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Photocatalytic oxidation of alcohols has received more and more attention in recent years following the numerous studies on the degradation of pollutants, hydrogen evolution, and CO2 reduction by photocatalysis. Instead of the total oxidation of organics in the degradation process, the photo-oxidation of alcohols aims at the selective conversion of alcohols to produce carbonyl/acid compounds. Promising results have been achieved in designing the catalysts and reaction system, as well as in the mechanistic investigations in the past few years. This review summarizes the state-of-the-art progress in the photo-oxidation of alcohols, including the development of photocatalysts and cocatalysts, reaction conditions including the solvent and the atmosphere, and the exploration of mechanisms with scavengers experiment, electron paramagnetic resonance (EPR) and diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. The challenges and outlook for the further research in this field are also discussed.

Extraction of uranium from radioactive waste-water is of significant importance for environmental protection and the recovery of uranium resource. Different from the previous reports to use the solid absorbent/photocatalyst for U(VI) removal, herein, we proposed a new eco-friendly method for the rapid and selective extraction of uranium from aqueous solutions under visible light without solid materials. At optimal pH value and in the presence of organics like alcohols, the U(VI) could be extracted efficiently to form brown uranium solid over wide uranium concentrations under anaerobic condition and visible light, by utilizing the excitation of the given U(VI) species. With comprehensive modelling of the electronic ultraviolet-visible (UV-Vis) properties, it is proved that pH adjusting towards U(VI) could induce efficient ligand-to-metal-charge-transfer (LMCT) within the uranyl complex under visible light and the reduction of U(VI) to form U(V), which can be transformed into U(IV) via disproportionation reaction. The resulting U(IV) in solid phase makes the extraction much more convenient in operation. More importantly, the excellent selectivity for uranium extraction over interfering alkali metal ions, transition metal ions and the lanthanide metal ions shows a powerful application potential.

In this letter, we present a novel analysis and design approach of self-oscillation frequency (SOF) for 0.8- ${{\mu }}\text{m}$ indium phosphide (InP) double-heterojunction bipolar transistor (DHBT) emitter-coupled logic (ECL) and current-mode logic (CML) static frequency dividers. SOF of ECL and CML dividers is designed to be the maximum value after theoretical analysis and multiparameter optimization. The results show that the SOF of the ECL and CML divider is 62 and 37.5 GHz, respectively. With sinusoidal waveform input, the operating frequency range of the ECL divider is from 0.1 to 65 GHz, and CML is from 0.1 to 55 GHz, while the cut-off frequency ${f_{T}}$ is 150 GHz. For ECL, the ${f_{T}}$ utilization of SOF (SOF ${/}{f_{T}}$ ) is 0.413, and CML is 0.25. These are the maximum SOF results that can be designed for the two dividers under the same design conditions.

Zinc oxide (ZnO) and cobalt (Co)-ZnO nanocomposites were first reacted with 2-Methylimidazole to synthesize the zeolitic imidazole frameworks as precursors. After calcination in nitrogen, the ZnO/N-C and Co/ZnO/N-C composites were received, respectively. The structure and composition of the samples at different stages were characterized in order to illustrate the transformation process. Finally, the ZnO/N-C and Co/ZnO/N-C composites were employed as catalysts for the hydrogenation of p-nitrophenol by sodium borohydride. The catalytic results suggested that the Co/ZnO/N-C composite with a proper amount of metallic cobalt, better dispersion, small size, and synergetic effect of N doping on carbon displayed a much more efficient catalytic ability for the reduction of p-nitrophenol in comparison with the ZnO/N-C composite as well as the Co/N-C composite synthesized by ZIF-67. The present work would provide further insight into the design of metal-carbon-based materials from the corresponded metal-organic frameworks derived from the relevant metal oxides and development of their applications from the aspect of interface and colloid chemistry.

Zeolitic Imidazolate Framework (ZIF-8) micropolyhedra were employed as a raw material for the synthesis of fine cadmium sulfide/zinc sulfide (CdS/ZnS) composite nanoparticle. The structure and optical properties of the composite nanoparticle were investigated and the results suggested that the introduction of cadmium nitrate tetrahydrate led to the decomposition of ZIF-8 polyhedra. The CdS/ZnS composite nanoparticle was selected as catalyst for the photo-reduction of Cr(VI) ion under visible light. The catalytic data indicated that the fine CdS/ZnS composite nanoparticle displayed an excellent performance and good reusability for the reduction of Cr(VI). In addition, the influence of the dosage of the catalyst, the concentration of Cr(VI) as well as the pH on the catalytic activity was investigated. Finally, the catalytic reaction mechanism was studied to illustrate the possible reaction process by adding the radical scavengers in the reaction solution and Electron Spin-resonance Spectroscopy. It was suggested that the advantage of the fine composite nanoparticles facilitated the exposure to Cr(VI) ions and prevent the aggregation of CdS nanoparticles in the composite structure. Besides, the presence of ZnS in the composite could well prevent the combination of the electrons and holes generated from CdS.

A novel micro-zone electrochemical exfoliation method for the large-scale fabrication of nitrogen-doped carbon quantum dots (N–CQDs) from pre-baked carbon anode (PCA) in ammonium bicarbonate electrolyte has been demonstrated. Therefore, an efficient (90.18 wt% utilization rate of raw material and high-yield conversion of 1.87 g(N-GQDs)g(PCA)−1 due to oxidation weight gain) and environment-friendly mass production (9.36 g in one pot) for N–CQDs really becomes promising and practical. Moreover, the N-CQDs with abundant functional groups and higher nitrogen content (30.18 at%) present strong dispersion stability and enhanced interfacial adsorption with copper substrates. By virtue of the excellent performance, we successfully applied the N–CQDs as an effective inhibitor to alleviate the corrosion of copper. Results showed the corrosion inhibition efficiency of the self-assembled N–CQDs film on the copper reached up to 96.32% at 150 mg/L N–CQDs. The mechanism for the realization of large-scale preparation and self-assembly of N–CQDs was also proposed.

