Analysis, Design, Modeling, and Implementation of an Active Clamp HF Link Converter

This paper deals with the system oriented analysis, design, modeling, and implementation of active clamp HF link three phase converter. The main advantage of the topology is reduced size, weight, and cost of the isolation transformer. However, violation of basic power conversion rules due to presence of the leakage inductance in the HF transformer causes over voltage stresses across the cycloconverter devices. It makes use of the snubber circuit necessary in such topologies. The conventional RCD snubbers are dissipative in nature and hence inefficient. The efficiency of the system is greatly improved by using regenerative snubber or active clamp circuit. It consists of an active switching device with an anti-parallel diode and one capacitor to absorb the energy stored in the leakage inductance of the isolation transformer and to regenerate the same without affecting circuit performance. The turn on instant and duration of the active device are selected such that it requires simple commutation requirements. The time domain expressions for circuit dynamics, design criteria of the snubber capacitor with two conflicting constrains (over voltage stress across the devices and the resonating current duration), the simulation results based on generalized circuit model and the experimental results based on laboratory prototype are presented.

End-bearing capacity of driven piles in sand using the stress characteristics method: analysis and implementation

The method of stress characteristics has been employed to compute the end-bearing capacity of driven piles. The dependency of the soil internal friction angle on the stress level has been incorporated to achieve more realistic predictions for the end-bearing capacity of piles. The validity of the assumption of the superposition principle while using the bearing capacity equation based on soil plasticity concepts, when applied to deep foundations, has been examined. Fourteen pile case histories were compiled with cone penetration tests (CPT) performed in the vicinity of different pile locations. The end-bearing capacity of the piles was computed using different methods, namely, static analysis, effective stress approach, direct CPT, and the proposed approach. The comparison between predictions made by different methods and measured records shows that the stress-level-based method of stress characteristics compares better with experimental data. Finally, the end-bearing capacity of driven piles in sand was expressed in terms of a general expression with the addition of a new factor that accounts for different factors contributing to the bearing capacity. The influence of the soil nonassociative flow rule has also been included to achieve more realistic results.

Space vector based bus clamped PWM algorithms for three level inverters: implementation, performance analysis and application considerations

This paper describes the different types of space vector based bus clamped PWM algorithms for three level inverters. A novel bus clamp PWM algorithm for low modulation indices region is also presented. The principles and switching sequences of all the types of bus clamped algorithms for high switching frequency are presented. Synchronized version of the PWM sequences for high power applications where switching frequency is low is also presented. The implementation details on DSP based digital controller and experimental results are presented. The THD of the output waveforms is studied for the entire operating region and is compared with the conventional space vector PWM technique. The bus clamped techniques can be used to reduce the switching losses or to improve the output voltage quality or both.. Different issues dominate depending on the type of application and power rating of the inverters. The results presented in this paper can be used for judicious use of the PWM techniques, which result in improved system efficiency and performance.

Linearization of Drucker-Prager yield criterion for axisymmetric problems: implementation in lower-bound limit analysis

The linearization of the Drucker-Prager yield criterion associated with an axisymmetric problem has been achieved by simulating a sphere with the truncated icosahedron with 32 faces and 60 vertices. On this basis, a numerical formulation has been proposed for solving an axisymmetric stability problem with the usage of the lower-bound limit analysis, finite elements, and linear optimization. To compare the results, the linearization of the Mohr-Coulomb yield criterion, by replacing the three cones with interior polyhedron, as proposed earlier by Pastor and Turgeman for an axisymmetric problem, has also been implemented. The two formulations have been applied for determining the collapse loads for a circular footing resting on a cohesive-friction material with nonzero unit weight. The computational results are found to be quite convincing. (C) 2013 American Society of Civil Engineers.

Energy-momentum conserving algorithm for nonlinear transient analysis within the framework of hybrid elements

This work deals with the formulation and implementation of an energy-momentum conserving algorithm for conducting the nonlinear transient analysis of structures, within the framework of stress-based hybrid elements. Hybrid elements, which are based on a two-field variational formulation, are much less susceptible to locking than conventional displacement-based elements within the static framework. We show that this advantage carries over to the transient case, so that not only are the solutions obtained more accurate, but they are obtained in fewer iterations. We demonstrate the efficacy of the algorithm on a wide range of problems such as ones involving dynamic buckling, complicated three-dimensional motions, et cetera.

