Numerical simulation technique was used for investigating water seepage problem at the Botanic Park Kuala Lumpur. A proposed sub-drains installation in problematic site location was simulated using Modular Three-Dimensional Finite Difference Groundwater Flow (MODFLOW) software. The results of simulation heads during transient condition showed that heads in between 43 m (water seepage occurred at level 2) until 45 m (water seepage occurred at level 4) which heads measurement are referred to mean sea level. However, elevations measurements for level 2 showed the values between 41 to 42 m from mean sea level and elevations for level 4 between 42 to 45 m from mean sea level. These results indicated an increase in heads for level 2 and level 4 between 1 to 2 m when compared to elevations slope at the level 2 and level 4. The head increases surpass the elevation level of the slope area that causing water seepage at level 2 and level 4. In order to overcome this problems, the heads level need to be decrease to 1 until 2 m by using two options of sub-drain dimension size. Sub-drain with the dimension of 0.0750 m (diameter), 0.10 m (length) and using 4.90 m spacing was the best method to use as it was able to decrease the heads to the required levels of 1 to 2 m

T Baharuddin, M F

Tajudin, S A A

Yusoff, N A

Z Abidin, M H

English

The main purpose of this study is to identify the factors affecting the continuance use intention of gamified m-learning applications by Higher Education Institution (HEI) learners in Malaysia.

Background 

Mobile learning (m-learning) has been a popular choice among learners in HEIs due to its convenient ‘on-the-go’ concept. On the other hand, embedding gamification elements in m-learning applications help in increasing the users’ interest in continuous use. Therefore, many HEIs have invested in producing their own m-learning products apart from utilizing existing m-learning applications that are widely available online. One of the challenges faced by HEIs is the low technology usage rates towards the ‘in-house’ developed applications, which affect the receptiveness of education stakeholders in investing or maintaining educational applications. Meanwhile, the lack of continuous usage had given a  negative impact on their academic-related tasks and performance. Hence, it is important to understand the significant factors that influence learners’ intentions in continuance usage of a gamified m-learning application. This will serve as an insight to the HEIs management regarding the needs and design that better suits their users’ expectations.

Methodology 

This study employed a correlational cross-sectional research design using an online survey. The participants of the final survey involved first-year students from one of the Malaysian public universities. For the final analysis, 269 responses were analysed using the partial least square-structural equation modelling (PLS-SEM) technique, which is a powerful multivariate analysis mechanism. The Expected Confirmation Model (ECM), which is a post-acceptance model, was extended with the pre-acceptance model named Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), to form the research proposed model that describes the continuance intention in using a gamificationbased m-learning application.

Contribution 

This research contributes to the body of knowledge and helps better understand users’ continuance intention in the post-acceptance phase of the gamified m-learning application. It exposes information at the individual level, regarding the continuance intention of using an m-learning tool that is equipped with gamification elements. This will mostly benefit the educational resource developers in the HEIs in producing effective ‘in-house’ learning tools.

Findings This research develops a theoretical enhancement of the Expectation Confirmation Model (ECM) that affects the HEIs’ m-learning resource developers and management, dealing with IT-related behaviour. Moreover, a solid continuance usage intention conceptual model, which incorporated two important models, was also introduced. Out of all ten hypotheses, only two were not supported that are related to factors facilitating conditions and social influence.

Those two factors negatively influence the HEI learners’ continuance use intention. Meanwhile, the core factors for satisfaction, which are perceived usefulness and confirmation, were found to be significant. Lastly, satisfaction was proven to mediate the positive path between perceived usefulness and the continuance intention of using the gamified m-learning application. Recommendations

for Practitioners This study offers insights into strategies that the HEIs’ management should perform in securing continuance usage of the ‘in-house’ developed m-learning

products. One of the strategies could be organising technology workshops that Roslan, Mohd Ayub, Ghazali, Zulkifli, Md Latip, & Abu Hanifah 99 will prepare their educators in implementing the institutions’ gamified teaching

and learning tools. Another highlighted issue is regarding the need for faculties  to design an effective approach to entice educators and learners towards applying new learning technologies. Recommendations for Researchers

This study contributes to the micro-level analysis of the continuance use intention of gamification-based m-learning applications by fostering the understanding of the phenomenon at the individual level. It is recommended that other researchers extend the research model by incorporating other theories, as this study was only based on two models (i.e., ECM and UTAUT2). Additionally, a

longitudinal study could be another approach that enables researchers to collect much richer data that includes a wide array of background characteristics or control variables. Another suggestion would be applying related factors that may contribute to the discovery of effective gamified m-learning application designs. Impact on Society The findings of the study show the importance of confirmation made by the applications’ users towards usefulness and usage satisfaction. Confirmation and perceived usefulness also have an increasingly similar impact on users’ satisfaction with the application and their subsequent continuance use intention. It is also revealed that easy-to-use products are commonly expected nowadays, as users might be reluctant to spend much time on them. On the other hand, for a specific gamification-based product, it is also expected by the users for it to be capable of giving an ‘enjoyable’ experience, hence motivating continuance usage. As a result, an effective gamified m-learning application or product will be able to be used by Malaysian HEI learners if the developers and stakeholders develop and evaluate the usage of their products with the consideration of the information provided by this research. Future Research Future studies could include respondents from other diploma programmes, resulting in an in-depth analysis. It is needed to support the generalizability of the findings in this study by considering larger populations from all different programmes. In addition, similar research can be done based on different circumstances; for instance, use of the gamified m-learning application during the incampus physical classes instead of virtual classes (online), which might influence the users’ perception in terms of the social influence and facilitating condition