Hard carbon materials have been considered as one of the most promising candidates as the anode in sodium-ion batteries. However, scale application of state-of-the-art hard carbon anodes is still h...

Rock brittleness is an essential mechanical property, which plays a significant role in rock classifications and rockburst risk evaluations. To overcome the problems associated with the traditional brittleness indexes not comprehensively charaterizing the rock strength and deformation behaviors, this study systematically summarized the existing rock brittleness indexes. Then, a novel brittleness index (BICSS) based on the complete stress–strain curves of rock under different confining pressures was proposed. Its advantages included innovatively considering the characteristic stresses and strains at the stage of crack initiation, the peak points, and residual points. The index also described the stress growth rates from the pre-peak crack-initiation stress to the peak stress points, as well as the stress drop rates from the peak stress to the residual stress points. This study conducted uniaxial and triaxial compression tests of metamorphic sandstone, granite, and gneiss obtained from a deeply buried long-line tunnel group. The aforementioned tests were combined with wave velocity tests and thin-section identification tests using polarizing microscopy techniques. The reliability and applicability of the index were then successfully verified. The results showed that the BICSS could not only quantify and classify the brittleness characteristics of different rock types and characterize the confining pressure inhibition behaviors of rock brittleness, but could also comprehensively express the influences of homogeneity, mineral compositions, and particle sizes on the rock brittleness. Finally, through the parameter sensitivity analysis of the BICSS, the influences of subjective errors in the results of the cracking initiation stress and strain values caused by the different selections during the linear elastic phase could be successfully excluded, resulting in the further verification of the stability of the BICSS.

The yolk–shell structure, realized by various synthesis methods, exhibits unique morphology and structural properties, which is currently undergoing a transition from material production technology to energy storage applications. To design an anode for lithium ion batteries (LIBs), a buffer space is designedly built between the Sb2Se3 nanorod yolk and the mesoporous carbon shell to obtain a novel yolk–shell structure (i.e., Sb2Se3@void@C). The confined void space is created by using a sacrificial template (such as silica) and the mesoporous carbon shell is obtained from the pyrolysis of phenolic resin, which effectively improves the electrical conductivity and structural stability of Sb2Se3 anode materials for LIB. Both the void space in the yolk–shell structure and the mesoporous carbon shell can efficiently buffer the volume expansion during the repeated discharge–charge processes, and further maintain the structural integrity. Besides, the permeable mesoporous carbon shell facilitates the electrolyte infiltration into the void space to ensure enough contact area between the Sb2Se3 and electrolyte, which benefits the shortening of the diffusion paths of Li+ ions. As a result, the Sb2Se3@void@C anode exhibits a high reversible specific capacity of 404.8 mA h g−1 at a rate of 1.0 A g−1 for at least 200 cycles, and maintains an average capacity of 594.7 at a rate of 3.0 A g−1. To further establish the detailed lithium storage behavior, in situ XRD is conducted to reveal the conversion reaction and alloying/dealloying reaction mechanisms. This research sheds light on yolk–shell structure designs with various morphologies to improve the electrochemical performance of energy storage materials.

With complicated structures and complex physicochemical reactions, most industrial processes are intrinsically characterized by high dimensionality, nonlinearity, non-Gaussianity, and self-correlation. In this article, a novel probabilistic generative model, called weighted copula regression (WCR), is developed for complex processes. This method employs a probabilistic graphical tool (vine copula) to flexibly handle the underlying patterns via the factorization of complex dependence structures into multiple bivariate copulas. Monte Carlo estimation is incorporated for establishing a fast and reliable computing framework. To avoid overinterpretation of the industrial data, an adaptive sample selection strategy is proposed to explore the underlying distribution of the sample space and to select the most “informative” samples. By considering the copula weights that carry crucial information on the local data, the probabilistic WCR method can provide fast point estimate with prediction uncertainty for every predicted sample. The proposed WCR method is compared with six state-of-the-art methods, and the efficiency is validated using a numerical example and the ethylene cracking furnace process.

The core-disk phenomenon has been observed generally in the drilling process under high-stress conditions. This paper presents the in-situ experimental study of the coring-disking failure mechanism of marble in an underground cavens with 2400 m depth. Based on the disk samples in several boreholes with different diameters, both macro- and micro-morphological characteristics of core-disks’ break surface were analysis, using 3D optical scanning and electron microscope scanning. Moreover, the numerical back analysis was also used to simulate the drilling process for demonstrating the development of core disking. The in-situ experiment results showed that the failure types of core disking consisted of tensile break and shear break, i.e., the shear break usually appears in the edge part of break surface, and tensile break appears in the central part. What’s more, the ration of core-disks thickness to borehole diameter is in a relatively stable range. Numerical back analysis indicated this micro asynchronous break of hard marble is induced by high geostress and unloading drill.

Core discing often occurs in deep rocks under high-stress conditions and has been identified as an important characteristic for deep rock engineering. This paper presents the formation mechanism of core discing firstly. Then, the interaction between diamond drill bits and rock was analyzed based on numerical modeling. A novel drill bit with an inner conical crown for the mitigation of core discing was designed and verified by simulation experiments. The mitigation method was applied in the cavern B1 of CJPL-II and satisfactory results had been achieved. The percentage of core discing had been obviously decreased from 67.8% when drilling with a rectangular crown drill bit, to 26.5% when an inner conical crown drill bit had been adopted. This paper gives full insight into core discing characteristics and provides a new method for core discing mitigation; it will potentially contribute to stress measurement in deep rock engineering.

