Cemented granular materials (CGM) are composed of densely packed particles bound together by a cement matrix that partially fills the interstitial pores which provides considerable stiffness to the material. This study investigated the mechanical behavior and acoustic emission (AE) response characteristics during uniaxial compression of an artificial cemented granular material made from high alumina ceramic beads combined with a self-compacting cement paste. The samples were fabricated using the rock-filled concrete technique without disturbing the granular backbone. The results show that the compressive strength is a linear function of the matrix volume fraction. Brittle fracture is the most significant mechanical behavior. Compaction in the linear-elastic regime is the dominant behavior in the pre-peak strength region with strain-softening accompanied by strain-hardening after the peak strength. The extent of the compaction phase linearly increases with the matrix volume fraction. However, the extent of the linear-elastic phase is independent of the matrix volume fraction. For the samples with little matrix material, an AE signal occurred when the material strength approached the peak value. The AE signals of samples with more matrix material mainly occurred in the initial stages of the elastic phase. The AE signals of samples with higher matrix volume fractions were found at the mid-term stage of the compaction phase and remained high until the samples failed. The results will help to further understand the mechanical behavior of cemented granular materials, and also provide an important reference for the studies of sandstone, conglomerate, rockfill concrete and grouted sands.

Predicting the shear strength of roller compacted concrete dams always involves uncertainty and nonlinearities that are influenced by various factors. This study used the artificial neural network and the fuzzy logic system to predict the interlayer shear strength parameters of RCC dams. The data input to the artificial neural network and the fuzzy logic system was divided into data sets from lab tests and data sets from in-situ shear strength tests with five input parameters for the water-binder ratio, total amount of binder, fly ash content, interlayer processing methods and time intervals with two output parameters for f' and c'. The training and testing results show that the lab tests have better correlations than the in-situ tests. Moreover, the artificial neural network has better prediction accuracy than the fuzzy logic system. The predicted values from both the artificial neural network and the fuzzy logic system are in good agreement with the test data. Thus, both models can be used to predict the shear strength parameters and can provide reference predictions for evaluating combinations of layers.

The Deze Reservoir is the water source for the Niulan River-Dian Lake Water Supplementation Project. The very fine incoming sediment and the complicated flow and sediment transport processes in the reservoir have led to high sediment concentrations and turbid water in the intake during floods, which has an adverse impact on the water environment of Dian Lake, Kunming Waterfall Park and Panlong River. This study investigated the effects of two solutions for reducing the intake sediment concentration by three-dimensional modeling. One solution is the construction of check dams in the mainstream and its tributaries while the other is the construction of a new multi-level water intake. The simulations show that the new multi-level water intake designed based on the stratification characteristics of the sediment concentration will increase the length of time until the sediment concentration exceeds the desired limits. The modified intake design keeps the surface layer turbidities to lower than 17.1 NTU during the flood season for between 47.0% and 62.1% of the time surface layer turbidities larger than 100 NTU for less than 7.6% of the time. The check dams will accelerate the deposition upstream of the check dams and reduce the water turbidity at the existing water intake; however, the turbidity is still high with the surface turbidity below the limit for only 13.9%-18.5% of the flood season, which are not much better than the values without the check dams. Thus, the multi-level water intake is the better choice for solving the sediment problems of the Niulan River-Dian Lake Water Supplementation Project because it provides longer periods of low turbidity than the check dams.

Water resource issues are complicated in China due to the vast territory, great differences in regional meteorological and hydrological conditions, and the uneven socio-economic development. Therefore, water resource carrying capacity issues and constraints need to be identified for the various hydrological zones. Such studies will need an indicator with a clear physical meaning and its corresponding critical condition that reflects the hydrological mechanism to ensure reliable and acceptable water resource carrying capacities around the country. This paper uses the Yangtze River Estuary as an example for a mechanistic analysis of regional water issues to identify the constraints on the water resource carrying capacity. The runoff to the sea is used as a controllable hydrological indicator with the hydrodynamic model using a salinity limit to determine the critical point where the runoff to the sea can resist sea water intrusion for the Estuary. This method can also be applied to other hydrological regions.