An innovative clustering technique for unsupervized learning in the context of remotely sensed earth resources data analysis

A new clustering technique, based on the concept of immediato neighbourhood, with a novel capability to self-learn the number of clusters expected in the unsupervized environment, has been developed. The method compares favourably with other clustering schemes based on distance measures, both in terms of conceptual innovations and computational economy. Test implementation of the scheme using C-l flight line training sample data in a simulated unsupervized mode has brought out the efficacy of the technique. The technique can easily be implemented as a front end to established pattern classification systems with supervized learning capabilities to derive unified learning systems capable of operating in both supervized and unsupervized environments. This makes the technique an attractive proposition in the context of remotely sensed earth resources data analysis wherein it is essential to have such a unified learning system capability.

Spectral analysis of noise in the neonatal intensive care unit

Objective To perform spectral analysis of noise generated by equipments and activities in a level III neonatal intensive care unit (NICU) and measure the real time sequential hourly noise levels over a 15 day period. Methods Noise generated in the NICU by individual equipments and activities were recorded with a digital spectral sound analyzer to perform spectral analysis over 0.5–8 KHz. Sequential hourly noise level measurements in all the rooms of the NICU were done for 15 days using a digital sound pressure level meter. Independent sample t test and one way ANOVA were used to examine the statistical significance of the results. The study has a 90% power to detect at least 4 dB differences from the recommended maximum of 50 dB with 95 % confidence. Results The mean noise levels in the ventilator room and stable room were 19.99 dB (A) sound pressure level (SPL) and 11.81 dB (A) SPL higher than the maximum recommended of 50 dB (A) respectively (p < 0.001). The equipments generated 19.11 dB SPL higher than the recommended norms in 1–8 KHz spectrum. The activities generated 21.49 dB SPL higher than the recommended norms in 1–8 KHz spectrum (p< 0.001). The ventilator and nebulisers produced excess noise of 8.5 dB SPL at the 0.5 KHz spectrum.Conclusion Noise level in the NICU is unacceptably high. Spectral analysis of equipment and activity noise have shown noise predominantly in the 1–8 KHz spectrum. These levels warrant immediate implementation of noise reduction protocols as a standard of care in the NICU.

A new approach for fault location identification in transmission system using stability analysis and SVMs

This paper presents a new approach to the location of fault in the high voltage power transmission system using Support Vector Machines (SVMs). A knowledge base is developed using transient stability studies for apparent impedance swing trajectory in the R-X plane. SVM technique is applied to identify the fault location in the system. Results are presented on sample 3-power station, a 9-bus system illustrate the implementation of the proposed method.

Design and analysis of rate aware ad hoc 802.11 networks

802.11 WLANs are characterized by high bit error rate and frequent changes in network topology. The key feature that distinguishes WLANs from wired networks is the multi-rate transmission capability, which helps to accommodate a wide range of channel conditions. This has a significant impact on higher layers such as routing and transport levels. While many WLAN products provide rate control at the hardware level to adapt to the channel conditions, some chipsets like Atheros do not have support for automatic rate control. We first present a design and implementation of an FER-based automatic rate control state machine, which utilizes the statistics available at the device driver to find the optimal rate. The results show that the proposed rate switching mechanism adapts quite fast to the channel conditions. The hop count metric used by current routing protocols has proven itself for single rate networks. But it fails to take into account other important factors in a multi-rate network environment. We propose transmission time as a better path quality metric to guide routing decisions. It incorporates the effects of contention for the channel, the air time to send the data and the asymmetry of links. In this paper, we present a new design for a multi-rate mechanism as well as a new routing metric that is responsive to the rate. We address the issues involved in using transmission time as a metric and presents a comparison of the performance of different metrics for dynamic routing.

Document page layout analysis using Harris corner points

Extraction of text areas from the document images with complex content and layout is one of the challenging tasks. Few texture based techniques have already been proposed for extraction of such text blocks. Most of such techniques are greedy for computation time and hence are far from being realizable for real time implementation. In this work, we propose a modification to two of the existing texture based techniques to reduce the computation. This is accomplished with Harris corner detectors. The efficiency of these two textures based algorithms, one based on Gabor filters and other on log-polar wavelet signature, are compared. A combination of Gabor feature based texture classification performed on a smaller set of Harris corner detected points is observed to deliver the accuracy and efficiency.