This paper proposes a process monitoring and fault diagnosis method based on a regular vine (R vine) and Bayesian network. The R vine model structure is determined by searching for the maximum sum ...

In this letter, we present a 24-GSa/s, >20-GHz wideband track-and-hold amplifier (THA) based on indium phosphide (InP) double-heterojunction bipolar transistor (DHBT) technology for high-speed sampling systems. In the proposed approach, the output pole of the input stage is canceled by the zero produced by the emitter capacitive/resistive degeneration, and the bandwidth is thereby extended without voltage drop. The compensation technique for $V_{\mathrm{be}}$ modulation in the output stage is introduced to reduce distortion. The monolithic microwave integrated circuit (MMIC) prototype occupies only 0.69 mm2, and the experimental results show that it has a 0.112– $f_{T}$ bandwidth from dc to 22.3 GHz, which is wider than any ratio reported compact THA solutions using the InP technology. In addition, a spurious-free dynamic range (SFDR) of better than 42 dB and total harmonic distortion (THD) of less than −25 dBc are demonstrated at a 24-GSa/s sampling rate. The THA consumes only 374 mW, which is among the lowest dc power dissipation reported for the InP technology.

This paper aims to propose a novel contextual adaptive fourth-order smoothing method for noise removal. The classical Laplacian operator is first modified into a multi-scale and robust form, which combines two distinct discontinuity measures simultaneously, i.e., inhomogeneity and local spatial gradient. Then the contextual adaptive fourth-order smoothing method is proposed based on the new Laplacian operator. Moreover, a gain control function is employed for the gain control of smoothing in terms of contextual discontinuities to better preserve the important features. Experimental results support that the proposed method achieves the best performance among the comparative methods with respect to some objective evaluation metrics and visual effects.

The strength of a rock cut by non-persistent open joint set is controlled by complex interactions of the joint network and intact rock bridges. An extensive series of uniaxial numerical tests of the particle models are carried out under different joint fabrics and rock compression-tension strength ratios. The test results show joint dip angle is the main factor controlling the overall anisotropic strength characteristics. With joint dip angle increasing, the main failure modes successively appear as splitting failure, block rotation failure, step-path failure, planar failure, and splitting failure. Accordingly, the strength generally shows a trend of decreasing first and then increasing, and the joint dip angle corresponding to the minimum strength is biased towards 0°, usually at 15°–30°. The damage of rock bridges is mainly controlled by tensile failure, except in planar failure mode. Joint spacing has an impact on the local anisotropic strength characteristics. The joint spacing and persistence ratio jointly control the degree of penetration difficulty of the rock bridges. The compression-tension strength ratio of intact rock uniformly affects the absolute magnitude of the jointed rock strength and does not affect its anisotropic characteristics. Based on the weakening mechanism, an empirical strength formula is established to realize the practical equivalent characterization of the anisotropic weakening degrees of the non-persistent open joint set on the rock strength.

Soft-sensing methods have been widely used in recent years to predict key variables that are difficult to measure or involve costly and time-consuming in chemical processes. Owing to the increasing complexity of industrial processes, industrial data often exhibit strong nonlinearities and self-correlation, and the data distribution fails to satisfy the Gaussian assumption. To address these problems, a vine copula-based soft-sensor model combined with the rolling pin method is proposed. This approach uses a D-vine copula to model a joint probability distribution of auxiliary variables and a key variable. In accordance with the joint distribution, the predicted value of the key variable can be determined by weighting the training samples. During modeling, the Bayesian information criterion is adopted to select the best-fitted copula pairs. Given the nonmonotonicity between variables of actual industrial data, the rolling pin monotonic transformation is simultaneously introduced to improve the suitability of...

Flooding is a very common natural hazard that causes catastrophic effects worldwide. Recently, ensemble-based techniques have become popular in flood susceptibility modelling due to their greater strength and efficiency in the prediction of flood locations. Thus, the aim of this study was to employ machine learning-based Reduced-error pruning trees (REPTree) with Bagging (Bag-REPTree) and Random subspace (RS-REPTree) ensemble frameworks for spatial prediction of flood susceptibility using a geographic information system (GIS). First, a flood spatial database was constructed with 363 flood locations and thirteen flood influencing factors, namely altitude, slope angle, slope aspect, curvature, stream power index (SPI), sediment transport index (STI), topographic wetness index (TWI), distance to rivers, normalized difference vegetation index (NDVI), soil, land use, lithology, and rainfall. Subsequently, correlation attribute evaluation (CAE) was used as the factor selection method for optimization of input factors. Finally, the receiver operating characteristic (ROC) curve, standard error (SE), confidence interval (CI) at 95%, and Wilcoxon signed-rank test were used to validate and compare the performance of the models. Results show that the RS-REPTree model has the highest prediction capability for flood susceptibility assessment, with the highest area under (the ROC) curve (AUC) value (0.949, 0.907), the smallest SE (0.011, 0.023), and the narrowest CI (95%) (0.928–0.970, 0.863–0.952) for the training and validation datasets. It was followed by the Bag-REPTree and REPTree models, respectively. The results also proved the superiority of the ensemble method over using these methods individually.

Photodegradation has been considered as an efficient environmental remediation technology to eliminate organic pollutants from wastewater, and the calling for high-performance photocatalysts is end...

