Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl m...Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175℃ to 250℃.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.展开更多
The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 M...The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.展开更多
Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the origin...Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.展开更多
The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.展开更多
In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to ...In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to evaluate the effectiveness of exteriorwall coat-ings with ozone decomposition catalysts for ozone removal in practical applications.ANSYS 2020R1 software was first used for simulation and analysis of ozone concentration and flow fields to investigate the decomposition boundary of these wall coatings.The results show that the exterior wall coatings with manganese-based catalysts can effectively reduce the ozone concentration near the wall coating.The ozone decomposition efficiency is nega-tively correlated with the distance fromthe coating and the decomposition boundary range is around 18 m.The decomposition boundary will increase with the increase of tempera-ture,and decrease with the increase of the wind speed and the relative humidity.These results underscore the viability of using exterior wall coatings with catalysts for controlling ozone pollution in atmospheric environments.This approach presents a promising avenue for addressing ozone pollution through self-purifying materials on building external wall.展开更多
In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrabilit...In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.展开更多
Cover cropping is a diversifying agricultural practice that can improve soil structure and function by altering the underground litter diversity and soil microbial communities.Here,we tested how a wheat cover crop alt...Cover cropping is a diversifying agricultural practice that can improve soil structure and function by altering the underground litter diversity and soil microbial communities.Here,we tested how a wheat cover crop alters the decomposition of cucumber root litter.A three-year greenhouse litterbag decomposition experiment showed that a wheat cover crop accelerates the decomposition of cucumber root litter.A microcosm litterbag experiment further showed that wheat litter and the soil microbial community could improve cucumber root litter decomposition.Moreover,the wheat cover crop altered the abundances and diversities of soil bacterial and fungal communities,and enriched several putative keystone operational taxonomic units(OTUs),such as Bacillus sp.OTU1837 and Mortierella sp.OTU1236,that were positively related to the mass loss of cucumber root litter.The representative bacterial and fungal strains B186 and M3 were isolated and cultured.In vitro decomposition tests demonstrated that both B186 and M3 had cucumber root litter decomposition activity and a stronger effect was found when they were co-incubated.Overall,a wheat cover crop accelerated cucumber root litter decomposition by altering the soil microbial communities,particularly by stimulating certain putative keystone taxa,which provides a theoretical basis for using cover crops to promote sustainable agricultural development.展开更多
In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based bou...In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based boundary intersection(PBI)are distributed parallelly while those based on the normal boundary intersection(NBI)are distributed radially in a conical shape in the objective space.To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications,this paper addresses the improvement of the Collaborative Decomposition(CoD)method,a multi-objective decomposition technique that integrates PBI and NBI,and combines it with the Elephant Clan Optimization Algorithm,introducing the Collaborative Decomposition Multi-objective Improved Elephant Clan Optimization Algorithm(CoDMOIECO).Specifically,a novel subpopulation construction method with adaptive changes following the number of iterations and a novel individual merit ranking based onNBI and angle are proposed.,enabling the creation of subpopulations closely linked to weight vectors and the identification of diverse individuals within them.Additionally,new update strategies for the clan leader,male elephants,and juvenile elephants are introduced to boost individual exploitation capabilities and further enhance the algorithm’s convergence.Finally,a new CoD-based environmental selection method is proposed,introducing adaptive dynamically adjusted angle coefficients and individual angles on corresponding weight vectors,significantly improving both the convergence and distribution of the algorithm.Experimental comparisons on the ZDT,DTLZ,and WFG function sets with four benchmark multi-objective algorithms—MOEA/D,CAMOEA,VaEA,and MOEA/D-UR—demonstrate that CoDMOIECO achieves superior performance in both convergence and distribution.展开更多
A novel gappy technology, gappy autoencoder with proper orthogonal decomposition(Gappy POD-AE), is proposed for reconstructing physical fields from sparse data. High-dimensional data are reduced via proper orthogonal ...A novel gappy technology, gappy autoencoder with proper orthogonal decomposition(Gappy POD-AE), is proposed for reconstructing physical fields from sparse data. High-dimensional data are reduced via proper orthogonal decomposition(POD),and low-dimensional data are used to train an autoencoder(AE). By integrating the POD operator with the decoder, a nonlinear solution form is established and incorporated into a new maximum-a-posteriori(MAP)-based objective for online reconstruction.The numerical results on the two-dimensional(2D) Bhatnagar-Gross-Krook-Boltzmann(BGK-Boltzmann) equation, wave equation, shallow-water equation, and satellite data show that Gappy POD-AE achieves higher accuracy than gappy proper orthogonal decomposition(Gappy POD), especially for the data with slowly decaying singular values,and is more efficient in training than gappy autoencoder(Gappy AE). The MAP-based formulation and new gappy procedure further enhance the reconstruction accuracy.展开更多
