Performance of WRF (ARW) over River Basins in Odisha, India During Flood Season 2014

Paper Title:- Performanceof WRF (ARW) over River Basins in Odisha, India During Flood Season 2014

Author Name:- Sumant Kr. Diwakar

India Meteorological Department, New Delhi, India

Abstract:- Operational Weather Research & Forecasting – Advanced Research WRF in short WRF (ARW) 9 km x 9 km Model (IMD) based rainfall forecast of India Meteorological Department (IMD) is utilized to compute rainfall forecast over River basins in Odisha during Flood season 2014. The performance of the WRF Model at the sub-basin level is studied in detail. It is observed that the IMD’s WRF (ARW) day1, day2, day3 correct forecast range lies in between 31-47 %, 37-43%, and 28-47% respectively during the flood season 2014.

Keywords: GIS; WRF (ARW); IMD; Flood 2014; Odisha     

I.      Introduction

Forecast during the monsoon season river sub-basin wise in India is difficult task for meteorologist to give rainfall forecast where the country have large spatial and temporal variations. India Meteorological Department (IMD) through its Flood Meteorological Offices (FMO) is issuing Quantitative Precipitation Forecast (QPF) sub-basin wise for all Flood prone river basins in India (IMD, 1994). There are 10 FMOs all over India spread in the flood prone river basins and FMO Bhubaneswar, Odisha is one of them. The Categories in which QPF are issued are as follows

Rainfall (in mm)

0

1-10

11-25

26-50

51-100

>100

    

    Odisha is an Indian state on the subcontinent’s east coast, by the Bay of Bengal. It is located between the parallels of 17.49’ N and 22.34’ N Latitudes and meridians of 81.27’ E and 87.29’ E Longitudes. It is surrounded by the Indian states of West Bengal to the north-east and in the east, Jharkhand to the north, Chhattisgarh to the west and north-west and Andhra Pradesh to the south. Bhubaneswar is the capital of Odisha.

     Odisha is the 9^th largest state by area in India and the 11^th largest by population. Odisha has a coastline about 480 km long. The narrow, level coastal strip including the Mahanadi river delta supports the bulk of the population. On the basis of homogeneity, continuity and physiographical characteristics, Odisha has been divided into five major morphological regions. The Odisha Coastal Plain in the east, the Middle Mountainous and Highlands Region, the Central Plateaus, the western rolling uplands and the major flood plains.     

A.      River System

The river system of Odisha comprises the Mahanadi, Brahmani, Baitarani, Subarnarekha, Vamasadhara, Burhabalanga, Rushikulya, Nagavali, Indravati, Kolab, Bahuda, Jambhira and other tributaries and distributaries.

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Evaluation of Response Reduction Factor using Nonlinear Analysis #IJIRST Journal

Paper Title:- Evaluation of Response Reduction Factor using Nonlinear Analysis 

Author Name:- Tia Toby

Department of Civil Engineering

Abstract:- The main objective of the study is to evaluate the response reduction factor of RC frames. We know that the actual earthquake force is considerably higher than what the structures are designed for. The structures can't be designed for the actual value of earthquake intensity as the cost of construction will be too high. The actual intensity of earthquake is reduced by a factor called response reduction factor R. The value of R depends on ductility factor, strength factor, structural redundancy and damping. The concept of R factor is based on the observations that well detailed seismic framing systems can sustain large inelastic deformation without collapse and have excess of lateral strength over design strength. Here the nonlinear static analysis is conducted on regular and irregular RC frames considering OMRF and SMRF to calculate the response reduction factor and the codal provisions for the same is critically evaluated. 