Unconventional natural gas, including coalbed methane and shale gas, has become important natural gas resources. Coal and shale reservoirs are characterised by low porosity and low permeability and difficult for gas production. These reservoirs are also considered as fractured reservoirs, i.e. the natural fracture/cleat system in coals and bedding direction microfractures in shales. Permeabilities of these reservoirs are sensitive to stress change. During gas production, the pressure drawdown significantly increases effective stress, and thus decreases the absolute permeability. The relationship between permeability and stress is characterised by fracture compressibility, which is difficult and costly to be obtained from the field, but can be acquired easily from laboratory measurement. In this review article, the laboratory methods to obtain fracture compressibility were reviewed. Literature data on fracture compressibility for coals and shales were collated and the relationships between fracture compressibility and pressure, stress and rock properties were discussed. It is found that fracture compressibility is higher for coals than for shales, and the fracture compressibility for proppant supported fracture is even lower than that for the same shale or coal. Moreover, fracture compressibility is variable depending on gas type, gas pressure, and stress. Fracture compressibility has no correlation with absolute permeability in general, but has a weak positive correlation for the same sample.

This paper proposes a boosting vine copula-based dependence description (BVCDD) method for multivariate and multimode process monitoring. The BVCDD aims to improve the standard vine copula-based de ...

Tectonic shear belts, with their low mechanical strengths, large spatial extents and obvious shearing damage, present challenges for the excavation of high slopes. In this study, we described the basic unloading performances of shear belts induced by excavation through observational data and numerical back analysis. The unloading deformation and failure processes of deep outward-dipping shear belts exposed on a hydraulic slope nearly 300 m tall were investigated first. The field observation and monitoring data indicated that the excavation-induced deformation pattern of the outward-dipping shear belt can be divided into two stages: primarily opening deformation normal to the shear belt during the first stage and primarily shear deformation along the shear belt during the second stage, manifested as opening and shear cracks along the active shear belt. Then, the numerical and analytical analysis were performed to expose the displacement evolution of the shear belt during the multistep excavation of the slope from the top down. The back analysis showed that the grading deformation mechanism of the shear belt was primarily related to the reduction of normal compressive stress on the shear belt's plane due to slope excavation. The reinforcement schemes, including a prestressed anchor cable to limit deep unloading deformation and a prestressed rock bolt to restrain the surface relaxation of the rock mass of the slope, were also discussed. In practice, actual excavation and corresponding monitoring data indicated that the unloading mechanism and supporting measures for the shear belt presented in this study were reasonable and effective. These presented experiences can also enrich the stability analysis and support design for similar high slopes.

Because of its local property, cellular automaton method has been widely applied in different subjects, but the main problem is that the cellular updating is time-consuming. In order to improve its calculation efficiency, a fast successive relaxation updating method is proposed in this paper. Firstly, an accelerating factor ω is defined, and a fast successive relaxation updating theory and its corresponding convergence conditions are developed. In each updating step, the displacement increment is enlarged ω times as a new increment to replace the old one, similarly, the nodal forces for its neighbors caused by this displacement increment are also enlarged by the same accelerating factor, and do those updating operations until the convergence is achieved. By this method, the convergence rate is greatly improved, by a suitable accelerating factor, 90 to 98% of iteration steps are decreased compared to that of the traditional method. Besides, the influence factors for the accelerating factor are studied, and numerical studies show that the suitable accelerating factor is 1.85

In this paper, the recently proposed continuous-discontinuous cellular automaton method (CDCA) is further developed for elastodynamic problems in 2D elastic solids. A continuity-to-discontinuity enriched function technique is developed for elastodynamics and combined with a cellular automaton formulation; the cellular automaton theory for elastodynamics, in which fast adaptive updating rules for the cell and its neighbors are developed, and the time domain CDCA are proposed. In this method, the cracks are independent of the integral meshes, and no assembled global matrix is needed for the whole process. Time-dependent equations for the cells are discretized by the Newmark method, and rapidly solved by the cellular automaton method. To analyze the fracture behaviors of elastic solids with dynamic loads, mixed-mode dynamic stress intensity factors are obtained by the interaction integral method. Some numerical examples for elastodynamic problems are studied to validate the accuracy and efficiency of the present method, and solutions from analytical method and some other methods are employed to show the high accuracy of the CDCA.

Natural rock joints with infilling materials such as clay, broken rock fragments, or even cement mortar infusion material are common in the field of rock engineering. The fracture behavior of a rock with a filled flaw is related to both the flaw inclination and mechanical properties of the infilling materials. In this study, uniaxial compression experiments were performed for sandstone specimens with different flaw inclinations varying from 0° to 90°, and four kinds of infilling conditions, including no filler, gypsum filler, cement filler, and resin filler were considered. The damage process of specimens was revealed and traced by acoustic emission (AE) and digital image correlation (DIC) to comprehensively understand the cracking evolution. Macroscopic cracking information was recorded with a high-resolution camera, and crack patterns were identified and classified. The influence of infilling material and flaw inclination on the sandstone cracking process was studied. The tensile stress was found to be suppressed due to the existence of infilling materials, and different infilling materials have different effects on the crack initiation stress. As a result, specimens with a filled flaw have larger crack initiation stress levels and smaller crack inclination angles than specimens with an unfilled flaw. The effects of infilling materials and flaw inclination angles on crack initiation are analyzed with a theoretical model based on the Coulomb friction law. The compressibility effect of infilling materials on the cracking behavior is also investigated through displacement and strain fields.

