CN121385015A - Composite green concrete salt-freezing-resistant durability evaluation system under soil environment of frozen soil area - Google Patents
Composite green concrete salt-freezing-resistant durability evaluation system under soil environment of frozen soil areaInfo
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Abstract
本发明涉及混凝土耐久性评估技术领域，具体地说，涉及冻土区土壤环境下复合型绿色混凝土抗盐冻耐久性评价系统，其包括数据输入单元、决策信息表存储单元、粗糙集分析处理单元及评估输出单元，数据输入单元接收含冻融循环次数、干湿循环次数、冻融‑干湿循环次数、长期浸泡时间、复合盐浓度、含气量及粉煤灰掺量的样本数据集，决策信息表存储单元存储基于粗糙集理论构建的决策信息表，关联影响因素组合与相对动弹性模量百分比，粗糙集分析处理单元通过属性约简和规则提取建立映射关系，量化各因素权重，评估输出单元输出相对动弹性模量预测值、耐久性等级分类及关键因素贡献排序，精准评估多因素耦合作用下的混凝土抗盐冻耐久性。
This invention relates to the field of concrete durability assessment technology, specifically to a salt-freezing resistance evaluation system for composite green concrete in permafrost soil environments. The system includes a data input unit, a decision information table storage unit, a rough set analysis and processing unit, and an evaluation output unit. The data input unit receives a sample dataset containing data on the number of freeze-thaw cycles, wet-dry cycles, freeze-thaw-wet-dry cycles, long-term soaking time, composite salt concentration, air content, and fly ash content. The decision information table storage unit stores a decision information table constructed based on rough set theory, linking the combination of influencing factors with the percentage of relative dynamic elastic modulus. The rough set analysis and processing unit establishes a mapping relationship through attribute reduction and rule extraction, quantifying the weight of each factor. The evaluation output unit outputs predicted values of relative dynamic elastic modulus, durability level classifications, and ranking of key factor contributions, accurately assessing the salt-freezing resistance of concrete under the coupled effects of multiple factors.
Description
Technical Field
The invention relates to the technical field of concrete durability evaluation, in particular to a composite green concrete salt-freezing-resistant durability evaluation system under a soil environment of a frozen soil area.
Background
The concrete durability evaluation is an important technology, in the infrastructure construction of northeast frozen soil areas, the concrete needs to bear multiple functions of freeze thawing cycle, dry-wet alternation and composite salt corrosion for a long time, the salt freezing resistance durability of the concrete is directly related to the service life and the safety performance of engineering structures, the salt freezing resistance durability of the composite green concrete is scientifically evaluated, key basis can be provided for material proportion optimization, engineering design and maintenance, and the concrete is an important technical support for guaranteeing the long-term stability of engineering in the frozen soil areas.
However, the existing concrete durability evaluation method has the problems that under the multi-factor coupling effect, the evaluation accuracy is insufficient in the complex environment of the northeast frozen soil area, an evaluation model is established aiming at single environmental factors in the traditional method, the synergistic effect of factors such as freeze thawing-dry-wet cycle, compound salt concentration and the like is not fully considered, so that the deviation between an evaluation result and an actual service state is large, meanwhile, the contribution weight of each factor is not quantized in the evaluation process, key factors playing a leading role in durability are difficult to identify, so that the evaluation result lacks pertinence, the problem causes the problem that the concrete performance degradation trend is difficult to accurately predict in engineering practice, the excessive use or the insufficient protection of materials can be caused, the economy and the safety of the frozen soil area engineering are finally influenced, and in order to solve the technical problem, the composite green concrete salt-resistant durability evaluation system under the soil environment of the frozen soil area is provided.
Disclosure of Invention
The invention aims to provide a composite green concrete salt-freezing-resistant durability evaluation system in a soil environment of a frozen soil area so as to solve the problems in the background technology.
1. Because the traditional method does not consider the influence of multi-factor coupling, the evaluation result has large deviation from reality, the concrete durability in a complex environment can be accurately evaluated by constructing a decision information table containing factors such as freeze thawing, dry and wet circulation and the like and using a rough set algorithm to extract rules to establish a mapping relation.
2. Because the existing method does not quantify the contribution weights of all factors and evaluation lacks pertinence, the case determines the weights by calculating the change amount of the attribute support, generates the contribution ordering of key factors, can clearly lead the factors and provides basis for material optimization.