Keywords: Response Reduction Factor, Ductility Factor, Strength Factor, Nonlinear Analysis, Regular and Irregular Frames, OMRF, SMRF

I.    Introduction

The devastating potential of an earthquake can have major consequences on infrastructures and lifelines. In the past few years, the earthquake engineering community has been reassessing its procedures, in the wake of devastating earthquakes which have caused extensive damage, loss of life and property. These procedures involve assessment of seismic force demands on the structure and then developing design procedures for the structure to withstand the applied actions Seismic design follows the same procedure, except for the fact that inelastic deformations may be utilized to absorb certain levels of energy leading to reduction in the forces for which structures are designed. This leads to the creation of the Response Modification Factor (R factor); the all-important parameter that accounts for over-strength, energy absorption and dissipation as well as structural capacity to redistribute forces from inelastic highly stressed regions to other less stressed locations in the structure. This factor is unique and different for different type of structures and materials used. The objective of this paper is to evaluate the response reduction factor of a RC frame designed and detailed as per Indian standards IS 456, IS 1893 and IS 13920.The codal provisions for the same will be critically evaluated. Moreover parametric studies will be done on both regular and irregular buildings and finally a comparison of R value between OMRF and SMRF is also done.

II.  Definition of r factor and its components

During an earthquake, the structures may experience certain inelasticity, the R factor defines the levels of inelasticity. The R factor is allowed to reflect a structures capability of dissipating energy via inelastic behavior. The statically determinate structures response to stress will be linear until yielding takes place. But the behavioral change in structure from elastic to inelastic occurs as the yielding prevails and linear elastic structural analysis can no longer be applied. The seismic energy exerted by the structure is too high which makes the cost of designing a structure based on elastic spectrum too high. To reduce the seismic loads, IS 1893 introduces a “response reduction factor” R. So in order to obtain the exact response, it is recommended to perform Nonlinear analysis. In actual speaking R factor is a measure of overstrength and redundancy. It may be defined as a function of various parameters of the structural system, such as strength, ductility, damping and redundancy.

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Performance Assessment for Students using Different Defuzzification Techniques

Paper Title:- Performance Assessment for Students using Different Defuzzification Techniques

Author Name:- Anjana Pradeep, Jeena Thomas

Department of Computer Science & Engineering

Abstract:- The aim of this study is to evaluate the performance of students using a fuzzy expert system. The fuzzy process is based solely on the principle of taking non-precise inputs on the factors affecting the performance of students and subjecting them to fuzzy arithmetic to obtain a crisp value of the performance. The system classifies each student's performance by considering various factors using fuzzy logic. Aimed at improving the performance of fuzzy system, several defuzzification methods other than the built methods in MATLAB have been devised in this system for producing more accurate and quantifiable result.  This study provides comparison and in depth examination of various defuzzification techniques like Weighted Average Formula (WAF), WAF-max method and Quality Method (QM). A new defuzzification method named as Max-QM which is extended from Quality method that falls within the general framework is also given and commented upon in this study.      

Keywords: Fuzzy logic, Fuzzy Expert System, Defuzzification, Weighted Average Formula, Quality Method 

I.   Introduction

An expert system is a software program that can be used to solve complex reasoning tasks that usually require a (human) expert. In other words, an expert system should help a novice, or partly experienced, problem solver, to match acknowledged experts in the particular domain of problem solving that the system is designed to assist. To be more specific, expert systems are generally conceptualized as shown in Fig 1. The user makes an interaction through the interface system and the system questions the user through the same interface in order to obtain the vital information upon which a decision is to be made. Behind this interface, there are two other sub-systems viz. the knowledge base, which is made up of all the domain-specific knowledge that human experts use when solving that category of problems and the inference engine, a system that performs the necessary reasoning and uses knowledge from the knowledge base in order to come to a judgment with respect to the problem modelled [1].

