Neil N. Eldin

Measurement and prediction of the strength of rubberized concrete

Abstract Illegally discarded piles of automobile tires are sources of potential hazards. Current disposal methods are wasteful and costly as they require either consumption of landfill space or continuous costly maintenance. A solution to the problem of scrap-tire disposal is the potential use of tire chips and crumb rubber as mineral aggregate substitutes in Portland cement concrete mixes. In this study, some of the engineering properties of rubberized concrete were examined and a neural network was developed to predict its compressive and tensile strengths. Rubberized concrete was found to possess good esthetics, acceptable workability, and a smaller unit weight than normal concrete. However, rubberized concrete did not perform as well as normal concrete under repeated freeze-thaw cycles. It exhibited lower compressive and tensile strength than that of normal concrete. Unlike normal concrete, rubberized concrete had the ability to absorb a large amount of plastic energy under compressive and tensile loads. It did not demonstrate the typical brittle failure, but rather a ductile, plastic failure mode. Test results were analyzed so that a model can be developed to predict the strength of rubberized concrete. Two neural network models were developed to predict the reduction in the compressive and tensile strength as a result of replacing mineral aggregate with rubber aggregate. A maximum difference of 9·2% between test results and model prediction was detected during the testing of the neural networks.

Observations on Rubberized Concrete Behavior

As a possible solution to the problem of scrap-tire disposal, an experimental study was conducted to examine the potential use of tire chips and crumb rubber as aggregate substitutes in portland-cement concrete mixes. In this study, strength, durability, and toughness as well as workability, unit weight, and volume change were examined. Rubberized concrete was found to possess acceptable workability and a smaller unit weight than plain concrete. Volume change of rubberized concrete specimens containing 38, 25, and 19-mm rubber aggregates was found to be larger than that of plain concrete. Rubberized concrete specimens exhibited lower compressive and splitting-tensile strength than did plain concrete specimens. However, rubberized concrete did not demonstrate a brittle failure, but rather a ductile, plastic failure, and had the ability to absorb a large amount of plastic energy under compressive and tensile loads. A mathematical model is used to describe quantitatively the effects of rubber aggregates on the compressive and splitting-tensile strength reduction of concrete.

Use of neural networks for condition rating of jointed concrete pavements

This paper discusses the use of backpropagation neural networks as a management tool for the maintenance of jointed concrete pavement. The backpropagation algorithm is applied to model the condition rating scheme adopted by Oregon State Department of Transportation. The backpropagation technique was successful in accurately capturing the nonlinear characteristics of the condition rating model. A large training set of actual pavement condition cases was used to train the network. The training was terminated when the average training error reached 0.022. A set of 6802 cases was used to test the generalization ability of the system. The trained network was able to accurately determine the correct condition ratings with an average testing error of 0.024. Finally, a statistical hypothesis test was conducted to demonstrate the systems fault-tolerance and generalization properties.

Environmental Impact of Runoff from Highway Construction and Repair Materials: Project Overview

A study was conducted to identify the possible effects of highway construction and repair (C&R) materials on the quality of surface water and groundwater near the highway environment. The scope involved the development of a validated methodology to assess such effects in three phases. Phases 1 and 2 involved a survey of C&R materials, laboratory testing of the chemical and toxicological characteristics of a selected number of these materials, development and validation of a laboratory testing–based screening and evaluation methodology for highway C&R materials, and development of a mathematical model to simulate the fate and transport of water quality constituents, including toxicity, along surface and subsurface pathways in the highway environment. Phase 3 focused on 10 tasks designed to confirm the evaluation methodology, test various hypotheses of the model development, develop additional leaching and sorption data, compare ecotoxicological testing procedures developed during the project with standard Environmental Protection Agency procedures, refine laboratory protocols, enhance the model, and investigate the availability of field data for model testing.