Roslan, Rosfuzah

Mohd Ayub, Ahmad Fauzi

Ghazali, Norliza

Zulkifli, Nurul Nadwa

Md Latip, Siti Noor Haslina

Abu Hanifah, Siti Syuhada

UTHM Institutional Repository

This content has been downloaded from IOPscience. Please scroll down to see the full text.Download details:IP Address: 103.31.34.2This content was downloaded on 26/04/2017 at 06:42Please note that terms and conditions apply.Simulation of Sub-Drains Performance Using Visual MODFLOW for Slope Water SeepageProblemView the table of contents for this issue, or go to the journal homepage for more2016 IOP Conf. Ser.: Mater. Sci. Eng. 136 012014(http://iopscience.iop.org/1757-899X/136/1/012014)Home Search Collections Journals About Contact us My IOPscienceSimulation of Sub-Drains Performance Using Visual MODFLOW for Slope Water Seepage Problem                 M F T Baharuddin1,2, S A A Tajudin1,2, M H Z Abidin2,1 and  N A Yusoff 2,1                                1 Research Center for Soft Soil, Universiti Tun Hussein Onn Malaysia, 86400 Batu                      Pahat Johor, MALAYSIA                                2 Faculty of Civil and Environmental Engineering, Tun Hussein Onn University, 86400    Batu Pahat, Johor, MALAYSIA                        E-mail:  mdfaizal@uthm.edu.my   Abstract. Numerical simulation technique was used for investigating water seepage problem at                      the Botanic Park Kuala Lumpur. A proposed sub-drains installation in problematic site location                       was simulated using Modular Three-Dimensional Finite Difference Groundwater Flow                       (MODFLOW) software. The results of simulation heads during transient condition showed that                       heads in between 43 m (water seepage occurred at level 2) until 45 m (water seepage occurred at                       level 4) which heads measurement are referred to mean sea level. However, elevations                       measurements for level 2 showed the values between 41 to 42 m from mean sea level and                       elevations for level 4 between 42 to 45 m from mean sea level. These results indicated an increase                      in heads for level 2 and level 4 between 1 to 2 m when compared to elevations slope at the level 2                      and level 4. The head increases surpass the elevation level of the slope area that causing water                       seepage at level 2 and level 4. In order to overcome this problems, the heads level need to be                       decrease to 1 until 2 m by using two options of sub-drain dimension size. Sub-drain with the                       dimension of 0.0750 m (diameter), 0.10 m (length) and using 4.90 m spacing was the best method                       to use as it was able to decrease the heads to the required levels of 1 to 2 m.  Keywords: Numerical simulation, seepage, modflow. 1. Introduction Occurrence of water seepage on slope face might be caused by presence of high pore water pressure in subsurface soil strata. Measurements of high pore water pressure always related with several times of heads observation on site that required a lots of number piezometers installation. This works involved time consuming, expensive cost and limited data coverage. Those limitations have created some gap of methods selection which be able to fulfill several considerations that related to cost, time and results quality [1, 2, 3].            Thus, in order to overcome those limitations mentioned, numerical simulation technique was used for investigating groundwater seepage occurs at Botanic Park of Kuala Lumpur. Furthermore, the sub-drain remediation technique approach for resolving a groundwater seepage problem by using simulation technique was also presented.      Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/012014Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distributionof this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Published under licence by IOP Publishing Ltd 12. Method and Methodology  2.1 Site description and conceptual numerical model The study conducted to understand groundwater seepage occurrence at Panggung Anniversary slope area as shown in Fig 1 and Fig 2. The conceptual model consists of a graphic representation of the groundwater flow systems, usually in the form of a block diagram or a cross section [4]. Conceptual model was developed with few assumptions on the aquitard (sandy silt) layers and hydraulic properties. The model boundary condition was extended to the north and south of the Panggung Anniversary location (Fig. 3). Boundary condition for numerical simulation in the north and south area were bounded with constant head boundary. The model was adjusted based on the measured water levels in the study area. Based on that data [5], the aquitard layer is generally formed by a medium to coarse grained SAND with dominant SILT material. The thickness of aquitard ranging from 13 to 25 m and assumed as unconfined layer, while at the bottom is the bedrock which consists of inter-bedded shale and sandstone that can be encountered at depths ranging from 13.0 to 25.0 m. Hydraulic conductivity in this study area ranging from 1.48 x 10-7 to 3.50 x10-8 cm/sec with an average of 9.25 x 10-8 cm/sec.                                                  