Understanding three-dimensional (3D) in situ stress field is of key importance for estimating the stability of large deep underground cavern groups near valleys. However, the complete 3D in situ stress fields around large deep underground cavern groups are difficult to determine based on in situ stress data from a limited number of measuring points due to the insufficient representativeness and unreliability of such measurements. In this study, an integrated approach for estimating the 3D in situ stress field around a large deep underground cavern group near a valley is developed based on incomplete in situ stress measurements and the stress-induced failures of tunnels excavated prior to the step excavation of the cavern group. This integrated approach is implemented via four interrelated and progressive basic steps, i.e. inference of the regional tectonic stress field direction, analyses of in situ stress characteristics and measurement reliability, regression-based in situ stress field analysis and reliability assessment, and modified in situ stress field analysis and reliability verification. The orientations and magnitudes of the 3D in situ stress field can be analyzed and obtained at a strategic level following these four basic steps. First, the tectonic stress field direction around the cavern group is deduced in accordance with the regional tectonic framework and verified using a regional crustal deformation velocity map. Second, the reliability of the in situ stress measurements is verified based on the locations and depths of stress-induced brittle failures in small tunnels (such as exploratory tunnels and pilot tunnels) within the excavation range of the cavern group. Third, considering the influences of the valley topography and major geological structures, the 3D in situ stress field is regressed using numerical simulation and multiple linear regression techniques based on the in situ stress measurements. Finally, the regressed in situ stress field is further modified and reverified based on the stress-induced brittle failures of small tunnels and the initial excavation of the cavern group. A case study of the Shuangjiangkou underground cavern group demonstrates that the proposed approach is reliable for estimating the 3D in situ stress fields of large deep underground cavern groups near valleys, thus contributing to the optimization of practical excavation and design of mitigating the instability of the surrounding rock masses during step excavations.

Uncertainty is critical to the tunnel design. In this study, a novel reliability-based design (RBD) method was developed by integrating the rock-support interaction and its uncertainties for rock tunnels. In this method, the rock-support interactions were analyzed based on a convergence-confinement method. Uncertainties were estimated by reliability analysis using Excel Solver. Chaotic particle swarm optimization (CPSO) was adopted to search the optimal tunnel design parameters based on the rock-support interaction analysis. The proposed method for estimating the reliability index and determining the tunnel support parameters was introduced in detail. To illustrate the proposed method, it was applied to two tunnels with rock-bolt and combined support systems. The results indicated that the method could obtain accurate solutions with a dramatically improved computing efficiency, guaranteeing the tunnel stability at the same time. The developed method provides an excellent way to deal with the uncertainty in tunnel design. It was proved to be an efficient and effective method for the support designs of rock tunnels.

Globally, and in China, landslides constitute one of the most important and frequently encountered natural hazard events. In the present study, landslide susceptibility evaluation was undertaken using novel ensembles of bivariate statistical-methods-based (evidential belief function (EBF), statistical index (SI), and weights of evidence (WoE)) kernel logistic regression machine learning classifiers. A landslide inventory comprising 222 landslides and 15 conditioning factors (slope angle, slope aspect, altitude, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to rivers, distance to roads, distance to faults, NDVI, land use, lithology, and rainfall) was prepared as the spatial database. Correlation analysis and selection of conditioning factors were conducted using multicollinearity analysis and classifier attribute evaluation methods, respectively. The receiver operating characteristic curve method was used to validate the models. The areas under the success rate (AUC_T) and prediction rate (AUC_P) curves and landslide density analysis were also used to assess the prediction capability of the landslide susceptibility maps. Results showed that the EBF-KLR hybrid model had the highest predictive capability in landslide susceptibility assessment (AUC values of 0.814 and 0.753 for the training and validation datasets, respectively; AUC_T value of 0.8511 and AUC_P value of 0.7615), followed in descending order by the SI-KLR and WoE-KLR hybrid models. These findings indicate that hybrid models could improve the predictive capability of bivariate models, and that the EBF-KLR is a promising hybrid model for the spatial prediction of landslides in susceptible areas.

Multi-plant indirect heat integration via an intermediate fluid loop is an effective and energy-saving method of heat recovery. It is most suitable in practical applications because it requires fewer inter-plant pipelines and has the advantages of a simple heat exchanger network. A well-designed heat exchanger network will significantly increase economic efficiency and reduce energy consumption in plants. In this paper, a multi-plant indirect heat exchanger network model is developed for recycling heat using intermediate fluid. This model aims to minimize the total annual cost, including utility cost, number of units and heat transfer area cost. An Alopex-based evolutionary algorithm is used to optimize the model and obtain the heat capacity flow rate of intermediate fluids, the temperature of the heat transfer medium and the configuration of the superstructure simultaneously. Results from three examples demonstrate that the proposed model can perform well in multi-plant heat exchanger network synthesis.

This study evaluates the possibility of a cascade failure by developing a coupled breach-modeling platform based on one-dimensional flow modeling of the river channel, flood propagation, regulation process of reservoir fluctuation, overtopping with breaching, and wave damping downstream. A hyperbolic model of the DB-IWHR was embedded into the platform to simulate the dam breaching process. Five breach models and software were used to calculate the Tangjiashan barrier lake breaching. The results of a sensitivity study were then compared with the measured data. The peak flow and the time of occurrence were confirmed to be predictable with a reasonable accuracy if the input values were within ranges appropriate for the model. The approach was applied to a case involving two layout planning schemes for a cascade of rock-filled dams under extreme operating conditions. The probability of the failure of a key control cascade downstream caused by a continuous cascade breach upstream was simulated. Moreover, measures to prevent the transmission of risk by advance warnings were investigated. The proposed methodology and the discharge capacity measures provide guidelines to assess the risk to a cascade of dams under extreme operating conditions and offer support for the design criteria of unusual discharge structures for very large dams.

Zonal disintegration refers to the phenomenon whereby fractured zones and intact zones appear alternately in surrounding hard rocks under high stress conditions. In this study, zonal disintegration within hard surrounding rocks of deep tunnels at the China Jinping Underground Laboratory Phase II (CJPL-II) was observed by using a digital borehole televiewer in pre-drilled boreholes. The results revealed that fractured zones within intact high-strength marbles were small and exhibited a higher degree of fracturing, whereas fractured zones within low-strength, low-integrity, marbles showed fewer, yet larger fractures. An evaluation method based on rock mass integrity index using digital borehole televiewer data (RMIBT) has been proposed for the analysis of zonal disintegration process in the deep hard rocks surrounding the tunnels. By using the method we were able to quantify the initiation and evolution of fractures during zonal disintegration. The formation mechanism of the second and third fractured zones induced by the existing fractures was further investigated using numerical analysis. The data provide an insight into the evolution of failures in, and a basis for support design and stability control of, deep engineering works in hard rock.

This paper proposes a new process monitoring method based on vine copula and active learning strategy under a limited number of labeled samples. The proposed method uses active learning strategy and the generalized Bayesian inference-based probability (GBIP) index to choose samples that can provide the most significant information for the process monitoring model. An adaptive strategy is used to select the number of training samples in every active learning loop. Then, the vine copula-based dependence description (VCDD) is used to fulfill fault detection for complex chemical processes. The validity and effectiveness of the proposed approach are illustrated using a numerical example and the Tennessee Eastman (TE) benchmark process. The results show that the proposed method can maximize the process monitoring performance while minimizing the number of samples labeled.

In the field of chemical process monitoring, the vine copula model provides a new idea for describing the interdependence between high-dimensional complex variables, and directly characterizes the correlation without dimensional reduction. However, in actual industrial processes, the number of pair copulas to be optimized and the parameters to be estimated increase rapidly when the dimensionality of the variables is large. This greatly increases the computational load and reduces the detection efficiency. In this paper, a fault diagnosis method based on a simplified R-vine (SRV) model is proposed. Without reducing the precision of the model significantly, the simplified level is set to reduce the complexity of the workload and calculations. The simplified level of an R-vine model is obtained by a Vuong test. Then, the generalized local probability (GLP) of the non-Gaussian state is constructed by using the theory of highest density region (HDR) and a density quantile table. The monitoring results of the T...

A group of nonsingular enrichment functions is proposed for an exact representation of the cohesive stresses, which are consistent with a nonsingular asymptotic stress field around a crack tip. An improvement in the adaptive crack tip polar coordinate is proposed for treating the local polar coordinate error. Finally, a discontinuous cellular automation model was developed, including a cell model, cell state, and updating rules. Combined with these developments and the cohesive rock model, a continuous-discontinuous cellular automaton method (CDCA) for a cohesive crack analysis is proposed, through which the calculation is only limited to the cell locality without re-meshing, and therefore, no assembled global stiffness matrix is required. Numerical simulations reveal the accuracy and efficiency of the presented method.

The heat exchanger network (HEN) is traditionally used for optimal heat recovery in a single chemical plant, while the multi-plant counterparts have been studied in recent years primarily for the purpose of reaping additional overall energy savings. Since all these works focused primarily upon minimization of the total energy cost, the resulting interplant heat integration arrangements were often infeasible due to the fact that the individual savings are not always acceptable to all participating parties. Although a few studies addressed this cost-sharing issue, the existing methodologies are still not mature enough for realistic applications. The present paper outlines a rigorous model-based two-stage procedure to handle this practical problem in the spirit of a cooperative game. The minimum total annual cost (TAC) of each and every potential coalition was first determined with a conventional MINLP model, while the core and the risk-based Shapley values of all players were then computed with explicit formulas derived in this work to settle the benefit allocation issues. A simple example is presented at the end of this paper to demonstrate the feasibility of the proposed approach.

This paper presents the results of in situ investigation of the internal displacement of hard surrounding rock masses within deep tunnels at China’s Jinping Underground Laboratory Phase II. The displacement evolution of the surrounding rock during the entire excavation processes was monitored continuously using pre-installed continuous-recording multi-point extensometers. The evolution of excavation-damaged zones and fractures in rock masses were also observed using acoustic velocity testing and digital borehole cameras, respectively. The results show four kinds of displacement behaviours of the hard surrounding rock masses during the excavation process. The displacement in the inner region of the surrounding rock was found to be greater than that of the rock masses near the tunnel’s side walls in some excavation stages. This leads to a multi-modal distribution characteristic of internal displacement for hard surrounding rock masses within deep tunnels. A further analysis of the evolution information on the damages and fractures inside the surrounding rock masses reveals the effects of excavation disturbances and local geological conditions. This recognition can be used as the reference for excavation and supporting design and stability evaluations of hard-rock tunnels under high-stress conditions.

Rockburst is a type of dynamic failure and often causes considerable damage during the construction of underground engineering. Geological structures have been regarded as a crucial factor influencing rockburst distribution, and more related research is urgently needed. This paper presents microseismic monitoring information, characteristics of 151 rockbursts, and various structural planes collected in detail from a deep tunnel located in Southwest China. The results show that microseismic activity tends to increase when joints with large scale begin to appear and vanish. Rockburst risk always increases between the spandrels and around the intersection of two joint sets. The joint dip angle changes the rockburst risk. In the presence of one or two joint sets with a 70– 80° dip angle, rockbursts are more prone to occur. The conclusions can be interpreted with the discrete element method. When more joints are encountered, the total number of rockbursts may decrease, but the rockbursts are more likely to be strong or induce collapse, causing more damage. This research can improve the understanding of rockburst mechanisms and guide the choice of construction and support methods.

The shearing performance and strength of the interface between rock foundations and structural concrete is a key issue for safety estimation in geotechnical engineering containing rock-concrete interface. In this paper, we focused on the effects of concrete wall strength and normal stress on the unbonding performances of sandstone-concrete interface. First, many sandstone-concrete specimens containing a natural dam bedrock interface had been produced by using “3D optical scanning technology + 3D digital engraving technology + pouring concrete” method. Subsequently, after the sandstone-concrete specimens were prepared, a series of shear tests for these sandstone-concrete specimens were carried out under different normal loading conditions. Finally, the shear characteristics of sandstone-concrete interface were discussed, and an improved rock-concrete shear strength formula was proposed based on the exposed experimental tests and theoretical derivation. Three primary outcomes are as follows: (i) shear damage only occurred at some special positions of the concrete wall, and its degree of shear damage gradually increased with increasing normal stress; (ii) the damage degree of the concrete surface performed obvious localization and nonuniformity was affected by the concrete strength; (iii) the global shear strength and residual strength of the rock-concrete interface were affected by the concrete strength and the normal load. Moreover, an improved rock-concrete shear strength formula was proposed based on the experimental cognition. This strength formula considers both the interface roughness and the mechanical strength of rock/concrete materials, and is more reasonable for estimating the shear strength of rock-concrete interfaces in geotechnical engineering.

The application of evolutionary algorithms (EAs) is becoming widespread in engineering optimisation problems because of their simplicity and effectiveness. The Alopex-based evolutionary algorithm (...

A novel copula subspace division strategy is proposed for fault detection and diagnosis. High-dimensional industrial data are analyzed in two elemental subspaces: margin distribution subspace (MDS) modeled by joint margin distribution, and dependence structure subspace (DSS) modeled by copula. The highest density regions of two submodels are introduced and quantified using probability indices. To improve the robustness of the monitoring index, a hyperrectangular control boundary in MDS is designed, and the equivalent univariate control limits are estimated. Two associated contribution indices are also constructed for fault diagnosis. The interactive relationships among the root-cause variables are investigated via a proposed state chart. The effectiveness and superiority of the proposed approaches (double-subspace and multisubspace) are validated using a numerical example and the Tennessee Eastman chemical process. Better monitoring performance is achieved compared with some conventional approaches such a...

Complex dependence structures often exist in chemical process multivariate data. Although they are difficult to capture, vine copula shows good performance and stronger flexibility in depicting the highly nonlinear dependencies. To identify and fully understand the complex dependence patterns in multivariate data, a mixture of D-vine copulas (MDVC) is proposed. By using the expectation-maximization (EM) algorithm and stepwise semi-parametric (SSP) estimation for parameter estimation, the proposed model can depict the complex dependence structures in multivariate data. The highest density region (HDR) and the density quantile approach (DQA) are both used to construct the highest density region distance-based probability (HDRP) index to achieve a real-time process fault monitoring. The effectiveness and benefits of the proposed model are illustrated with a numerical example, the Tennessee Eastman (TE) benchmark process and a real acetic acid dehydration distillation system for fault detection. The results show that the proposed mixture of D-vine copulas can achieve good performance in chemical process fault monitoring.

The product of the self-metathesis of soybean oil (MSBO) containing ∼80% of triacylglycerol (TAG) oligomers was easily transformed into polyols by a conventional one-pot epoxidation and hydroxylation reaction. The MSBO polyol inherited the oligomeric structure of its parent oil without significantly altering its functionality. The OH-value of the polyol from MSBO was easily customized by controlling the reaction conditions. Polyols having OH-values between 83 and 263 mg KOH/g were achieved and used to make polyurethane foams with controlled combinations of strength (stress at 10% deformation of 0.07–0.75 MPa) and flexibility (recovery from deep compression of 75–95%) suitable for versatile applications, particularly those requiring strength and resiliency. The large resistance to load and significant spring for recovery achieved by the polyurethane foams are attributable to the association of the high OH value and oligomeric structure of the MSBO polyols. More importantly, the self-metathesis is demonstrated to extend the range of the products derived from vegetable oils, particularly polyols and polyurethane foams.

A novel boundary type meshless method called continuous–discontinuous hybrid boundary node method is proposed in this paper, in which the enriched discontinuous shape function is developed to solve linear elastic crack problems. Firstly, the whole boundary is divided into several individual segments, and variables on each one of those segments are interpolated, respectively. For continuous segments, radial point interpolation method is employed. In regard to discontinuous segments, the enriched discontinuous basis functions combining with radial point interpolation method are developed for simulating the discontinuity of displacement and stress field on surfaces of crack, and the near tip asymptotic field functions are employed for simulating the high gradient of stress field around crack tip, so that high accuracy and discontinuity property of a crack can be easily described. Stress intensity factors are calculated directly using displacement extrapolation by displacement field near crack tip. Some numerical examples are shown that the present method is effective and can be widely applied in some practical engineering.

This paper presents the results of in situ observation of rock spalling process of a large underground powerhouse, with 34 m in span and 88.7 m in height, during excavation layer by layer over two years. A method for in situ observation of rock spalling process has been established in pre-installed boreholes by using digital borehole camera. Observation results clearly show the whole process of rock fracturing and the associated spalling failure. Not only could the development of rock fracturing and spalling affected by the step-by-step excavations along the cavern's axis be captured, but also could the effect of the subsequent excavation layer by layer on the previous rock fracturing and spalling area be observed. The failure mechanism of rock mass surrounding the large cavern, which involves complex excavation sequences, could be better understood through the observation results. The difference of rock spalling behavior between large cavern and small tunnel is discussed. Influence of geostress, geological structures, rock mechanical properties, and layered excavation process on rock spalling process has been analyzed. The results in this study is instructive for rethinking the engineering design including the excavation and support at similar large underground caverns, as well as for the dynamic adjustment of excavation schemes and support optimization during the construction of a large cavern subjected to high geostress.

The updating scheme is very important for cellular automata, which costs the vast majority of CPU time of the whole calculating process and dramatically influences the convergence rate, and the traditional node sequence scheme is often ineffective. Aimed at this issue, based on the unbalanced nodal force, an adaptive updating scheme for continuous–discontinuous cellular automaton method is proposed in this paper. The cell whose unbalanced force is maximum is the first updating cell, and the next one is its neighbors whose unbalanced force is also maximum in all remain neighbors, and do the updating operation according to this scheme until the updating for all cells is finished. Theory and convergence of the present scheme is studied, then we can get the maximum calculating efficiency, and the computational expanse can be greatly improved. Some examples by different iteration schemes are shown to demonstrate that the present scheme is efficient and time saving.

