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Heat balance plays a significant role in reflecting the health state of aluminum electrolysis process (AEP). However, current methods hardly take into consideration the quantitative Heat Balance Indicator (HBI) construction by using the unlabeled data. In addition, it is limited to construct HBI by learning the complex relationship between degraded features and large-scale HBI labels in a supervised manner, because the labeled data are scarce and annotations are expensive in practice. To quantitatively construct HBI by using the unlabeled data, this paper proposes an unsupervised HBI construction method based on variational autoencoder (VAE). Firstly, we propose fuzzy evaluation strategy to estimate the tendency of cell temperature to highlight the trend of heat balance. Rather than simply using the latent features, we extract the feature representation of the heat balance state considering not only the latent features but also the reconstruction error. Finally, HBI is constructed by calculating the distance between the features representation of normal heat balance and degraded state. The applications of heat balance monitoring in a real-world aluminum electrolysis plant are performed to verify its effectiveness. The experimental results demonstrate that our proposed HBI construction method can better represent heat balance state of AEP, the average fault detection rate can achieve 80% for the monitoring electrolytic cells, increasing by more than 3% compared with these traditional monitoring statistics. [ABSTRACT FROM AUTHOR]

Satisfying the process technical requirements while optimizing the control of oxygen and zinc oxide is the main task for optimal operation of the iron removal process. However, due to the complicated mechanism and varied production conditions, the process is difficult to achieve optimal operation with the simple controller. The manual control, as a result, is extensively used in practice. In this paper, we develop an optimal setting and control (OSC) system for the iron removal process to achieve its technical requirements with minimal process consumptions. The OSC system is composed of a neural network soft-sensor, an optimal setting module, an optimal controller, and a fuzzy-logic-based compensator. First, we define the oxygen reaction efficiency (ORE) to measure the difference between the theoretical oxygen amount and its actual amount. Due to the ORE cannot be measured online and it varies with the production conditions, an adaptive weight radial basis function neural network soft-sensor is designed to estimate it. The adaptive weight adjusting method contributes to improve the adaptability of the soft-sensor, and its convergence is discussed. The optimal setting module provides the set-point of outlet ferrous ion concentration for the optimal operation of every reactor. The steady-state optimal control of oxygen and zinc oxide is then established, and the compensator compensates the control inputs utilizing the feedforward and feedback information. Finally, simulations validate that the ORE is important for the optimal control of the process. Furthermore, industrial experiments are presented to verify the effectiveness and potential of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this paper, a novel three-layer coordinating optimization and control strategy involving fuzzy neural networks (FNNs) is proposed for industrial plant-wide control. This strategy includes a coordinator (top layer), local optimizers (middle layer), and local controllers (bottom layer). The coordinator determines and coordinates set-points of production indices for each process in the plant, aiming to achieve plant-wide optimal control. The local optimizers optimize individual unit and deliver the information to the coordinator. The controllers calculate optimal control inputs for the processes according to the set-points. Model predictive control (MPC) is used in this layer. Also used are FNNs with a gradient-based learning algorithm, which are trained to represent the models of the processes that are controlled by MPC. By constructing a Lyapunov function, convergence of the FNNs is established. Experiments are carried out in the largest zinc hydrometallurgy plant in China. The results demonstrate performance of our strategy in tracking the set-points and saving processing costs. Moreover, the strategy achieves a more optimal overall plant operation when compared to the same FNN-based MPC scheme that does not use the coordinator. [ABSTRACT FROM AUTHOR]

• A hybrid fuzzy control strategy is developed for the control of the goethite process. • The hybrid fuzzy control strategy combines a T1 FLC and an IT2 FLC. • The T1 FLC with parameter tuning method is designed to control the zinc oxide additive rate. • The IT2 FLC is constructed to control the oxygen flow rate, and simultaneous perturbation gradient approximation method is used to update the parameters. • The effectiveness of the proposed control strategy is verified by the simulations using real-world production data. The goethite process is a complicated reaction system which holds a significant position in zinc hydrometallurgy process. It exhibits nonlinear behavior and time-delay nature because of the chemical reactions. To achieve the stable and real-time control performance, a hybrid fuzzy control strategy integrating a type-1 and a type-2 fuzzy logic controllers is proposed in this paper. According to the on-line measured pH, the type-1 fuzzy controller (T1 FLC) via the Takagi–Sugeno fuzzy control is employed to control the zinc oxide additive rate. A parameter tuning method that does not require the system model is designed for the T1 FLC. Because the ferrous ion concentration cannot be measured on-line, the interval type-2 fuzzy logic controller (IT2 FLC) is utilized to control the oxygen flow rate. According to the feedback information, gradient descent algorithm is used to update the parameters in the IT2 FLC. Because of the unknown system structure, gradient descent information is estimated by the simultaneous perturbation stochastic approximation. Finally, simulations are conducted using the practical production data. The simulation results show the effectiveness of the proposed strategy. The hybrid fuzzy control strategy improves the control performance of the goethite process, compared with PID controller. [ABSTRACT FROM AUTHOR]