Figure 1. Study area and boreholes locations.   Figure 2. Location of groundwater seepage occurrence at Panggung Anniversary site. Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/0120142   Figure 3. Conceptual model of numerical modelling at Panggung Anniversary site.  2.1 Numerical model setup Three-dimensional representation of the site was created in Visual MODFLOW. The development of input files was compiled using Visual MODFLOW® (Version 2003.3.1.0.85), a commonly used data preprocessor to accelerate and facilitate the development of the MODFLOW model. This model was created as a 141 m x 147 m area in the x and y directions (east–west and north–south directions, respectively) (Fig. 4). Topography model (the first layer) was imported from elevation data for the wells (BH1-BH4) and surface elevations of the site generated by the digital elevation model and by field survey with the use of theodolite (Fig. 5). Relative elevations of water level monitoring points were determined using a total station theodolite. The water table in the model was referred to indicate sea level (rectified skew orthomorphic). This configuration allowed the placement of the piezometer screens in the model immediately at the terminated borehole depth.   2.3 Model parameters Hydraulic conductivities of model layer was estimated from the analysed data of permeability tests from BH2 and BH3. Single layer model was assumed to have homogeneous hydraulic properties because the data were not enough to determine heterogeneity layer in this area.  Model parameters data such as specific yields (Sy), specific storage (Ss), total porosity and effective porosity values were estimated from data interpreted by previous study (Table 1). A value between 5% and 20% of annual precipitation was recommended as an estimate of recharge when data were unavailable [6]. Hence, recharge was set equal to 10% of the average annual precipitation after the revision throughout model calibration and validation processes. Recharge parameter of surface water into groundwater system was estimated by 10% of total annual rainfall at open area [6]. Meanwhile, zero value of recharge parameter was imposed in closed area of Panggung Anniversary.   Evapotranspiration values was estimated using 1.44 times by total annual transpiration at open area. Meanwhile, zero value of evapotranspiration was imposed in closed area of Panggung Anniversary [6].  Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/0120143 Figure 4. Grid mesh refine and area dimensional.   Figure 5. Surface elevation and boundary of study area.   2.4 Boundary Condition Constant head boundaries were assigned for the northern and southern edges of the modelled area which are bounded by groundwater head of BH1-BH2 (south) and BH3-BH4 (north). The heads in the model was referred at mean sea level datum. This depth was on average 5 m below the ground surface. The highest heads located at the south area with an average head level of 48 m referred to mean sea level meanwhile the lowest heads located at the south area with an average 38 m referred to mean sea level. The model setup for the remediation technique were applied Drain, Wall and Pumping well Package where are contained in Visual MODFLOW software.  Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/0120144Table 1. Input parameters for the model and simulation strategies for this study. Parameters Value Kx (cm/sec) 9.25e-8 (average value from permeability test average conducted at BH2 and BH3) Ky (cm/sec) 9.25e-8 (average value from permeability test average conducted at BH2 and BH3) Kz (cm/sec) 1e-9 [7] Ss 1e-5 [8] Sy 0.8 [8] Total Porosity 0.3 [9] Effective Porosity 0.15 [9] Recharge (mm/year) 220 (10% of Annual Rainfall) and 0 at Panggung Anniversary [6] Evapotranspiration (mm/year) 500 and 0 at Panggung Anniversary [6] Conductance (m2/day) 0.00094 – 0.00562  2.5 Transient groundwater flow simulation and calibration The equation for groundwater flow through the porous media used in the model can be written as a partial differential equation: ∂∂x(Kx∂h∂x) +∂∂y(Ky∂h∂y) +∂∂z(Kz∂h∂z) = Ss∂h∂t−W      (1) where Kx, Ky, and Kz are the hydraulic conductivities in the three orthogonal directions (m/s or ft/day), h is the head that drives the flow or the saturated thickness of the aquifer (m or ft),W is the volumetric flux per unit volume and represents the source/sink term for water or withdrawal (m3/s or ft3/day), Ss is the specific storage capacity of the porous medium (dimensionless), and t is the time (s or day). When the water withdraws, –W = R, where R is a general sink/source term, it is defined to be intrinsically positive to represent recharge (defines the volume of inflow to the system per unit volume of aquifer per unit of time (ft3/ft3/day or m3/m3/s)).The Visual MODFLOW model was run at transient state then calibrated to hydraulic heads recorded on a weekly basis from 16 April 2015 to 7 May 2015 at four standpipes (BH1-BH4) for calibration. For each transient model run, an analysis of the observed versus computed water levels was conducted to determine the accuracy of the simulation.  