A machine learning-based APP may quickly and non-destructively evaluate the quality of parameters,such as hardness and anthocyanin content in blue honeysuckle berries(Lonicera caerulea L.,BHB),based on changes in peri...A machine learning-based APP may quickly and non-destructively evaluate the quality of parameters,such as hardness and anthocyanin content in blue honeysuckle berries(Lonicera caerulea L.,BHB),based on changes in pericarp color characteristics.The color feature information of the BHB pericarp was extracted,and the corresponding hardness and anthocyanin content were determined at various growing stages.Correlation analysis of BHB quality indexes was conducted by single and combined components of BHB epidermal color features.The results showed that fruit hardness had a significantly negative correlation with color feature parameter R-G,and its anthocyanin content had a significantly positive correlation with color feature parameter R.Comparing the eight models,random forest(RF)was established to evaluate the hardness and anthocyanin content of BHB according to the correlation between pericarp color features and hardness and anthocyanin content on BHB quality evaluation APP on the WeChat platform.The credibility of APP embedding RF model for evaluating hardness and anthocyanin content in BHB was validated with the determination coefficient of 0.89 and 0.93 in practice.This approach could efficiently and conveniently evaluate the quality indexes of BHB in real time and serve as a technical reference for the detection of quality indicators of other berries using smartphones.展开更多
Owing to overcoming the characteristics that there are many economic and technical indexes which are fuzzy and incompatibility to each other in evaluating investment project,a new method is proposed.The method is base...Owing to overcoming the characteristics that there are many economic and technical indexes which are fuzzy and incompatibility to each other in evaluating investment project,a new method is proposed.The method is based on the matter-element analysis and combined with the concepts of fuzzy mathematics,which is called the method of fuzzy matter-element analysis.It constructs the compound fuzzy matter element with the investment projects,evaluation factors and their fuzzy value.Through establishing the best subjection degree (fuzzy value),complex fuzzy matter element of relational coefficient and weight aggregation of fuzzy matter-element model,the writer achieves on optimum order of the investment projects according to the calculated relational degree and finds the best project.In this paper,the calculation of weight adopts the analytical hierarchy process method(AHP).Through the actual example,it shows that the model is simple and its calculation is reliable.It is very significant for the engineering evaluated bid and investment decision.展开更多
To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit t...To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit to circuit. In this paper, the genetic algorithms are used to construct the models of existing test generation algorithms in making such choice more easily. Therefore, we may forecast the testability parameters of a circuit before using the real test generation algorithm. The results also can be used to evaluate the efficiency of the existing test generation algorithms. Experimental results are given to convince the readers of the truth and the usefulness of this approach.展开更多
Vendors’Evaluating and Selecting is one study focu s in SCM and VMO. It is one of the very important operations management and can ad vance to implement the strategic aims. With the increase in use of total quality m...Vendors’Evaluating and Selecting is one study focu s in SCM and VMO. It is one of the very important operations management and can ad vance to implement the strategic aims. With the increase in use of total quality management and just-in-time concepts by a wide range of firms, the vendor sel ection question has become extremely important. It is necessary for firms to tak e part in the global competition and global manufacture. There are some decision -making techniques which can be used for evaluating and selecting vendors, such as weighting point methods, utility theary, multi-objective programming, analy tic hierarchy process, vendor profile analysis, and so on. Analytic Hierarchy Pr ocess(AHP) is a technique in common use for quantifying the problem. Since AHP i s put forward in 1973 by Satty, it has been accepted. However, this technique ha s its shortcomings, and one of them is that distributing weights is subjective. In recent years,some scholars prove that it is defferent from factual doing usin g subjective ways for vendors’ evaluating and selecting. In fact, the methods f or vendors’evaluating and selecting should be given by practical circs. Today, there’s somebody who has brought forward that it is studied by deviding four ty pes of relationships in view of two major factors: the reference time horizon of the relationship; and the content of the relationship in terms of the nature of the interation between supplier and customer. In the paper, we only consider th e scenario of short-term and logistic intergration brought forward by Cristina and Andrea. In the scenario, we only consider current manufacturing performance. In fact, the scenario is often seen in these developing countries.We bring up a model for grey system analysis on vendors’evaluating and selecting to attempt to expore this problem. The model integrates AHP and the grey system theory and attempt to eliminate the subjective factors in AHP using objective datum. Moreov er, it is based on the feature of data insufficiency and uncertainty and sample information of abnormality in system data.So,it overcomes the issues of deficien t information and absent data(it is often seen in management).展开更多
Through applying PPE model based on RAGA to evaluate the benefit of rice water saving,the author turns multi-dimension data into low dimension space.So the optimum projection direction can stand for the best influence...Through applying PPE model based on RAGA to evaluate the benefit of rice water saving,the author turns multi-dimension data into low dimension space.So the optimum projection direction can stand for the best influence on the collectivity.Thus,the value of projection function can evaluate each item good or not.The PPE model can avoid jamming of weight matrix in the method of fuzzy synthesize judgement,and obtain better result.The author wants to provide a new method and thought for readers who are engaged in investment decision-making of water saving irrigation and other relative study.展开更多
The evaluation method and its accuracy for evaluating complex systems are considered. In order to evaluate accurately complex systems, the existed evaluating methods are simply analyzed, and a new comprehensive evalua...The evaluation method and its accuracy for evaluating complex systems are considered. In order to evaluate accurately complex systems, the existed evaluating methods are simply analyzed, and a new comprehensive evaluating method is developed. The new method is integration of Delphi approach, analytic hierarchy process, gray interconnect degree and fuzzy evaluation (DHGF). Its theory foundation is the meta-synthesis methodology from qualitative analysis to quantitative analysis. According to fuzzy set approach, using the methods of concordance of evaluation, redundant verify, double models redundant, and limitations of the method etc, the accuracy of evaluating method of DHGF is estimated, and a practical example is given. The result shows that using the method to evaluate complex system projects is feasible and credible.展开更多
According to the method of water balance,the parameters of groundwater resouce of Jian San Jiang area have been calculated in the paper.At the same time,the quality of water supplying and water mining can be calculate...According to the method of water balance,the parameters of groundwater resouce of Jian San Jiang area have been calculated in the paper.At the same time,the quality of water supplying and water mining can be calculated.Furthermore,the groundwater resource have been evaluated.Thus,the paper provides the important references for managers to using groundwater reasonable.展开更多
Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple l...Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple label matching.However,previous studies have largely modeled this task as syndrome pattern classification within a fixed label space,which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning,and is also insufficient to capture the openness,semantic variability,and cross-disease reusability of syndrome manifestation expression.This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought(PR-CoT)supervision into large language models(LLMs)could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer.Methods Syndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information(X)→pathogenesis structure(Z)→syndrome pattern output(Y),where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment.Within this framework,a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders.After preprocessing,information extraction,manual proofreading,and data cleaning,the dataset comprised 4800 training cases,400 development cases,and 400 test cases.Each sample was annotated with a structured PR-CoT consisting of three progressive levels:clinical information summarization,comprehensive pathogenesis analysis,and syndrome pattern output.Supervised fine-tuning was conducted on open-source LLMs,with an end-to-end model serving as the baseline.Qwen3-32B was used as the primary experimental model,and Qwen3-14B as the scale comparison model.A progressive multidimensional evaluation framework was further established,comprising a structural parsing level,a semantic similarity level,and an expert blind review level.At the structural parsing level,syndrome pattern expressions were decomposed into structural elements and evaluated using Precision,Recall,F1 score,and Jaccard similarity.At the semantic similarity level,independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns.At the expert blind review level,three TCM experts independently evaluated model outputs on two dimensions:syndrome differentiation consistency and terminology standardization of syndrome patterns.In addition,zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets.Results At the structural parsing level,PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components.Compared with the corresponding baselines,neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision.In contrast,at the semantic similarity level,PR-CoT supervision produced stable positive gains across different model scales and evaluation systems.The average semantic score of Qwen3-32B increased from 6.4258 in the baseline model to 6.5850 after PR-CoT supervision,and that of Qwen3-14B increased from 5.8700 to 5.9642.At the expert blind review level,the overall score of Qwen3-32B(PR-CoT)was 7.0260±0.1077,higher than 6.4163±0.2889 for its baseline.In zero-shot cross-disease testing,the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets,indicating a certain degree of transferability.Conclusion The benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility,rather than in improved hard matching of structural elements.These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures,rather than as a classification task within a traditional fixed label space.By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework,this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment,interpretability,and multi-level evaluation.展开更多
Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces ...Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.展开更多