An adaptive generalized predictive control (GPC) scheme for an industrial process is designed based on a neuron adaptive splitting and merging radial basis function neural network (NASM-RBFNN) in this paper. The NASM-RBFNN is developed to identify the dynamic behaviors of the industrial process. In order to provide an accurate prediction model for the GPC, a neuron adaptive splitting and merging strategy and a weighted parameters adaptive correction approach are proposed. The neuron adaptive splitting and merging strategy can automatically add or delete the hidden neurons on-line, and the weighted parameters adaptive correction approach can update the weights based on the error of the neural network. The proposed approaches can enable the NASM-RBFNN to be adapted to the time-varying production condition and stochastic disturbance. The stability analysis and convergence of neuron adaptive splitting and merging strategy and weighted parameters adaptive correction approach are given. Finally, the NASM-RBFNN-based GPC (NASM-RBFNN-GPC) is applied to control the iron removal process in the largest zinc hydrometallurgy plant in China. The industrial experiments demonstrate that the NASM-RBFNN-GPC has a satisfactory tracking and control performance. [ABSTRACT FROM AUTHOR]

In aluminum electrolysis process, cell temperature is an important index to reflect the current efficiency of electrolytic cell. Maintaining cell temperature in an appropriate range can improve current efficiency and economic benefits. Because aluminum electrolysis process is in a complex environment with high temperature, strong corrosivity, multivariable coupling and nonlinearity, cell temperature measuring instrument and equipment have the shortcomings of short service life and high cost. Therefore, this paper develops a cell temperature prediction model based on the integration of dual attention long short-term memory (DA-LSTM) and autoregressive moving average (ARMA). Firstly, the cell temperature series is decomposed into non-stationary sub-sequence and stationary sub-sequences by wavelet transform. The DA-LSTM is proposed to approximate non-stationary sub-sequence, which introduces a two-stage attention mechanism including feature attention mechanism and temporal attention mechanism. ARMA is employed to predict the stationary sub-sequences. Then, the integration model for the cell temperature prediction is reconstructed through multiple linear regression of DA-LSTM and ARMA. The integration model can overcome the problems that the prediction accuracy of a single model is low and the hysteresis phenomenon due to the mixed multi-information of aluminum electrolysis time series data. Experiments in a real-world aluminum electrolysis production process are conducted to demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The analytical structure of fuzzy controller is important for better understanding and effective design of the fuzzy control system, especially for explaining why fuzzy control system work well. In this paper, we develop a three-dimensional fuzzy controller with arbitrary triangular input fuzzy sets. Then, the analytical structure of this fuzzy controller is derived rigorously, and some properties of this controller are given. To determine the parameters of the fuzzy controller, a novel proximal policy optimization algorithm with recall pool (RP-PPO) is proposed. A recall pool is designed in proximal policy optimization algorithm to store the best ten sets of parameters to enhance the optimization results. Finally, simulation studies are carried out on two time-delay systems and a nonlinear chemical process with time-varying time delay to validate the applicability and effectiveness of the proposed fuzzy controller. • A three-dimensional fuzzy controller with arbitrary triangular input fuzzy sets is designed. • We derive the analytical structure of fuzzy controller and analysis its properties. • A proximal policy optimization algorithm with a recall pool is proposed to optimize the parameters of fuzzy controller. • Simulations on time-delay models demonstrate the excellent performance of our proposed fuzzy controller. [ABSTRACT FROM AUTHOR]

The goethite process is a complicated process with multiple interactive chemical reactions in zinc hydrometallurgy. The use of a dynamic model plays an important role in predicting the key indicator on-line and in process control and optimization. However, because of the coupling influences among the chemical reactions, the conventional continuous stirred tank reactor (CCSTR) model is not adequate to describe this process. In this paper, we develop a weighted-coupling CSTR (WCCSTR) model for the goethite process by introducing weighted parameters. A parameter identification method is proposed to determine the unknown parameters. Then, a model predicted control (MPC) scheme is designed to achieve the process performance goals and minimize the process cost. To overcome the impact of frequent fluctuations in production conditions on the control performance, a novel parameter adaptive correction approach is proposed. The convergence of the adaptive correction approach is proved based on Lyapunov stability theory. Simulation results verify that the WCCSTR model has a higher prediction accuracy than the CCSTR model. The experimental results demonstrate that the MPC scheme performs better in controlling the process and reducing the process costs. [ABSTRACT FROM AUTHOR]

Generally, the iron removal process is modelled as a lumped parameter system that does not provide information about the distribution of reactants in the steady state. In this paper, we investigate the distributed parameter model and control for the iron removal process. By analyzing the process properties, we study the mass balance over a differential volume element, and the spatiotemporal distributions of the Fe 2+ , Fe 3+ and H + concentrations are derived by partial differential equations. An optimization problem is constructed to estimate the unknown parameters. Then, an optimal control problem for the oxidation rate of the ferrous ions in the steady state is proposed to achieve process requirements that have the lowest cost of oxygen and zinc oxide and obtain high goethite quality. To eliminate the impact from inevitable disturbances, an expert-based correction mechanism is constructed to compensate for the optimal control when the outlet ferrous ion concentrations are out of the desired range. Finally, the simulation results demonstrate the good performance of distributed parameter model. Industrial experiments demonstrate the satisfactory control performance of the optimal control strategy. Regarding manual operation and PI control, the control strategy increased the qualified ratio of the #4 reactor outlet Fe 2+ concentrations by 8.4% and 3.4%, respectively. Additionally, on average 17760 m 3 of oxygen and 109.68 t of zinc oxide per month were saved compared to manual operation. The mass percent of iron in the goethite increased from 34.31% (manual operation) and 35.12% (PI control) to 35.83%. [ABSTRACT FROM AUTHOR]