3. Result and discussion  3.1 Calibration results for groundwater flow simulation The assessment of the model fit was quantified by the simulations, computed as the difference between the simulated and the observed hydraulic heads. For this model, the estimated average of mean absolute error (MAE) is 0.5 m, the root mean square (RMS) is 1.2 m, and the normalized root mean square error (NRMS) is 12%, which indicate a well calibrated model. Overall, the calibrated model is able to simulate water levels and water level fluctuations sufficiently to evaluate the options of remediation approach on groundwater seepage problem.   3.2 Sub-Drain  Sub-drain was proposed to overcome the water seepage problem at levels 2 and 4. Two options on the sub-drain dimensional design were suggested with taken consideration of materials is easy acquired in market.  Option 1:- 0.0750 m (diameter), 0.10 m (length), 4.90m (spacing) Option 2:- 0.0375 m (diameter), 0.10 m (length), 4.90m (spacing) Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/0120145Sub-drain using option 1 showed heads result between 41 and 44 m at level 2 and 4 (Fig. 6) respectively. Drawdown that is the difference in the head between the initial head (without sub-drain) and the head with sub-drain (option 1) showed difference of 1 – 2 m. Meanwhile for option 2, simulated head results showed heads between 42 m  at level 2 until 45 m at level 4 (Fig. 7). Drawdown showed difference of 0 - 1 m for option 2 and also indicated that the drawdown was smaller compared to option 1. It was suggested that option 1 with the use of sub-drain of 0.0750 m (diameter), 0.10 m (length) and using 4.90 m spacing can be use in the remediation of the water seepage. This option can reduced the heads in optimal values to prevent settlement of the stage structure.                                                 Figure 6. Option 1 (Plan View).            Figure 7. Option 2 (Plan View).  4. Conclusion  The results of the analysis using numerical simulation groundwater flow (Visual MODFLOW), has succeeded in determining the cause of water seepage problem in the study area. Water seepage occurrence at Panggung Anniversary was caused by the elevated groundwater heads compared to the elevation levels of the area. In order to overcome the water seepage occurrence caused by the increase of heads level, the reduction of the head levels between 1 – 2 m need to be done. The usage of the sub-drain with dimensional design of 0.0750 m (diameter), 0.10 m (length) and using 4.90 m spacing was able to reduce about 1 – 2 m of the heads level and is the best option of remediation to be considered. The usage of dimensional design remediation with sub-drain is the safest method to be use to prevent any structure settlement from occurring.  Reference [1]   Zainal Abidin M H, Tajul Baharuddin M F, Zawawi M H, Ali N M d, Madun A and Ahmad  Tajuddin  S.A. 2015 Groundwater Seepage Mapping using Electrical Resistivity Imaging,  Applied Mechanics and Materials 1524-1534. [2]   Zainal Abidin M H, Saad R., Ahmad F, Wijeyesekera D C, Matarul J, Tajul Baharuddin M F, 2013 Mapping of Geotechnical Data Using Seismic Refraction Studies, AWAM International Conference on Civil Engineering & Geohazard Information Zonation 1-9. [3]  Zainal Abidin M H, Saad R, Ahmad F, Wijeyesekera D C, Tajul Baharuddin M F, 2015 Correlation Analysis between Field Electrical Resistivity Value (ERV) and Basic Geotechnical Properties (BGP), Soil Mechanics and Foundation Engineering 117-125. [4]   Anderson M P, Woessner W W, 1992 Applied groundwater modeling; simulation of flow and advective transport. Academic Press, San Deigo381. [5]  IKRAM, 2015Seepage Problem and Groundwater Studies at Panggung Anniversary, Taman   Botani, Kuala Lumpur, IKRAM Preliminary Report,. [6]  Waterloo, Visual MODFLOWv 4/1 User’s Manual. 2005 Waterloo Hydrogeologic Inc., Waterloo. [7]   Todd D K, 1980 Groundwater Hydrology (2nd ed) Wiley India Pvt Ltd, 556. [8]  Younger P L, 1993, Possible environmental impact of the closure of two collieries in County   Durham. Journal of the Institution of Water and Environmental Management 7, 521-531. [9]  Freeze RA and Cheery JA, 1979 Groundwater Prentice Hall College Div. ISBN-13: 978-0130617309  604. Soft Soil Engineering International Conference 2015 (SEIC2015) IOP PublishingIOP Conf. Series: Materials Science and Engineering 136 (2016) 012014 doi:10.1088/1757-899X/136/1/0120146

