60 research outputs found
Factors Affecting Resilient Behavior of Subgrade Soils in Saudi Arabia
This paper presents a study of the effect of relative density and moisture content on the resilient behavior of subgrade soils in Saudi Arabia. Thirteen representative soil samples, representing subgrade soils from all over the Kingdom, were tested at two different relative densities (93% and 96%) and the corresponding moisture contents on the compaction curves in addition to the optimum moisture content and maximum density. The results show that the resilient behavior depends on soil type (fine grained or granular) as well as moisture content and relative density. The study shows that both moisture content and relative density governs the effect of deviator and confining stresses on MR behavior. The study emphasized the importance of using a model that describes correctly the dependency of MR on both confining and deviator stresses. Keywords: resilient modulus, subgrade soil, modelin
A Model for Asphalt Concrete Modulus Prediction from Basic Mix Variables in Saudi Arabia
The asphalt concrete, being the upper layer in flexible pavement structures, is the most important layer as it largely controls the performance of flexible pavements. Therefore, characterization of bituminous mixes comprising asphalt concrete layers is essential in predicting pavement behavior under different loading and environment conditions. In this study, data on the basic characteristics of bituminous mixtures from 138 mixes was collected from the Ministry of Communications′ (MOC) projects and research reports. The main objective of collecting this data was to select an appropriate model that can be used to predict the bituminous mix moduli from the basic mix characteristics. First, the data was used to investigate the prediction accuracy of several widely used models in order to select the most appropriate one for the Kingdom’s conditions. The ability of all models to predict the modulus of local materials was found to be limited. Therefore, it was decided to develop a new model that suits the local conditions. Regression analysis, using the stepwise procedure was used to develop a model that showed a relatively high coefficient of determination (R2=0.86). The variables selected by this analysis were: percent air voids, percent asphalt absorbed by weight, asphalt viscosity at 70°F, asphalt concrete temperature, percent asphalt by volume of mix, and percent aggregate passing sieve # 200
Multi-linear Repair and Maintenance Cost Models for Tractors in Saudi Arabia
The relationship between the cumulative costs for repair, maintenance, the annual operating hours, tractor power and price, tractor age (years), and the rate of annual cumulative costs per kW-h was studied. Complete and accurate data recorded by Hail agricultural development company (HADCO) for 39 tractors were used in this study. The analysis showed that the average annual operating hours reduced from 1558 to 1338 as the tractor age (years) increased. Also the average annual operating hours increases with the tractor power except for huge tractors where their use was limited for high draft operations only. Based on the effect of different factors on the repair and maintenance costs, multi-linear models were developed to estimate tractor repairs and maintenance costs represented by the following function.
ATC = f(N,P,AHRY,kw)
Where:
[ATC: accumulated repair and maintenance costs, N, P, AHRY, kW tractor age (years), tractor price, accumulated operating hours and tractor power respectively.
The multi-linear models compared with exponential models which were developed in previous study. The comparison showed that there is no difference between the two models for tractors with power less than 80 kW and age of 6 years or less. But for other cases the difference from the actual costs ranged between 68.8 to 8% when the exponential models used, while the estimated cost was less than 2% of the actual costs when multi-linear models used for the same tractors
Prediction of CBR Using Dynamic Cone Penetrometer
California Bearing Ratio (CBR) value is very popular among highway engineers as a soil support value for pavement design. However, since CBR cannot be easily determined in the field, prediction of CBR values from other soil support tests such as Dynamic Cone Penetrometer (DCP) is a valuable alternative. In this study penetration depth (D) of the dynamic cone penetrometer from the laboratory prepared samples were correlated with laboratory CBR's for a number of different soil types ranging from clay to gravely sand. Unique models were found for each type of soil with good coefficient of determination (R2) and low standard error of estimate. The combined data gave also a correlation between CBR and D which compare very well with those obtained from other studies
Optimizing Yield and Quality of Silage and Hay for Pea–Barley Mixtures Ratio under Irrigated Arid Environments
The changing climate, water scarcity, reduction in the land area under forage crops, expanding ruminant population, burgeoning demands for milk and meat production and food security concerns all insist on a necessary increase in forage production and quality. Cereal–legume mixed intercropping offers a biologically superior option to boost herbage yield and quality of preserved fodder (hay and silage), provided that rationalization of the component crop’s proportional ratio is performed. Therefore, the current study was conducted to determine the forage yield and quality of barley (Hordeum vulgare L.) and pea (Pisum sativum L.) mixtures at the ratios 100:0, 75:25, 50:50, 25:75 and 0:100. The experiment was laid out in the regular arrangement of a randomized complete block design with three replicates. The results exhibited that forage quality was significantly affected by the mixture ratio. There was a significant improvement in protein, fiber rate and digestibility from the mixture. The ratios of barley and pea with 50:50 and 25:75 produced the maximum productivity and the best quality of forage. Regarding forage preservation, silage recorded higher contents of crude protein, ash and lower fiber contents than hay. Among seed mixtures, 0:100 ratio of barley–pea yielded the highest quality of silage with the maximum crude protein, ash and digestibility with lowest fiber contents
Prediction of CRR using dynamic cone penetrometer
California Bearing Ratio (CBR) value is very popular among highway engineers as a soil support value for pavement design. However, since CBR cannot be easily determined in the field, prediction of CBR values from other soil support tests such as Dynamic Cone Penetrometer (DCP) is a valuable alternative. In this study penetration depth (D) of the dynamic cone penetrometer from the laboratory prepared samples were correlated with laboratory CBR's for a number of different soil types ranging from clay to gravely sand. Unique models were found for each type of soil with good coefficient of determination (R2) and low standard error of estimate. The combined data gave also a correlation between CBR and D which compare very well with those obtained from other studies.Corresponding Author:
Prof. Talal Obeid Al-Refeai, Civil Engineering Department, College of Engineering, P.O. Box 800, Riyadh-11421, Saudi Arabia.