     Expert system has been playing a major role in many disciplines such as in medicines, assist physician in diagnosis of diseases, in agriculture for crop management, insect control, in space technology and  in power systems for fault diagnosis[5]. Some expert systems have been developed to replace human experts and to aid humans. The use of an expert system is increasing day by day in today’s world [40]. Expert systems are becoming an integral part of engineering education and even other courses like accounting and management are also accepting them as a better way of teaching[4].Another feature that makes expert system more demanding for students is its ability to adaptively adjust the training for each particular student on the bases of individual students learning pace. This feature can be used more effectively in teaching engineering students. It should be able to monitor student’s progress and make a decision about the next step in training.

Fig. 1: Expert system structure

        The few expert systems available in the market present a lot of opportunities for the students who desire more spotlight and time to learn the subjects. Some expert systems present an interactive and friendly environment for students which encourage them to study and adopt a more practical approach towards learning. The expert systems can also act as an assistor or substitute for the teacher. Expert systems focus on each student individually and also keep track of their learning pace. This behavior of an expert system provides autonomous learning procedure for both student and teacher, where teachers act as mentor and students can judge their own performance. Expert system is not only beneficial for the students but also for the teachers which help them guiding students in a better way.

        The integration of fuzzy logic with an expert system enhances its capability and is called a fuzzy expert system, as it is useful for solving real world problems which do not require a precise solution. So, there is a need to develop a fuzzy expert system as it can handle imprecise data efficiently and reduces the manual working while enhancing the use of expert system[40].

      There are various factors inside and outside college that results in poor quality of academic performance of students[2,3]. To determine all the influencing factors in a single effort is a complex and difficult task. It necessitates a lot of resources and time for an educator to identify all these factors first and then plan the classroom activities and approaches of teaching and learning. It also requires appropriate training, organizational planning and skills to conduct such studies for determining the contributing factors inside and outside college. This process of identification of determinants must be given full attention and priority so that the teachers may be able to develop instructional strategies for making sure that all the students be provided with the opportunities to attain at their fullest potential in learning and performance.  By using suitable statistical package it was found that communication, learning facilities, proper guidance and family stress were the factors that affect the student performance. Communication, learning facilities and proper guidance showed a positive impact on student performance and family stress showed a negative impact on student performance. It is indicated that communication is more important factor that affect the student performance than learning facilities and proper guidance [3].

      In this research article seven most important factors are included which affect the students’ performance. These are personal factors, college environment, family factors, and university factors, teaching factors, attendance and marks obtained by students. All these factors are scaled and ranked based on the various sub-factors that are further divided from the base factors. In this study the students’ marks have been focused and not solely on social, economic, and cultural features.  To evaluate students’ performance, fuzzy expert system has been developed by considering all the seven factors as inputs to the system. This system has been developed by taking the data of students collected from St. Josephs College of Engineering and Technology, Palai affiliated to M.G University.

II.   Literature review

In recent years, many researchers worked on the applications of fuzzy logic and fuzzy sets in educational assessments and grading systems. Biswas[25] presented two methods for evaluating  students’ answer scripts using fuzzy sets and a matching function: a fuzzy evaluation method (FEM) and a generalized fuzzy evaluation method. He used fuzzy set theory in student evaluation and found that it is potentially finer than awarding grades or numbers when evaluating answer scripts. He also highlighted that the importance of education system should be to provide students with the evaluation reports regarding their test/examination as sufficient as possible with unavoidable error as small as possible so as to make evaluation system more transparent and fairer to students.

                Chen and Lee [26] presented two methods for applying fuzzy sets to overcome the problem of giving two different fuzzy marks to students with the same total score which could arise from Biswas’ method. Their methods perform calculations much faster and complicated matching operations were not required. Echauz and Vachtsevanos [27] proposed a fuzzy logic system for translating traditional scores into letter-grades. Law [28] built a fuzzy structure model with its algorithm to aggregate different test scores in order to produce a single score for individual students in an educational grading system. A method to build the membership functions (MFs) of several linguistic values with different weights was also proposed in this paper. 