Gravity-caisson wharves have been widely constructed in coastal and island regions, which are threaten by potential underwater explosions. This work aims to study the dynamic behaviors and propose a damage evaluation ...Gravity-caisson wharves have been widely constructed in coastal and island regions, which are threaten by potential underwater explosions. This work aims to study the dynamic behaviors and propose a damage evaluation approach of caisson wharf against underwater explosion. Firstly, based on both the underwater explosion loading test and underwater explosion test on the reduced-scale caisson specimen, a high-fidelity finite element analysis approach for numerically reproduce the dynamic behaviors of prototype caisson wharves against underwater explosions was proposed and verified. Secondly, the underwater explosion loadings and dynamic behaviors of prototype caisson wharf (14.9 m×8.1 m×10.95 m) against sequential blast wave and bubble pulsation of typical torpedo with a charge weight of 200 kg were studied. The influences of the seabed and cabin infill materials, as well as the explosion standoff distances of 3.4–10.2 m and depths of burst between 1/4 and 3/4 of water depth, on the blast resistance of caisson wharf were further examined through deflection distributions of exterior wall, damage evolution, and overall displacement of caisson wharf. Finally, a performance evaluation approach for prototype caisson wharves against underwater explosions was proposed by comprehensively considering the bearing, storage, and berthing capabilities. The corresponding protective measures and design recommendations were further provided. It indicates that: (i) under the explosion of a typical torpedo, the damage modes of prototype caisson wharf mainly involve the overall vibration, spalling and cracking of the exterior wall, collapse of the upper operating platform and cracking of the top plate;(ii) the blast wave and cavitation zone generated between the bubble and the exterior wall are the two primary causes of damage to caisson wharf;(iii) compared to the saturated calcareous sand seabed, the assumption of rigid seabed underestimates the spalling on the exterior wall, which is not recommended for scenarios where cavitation zones may generate;(iv) rock rubble is the most effective infill material in improving the blast resistance of caisson wharf among four types of infill configurations, i.e., fully filled and half-filled saturated calcareous sand, rock rubble and pure water;(v) the standoff distance of 10.2 m is regarded as a secure protective range in the scenarios discussed currently. As the standoff distance decreases and the depth of burst increases, the spalling of the exterior wall induced by the cavitation intensifies, posing a great threat to the functionality of caisson wharf.展开更多
The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on sta...The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on static evaluation methods.Therefore,this paper proposes a dynamic multi-round decision evaluation method based on the characteristics of multi-round unmanned aerial vehicle air combat under opponent’s optimal strategy.In order to determine objective weights,an improved multi-attribute decision making method is proposed,which incorporates the proximity as a correction coefficient for evaluation indicators,utilizing the cosine similarity instead of Euclidean distance,and incorporating both actual and theoretical objective weights to prevent data mutations.Subsequently,the game theory is employed to reasonably adjust subjective and objective weights to obtain comprehensive weights.To address the issues related to the ambiguity and randomness during the evaluation process,a reverse cloud generator is utilized to determine the center of gravity of the cloud model using comprehensive weights while employing the weighted deviation degree for evaluating air combat decision-making effectiveness.By activating the cloud generator through the cloud model,the optimal strategies for each round of air combat are determined,thereby completing the dynamic evaluations for multi-round sequential decision-making processes.Finally,the feasibility and effectiveness of the proposed method are verified through simulations.展开更多
The comprehensive evaluation of six properties for equipment product is an important basis for their quality control,and their correlative relationship among six properties will affect their quality level.To understan...The comprehensive evaluation of six properties for equipment product is an important basis for their quality control,and their correlative relationship among six properties will affect their quality level.To understand their correlative relationship among six properties,this paper firstly combines group evaluation with decision-making trial and evaluation laboratory(DEMATEL)model,and develops the optimization model based on group consensus to form six influent relationship matrices.Secondly,group consensus matrix is used to design super network hierarchy matrix,and the weights of six properties with relevant environment is also proposed.Thirdly,the elimination and choice translating reality(ELECTRE)model is used to make comprehensive evaluation,and an example is used to compare the results under two kinds of conditions,and illustrate the effect of the weights of six properties on the priority of equipment products.