In order to achieve the above object, there is provided a system for evaluating salt-freezing durability of composite green concrete in a soil environment of a frozen soil region, a data input unit for receiving a sample data set of composite green concrete, the sample data set including a plurality of preset influencing factors, the system comprising:
The decision information table storage unit is used for storing a predefined decision information table, the decision information table is constructed based on a rough set theory and comprises a plurality of records, each record corresponds to a group of specific influence factor combinations and a percentage value of relative dynamic elastic modulus associated with the specific influence factor combinations, and the relative dynamic elastic modulus is used as a decision attribute for representing the dynamic elastic modulus loss rate of the concrete;
The rough set analysis processing unit is connected with the data input unit and the decision information table storage unit and is used for inquiring the decision information table according to an input sample data set, and attribute reduction and rule extraction are carried out by applying a rough set algorithm so as to establish a mapping relation between influence factors and relative dynamic elastic modulus loss rate and generate a salt-freezing-resistant durability assessment result;
The evaluation output unit is used for outputting the evaluation result of the salt-freezing resistance durability, and comprises a predicted value of the relative dynamic elastic modulus and a corresponding durability grade classification.
Compared with the prior art, the invention has the beneficial effects that:
1. By integrating multiple working condition data such as salt leaching, salt corrosion, freeze thawing, dry and wet, and the like, coupling factors such as freeze thawing, dry and wet circulation, and the like are brought into a decision information table, the problem of disjointing of traditional single factor evaluation and actual environment is solved, and the influence of multi-factor synergism on the concrete performance in the complex environment of northeast frozen soil area can be accurately reflected by means of a mapping rule of a rough set algorithm extraction factor combination and relative dynamic elastic modulus, so that an evaluation result is more fit with engineering practice.
2. The dominant effects of factors such as freeze thawing, dry and wet circulation and the like are defined by calculating the support degree variation of each factor on the decision attribute to determine the weight, the outputted key factor contribution ordering provides a targeting direction for material optimization, meanwhile, the relative dynamic elastic modulus is divided into multiple levels of durability, visual mapping from the performance degradation degree to the specific level is realized, and engineering personnel can conveniently and rapidly judge the concrete state.
3. The dual verification mechanism dynamically optimizes attribute reduction and mapping relation through a sample reverse verification rule base which does not participate in training, ensures stable and reliable evaluation results, and predicts values, class classification and factor sequencing output by the system, comprehensively meets the requirements of frozen soil region engineering in aspects of material proportioning, structural maintenance and the like, provides scientific basis for engineering design and operation maintenance, and ensures long-term safe and stable operation of infrastructure.
Drawings
Fig. 1 is an overall block diagram of the present invention.
The meaning of each reference sign in the figure is:
1. the system comprises a data input unit, a decision information table storage unit, a rough set analysis processing unit and an evaluation output unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a composite green concrete salt-freezing-resistant durability evaluation system in a soil environment of a frozen soil area, referring to fig. 1, the system comprises a data input unit 1, a data analysis unit and a data analysis unit, wherein the data input unit is used for receiving a sample data set of composite green concrete, and the sample data set comprises a plurality of preset influence factors;
the sample data set comprises a plurality of preset influencing factors, specifically freeze thawing cycle times, dry and wet cycle times, freeze thawing-dry and wet cycle times, long-term soaking time, compound salt concentration, gas content and fly ash mixing amount;
In the complex soil environment of northeast frozen soil region, the salt freezing resistance and durability of the composite green concrete are jointly influenced by various environment and material factors, and the sample data set provides a structured condition attribute value for subsequent analysis by taking in key influencing factors and performing discretization treatment. The preset influencing factors comprise specifically freeze thawing cycle times, dry and wet cycle times, freeze thawing-dry and wet cycle times, long-term soaking time, compound salt concentration, air content and fly ash mixing amount, the erosion effect born by concrete and self deterioration resistance are respectively reflected from different dimensions, and the process of discretizing and converting each influencing factor into a conditional attribute value is as follows:
the number of freeze thawing cycles is divided into 5 stages according to the number of freeze thawing cycles actually experienced by concrete, 1 stage corresponds to 0-50 times (slight freeze thawing), 2 stage corresponds to 51-100 times (moderate freeze thawing), 3 stage corresponds to 101-200 times (severe freeze thawing), 4 stage corresponds to 201-300 times (extremely severe freeze thawing), 5 stage corresponds to more than 301 times (extreme freeze thawing), each stage value represents the interval of freeze thawing action intensity, the higher the numerical value is, the more severe the freeze thawing erosion, the dry and wet cycle number is divided into 4 stages according to the frequency of dry and wet alternation, 1 stage is 0-30 times (low frequency alternation), 2 stage is 31-60 times (medium frequency alternation), 3 stage is 61-100 times (high frequency alternation), 4 stage is more than 101 times (extreme frequency alternation), the method reflects the repeated action of dry and wet environment on the surface and internal structure of concrete, the freeze thawing-dry and wet cycle times are used as indexes of the coupling action of freeze thawing and dry and wet, the coupling cycle times are divided into 5 stages, 1 stage is 0-40 times (light coupling), 2 stage is 41-80 times (moderate coupling), 3 stage is 81-150 times (heavy coupling), 4 stage is 151-250 times (extremely heavy coupling), 5 stage is more than 251 times (extreme coupling), the accumulated effect of superposition of the two actions is quantified, the factors have important weights because of directly reflecting the typical composite erosion characteristics of a frozen soil area, the long-term soaking time is divided into 4 stages according to the continuous erosion days of the concrete in a salt solution, 1 stage is 0-30 days (short-term soaking), the 2 level is 31-90 days (medium soaking), the 3 level is 91-180 days (long soaking), the 4 level is more than 181 days (ultra-long soaking), the longer the days are, the greater the depth of penetration of the salt ions, the more significant the damage to the internal structure of the concrete, the more complex salt concentrations will attack the multiple salt species in the solution (e.g., naCl, Na 2SO4, etc.) is divided into 4 levels, 0-2% (low concentration), 2 levels 2% -5% (medium concentration), 3 levels 5% -8% (high concentration), 4 levels 8% or more (extremely high concentration), the higher the concentration is, the more severe the salt corrosion reaction is, the higher the risk of spalling of the concrete surface layer and internal cracking is, the gas content is divided into 3 levels according to the volume proportion of bubbles inside the concrete, 1 levels 1% -3% (low gas content), 2 levels 3% -5% (medium gas content), 3 levels 5% -7% (high gas content), a proper amount of bubbles (2 levels) can relieve the volume expansion pressure in the freezing and thawing process, the low gas content or the excessively high gas content can possibly reduce the freezing resistance, the fly ash doping amount is divided into 4 levels according to the proportion of the fly ash accounting for the total amount of the gelled material, 1 levels 0-10% (low doping amount), 2 levels 10% -20% (medium doping amount), 3 levels 20% -30% (high doping amount), 4 levels are 30% (ultra-high doping amount), the reasonable doping amount (2-3 levels) can be used for improving the concrete quality by a concrete quality factor, and the concrete quality factor is not further improved based on the accuracy of the analysis, and the quality of the concrete is not further improved, the quality factor is not serious, and the quality is not improved based on the theoretical doping level, and the quality is not improved.
Characterized by further comprising:
The decision information table storage unit 2 is used for storing a predefined decision information table, the decision information table is constructed based on a rough set theory, and comprises a plurality of records, each record corresponds to a group of specific influence factor combinations and a percentage value of relative elastic modulus associated with the specific influence factor combinations, and the relative elastic modulus is used as a decision attribute for representing the loss rate of the elastic modulus of the concrete;
the concrete mode of constructing the decision information table based on the rough set theory is as follows:
After the discretization processing of the influencing factors of the sample data set is completed, a decision information table is required to be constructed based on the rough set theory, the process is the key of converting the original test data into a regularized evaluation basis, the quantization processing of the influencing factors is accepted, a structured data basis is provided for the subsequent rough set analysis, the association relation between the influencing factors and the concrete salt-freezing resistance is systematically presented, and the decision information table is specifically constructed in the following manner:
Integrating concrete durability data under four typical test conditions, namely a salt leaching condition (soaked by a composite salt solution), a salt corrosion-dry-wet condition (salt leaching and dry-wet are alternately coupled), a salt corrosion-freeze thawing condition (salt leaching and freeze thawing cycle are coupled), a salt corrosion-freeze thawing-dry-wet condition (salt leaching, freeze thawing and dry-wet triple coupling), wherein the conditions cover main erosion scenes possibly encountered by concrete in the soil environment of northeast frozen soil area, when the data are integrated, 7 influence factors (freeze thawing cycle times and the like) after discretization are taken as condition attribute columns, the relative elastic modulus percentage is taken as decision attribute columns, the index directly reflects the loss degree of the elastic modulus of the concrete caused by salt freezing damage, thereby forming an original data table containing condition attribute sets and decision attributes, loading the original data table through a ROSETTA software platform, and starting an attribute reduction flow based on a genetic algorithm:
The genetic algorithm aims at eliminating redundant attributes and retaining core influence factors, each condition attribute is regarded as a gene, attribute subsets are generated through selection, intersection and mutation operations, the dependence of each subset on decision attributes is calculated, namely whether the subset can completely explain the change of the decision attributes, for example, if the dependence of the residual attributes on the decision attributes is still kept above 90% after the fly ash doping amount is removed, the attribute is judged to be the redundant attribute, otherwise, if the dependence is reduced by more than 20% after the freeze thawing-dry wet cycle times are removed, the attribute is retained as the core factor. Through multiple iterations (50 generations of evolution are usually set), the core factor combination with the most obvious influence on the concrete salt freezing resistance durability is finally screened out, a decision information table is generated based on the reduced core condition attribute and decision attribute, each record in the table corresponds to a discrete combination of a group of core influence factors ("freeze thawing-dry and wet cycle number 3 level+compound salt concentration 2 level+gas content 2 level"), and the relative dynamic elastic modulus percentage values under the combination are related to form a clear mapping relation of the condition attribute to the decision attribute. For example, a record shows that when the number of freeze thawing-dry and wet cycles is 3, the concentration of the compound salt is 3, and the air content is 1, the relative elastic modulus percentage is 60%, and this map directly reflects the performance degradation state of the concrete under the combination of factors, so that the system can quickly query based on the input sample data and generate reliable durability evaluation results.
The specific combinations of influencing factors in each record consist of discretized values:
In the construction of the decision information table, each recorded specific influence factor combination needs to be presented in a discretized numerical value, and the processing not only accepts the quantitative classification of each influence factor, but also provides standardized input for the attribute reduction and rule extraction of a rough set algorithm, so that the factor intensities under different test working conditions can be recognized and associated by the system, and the specific classification mode is as follows:
The number of freeze thawing cycles is divided into 5 stages according to the actual number of cycles, wherein stage 1 corresponds to 0-50 times (mild freeze thawing), stage 2 corresponds to 51-100 times (moderate freeze thawing), stage 3 corresponds to 101-200 times (severe freeze thawing), stage 4 corresponds to 201-300 times (severe freeze thawing), and stage 5 corresponds to 301 times or more (extreme freeze thawing). The value of each stage visually reflects the strength of the concrete subjected to the freeze thawing action, for example, in a salt corrosion-freeze thawing working condition, the 3-stage freeze thawing cycle number means that the concrete has undergone more severe freeze thawing corrosion, the internal pore structure of the concrete may be obviously deteriorated, the dry-wet cycle number is divided into 4 stages according to the dry-wet alternation frequency, the 1 stage is 0-30 times (low-frequency alternation), the 2 stage is 31-60 times (medium-frequency alternation), the 3 stage is 61-100 times (high-frequency alternation), and the 4 stage is more than 101 times (extreme-frequency alternation). Under the working condition of salt corrosion, dry and wet, the dry and wet circulation of 3 stages and above can accelerate the formation and peeling of salt frost on the concrete surface, so the grading is directly related to the accumulation degree of surface damage, the freeze thawing-dry and wet circulation times are used as core indexes of the freeze thawing and dry and wet coupling action, the coupling times are divided into 5 stages, 1 stage is 0-40 times (light coupling), 2 stage is 41-80 times (moderate coupling), 3 stage is 81-150 times (heavy coupling), 4 stage is 151-250 times (extremely heavy coupling), and 5 stage is more than 251 times (extreme coupling). In the most complex working condition of salt corrosion, freeze thawing, dry and wet, the higher the grading of the index, the stronger the superposition effect of the two effects, the higher the risk of microcrack expansion in the concrete, the long-term soaking time is divided into 4 grades according to the corrosion days of the salt solution, the 1 grade is 0-30 days (short-term soaking), the 2 grade is 31-90 days (medium-term soaking), the 3 grade is 91-180 days (long-term soaking), and the 4 grade is more than 181 days (ultra-long-term soaking). in the simple salt leaching working condition, 3-grade or above soaking time can lead a large amount of salt ions to permeate into the concrete, so as to provide a material basis for salt freezing damage, wherein the concentration of the compound salt is divided into 4-grade according to the percentage of the total concentration of multiple salt types in the solution, the concentration of the compound salt is 0-2 percent (low concentration), the concentration of the compound salt is 2-5 percent (medium concentration), the concentration of the compound salt is 5-8 percent (high concentration), and the concentration of the compound salt is more than 8 percent (extremely high concentration). The higher the concentration, the more violent the reaction of salt ions with the concrete hydration products, especially at high concentrations, the crystallization expansion of sodium sulfate can significantly exacerbate structural damage, the gas content being classified as 3 levels, 1 level to 3% by volume of the internal air bubbles of the concrete (low gas content), 2 level to 3% to 5% by volume (moderate gas content), and 3 level to 5% to 7% by volume (high gas content). The moderate air content (grade 2) can buffer the expansion pressure of ice crystals in the freezing and thawing process, and grade 1 or grade 3 can reduce the freezing resistance effect due to insufficient air bubbles or uneven distribution, and the characteristic