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The Federal Highway Administration (FHWA) has recently developed the Portable Scour Testing Device (PSTD) to improve scour analysis around bridge piers in cohesive soils as part of the NextScour project. The PSTD is a compact field erosion testing device that, apart from a drill rig and larger water pump, has a lot of similarity with the In-situ Scour Testing Device (ISTD) in mechanism and data acquisition. The purpose of this paper is to provide recommendations on the suitability of using PSTD and ISTD at sites that have cohesive subsurface soils. An overview of the capabilities and limitations of the PSTD/ISTD in relation to hydraulic considerations, soil types, depth coverages, and erodibility potential is given. A multi-criteria assessment methodology to evaluate site suitability for conducting PSTD/ISTD is presented. The assessment methodology was utilized to detect suitable sites among 30 Illinois bridge sites using soil layer information, boring locations, groundwater level readings, in-situ testing results, geospatial analysis, site accessibility, and aerial photos.

Standard penetration tests (SPTs) have been used to estimate strength parameters of soils and weak rocks when it is difficult to obtain high-quality samples for laboratory shear testing. SPTs require 45 cm (18 in.) of split-spoon sampler penetration to determine the blowcounts per 0.3 m (1 ft), which is difficult to impossible to obtain in weak rock, that is, intermediate geomaterials. As a result, a modified SPT is presented here for sampler penetrations less than 45 cm (18 in.) in weak rocks. This new procedure is termed the modified standard penetration test (MSPT) and uses the penetration rate, not the sum of penetration blowcounts per 0.3 m, to estimate the unconfined compressive strength for the design of drilled shafts in weak fine-grained rocks. The penetration rate is the inverse of the linear slope of the penetration depth versus blowcount relationship. With this new test and interpretation procedure, 45 cm (18 in.) of sampler penetration is no longer required to estimate the unconfined compressive strength of weak rocks. An empirical correlation between MSPT penetration rate and laboratory-measured unconfined compressive strength is presented here for weak Illinois shale. This correlation could be used to estimate the unconfined compressive strength for the design of drilled shafts in weak rocks.

This study aims to improve the unconfined compressive strength of soils using additives as well as by predicting the strength behavior of stabilized soils using two artificial-intelligence-based models. The soils used in this study are stabilized using various combinations of cement, lime, and rice husk ash. To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratory dataset comprising 137 soil specimens treated with different combinations of cement, lime, and rice husk ash is used. Two artificial-intelligence-based models including artificial neural networks and support vector machines are used comparatively to predict the strength characteristics of soils treated with cement, lime, and rice husk ash under different conditions. The suggested models predicted the unconfined compressive strength of soils accurately and can be introduced as reliable predictive models in geotechnical engineering. This study demonstrates the better performance of support vector machines in predicting the strength of the investigated soils compared with artificial neural networks. The type of kernel function used in support vector machine models contributed positively to the performance of the proposed models. Moreover, based on sensitivity analysis results, it is discovered that cement and lime contents impose more prominent effects on the unconfined compressive strength values of the investigated soils compared with the other parameters.

March 2014 Oso landslide, which demolished Steelhead Haven Community near Oso, Washington, is the deadliest in US history. Several factors have been suggested for the initiation of this landslide by various researchers including, the heavy rainfall before the landslide, timber harvesting on the upper plateau, river erosion at the slope toe, groundwater rise due to rainfall infiltration, and irregular 3D topography of the slope. This study utilizes 3D limit equilibrium and 3D finite element seepage analyses to investigate the effect of rainfall infiltration in the 7.5 acres timber harvest area at the top of the slope as well as potential changes of groundwater elevation on the initiation of 2014 Oso landslide. To achieve these objectives, the infiltration rate was varied in the harvested area to investigate its effect on the first phase initiation. Also, two potential groundwater levels were examined to assess the sensitivity of the first phase slide mass to changes in groundwater conditions. The 3D factor of safety for the critical slip surfaces was obtained for the two groundwater levels using two conventional limit equilibrium methods. The safety factor for the critical slip surface is slightly different for the first and second groundwater levels. The difference is such small that it can be concluded that a reasonable rise in groundwater level would not have been the triggering factor for the 2014 Oso landslide. The impacts of other potential factors such as shear strength reductions of upper layers due to the rainfall infiltration, timber harvesting, and/or 3D slope geometry effects appear to have been more influential in the initiation of the landslide.

