Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

Residual alkali-evoked cross-linked polymer layer for anti-air-sensitivity LiNi_(0.89)Co_(0.06)Mn_(0.05)O_(2)cathode

High-energy density lithium-ion batteries(LIBs)with layered high-nickel oxide cathodes(LiNi_(x)Co_(y)Mn_(1-x-y)O_(2),x≥0.8)show great promise in consumer electronics and vehicular applications.However,LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)faces challenges related to capacity decay caused by residual alkalis owing to high sensitivity to air.To address this issue,we propose a hazardous substances upcycling method that fundamentally mitigates alkali content and concurrently induces the emergence of an anti-air-sensitive layer on the cathode surface.Through the neutralization of polyacrylic acid(PAA)with residual alkalis and then coupling it with 3-aminopropyl triethoxysilane(KH550),a stable and ion-conductive cross-linked polymer layer is in situ integrated into the LiNi_(0.89)Co_(0.06)Mn_(0.05)O_(2)(NCM)cathode.Our characterization and measurements demonstrate its effectiveness.The NCM material exhibits impressive cycling performance,retaining 88.4%of its capacity after 200 cycles at 5 C and achieving an extraordinary specific capacity of 170.0 mA h g^(-1) at 10 C.Importantly,this layer on the NCM efficiently suppresses unfavorable phase transitions,severe electrolyte degradation,and CO_(2)gas evolution,while maintaining commendable resistance to air exposure.This surface modification strategy shows widespread potential for creating air-stable LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)cathodes,thereby advancing high-performance LIBs.

Residual stress modeling of mitigated fused silica damage sites with CO_(2)laser annealing

A numerical model based on measured fictive temperature distributions is explored to evaluate the residual stress fields of CO_(2)laser-annealed mitigated fused silica damage sites.The proposed model extracts the residual strain from the differences in thermoelastic contraction of fused silica with different fictive temperatures from the initial frozen-in temperatures to ambient temperature.The residual stress fields of mitigated damage sites for the CO_(2)laser-annealed case are obtained by a finite element analysis of equilibrium equations and constitutive equations.The simulated results indicate that the proposed model can accurately evaluate the residual stress fields of laser-annealed mitigated damage sites with a complex thermal history.The calculated maximum hoop stress is in good agreement with the reported experimental result.The estimated optical retardance profiles from the calculated radial and hoop stress fields are consistent with the photoelastic measurements.These results provide sufficient evidence to demonstrate the suitability of the proposed model for describing the residual stresses of mitigated fused silica damage sites after CO_(2)laser annealing.

A method for establishing a bearing residual life prediction model for process enhancement equipment based on rotor imbalance response analysis

A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.

Antagonism effect of residual S triggers the dual-path mechanism for water oxidation

Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of the residual chalcogen in the reconstructed layer is lacking in detail,and the corresponding catalytic mechanism remains controversial.Here,taking Cu_(1-x)Co_(x)S as a platform,we explore the regulating effect and existence form of the residual S doped into the reconstructive layer for oxygen evolution reaction(OER),where a dual-path OER mechanism is proposed.First-principles calculations and operando~(18)O isotopic labeling experiments jointly reveal that the residual S in the reconstructive layer of Cu_(1-x)Co_(x)S can wisely balance the adsorbate evolution mechanism(AEM)and lattice oxygen oxidation mechanism(LOM)by activating lattice oxygen and optimizing the adsorption/desorption behaviors at metal active sites,rather than change the reaction mechanism from AEM to LOM.Following such a dual-path OER mechanism,Cu_(0.4)Co_(0.6)S-derived Cu_(0.4)Co_(0.6)OSH not only overcomes the restriction of linear scaling relationship in AEM,but also avoids the structural collapse caused by lattice oxygen migration in LOM,so as to greatly reduce the OER potential and improved stability.

Attention-Based Residual Dense Shrinkage Network for ECG Denoising

Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac diagnosis.However,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affectsthe subsequent pathological analysis.Therefore,the effective removal of the noise from ECG signals has becomea top priority in cardiac diagnostic research.Aiming at the problem of incomplete signal shape retention andlow signal-to-noise ratio(SNR)after denoising,a novel ECG denoising network,named attention-based residualdense shrinkage network(ARDSN),is proposed in this paper.Firstly,the shallow ECG characteristics are extractedby a shallow feature extraction network(SFEN).Then,the residual dense shrinkage attention block(RDSAB)isused for adaptive noise suppression.Finally,feature fusion representation(FFR)is performed on the hierarchicalfeatures extracted by a series of RDSABs to reconstruct the de-noised ECG signal.Experiments on the MIT-BIHarrhythmia database and MIT-BIH noise stress test database indicate that the proposed scheme can effectively resistthe interference of different sources of noise on the ECG signal.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

Quality assessment of the Topo-Iberia CGPS stations and data quality's effects on postfit ionosphere-free phase residuals

