Geotechnical behavior of uranium mill tailings from Saskatchewan,Canada

This paper investigates the geotechnical behavior of uranium mill tailings from Saskatchewan, Canada.The 4% tailings were well-graded with 29% fines whereas the 5% and 6% tailings were gap-graded with 49% fines. All samples exhibited a negligible strength(0.4 k Pa) up to 60% solids, followed by a rapid increase. The 4% tailings exhibited a lower rate and amount of settlement than 5% and 6% tailings. The kidecreased from 10~(-2)to 10~(-4)m/s with a decrease in eifrom 16 to 4 and a decrease in ef from 8 to 4 such that 4% tailings showed one order of magnitude lower values than the 5% and 6%tailings. The settling potential decreased ten times(50%–5%) for 4% tailings and four times(60%–15%)for 5% and 6% tailings. The effective stress increased from 80 to 260 Pa in the settling tests. The 4%tailings were less prone to segregation when compared with 5% and 6% tailings. The average solids content after settling was 35% for 4% tailings, 40% for 5% tailings and 39% for 6% tailings with a solids content deviation of ±3%, ±8%, ±6%, respectively. All materials were essentially non-segregating at 40%initial solids.     

Stability analyses of vertically exposed cemented backfill:A revisit to Mitchell's physical model tests

Mitchell's solution is commonly used to determine the required strength of vertically exposed cemented backfill in mines. Developed for drained backfill, Mitchell model assumed a zero friction angle for the backfill. Physical model tests were performed. Good agreements were obtained between the required strengths predicted by the analytical solution and experimental results. However, it is well-known that zero friction angle can only be possible in terms of total stresses when geomaterials are submitted to unconsolidated and undrained conditions. A revisit to Mitchell's physical model tests reveals that both the laboratory tests performed for obtaining the shear strength parameters of the cemented backfill and the box stability tests were conducted under a condition close to undrained condition. This explains well the good agreement between Mitchell's solution and experimental results. Good agreements are equally obtained between Mitchell's experimental results and FLAC3 D numerical modeling of shortterm stability analyses of exposed cemented backfill.     

Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration

Calibrating watershed-scale hydrologic models remains a critical but challenging step in the modeling process. The Soil and Water Assessment Tool (SWAT) is one example of a widely used watershed-scale hydrologic model that requires calibration. The calibration algorithms currently available to SWAT modelers through freely available and open source software, however, are limited and do not include many multi-objective genetic algorithms (MOGAs). The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient MOGA calibration algorithm for a wide variety of applications including for SWAT model calibration. Therefore, the objective of this study was to create an open source software library for multi-objective calibration of SWAT models using NSGA-II. The design and implementation of the library are presented, followed by a demonstration of the library through a test case for the Upper Neuse Watershed in North Carolina, USA using six objective functions in the model calibration.     

Computer vision techniques for construction safety and health monitoring

For construction safety and health, continuous monitoring of unsafe conditions and action is essential in order to eliminate potential hazards in a timely manner. As a robust and automated means of field observation, computer vision techniques have been applied for the extraction of safety related information from site images and videos, and regarded as effective solutions complementary to current time-consuming and unreliable manual observational practices. Although some research efforts have been directed toward computer vision-based safety and health monitoring, its application in real practice remains premature due to a number of technical issues and research challenges in terms of reliability, accuracy, and applicability. This paper thus reviews previous attempts in construction applications from both technical and practical perspectives in order to understand the current status of computer vision techniques, which in turn suggests the direction of future research in the field of computer vision-based safety and health monitoring. Specifically, this paper categorizes previous studies into three groups—object detection, object tracking, and action recognition—based on types of information required to evaluate unsafe conditions and acts. The results demonstrate that major research challenges include comprehensive scene understanding, varying tracking accuracy by camera position, and action recognition of multiple equipment and workers. In addition, we identified several practical issues including a lack of task-specific and quantifiable metrics to evaluate the extracted information in safety context, technical obstacles due to dynamic conditions at construction sites and privacy issues. These challenges indicate a need for further research in these areas. Accordingly, this paper provides researchers insights into advancing knowledge and techniques for computer vision-based safety and health monitoring, and offers fresh opportunities and considerations to practitioners in understanding and adopting the techniques.     