Compacted soil is an essential element in the construction of geo-structures as not any soil site on its own is ideal for the intended construction. This research is an experimental study that investigates the interactional effect of moisture and fines contents on electrical resistivity (ER) of compacted soils. The soil type used in this study is sand with 0%, 30%, and 60% fines content. A non-conductive standard proctor mold is built and modified for measuring the electrical resistivity of soil samples with different dry densities and moisture contents. The electrical resistivity measurements are conducted using four electrodes; two electrodes for injecting the current and two electrodes for measuring the electrical potential difference. The soil specimens are tested under the same electrical setup in both dry and wet sides of the soil compaction curve. The results show that there is an inverse relationship between the electrical resistivity amount and both soil density and moisture content. The plot of electrical resistivity versus moisture content indicates that even though the electrical resistivity decreases with increasing the moisture content, the rate of electrical resistivity changes is different in wet and dry sides of optimum moisture content (OMC). In the dry side of OMC, the electrical resistivity decreases with a steep slope because of an increase in both soil density and moisture content. However, on the wet side of optimum moisture content, the soil density starts to decrease and electrical resistivity moves with a milder slope just because of an increase in moisture content.

Stability of the soil slopes is one of the most challenging issues in civil engineering projects. Due to the complexity and non-linearity of this threat, utilizing simple predictive models does not satisfy the required accuracy in analysing the stability of the slopes. Hence, the main objective of this study is to introduce a novel metaheuristic optimization namely Harris hawks’ optimization (HHO) for enhancing the accuracy of the conventional multilayer perceptron technique in predicting the factor of safety in the presence of rigid foundations. In this way, four slope stability conditioning factors, namely slope angle, the position of the rigid foundation, the strength of the soil, and applied surcharge are considered. Remarkably, the main contribution of this algorithm to the problem of slope stability lies in adjusting the computational weights of these conditioning factors. The results showed that using the HHO increases the prediction accuracy of the ANN for analysing slopes with unseen conditions. In this regard, it led to reducing the root mean square error and mean absolute error criteria by 20.47% and 26.97%, respectively. Moreover, the correlation between the actual values of the safety factor and the outputs of the HHO–ANN (R2 = 0.9253) was more significant than the ANN (R2 = 0.8220). Finally, an HHO-based predictive formula is also presented to be used for similar applications.

Unbound aggregate base and subbase layers distribute traffic induced wheel loads in a pavement and protect the weak subgrade. In this study, effects of plasticity index (PI), fines content (FC) (pe...

Performance period or life span of a flexible pavement is dependent upon the load carrying capacity of its base and subbase layers. Pavement strength characteristics influenced by material properties of these foundation layers are of utmost importance in the pavement design. In this experimental study, the goal was to adequately define the limits of different unbound aggregate properties influencing the strength of unbound aggregate. Material type, gradation, maximum particle size, fines content, dust ratio and plasticity index were among the different properties studied. Dust ratio is defined as the ratio of material passing the No. 200 sieve (i.e. fines content) to material passing the No. 40 sieve. As for the aggregate materials, crushed limestone and crushed gravel, commonly used in Illinois in base/subbase applications, were considered. Illinois dense graded base specifications allow aggregate materials with a maximum particle size of 25 mm for the CA 6 specification and 50 mm maximum particle size for the CA 2 aggregate. Plasticity index, fines content, and dust ratio ranged from 5% to 13%, 5% to 12%, and 0.4 to 1.0, respectively. California Bearing Ratio (CBR) and staged triaxial tests were performed to characterize the material strength. Higher strength values were obtained for the CA 6 aggregates with 25-mm maximum particle size compared to the aggregates tested for CA 2 specification. Considering typical property ranges, a dust ratio of 1.0 was found to be a viable option in some cases for base/subbase applications providing an acceptable soaked strength for both crushed limestone and crushed gravel. However, for both material types, the combination of a dust ratio of 0.4 and a fines content of 12% posed a severe negative effect on aggregate strength.