This paper analyzed GPS data from the Topo-Iberia network spanning almost 12 years(2008-2020).The data quality information for all 26 Topo-Iberia stations is provided for the first time,complementing the Spanish Geological Survey’s storage work.Data analyses based on quality indicators obtained using TEQC have been carried out.The guidelines and data quality information from the IGS stations have been considered as the quality references,with the stations ALJI,EPCU,and TIOU standing out as the worst stations,while on the contrary,FUEN,PALM,PILA,and TRIA meet the quality requirements to become an IGS station.The relationship between the GPS data quality and their GAMIT-and Gipsy X-derived postfit ionosphere-free phase residuals has also been investigated,and the results reveal an inversely proportional relationship.It has been found that the stations showing an increase in elevation of the horizon line,also show an increase in cycle slips and multipath,are among the poorest quality stations,and among those with the highest postfit RMS of phase residuals.Moreover,the evolution of the vegetation around the antenna should be considered as it could cause a progressive loss of quality,which is not complying with the IGS standards.The quality assessment shows that the Topo-Iberia stations are appropriate for geodetic purposes,but permanent monitoring would be necessary to avoid the least possible loss of data and quality.In addition,a method to characterize the GNSS data quality is proposed.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

A Normalizing Flow-Based Bidirectional Mapping Residual Network for Unsupervised Defect Detection

Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.

Radar Signal Intra-Pulse Modulation Recognition Based on Deep Residual Network

In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB).

A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

Range estimation of few-shot underwater sound source in shallow water based on transfer learning and residual CNN

Taking the real part and the imaginary part of complex sound pressure of the sound field as features,a transfer learning model is constructed.Based on the pre-training of a large amount of underwater acoustic data in the preselected sea area using the convolutional neural network(CNN),the few-shot underwater acoustic data in the test sea area are retrained to study the underwater sound source ranging problem.The S5 voyage data of SWellEX-96 experiment is used to verify the proposed method,realize the range estimation for the shallow source in the experiment,and compare the range estimation performance of the underwater target sound source of four methods:matched field processing(MFP),generalized regression neural network(GRNN),traditional CNN,and transfer learning.Experimental data processing results show that the transfer learning model based on residual CNN can effectively realize range estimation in few-shot scenes,and the estimation performance is remarkably better than that of other methods.

Effect of petroleum chemical fraction and residual oil content in saline lacustrine organic-rich shale: A case study from the Paleogene Dongpu Depression of North China

Halite and gypsum minerals in saline shale make the retention mechanism and chemical fractionation of residual oil unique. The Dongpu Depression in North China is a typically saline lacustrine basin with developing halite and gypsum. The effect of gypsum minerals on residual oil content and chemical fractionation remains unclear. In this study, shale samples with different gypsum contents were used in organic geochemical experiments, showing that the high total organic matter (TOC) content and type II kerogen leads to a high residual oil content, as shown by high values of volatile hydrocarbon (S1) and extractable organic matter (EOM). XRD and FE-SEM result indicate that the existence of gypsum in saline shale contributes to an enhanced pore space and a higher residual oil content in comparison to non-gypsum shale. Additionally, the increase in the gypsum mineral content leads to an increase in the saturated hydrocarbon percentage and a decrease in polar components percentage (resins and asphaltene). Furthermore, thermal simulation experiments on low-mature saline shale show that the percentage of saturated hydrocarbons in the residual oil is high and remains stable and that the storage space is mainly mesoporous (> 20 nm) in the oil expulsion stage. However, the saturated hydrocarbons percentage decreases rapidly, and oil exists in mesopores (> 20 nm and < 5 nm) in the gas expulsion stage. In general, gypsum is conducive to the development of pore space, the adsorption of hydrocarbons and the occurrence of saturated hydrocarbon, leading to large quantities of residual oil. The data in this paper should prove to be reliable for shale oil exploration in saline lacustrine basins.

Additive manufacturing of Ni-based superalloys: Residual stress, mechanisms of crack formation and strategies for crack inhibition

The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in high-end industrial systems.However,the intense temperature gradient induced by the rapid heating and cooling processes of AM can generate high levels of residual stress and metastable chemical and structural states,inevitably leading to severe metallurgical defects in Ni-based superalloys.Cracks are the greatest threat to these materials’integrity as they can rapidly propagate and thereby cause sudden and non-predictable failure.Consequently,there is a need for a deeper understanding of residual stress and cracking mechanisms in additively manufactured Ni-based superalloys and ways to potentially prevent cracking,as this knowledge will enable the wider application of these unique materials.To this end,this paper comprehensively reviews the residual stress and the various mechanisms of crack formation in Ni-based superalloys during AM.In addition,several common methods for inhibiting crack formation are presented to assist the research community to develop methods for the fabrication of crack-free additively manufactured components.

Application of Nonlinear Lamb Wave Mixing Method for Residual Stress Measurement in Metal Plate

Harmonic nonlinear ultrasound can offer high sensitivity for residual stress measurements;however,it cannot be used for local stress measurements at a point in space and exhibits nonlinear distortions in the experimental system.This paper presents a feasibility study on the measurement of residual stress in a metal plate using a nonlinear Lamb wave-mixing technique.The resonant conditions for two Lamb waves to generate a mixing frequency wave are obtained via theoretical analysis.Finite element simulations are performed to investigate the nonlinear interactions between the two Lamb waves.Results show that two incident A0 waves interact in regions of material nonlinearity and generate a rightward S0 wave at the sum frequency.Residual stress measurement experiments are conducted on steel plate specimens using the collinear Lamb wave-mixing technique.By setting different delays for two transmitters,the generated sum-frequency component at different spatial locations is measured.Experimental results show that the spatial distribution of the amplitude of the sum-frequency component agrees well with the spatial distribution of the residual stress measured using X-rays.The proposed collinear Lamb wave-mixing method is effective for measuring the distribution of residual stress in metal plates.

Reservoir heterogeneity controls of CO_(2)-EOR and storage potentials in residual oil zones:Insights from numerical simulations

Residual oil zones(ROZs)have large potential for CO_(2)enhanced oil recovery(EOR)and geologic storage.During CO_(2)injection,the migration of CO_(2)in ROZs controls the performance of both EOR and storage.However,it has not been clearly visualized and understood that how geological heterogeneity factors control the transport of CO_(2)in ROZs.In this study,the oil recovery performance and geologic storage potential during continuous CO_(2)injection in a representative ROZ are studied based on geostatistical modelling and high-fidelity three-phase flow simulation.We examined the influence of autocorrelation length of permeability,global heterogeneity(DykstraeParsons coefficient),and permeability anisotropy on cumulative oil recovery and CO_(2)retention fraction.Simulation results indicate that,as the permeability autocorrelation length increases,the cumulative oil recovery and CO_(2)storage efficiency decrease.This results from the accelerated migration of CO_(2)along high permeability zones(i.e.,gas channeling).The increase in global heterogeneity and permeability anisotropies can lead to low oil recovery and poor CO_(2)sequestration performance,depending on the degree of CO_(2)channeling.The net utilization ratio of CO_(2)(CO_(2)retained/oil produced)unfavorably increases with both autocorrelation length and Dykstra eParsons coefficient,but decreases with the increase in kv/kh.Such a decrease is attributed to enlarged swept volume induced by gravity override.The study provides important implications for fieldscale CO_(2)EOR and storage applications in ROZs.

Mesoscopic measurement of damage and shear bands of granite residual soil using Micro-CT and digital volume correlation

The mesomechanics of geotechnical materials are closely related to the macromechanical properties,especially the mesoscale evolution of shear bands,which is helpful for understanding the failure mechanism of geotechnical materials.However,there is lack of effective quantitative analysis method for the complex evolution mechanism of threedimensional shear bands.In this work,we used X-ray computed tomography(CT)to reconstruct volume images and used the digital volume correlation(DVC)method to calculate the three-dimensional strain fields of granite residual soil samples at different loading stages.The trend of the failure surface of the shear bands was obtained by the planar fitting method,and the connectivity index was constructed according to the projection characteristics of the shear bands on the failure trend surface.The results support the following findings:the connectivity index of the shear band increases rapidly and then slowly with increasing axial strain,which is characterized by a near'S'curve.As the stress reaches the peak value,the connectivity index of the shear bands almost exceeds 0.7.The contribution of the new shear band volume to the connectivity of the shear bands becomes increasingly small with increasing axial loading.Affected by quartz grains and stress at the initial stage,the dip angle gradually and finally approaches the included angle of the maximum shear stress from the discrete state with increasing axial loading.The tendency and dip angle of the resulting shear bands are dynamic,and the tendency slightly deflects with increasing loading.

Numerical analysis of water-alternating-CO_(2) flooding for CO_(2)-EOR and storage projects in residual oil zones

Residual oil zones(ROZs)have high residual oil saturation,which can be produced using CO_(2) miscible flooding.At the same time,these zones are good candidates for CO_(2) sequestration.To evaluate the coupled CO_(2)-EOR and storage perfor-mance in ROZs for Water-Alternating-CO_(2)(WAG)flooding,a multi-compositional CO_(2) miscible model with molecular diffusion was developed.The effects of formation parameters(porosity,permeability,temperature),operation parameters(bottom hole pressure,WAG ratio,pore volume of injected water),and diffusion coeffcient on the coupled CO_(2)-EOR and storage were investigated.Five points from the CO_(2) sequestration curve and the oil recovery factor curve were selected to help better analyze coupled CO_(2)-EOR and storage.The results demonstrate that enhanced performance is observed when formation permeability is higher and a larger volume of water is injected.On the other hand,the performance diminishes with increasing porosity,molecular diffusion of gas,and the WAG ratio.When the temperature is around 100℃,coupled CO_(2)-EOR and storage performance is the worst.To achieve optimal miscible flooding,it is recommended to maintain the bottom hole pressure(BHP)of the injection well above 1.2 minimum miscibility pressure(MMP),while ensuring that the BHP of the production well remains sufficiently high.Furthermore,the tapered WAG flooding strategy proves to be profitable for enhanced oil recovery,as compared to a WAG ratio of 0.5:1,although it may not be as effective for CO_(2) sequestration.