress and actual factor of safety and Bishop's factor of safety is performed. The actual factor of safety is obtained by consideration of contours of mobilised shear strains. Using Bishop's method of slices, the critical slip surfaces of a number of soil slopes with different geometries are determined and both the factors of safety are obtained. The actual normal stresses and shear stresses are determined from finite difference formulation using FLAG (Fast Lagrangian Analysis of Continuaa) with Mohr-Coulomb model. The comparative study is performed in terms of parameter lambda(c phi) (= gamma H tan phi/c). I is shown that actual factor of safety is higher than Bishop's factor of safety depending on slope angle and lambda(c phi).

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Stability analysis of residual soil slopes are now increasingly being performed with the incorporation of the matric suction component of strength. The matric suction (u(a)-u(w)) component of shear strength is known as apparent cohesion. The relation between matric suction and apparent cohesion (c(app)) may be linear or non-linear. The impact of type of apparent strength versus matric suction relationship on the stability of an unsaturated residual soil slope is examined in this study. Results of the study showed that the factor of safety values were unaffected by the nature of the strength versus matric suction relationship for the residual soil slope examined. This was so as contribution from the effective stress- strength component to the factor of safety predominated over the contribution made by the apparent strength component.

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Most HIV-1 broadly neutralizing antibodies are directed against the gp120 subunit of the env surface protein. Native env consists of a trimer of gp120-gp41 heterodimers, and in contrast to monomeric gp120, preferentially binds CD4 binding site (CD4bs)-directed neutralizing antibodies over non-neutralizing ones. Some cryo-electron tomography studies have suggested that the V1V2 loop regions of gp120 are located close to the trimer interface. We have therefore designed cyclically permuted variants of gp120 with and without the h-CMP and SUMO2a trimerization domains inserted into the V1V2 loop. h-CMP-V1cyc is one such variant in which residues 153 and 142 are the N- and C-terminal residues, respectively, of cyclically permuted gp120 and h-CMP is fused to the N-terminus. This molecule forms a trimer under native conditions and binds CD4 and the neutralizing CD4bs antibodies b12 with significantly higher affinity than wild-type gp120. It binds non-neutralizing CD4bs antibody F105 with lower affinity than gp120. A similar derivative, h-CMP-V1cycl, bound the V1V2 loop-directed broadly neutralizing antibodies PG9 and PG16 with similar to 20-fold higher affinity than wild-type JRCSF gp120. These cyclic permutants of gp120 are properly folded and are potential immunogens. The data also support env models in which the V1V2 loops are proximal to the trimer interface.

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Designing a heat sink based on a phase change material (PCM) under cyclic loading is a critical issue. For cyclic operation, it is required that the fraction of the PCM melting during the heating cycle should completely resolidify during the cooling period, so that that thermal storage unit can be operated for an unlimited number of cycles. Accordingly, studies are carried out to find the parameters influencing the behavior of a PCM under cyclic loading. A number of parameters are identified in the process, the most important ones being the duty cycle and heat transfer coefficient (h) for cooling. The required h or the required cooling period for complete resolidification for infinite cyclic operation of a conventional PCM-based heat sink is found to be very high and unrealistic with air cooling from the surface. To overcome this problem, the conventional design is modified where h and the area exposed to heat transfer can be independently controlled. With this arrangement, the enhanced area provided for cooling keeps h within realistic limits. Analytical investigation is carried out to evaluate the thermal performance of this modified PCM-based heat sink in comparison to those with conventional designs. Experiments are also performed on both the conventional and the modified PCM-based heat sinks to validate the new findings.

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A numerically stable sequential Primal–Dual LP algorithm for the reactive power optimisation (RPO) is presented in this article. The algorithm minimises the voltage stability index C 2 [1] of all the load buses to improve the system static voltage stability. Real time requirements such as numerical stability, identification of the most effective subset of controllers for curtailing the number of controllers and their movement can be handled effectively by the proposed algorithm. The algorithm has a natural characteristic of selecting the most effective subset of controllers (and hence curtailing insignificant controllers) for improving the objective. Comparison with transmission loss minimisation objective indicates that the most effective subset of controllers and their solution identified by the static voltage stability improvement objective is not the same as that of the transmission loss minimisation objective. The proposed algorithm is suitable for real time application for the improvement of the system static voltage stability.

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This paper presents a methodology for selection of static VAR compensator location based on static voltage stability analysis of power systems. The analysis presented here uses the L-index of load buses, which includes voltage stability information of a normal load flow and is in the range of 0 (no load of system) to 1 (voltage collapse). An approach has been presented to select a suitable size and location of static VAR compensator in an EHV network for system voltage stability improvement. The proposed approach has been tested under simulated conditions on a few power systems and the results for a sample radial network and a 24-node equivalent EHV power network of a practical system are presented for illustration purposes. © 2000 Published by Elsevier Science S.A. All rights reserved.

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Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.

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Considering voltage stability as a static viability problem, this paper takes a particular concern of Q-V characteristics and reflects on certain notions that do not seem to have been explicitly mentioned or derived in the existing documented literature. The equations of Q-V characteristics are rederived in exactness, some salient points on the curve are discovered and analysed. The results of the analysis are illustrated through a case study

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As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

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This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices