Finite element analysis of dynamic structure-medium interaction with some reference to underground nuclear reactor containments

A finite element solution is developed for the problem of time-history response of reinforced underground cavity subjected to dynamic disturbances of the underground environment. The cavity can be of any shape, reinforced by either rock bolts or any elastic liner, with bending stiffness taken into consideration. Available methods that can solve the cavity problem are examined and an available computer programme (plane stress) modified. Introduction of a new reinforcing plate element necessitated development of two new subroutines and the extension of a third one along with certain modifications in the other subroutines and the main programme for matching requirements. The modifications enable the determination of displacements and the internal forces - time histories of the liner. -- A quantitative study of the following parameters that affect the response of the cavity reinforcement and the surrounding medium is carried out: 1) cavity reinforcement, 2) cavity shape, 3) isolation of the entire structure from the surrounding medium by a soft, energy absorbing material and 4) properties of the filling material in the cut-and-cover structural type. The modified computer programme has applications to problems outside the field of two-dimensional rock-structure interaction such as the dynamic analysis of beams, plane frames and arches. -- A finite element model is developed to simulate the dynamic analysis of infinite space. The results of the study indicate that reinforcing the cavity by a steel liner decreases the stresses in the medium by about 10% while the use of a rock bolting pattern with about 80% of the amount of steel required in a reinforcing liner decreases the stresses around the cavity by 25% and more. The horseshoe shape proves to be the best among the various shapes considered decreasing the stresses by 10-15%. Large reductions (of the order of 80%) in shell (liner) membrane forces and bending moments are reached by isolating the entire structure from the surrounding medium by a soft, energy absorbing material, which agree with the results from another investigation. It is also pointed out that a proper selection of the properties of the filling material in the cut-and-cover structure can reduce the internal forces in the structure and the stresses in the adjacent medium. It is shown that a significant reduction cannot be achieved by a single property variation but only through a proper combination of different properties (Figs. 33 to 36). The results obtained from the new model indicate the need for further modelling work in the solution of earthquake interaction problems for underground cavities

Accelerating linear projects

Scheduling linear repetitive construction projects, such as highways and pipelines, poses unique challenges due to maintaining crew work continuity. An efficient method is presented, developed to accelerate the delivery of this class of projects so as to meet a specified deadline with least associated cost. The method is simple and ensures crew work continuity. An iterative approach is employed, where, in each iteration, the project schedule is analysed and an activity is identified as the controlling activity. A controlling activity is an activity that if accelerated, would reduce project duration at least additional cost. Upon its identification, the method selects an expediting strategy that would reduce project duration, and the project is rescheduled. Several expediting strategies are considered, including working overtime, double shifts and weekends. The method is implemented in a prototype software that operates in a Windows� environment, providing a user-friendly graphical interface. It has an open architecture, enabling the user to actively participate in tailoring the generated schedule to suit the requirements of the project at hand. The proposed method accounts for incentives and liquidated damages to aid users in identifying the most cost-efficient schedule. A relational database model is implemented in Microsoft Access� to store typical crews and their associated productivity, as well as their availability dates. A project, drawn from the literature, is analysed to demonstrate the basic features of the proposed method and highlight its capabilities.Repetitive construction, acceleration, crew productivity, time-cost trade-off,

Enhanced Localization for Indoor Construction

AbstractConsiderable research work had been conducted in recent years embracing the utilization of wireless technologies in construction with a focus on identification of locations of material, equipment and personnel. A fundamental key for reliable and accurate use of these technologies is path loss models, which are used to estimate distances based on received signal strength (RSSI). This paper introduces a newly developed path loss model accounting for signal de-noising using a Kalman filter. The developed model is tested using four wireless technologies (WLAN, Bluetooth, Zigbee and Synapse SNAP), 20 experiments were carried out in laboratory environment and 1500 data sets were analyzed to investigate the accuracy of distance estimation. The results show an average of 50% enhancement in the distance estimation accuracy, which considered a potential for enhanced localization on indoor construction jobsites

AI-based cloud computing application for smart earthmoving operations

This paper introduces a newly developed model for automated monitoring and control of productivity in earthmoving operations. The model makes use of advancements in wireless sensing networks, Internet of things (IoT), and artificial intelligence. It utilizes data analytics and a dashboard to provide project managers with actionable data on the status of these operations in near-real time. The model consists of two modules; the first is a low-cost open-source remote sensing data acquisition module for collecting data throughout the execution of earthmoving operations. The collected data are sent to a cloud-based MySQL database, in which the second module is designed to (1) measure actual productivity in near-real-time, (2) detecting the location and condition of hauling roads, and (3) monitoring and reporting driving conditions over these roads. Artificial neural network (ANN) is used in cloud computing for analyzing the productivity to determine and prioritize causes behind experienced loss of productivity from that planned. This paper presents cloud computing over a web-based platform (Knowi®). Productivity measurement and analysis outputs are retrieved through any web browser. The work encompassed field and scaled laboratory experiments in the development and validation processes of the developed model. The laboratory experiments 1:24 scaled loader and dumping truck to simulate loading, hauling, and dumping operations. The data collected from the lab experiments and field work was used as input for the developed model. The results obtained highlight the accuracy of the developed model in recognition of the status of the hauling truck, traveled road condition, and in the estimated duration of the simulated earthmoving cycles.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Automated Monitoring and Assessment of Productivity in Earthmoving Projects