Iron precipitation by goethite plays an important role in zinc hydrometallurgy. The ferrous ion concentration, which is a key index for assessing the iron removal rate and process control results, cannot be measured on-line. In this study, an integrated predictive model of the ferrous ion concentration is established by integrating the mechanism model and error compensation model, which is based on data identification. The mechanism model is proposed based on an analysis of the process reaction and considering the reaction unit as a continuous stirred tank reactor model. For unknown parameters in the mechanism model, a double-particle swarm optimization algorithm based on information exchange and dynamic adjustment of the feasible region is developed for optimal selection. To improve the adaptive capability of the integrated model, we propose a model-updating strategy and parameter calibration method based on a sensitivity analysis to accomplish on-line adaptive updating of the predictive model. The simulation results demonstrate that the proposed model can effectively track the variation tendency of the ferrous ion concentration and successfully improve the adaptability of the integrated model. [ABSTRACT FROM AUTHOR]

Eastern Shandong is one of the important early Precambrian areas in the North China Craton, where extensive 2.5, 2.7 and 2.9 Ga magmatic activities have been identified, followed by very strong late Neoarchean and Paleoproterozoic tectono-thermal events. We carried out SHRIMP zircon dating, Hf-in-zircon isotope analysis and a whole-rock geochemical study on ca. 2.9 Ga Mesoarchean magmatic rocks. These include gneissic diorite, gneissic quartz diorite, gneissic tonalite and gneissic high-Si trondhjemite and were identified in five new areas. All these rocks contain ca. 2.5 Ga metamorphic zircons. The dioritic and tonalitic rocks are enriched in large ion lithosphile (LIL) elements (K, Rb, Ba) and depleted in Nb and P with moderate to highly fractionated REE patterns, similar in chemical compositions to Archean TTG rocks worldwide. The high-Si trondhjemites are characterized by very high SiO 2 and very low FeOt + MgO. The magmatic zircon grains from all these rocks are similar in their Hf isotopic compositions and have ɛ Hf ( t ) values ranging from + 1.3 to +9.9. Combined with previous work, our main conclusions are: (1) eastern Shandong underwent a major magmatic event at ca. 2.9 Ga; (2) diorites and tonalites formed by melting of thickened lower crust or the root of an oceanic plateau, whereas the high-Si trondhjemites were derived from melting of intermediate to felsic rocks; (3) the Mesoarchean (ca. 2.9 Ga) was a major period of juvenile crustal addition from the depleted mantle, earlier than the major crustal growth period at 2.7–2.8 Ga in the North China Craton; (4) the 2.7–2.9 Ga rocks underwent strong metamorphism at ca. 2.5 Ga, probably as a result of magmatic underplating. [ABSTRACT FROM AUTHOR]

Highlights: [•] ∼2.7 Ga rocks have been identified in eight areas of the North China Craton. [•] They are mainly tonalitic in composition and frequently underwent late alteration. [•] Their formation was a result of juvenile additions to the continental crust. [•] The North China Craton is similar in main period of crustal growth to other cratons. [ABSTRACT FROM AUTHOR]

Abstract: The Dabie–Sulu orogen in east-central China is the largest UHP belt in the world. Many studies have dealt with detrital minerals from sedimentary basins surrounding the Dabie belt in order to constrain the tectonic unroofing of this terrane. On the other hand, still few are the works focused on detritals from the basins associated with the Sulu belt. The Jiaolai basin, adjacent to the Sulu belt, is made of Mesozoic sedimentary rocks. Two sandstone samples collected from the Early Cretaceous Laiyang Group in the northern and southern margins of the Jiaolai basin were selected for zircon U–Pb dating and trace element analysis. The zircons show main U–Pb age clusters at ca. 2500–2400, 2000–1700, 850–700, and 330–130Ma, with a minor peak at ca. 1100Ma and a few Archean ages. Most zircons show texture features reflecting a magmatic origin, whereas several late Paleoproterozoic and Triassic zircons show homogeneous CL images and low Th/U ratios, indicating a metamorphic origin. The Neoproterozoic ages are consistent with the protolith ages of the metamorphic rocks in the Sulu terrane, implying that the Sulu tarrane may be a major source for this component. Whereas most Neoproterozoic zircons are euhedral to subhedral or angular in shape and are not surrounded by overgrowths, this implies that low-grade metamorphic Neoproterozoic metaigneous rocks ocurring along the northern margin of the Sulu terrane or metasediments overlying the HP–UHP rocks in the Sulu terrane might provide source materials to these detrital zircons. The late and early Paleoproterozoic age peaks are consistent with the thermal events occurred in the Jiaobei terrane, slightly younger than those in the Yangtze Block. These suggest that the Jiaobei terrane was a potential source for the Paleoproterozoic to Archean detrital zircon components. Only two early Paleozoic zircon grains were found in the studied samples, indicating the early Paleozoic arc did not extend into the Sulu terrane. According to the distribution of different kinds of rock adjacent to the Sulu terrane, the Early Cretaceous detrital zircons may be potentially derived from Cretaceous plutons from the Sulu belt. Eight detrital zircons including six metamorphic grians and two metamorphic overgrowth rims yield the Triassic ages, which might be derived from HP–UHP rocks from the Sulu terrane. A metamorphic overgrowth rim yields a metamorphic age of 246±3Ma, probably recording the timing of the prograde metamorphism of the Sulu terrane. One metamorphic grain yields an age of 212±2Ma, which is interpreted to record a retrograde metamorphic event. Based on the REE patterns, the remaining six Triassic analyses can be subdivided into two groups. Four of them record a weighted mean age of 230±6Ma and show nearly flat HREE patterns and slight negative or positive Eu anomalies. The last two grains are enriched HREE; considering their ages and the REE patterns, it is suggested that they may originate from other diverse UHP rocks. The Triassic metamorphic zircons were detected in the Laiyang Group, indicating that the Sulu UHP rocks were exposed to the surface before the Early Cretaceous. [Copyright &y& Elsevier]

