IEDC-2010 Conference Proceedings (Download ... - NED University

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Table 2. Engineering Test Results and Petrographic Studies Quarry: Maru Dakka Crusher: Rais Goth Quarry: Langlohar Crusher: Ahmed Goth Quarry: Hasan Pir Hill Crusher: Hasan Pir S.no. Engineering test Weighted %age Quarry: M.Inayat Crusher: M. Inayat 1 Flakiness index 39.67 14.73 12.53 37.86 2 Elongation index 7.23 23.52 17.05 17.33 3 Specific gravity and absorption (i) Absorption (%) 0.45 0.30 0.18 1.61 (ii) Bulk specific gravity(bsg) 2.6 2.65 2.66 2.88 (iii) Bulk specific gravity(ssd) 2.6 2.67 2.66 2.95 (iv) Apparent specific gravity 2.6 2.69 2.67 2.98 4 Crushing value 21.61 25.37 27.15 25.57 5 Impact value 16.00 15.32 14.76 14.69 6 L.A. abrasion 26.39 27.22 26.15 26.24 7 Mineralogy (i) Carbonate content 76.22 89.51 88.38 87.79 (ii) Non carbonate content 23.78 10.49 11.62 12.21 Proceedings of IEDC 2010, 1-3 July, 2010 97 IEDC-136-063
Temperature (°C) 2.1.2 Aggregate Characterization Stage 2: Performance Testing and Predictive Model Pavement performance modeling is an important tool used by pavement managers in decision making in prioritization and budgeting for maintenance work (Isa et al., 2005). Prediction Models are used in both design procedures with the intention of providing good future pavement performance. Asphalt concrete pavements primarily suffer from three types of distresses that is rutting, fatigue cracking and thermal cracking. In this paper, the most severe distress rutting with respect to pavement damage is selected for the study which is confirmed from pavement distress surveys of Karachi Highways. Rutting in flexible pavement has been a significant concern for highway engineers and users, caused by a load passing repeatedly across the surface of pavement and results in lateral spreading of the pavement from the location of load application, thus producing a rut or groove (McAlister et al., 1996). It is also described as the permanent deformation which initiate in longitudinal depression accompanied by upheavals to the side. In this study, wheel-tracking device is used to asses the rutting potential of asphalt mixes which helps to suggest the pass-or-fail criterion for performance prediction purposes of asphalt mixture with Hub river aggregates. In this stage, the objective is to establish a performance prediction model based on laboratory experiment, which describe and predict the rutting accumulation in asphalt concrete under repeated loading cycle. The model shall contribute the effects of significant factors and interaction of these factors which contribute to develop rutting in pavements. The model shall integrate the relevant independent variable; temperature and percentage of asphalt with the constant traffic loading of 10,000 passes. The results of wheel tracking device are shown in Table 3. Statistical analysis by mean of multiple linear regressions were conducted to test and examine the data as well as to develop the model. Table 3. Rut Depths at 10,000 wheel passes (of Wheel Tracking Test) 25 40 55 Asphalt Content%(gm) 4.5(562.5) 5(625) 5.5(687.5) 4.12 3.89 6.43 3.46 3.3 4.12 4.9 2.71 4.97 6.25 6.4 7.48 6.24 6.24 7.36 4.83 6.71 8.23 8.77 10.94 11.81 6.37 9.06 9.11 9.13 9.95 9.66 2.2 Pavement Asset Management Tools (Fwa, 2006) These tools are composed of three main record which are used in the analysis box, as described below: 2.2.1 Core Asset Data The management system is always supported by the large amount of data present for evaluation to proceed with decision on the basis of analysis (FHWA, 2009). The data bases are preliminary useful in prioritization process that ultimately focus on risk reduction and provide support for their remedies (Moteff, 2007). These data are also inducted in the cost benefit analysis and helps the agencies to improve the technical models which produce vital results for improved decisions and ways to reduce the cost (Falls Proceedings of IEDC 2010, 1-3 July, 2010 98 IEDC-136-063
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IEDC 2010 Proceedings of the Third
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CONTENTS Preface Conference Committ
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IEDC-231-023 2.3 Transportation net
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PREFACE Over the last decade, issue
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1. Mr. Afzal Ahmed Lecturer, Depart
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Surname Forenames E-mail Address Pa
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Spaceborne Remote Sensing Data for
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1.3 Karachi Metropolitan Transporta
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3. Travel Demand Modeling and Daily
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AADT , veh/day traffic count sites.