The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high...The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits ...Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits in the future.However,designing catalysts that simultaneously exhibit high activity and long-term stability remains a significant challenge.Tuning the catalyst’s structure and electronic properties is an effective strategy for enhancing the reaction performance.In this work,a series of NixZr/ZSM-5 catalysts were prepared using the incipient wetness impregnation method,and the effect of Zr loadings on catalyst properties and performance was systematically investigated.The calcined and reduced catalysts were characterized by low-temperature N_(2)adsorption-desorption,XRD,SEM,H_(2)-TPR and XPS.The results showed that the addition of Zr significantly increased the specific surface area of the catalyst and reduced the metal particle size.Smaller NiO particles were found to enter the pores of the HZSM-5 support,and electronic interactions between NiO and ZrO_(2)markedly enhanced the metal-support interaction.The catalyst exhibited optimal catalytic performance at a Zr loading of 5%,achieving a maximum methane conversion of 68%at 625℃,maintaining activity for 900 min,and delivering a carbon yield of 1927%.Further increasing the Zr loading yielded only limited improvements in catalytic performance.Characterization of the spent catalysts and carbon products via TEM,Raman spectroscopy,and TGA revealed that the introduction of ZrO_(2)reduced metal sintering and promoted a shift in carbon nanofibers growth mode from tip-growth to base-growth.The mechanism of base-growth enabled the catalyst to maintain reaction activity for an extended period.展开更多
Digital twin is considered the key technique for real-time monitoring and life-cycle management of electric equipment.To construct the digital twin model of electric equipment,a multi-parameter electromagnetic analysi...Digital twin is considered the key technique for real-time monitoring and life-cycle management of electric equipment.To construct the digital twin model of electric equipment,a multi-parameter electromagnetic analysis is needed to generate a large amount of high fidelity data under various working condition.However,repeated solving such multi-parameter electromagnetic problems based on full order finite element method may lead to extreme scale calculations.To address this issue,a hybrid approach that combines tensor decomposition and proper orthogonal decomposition(POD)is introduced,which can effectively establish a reduced order model for multi-parameter electromagnetic field problems.The performance of the proposed approach is illustrated through three numerical examples,namely an electrical motor,a transformer and a voice coil actuator including parameter variations of operating conditions,geometric parameters,and material parameters.The numerical results show that the proposed hybrid approach has significant advantage compared to conventional reduced order model in situation where the solution changes dramatically within the parameter variation range and even more apparent when the parameter dimension is high.展开更多
The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.A...The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.展开更多
In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,eff...In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).展开更多
Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics i...Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics in this region remains unexplored at finer scales.This study investigates how micro site conditions influence litter decomposition of 15 upper Andean species over time.A reciprocal translocation field experiment was conducted over 18 months in 14 permanent plots within four sites in Colombian Andean mountain forests.Each plot contained three litterbeds(microsites),each with the 15 species,harvested at 3,6,12 and 18 months,totaling 2520 litterbags.Different forest variables,including canopy openness,leaf area index,slope and depth of litter,were measured in each litterbed.ANOVAs and linear mixed models were used to assess variation between sites and plots respectively,while multiple linear regression analyses evaluated the effects of forest variables on decay rates over time at the micro site scale.Results showed differences in absolute decay rates between sites but consistent relative decay rates,indicating varying magnitudes of decomposition,yet maintaining the same order based on their litter quality.Decay rates varied between species,with more variation in labile species compared to recalcitrant ones.Despite substantial variation in forest characteristics within sites,their influence on litter decomposition was minimal and declined over time.This suggests that,at finer spatial scales,the forest microenvironment plays a lesser role in litter decomposition,with litter quality emerging as the primary driver.This study is a step towards understanding the fine-scale dynamics of litter decomposition in upper Andean tropical forests,highlighting the intricate interplay between microenvironmental factors and decomposition processes.展开更多
Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativ...Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.展开更多
Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ...Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.展开更多
Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have un...Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have unique chemical and physical properties that allow np-Fe^(0) to form at a lower initial reaction temperature.Through the insitu heating experiment of ilmenite in the Chang'e-5 sample,it was found that ilmenite can form np-Fe^(0) at 400℃under high vacuum(10-6 Pa).This fills in the missing information on the lowest measured temperature at which ilmenite forms np-Fe^(0).At 400-800℃,only np-Fe^(0) and vesicles were formed without new Ti-rich minerals.At the same time,thermodynamic calculations showed that decomposition of ilmenite occurs in two stages.The experiments correspond to the initial stage of ilmenite thermal decomposition under high vacuum.The study explains the thermal decomposition reaction of ilmenite in a vacuum environment,provides a reference for the minimum measured temperature required for the formation of np-Fe^(0),and further improves the formation mechanism of np-Fe^(0).展开更多
In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-pin...In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.展开更多
基金sponsored by the Department of Defense,Defense Threat Reduction Agency under the Materials Science in Extreme Environments University Research Alliance,HDTRA1-20-2-0001。
文摘Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175℃ to 250℃.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.
基金supported by the National Key R&D Program of China (No. 2021YFB3700700)the Henan Province Top Talent Training Program Project, China (No. 244500510020)the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences, China (No. 242017001)。
文摘The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.
基金supported in part by the Interdisciplinary Project of Dalian University(DLUXK-2023-ZD-001).
文摘Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
基金supported by the National Natural Science Foundation of China(Nos.52470114 and 52022104)the National Key R&D Program of China(No.2022YFC3702802)the Youth Innovation Promotion Association,CAS(No.Y2021020).
文摘In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to evaluate the effectiveness of exteriorwall coat-ings with ozone decomposition catalysts for ozone removal in practical applications.ANSYS 2020R1 software was first used for simulation and analysis of ozone concentration and flow fields to investigate the decomposition boundary of these wall coatings.The results show that the exterior wall coatings with manganese-based catalysts can effectively reduce the ozone concentration near the wall coating.The ozone decomposition efficiency is nega-tively correlated with the distance fromthe coating and the decomposition boundary range is around 18 m.The decomposition boundary will increase with the increase of tempera-ture,and decrease with the increase of the wind speed and the relative humidity.These results underscore the viability of using exterior wall coatings with catalysts for controlling ozone pollution in atmospheric environments.This approach presents a promising avenue for addressing ozone pollution through self-purifying materials on building external wall.
基金sponsored by the National Natural Science Foundations of China under Grant Nos.12301315,12235007,11975131the Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ20A010009。
文摘In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.
基金supported by the National Natural Science Foundation of China(32072655 and 32272792)。
文摘Cover cropping is a diversifying agricultural practice that can improve soil structure and function by altering the underground litter diversity and soil microbial communities.Here,we tested how a wheat cover crop alters the decomposition of cucumber root litter.A three-year greenhouse litterbag decomposition experiment showed that a wheat cover crop accelerates the decomposition of cucumber root litter.A microcosm litterbag experiment further showed that wheat litter and the soil microbial community could improve cucumber root litter decomposition.Moreover,the wheat cover crop altered the abundances and diversities of soil bacterial and fungal communities,and enriched several putative keystone operational taxonomic units(OTUs),such as Bacillus sp.OTU1837 and Mortierella sp.OTU1236,that were positively related to the mass loss of cucumber root litter.The representative bacterial and fungal strains B186 and M3 were isolated and cultured.In vitro decomposition tests demonstrated that both B186 and M3 had cucumber root litter decomposition activity and a stronger effect was found when they were co-incubated.Overall,a wheat cover crop accelerated cucumber root litter decomposition by altering the soil microbial communities,particularly by stimulating certain putative keystone taxa,which provides a theoretical basis for using cover crops to promote sustainable agricultural development.
文摘In recent years,decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios.In these algorithms,the reference vectors of the Penalty-Based boundary intersection(PBI)are distributed parallelly while those based on the normal boundary intersection(NBI)are distributed radially in a conical shape in the objective space.To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications,this paper addresses the improvement of the Collaborative Decomposition(CoD)method,a multi-objective decomposition technique that integrates PBI and NBI,and combines it with the Elephant Clan Optimization Algorithm,introducing the Collaborative Decomposition Multi-objective Improved Elephant Clan Optimization Algorithm(CoDMOIECO).Specifically,a novel subpopulation construction method with adaptive changes following the number of iterations and a novel individual merit ranking based onNBI and angle are proposed.,enabling the creation of subpopulations closely linked to weight vectors and the identification of diverse individuals within them.Additionally,new update strategies for the clan leader,male elephants,and juvenile elephants are introduced to boost individual exploitation capabilities and further enhance the algorithm’s convergence.Finally,a new CoD-based environmental selection method is proposed,introducing adaptive dynamically adjusted angle coefficients and individual angles on corresponding weight vectors,significantly improving both the convergence and distribution of the algorithm.Experimental comparisons on the ZDT,DTLZ,and WFG function sets with four benchmark multi-objective algorithms—MOEA/D,CAMOEA,VaEA,and MOEA/D-UR—demonstrate that CoDMOIECO achieves superior performance in both convergence and distribution.