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Objective To explore the therapeutic effect of LuoFuShan Rheumatism Plaster(LFS)on neuropathic pain(NP)and its molecular mechanism.Methods Mouse models of sciatic nerve chronic constriction injury(CCI)were treated wit...Objective To explore the therapeutic effect of LuoFuShan Rheumatism Plaster(LFS)on neuropathic pain(NP)and its molecular mechanism.Methods Mouse models of sciatic nerve chronic constriction injury(CCI)were treated with low,medium,and high doses(2.2,4.4,and 8.8 cm2,respectively)of LFS by topical application for 14 consecutive days.The therapeutic effects were assessed by evaluating the mechanical withdrawal threshold(MWT),paw withdrawal latency(PWL),plasma IL-6 and TNF-αlevels,and histopathology of the sciatic nerve.Network pharmacology and molecular docking were used to identify the key targets and signaling pathways.The key targets were verified by RT-qPCR and immunohistochemistry.The biosafety of LFS was evaluated by measuring the organ indices and damage indicators of the heart,liver,and kidneys.Results Compared with the CCI group,LFS dose-dependently increased MWT and PWL,reduced plasma IL-6 and TNF-αlevels,and alleviated sciatic nerve inflammation in the mouse models.Network pharmacology identified 378 bioactive compounds targeting 279 NPassociated genes enriched in TLR and TNF signaling.Molecular docking showed that quercetin and ursolic acid in LFS could stably bind to TLR4 and TNF-α.In the mouse models of sciatic nerve CCI,LFS significantly downregulated the mRNA expression levels of Tlr4 and Tnf-αin the spinal cord in a dose-dependent manner and lowered the protein expressions of TLR4 and TNF-αin the sciatic nerve.LFS treatment did not cause significant changes in the organ indices or damage indicators of the heart,liver and kidneys as compared with those in the CCI model group and sham-operated group.Conclusion LFS alleviates NP in mice by suppression of TLR4/TNF-α-mediated neuroinflammation with a good safety profile.展开更多
Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a ...Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.展开更多
A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV s...A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.展开更多
To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a b...To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty)...To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty).Three representative sections were examined:adobe brick masonry repaired(Area 1),well-preserved original(Area 2),and layer-by-layer ramming repaired(Area 3).THz spectral data revealed significant differences between Area 1(time delay:3.72 ps;refractive index:2.224)and Area 2(time delay:3.02 ps;refractive index:2.107),while Area 3(time delay:3.12 ps;refractive index:2.098)demonstrated nearly identical THz spectral data to Area 2.Infrared thermal imaging also showed that the Area 3 restored by layer-by-layer ramming exhibited greater uniformity with fewer instances of cracks,capillary phenomena,or biological diseases.The proposed point-surface integrated evaluation methodology synergistically combines infrared thermography mapping of heritage surfaces with THz spectral datasets acquired through in-situ micro-sampling,enabling quantitative restoration assessment and providing a novel approach for scientifically validating traditional conservation techniques.展开更多
Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic re...Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic resin and n-octanol were used to synthesize the main agent SCA-2.Hexamethylenetetramine and vinyl carbonate were selected to prepare the curing agent YGA-1,which was then compounded with SCA-2 to develop a sand fixation and water plugging system.Firstly,single-factor experiments were conducted to determine the optimal concentrations of SCA-2 and YGA-1,subsequently,the system’s sand fixation and water blocking performance were evaluated.Finally,a pilot test was carried out in the mining site.Experimental results showed that the optimal formula composition of the system was 10%SCA-2+5%YGA-1.The gelation time of the system was 180 minutes and the viscosity after gelation could reach 108.4 mPa·s.When the dosage of the drug system was 0.6 PV,the sand production rate remained below 0.08%.Dual-tube parallel experiments showed that the sand fixation and water plugging system had a water flow channel plugging rate of 87.5%,while the oil flow channel plugging rate was only 11.3%,indicating minimal damage to the oil-bearing reservoir.The field test showed that after the measures taken in Well M of X oilfield,the sand free oil recovery period exceeded 360 days,the water content decreased by 5.0%and the cumulative oil production increased by 7092 m^(3).This study provides new ideas for efficient development of loose sandstone reservoirs.展开更多
基金Supported by the National Natural Science Foundation of China(32072352)the National Key Research and Development Program Project of China(2022YFD1600500)。
文摘A machine learning-based APP may quickly and non-destructively evaluate the quality of parameters,such as hardness and anthocyanin content in blue honeysuckle berries(Lonicera caerulea L.,BHB),based on changes in pericarp color characteristics.The color feature information of the BHB pericarp was extracted,and the corresponding hardness and anthocyanin content were determined at various growing stages.Correlation analysis of BHB quality indexes was conducted by single and combined components of BHB epidermal color features.The results showed that fruit hardness had a significantly negative correlation with color feature parameter R-G,and its anthocyanin content had a significantly positive correlation with color feature parameter R.Comparing the eight models,random forest(RF)was established to evaluate the hardness and anthocyanin content of BHB according to the correlation between pericarp color features and hardness and anthocyanin content on BHB quality evaluation APP on the WeChat platform.The credibility of APP embedding RF model for evaluating hardness and anthocyanin content in BHB was validated with the determination coefficient of 0.89 and 0.93 in practice.This approach could efficiently and conveniently evaluate the quality indexes of BHB in real time and serve as a technical reference for the detection of quality indicators of other berries using smartphones.