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operating cost is 19-24 cents per v
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Prioritizing Environmental Infrastr
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The rapid growth of Punjab's cities
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In Table 1 the BOD estimates have b
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The results clearly indicate that i
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An Intelligent Drainage System to P
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level. The situation caused objecti
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4.3 Electro-mechanical system requi
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Contribution of NED University in E
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were felt in some areas of Pakistan
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the USA and held meetings with the
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Figure 4. Demand response spectrum
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3.4 Vertical deformation near Karac
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Earthquake Performance of RC Struct
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Inadequate code implementation; Ina
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(a) (b) (c) Figure 2. Unsymmetrical
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(a) (b) Figure 5. Construction of o
Page 57 and 58: (a) (b) Figure 8. Splicing of colum
Page 59: Lin, J.H. (2005). ―Evaluation of
Page 62 and 63: Persons (Human) induced disaster is
Page 64 and 65: and non human resources to protect
Page 66 and 67: In case of major events and disaste
Page 68 and 69: 3.2.1 Aims and Objectives of DMP at
Page 70 and 71: - Manmade disasters. 3.3 Practical
Page 72 and 73: c. Students Information Block. d. S
Page 74 and 75: - Seek assistance from University a
Page 76 and 77: Pearce, Laurie; Hightower, Henry, K
Page 78 and 79: If the location of the charge weigh
Page 80 and 81: Exterior Columns: These are designe
Page 82 and 83: If Pso is the pressure in the regul
Page 84 and 85: Height of Structure (H s ) (m) Tabl
Page 86 and 87: 6. Conclusions Following conclusion
Page 88 and 89: agencies. It shares 65% of the tota
Page 90 and 91: 2.2 Soils and Landforms Different l
Page 92 and 93: 2.4 Land Capability Eight (8) class
Page 94 and 95: Northing (m) 3.2 Water Quality The
Page 96 and 97: Ejaz, M. S. & Bhatti, H. A. (2007).
Page 98 and 99: esearch, a semi-automated data surv
Page 100 and 101: database contain the picture code,
Page 102 and 103: imposes the erroneous data. During
Page 104 and 105: Aggregate Characterization - A Gate
Page 106 and 107: 2.1 Aggregate Characterization Aggr
Page 110 and 111: and Tighe, 2004). The databases for
Page 112 and 113: the development of a comprehensive
Page 114 and 115: Satellite Image from Google Earth S
Page 116 and 117: Evaluation of Driving Comfort and S
Page 118 and 119: mobile station, and the satellite d
Page 120 and 121: PSD((m/s 2 ) 2 /Hz) PSD((m/s 2 ) 2
Page 122 and 123: The simulation data during travelin
Page 124 and 125: Yaw rate RMS(deg/s) Steering angle
Page 126 and 127: SUSTAINABLE TRANSPORTATION AND ENVI
Page 128 and 129: great centre of learning, knowledge
Page 130 and 131: 2.2 Urban Development Plans - After
Page 132 and 133: The proposed alignment was made acc
Page 134 and 135: have enriched the Ring Road proposa
Page 136 and 137: project were completed under Lahore
Page 138 and 139: Therefore, the Ring Road or ‗Sout
Page 140 and 141: For the Ring Road, CSTS estimated n
Page 142 and 143: Government of Pakistan, Planning Co
Page 144 and 145: Traffic Management, A Social Concer
Page 146 and 147: 5. Magnitude of problems encompassi
Page 148 and 149: SO 2 (10 -6 ) 44 38 - NO 2 (10 -9 )
Page 150 and 151: action. Movement through the levels
Page 152 and 153: STMS Government Society Figure 2. S
Page 154 and 155: Development of Guidelines for Road
Page 156 and 157: Through secondary safety measures,
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and fatal injuries while road users
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The ending portion of Shahrah-e-usm
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Again this example is good for bett
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Environmental Impacts of Road Trans
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Lagos was the capital of Nigeria un
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Table 1. Areal Extents of the Landu
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Figure 4. Point Based Features alon
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Chokor B. A. and Odemerho F.O. (199
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ecause of complexities and connecti
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Number of accident Year of accident
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clarified that about 75% of the cri
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elative frequency Figure 10- map of
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elative frequency Most accidents ha
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Economic Evaluation of Road Traffic
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4.3 Human Consequences An accident
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Table 1. Descriptive Statistics for
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comes to 30% whereas a small share
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Accidents Reduction (%) CBR 1.80 15
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Accident Prediction Linear Model fo
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About 15% of the drivers are owners
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Accidents in last two years Acciden
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Presence Of Cassette Player, Yes .0
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An Evaluation of Future Travel Patt
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infrastructure, public transport, a
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Table 2. Present OD Matrix Used in
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RMS(Root Mean Square) error rate Ro
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4. Results and Discussions In trans
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The highest LOS we come across was
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Abstract A Model for Travel Decisio
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2.1 Household description and its t
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individuals when faced same set of
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Change in Consumption Stock Need Ac
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Table 1 depicted that in almost all
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6. Conclusion The research reported
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Design of Stated Preference Experim
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travellers and what are the determi
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2.3 Choice of Modelling Framework A
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unattractive. The scenario hence fo
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4.2 Simulation Test The SP design w
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framework, particularly with regard
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Assessing the Implementation of Raw
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Figure 1. Master Plan of Rawalpindi
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does not give a holistic view of th
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Figure 7. Guided Development Plan o
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Below is a comparison of the estima
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Urban Design and Integrated Transpo
