Plane wave analysis of rectangular axial-inlet, axial-outlet and transverse-inlet, transverse-outlet air cleaners

In this work, one-dimensional flow-acoustic analysis of two basic configurations of air cleaners, (i) Rectangular Axial-Inlet, Axial-Outlet (RAIAO) and (ii) Rectangular Transverse-Inlet, Transverse-Outlet (RTITO), has been presented. This 1-D analytical approach has been verified with the help of 3-D FEM based software. Through subtraction of the acoustic performance of the bare plenum (without filter element) from that of the complete air cleaner box, the solitary performance of the filter element has been evaluated. Part of the present analysis illustrates that the analytical formulation remains effective even with offset positioning of the air pipes from the centre of the cross section of the air cleaner. The 1-D analytical tool computes much faster than its 3-D simulation counterpart. The present analysis not only predicts the acoustical impact of mean flow, but it also depicts the scenario with increased resistance of the filter element. Thus, the proposed 1-D analysis would help in the design of acoustically efficient air cleaners for automotive applications. (C) 2011 Institute of Noise Control Engineering.

Robust Fixed Order Lateral H2 Controller for Micro Air Vehicle

This paper presents a robust fixed order H2controller design using strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H2controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation

Modeling urban traffic planning thro' strategic decisions- A case from Bangalore, India

This paper deals with reducing the waiting times of vehicles at the traffic junctions by synchronizing the traffic signals. Strategies are suggested for betterment of the situation at different time intervals of the day, thus ensuring smooth flow of traffic. The concept of single way systems are also analyzed. The situation is simulated in Witness 2003 Simulation package using various conventions. The average waiting times are reduced by providing an optimal combination for the traffic signal timer. Different signal times are provided for different times of the day, thereby further reducing the average waiting times at specific junctions/roads according to the experienced demands.

Reinforcement learning with average cost for adaptive control of traffic lights at intersections

We propose for the first time two reinforcement learning algorithms with function approximation for average cost adaptive control of traffic lights. One of these algorithms is a version of Q-learning with function approximation while the other is a policy gradient actor-critic algorithm that incorporates multi-timescale stochastic approximation. We show performance comparisons on various network settings of these algorithms with a range of fixed timing algorithms, as well as a Q-learning algorithm with full state representation that we also implement. We observe that whereas (as expected) on a two-junction corridor, the full state representation algorithm shows the best results, this algorithm is not implementable on larger road networks. The algorithm PG-AC-TLC that we propose is seen to show the best overall performance.

Tribology of ethylene-air diffusion flame soot under dry and lubricated contact conditions

Soot particles are generated in a flame caused by burning ethylene gas. The particles are collected thermophoretically at different locations of the flame. The particles are used to lubricate a steel/steel ball on flat reciprocating sliding contact, as a dry solid lubricant and also as suspended in hexadecane. Reciprocating contact is shown to establish a protective and low friction tribo-film. The friction correlates with the level of graphitic order of the soot, which is highest in the soot extracted from the mid-flame region and is low in the soot extracted from the flame root and flame tip regions. Micro-Raman spectroscopy of the tribo-film shows that the a priori graphitic order, the molecular carbon content of the soot and the graphitization of the film as brought about by tribology distinguish between the frictions of soot extracted from different regions of the flame, and differentiate the friction associated with dry tribology from that recorded under lubricated tribology.

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.

Impact-Angle-Constrained Suboptimal Model Predictive Static Programming Guidance of Air-to-Ground Missiles

A nonlinear suboptimal guidance law is presented in this paper for successful interception of ground targets by air-launched missiles and guided munitions. The main feature of this guidance law is that it accurately satisfies terminal impact angle constraints in both azimuth as well as elevation simultaneously. In addition, it is capable of hitting the target with high accuracy as well as minimizing the lateral acceleration demand. The guidance law is synthesized using recently developed model predictive static programming (MPSP). Performance of the proposed MPSP guidance is demonstrated using three-dimensional (3-D) nonlinear engagement dynamics by considering stationary, moving, and maneuvering targets. Effectiveness of the proposed guidance has also been verified by considering first. order autopilot lag as well as assuming inaccurate information about target maneuvers. Multiple munitions engagement results are presented as well. Moreover, comparison studies with respect to an augmented proportional navigation guidance (which does not impose impact angle constraints) as well as an explicit linear optimal guidance (which imposes the same impact angle constraints in 3-D) lead to the conclusion that the proposed MPSP guidance is superior to both. A large number of randomized simulation studies show that it also has a larger capture region.