基金supported by the National Natural Science Foundation of China(No.12472197)。
文摘A novel gappy technology, gappy autoencoder with proper orthogonal decomposition(Gappy POD-AE), is proposed for reconstructing physical fields from sparse data. High-dimensional data are reduced via proper orthogonal decomposition(POD),and low-dimensional data are used to train an autoencoder(AE). By integrating the POD operator with the decoder, a nonlinear solution form is established and incorporated into a new maximum-a-posteriori(MAP)-based objective for online reconstruction.The numerical results on the two-dimensional(2D) Bhatnagar-Gross-Krook-Boltzmann(BGK-Boltzmann) equation, wave equation, shallow-water equation, and satellite data show that Gappy POD-AE achieves higher accuracy than gappy proper orthogonal decomposition(Gappy POD), especially for the data with slowly decaying singular values,and is more efficient in training than gappy autoencoder(Gappy AE). The MAP-based formulation and new gappy procedure further enhance the reconstruction accuracy.
基金supported by the National Natural Science Foundation of China (Grant No. 12302056)the Postdoctoral Fellowship Program of CPSF:GZC20233445。
文摘The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
基金Supported by Innovative Research Groups of the National Natural Science Foundation of China(22021004)。
文摘Catalytic decomposition of methane,which produces high-purity hydrogen and high-value-added carbon nanomaterials,has shown considerable potential for development and is expected to yield significant economic benefits in the future.However,designing catalysts that simultaneously exhibit high activity and long-term stability remains a significant challenge.Tuning the catalyst’s structure and electronic properties is an effective strategy for enhancing the reaction performance.In this work,a series of NixZr/ZSM-5 catalysts were prepared using the incipient wetness impregnation method,and the effect of Zr loadings on catalyst properties and performance was systematically investigated.The calcined and reduced catalysts were characterized by low-temperature N_(2)adsorption-desorption,XRD,SEM,H_(2)-TPR and XPS.The results showed that the addition of Zr significantly increased the specific surface area of the catalyst and reduced the metal particle size.Smaller NiO particles were found to enter the pores of the HZSM-5 support,and electronic interactions between NiO and ZrO_(2)markedly enhanced the metal-support interaction.The catalyst exhibited optimal catalytic performance at a Zr loading of 5%,achieving a maximum methane conversion of 68%at 625℃,maintaining activity for 900 min,and delivering a carbon yield of 1927%.Further increasing the Zr loading yielded only limited improvements in catalytic performance.Characterization of the spent catalysts and carbon products via TEM,Raman spectroscopy,and TGA revealed that the introduction of ZrO_(2)reduced metal sintering and promoted a shift in carbon nanofibers growth mode from tip-growth to base-growth.The mechanism of base-growth enabled the catalyst to maintain reaction activity for an extended period.
基金supported by the UCAS-ULille joint PhD training program and also partially supported within the frame of the EE4.0(Electrical Energy 4.0)project,which is co-financed by the European Union,with the financial support of the European Regional Development Fund(ERDF),the French state,and the French Region of Hautsde-France.
文摘Digital twin is considered the key technique for real-time monitoring and life-cycle management of electric equipment.To construct the digital twin model of electric equipment,a multi-parameter electromagnetic analysis is needed to generate a large amount of high fidelity data under various working condition.However,repeated solving such multi-parameter electromagnetic problems based on full order finite element method may lead to extreme scale calculations.To address this issue,a hybrid approach that combines tensor decomposition and proper orthogonal decomposition(POD)is introduced,which can effectively establish a reduced order model for multi-parameter electromagnetic field problems.The performance of the proposed approach is illustrated through three numerical examples,namely an electrical motor,a transformer and a voice coil actuator including parameter variations of operating conditions,geometric parameters,and material parameters.The numerical results show that the proposed hybrid approach has significant advantage compared to conventional reduced order model in situation where the solution changes dramatically within the parameter variation range and even more apparent when the parameter dimension is high.
基金financially supported by the National Natural Science Foundation of China(Nos.52034002 and U2202254)the Fundamental Research Funds for the Central Universities,China(No.FRF-TT-19-001)。
文摘The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.
基金funded by Anhui Province University Key Science and Technology Project(2024AH053415)Anhui Province University Major Science and Technology Project(2024AH040229)+3 种基金Talent Research Initiation Fund Project of Tongling University(2024tlxyrc019)Tongling University School-Level Scientific Research Project(2024tlxyptZD07)TheUniversity Synergy Innovation Programof Anhui Province(GXXT-2023-050)Tongling City Science and Technology Major Special Project(Unveiling and Commanding Model)(200401JB004).