makes the ice crystals become a key regulating factor in the salt corrosion-freezing and thawing related working condition, the mixing amount of the fly ash is divided into grade 4 according to the proportion of the fly ash to the total amount of the cementing material, grade 1 is 0-10% (low mixing amount), grade 2 is 10-20% (medium mixing amount), grade 3 is 20-30% (high mixing amount), and grade 4 is more than 30% (ultra-high mixing amount). The medium-high doping amount (grade 2-3) can improve the salt corrosion resistance by improving the compactness of the concrete, but the ultrahigh doping amount possibly has the adverse effect due to insufficient early strength, so that the grading needs to be considered in cooperation with other factors, the structuring treatment enables the attribute reduction of the subsequent genetic algorithm to accurately identify the core factors, and the finally generated decision information table also has clear condition-decision mapping logic, thereby providing a reliable data frame for the systematic evaluation of the salt freezing resistance durability of the concrete.
After the discretization of the influence factor combinations is completed, the relative elasticity modulus percentages related to the combinations are classified according to the degradation degree of the concrete performance, the process is to quantitatively define decision attributes, the structuring treatment of the condition attributes is carried out, and clear result labels are provided for the condition-decision mapping relation in a decision information table, so that rough set analysis can regularly extract the direct relation factor combinations and the durability states, the concrete classification mode is based on the observation result of the elasticity modulus loss test of the concrete under the action of multiple environmental factors, the relative elasticity modulus percentages (namely the ratio of the corroded elasticity modulus to an initial value) are classified into 5 grades, each grade corresponds to one discretization label and is used for precisely quantifying the durability states of the concrete, the 1 grade relative elasticity modulus is more than or equal to 90 percent and corresponds to the optimal state, at the moment, the elasticity loss rate of the concrete is less than or equal to 10 percent, the observation result shows that the internal structure of the concrete is basically free from damage, the surface is free from obvious salt frost or cracks, and good mechanical properties are still maintained, and the grade is immersed in the salt dipping grade (1 grade) working condition The composite salt is relatively common under slight erosion conditions such as low composite salt concentration (grade 1), the relative dynamic elastic modulus is less than or equal to 80 percent and less than 90 percent, the composite salt corresponds to a 'good' state, the dynamic elastic modulus loss rate is between 10 percent and 20 percent, the test shows that the surface of the concrete has little salt frost, but no obvious cracking, the internal pore structure is slightly degraded, the whole mechanical property still can meet the basic use requirement, the composite salt is mostly appeared in medium erosion environments such as medium-frequency dry-wet circulation (grade 2), medium-degree freeze thawing (grade 2), and the like, the composite salt is mostly appeared in medium-frequency dry-wet circulation (grade 3), the relative dynamic elastic modulus is less than or equal to 70 percent and less than or equal to 80 percent, the dynamic elastic modulus loss rate is 20 percent to 30 percent, obvious salt erosion spalling occurs on the surface of the concrete, local visible fine cracks, internal structural damage is accumulated, the composite salt is seriously frozen, frozen-thawed-dry-wet coupled (grade 3), and the composite salt is mainly used in medium-dry-wet environment The composite concrete is easy to reach the grade under severe conditions such as high composite salt concentration (grade 3), grade 4 (the relative dynamic elastic modulus is 60 percent to less than or equal to 70 percent), the dynamic elastic modulus loss rate is increased to 30 percent to 40 percent corresponding to a 'bad' state, experiments show that the concrete surface is peeled off in a large area, cracks are extended to deep layers, the internal compactness is obviously reduced, the mechanical properties are greatly attenuated, the composite concrete is usually in strong erosion environments such as extremely severe freeze thawing action (grade 4), ultra-long term soaking (grade 4) and the like, grade 5 (the relative dynamic elastic modulus is less than 60 percent) corresponding to a 'bad' state, the dynamic elastic modulus loss rate is more than 40 percent, the concrete structure is seriously damaged, through cracks appear, even partial cracks are accompanied, the bearing capacity is basically lost, and the composite concrete is mostly subjected to extreme freeze thawing-dry wet coupling (grade 5), under extreme erosion conditions such as extremely high compound salt concentration (level 4), for example, when the number of freeze thawing-dry and wet cycles is 3, the compound salt concentration is 3, and the gas content is 1, the corresponding relative dynamic elastic modulus percentage may fall into the range of 70% -80%, i.e. the decision attribute label is 3, which intuitively reflects that the concrete durability is in the "medium" state under the combination of the factors. The grading mode is based on objective observation of test data, and the calculability of decision attributes is realized through the discretization label, so that a standardized output target is provided for establishing a mapping relation between influence factors and durability states for a subsequent rough set analysis processing unit 3, and the logic of the whole evaluation system is enabled to form a complete closed loop from factor quantification to result grading.