INVESTIGATING FACTORS THAT AFFECT THE CONTINUANCE USE INTENTION AMONG THE HIGHER EDUCATION INSTITUTIONS’ LEARNERS TOWARDS A

GAMIFIED M-LEARNING APPLICATION

Applied Meclwnics and Mderials Vols. 256259 (2013) p 187I-1881O(2013) Trans Tech Publicaions, SryiEerlanddoi : I 0. 4028hvw'w.scientifrc. net/AMM.2 5 6-2 5 9. I 87 IPavement Primary Response using Influence Function and Peaklnfiuence FunctionBuhari R.r'" and Collop AC.t'otFaculty of Ciuirt and Environmantd Engineedng, Unlversiti Tun Hussdn Otn llalaysb (UTHM),864{Xl,Parfr Raia, Batu Htet, Johor.tunirersity of Noilingham, UK"rosn@lthm.edu.my, bcoflopt@rmingham.ac.ukKryrcrdc vefiide q/nandc lcd, qu*terfud( rndel, pdmary response, foffsrce func'tion,peakinfluene furdion.A6gtrrc6 It was idelrtified in prwious research that errors in theoretical damnge much associatedwith the influelce fimction cal,culetion. Thus, this papsr prcs€,nt the effcient pediction of primaryr€spolls€ due to dynamic vehicb loading using influeirce function and peak influe,nce functionrpp*on. In odei to provide tte realistic loading condition, dfmamic road response model withiAeanseA bads re,prese,ntative by maftemdical quarter-tnrck model widr two degrcc of fireedom wasexcited by a random road srlrfrcc profrle uilrich equalty spac€d points along the simulated road withvarious Aiferot speeds, Cmsequentty, the simplified computntional appaoh (peak influencefunction method) was identified only a few points gcve a small differcnt cunpar€ wift the influencefimction method fo,r along the lmgihdinal distance. In order to identis the impact of both methods,further implementation was dre to calculate fdigue damage ftorizontal tensilc strain atthe bottomof a bouni layer) or nrtting damage (vertical compressive shain at the top of the subgrade layer)predicted by constant load moving at vuies spd. It was found that the ditrerences in response are'particufarfy $nall and increased *caOity as the increasing of the vehicle Seeil It was conclude thatihe simpliiy calculdion was able to pr€dict strresses and strains sufficientty accurately and ideirtifiedrelatively smell eimrs into the pavemcnt damage prediction. He,nce the simplification in particularmuch reducedthecmputationtime sufficitnttyand minimized the compserres$rccs significantly.IntroductionResult from prwiols research showedfrd dynmic wlrccl loads (DWI-s) dle an important faotor inpavement failgre and fatigue damage tl-fl. Thus, it is important to consider dpamic effects inpavement desrgp because Apt-io p""u-*t rcspons€s' srf4 as displaoements' $11P and snessesr* U" sigdficantty Aiferent fiom their static counterparts [3-5]. Previous research has also shownth* peak?orces rylied by a fleet of hear.y goods vehicles se d distributed randmly along the roadbut are applied tosimilario".tio* t6l, Iil;ls]. This b8s bo€n t€rmd spatial repeatability and meanlthat foad failure will be governed ti i*atitea pe"t s in fte dmage prcfile rafter ! P the mean lweldamage tSl. Hardy and Cebon shdiedft€ importanceof the dynamic respons€ of florible pavementrt".t*-; primry r3spons€s due to drynamic, moving wh€el loads t9l- Thcy concluded that ther€spoil;3 of tire -"i *"r sensitive to vehicle speed but ttd the effects of loading frequency were,-Al Consoquenfly, in most sitntions a quasi-static mo&l of the road stnrctre was consideredadequde.Loding ConditionsIn order to consider a realistic loading mndition, a simple quarter-tnrck vehicle simuldion with tlodegrees of freedom (as Sown in Fig;l md Table l) was excited by a rmdom road surface profileuft-ioh is described ti O" elevdion "f uq*tty spaoed points along the road. The quarter-tnrck modelhas been used by many previous researches 1i1, [S1, t9-10]. This simple model captures many of moreS,ffi.ffir#t#ffii;iffi'frStt**'.prodrcdatrrcnfr'dh.nvbnno.'bv.'uns*wlhoutth'slt'rFnrdr'londrrP'1872 Advances in Civil Engineerlng llimportant charac"teristics of dlmamic tyre forces even though it does not contain detailed suspensionnonlinearities and complexities of sprung mass motion that are qpical of heavy vehicles [2].State-space equations were generatod for the quarter-tnrck model which solved in the time domain.Eig.2 shows the input surface profile corresponding to a road with an IRI of 2 and Fig. 3 shows anexample ofthe resulting DWL for a vehicle speed of 20mls. The initial pavement surface profile weregenerated by applying a set of random phase angles wiformly distibuted between 0 ta 2n, to a seriesof coefficie,nb derived from the desirad roughness qpeced fusities (see [] for further details).vadtaHt:v+Fig. 1. Quarter