文摘In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).
基金supported by the Universidad del Rosario(Small grant ID:IV-FPD003)。
文摘Upper Andean tropical forests are renowned for their extraordinary biodiversity and heterogeneous environmental conditions.Despite the critical role of litter decomposition in carbon and nutrient cycles,its dynamics in this region remains unexplored at finer scales.This study investigates how micro site conditions influence litter decomposition of 15 upper Andean species over time.A reciprocal translocation field experiment was conducted over 18 months in 14 permanent plots within four sites in Colombian Andean mountain forests.Each plot contained three litterbeds(microsites),each with the 15 species,harvested at 3,6,12 and 18 months,totaling 2520 litterbags.Different forest variables,including canopy openness,leaf area index,slope and depth of litter,were measured in each litterbed.ANOVAs and linear mixed models were used to assess variation between sites and plots respectively,while multiple linear regression analyses evaluated the effects of forest variables on decay rates over time at the micro site scale.Results showed differences in absolute decay rates between sites but consistent relative decay rates,indicating varying magnitudes of decomposition,yet maintaining the same order based on their litter quality.Decay rates varied between species,with more variation in labile species compared to recalcitrant ones.Despite substantial variation in forest characteristics within sites,their influence on litter decomposition was minimal and declined over time.This suggests that,at finer spatial scales,the forest microenvironment plays a lesser role in litter decomposition,with litter quality emerging as the primary driver.This study is a step towards understanding the fine-scale dynamics of litter decomposition in upper Andean tropical forests,highlighting the intricate interplay between microenvironmental factors and decomposition processes.
基金financial y supported by the National Key Research and Development Program of China (2023YFD1900902)the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (LLSSZ24C030001)+1 种基金the Earmarked Fund for China Agriculture Research System (CARS-08-G-09)sponsored by the K.C.Wong Magna Fund of Ningbo University,China。
文摘Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.
文摘Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.
基金funding support from the National Natural Science Foundation of China(Grant Nos.42441804,42403043,42273042,42303041,and U24A2008)Youth Innovation Promotion Association CAS awards+5 种基金"From 0 to 1"Original Exploration Cultivation Project,Institute of Geochemistry,Chinese Academy of Sciences(Grant No.DHSZZ2023.3)Bureau of Frontier Sciences and Basic Research,CAS,(Grant No.QYJ-2025-0103)Guizhou Provincial Foundation for Excellent Scholars Program(Grant No.GCC[2023]088)Provincial Key Research and Development(R&D)Plan Projects of Heilongjiang(Grant No.2024ZXDXB52)The Innovation and Development Fund of Science and Technology of Institute of Geochemistry,Chinese Academy of SciencesGuizhou Province Basic Research Program Project(QKHJC-ZK[2023]-General 473)。
文摘Nanophase iron particles(np-Fe^(0))have multiple formation mechanisms in lunar soil,which are mostly related to meteorite and micro meteorite impacts.Thermal modification of the impact is critical.Metal oxides have unique chemical and physical properties that allow np-Fe^(0) to form at a lower initial reaction temperature.Through the insitu heating experiment of ilmenite in the Chang'e-5 sample,it was found that ilmenite can form np-Fe^(0) at 400℃under high vacuum(10-6 Pa).This fills in the missing information on the lowest measured temperature at which ilmenite forms np-Fe^(0).At 400-800℃,only np-Fe^(0) and vesicles were formed without new Ti-rich minerals.At the same time,thermodynamic calculations showed that decomposition of ilmenite occurs in two stages.The experiments correspond to the initial stage of ilmenite thermal decomposition under high vacuum.The study explains the thermal decomposition reaction of ilmenite in a vacuum environment,provides a reference for the minimum measured temperature required for the formation of np-Fe^(0),and further improves the formation mechanism of np-Fe^(0).
基金funded by the National Natural Science Foundation of China,grant number U24A20135Inner Mongolia Natural Science Foundation major project,grant number 2023ZD12+7 种基金Inner Mongolia Autonomous Region key research and development and achievement transformation plan project,grant number 2023YFHH0090Natural Science Foundation of Inner Mongolia,grant number 2022MS05006Inner Mongolia Autonomous Region Talent Development FundUniversity basic research business expenses,grant number 2023RCTD012University basic research business expenses,grant number 2023QNJS075Postgraduate Research Innovation Program and of Inner Mongolia Autonomous Region,grant number KC2024053BUniversity basic research business expenses,grant number 2024YXXS012National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology,grant number GZ2023KF012.
文摘In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.
