Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7

Publications

7 Annual and Seasonal Variations in Air Quality Index of the National Capital Region, India

Authors: Surinder Deswal, Vineet Verma

Abstract:

Air Quality Index (AQI) is used as a tool to indicate the level of severity and disseminate the information on air pollution to enable the public to understand the health and environmental impacts of air pollutant concentration levels. The annual and seasonal variation of criteria air pollutants concentration based on the National Ambient Air Quality Monitoring Programme has been conducted for a period of nine years (2006-2014) using the AQI system. AQI was calculated using IND-AQI methodology and Maximum Operator Concept is applied. An attempt has been made to quantify the variations in AQI on an annual and seasonal basis over a period of nine years. Further, year-wise frequency of occurrence of AQI in each category for all the five stations is analysed, which presents in depth analysis of trends over the period of study. The best air quality was observed in the Noida residential area, followed by Noida industrial area during the study period; whereas, Bulandshahar industrial area and Faridabad residential area were observed to have the worst air quality. A shift in the worst air quality from winter to summer season has also been observed during the study period. Further, the level of Respirable Suspended Particulate Matter was found to be above permissible limit at all the stations. The present study helps in enhancing public awareness and calls for the need of immediate measures to be taken to counter-effect the cause of the increasing level of air pollution.

Keywords: Air quality index, annual trends, criteria pollutants, seasonal variation.

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6 Stature Prediction Model Based On Hand Anthropometry

Authors: Arunesh Chandra, Pankaj Chandna, Surinder Deswal, Rajesh Kumar Mishra, Rajender Kumar

Abstract:

The arm length, hand length, hand breadth and middle finger length of 1540 right-handed industrial workers of Haryana state was used to assess the relationship between the upper limb dimensions and stature. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then simple and multiple linear regression models were used to estimate stature using SPSS (version 17). There was a positive correlation between upper limb measurements (hand length, hand breadth, arm length and middle finger length) and stature (p < 0.01), which was highest for hand length. The accuracy of stature prediction ranged from ± 54.897 mm to ± 58.307 mm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of male industrial workers of Haryana (India). The results of this research indicate that stature can be determined using hand dimensions with accuracy, when only upper limb is available due to any reasons likewise explosions, train/plane crashes, mutilated bodies, etc. The regression formula derived in this study will be useful for anatomists, archaeologists, anthropologists, design engineers and forensic scientists for fairly prediction of stature using regression equations.

Keywords: Anthropometric dimensions, Forensic identification, Industrial workers, Stature prediction.

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5 Modeling Oxygen-transfer by Multiple Plunging Jets using Support Vector Machines and Gaussian Process Regression Techniques

Authors: Surinder Deswal

Abstract:

The paper investigates the potential of support vector machines and Gaussian process based regression approaches to model the oxygen–transfer capacity from experimental data of multiple plunging jets oxygenation systems. The results suggest the utility of both the modeling techniques in the prediction of the overall volumetric oxygen transfer coefficient (KLa) from operational parameters of multiple plunging jets oxygenation system. The correlation coefficient root mean square error and coefficient of determination values of 0.971, 0.002 and 0.945 respectively were achieved by support vector machine in comparison to values of 0.960, 0.002 and 0.920 respectively achieved by Gaussian process regression. Further, the performances of both these regression approaches in predicting the overall volumetric oxygen transfer coefficient was compared with the empirical relationship for multiple plunging jets. A comparison of results suggests that support vector machines approach works well in comparison to both empirical relationship and Gaussian process approaches, and could successfully be employed in modeling oxygen-transfer.

Keywords: Oxygen-transfer, multiple plunging jets, support vector machines, Gaussian process.

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4 Estimation of Individual Power of Noise Sources Operating Simultaneously

Authors: Pankaj Chandna, Surinder Deswal, Arunesh Chandra, SK Sharma

Abstract:

Noise has adverse effect on human health and comfort. Noise not only cause hearing impairment, but it also acts as a causal factor for stress and raising systolic pressure. Additionally it can be a causal factor in work accidents, both by marking hazards and warning signals and by impeding concentration. Industry workers also suffer psychological and physical stress as well as hearing loss due to industrial noise. This paper proposes an approach to enable engineers to point out quantitatively the noisiest source for modification, while multiple machines are operating simultaneously. The model with the point source and spherical radiation in a free field was adopted to formulate the problem. The procedure works very well in ideal cases (point source and free field). However, most of the industrial noise problems are complicated by the fact that the noise is confined in a room. Reflections from the walls, floor, ceiling, and equipment in a room create a reverberant sound field that alters the sound wave characteristics from those for the free field. So the model was validated for relatively low absorption room at NIT Kurukshetra Central Workshop. The results of validation pointed out that the estimated sound power of noise sources under simultaneous conditions were on lower side, within the error limits 3.56 - 6.35 %. Thus suggesting the use of this methodology for practical implementation in industry. To demonstrate the application of the above analytical procedure for estimating the sound power of noise sources under simultaneous operating conditions, a manufacturing facility (Railway Workshop at Yamunanagar, India) having five sound sources (machines) on its workshop floor is considered in this study. The findings of the case study had identified the two most effective candidates (noise sources) for noise control in the Railway Workshop Yamunanagar, India. The study suggests that the modification in the design and/or replacement of these two identified noisiest sources (machine) would be necessary so as to achieve an effective reduction in noise levels. Further, the estimated data allows engineers to better understand the noise situations of the workplace and to revise the map when changes occur in noise level due to a workplace re-layout.

Keywords: Industrial noise, sound power level, multiple noise sources, sources contribution.

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3 Artificial Neural Network based Modeling of Evaporation Losses in Reservoirs

Authors: Surinder Deswal, Mahesh Pal

Abstract:

An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Keywords: Artificial neural network, evaporation losses, multiple linear regression, modeling.

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2 Oxygen Transfer by Multiple Inclined Plunging Water Jets

Authors: Surinder Deswal

Abstract:

There has been a growing interest in the oxygenation by plunging water jets in the last few years due to their inherent advantages, like energy-efficient, low operation cost, etc. Though a lot of work has been reported on the oxygen-transfer by single plunging water jets but very few studies have been carried out using multiple plunging jets. In this paper, volumetric oxygen-transfer coefficient and oxygen-transfer efficiency has been studied experimentally for multiple inclined plunging jets (having jet plunge angle of 60 0 ) in a pool of water for different configurations, in terms of varying number of jets and jet diameters. This research suggests that the volumetric oxygen-transfer coefficient and oxygentransfer efficiency of the multiple inclined plunging jets for air-water system are significantly higher than those of a single vertical as well as inclined plunging jet for same flow area and other similar conditions. The study also reveals that the oxygen-transfer increase with increase in number of multiple jets under similar conditions, which will be most advantageous and energy-efficient in practical situations when large volumes of wastewaters are to be treated. A relationship between volumetric oxygen-transfer coefficient and jet parameters is also proposed. The suggested relationship predicts the volumetric oxygen-transfer coefficient for multiple inclined plunging jet(s) within a scatter of ±15 percent. The relationship will be quite useful in scale-up and in deciding optimum configuration of multiple inclined plunging jet aeration system.

Keywords: Multiple inclined plunging jets, jet plunge angle, volumetric oxygen-transfer coefficient, oxygen-transfer efficiency.

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1 Performance Evaluation and Modeling of a Conical Plunging Jet Aerator

Authors: Surinder Deswal, D. V. S. Verma

Abstract:

Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.

Keywords: Conical plunging jet, oxygen-transfer efficiency, support vector machines, volumetric oxygen-transfer coefficient.

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