The riverbed bedrock of a 300-m-high arch dam has a deep groove so the arch dam design must choose between filling this groove with concrete or excavating to the bottom of the groove. 3-D finite element models were developed for the concrete backfilling scheme and the deep excavation scheme. Deformation reinforcement theory (DRT) was then used to analyze the dam displacement, stresses and plastic zone extensions for both normal and overloaded conditions. The global stabilities of both schemes were evaluated based on the unbalanced force and the plastic complementary energy. The results show that both design schemes meet the requirements for the overloading capacity and global stability with the concrete backfilling scheme somewhat better than the deep excavation scheme in terms of the displacement, stresses and global stability of the arch dam.

The shear deformation transversal section effect can have a large effect on the mechanical properties of thin-walled beam, which can lead to enormous calculation errors when using primary beam theory in traditional designs. The faceplate of a hydraulic steel gate in a dam acts as a flange on the main beam with the main beam having the nonlinear stress characteristics of short deep beams at high heads. The energy-variational method for the shear deformation energy of the whole I-beam section is used in this study with proper selection of the longitudinal displacement function and the warping function to derive formulas for the deflection, bending normal stress and natural frequency of the beam. The results compare well with various analytical methods and finite element results. The results indicate that when the span-depth ratio or the span-width ratio is small, the bending normal stress is greatly affected by the transverse shear with concentrated loads giving greater effects, but the shear effect reduces the nature frequency calculated using other methods. The current method gives more accurate results than existing analytical methods with an extended range of applications for structural designs.

Traditional millimeter wave security imaging radar ignores the effects of scattering due to the point target assumption. However, for frequencies in the terahertz band, the target surface should be modeled as a rough surface and the effects of scattering must be considered. In this paper, a small perturbation method (SPM) is used to get the backscattering coefficient of a rough surface. Then, the imaging results for the traditional security radar imaging model are simulated for various roughnesses. The effects of key scattering parameters including the roughness and frequency are then analyzed by comparisons with a Lambert surface and an ideal specular surface. The results show that a greater backscattering persistence angle improves the imaging quality with terahertz security radar imaging. The results also show that the angular width and shape of the backscattering characteristic curve both affect the imaging resolution and peak side lobe ratio. Finally, increasing the electromagnetic wave frequency facilitates rough surface imaging.

A fast predictive control algorithm was developed for simpler, faster MPC optimization based on an FPAA analog neural network. An FPAA analog circuit provides the quadratic programming using a continuous neural network which avoids the convergence problem of discrete neural networks in a fast, simple and flexible algorithm that uses less computational resources than previous methods. The signal constraint of the FPAA analog circuit is solved by translation and scaling. The software and hardware design of the FPAA analog neural network predictive control is presented and verified in tests that show that the algorithm is effective.

In the control of distribution processes, the traditional integral square error performance index only considers the area between the output curve and the target curve, which ignores the structural features of the distribution curve. A gradient feature-based model predictive control algorithm that takes into account the curve similarities is developed for distribution processes. The algorithm first models the distribution process curve with B-splines. Then, the algorithm quantifies the similarity between the curves based on gradient features and optimizes the design by combining numerical and gradient information. The composite trapezoidal rule is then used to discretize the optimization proposition. Finally, the optimization proposition is solved to get the optimal solution. Simulations show that this algorithm improves the similarity between the output curve and the target curve during curve switching with natural transitions of the curve shape.

Reasonable urban planning requires public participation. Crowdsourcing is an emerging data acquisition and information evaluation method that encourages public participation and makes urban planning more scientific. This article articulates the necessity of utilizing crowdsourcing for urban planning. Then, this study identifies the crowdsourcing phases for urban planning by summarizing several cases and reviewing existing crowdsourcing techniques for data collection, cleaning and analysis. This study then summarizes future research directions for crowdsourcing such as 1) data cleaning techniques need to be further developed for instant feedback to mobile terminals to provide high quality data for urban planning and 2) methods for integrating multisource data to extract feedback from the public as the basis for decision making. Lastly, this study shows that to effectively utilize crowdsourcing, governments should carefully define the study scope and process when implementing crowdsourcing.