基金Project supported by the National High-Tech Research and Development program of China (863 Program ) (No.2 0 0 2 AA2 Z42 5 1-2 10 0 41) Postdoctoral Scientific Foundation of Northeast Agricultural U niversity. (No. 2 40 0 0 9) and postdoctoral Scien
文摘Owing to overcoming the characteristics that there are many economic and technical indexes which are fuzzy and incompatibility to each other in evaluating investment project,a new method is proposed.The method is based on the matter-element analysis and combined with the concepts of fuzzy mathematics,which is called the method of fuzzy matter-element analysis.It constructs the compound fuzzy matter element with the investment projects,evaluation factors and their fuzzy value.Through establishing the best subjection degree (fuzzy value),complex fuzzy matter element of relational coefficient and weight aggregation of fuzzy matter-element model,the writer achieves on optimum order of the investment projects according to the calculated relational degree and finds the best project.In this paper,the calculation of weight adopts the analytical hierarchy process method(AHP).Through the actual example,it shows that the model is simple and its calculation is reliable.It is very significant for the engineering evaluated bid and investment decision.
基金This work was supported by National Natural Science Foundation of China (NSFC) under the grant !No. 69873030
文摘To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit to circuit. In this paper, the genetic algorithms are used to construct the models of existing test generation algorithms in making such choice more easily. Therefore, we may forecast the testability parameters of a circuit before using the real test generation algorithm. The results also can be used to evaluate the efficiency of the existing test generation algorithms. Experimental results are given to convince the readers of the truth and the usefulness of this approach.
文摘Vendors’Evaluating and Selecting is one study focu s in SCM and VMO. It is one of the very important operations management and can ad vance to implement the strategic aims. With the increase in use of total quality management and just-in-time concepts by a wide range of firms, the vendor sel ection question has become extremely important. It is necessary for firms to tak e part in the global competition and global manufacture. There are some decision -making techniques which can be used for evaluating and selecting vendors, such as weighting point methods, utility theary, multi-objective programming, analy tic hierarchy process, vendor profile analysis, and so on. Analytic Hierarchy Pr ocess(AHP) is a technique in common use for quantifying the problem. Since AHP i s put forward in 1973 by Satty, it has been accepted. However, this technique ha s its shortcomings, and one of them is that distributing weights is subjective. In recent years,some scholars prove that it is defferent from factual doing usin g subjective ways for vendors’ evaluating and selecting. In fact, the methods f or vendors’evaluating and selecting should be given by practical circs. Today, there’s somebody who has brought forward that it is studied by deviding four ty pes of relationships in view of two major factors: the reference time horizon of the relationship; and the content of the relationship in terms of the nature of the interation between supplier and customer. In the paper, we only consider th e scenario of short-term and logistic intergration brought forward by Cristina and Andrea. In the scenario, we only consider current manufacturing performance. In fact, the scenario is often seen in these developing countries.We bring up a model for grey system analysis on vendors’evaluating and selecting to attempt to expore this problem. The model integrates AHP and the grey system theory and attempt to eliminate the subjective factors in AHP using objective datum. Moreov er, it is based on the feature of data insufficiency and uncertainty and sample information of abnormality in system data.So,it overcomes the issues of deficien t information and absent data(it is often seen in management).