Abstract: Late Paleozoic to Mesozoic strata, which were deposited in the Western Hills of Beijing, North China, recorded the contemporary tectonic evolution of the northern part of the North China Craton (NCC). Fine-grained sandstones and siltstones of these strata were analyzed for their major and trace element concentrations and Sr–Nd isotope compositions. Their La/Sc, Th/Sc, La/Co, Th/Co and Cr/Th ratios are similar to those of sediments derived from felsic source rocks, indicating that the original source materials were mostly intermediate to acidic rocks. Their εNd(0) values show dramatic shifts, implying changes in provenances from the Late Paleozoic to the Early Cretaceous. The εNd(0) values of the Late Paleozoic and the Late Jurassic to Early Cretaceous formations are very low. Whereas, the εNd(0) values of the Xingshikou and the Xiaoyaopo formations are much higher, indicating that a juvenile component has been added into their sources. Based on the Sr–Nd isotope compositions, the Late Paleozoic and the Late Jurassic to Early Cretaceous samples fall in the Paleozoic to Mesozoic magmatic rocks distributed in the northern part of the NCC. However, the Sr–Nd isotope compositions of the Xingshikou and the Xiayaopo formations vary between the Xing-Meng Orogenic Belt (XMOB) and the north part of the NCC components. These changes can be interpreted by the complex uplift and exhumation history of the northern NCC from the Late Paleozoic to the Early Cretaceous. During the Late Carboniferous, the uplift of the Inner Mongolia Paleo-uplift (IMPU), which probably commenced at the Late Carboniferous, might supply detrital materials to the Late Paleozoic strata. In the Late Triassic, the uplift of the XMOB and IMPU was responsible for the mixing source of the Xingshikou Formation. After that, the northern XMOB became the main source of the Xiayaopo Formation, resulting from the uplift of the XMOB due to the collision of Siberia and North China–Mongolia plates during the Middle to Late Jurassic. Finally, the uplift of the YFTB, which occurred from the Late Jurassic to Early Cretaceous, provided the source materials and blocked the input of the XMOB components. [Copyright &y& Elsevier]

• We propose an image enhancement method based on region decomposition and guided filtering. • In regions with insufficient illumination, we employ guided filtering to get information from brighter points in their neighborhood. • In regions with sufficient illumination, we regulate the magnitude of pixel variations to prevent overexposure. • A detail enhancement method is proposed based on a multi-scale Gaussian pyramid and texture fusion to improve clarity and naturalness. • The experiments show that the proposed method surpasses several state-of-the-art algorithms. Extraction of information from froth images is important for automatic control of froth flotation. However, images captured by cameras often suffer from severe uneven lighting, which significantly reduces the quality of froth images. Low-quality images hinder the accurate extraction of froth information, thereby affecting the control of the froth flotation system. Hence, we propose an image enhancement method based on region decomposition and guided filtering to improve the quality of images. Initially, we separate the image into regions with sufficient and insufficient illumination based on reflectance. In regions with insufficient illumination, the guided filter is applied to direct pixels to acquire information from brighter points in their neighborhood. Conversely, in other regions, we regulate the magnitude of pixel variations to prevent overexposure. Finally, a detail enhancement method is proposed based on a multi-scale Gaussian pyramid and texture fusion to improve clarity and naturalness. The experiments show that the method we proposed surpasses several state-of-the-art algorithms on public datasets. In the field of flotation, our method effectively enhances the image quality. Compared to other enhancement methods under the same segmentation strategy, our method significantly improves segmentation accuracy, demonstrating its strong practical value. In addition, our method also shows advantages in terms of computational speed. [ABSTRACT FROM AUTHOR]

Operational optimization of the Hall-Héroult cell is essential for achieving high efficiency and cost-effectiveness in the aluminum electrolysis process. Due to the complicated mechanism and variable working conditions, manual operational decision-making is extensively used in practice. They challenge the reliable and optimal operation of aluminum electrolysis process. In this paper, we develop a data-knowledge-driven decision-making support system (DMSS) to achieve operational optimization for the aluminum electrolysis process. DMSS consists of a prediction model, a multi-objective optimizer, and a knowledge-guided decision-making module. Specifically, we propose a working-conditions-based attention with the exogeneous inputs auto-regressive neural network (WCA-NARX) to construct a data-driven heat balance indicator (HBI) prediction model, where the working condition-related variables serve as covariates to enhance predictability. In addition, the designed structure of introducing working condition information through an attention mechanism can decouple covariates from operational variables and autoregressive variables, facilitating subsequent operational optimization. Then, a novel knowledge-assigned reference vector evolutionary algorithm (KRVEA) is designed to solve the multi-objective optimization problem of the aluminum electrolysis process, in which Pareto front solutions can be solved in the preferred region. Finally, we utilize the knowledge base that stores historical optimization cases to make decisions regarding the selection of a practical-requirement-based control scheme from the Pareto set. Real-world industrial experiments demonstrate that DMSS can effectively enhance control performance and achieve superior results compared to other competitive methods. The source code is available at https://github.com/wjiecsu/WCA-NARX. [ABSTRACT FROM AUTHOR]

In modern industrial processes, each subsystem interacts frequently and involves a large number of process variables with complex relations, which challenge process monitoring. In this paper, a distributed process monitoring method based on joint mutual information (JMI) and projective dictionary pair learning (DPL) is proposed for effective process monitoring in industrial systems with multimode, complex, and high-dimensional data. Firstly, considering the interactive information, redundancy and irrelevance among process variables, an automatic block division method based on JMI is proposed to divide process variables into several low dimensional blocks. Secondly, DPL-based monitoring model is established in each block of each mode. According to the multimode characteristic of industrial processes, a joint probability based on reconstruction error is proposed for mode recognition. Then, Bayesian inference method that fuses block statistics into global statistics is introduced for anomaly detection. The anomaly source is further determined by defining the block contribution coefficient and variable contribution coefficient. Finally, the effectiveness of the proposed method is demonstrated by a numerical simulation, Tennessee Eastman benchmark test, and experiments in an aluminum electrolysis industrial process. • A distributed process monitoring method via JMI-DPL is proposed. • An automatic block division method based on JMI is developed. • This method gives better performances in mode identification and anomaly detection. • An application in a real-world aluminum electrolysis process is provided. [ABSTRACT FROM AUTHOR]

Froth flotation is a complicated process which is difficult to establish its first-principle model. Due to the fluctuations in the grade of raw ore, adaptively adjusting the set-points is extremely important in the flotation process. The inappropriate set-points easily lead to the instability of the process. This paper presents a fuzzy association rule-based set-point adaptive optimization and control strategy for the antimony flotation process without knowing the system model. Firstly, a fuzzy neural network is constructed as a soft-sensor to estimate the feed grade online because of the lack of efficient measurement equipment. Then, fuzzy association rule is used to mine the hidden relationship between the feed grade with reagent dosages and the optimal set-points. Through data mining from the quantitative database, the fuzzy inference system generates the optimal set-points. To implement satisfactory tracking performance, predictive controller is used to compute the control inputs. Because the system dynamics is unknown, long short-term memory network model is established to predict the future behaviors of the process. Finally, simulations and experiments are carried out to demonstrate the effectiveness of the proposed strategy. Compared to the manual manipulation, which is widely used in flotation processes, our control strategy achieves a better control performance, and the concentrate grades are more in line with the process requirement. [ABSTRACT FROM AUTHOR]

The development of information and communication technology and its wide application in industrial control systems (ICSs) has brought a growing number of security risks to ICSs. Quantifying and dynamically assessing the security risks of ICSs is of great significance to protect ICSs from cyber attacks. Current risk assessment methods, however, do not take into account social engineering (SE) attacks and the potential cyber-to-physical risks associated with cyber attacks. To address these issues, we propose a novel method for the dynamic security risk assessment of ICSs, called SEAG. Specifically, the scheme first extends and modifies three metrics in the common vulnerability scoring system to four metrics for objectively calculating the exploit probability of SE. Then, we construct the attack graph by relying on the knowledge graph that integrates three kinds of knowledge including SE knowledge, common vulnerability knowledge, and control system knowledge. In addition, we combine real time attack data that causes system performance loss with the industrial protocol function code attack detected by the intrusion detection system to accurately quantify the potential cyber-to-physical risks associated with cyber attacks. This method allows us to dynamically assess the security risks of ICSs in real time. Finally, the method is verified by one simulation testbed, which shows the effectiveness and accuracy of the proposed method for dynamic quantitative evaluating security risks of ICSs. • Propose a novel method for the dynamic security risk assessment of ICSs, called SEAG. • Extend the CVSS metrics for calculating the exploit probability of social engineering. • Relying on the knowledge graph that integrates multi-knowledge, construct attack graph. • Combine attack data to quantify the cyber-to-physical risks. [ABSTRACT FROM AUTHOR]

Outlet ferrous ion concentration is an essential indicator to manipulate the goethite process in the zinc hydrometallurgy plant. However, it cannot be measured on-line, which leads to the delay of this feedback information. In this study, a self-adjusting structure radial basis function neural network (SAS-RBFNN) is developed to predict the outlet ferrous ion concentration on-line. First, a supervised cluster algorithm is proposed to initialize the RBFNN. Then, the network structure is adjusted by the developed self-adjusting structure mechanism. This mechanism can merge or divide the hidden neurons according to the distance of the clusters to achieve the adaptability of the RBFNN. Finally, the connection weights are determined by the gradient-based algorithm. The convergence of the SAS-RBFNN is analyzed by the Lyapunov criterion. A simulation for a benchmark problem shows the effectiveness of the proposed network. The SAS-RBFNN is then applied to predict the outlet ferrous ion concentration in the goethite process. The results demonstrate that this network can provide a more accurate prediction than the mathematical model, even under the fluctuating production condition. • A self-adjusting structure RBF neural network (SAS-RBFNN) is developed. • The network is initialized by the proposed supervised cluster algorithm. • The network structure is adjusted by the proposed self-adjusting structure mechanism. • The convergence of the SAS-RBFNN is analyzed by Lyapunov criterion. [ABSTRACT FROM AUTHOR]

Glacial diamictite may provide important information on paleoenvironment and average composition of the upper continental crust (UCC). In this study, we report sedimentary facies, petrological and geochemical characteristics of Neoproterozoic diamictite from a profile of the Luoquan Formation on the southern margin of the North China Block (NCB). Upwards the sampling profile, lithostratigraphic strata vary from massive diamictite with poorly sorted carbonate gravels to laminated diamictite with small gravels of terrestrial detrital materials. Along the profile, CaO-MgO-LOI-Sr values decrease with the increase of SiO2-Al2O3-K2O contents. All these petrological and geochemical variations indicate a change from lodgement till deposition in the proximal of ice sheet to ice-rafting deposition in glacial-marine environment with less dolomite to supply their source. Together with previous studies on diamictite from other outcrops on the NCB, the deposition of Luoquan diamictite reflects that the glaciation on the NCB vanished and the ice-rafting effect weakened with glacial transgression process. In addition, significant co-variations of various elements with La and Al2O3 confirm the significant conservation of most analyzed elements during the sedimentary processes to produce diamictite. [ABSTRACT FROM AUTHOR]

Orbital data indicate that the youngest volcanic units on the Moon are basalt lavas in Oceanus Procellarum, a region with high levels of the heat-producing elements potassium, thorium, and uranium. The ChangÕe-5 mission collected samples of these young lunar basalts and returned them to Earth for laboratory analysis. We measure an age of 1963 ± 57 million years for these lavas and determine their chemical and mineralogical compositions. This age constrains the lunar impact chronology of the inner Solar System and the thermal evolution of the Moon. There is no evidence for high concentrations of heat-producing elements in the deep mantle of the Moon that generated these lavas, so alternate explanations are required for the longevity of lunar magmatism. [ABSTRACT FROM AUTHOR]

The Jinghong mafic–ultramafic complex, exposed in the eastern margin of the Lancangjiang tectonic belt, is related to the subduction of the Paleo‐Tethys Ocean. Its petrogenesis plays a key role in constraining the tectonic evolution of the eastern Paleo‐Tethys Ocean in southwestern China. In this study, we present petrological, geochemical and geochronological results of the Jinghong complex rocks, in order to decipher their origin and tectonic significance. The Jinghong mafic–ultramafic complex was composed of peridotite, gabbro, basalt and minor plagiogranite. Whole‐rock geochemical data of the mafic rocks indicate that they have both MORB and IAB affinities and plot in the back‐arc basin basalt (BABB) field in the FeO∗/MgO vs. TiO2 diagram. Combined with their trace element characteristics, it can be concluded that the Jinghong mafic–ultramafic complex represents an ophiolite suite that was formed in a back‐arc ocean basin. Precise LA‐ICP‐MS zircon U‐Pb dating yielded weighted mean 206Pb/238U ages of 298.4 ± 1.7 Ma, 294.3 ± 1.6 Ma, and 292.8 ± 2.0 Ma for gabbroic rocks from this complex, which indicates that the Jinghong ophiolites were formed during the early Permian (298–293 Ma). We propose that during subduction of the main Paleo‐Tethys Ocean, a back‐arc ocean basin was formed at the east of the Lancangjiang tectonic belt. [ABSTRACT FROM AUTHOR]

The Neoarchean basement rocks of the Qixingtai region in the northwest of western Shandong, eastern North China Craton are divided into western and eastern domains, separated by a ductile shear zone. The western domain is mainly composed of early Neoarchean tonalitic and supracrustal rocks, and the eastern domain is composed of late Neoarchean crustally‐derived granite with diverse early Neoarchean enclaves up to several kilometres long of supracrustal and gneissic TTG‐diorite rocks. This study reports an integrated field, whole‐rock geochemistry and zircon U–Pb‐Hf study on the granites and their enclaves in the eastern domain. The supracrustal enclaves are mainly composed of meta‐basaltic and meta‐ultramafic rocks and are the same in lithological association and formation time as the 2,750–2,700 Ma Liuhang "Formation" in the western area. The TTG‐diorite enclaves can be divided into early and late groups. Magmatic zircons from early TTG‐diorite samples have U–Pb ages of 2,731 ± 17 to 2,748 ± 13 Ma and εHf(t) values of +2.7 to +9.5, whereas trondhjemite samples of the late group have U–Pb zircon ages of 2,588 ± 18 to 2,606 ± 12 Ma and εHf(t) values of +0.6 to +6.5. The Hf isotopic signatures on magmatic zircon from the >2,700 Ma diorite‐tonalites indicate that they are predominantly juvenile crustal additions, probably with minor involvement of older crust in their genesis, as given by tDM (Hf) ages ranging back to 2.92 Ga. The eastern granites range from monzogranite to syenogranite in composition and commonly have negative Eu anomalies, indicating residual plagioclase in the source region. Magmatic zircons from two granite samples have U–Pb ages of 2,516 ± 24 and 2,527 ± 18 Ma and εHf(t) values of +1.0 to +7.0. A fine‐grained syenogranite dyke contains inherited early Neoarchean zircons with εHf(t) values of +1.6 to +7.4. The isotopic signatures of the late Neoarchean granites that dominate the eastern domain show that they were derived from partial melting recycling of older continental crust recognized in the region – early Neoarchean rocks formed as a result of juvenile crustal additions. This is a common signature for late Archean crustal evolution throughout much of the North China Craton, and is the hallmark of some other Archean terranes, such as the Dharwar Craton of south India. The geodynamic explanations for the formation globally of vast amounts of crustally‐derived late Neoarchean granite are discussed. [ABSTRACT FROM AUTHOR]

Distributed anode current (DAC) is a high-dimensional spatial-distributed signal that can be measured online in the industrial aluminum electrolysis process. The difference of physicochemical properties in different spatial regions in an aluminum electrolysis cell can be obtained by spatial clustering analysis of DAC data. In this study, a dynamic spatial distributed information clustering method (DSDIC) for aluminum electrolysis cell is proposed. This method can effectively capture the complex dynamic spatio-temporal correlations in DAC. Firstly, the dynamic graph is identified to capture the complex dynamicity of the DAC. Then, the anode-spatial structure information (ASSI) extends the one-dimensional current signal generated by each carbon anode into a feature matrix to achieve the fusion of data and spatial structure knowledge. Finally, the adjacency matrix of dynamic graph performs low-pass filtering on the feature matrix to obtain low-frequency information that is beneficial to downstream learning tasks. Meanwhile, a fixed graph structure based on process mechanism knowledge is designed to capture the spatial correlation caused by external periodic operations in industrial process. The experimental results on the actual industrial aluminum electrolysis datasets show that our method improves the clustering accuracy by 3.96% compared with existing clustering methods. • A dynamic spatial distributed information clustering method is proposed. • A novel fixed graph structure based on process mechanism knowledge is proposed. • A method using adaptive dynamic graph to capture the dynamic spatial correlation is proposed. • A learning mode combining dynamic graph and static graph is proposed. [ABSTRACT FROM AUTHOR]

Antimony flotation is a complicated industrial process with an unknown system structure. Manual manipulation is still widely used by observing the froth appearance, which relies on operators' experience. Therefore, this paper proposes a reagent predictive control strategy for the antimony flotation process based on machine vision, which is an optional replacement of manual control. Froth image is a good indicator to reflect the working conditions of the process. A shape-weighted bubble size distribution (SWBSD) is developed to characterize the froth image feature. The SWBSD combines the bubble size and bubble shape, which differs from the separate use of froth features. Since lots of the froth images can be obtained, a random selection of an image from a froth video as the indicator of the working conditions is not advisable. A typical froth image selection method is proposed to choose the froth image which can best characterize the current working conditions. Due to the unknown system model, multi-output least square support vector regressor (LS-SVR) is used to predict the future image feature according to the current image feature and reagent dosages. Based on the above methods, predictive control technique is employed to calculate the optimal control inputs of the reagents. Simulations using the real-world production data verify the effectiveness of the proposed control strategy. In further, industrial experiments in the antimony flotation plant of China demonstrate that our control strategy improved the tracking performance and decreased the tailing grade, compared with the manual manipulation. [ABSTRACT FROM AUTHOR]

Mesoarchean and older potassic granites are important indicators of recycling of ancient continental crust early in Earth's history. This study of integrated whole rock and zircon geochemistry and geochronology reports the age and identification of the source materials of the > 200 km 2 Mesoarchean Tiejiashan-Gongchangling granite in the Anshan-Benxi area, North China Craton, the largest pre-Neoarchean granite domain in the craton. SHRIMP U-Pb zircon dating on 15 samples indicates the magmatic crystallization of the granites between 2.95 and 3.0 Ga and reveals a superimposed tectonothermal event at ~ 2.91 Ga. The granites are characterized by high SiO 2 and K 2 O, low CaO, FeOt, MgO and TiO 2 with peraluminuous features. They show large variations in (La/Yb) n and strong negative Eu and Ba anomalies and Nb, P and Ti depletions. Whole rock Nd and magmatic zircon Hf isotopic compositions show large variations, but with most having ε Nd (t) and ε Hf (t) values < 0, with t DM (Nd) and t DM (Hf) values varying from 3.3 to 3.9 Ga and 3.3 to 4.0 Ga, respectively. Magmatic zircons without very strong lead loss (discordance ≤ 20%) have δ 18 O values of + 3.14 to + 8.39. 3.3–3.7 Ga xenocrystic zircons occur in some samples. The granite formed as a result of recycling of Paleo- to Eoarchean continental material in an intracontinental environment, with little if any contribution from Mesoarchean mantle sources. The sources could be predominantly unaltered ancient gneisses, together with yet to be identified Paleo- to Eoarchean materials affected by early low temperature alteration (weathered rocks or clastic sediment). [ABSTRACT FROM AUTHOR]