Photo-modeling for Construction Site Space Planning

Space planning of complex and congested construction sites affects construction safety and field performance. The traditional method of relying on visual inspection and 2 dimensional (2D) drawings for layout planning is limited by the fact that construction sites are usually highly complex and dynamic. Existing site conditions must be frequently captured to represent its latest status for space planning. Recent development of 3 dimensional (3D) reality-capturing technologies, such as laser scanning and photo-based modeling, allows an accurate measurement of a job site and its representation in a 3D format. This research proposes a photo-modeling approach for capturing as-built conditions for space planning purposes. This technique automates the reality-capturing process in which a series of 2D photos taken from different perspectives are used to derive an as-built 3D model of a construction site. The feasibility and effectiveness of the proposed approach is demonstrated in an industrial case study.

ENVIRONMENTAL IMPACT OF CONSTRUCTION AND REPAIR MATERIALS ON SURFACE WATER AND GROUNDWATER: SCREENING AND EVALUATION METHODOLOGY

The 6-year NCHRP Project 25-9, titled Environmental Impact of Construction and Repair Materials on Surface and Ground Waters, concluded in March 2000. The main purpose of the study was to develop and demonstrate a methodology for identification of the possible impact of highway construction and repair (C&R) materials on the quality of surface water and groundwater in the immediate highway environment. The evaluation methodology consisted of an initial screening of a raw (unamended) C&R material leachate for aquatic toxicity by using bioassay tests and of further detailed testing and evaluation of those materials identified as potentially toxic. In the detailed evaluation, leaching source term tests were conducted to determine leachate composition under varying environmental conditions. Environmental tests were then conducted on the leachate to determine the effects of removal, reduction, and retardation (RRR) processes in the highway environment. The environmental processes included photolysis, volatilization, biodegradation, and soil sorption. The leaching and RRR tests identified interactions between specific environmental processes and leachate contaminants and yielded empirically derived functions for each process. The functions were coupled with selected reference environments in a computer model to simulate fate and transport for surface and subsurface pathways. Model results were reported as concentrations, loads, or fluxes of contaminants as a function of time at the highway boundary. Complete evaluation methodology results are presented for a standard asphalt cement concrete developed to serve as a reference asphalt concrete for interlaboratory comparisons.

Scheduling of linear projects with single loop structures

Abstract In the last decade, a number of linear scheduling methods based on the theories of linear and dynamic programming were developed for the scheduling of linear projects. However, these methods are only suitable for the scheduling of serial linear projects (i.e. sequential activities). In this paper, a nonserial dynamic programming formulation for the scheduling and control of linear projects that involve single loop structures is presented. The objective is to provide for the selection of crew formations, interruptions, and lags for the production activities that result in the minimum project duration. The advantage of this nonserial dynamic programming approach is its ability to handle both serial and nonserial linear projects with variable crew formations and work interruptions. In addition, the system presented produces a graphical representation of the project schedule of minimum duration and updates the original schedule based on current information supplied by the user. A numerical example is included to illustrate the input and output of the system presented.

Impact of weather conditions on construction labour productivity in Qatar

Qatari construction projects frequently encounter significant delays. One of the major causes of these delays is ignoring Qatars extreme weather conditions on labour productivity. This paper studies the impact of temperature, humidity, and wind on labour productivity in Qatar for four construction trades, namely, formwork, masonry, plaster, and ceramic tiles. These trades were chosen because they are time-consuming and commonly found in most construction projects. Weather and trade labour productivity data were recorded between July 2013 and February 2014. The results showed that weather conditions have a high impact on trade labour productivity. They also showed that the labour productivity in the summer can be as low as half of that in the winter. Linear regression models were developed to predict trade productivity on a given day of the year.

Analysis of change orders in Qatari construction projects

Change orders affect the performance of construction projects and may induce significant cost overruns. The paper identifies the main causes/factors that lead to change orders in Qatari construction projects. It also quantifies the cost overrun impact of these change orders in Qatari construction projects. A total of 1122 change orders were collected from 22 Qatari residential and commercial construction projects. The collected data was analyzed using statistical methods such as Pearson correlation and analysis of variance (ANOVA). The analysis results were used to quantify the change order impacts on cost overruns in Qatari construction projects. Regression analysis models were also developed to predict change order cost overruns with respect to project size/contract value. Finally, recommendations were developed to address change order impacts on cost overruns in the Qatari construction industry.