Slip resistance of soil on buried pipelines develops from movement caused by faults, subsidence, and landslides. In areas with underground mining where subsidence is projected at the ground...

Strength characteristics of unbound aggregate materials critically affect base and sub-base thickness designs of construction working platforms and flexible pavements. Unsoaked California Bearing Ratio (CBR) is commonly used by state transportation agencies for quality control and design. However, depending on the amount of fines content (i.e., passing No. 200 sieve), the strength characteristics of unbound aggregate layers may severely be affected after soaking. This study investigates any correlations that may exist between soaked and unsoaked strengths of crushed gravel and limestone aggregates commonly used in the State of Illinois. A test matrix was established to consider the effects of varying fines content at 5% and 12%, plasticity index (PI) at 5% and 9%, and dust ratio (DR) at 0.4, 0.6, and 1.0 on aggregate strength. DR is the ratio of percent passing No. 200 sieve to percent passing No. 40 sieve. Most of the aggregate strength characterizations with 5% fines content were not sensitive to soaking in terms of CBR index. However, significant reductions in soaked and unsoaked CBR values were observed when fines content increased from 5% to 12%. The crushed limestone aggregate strengths were more affected by soaking than the crushed gravel aggregates. A prediction model was developed to predict soaked CBR values from unsoaked CBR tests considering material type, fines content, PI and DR.

The seismic motion response of a cantilever retaining wall with cohesive and cohesionless backfill materials was evaluated using fully dynamic analysis based on finite difference method. The dynamic analysis was validated based on experimental test results and then compared to analytical and empirical correlations based on Newmark sliding block method. Seven different earthquake events and the backfills with low to high levels of cohesion were considered. Nonlinear regression analyses were carried out to provide correlations between free-field peak ground acceleration (PGA) and maximum relative displacement of the retaining wall. These results were compared to results from empirical and analytical methods. Furthermore, fragility analyses were conducted to determine the probability of damage to the retaining wall for different free-field PGAs and backfill cohesions. It is demonstrated to what extent a small amount of cohesion in backfill material can influence displacement of the retaining wall and probability of damage in seismic conditions.

Characterizing soil erosion and predicting levee erosion rates for various levee soils and storm conditions during floodwall overtopping events is necessary in designing levee-floodwall systems. In this study, a series of laboratory scaled levee-floodwall erosion tests were conducted to determine erosion characteristics of fine grained soils subject to overtopping from different floodwall heights with variable flow-rates. A decreasing rate of erosion was observed as a pool of water was generated in the created scour hole at the crest of the levee model. The erosion rates were also assessed using jet erosion test (JET) and erosion function apparatus (EFA) tests. The results of levee-floodwall overtopping along with soil geotechnical characteristics such as plasticity index, compaction level, and saturation level of the levee soils as well as hydraulic parameters such as water overtopping velocity were used to develop a levee-floodwall erosion rate prediction model. Then, the results of JET and EFA were integrated to develop another prediction model for levee-floodwall erosion rate estimation. Consequently, the prediction models were evaluated by conducting additional tests and comparing the prediction results with the actual measured erosion rates.