tnrck vehicle modelTable 1: QuarGr +uck model parametersPrnncterr Symbolc VduesSoruncmass mu 8900 ksUnsonmsmass ms 1100 ksSusoensim uing ks 2lvlN/mSusoeirsion damper kt 40kl.IVmTire sprins cs 2 MN/mTire damoer ct 4kl.Is/mEEcoEoIJ.EC\l3oFig. 2: Initial surface ProfileApplied Xechanics and taterials Vob. 25&259 {87311zJEolI.EF.9Eocol0 10506070Didame/mFig; 3: D5rnamic ufreel load at 20mls.Pevcmcnt StncturcA typical flexible parrement sEuctre was modelled as a three layer system wi6 6e load uniformly,peri"a on thc *ti*" or,€f, a circuh contact area 03m in diemeter. Thc lr''Er cofigrration in thissiucy compriseo a 0.2m asphsltic la;rcr over a 0.2m a granular subbase layer ovcr the natgral soilGubgnde)uftich is assumed infuite invertical extenlAll lqrersreassrmedtobc infmite in horizontal srd€nt, homogeneous, tlgre!*lc and isotropic'poisson,s ratio was talcen to bG 0.35 for the asphaltic layer and 0.4 for the unbormd layers' Thestiffiress modulus of the ssphdtic la5rcr was taken to be 6.9GPa' 7.9GPa and t'7GPa for vehioles@s of lgm/s, 20m/s and 30 m/s rcspectivety. The stiftcss mdulus of tte $fibose and zubgradewene taken to be lOOMPa md'f0MPa respectively'Inportrre of Spocd ir Prinrry Rcrporre DetcrnirelionDeterminingprimaryrpsponse involves simulatingthe Dtr4,s geirerated by avehicle travelling over a,prrifl"A rdi p*nfu. 1.wo different methods foicafcuming 6€ prinry rcspms€ h8s been studied;the influence function mcthod md thc peak influcnce fimctim method at three vehicle speeds (10, 20and 30m/s).The effect ofvehicle speed m pavemcnt rcsponse has becn the focus of sev€ral sndies and seve'ralauthors have concluded in* *,t* t" ufreel ntt* more quickly ov€r & specific location on the roadthe time available fm plastic (pemranent) deform*ion to oocrr is reduced and therp will be reducedroaddamage [6]. Howlver, C"U* perfumedatheom*ical stdyinrvhichbshou/cdthdtmder someconditions, Dwrs cm increase with vehicle speed and thus increase theoretical road damage [2]'Cryenes notod ttat the increase in DWI-S with sp€ed is compensated for by 6e $orter duration of theload and there is little additimal iH€8sG in tte avemge "n a.po along a road rising fr'om dpamictnrckbehaviour [6].Pevencrt PriuY ncrPor*Curr€nt analyhcal (or semi-ana$tical) povemotdesig! proccer€s relde fatigue damage and ruttingto the horizontal ternsile shain d th€ bofim of a UlnA tErcrs and the vertical compressive strain atthe top of the subgrade layer rcspcc'tivety which are tlryicatty catcucea using a l8y€rcd elastic model'Alternatively, Odeinark's fr4AfioA of fouivatent Thicknesses G\mD can be used to transform alayered slrstem into a half-spoce ana golsin€sq's equdions cm be usd to calculatc stnesses' stainsand displacements [l l-12].1871 Advanceg in Civll Englneerlng llThe resulting vertical and horizontal oomponents of stness and stain calculated using MET due to auniformly loaded circular aiea are shown in Figure 4. It can be seen from this figure that, as expected,the radiJ sftain is tensile at the bottom ofthe bituminous layer and the vertical strain is compressive atthe top of the subgrade.Influence Function MethodThe pavement primary responses shown in Fig. 4 have been calculated due to a particular ap'pliedload. Since the load will vary along the road due vehicle dpamics these primary responses have beennormalised by the applied load and are termed influence functions. The influence functions are thencombined o'ith the DWLs to give the r€sponse/ at a particular location.r as a fimction of time I usingthe following equation (see Fig. 5):y(:LtFF(t) ' I(V, x-Vt) (1)Wherp t(y,x-Zr) is the influence function for speed V and distance x-Yt from the point ofapplication ofthe load. Figure Fig. 6(a) and 6(b) showthe results of this calculation for a single pointorr'Oe toad surface in terms of stain "t tl" U"s" of the asphalt layers (Figure 6(a) and strain at the topof the subgrade (Fie. 6(b)).E00700600300200t000-100-20/J€{n-{00€00.=Eae(,EOEgu,gIgE!t€ItcEI-1 {500.5 1Rdblffirce (m)Figpr€ 4: Critical $iainsFig. 6: Influenoe fimction under&e loodApplied techanics and taterials Vols. 256-259 1875ta*bbncert \---r/_\\l,(,'l.t;l.'lI I'\\t,. l-r' ,'1't&lir :i a+2)'clo+tt /n -7r2r3rlPerk Influence Function MethodA fu(her simplification can be made to the influence firnction method is the peak rcsponse occursdfu€ctty over the point of int€rest In ftis case, Equatim [l] reduces to:y(xFF(x)'I(V,x) Q)To qramine 6e erffects of ftis simplificdim, resufts frm simoldions rmdertakeir using Equations I I ]d f2l have been compared using vehicle spccds of l{ds, Z0m.ls and 30m/s. Fig- 7(a) shows thep"oi"iry differpnce incompressive *rainmtopofthe snbgradebetweenthetwomeilhods at20m/sio, eactr-point along the road^and Fig. ?