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#IJIRST Journal : A Review on Thermal Insulation and Its Optimum Thickness to Reduce Heat Loss

Title:- A Review on Thermal Insulation and Its Optimum Thickness to Reduce Heat Loss

Author Name: Dinesh Kumar Sahu, Prakash Kumar Sen, Gopal Sahu, Ritesh Sharma, Shailendra Bohidar

Department of Mechanical Engineering

Abstract:- An understanding of the mechanisms of heat transfer is becoming increasingly important in today’s world. Conduction and convection heat transfer phenomena are found throughout virtually all of the physical world and the industrial domain. A thermal insulator is a poor conductor of heat and has a low thermal conductivity. In this paper we studied that Insulation is used in buildings and in manufacturing processes to prevent heat loss or heat gain. Although its primary purpose is an economic one, it also provides more accurate control of process temperatures and protection of personnel. It prevents condensation on cold surfaces and the resulting corrosion. We also studied that critical radius of insulation is a radius at which the heat loss is maximum and above this radius the heat loss reduces with increase in radius. We also gave the concept of selection of economical insulation material and optimum thickness of insulation that give minimum total cost.       

Keywords: Heat, Conduction, Convection, Heat Loss, Insulation

I.    Introduction

Heat flow is an inevitable consequence of contact between objects of differing temperature. Thermal insulation provides a region for insulation in which thermal conduction is reduced or thermal radiation is reflected rather than absorbed by the lower temperature body. To change the temperature of an object, energy is required in the form of heat generation to increase the temperature, or heat extraction to reduce the temperature. Once the heat generation or heat extraction is terminated a reverse flow of heat occurs to reverse the temperature back to ambient. To maintain a given temperature considerable continuous energy is required. Insulation will reduce this energy loss.

     Heat may be transferred in three mechanisms: conduction, convection and radiation. Thermal conduction is the molecular transport of heat under the effect of temperature gradient. Convection mechanism of heat occurs in liquids and gases, whereby the flow processes transfer heat. Free convection is flow caused by the differences in density as a result of temperature differences. Forced convection is flow caused by external influences (wind, ventilators, etc.). Thermal radiation mechanism occurs when thermal energy is emitted similar to light radiation.

      Heat transfers through insulation material occur by means of conduction, while heat loss to or heat gain from atmosphere occurs by means of convection and radiation. Materials, which have a low thermal conductivity, are those, which have a high proportion of small voids containing air or gases. These voids are not big enough to transmit heat by convection or radiation, and therefore reduce the flow of heat. Thermal insulation materials come into the latter category. Thermal insulation materials may be natural substances or man-made.

II.   The Need for Insulation

A thermal insulator is a poor conductor of heat and has a low thermal conductivity. Insulationis used in buildings and in manufacturing processes to prevent heat loss or heat gain. Although its primary purpose is an economic one, it also provides more accurate control of process temperatures and protection of personnel. It prevents condensation on cold surfaces and the resulting corrosion. Such materials are porous, containing large number of dormant air cells. Thermal insulation delivers the following benefits: [1][2]

A.      Energy Conservation

Conserving energy by reducing the rate of heat flow (fig 1) is the primary reason for insulating surfaces. Insulation materials that will perform satisfactorily in the temperature range of -268°C to 1000°C are widely available.

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Study on the Ductile Characteristics of Hybrid Ferrocement Slab #IJIRST Journal

Author Name:- Rahul Reddy

Department of Civil Engineering

Poojya Doddappa Appa college of Engineering, Kalaburagi – 585102, Karnataka, India

Abstract:- This paper presents the ductile characteristics of hybrid Ferro cement slab incorporating polypropylene fibres and GFRP sheet. A total of 9 slab have been tested under two point flexural loading. The size of the slab is 1000 mm(length) x1000 mm(width) x 60 mm(thickness). The parameters studied in this investigation includes the number of weld mesh layers, polypropylene fibres i.e (0.3%) and GFRP sheet. from the studies, it is observed that the load carrying capacity and deformation. The stiffness of the specimens with zero layer weld mesh is lower than that of the specimens with two layers and three layers bundled. Further, there is reduction in number of cracks with increase in fibre content.