Continuous monitoring of productivity and assessment of its variations are crucial processes that significantly contribute to success of earthmoving projects. Numerous factors may lead to productivity variations. However, these factors are subjectively identified using manual knowledge-based expert judgment. Such manual recognition process is not only subject to errors but also time-consuming. There is a lack of research work that focuses on near real-time assessment of productivity variation and its effect on cost, schedule and effective utilization of resources in earthmoving projects. This paper presents a customized multi-source automated data acquisition model that acquires data from a variety of wireless sensing technologies. The acquired multi-sensor data are transmitted to a central MySQL database. Then a newly developed data fusion algorithm is applied for truck state recognition, and hence the duration of each earthmoving state. Multi-sensor data fusion facilitates measurement of actual productivity, and consequently the assessment of productivity ratios that support continuous monitoring of productivity variation in earthmoving operations. The developed tracking and monitoring model generates an early warning that supports proactive decisions to avoid schedule delays, cost overruns, and inefficient depletion of resources. A case study is used to reveal the applicability of the proposed model in monitoring and assessing actual productivity and its deviations from planned productivity. Finally, results are discussed and conclusions are drawn highlighting the features of the proposed model.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Self-calibrated WSN for indoor tracing and control of construction operations

Effective tracking and timely progress reporting are essential for successful delivery of construction projects. In this respect, several research attempts have been made to identify and track the locations of material, equipment and labor on construction Jobsites using wireless sensing technologies. Such developed methods utilize radio signal propagation models to estimate location based on measured received signal strength (RSSI). However, radio signal propagation models are highly dependent on the surrounding environment. As well, these methods are susceptible to interferences caused by metallic structures and obstacles, which are continually changing location on highly dynamic construction jobsites. This paper presents fundamental research work, designed to study the beneficial effect of self-calibrated wireless sensor network (SC-WSN) for higher accuracy of indoor localization. The developed SC-WSN hardware consists of fixed gateway unites mounted at predefined locations and mobile unites mounted on tracked objects. The designed network estimates a tagged object location based on its measured signal strength, which is then converted to corresponding distance using a dynamic signal propagation model. The developed dynamic model calibrates its parameters periodically to minimize errors in its estimated locations using particle swarm optimization algorithm. Experimental results are presented to illustrate the relative effectiveness of the developed system in comparison to commonly used fixed propagation systems.Non UBCUnreviewedFacultyOthe

Optimized material management in construction using multi-layer perceptron

Construction material represents a major component of the project cost. Therefore, it is essential to control material on construction job sites. Efficient material management system requires trade-offs and optimized balance among elements of material cost including purchase cost, storage cost, opportunity cost, ordering cost, and unavailability cost. Thus, there is a need to develop an automated method for optimizing the delivery and inventory of construction materials not only in the planning phase but also in the construction phase to account for introduced changes. In this research a novel genetic algorithm – multi-layer perceptron (GA-MLP) method is proposed to generate optimized material delivery schedule. Multi-layer perceptron (MLP) is utilized to improve genetic algorithm (GA) by generating memory to overcome local minima encountered in applying GA for optimization. This automated method supports contractors to buy construction materials with the least cost and without leading to material shortage or surplus. The proposed automated method has been validated through a numerical example. The obtained results demonstrate that GA-MLP outperform GA in optimizing construction material inventory.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

An Evolutionary Stochastic Discrete Time-cost Trade-off Method

This study introduces a newly developed method for optimized time-cost trade-off under uncertainty. It identifies the optimal execution mode for each project activity that results in minimizing the overall project cost and/or duration while satisfying a specified joint confidence level of both time and cost. The method uses an evolutionary-based algorithm along with a design generator of experiments and blocking techniques. The developed method accounts for managerial flexibility towards the selection of execution modes. This accommodates experience-based judgement of project managers in this process. Hence, the second fold of the developed method is a completely randomized experiment module that depicts the main effect of changing an activity mode on the project total cost and overall duration. The method provides the decision maker a guideline for making well-informed implementation strategies. The results obtained demonstrate benefits and accuracy of the developed method and its applicability for large scale projects.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author