Resilient modulus (Mr) and permanent deformation (PD) characteristics of unbound aggregates under repetitive traffic loads dictate the structural response and performance of pavement base and subbase layers. Aggregate material behavior is dependent on the amount of fines in particulate matrix, also referred to as fines content (percent passing number 200 sieve), as well as plasticity index, dust ratio (percent passing number 200 sieve to percent passing number 40 sieve), material type, aggregate gradation/packing and the interactions of these properties with each other. In this study, repeated load triaxial tests were conducted on crushed limestone and crushed gravel aggregates. Fines content and plasticity index were varied from 5% to 12% and 5% to 9%, respectively. Two most typical gradations of aggregates used in roadway construction in Illinois were utilized with dust ratios ranging from 0.4 to 1.0. The results of these tests were analyzed using the shakedown theory for evaluating typical base/subbase permanent deformation or rutting trends linked to practical design considerations. Charts were also established for the modulus and deformation characteristics of unbound aggregates to designate the material quality with performance trends. Such guiding charts were compared with others developed in previous studies by authors for determining aggregate behavior under monotonic loading tests such as California Bearing Ratio (CBR). The comparisons provide valuable insights on how each aggregate property influences strength, modulus and permanent deformation behavior under different loading conditions.

Floodwall overtopping erodes the levee surface. A better understanding of the erosion rate of levee-floodwall systems is crucial for designing such structures. Scouring induced by overtopping during storm events can cause failure of these geo-structures. In this study, the contributing factors such as floodwall height, soil characteristics, and hydraulic characteristics of overtopped flow are considered to predict erosion rates for such levees built with fine-grained soils. Using over 60 simulated scaled levee-floodwall test results, the effect of the contributing parameters on soil erosion are described and quantified. The tested soils had relatively wide ranges of plasticity index (non-plastic (NP) to 40 %), degree of compaction (70 to 90 %), and degree of saturation (15 to 85 %). Various scales of the floodwalls (1:20 to 1:2) and overtopped flow velocities (FV) (0.2 to 0.6 m/s) were used. The response of soils with high plasticity and low plasticity was different to erosion. Highly plastic soils experienced sloughing and more resistance toward erosion, whereas in low plastic soils scour developed. Also, the erosion rates are more sensitive to plasticity index and floodwall height than degree of compaction or degree of saturation. Using the lab-scaled simulation results, a prediction model was developed to estimate erosion rates. The developed model was used to estimate the erosion rates in three case histories and compared with measured values. The limitations and advantages of the model were analyzed and discussed.

The United States witnessed its deadliest landslide on March 22, 2014 in Oso, Washington. Forty-three people were killed and the direct financial damage exceeded 170 million dollars. The topography of the slope prior to this landslide was complex due to the occurrence of several historical landslides on the same slope and three-dimensional (3D) features of the slope. This paper utilizes an inverse 3D limit equilibrium analysis to propose a 3D failure mechanism and sequence for the 2014 Oso Landslide. The 3D mechanism consists of two main phases (Phase I and II) with three retrogressive slides that were identified during field reconnaissance and confirmed via the 3D limit equilibrium slope stability analyses. The 3D analysis suggests that Phase II of the Stark et al. (2017) mechanism consists of two separate retrogressive slides instead of a single slide. The two slides of Phase II are referred to as Phase IIa and Phase IIb herein for comparison with Stark et al. (2017) . Photographs herein show the geometry and runout of Phases IIa and IIb. After Phase IIa, sloughing of the steep scarp in the upper plateau onto the Phase IIb slide mass continued for months. The 3D analysis includes the complexities of the ancient landslide bench along with surrounding slope geometry and features, which help explain the initiation and direction of slide movement.

The analyses of retaining walls in California showed many backfills are coarse material with some cohesion. In this investigation, seismic response of cantilever retaining walls, backfilled with dirty sandy materials with up to 30 kPa cohesion, is evaluated using fully dynamic analysis. The numerical simulation procedure is first validated using reported centrifuge test results. The validated methodology is then used to investigate the effects of three earthquake ground motions including Kobe, Loma Prieta, and Chi-Chi on seismic response of retaining walls. In addition, the input peak ground acceleration values are varied to consider a wide range of earthquake acceleration intensity.