(b) for 30m/s. It cm bc seen th* for the lO(hn of road lengthsinulate4 the ma:rimgm difference are small with appro:rinely lYo fq a vehicle s@ of 10m/s,| .SYo fot I vehicle ryeed of 20mls and l.7o/o for vehicle speed 30tn/s.ffisotlo5oilmglq, ltx,OHrc.(n)o)aaaoc2€aI!e€oFig. 5: Primary respmse vften loading d point i and i +ni!llrllI'trli,IIliiti5{t o{876 Advances in Civil Engineering lltoIcE€o"o to 2o 30 fi** OT 70 80 e0 1(n(c)Fig. ?: Differenoes compressive strains 'sitg influence fimction method 8nd peak influe,nce functionmetrod using vehicle specd d lOm/s, 20m/s and 30m/sFrdguc nd Rnttiry DenryeFatigue cracking and nrting are the two principle type of distress considered in this study. In fatiguecracfing mime crltcrim, G db*"blu number of load repaitions ( rr sat causcd fuigue cracking isrelated to th" t nsil" sfiain (q) at the bofiom of the asPhdtic h5rcr as:Nr: kr(q)P (3)The maja factors ftd affect the constmts tr and tz ue the vohmctric pnoportion ofbinder Za and itsinidaf Sonening Point SP; The fatigrre constants tl md tz for tjpical were dlermined from theequatim giv€,n-in Brrorvn and Bruntm (lgg2r. For nrfiing danage the allowable number of load"i"titir"iis relded wi& the vertical compression strain m try ofthe subgrade using:Nr= k(e")-k' (4)Where, tt and k are constants which can be calibrated to match the field obse'lsations. Fig' 8(a)shows the difference in rutting between the two methods for a vehicle speed of 30m/s. It can be seento. thi, figur€ that the.oi.* difference is approximatsly 5.7Vo which is greater than thedifference in subgrade strain because of the "*poneoi used in Equation (4): T: atral maximumdifferenc€ in preeictea fife is approximatety O.OZS qillion cy- cles (Fig' E (b))' There were nodifferences found between the trno-methods for fatigue damage. This is probably due to Ore fact thatthe fatigue influence function is narrower than G rufting influe'nce fimction which means thatchanges in dpamic load over are likelyto have more effect'IIIIIlltltfrl ";1tll!Il1LlIApplied techanics and taterials Vols.256-259 1877t!2€o-5=gTEo41020304050607I,0s1@Dilttc(m)(a)Fig. 8: Differtnces in percentage ad in gcdicting life fs 20 m/sFig. 9(a) and 9ft) show similar results for a simulation s@ of lOm/s and 20mls. It can be seen fromFG. 9(") and 9(b) trd fte differcnces in prcdictd life befween the two methods has increased fromrpg-ii-C"ly 0.007 millim cycles fi)12 million rycles. This sbws trct ft€ difference befireen thettnl methods is significantly atrccted by 6e sped of the vehicle with higher vehicle speeds increasedthe magnihrde ofthe difference.70 80 00a5E;05€oeC.P-gaaEeoDidrr(m) (a) O)Fig. 9: Difference in predicting life for l(hn/s and 20 m/sFig.l0 shows the permanent deformation profile calculated by using both approach at distance 4l toaim.rnthis figure it shown the pote'ntial different appears among the point situated at the higherslope wherc the permanent damage calculated among the nearest point is considerable differentcompare with others Points.1878 Advancer In Givll Engincerlng lllnfr.erce fmdbn method- Ped< turlLpra findiln m€Olod0.450.40.350.3o.I('da6C=-('}EovEPsJEE8eEtzDbtance (m)Fig. l0: Number of allowable load to pennan€nt deformation profile calculated usingTwo differentmethodsConsidering the reality of taffrc loading condition will contain a distribution of axles load betweenunladen *I rury hden, the study was-further to take into account realistic a:de load variation. Toachieve this adjustmen! the spnrng mass (see Table 1) was divided into two other weight bands of l/3and 2lj of fuliy laden. As " t"r"ft bading of ll3 of fully laden were shown an increasing of thedifference behneen bottr method and in number ofpoint contibuted (Fig. 11(a) and Table 2). It showsthat there has a considerable increasing in manimum differences for vehicle loading 1/3 and 213 offully laden when fruck moving at 10m/s, 20m/s and 30 rn/s'In addition, considerinl the effect of material properties, there werc two bituminous propertieseffect on the perce,ntage diffeipnces between the two methods were investigated. Fig. 11(a) showsmaximun differences in nrtting for pavement surface layer using bitumen grade 50 with bitumenconteirt l0.4vo, ll .7% and 13 .li/owhen tuck moving at 10m/s, 20rn/s and 30m/s- It can be seen fromthe figure that the maximum differences is higher for lowq bitumen content at the same tuck speedand hlgher for higher tnrck