Keyword:- Ferrocement Slabs, GFRP Wrapping, Fibre Reinforcement, Ductility Factors, Crack Pattern

I.       Introduction

The development of new technology in the material science is progressing rapidly. In recent two or three decades, a lot research was carried out throughout globe for how to improve the performance of concrete in terms of strength and durability qualities. consequently concrete has no longer remained as a construction material. A new material consisting of wire meshes and cement mortar called ferrocement. it is one of the construction materials which may be able to fill the need for building light structures. ferrocement composite consist of cement-sand mortar and single or multi-layers of steel wire mesh to produce elements of small thickness having high durability, and when properly shaped it has high strength and rigidity. These thin elements can be shaped to produce structural members such as folded plates, flanged beams, wall pane,. etc for use in the construction of cheap structures. Ferro cement elements are generally more ductile when compared to conventional reinforced concrete elements but post peak portion of load- deflection curve in bending test of Ferro cement elements reveals that failure occur  either due to mortar failure in compression or due to failure of extreme layers of mesh.  From the above discussions, it can be noted that, research work out on the ductile behavior of hybrid ferrocement slab with fibre. The present Investigation is aimed at to investigate the ductile behavior of hybrid ferrocement slabs with and without Considering the effect of fibres.  Compared with the conventional reinforced concrete, ferrocement is reinforced in two directions; therefore, it has homogenous-isotropic properties in two directions. Benefiting from its usual high reinforcement ratio, ferrocement generally has a high tensile strength and a high modulus of rupture. In addition, since the specific surface of reinforcement in ferrocement is one to two orders of magnitude higher than that of reinforced concrete, larger bond forces develop with the matrix resulting in average crack spacing and width more than one order of magnitude smaller than in conventional reinforced concrete (Shah and Naaman 1997, Guerra et al 1978). Other appealing features of ferrocement include ease of prefabrication and low cost in maintenance and repair. Based on the abovementioned advantages, the typical applications of ferrocement are water tanks, boats, housing wall panel, roof, formwork and sunscreen (Nimityongskul et al 1980 and Kadir 1997).. Ferrocement over the years have gained respect in terms of its superior performance and versatility. Ferrocement is a form of reinforced concrete using closely spaced multiple layers of mesh and/or small diameter rods completely infiltrated with, or encapsulated in, mortar. In 1940 Pier Luigi Nervy, an Italian engineer, architect and contractor, used ferrocement first for the construction of aircraft hangars, boats and buildings and a variety of other structures. It is a very durable, cheap and versatile material.

II.       Experimental investigation

The experimental investigation consists of testing of nine hybrid ferrocement slabs. the Variables Considered In The Study(I) Numbers Of Welded Square Mesh Reinforcement.(ii) Percentage of polypropylene fibres in mortar.(iii) Number of GFRP layer wrapping. The details of experimental studies including characterization are presented below.

A.      Materials Used

The materials that are used in this experiment are cement, steel fiber, fine aggregate, super plasticizer and water.

1)     Cement:

OPC 53 grade cement from a single batch has been used throughout the course of the project work, properties of cement are shown in table 2.

2)     Fine aggregates:

Only fine aggregate is used in Ferrocement the aggregate consists of well graded fine aggregate (sand)   that   passes   a   4.75  mm   sieve.  and   since   salt-free   source   is recommended, sand should preferably be selected from river-beds and be free from  organic  or  other  deleterious  matter. Good amount of consistency and compactibility is achieved by using a  well- graded, rounded, natural sand having a maximum top size about one-third of the small opening in the reinforcing mesh to ensure proper penetration. The moisture content of the aggregate should be considered in the calculation of required water.