Proper characterization of a dense-graded aggregate base/subbase material should include both quality and strength aspects. Gradation, passing the No. 200 sieve (smaller than 0.075 mm) fines content, and Atterberg limits for plasticity index (PI) are the most important properties that affect the quality and longevity of aggregates used as unbound layers in flexible pavement applications. The criterion used for allowing fines in high quality aggregates for highway applications vary among the state agencies. Most specifications call for controlling fines content, PI and the dust ratio, which is defined as percent passing the No. 200 sieve divided by percent passing the No. 40 sieve. In this study the effect of these fines on moisture-density relationship and strength of a crushed limestone aggregate with 25.4-mm (1-in.) maximum particle size was investigated. A typical range of 5–12% fines content inclusion with plasticity indices of 5–13% and dust ratios of 0.4–1.0 were studied. In order to evaluate the influence of each of these properties of the fines, a comprehensive number of samples were tested for the soaked California Bearing Ratio (CBR). The moisture sensitivity of aggregate strength was evaluated within ±1.5% of the optimum moisture content. The findings were summarized to propose a new approach for proper material selection based on the fines content and dust ratio.

Unbound aggregate base and subbase courses consist of coarse-grained materials with limited percentages of fines (i.e., passing the No. 200 sieve) allowed. The fines are mineral fillers that occupy the void spaces between the sand and gravel-sized particles. An excessive quantity of fines can negatively affect the strength characteristics of unbound aggregate layers, and this effect can easily be aggravated when the matrix is saturated. A set of unsoaked and soaked California bearing ratio (CBR) tests were performed on engineered gradations of unbound aggregate samples so that the effect of soaking on CBR test results could be studied. A detailed comparison between soaked and unsoaked CBR results was carried out by considering various index properties, such as the fines content, plasticity index, and dust ratio (percentage passing the No. 200 sieve divided by the percentage passing the No. 40 sieve). It was found that higher plasticity indexes, such as 9% and 13%, have a negative effect on both soaked and unsoaked CBR values for samples with a dust ratio of 1.0. Samples with a dust ratio of 0.4 were, in general, not influenced by soaking in terms of the CBR index. Moreover, the effect of soaking on strength reduction was noticeable when the fines content was as high as 12% and the dust ratio was greater than 0.6. Furthermore, a correlation between soaked and unsoaked CBR is also proposed on the basis of experimental results obtained from this study.

Unbound aggregate base and subbase layers are the main load-bearing layers in a pavement structure. Size and shape properties of these aggregate materials should be controlled to ensure proper workability during construction and improved performance for pavement longevity. The effects of gradation, maximum particle size, fines content (percentage passing the No. 200 sieve), and dust ratio on the quality of aggregates were investigated by performing many soaked California bearing ratio tests on a crushed limestone material. The dust ratio represents the amount of fines content divided by the amount of minus No. 40 sieve material. The dust ratios studied were 0.4, 0.6, and 1.0. Two gradations commonly used in Illinois, with maximum particle sizes of 1 in. and 2 in., were studied to analyze the effect of fines content with respect to maximum particle size in the gradation. A typical range of fines contents (i.e., 5%, 8%, and 12%) was also considered. The results show that the gradation, dust ratio, and fines content should be taken into account in the selection of aggregate properties for stability requirements. Aggregates with larger maximum size particles provide high strength, and they are not affected as much as aggregates with smaller maximum size particles by an increase in fines content. The aggregates with smaller maximum size particles provide lower strength. It was also concluded that samples with a dust ratio of 1.0 do not necessarily result in an aggregate material with low strength.

This study focuses on the performance analysis of mine roof rock due to moisture variation using a case study, which experienced roof falls. The roof layer types, thicknesses, and properties were determined using extensive lab and field data. A novel numerical model is developed using site information and observed field performance to incorporate: (1) the interaction between roof rock unit beddings, (2) the interaction of roof bolts and rock units, and (3) the effect of moisture increase on roof deformation and failure. Using the proposed methodology, the mine roof layers’ allowable maximum moisture contents prior to failure can be estimated.