There are different viewpoints on metamorphic and anatectic zircons recording ages of 2.45–2.48 Ga or even younger in some areas of the North China Craton where both late Neoarchean and late Paleoproterozoic tectono-thermal events are well developed. These are: 1) partial resetting of the U-Pb isotopic system in the late Neoarchean zircons, 2) metamorphism lasting from the late Neoarchean to the earliest Paleoproterozoic, and 3) earliest Paleoproterozoic metamorphism as separate different event. Western Shandong Province is an area where the late Neoarchean tectono-thermal event is widely developed but the late Paleoproterozoic event has not been identified. This provides an opportunity to understand the geological processes around the Archean-Proterozoic boundary. Based on a field study, we carried out SHRIMP U-Pb zircon dating on seventeen samples of ∼2.5 Ga old metamorphic and anatectic rocks, including tonalite, trondhjemite, granodiorite, gabbro, quartz diorite, granite and paragneiss with primary emplacement or depositional ages of 2.52–2.68 Ga. Anatectic zircons show some textural and compositional features: a) Homogenous or blurred oscillatory zoning, b) high U contents and low in Th/U ratios (commonly <0.3), c) rare idiomorphic morphologies, and d) commonly containing inherited (xenocrystic) cores. We conclude that the strong late Neoarchean event is widespread in western Shandong and is limited between ∼2.50 and 2.54 Ga. In contrast, apparent 2.45–2.48 Ga metamorphic zircon ages in some other areas of the North China Craton may be the result of overprinting and partial recrystallization of Neoarchean metamorphic zircons during the late Paleoproterozoic event. The Archaean rocks of western Shandong can be divided into three belts, namely Belts A, B and C from the northeast to the southwest. The difference between Belts A and B in ∼2.5 Ga metamorphic and anatectic intensity may indicate that the former was elevated to a higher crustal level compared with the latter at the end of the Neoarchean. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new complex, named as the Hujiamiao Complex, was discovered in the Anshan area, NCC. • Trondhjemitic rocks of different ages from 3.79 to 3.11 Ga have been identified. • It is the first time in Anshan to identify trondhjemitic rocks with relatively high (La/Yb) n ratios. • Magmatic zircons have ε Hf (t) of −12.3 to 1.6, t DM (Hf) and t CC (Hf) ages of 4.1 to 3.6 Ga and 4.3 to 3.7 Ga. • All the Anshan 3.8–3.3 Ga complexes are the relics of the same larger complex in the area. Anshan is located in the northeastern North China Craton and has a long-term geological history back to 3.8 Ga. Four complexes with ages of 3.8–3.1 Ga have been identified previously, namely the Baijiafen, Dongshan, Shengousi and Guodishan complexes. Being similar to the neighbouring Beijiafen Complex, the newly-discovered Hujiamiao Complex extends in a northwest-southeast direction and shows tectonic contacts on one side with the Chengtaigou granite and on the other with the Chengtaigou supracrustal rocks. In the Hujiamiao Complex, trondhjemitic rocks of 3789 Ma, 3786 Ma, 3698 Ma, 3617 Ma, 3566 Ma, 3504 Ma and 3106 Ma have been identified. More work is required to establish if a gabbro also has a formation age of 3.8 Ga. The trondhjemitic rocks show similar compositional features in being high in SiO 2 (72.37–76.71 %) and Na 2 O (5.00–6.47 %) and low in K 2 O (0.60–1.95 %), ∑REE contents (32.83–91.83 ppm) and (La/Yb) n ratios (11.09–48.64). They have whole-rock ε Nd (t) values of 0.35–4.43, t DM (Nd) of 3.74–3.46 Ga and t CC (Nd) ages of 3.74–3.43 Ga, and in situ magmatic zircon ε Hf (t) values of −12.3 to 1.56, t DM (Hf) ages of 4.2 to 3.5 Ga and t CC (Hf) ages of 4.6 to 3.7 Ga. Combined with previous work, it is concluded that all the Anshan area 3.8–3.3 Ga complexes are the relics of a larger complex which was once more widely distributed in the Anshan area. The trondhjemitic rather than tonalitic character of the Anshan Eoarchean rocks shows diversity in the formation and evolution of the earliest continental crust with a range of T/P for crustal anatexis. [ABSTRACT FROM AUTHOR]

Voluminous Neoarchean plutonic and supracrustal rocks are well developed in the Western Shandong Province of the North China Craton, which has been divided into a late Neoarchean crustally-derived granite belt, a middle to early Neoarchean ancient rock belt and a late Neoarchean juvenile rock belt. Earlier studies provided reconnaissance evidence for ∼2.60 Ga metamorphism in some areas. This study presents SHRIMP zircon U–Pb dating and O isotope analysis on nine metamorphosed igneous rock samples (gneissic tonalite, gneissic trondhjemite, gneissic quartz diorite and meta-gabbro) from the ancient rock belt. Magmatic zircons vary in age from 2.74 Ga to 2.60 Ga, whereas metamorphic and anatectic zircons vary in age from 2.63 Ga to 2.59 Ga, with an age peak of 2.61 Ga. In this study, we identified 2.69–2.67 Ga metamorphic zircons for the first time. Most of zircons, whether magmatic or metamorphic, have δ 18 O values of +4.5‰ to +6.5‰ (V-SMOW). However, the oldest tonalite sample with a protolith age of 2735 Ma has zircons showing low δ 18 O (V-SMOW) values, particularly in recrystallized domains and overgrowths. This suggests at least in local crustal extension and influx of meteoric water during the evolution of the rocks. Combined with data from earlier studies, we draw the conclusion that the Western Shandong Province experienced a regional tectono-thermal event at ∼2.60 Ga, as a result of high heat flow and crustal extension, perhaps caused by a mantle plume or mantle overturn activity. Therefore we conclude that 2.60 Ga can be regarded the break between early and late Neoarchean crustal accretion. The O isotope study indicates that in some cases, trondhjemitic leucosome was not derived from nearby gneissic tonalite, although they show a close relationship in outcrop. [ABSTRACT FROM AUTHOR]

Western Shandong Province is a typical area of the North China Craton (NCC) where Neoarchean plutonic and supracrustal rocks are widely distributed. Early studies documented that ∼2.7 Ga and ∼2.5 Ga magmato-tectono-thermal events are well developed in the area. Here we report SHRIMP U–Pb ages and Hf-in-zircon isotopic data from ten samples of different magmatic rock types including hornblendite, gneissic tonalite, gneissic trondhjemite and gneissic granite. Magmatic zircon grains have 207 Pb/ 206 Pb ages ranging from 2667 to 2598 Ma. Some rocks contain ∼2.5 Ga metamorphic rims and ∼2.7 Ga zircon cores. The magmatic zircon grains have ɛ Hf ( t ) values and Hf crustal model ages of −1.1 to +11.3 and 3.02–2.4 Ga, respectively. Combined with an earlier study, our main conclusions are that the middle Neoarchean rocks mainly occur together with early Neoarchean rocks in the northeastern portion of the central belt. Juvenile additions to continental crust and crustal recycling played important roles in the middle Neoarchean of western Shandong Province, and the entire Neoarchean tectonic evolution can be divided into middle to early Neoarchean (2.75–2.6 Ga) and late Neoarchean (2.6–2.5 Ga) events. [ABSTRACT FROM AUTHOR]