Macro-economic analysis of forestry options on carbon sequestration in India

The forestry sector provides a number of climate change mitigation options. Apart from this ecological benefit, it has significant social and economic relevance. Implementation of forestry options requires large investments and sustained long-term planning. Thus there is a need for a detailed analysis of forestry options to understand their implications on stock and flow of carbon, required investments, value of forest wealth, contribution to GNP and livelihood, demand management, employment and foreign trade. There is a need to evaluate the additional spending on forestry by analysing the environmental (particularly carbon abatement), social and economic benefits. The biomass needs for India are expected to increase by two to three times by 2020. Depending upon the forest types, ownership patterns and land use patterns, feasible forestry options are identified. It is found among many supply options to be feasible to meet the 'demand based needs' with a mix of management options, species choices and organisational set up. A comparative static framework is used to analyze the macro-economic impacts. Forestry accounts for 1.84% of GNP in India. It is characterized by significant forward industrial linkages and least backward linkage. Forestry generates about 36 million person years of employment annually. India imports Rs. 15 billion worth of forest based materials annually. Implementation of the demand based forestry options can lead to a number of ecological, economic and institutional changes. The notable ones are: enhancement of C stock from 9578 to 17 094 Mt and a net annual C-sequestration from 73 to 149 Mt after accounting for all emissions; a trebling of the output of forestry sector from Rs. 49 billion to Rs. 146 billion annually; an increase in GDP contribution of forestry from Rs. 32 billion to Rs. 105 billion over a period of 35 years; an increase in annual employment level by 23 million person years, emergence of forestry as a net contributor of foreign exchange through trading of forestry products; and an increase in economic value of forest capital stock by Rs. 7260 billion with a cost benefit analysis showing forestry as a profitable option. Implementation of forestry options calls for an understanding of current forest policies and barriers which are analyzed and a number of policy options are suggested. (C) 1997 Elsevier Science B.V.

Scalable Context-Sensitive Points-To Analysis Using Multi-Dimensional Bloom Filters

Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the analysis increase tremendously for large programs, making the analysis non-scalable. We propose a scalable flow-insensitive context-sensitive inclusion-based points-to analysis that uses a specially designed multi-dimensional bloom filter to store the points-to information. Two key observations motivate our proposal: (i) points-to information (between pointer-object and between pointer-pointer) is sparse, and (ii) moving from an exact to an approximate representation of points-to information only leads to reduced precision without affecting correctness of the (may-points-to) analysis. By using an approximate representation a multi-dimensional bloom filter can significantly reduce the memory requirements with a probabilistic bound on loss in precision. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that with an average storage requirement of 4MB, our approach achieves almost the same precision (98.6%) as the exact implementation. By increasing the average memory to 27MB, it achieves precision upto 99.7% for these benchmarks. Using Mod/Ref analysis as the client, we find that the client analysis is not affected that often even when there is some loss of precision in the points-to representation. We find that the NoModRef percentage is within 2% of the exact analysis while requiring 4MB (maximum 15MB) memory and less than 4 minutes on average for the points-to analysis. Another major advantage of our technique is that it allows to trade off precision for memory usage of the analysis.

Application of the random eigenvalue problem in forced response analysis of a linear stochastic structure

The random eigenvalue problem arises in frequency and mode shape determination for a linear system with uncertainties in structural properties. Among several methods of characterizing this random eigenvalue problem, one computationally fast method that gives good accuracy is a weak formulation using polynomial chaos expansion (PCE). In this method, the eigenvalues and eigenvectors are expanded in PCE, and the residual is minimized by a Galerkin projection. The goals of the current work are (i) to implement this PCE-characterized random eigenvalue problem in the dynamic response calculation under random loading and (ii) to explore the computational advantages and challenges. In the proposed method, the response quantities are also expressed in PCE followed by a Galerkin projection. A numerical comparison with a perturbation method and the Monte Carlo simulation shows that when the loading has a random amplitude but deterministic frequency content, the proposed method gives more accurate results than a first-order perturbation method and a comparable accuracy as the Monte Carlo simulation in a lower computational time. However, as the frequency content of the loading becomes random, or for general random process loadings, the method loses its accuracy and computational efficiency. Issues in implementation, limitations, and further challenges are also addressed.