Unbound aggregate base and subbase layers distribute wheel load induced stresses to protect subgrade. Standards such as AASHTO and individual states specifications have set several quality control limits for a variety of properties of aggregates used in the pavement base and subbase courses. Most standards and DOT specifications suggest that the ratio of percent passing No. 200 sieve to percent passing No. 40 sieve should not be greater than two thirds, and plasticity index of the material passing No. 40 sieve should be less than 6%. The ratio of percent passing No. 200 to percent passing No. 40 sieves is called the dust ratio (DR). There are many states that have either waived the standard limits or adopted their own quality control method. In this study the effect of dust ratio, percent passing No. 200 sieve and plasticity index (PI) affecting moisture-density and strength characteristics of crushed limestone aggregates are investigated. The prepared samples represented one of the most commonly utilized dense-graded standard aggregate gradation in Illinois, i.e. CA6. Standard Proctor compaction and soaked California Bearing Ratio (CBR) tests were conducted on specimens to determine the moisture-density and strength characteristics of the material with moisture content, respectively. In addition, two staged triaxial tests using three confining pressures were performed to study the effect of confining pressure and fine quantity on strength of aggregates. According to the results, the effect of percent passing No. 200 sieve on strength variation is significant in unbound aggregates. The sensitivity of aggregate strength to moisture content variation is also discussed.

In this research, the novel metaheuristic algorithm Harris hawks optimization (HHO) is applied to landslide susceptibility analysis in Western Iran. To this end, the HHO is synthesized with an artificial neural network (ANN) to optimize its performance. A spatial database comprising 208 historical landslides, as well as 14 landslide conditioning factors&mdash, elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), topographic wetness index (TWI), and rainfall&mdash, is prepared to develop the ANN and HHO&ndash, ANN predictive tools. Mean square error and mean absolute error criteria are defined to measure the performance error of the models, and area under the receiving operating characteristic curve (AUROC) is used to evaluate the accuracy of the generated susceptibility maps. The findings showed that the HHO algorithm effectively improved the performance of ANN in both recognizing (AUROCANN = 0.731 and AUROCHHO&ndash, ANN = 0.777) and predicting (AUROCANN = 0.720 and AUROCHHO&ndash, ANN = 0.773) the landslide pattern.

Regular optimization techniques have been widely used in landslide-related problems. This paper outlines two novel optimizations of artificial neural network (ANN) using grey wolf optimization (GWO) and biogeography-based optimization (BBO) metaheuristic algorithms in the Ardabil province, Iran. To this end, these algorithms are synthesized with a multi-layer perceptron (MLP) neural network for optimizing its computational parameters. The used spatial database consists of fourteen landslide conditioning factors, namely elevation, slope aspect, land use, plan curvature, profile curvature, soil type, distance to river, distance to road, distance to fault, rainfall, slope degree, stream power index (SPI), topographic wetness index (TWI) and lithology. 70% of the identified landslides are randomly selected to train the proposed models and the remaining 30% is used to evaluate the accuracy of them. Also, the frequency ratio theory is used to analyze the spatial interaction between the landslide and conditioning factors. Obtained values of area under the receiver operating characteristic curve, as well as mean square error and mean absolute error showed that both GWO and BBO hybrid algorithms could efficiently improve the learning capability of the MLP. Besides, the BBO-based ensemble surpasses other implemented models.