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empower local communities with easy
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Figure 1. Traditional Planning Appr
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trends of sprawls and constant addi
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7. Comprehensive Transport Artery S
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9. Conclusion Integrated transport
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Solving Transportation Network Desi
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that stochastic user equilibrium ba
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E x x 0 = a E x x 5 a a a 0 2 1 F 0
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4. Experimental Results Using the n
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that if a truncated density f x x 0
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Streamling of Road Safety Asghar Ab
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3.1 Statistics Table 1 Accident Loc
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The secondary signals provide motor
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S S P P P S P P P S S S ANNEX-A EXI
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Urban Transportation Policy Framewo
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of Karachi. In this regard, major d
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Table 2. Urgency Indices of Strateg
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4. Urban Transportation Policy Fram
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Urban Public Transport Problems for
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There‘s been an absolutely fantas
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6. Social and Behavioral Problems S
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Determination of Efficient Fare and
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2). All the gathered knowledge and
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Figure 3. Relationship between Cost
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practice as a hazard to the users.
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Table 6. Adjustments for Bus Recove
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Public Opinion towards Public Priva
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esidential area, income etc. The fi
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Table 2. Ageing of the Bus Fleet Ag
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6.1 Quality were from Shah faisal t
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facilitated through private public
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ITS Modeling and Analysis
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mostly highways or main arterials,
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of the link. If they are not on the
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Further more, 144 intersection node
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Therefore, interval of 07:00 AM - 0
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They methods proposed in this study
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the method used for estimation of t
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1 ( * T a T ) [ln( v f ) ( ) ] [ 1
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speed(km/h) speed(km/h) p cr (veh/k
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v f (km/h) p cr (veh/km/lane) a z l
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speed(km/h) a 2.5 exponent exponent
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Free-flow Travel time on the link T
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This says that travel time is equal
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The following paragraphs discuss th
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Therefore, the first two terms in t
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profile obtained for the Point-Queu
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Figure 5. 3 rd Case Travel time and
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Mun, J.-S.(2007), ―Traffic Perfor
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Activity-Based Trip Generation Mode
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area and parking area of a park, to
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educational activities are prominen
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inferred from the above results tha
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negative effect over the choice of
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Dependant Variable trips (employed
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1000 126000 0 20000 20 1 0 0 0 1 15
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Relationship between Land Use and T
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found that other factors associated
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Onipepeye 1092 1652.42 8.26 8 South
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Table 3. Correlation Coefficients b
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of transport planning into urban pl
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Standardising Transport Infrastruct
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Systematic and integrated road side
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4. Description of the Manual Standa
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4.4 Utility Corridor Utility corrid
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Punjab. The manual also provides gu
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designers and other practitioners a
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Master Plan 2020; Secondly there is
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corridor and completed the project
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9. Evaluation of Signal Free Corrid
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Causes Table 2. Comparison of Accid
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Software Architecture of a Distribu
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from one site mixed to or confused
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Figure 4. DDCS as a distributed too
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Table 1. DDCS Reliability Evaluatio
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environment was better comparativel
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Role of GIS in RTA Analysis : A Cas
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Table 1. Feature Layers Used for RT
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micro details i.e. local level info
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overall influence of RTA incidents
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The change detection in the Road Tr
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GIS Based Placement and Route Plann
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fatal road accidents in Missouri, w
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Figure 2. Spatial distribution of E
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so may be more travel time covered
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Table 3. Shows the Mode of Arrival
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100% 90% 80% 543 42 9 11 70% 60% 86
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Abstract Role of Traffic Network in
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1.2 Efficiency of GIS for Policing
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2.1.4.6 Thematic mapping of Geograp
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4.2 Spatial distribution of crimina
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5. Conclusion This study establishe
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