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Applications and Challenges of Human Activity Recognition using Sensors in a Smart Environment #IJIRST Journal

Author name:- Jubil T Sunny

Department of Computer Science and Engineering

St. Joseph’s College of Engineering and Technology, Palai, Kerala, India

Abstract:- We are currently using smart phone sensors to detect physical activities. The sensors which are currently being used are accelerometer, gyroscope, barometer, etc. Recently, smart phones, equipped with a rich set of sensors, are explored as alternative platforms for human activity recognition. Automatic recognition of physical activities – commonly referred to as human activity recognition (HAR) – has emerged as a key research area in human-computer interaction (HCI) and mobile and ubiquitous computing. One goal of activity recognition is to provide information on a user’s behavior that allows computing systems to proactively assist users with their tasks. Human activity recognition requires running classification algorithms, originating from statistical machine learning techniques. Mostly, supervised or semi-supervised learning techniques are utilized and such techniques rely on labeled data, i.e., associated with a specific class or activity. In most of the cases, the user is required to label the activities and this, in turn, increases the burden on the user. Hence, user- independent training and activity recognition are required to foster the use of human activity recognition systems where the system can use the training data from other users in classifying the activities of a new subject.

Keyword:- Human Activity Recognition

I.       Introduction

Mobile phones or smart phones are rapidly becoming the central computer and communication device in people’s lives. Smart phones, equipped with a rich set of sensors, are explored as an alternative platform for human activity recognition in the ubiquitous computing domain. Today’s Smartphone not only serves as the key computing and communication mobile device of choice, but it  also comes with a rich set of embedded sensors [1], such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera. Collectively, these sensors are enabling new applications across a wide variety of domains, such as healthcare, social networks, safety, environmental monitoring, and transportation, and give rise to a new area of research called mobile phone sensing. Human activity recognition systems using different sensing modalities, such as cameras or wearable inertial sensors, have been an active field of research. Besides the inclusion of sensors, such as accelerometer, compass, gyroscope, proximity, light, GPS, microphone, camera, the ubiquity, and unobtrusiveness of the phones and the availability of different wireless interfaces, such as WI-Fi, 3G and Bluetooth, make them an attractive platform for human activity recognition. The current research in activity monitoring and reasoning has mainly targeted elderly people, or sportsmen and patients with chronic conditions.

The percentage of elderly people in today’s societies keep on growing. As a consequence, the problem of supporting older adults in loss of cognitive autonomy who wish to continue living independently in their home as opposed to being forced to live in a hospital. Smart environments have been developed in order to provide support to the elderly people or people with risk factors who wish to continue living independently in their homes, as opposed to live in an institutional care. In order to be a smart environment, the house should be able to detect what the occupant is doing in terms of one’s daily activities. It should also be able to detect possible emergency situations. Furthermore, once such a system is completed and fully operational, it should be able to detect anomalies or deviations in the occupant’s routine, which could indicate a decline in his abilities. In order to obtain accurate results, as much information as possible must be retrieved from the environment, enabling the system to locate and track the supervised person in each moment, to detect the position of the limbs and the objects the person interacts or has the intention to interact with. Sometimes, details like gaze direction or hand gestures [1] can provide important information in the process of analyzing the human activity. Thus, the supervised person must be located in a smart environment, equipped with devices such as sensors, multiple view cameras or speakers.

Although smart phone devices are powerful tools, they are still passive communication enablers rather than active assistive devices from the user’s point of view. The next step is to introduce intelligence into these platforms to allow them to proactively assist users in their everyday activities. One method of accomplishing this is by integrating situational awareness and context recognition into these devices. Smart phones represent an attractive platform for activity recognition, providing built-in sensors and powerful processing units. They are capable of detecting complex everyday activities of the user (i.e. Standing, walking, biking) or the device (i.e.  Calling), and they are able to exchange information with other devices and systems using a large variety of data communication channels.

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http://ijirst.org/Article.php?manuscript=IJIRSTV2I4024

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