基金National"863"High-Technique Programm e.(No.2 0 0 2 AA2 Z42 5 1-2 10 0 41) Postdoctoral Scientific Foundation of NEAU(No.2 3 0 0 0 9) and Postdoctoral Scientific Foundation of Heilongjiang Province.
文摘Through applying PPE model based on RAGA to evaluate the benefit of rice water saving,the author turns multi-dimension data into low dimension space.So the optimum projection direction can stand for the best influence on the collectivity.Thus,the value of projection function can evaluate each item good or not.The PPE model can avoid jamming of weight matrix in the method of fuzzy synthesize judgement,and obtain better result.The author wants to provide a new method and thought for readers who are engaged in investment decision-making of water saving irrigation and other relative study.
文摘The evaluation method and its accuracy for evaluating complex systems are considered. In order to evaluate accurately complex systems, the existed evaluating methods are simply analyzed, and a new comprehensive evaluating method is developed. The new method is integration of Delphi approach, analytic hierarchy process, gray interconnect degree and fuzzy evaluation (DHGF). Its theory foundation is the meta-synthesis methodology from qualitative analysis to quantitative analysis. According to fuzzy set approach, using the methods of concordance of evaluation, redundant verify, double models redundant, and limitations of the method etc, the accuracy of evaluating method of DHGF is estimated, and a practical example is given. The result shows that using the method to evaluate complex system projects is feasible and credible.
基金Chinese Postdctoral Science Fund and Youngth Science Fund of Si Chuan U niversity.
文摘According to the method of water balance,the parameters of groundwater resouce of Jian San Jiang area have been calculated in the paper.At the same time,the quality of water supplying and water mining can be calculated.Furthermore,the groundwater resource have been evaluated.Thus,the paper provides the important references for managers to using groundwater reasonable.
文摘Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple label matching.However,previous studies have largely modeled this task as syndrome pattern classification within a fixed label space,which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning,and is also insufficient to capture the openness,semantic variability,and cross-disease reusability of syndrome manifestation expression.This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought(PR-CoT)supervision into large language models(LLMs)could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer.Methods Syndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information(X)→pathogenesis structure(Z)→syndrome pattern output(Y),where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment.Within this framework,a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders.After preprocessing,information extraction,manual proofreading,and data cleaning,the dataset comprised 4800 training cases,400 development cases,and 400 test cases.Each sample was annotated with a structured PR-CoT consisting of three progressive levels:clinical information summarization,comprehensive pathogenesis analysis,and syndrome pattern output.Supervised fine-tuning was conducted on open-source LLMs,with an end-to-end model serving as the baseline.Qwen3-32B was used as the primary experimental model,and Qwen3-14B as the scale comparison model.A progressive multidimensional evaluation framework was further established,comprising a structural parsing level,a semantic similarity level,and an expert blind review level.At the structural parsing level,syndrome pattern expressions were decomposed into structural elements and evaluated using Precision,Recall,F1 score,and Jaccard similarity.At the semantic similarity level,independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns.At the expert blind review level,three TCM experts independently evaluated model outputs on two dimensions:syndrome differentiation consistency and terminology standardization of syndrome patterns.In addition,zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets.Results At the structural parsing level,PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components.Compared with the corresponding baselines,neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision.In contrast,at the semantic similarity level,PR-CoT supervision produced stable positive gains across different model scales and evaluation systems.The average semantic score of Qwen3-32B increased from 6.4258 in the baseline model to 6.5850 after PR-CoT supervision,and that of Qwen3-14B increased from 5.8700 to 5.9642.At the expert blind review level,the overall score of Qwen3-32B(PR-CoT)was 7.0260±0.1077,higher than 6.4163±0.2889 for its baseline.In zero-shot cross-disease testing,the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets,indicating a certain degree of transferability.Conclusion The benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility,rather than in improved hard matching of structural elements.These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures,rather than as a classification task within a traditional fixed label space.By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework,this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment,interpretability,and multi-level evaluation.
文摘Evaluating the adversarial robustness of classification algorithms in machine learning is a crucial domain.However,current methods lack measurable and interpretable metrics.To address this issue,this paper introduces a visual evaluation index named confidence centroid skewing quadrilateral,which is based on a classification confidence-based confusion matrix,offering a quantitative and visual comparison of the adversarial robustness among different classification algorithms,and enhances intuitiveness and interpretability of attack impacts.We first conduct a validity test and sensitive analysis of the method.Then,prove its effectiveness through the experiments of five classification algorithms including artificial neural network(ANN),logistic regression(LR),support vector machine(SVM),convolutional neural network(CNN)and transformer against three adversarial attacks such as fast gradient sign method(FGSM),DeepFool,and projected gradient descent(PGD)attack.
