A quasi-steady performance prediction model for dynamic characteristics of a volute pump

A performance prediction model generally applicable for volute-type centrifugal pumps has been extended to predict the dynamic characteristics of a pump during its normal starting and stopping periods. Experiments have been conducted on a volute pump with different valve openings to study the dynamic behaviour of the pump during normal start-up and stopping, when a small length of discharge pipeline is connected to the discharge flange of the pump. Such experiments have also been conducted when the test pump was part of a hydraulic system, an experimental rig, where it is pumping against three similar pumps, known as supply pumps, connected in series, with the supply pumps kept idle or running. Instantaneous rotational speed, flowrate, and delivery and suction pressures of the pump were recorded and it was observed in all the tested cases that the change of pump behaviour during the transient period was quasi-steady, which validates the quasi-steady approach presented in this paper. The nature of variation of parameters during the transients has been discussed. The model-predicted dynamic head-capacity curves agree well with the experimental data for almost all the tested cases.

On-line Dynamic Security Assessment: Determination of Critical Transmission Lines

The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.

Characterisation of dynamic recrystallisation in nickel using processing map for hot deformation

The hot deformation behaviour of polycrystalline nickel has been characterised in the temperature range 750-1200-degrees-C and strain rate range 0.0003-100 s-1 using processing maps developed in the basis of the dynamic materials model. The efficiency of power dissipation, given by [2m/(m + 1)]. where m is the strain rate sensitivity, is plotted as a function of temperature and strain rate to obtain a processing map. A domain of dynamic recrystallisation has been identified, with a peak efficiency of 31% occurring at 925-degrees-C and 1 s-1. The published results are in agreement with the prediction of the processing map. The variations of efficiency of power dissipation with temperature and strain rate in the dynamic recrystallisation domain are identical to the corresponding variation of hot ductility. The stress-strain curves exhibited a single peak in a single peak in the dynamic recrystallisation domain, whereas multiple peaks and 'drooping' stress-strain curves were observed at lower and higher strain rates, respectively. The results are explained on the basis of a simple model which considers dynamic recrystallisation in terms of rates of interface formation (nucleation) and migration (growth). It is shown that dynamic recrystallisation in nickel is controlled by the rate of nucleation, which is slower than the rate of migration. The rate of nucleation itself depends on the process of thermal recovery by climb, which in turn depends on self-diffusion.

Criteria for prediction of flow instabilities and microstructural manifestations during warm working of AISI 304L stainless steel

The deformation characteristics of 304L stainless steel in compression in the temperature range 20–700°C and strain rate range 0·001–100 s−1 have been studied with the aim of characterising the .flow instabilities occurring in the microstructure. At higher temperatures and strain rates the stainless steel exhibits flow localisation, whereas at temperatures below 500°C and strain rates lower than 0·1 s−1 the flow instabilities are due to dynamic strain aging. Strain induced martensite formation is responsible for the flow instabilities at room temperature and low strain rates (0·01 s−1). In view of the occurrence of these instabilities, cold working is preferable to warm working to achieve dimensional tolerance and reproducible properties in the product. Among the different criteria tested to explain the occurrence of instabilities, the continuum criterion, developed on the basis of the principles of maximum rate of entropy production and separability of the dissipation function, predicts accurately all the above instability features.

Effects of phase inhomogeneity and boundary conditions on the dynamic response of SMA wire actuators

This paper reports the simulation results from the dynamic analysis of a Shape Memory Alloy (SMA) actuator. The emphasis is on understanding the dynamic behavior under various loading rates and boundary conditions, resulting in complex scenarios such as thermal and stress gradients. Also, due to the polycrystalline nature of SMA wires, presence of microstructural inhomogeneity is inevitable. Probing the effect of inhomogeneity on the dynamic behavior can facilitate the prediction of life and characteristics of SMA wire actuator under varieties of boundary and loading conditions. To study the effect of these factors, an initial boundary value problem of SMA wire is formulated. This is subsequently solved using finite element method. The dynamic response of the SMA wire actuator is analyzed under mechanical loading and results are reported. Effect of loading rate, micro-structural inhomogeneity and thermal boundary conditions on the dynamic response of SMA wire actuator is investigated and the simulation results are reported.

Fuzzy inference based data preprocessing for VBR video traffic prediction

Prediction of variable bit rate compressed video traffic is critical to dynamic allocation of resources in a network. In this paper, we propose a technique for preprocessing the dataset used for training a video traffic predictor. The technique involves identifying the noisy instances in the data using a fuzzy inference system. We focus on three prediction techniques, namely, linear regression, neural network and support vector regression and analyze their performance on H.264 video traces. Our experimental results reveal that data preprocessing greatly improves the performance of linear regression and neural network, but is not effective on support vector regression.