Particle swarm algorithm with adaptive constraint handling and integrated surrogate model for the management of petroleum fields

This paper deals with the development of effective techniques to automatically obtain the optimum management of petroleum fields aiming to increase the oil production during a given concession period of exploration. The optimization formulations of such a problem turn out to be highly multimodal, and may involve constraints. In this paper, we develop a robust particle swarm algorithm coupled with a novel adaptive constraint-handling technique to search for the global optimum of these formulations. However, this is a population-based method, which therefore requires a high number of evaluations of an objective function. Since the performance evaluation of a given management scheme requires a computationally expensive high-fidelity simulation, it is not practicable to use it directly to guide the search. In order to overcome this drawback, a Kriging surrogate model is used, which is trained offline via evaluations of a High-Fidelity simulator on a number of sample points. The optimizer then seeks the optimum of the surrogate model.     

Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications

Uncertainty estimates corresponding to measured hydrologic and water quality data can contribute to improved monitoring design, decision-making, model application, and regulatory formulation. With these benefits in mind, the Data Uncertainty Estimation Tool for Hydrology and Water Quality (DUET-H/WQ) was developed from an existing uncertainty estimation framework for small watershed discharge, sediment, and N and P data. Both the software and its framework-basis utilize the root mean square error propagation methodology to provide uncertainty estimates instead of more rigorous approaches requiring detailed statistical information, which is rarely available. DUET-H/WQ lists published uncertainty information for data collection procedures to assist the user in assigning appropriate data-specific uncertainty estimates and then calculates the uncertainty for individual discharge, concentration, and load values. Results of DUET-H/WQ application in several studies indicated that substantial uncertainty can be contributed by each procedural category (discharge measurement, sample collection, sample preservation/storage, laboratory analysis, and data processing and management). For storm loads, the uncertainty was typically least for discharge (±7–23%), greater for sediment (±16–27%) and dissolved N and P (±14–31%) loads, and greater yet for total N and P (±18–36%). When these uncertainty estimates for individual values were aggregated within study periods (i.e. total discharge, average concentration, and total load), uncertainties followed the same pattern (Q < TSS < dissolved N and P < total N and P). This rigorous demonstration of uncertainty in discharge and water quality data illustrates the importance of uncertainty analysis and the need for appropriate tools. It is our hope that DUET-H/WQ contributes to making uncertainty estimation a routine data collection and reporting procedure and thus enhances environmental monitoring, modeling, and decision-making. Hydrologic and water quality data are too important for scientists to continue to ignore the inherent uncertainty.     

FE-shape sensitivity of elastoplastic response

A new approach for performing FE-shape design sensitivity analyses (DSA) of structural models with both linear elastic and elastoplastic material behaviour is presented. In the formulation of the method the derivation of the FE equilibrium equations is performed analytically leading to various terms. The differentiation of some parts of these terms is determined numerically, therefore the method is semianalytical. The formulation is particularized for isoparametric finite elements for which exact numerical differentiation can be obtained (exact up to round-off error). Examples of some plane stress problems testify that the results of the new method are not dependent either on the size of perturbation of the design variables or on the FE mesh refinement among other factors.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Comparing the pozzolanic behavior of sugar cane bagasse ash to amorphous and crystalline SiO2

The present paper aims to clarify the pozzolanic behavior of sugar cane bagasse ash-SCBA by comparing it to amorphous and crystalline silica. It is shown that calcium silicate hydrate is formed in lime solution with SCBA but the reaction is slow and does not consume all the material. Comparing its results with the obtained in tests with silica fume and with crushed quartz show a better agreement with the latter. Characterization of cement pastes shows 20% of cement replacement by sugar cane bagasse ash leads to only a minor reduction in the amount of calcium hydroxide formed. This behavior is also closer to the observed in quartz than in silica fume. The results suggest SCBA should be used as a replacement for inert constituents in cement composites rather than pozzolanic addition. Analysis of the microstructure of the cement pastes revealed the presence of calcium hydroxide in samples prepared with partial replacement by silica fume, quartz and sugar cane bagasse ash. The presence of this phase in the sample prepared with silica fume was attributed to agglomeration of the particles that affected the reactivity of this material.