Air Pollution Control

The air we breathe is being polluted by activities such as vehicles; burning coal, oil, and other fossil fuels; and manufacturing chemicals. Air pollution can even come from smaller, everyday activities such as cooking, space heating, and degreasing and painting operations. These activities add gases and particles to the air we breathe. When these gases and particles accumulate in the air in high enough concentrations, they can harm us and our environment. The module on Air Pollution deals with the various sources of air pollution and the associated environmental and health impacts. It also discusses the appropriate measures to control/prevent the same.

Dry tribology and nanomechanics of gaseous flame soot in comparison with carbon black and diesel soot

Ethylene gas is burnt and the carbon soot particles are thermophoretically collected using a home-built equipment where the fuel air injection and intervention into the 7.5-cm long flame are controlled using three small pneumatic cylinders and computer-driven controllers. The physical and mechanical properties and tribological performance of the collected soot are compared with those of carbon black and diesel soot. The crystalline structures of the nanometric particles generated in the flame, as revealed by high-resolution transmission electron studies, are shown to vary from the flame root to the exhaust. As the particle journeys upwards the flame, through a purely amorphous coagulated phase at the burner nozzle, it leads to a well-defined crystalline phase shell in the mid-flame zone and to a disordered phase consisting of randomly distributed short-range crystalline order at the exhaust. In the mid-flame region, a large shell of radial-columnar order surrounds a dense amorphous core. The hardness and wear resistance as well as friction coefficient of the soot extracted from this zone are low. The mechanical properties characteristics of this zone may be attributed to microcrystalline slip. Moving towards the exhaust, the slip is inhibited and there is an increase in hardness and friction compared to those in the mid-flame zone. This study of the comparison of flame soot to carbon black and diesel soot is further extended to suggest a rationale based on additional physico-chemical study using micro-Raman spectroscopy.

Traffic Profiling for Efficient Network Resource Utilization.

Traffic Engineering has been the prime concern for Internet Service Providers (ISPs), with the main focus being minimization of over-utilization of network capacity even though additional capacity is available which is under-utilized, Furthermore, requirements of timely delivery of digitized audiovisual information raises a new challenge of finding a path meeting these requirements. This paper addresses the issue of (a) distributing load to achieve global efficiency in resource utilization. (b) Finding a path satisfying the real time requirements of, delay and bandwidth requested by the applications. In this paper we do a critical study of the link utilization that varies over time and determine the time interval during which the link occupancy remains constant across days. This information helps in pre-determining link utilization that is useful in balancing load in the network Finally, we run simulations that use a dynamic time interval for profiling traffic and show improvement in terms number of calls admitted/blocked.

Tar characterisation in new generation agro-residue gasifiers - Cyclone and downdraft open top twin air entry systems

This paper deals with the characterisation of tar from two configurations of bioresidue thermochemical conversion reactors designed for producer gas based power generation systems. The pulverised fuel reactor is a cyclone system (R1) and the solid bioresidue reactor (denoted R2) is an open top twin air entry system both at 75-90 kg/h capacity (to generate electricity similar to 100 kVA). The reactor, R2, has undergone rigorous test in a major Indo-Swiss programme for the tar quantity at various conditions. The former is a recent technology development. Tars collected from these systems by a standard tar collection apparatus at the laboratory at Indian Institute of Science have been analysed at the Royal Institute of Technology (KTH), Sweden. The results of these analyses show that these thermochemical conversion reactors behave differently from the earlier reactors reported in literature in so far as tar generation is concerned. The extent of tar in hot gas is about 700-800 ppm for R1 and 70-100 ppm for R2. The amounts of the major compounds - naphthalene and phenol-are much lower that what is generally understood to happen in the gasifiers in Europe. It is suggested that the longer residence times at high temperatures allowed for in these reactors is responsible for this behavior. It is concluded the new generation reactor concepts extensively tried out at lower power levels hold promise for high power atmospheric gasification systems for woody as well as pulverisable bioresidues.

Performance of cellular CDMA with voice/data traffic with an SIR based admission control

We analyze the performance of an SIR based admission control strategy in cellular CDMA systems with both voice and data traffic. Most studies In the current literature to estimate CDMA system capacity with both voice and data traf-Bc do not take signal-tlFlnterference ratio (SIR) based admission control into account In this paper, we present an analytical approach to evaluate the outage probability for voice trafllc, the average system throughput and the mean delay for data traffic for a volce/data CDMA system which employs an SIR based admission controL We show that for a dataaniy system, an improvement of about 25% In both the Erlang capacity as well as the mean delay performance is achieved with an SIR based admission control as compared to code availability based admission control. For a mixed voice/data srtem with 10 Erlangs of voice traffic, the Lmprovement in the mean delay performance for data Is about 40%.Ah, for a mean delay of 50 ms with 10 Erlangs voice traffic, the data Erlang capacity improves by about 9%.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.