Email: [email protected]
A model for asphalt concrete modulus prediction from basic mix variables in Saudi Arabia
The asphalt concrete, being the upper layer in flexible pavement structures, is the most important layer as it largely controls the performance of flexible pavements. Therefore, characterization of bituminous mixes comprising asphalt concrete layers is essential in predicting pavement behavior under different loading and environment conditions. In this study, data on the basic characteristics of bituminous mixtures from 138 mixes was collected from the Ministry of Communications' (MOC) projects and research reports. The main objective of collecting this data was to select an appropriate model that can be used to predict the bituminous mix moduli from the basic mix characteristics. First. the data was used to investigate the prediction accuracy of several widely used models in order to select the most appropriate one for the Kingdom's conditions. The ability of all models to predict the modulus of local materials was found to be limited. Therefore, it was d~cided to develop a new model that suits the local conditions. Regression analysis, using the stepwise procedure was used to develop a model that showed a relatively high coefficient of determination (R2=0.86). The variables selected by this analysis were: percent air voids, percent asphalt absorbed by weight, asphalt viscosity at 70°F, asphalt concrete temperature, percent asphalt by volume of mix, and percent aggregate passing sieve # 200
Farm tractors breakdown classificati
Work orders for 40 tractors, collected by Hail Agricultural Development Company (HADCO), Saudi Arabia, were used in this study. Data for more than 1670 work orders were classified as repairs or maintenance. The relationship between tractor age and power on repair and maintenance costs was also investigated. A cost ratio (CR) term was developed by dividing the repair or maintenance cost by the tractor purchase price. This CR was used in all variables affected the repairs and maintenance costs. 51% of the work orders were classified as repair works while 49% were classified as maintenance jobs. The highest CRs were listed for both repair and maintenance. The 64 WJOs for transmission repairs had the highest CR, while electrical system repairs WJOs were 197 and had the lowest CR. That is because the costs of some parts were much affecting the CR and not the number of work orders. Similar results were obtained when calculating the classified maintenance CR. The repair CR was higher than that of the maintenance. Both repair CR and maintenance CR were directly related to tractor working life (age) and tractor power
An Instrumentation System for Measuring Field Performance of Agricultural Tractors
An instrumentation system is designed to measure the field performance parameters of the most common agricultural tractors and implements. The package is designed such that it can be shifted from one to another easily. Transducers such as load cell, PTa (Power Take Off) torque transducer, magnetic pickups, fuel flow sensor, and PRTs (Platinum Resistance Thermometers) are used to measure drawbar pull, PTa torque and speed, tractor speed and slip, fuel flow, engine speed, and temperatures of fuel and engine. Signals from the transducers are scanned and recorded using a datalogger
The Design of a datePalm service Machine
Dates are one of the most important crops in Saudi Arabia Many of the cultural Operations, and particularly harvesting, require the man to climb the tree and work at a considerable height above the ground. This is a dangerous and slow operation further compounded by a severe labour shortage.
The functions required of a date palm service machine are dethorning pollination, thinning, bagging pruning, harvesting individual dates and whole bunches and spraying for insect control.
In order to determine the size, reach and general physical requirements of a suitable machine a survey was carried out on 19 farms where nearly 1200 trees were measured. Ground profiles were also recorded to provide information on to required ground clearance and tyre size.
From this information the specification for a machine was proposed which should be able to service trees in most of the situation encountered. A prototype machine is now being constructed and will be tested during 1988 in Saudi Arabia
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