This study focuses on the settlement of soft soil improved by floating soil cement columns in a small-scale physical test. The effect of area improvement ratio (ap) and column height (Hc) on the improved ground under design load (Wd) were investigated via small-scale physical modeling tests. The area improvement ratios of 21.7, 32.5, and 43.4% and column heights of 50 and 100 mm were examined. The models were instrumented to measure displacements and soil pressures. Two loading scenarios were applied on treated and untreated soils. The first series was conducted under strain controlled mode to identify the failure mechanism. The second series was conducted under design load to evaluate the stress distribution, settlement, and failure pattern. The settlements also were measured using particle image velocimetry (PIV) technique. The PIV showed that the final settlement of the improved ground decreases as the area improvement ratio (ap) increases and the column height (Hc) increases. For controlling the distribution of stresses, an intermediate range of area improvement ratio is recommended. In addition, this study proved that the PIV technique is an effective optical method to simulate ground deformations at the lowest strain without performing a full-scale test.

Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited Due to the wide application of evolutionary science in different engineering problems, the main aim of this paper is to present two novel optimizations of multi-layer perceptron (MLP) neural network, namely dragonfly algorithm (DA) and biogeography-based optimization (BBO) for landslide susceptibility assessment at a study area, West of Iran. Utilizing 14 landslide conditioning factors, namely elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), and topographic wetness index (TWI) and rainfall as the input variables, and 208 historical landslides as target variable, the required spatial database is created. Then, the MLP is synthesized with the mentioned algorithms to develop the proposed DA-MLP and BBO-MLP ensembles. Three accuracy criteria of mean square error, mean absolute error, and area under the receiving operating characteristic curve are used to evaluate the performance of the models and also to develop a score-based ranking system. As the first outcome, the application of the DA and BBO metaheuristic algorithms enhances the accuracy of the MLP. Moreover, referring to the calculated total ranking scores of 6, 14, and 16, it was revealed that the BBO performs more efficiently than DA in optimizing the MLP.

Foundations on claystone with swell potential may experience upward movement and failure. In this case study, the cause of 58 mm upward movement of drilled-in piers is analyzed using survey data, extensometer readings, and moisture content monitoring of claystone at the site. Laboratory swell tests were conducted to characterize the swelling characteristics of the weathered rock. A swell potential analysis for the pier group foundations is presented. The interaction of the pier group with the swelling rock is considered in analyzing the initiation of the upward movement. Furthermore, a novel inverse analysis method is presented to integrate the laboratory swell test results and numerical modeling to identify the representative swell pressures acting on the pier group as well as upward movement of the pier system. The numerical analysis indicates that the studied pier system is expected to have 135 mm heave and its rate of upward movement is compared with field observations. The behavior of the pier group foundation in swelling rock under various pier spacings and superstructure pressures shows that the uplift is considerably less for piers with smaller center-to-center spacing. The results of pier group numerical modeling provide the correlation of upward deformation changes due to center-to-center spacing of the piers, pier diameters and superstructure pressures.

Among all United States underground coal fields, those in Illinois have the highest rate of roof fall events due to their weak and severely moisture sensitive roof rock units. Rockmass characterization is the key initial step in designing safe and economical roof control measures in underground coal mines. In this study, a performance-based roof rockmass characterization is investigated. The geologic conditions as well as underground mine geographic specifications, roof fall analysis, mining method, utilized supplemental roof control measures, and geotechnical properties of roof rock units were considered to link the roof performance to rockmass characterization. The coal mine roof rating (CMRR) rockmass characterization method was used to evaluate the roof conditions and roof support design for an underground coal mine located in the Illinois Coal Basin. The results of several mine visit mappings, laboratory test results, and geotechnical issues and concerns are presented and discussed. The roof support designs are analyzed based on the rockmass characterization and are compared with the observed performance. This study shows that (1) CMRR index is a reasonable method for characterizing roof rockmass; (2) moisture sensitivity and bedding strengths in the horizontal direction are essential parameters for roof support design in mines with weak roof conditions; and (3) the applicability of the analysis of roof bolt system for roof support design of the studied mine is questionable.

Quality classes of aggregate materials used in unbound base and subbase construction are quite important for the longevity of highway pavements. Aggregate gradation, fines content, Atterber...