基金supported by National Natural Science Foundations of China(Grant No.52308522).
文摘Gravity-caisson wharves have been widely constructed in coastal and island regions, which are threaten by potential underwater explosions. This work aims to study the dynamic behaviors and propose a damage evaluation approach of caisson wharf against underwater explosion. Firstly, based on both the underwater explosion loading test and underwater explosion test on the reduced-scale caisson specimen, a high-fidelity finite element analysis approach for numerically reproduce the dynamic behaviors of prototype caisson wharves against underwater explosions was proposed and verified. Secondly, the underwater explosion loadings and dynamic behaviors of prototype caisson wharf (14.9 m×8.1 m×10.95 m) against sequential blast wave and bubble pulsation of typical torpedo with a charge weight of 200 kg were studied. The influences of the seabed and cabin infill materials, as well as the explosion standoff distances of 3.4–10.2 m and depths of burst between 1/4 and 3/4 of water depth, on the blast resistance of caisson wharf were further examined through deflection distributions of exterior wall, damage evolution, and overall displacement of caisson wharf. Finally, a performance evaluation approach for prototype caisson wharves against underwater explosions was proposed by comprehensively considering the bearing, storage, and berthing capabilities. The corresponding protective measures and design recommendations were further provided. It indicates that: (i) under the explosion of a typical torpedo, the damage modes of prototype caisson wharf mainly involve the overall vibration, spalling and cracking of the exterior wall, collapse of the upper operating platform and cracking of the top plate;(ii) the blast wave and cavitation zone generated between the bubble and the exterior wall are the two primary causes of damage to caisson wharf;(iii) compared to the saturated calcareous sand seabed, the assumption of rigid seabed underestimates the spalling on the exterior wall, which is not recommended for scenarios where cavitation zones may generate;(iv) rock rubble is the most effective infill material in improving the blast resistance of caisson wharf among four types of infill configurations, i.e., fully filled and half-filled saturated calcareous sand, rock rubble and pure water;(v) the standoff distance of 10.2 m is regarded as a secure protective range in the scenarios discussed currently. As the standoff distance decreases and the depth of burst increases, the spalling of the exterior wall induced by the cavitation intensifies, posing a great threat to the functionality of caisson wharf.
基金supported by the Major Projects for Science and Technology Innovation 2030(2018AAA0100805)National Natural Science Foundation of China(62373187).
文摘The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on static evaluation methods.Therefore,this paper proposes a dynamic multi-round decision evaluation method based on the characteristics of multi-round unmanned aerial vehicle air combat under opponent’s optimal strategy.In order to determine objective weights,an improved multi-attribute decision making method is proposed,which incorporates the proximity as a correction coefficient for evaluation indicators,utilizing the cosine similarity instead of Euclidean distance,and incorporating both actual and theoretical objective weights to prevent data mutations.Subsequently,the game theory is employed to reasonably adjust subjective and objective weights to obtain comprehensive weights.To address the issues related to the ambiguity and randomness during the evaluation process,a reverse cloud generator is utilized to determine the center of gravity of the cloud model using comprehensive weights while employing the weighted deviation degree for evaluating air combat decision-making effectiveness.By activating the cloud generator through the cloud model,the optimal strategies for each round of air combat are determined,thereby completing the dynamic evaluations for multi-round sequential decision-making processes.Finally,the feasibility and effectiveness of the proposed method are verified through simulations.