speed. The same p"tt"- in Fg I 1(c), the higher pavement surfacet"mp"iutrre result the lower maximum diffeiences. The reason for this is due to the fact that highercomprssion strain result from higlrer temperature is narrower than compression strain at lowertemperature for the same tnrck rp*a "t 20mls (Fig. l2(a)). It can also be seen from Fig' l2(b)' thehigher the tnrck speed, the compiession strain are getting lower, although for the entire length of theroad some nodes will result high€r compression srain (narrower; as the tnrck speed become higherJo" to dynamic loading. eruroigh, in fact increasing considerable different among the nearest pointfor highlr mrck speeifikely to give more effect. As a result more points along the pavement arediffereirt using both methods (see raurc 2). consequently, in all cases the higher tnrck speed, themanimum differenoes are become higher.1880 Advances In Clvil Engineerlng ll.EI-ellEgEac.9taeeEoocEaellEcEEcooOeeEoC'a) O)Fig 12: Compession strain for varying condition; (a) different t€mp€rdtr€s' @) different truckspeedsTable 2: Numbcr of nodes shows in differencesVariablcs Peimanent deformdion failure' \lVehicle speed(m/s)l0 20 30t Truck loadingConditionl/3 offultvlden 218 339 4122/3 offirlbladen 168 ta 202Fullv lade,n 46 54 572. Bibmeir oomentto.4% 36 49 65ll.7 Yo l3 35 53l3.l Yo 2 22 313. Surface larer teinPera{Uql0c 36 49 65l5c 2 2l 2920c 0 0 3Conclusionc(i) Nanower compressive $rains will reduce the maximnm difference of ruaing cal'culded usinginflue,nce fimction and peak influence function and hence the number of nodes in contibution'(ii) Lower truck loa4 high€r surfroc ffiP€rdr€ and lowtrtihrmen content in bihrminous layerincrease fre ditrerenJ,s in compression strain on top of tre subgrade layer by using influencefimction and peak influence function method'(iii) Increasing in compression strain differences result in increasing the difrerences in pennanentdeformation.(iv) No difference r€surt€d in te,nsile strain at the bottom of the asphaltic leyer calculated using bothmethod for low vehicle speed and each loading condition and heirce the fatigue damage'(v) The differences between the two methods were inq€ased as the tnrck moving for higler speed forall cases.(vi) The apcwacy in predicting pav€m€,lrt damage using peak influence firnction merthod isappropriate due to low differences in all cases'0./t O0 0.ERadd(l3ltr(m) 0.f 0.6 0.ERsdCDLltr(m)Applied techanics and tabrlals Vob. 256-259 1881AcknowlcdgementThe althors would like to acJrnowledgs fte University Tun Hussein Onn Malaysia and Ministry ofHiS€r Leaming for their cmtrih*ims.Refercnccs[1] Collop A.C., Effect of Traffic alrd Temperanre on Flexible Pavement Wear, PhD thesis, (1994)Cambridge University Engirering Deprtment Camffige LrK-[2] Cebon D., Vehicle - Gmuod Road hage: a Rwiew, Vehicle S]dcm Dlmmic (1989), l8'107-150.[3] Sun L., Computcr Simulation and Field Measurement of D5namic Pavement loadingIv{affrematic and Computcts in Simuldi<n, (2001)' 56,2y1-313-[a] Sun L. and K€nn€dy T.W., Specfial Analysis and Parametic Shrdy of Stohastic Pavement loads,Journal of Engineering Mechmic QUiiz)' 128, p 31Y327 -[5] Sun L. and llo Feiguan, Nm-stdionary D5mamic Pavement L@ds G€neraf,ed by VehicleTravelling at varying spee4 Joumal of Transportdim Engineering Q007).[6] Gyenes f, tr{itcnen CGg, philip SD.,Dynamic Pavement Lod and Tests of Road Friendlinessior Heayy Vehicle Sgspensim., Thfod Int Symposiun on Heavy Vehicle Weights andDimensions, UK (1992), Thmas Telford.t7l Belay A., Obrien E- and ifu"s€ D., Truck Fleet Model fc Design and Assessment of FlexiblePave,rnen! Joumd Of Sound and Vibration' (200t)' ?ll,116l'1174'[E] Cole DJ, Cebon D., Truck Suspension Desig to Minimise Road Damage, MechE- J. Auto. Eng.,(1996), Vol. 2lO 95-lO7-tql Hardy nt-S. A., Ce,bon D.,Importance of S@ md Frequency in Florible Pavement Response,J. Eng. Meoh. ASCE, (1994),120(3\,4634E2.[10] Sun L]and Kennedy T.Iil., Spectat inatlais and Paramsic Study of Stohastio Pavement loads,Jorrnal of Engineering Mechanic' (zWZ), I 28, pp 319-327'tl U Ullidtz P. Pavemcnt Anat5nis' Elscvier.(1987)'ifZi UUiau p. and Ekadhl p., fuU Scale Testing of Pavem€Nrt Response, P-"""dPg of the FiffhIntern*ional Cmferencc on tfoe Bcaring Capocity of Road and Airfields, Trondheim.(1998)'

Simulation of sub-drains performance using visual MODFLOW for slope water seepage Problem

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Simulation of sub-drains performance using visual MODFLOW for slope water seepage Problem

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