Position control of DC motors with experience mapping based prediction controller

The paper presents a new controller inspired by the human experience based, voluntary body action control (dubbed motor control) learning mechanism. The controller is called Experience Mapping based Prediction Controller (EMPC). EMPC is designed with auto-learning features without the need for the plant model. The core of the controller is formed around the motor action prediction-control mechanism of humans based on past experiential learning with the ability to adapt to environmental changes intelligently. EMPC is utilized for high precision position control of DC motors. The simulation results are presented to show that accurate position control is achieved using EMPC for step and dynamic demands. The performance of EMPC is compared with conventional PD controller and MRAC based position controller under different system conditions. Position Control using EMPC is practically implemented and the results are presented.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

CFD Analysis of two phase flow with a prediction of torque demand of a Bi-lobe rotor of a mixing chamber

An attempt to study the fluid dynamic behavior of two phase flow comprising of solid and liquid with nearly equal density in a geometrical case that has an industrial significance in theareas like processing of polymers, food, pharma ceutical, paints. In this work,crystalline silica is considered as the dispersed medium in glycerin. In the CFD analysis carried out,the two phase components are considered to be premixed homogeneously at the initial state. The flow in a cylinder that has an axially driven bi-lobe rotor, a typical blender used in polymer industry for mixing or kneading to render the multi-component mixture to homogeneous condition is considered. A viscous, incompressible, isothermal flow is considered with an assumption that the components do not undergo any physical change and the solids are rigid and mix in fully wetting conditions. Silica with a particle diameter of 0.4 mm is considered and flow is analyzed for different mixing fractions. An industry standard CFD code is used for solving 3D-RANS equations. As the outcome of the study the torque demand by the bi-lobe rotor for different mixture fractions which are estimated show a behavioral consistency to the expected physical phenomena occurring in the domain considered.

Threshold-Independent QRS Detection Using the Dynamic Plosion Index

Detection of QRS serves as a first step in many automated ECG analysis techniques. Motivated by the strong similarities between the signal structures of an ECG signal and the integrated linear prediction residual (ILPR) of voiced speech, an algorithm proposed earlier for epoch detection from ILPR is extended to the problem of QRS detection. The ECG signal is pre-processed by high-pass filtering to remove the baseline wandering and by half-wave rectification to reduce the ambiguities. The initial estimates of the QRS are iteratively obtained using a non-linear temporal feature, named the dynamic plosion index suitable for detection of transients in a signal. These estimates are further refined to obtain a higher temporal accuracy. Unlike most of the high performance algorithms, this technique does not make use of any threshold or differencing operation. The proposed algorithm is validated on the MIT-BIH database using the standard metrics and its performance is found to be comparable to the state-of-the-art algorithms, despite its threshold independence and simple decision logic.

Experimental and theoretical studies on static and dynamic pressure-concentration isotherms of MmNi(5-x)Al(x) (x=0, 0.3, 0.5 and 0.8) hydrides

The static and dynamic pressure concentration isotherms (PCIs) of MmNi(5-x)Al(x). (x = 0, 0.3, 0.5 and 0.8) hydrides were measured at different temperatures using volumetric method. The effect of Al substitution on PCI and thermodynamic properties were studied. The plateau pressure and maximum hydrogen storage capacity decreased with Al content whereas reaction enthalpy increased. The plateau pressure, plateau slope and hysteresis effect was observed more for dynamic PCIs compared to static PCIs. Different mathematical models used for metal hydride-based thermodynamic devices simulation are compared to select suitable model for static and dynamic PCI simulation of MmNi(5)-based hydrides. Few important physical coefficients (partial molar volume, reaction enthalpy, reaction entropy, etc.) useful for development of thermodynamic devices were estimated. A relation has been proposed to correlate aluminium content and physical coefficients for the prediction of unknown PCI. The simulated and experimental PCIs were found matching closely for both static and dynamic conditions. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Performance of New Dynamic Benefit-Weighted Scheduling Scheme in DiffServ Networks

In this paper, we design a new dynamic packet scheduling scheme suitable for differentiated service (DiffServ) network. Designed dynamic benefit weighted scheduling (DBWS) uses a dynamic weighted computation scheme loosely based on weighted round robin (WRR) policy. It predicts the weight required by expedited forwarding (EF) service for the current time slot (t) based on two criteria; (i) previous weight allocated to it at time (t-1), and (ii) the average increase in the queue length of EF buffer. This prediction provides smooth bandwidth allocation to all the services by avoiding overbooking of resources for EF service and still providing guaranteed services for it. The performance is analyzed for various scenarios at high, medium and low traffic conditions. The results show that packet loss is minimized, end to end delay is minimized and jitter is reduced and therefore meet quality of service (QoS) requirement of a network.

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.