Performance evaluation of an integrated solar water heater as an option for building energy conservation

Since a majority of residential and industrial building hot water needs are around 50 degrees C, an integrated solar water heater could provide a bulk source that blends collection and storage into one unit. This paper describes the design, construction and performance test results of one such water-heating device. The test unit has an absorber area of 1.3 m(2) and can hold 1701 of water, of which extractable volume per day is 1001. Its performance was evaluated under various typical operating conditions. Every morning at about 7:00 a.m., 1001 of hot water were drawn from the sump and replaced with cold water from the mains. Although, during most of the days, the peak temperatures of water obtained are between 50 and 60 degrees C, the next morning temperatures were lower at 45-50 degrees C. Daytime collection efficiencies of about 60% and overall efficiencies of about 40% were obtained. Tests were conducted with and without stratification. Night radiation losses were reduced by use of a screen insulation.

Design and performance evaluation of a systolic architecture for hidden-surface removal

In this paper, we propose a systolic architecture for hidden-surface removal. Systolic architecture is a kind of parallel architecture best known for its easy VLSI implementability. After discussing the design details of the architecture, we present the results of the simulation experiments conducted in order to evaluate the performance of the architecture.

S-nets: A Petri net based model for performance evaluation of real-time scheduling algorithms

A new class of nets, called S-nets, is introduced for the performance analysis of scheduling algorithms used in real-time systems Deterministic timed Petri nets do not adequately model the scheduling of resources encountered in real-time systems, and need to be augmented with resource places and signal places, and a scheduler block, to facilitate the modeling of scheduling algorithms. The tokens are colored, and the transition firing rules are suitably modified. Further, the concept of transition folding is used, to get intuitively simple models of multiframe real-time systems. Two generic performance measures, called �load index� and �balance index,� which characterize the resource utilization and the uniformity of workload distribution, respectively, are defined. The utility of S-nets for evaluating heuristic-based scheduling schemes is illustrated by considering three heuristics for real-time scheduling. S-nets are useful in tuning the hardware configuration and the underlying scheduling policy, so that the system utilization is maximized, and the workload distribution among the computing resources is balanced.

Performance evaluation of nonthermal plasma reactors for NO oxidation in diesel engine exhaust gas treatment

The discharge plasma-chemical hybrid process for NOinfinity removal from the flue gas emissions is an extremely effective and economical approach in comparison with the conventional selective catalytic reduction system. In this paper we bring out a relative comparison of several discharge plasma reactors from the point of NO removal efficiency. The reactors were either energized by ac or by repetitive pulses. Ferroelectric pellets were used to study the effect of pellet assisted discharges on gas cleaning. Diesel engine exhaust, at different loads; is used to approximately simulate the flue gas composition. Investigations were carried out at room temperature with respect to the variation of reaction products against the discharge power. Main emphasis is laid on the oxidation of NO to NO2, without reducing NOx concentration (i.e., minimum reaction byproducts), with least power consumption. The produced NO2 will be totally converted to N-2 and Na-2 SO4 using Na-2 SO3. The ac packed-bed reactor and pelletless pulsed corona reactor showed better performance, with minimum reaction products for a given power, when the NO concentration was low (similar to 100 ppm). When the engine load exceeds 50% (NO > 300 ppm) there was not much decrease in NO reduction and more or less all the reactors performed equally. The total operating cost of the plasma-chemical hybrid system becomes $4010/ton of NO, which is 1/3-1/5 of the conventional selective catalytic process.

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Performance evaluation of nonthermal plasma reactors for NO oxidation in diesel engine exhaust gas treatment

The discharge plasma-chemical hybrid process for NO/sub x/ removal from the due gas emissions is an extremely effective and economical approach in comparison with the conventional selective catalytic reduction system. In this paper we bring out a relative comparison of several discharge plasma reactors from the point of NO removal efficiency. The reactors were either energized by AC or by repetitive pulses. Ferroelectric pellets were used to study the effect of pellet assisted discharges on gas cleaning. Diesel engine exhaust, at different loads, is used to approximately simulate the due gas composition. Investigations were carried out at room temperature with respect to the variation of reaction products against the discharge power. Main emphasis is laid on the oxidation of NO to NO/sub 2/, without reducing NOx concentration (i.e., minimum reaction byproducts), with least power consumption. The produced NO/sub 2/ will be totally converted to N/sub 2/ and Na/sub 2/SO/sub 4/ using Na/sub 2/SO/sub 3/. The AC packed bed reactor and pelletless pulsed corona reactor showed better performance, with minimum reaction products for a given power, when the NO concentration was low (/spl sim/100 ppm). At high engine loads (NO>300 ppm) there was not much decrease in NO/sub x/ reduction and more or less all the reactors performed equally. The paper discusses these observations in detail.

Fuzzy data envelopment analysis for performance evaluation of an irrigation system

Sixteen irrigation subsystems of the Mahi Bajaj Sagar Project, Rajasthan, India, are evaluated and selection of the most suitable/best is made using data envelopment analysis (DEA) in both deterministic and fuzzy environments. Seven performance-related indicators, namely, land development works (LDW), timely supply of inputs (TSI), conjunctive use of water resources (CUW), participation of farmers (PF), environmental conservation (EC), economic impact (EI) and crop productivity (CPR) are considered. Of the seven, LDW, TSI, CUW, PF and EC are considered inputs, whereas CPR and EI are considered outputs for DEA modelling purposes. Spearman rank correlation coefficient values are also computed for various scenarios. It is concluded that DEA in both deterministic and fuzzy environments is useful for the present problem. However, the outcome of fuzzy DEA may be explored for further analysis due to its simple, effective data and discrimination handling procedure. It is inferred that the present study can be explored for similar situations with suitable modifications.

Performance evaluation of chemistry transport models over India

Using continuous and near-real time measurements of the mass concentrations of black carbon (BC) aerosols near the surface, for a period of 1 year (from January to December 2006) from a network of eight observatories spread over different environments of India, a space-time synthesis is generated. The strong seasonal variations observed, with a winter high and summer low, are attributed to the combined effects of changes in synoptic air mass types, modulated strongly by the atmospheric boundary layer dynamics. Spatial distribution shows much higher BC concentration over the Indo-Gangetic Plain (IGP) than the peninsular Indian stations. These were examined against the simulations using two chemical transport models, GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) and CHIMERE for the first time over Indian region. Both the model simulations significantly deviated from the measurements at all the stations; more so during the winter and pre-monsoon seasons and over mega cities. However, the CHIMERE model simulations show better agreement compared with the measurements. Notwithstanding this, both the models captured the temporal variations; at seasonal and subseasonal timescales and the natural variabilities (intra-seasonal oscillations) fairly well, especially at the off-equatorial stations. It is hypothesized that an improvement in the atmospheric boundary layer (ABL) parameterization scheme for tropical environment might lead to better results with GOCART.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.