Rocks that are far removed from caverns or tunnels peripheries and subjected to high geostress may undergo ‘deep fracturing’. Deep fracturing of hard rock can cause serious hazards that cause delays and increase the cost of construction of underground caverns with high sidewalls and large spans (especially when subjected to high geostress). To extensively investigate the mechanism responsible for deep fracturing, and the relationship between fracturing and the excavation & support of caverns, this paper presents a basic procedure for making in situ observations on the deep fracturing process in hard rock. The basic procedure involves predicting the stress concentration zones in the surrounding rocks of caverns induced by excavation using geomechanical techniques. Boreholes are then drilled through these stress concentration zones from pre-existing tunnels (such as auxiliary galleries) toward the caverns before its excavation. Continuous observations of the fracturing of the surrounding rocks are performed during excavation using a borehole camera in the boreholes in order to analyze the evolution of the fracturing process. The deep fracturing observed in a large underground cavern (high sidewalls and large span) in southwest China excavated in basalt under high geostress is also discussed. By continuously observing the hard rock surrounding the arch on the upstream side of the cavern during the excavation of the first three layers, it was observed that the fracturing developed into the surrounding rocks with downward excavation of the cavern. Fracturing was found at distances up to 8–9 m from the cavern periphery during the excavation of Layer III. Also, the cracks propagated along pre-existing joints or at the interfaces between quartz porphyry and the rock matrix. The relationship between deep fracturing of the surrounding rocks and the advance of the cavern working faces was analyzed during excavation of Layer Ib. The results indicate that the extent of the stress relief zone is about 7 m if footage of 3 m is adopted for the rate of advance of the cavern faces. An analysis of the effects of the initial geostress and evolving stress concentration on deep fracturing was also made. It could be concluded that the deep fracturing of the rocks in the upstream side of the cavern is caused by the combined effect of the high initial geostress, the transfer of the stress concentration zone toward the deep surrounding rocks, and the occurrence of discontinuities.

The response surface method (RSM), a simple and effective approximation technique, is widely used for reliability analysis in civil engineering. However, the traditional RSM needs a considerable number of samples and is computationally intensive and time-consuming for practical engineering problems with many variables. To overcome these problems, this study proposes a new approach that samples experimental points based on the difference between the last two trial design points. This new method constructs the response surface using a support vector machine (SVM); the SVM can build complex, nonlinear relations between random variables and approximate the performance function using fewer experimental points. This approach can reduce the number of experimental points and improve the efficiency and accuracy of reliability analysis. The advantages of the proposed method were verified using four examples involving random variables with different distributions and correlation structures. The results show that this approach can obtain the design point and reliability index with fewer experimental points and better accuracy. The proposed method was also employed to assess the reliability of a numerically modeled tunnel. The results indicate that this new method is applicable to practical, complex engineering problems such as rock engineering problems.

Filled joints, which are characterized by high deformability and low shear strength, are among the most critical discontinuities in rock mass and may be sheared repeatedly when subject to cyclic loading. Shear tests were carried out on tension splitting joints, with soil and granular cement mortar particles used as infillings, and the effects of the shear history on the mechanical behavior and acoustic emission (AE) of clean and filled joints were studied. The maximum strength in the subsequent shears was approximately 60% of the peak strength of the first shear for a clean joint, and the friction angle degraded from 63° to 45° after the first shear. The maximum shear strength of the filled joints was lower than 35% of the peak strength of the clean joint under the same normal stress. The change in the shear strength of filled joints with the number of shearing cycles was closely related to the transformation of the shear medium. Rolling friction occurred and the shear strength was low for the granular particle-filled joint, but the strength was elevated when the particles were crushed and sliding friction occurred. The AEs were significantly reduced during the second shear for the clean joint, and the peak AEs were mainly obtained at or near the turning point of the shear stress curve for the filled joint. The AEs were the highest for the cement particle-filled joint and lowest for the dry soil-filled joint; when subjected to repeated shears, the AEs were more complex because of the continuous changes to the shear medium. The evolution of the AEs with the shear displacement can accurately reflect the shear failure mechanism during a single shear process.

The columnar jointed basalt (CJB) in the left-bank dam foundation of the Baihetan hydropower station, China, is a special jointed rock mass with a columnar cylinder structure. A field investigation revealed three types of joints developing in the CJB: (1) columnar joints, (2) internal steeply dipping joints (ISDJ), and (3) internal gently dipping joints (IGDJ). A uniform distribution survey lines method (UDSLM) is proposed to describe quantitatively the spatial structural features of CJB exposed in limited outcrops. The visible spacing of internal joints in CJB is found to evolve; joint spacing decreases with increased degrees of weathering, disturbance, and time after unloading excavation. Combined with the actual structure, the formation mechanism of CJB is discussed from the structure of a single column to the whole rock mass, based on the contraction hypothesis. A columnar joint tensor, which is closely related to the CJB deformation characteristics, is established for describing the complex columnar joint network in the three-dimensional space based on the measurement data with the UDSLM. In addition, the structural characteristics of intact columns were exposed through dismantling cuboid specimens of 0.5 m edge lengths and 1.0 m height, verifying the rationality of the UDSLM and the evaluation of structural characteristics of CJB in the Baihetan dam foundation. This in situ study presents an in-depth understanding of CJB structure and provides meaningful guidance for excavation and supporting reinforcement for the CJB exposed on the Chinese Baihetan dam foundation.