文摘The comprehensive evaluation of six properties for equipment product is an important basis for their quality control,and their correlative relationship among six properties will affect their quality level.To understand their correlative relationship among six properties,this paper firstly combines group evaluation with decision-making trial and evaluation laboratory(DEMATEL)model,and develops the optimization model based on group consensus to form six influent relationship matrices.Secondly,group consensus matrix is used to design super network hierarchy matrix,and the weights of six properties with relevant environment is also proposed.Thirdly,the elimination and choice translating reality(ELECTRE)model is used to make comprehensive evaluation,and an example is used to compare the results under two kinds of conditions,and illustrate the effect of the weights of six properties on the priority of equipment products.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
文摘Objective To explore the therapeutic effect of LuoFuShan Rheumatism Plaster(LFS)on neuropathic pain(NP)and its molecular mechanism.Methods Mouse models of sciatic nerve chronic constriction injury(CCI)were treated with low,medium,and high doses(2.2,4.4,and 8.8 cm2,respectively)of LFS by topical application for 14 consecutive days.The therapeutic effects were assessed by evaluating the mechanical withdrawal threshold(MWT),paw withdrawal latency(PWL),plasma IL-6 and TNF-αlevels,and histopathology of the sciatic nerve.Network pharmacology and molecular docking were used to identify the key targets and signaling pathways.The key targets were verified by RT-qPCR and immunohistochemistry.The biosafety of LFS was evaluated by measuring the organ indices and damage indicators of the heart,liver,and kidneys.Results Compared with the CCI group,LFS dose-dependently increased MWT and PWL,reduced plasma IL-6 and TNF-αlevels,and alleviated sciatic nerve inflammation in the mouse models.Network pharmacology identified 378 bioactive compounds targeting 279 NPassociated genes enriched in TLR and TNF signaling.Molecular docking showed that quercetin and ursolic acid in LFS could stably bind to TLR4 and TNF-α.In the mouse models of sciatic nerve CCI,LFS significantly downregulated the mRNA expression levels of Tlr4 and Tnf-αin the spinal cord in a dose-dependent manner and lowered the protein expressions of TLR4 and TNF-αin the sciatic nerve.LFS treatment did not cause significant changes in the organ indices or damage indicators of the heart,liver and kidneys as compared with those in the CCI model group and sham-operated group.Conclusion LFS alleviates NP in mice by suppression of TLR4/TNF-α-mediated neuroinflammation with a good safety profile.
基金Project(52274096)supported by the National Natural Science Foundation of ChinaProject(WS2023A03)supported by the State Key Laboratory Cultivation Base for Gas Geology and Gas Control,China。
文摘Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.
基金National Natural Science Foundation of China (12202293)Sichuan Science and Technology Program (2023NSFSC0393,2022NSFSC1952)。
文摘A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.
文摘To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
文摘To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty).Three representative sections were examined:adobe brick masonry repaired(Area 1),well-preserved original(Area 2),and layer-by-layer ramming repaired(Area 3).THz spectral data revealed significant differences between Area 1(time delay:3.72 ps;refractive index:2.224)and Area 2(time delay:3.02 ps;refractive index:2.107),while Area 3(time delay:3.12 ps;refractive index:2.098)demonstrated nearly identical THz spectral data to Area 2.Infrared thermal imaging also showed that the Area 3 restored by layer-by-layer ramming exhibited greater uniformity with fewer instances of cracks,capillary phenomena,or biological diseases.The proposed point-surface integrated evaluation methodology synergistically combines infrared thermography mapping of heritage surfaces with THz spectral datasets acquired through in-situ micro-sampling,enabling quantitative restoration assessment and providing a novel approach for scientifically validating traditional conservation techniques.
文摘Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic resin and n-octanol were used to synthesize the main agent SCA-2.Hexamethylenetetramine and vinyl carbonate were selected to prepare the curing agent YGA-1,which was then compounded with SCA-2 to develop a sand fixation and water plugging system.Firstly,single-factor experiments were conducted to determine the optimal concentrations of SCA-2 and YGA-1,subsequently,the system’s sand fixation and water blocking performance were evaluated.Finally,a pilot test was carried out in the mining site.Experimental results showed that the optimal formula composition of the system was 10%SCA-2+5%YGA-1.The gelation time of the system was 180 minutes and the viscosity after gelation could reach 108.4 mPa·s.When the dosage of the drug system was 0.6 PV,the sand production rate remained below 0.08%.Dual-tube parallel experiments showed that the sand fixation and water plugging system had a water flow channel plugging rate of 87.5%,while the oil flow channel plugging rate was only 11.3%,indicating minimal damage to the oil-bearing reservoir.The field test showed that after the measures taken in Well M of X oilfield,the sand free oil recovery period exceeded 360 days,the water content decreased by 5.0%and the cumulative oil production increased by 7092 m^(3).This study provides new ideas for efficient development of loose sandstone reservoirs.