On the basis of dividing the relative dynamic elastic modulus percentage into corresponding durability grades, the dynamic elastic modulus loss rate is characterized by taking the dynamic elastic modulus percentage as a decision attribute, and is determined based on the intrinsic mechanism of concrete material degradation and a data association rule, and the setting not only accepts the quantification treatment of the grading of the decision attribute, but also provides scientific basis for extracting association rules of influencing factors and performance degradation through a rough set algorithm, so that the core logic of the whole evaluation system is penetrated, and the specific mechanism and the implementation mode are as follows:
Firstly, verifying the effectiveness of indexes through association degree analysis, selecting concrete samples with different air contents (the air content is 1% -7%), carrying out comparison test under the salt corrosion-freeze thawing-dry and wet coupling working condition, collecting relative dynamic elastic modulus and internal structure damage data of each sample under different circulation times, analyzing to find that the air content and the loss rate of the relative dynamic elastic modulus show obvious negative correlation, the relative dynamic elastic modulus is still kept above 80% after 150 freeze thawing-dry and wet circulation, the internal crack density is lower than 0.5 pieces/mm < 2 >, the relative dynamic elastic modulus is reduced to below 65% under the same circulation times, and the crack density is up to 1.2 pieces/mm < 2 >. This result proves that the decrease of the relative elastic modulus percentage is directly and positively correlated with the damage (increase of pores and crack growth) of the internal structure of the concrete, namely the index can objectively reflect the performance degradation degree of the material caused by the salt freezing action, has scientificity as a decision attribute, and can establish a mapping relation between a condition attribute combination and macroscopic performance degradation after setting the relative elastic modulus as the decision attribute, for example, when the condition attribute combination of the freezing thawing-dry-wet cycle number 3 grade+the compound salt concentration 3 grade+the air content 1 grade appears, the corresponding relative elastic modulus percentage falls into a range of 70% -80% (grade 3 decision attribute), which indicates that the factor combination can cause the concrete to be degraded moderately, and the combination of the freezing thawing-dry-wet cycle number 5 grade+the compound salt concentration 4 grade+the air content 1 grade corresponds to the relative elastic modulus <60% (grade 5 decision attribute), which indicates serious degradation. The mapping relation is used for associating scattered influence factors with visual performance results, laying a foundation for rule extraction, and when the contribution degree of each factor to the damage evolution is disclosed through rough set rule extraction, a system can automatically identify a key influence path based on the mapping relation, for example, if the number of freeze thawing-dry and wet circulation is more than or equal to 3 and the air content is less than or equal to 1, the support degree of the relative dynamic elastic modulus is less than or equal to 70% reaches 85% according to the rule, so that the combination of the two factors plays a leading role in the damage evolution, and the level 4 of the fly ash doping amount only has a significant influence on the decision attribute when the compound salt concentration is less than or equal to 2, so that the contribution degree is limited by other factors. The rules quantify the action intensity of different factor combinations, reveal the inherent logic of the damage evolution, enable the evaluation result to not only predict the durability state of the concrete, but also definitely lead to the key factor of degradation, provide targeted guidance for material optimization, in sum, relatively move the elastic modulus as decision attribute, both verify the effectiveness of the characterization damage through the association analysis, and provide the carrier for rule extraction through the mapping relation with the condition attribute, so that the whole evaluation system can form a complete logic chain from index selection to rule mining, ensure that the analysis of the salt-freezing resistance durability of the composite green concrete is scientific and accurate, and have practical application value.
The rough set analysis processing unit 3 is connected with the data input unit 1 and the decision information table storage unit 2 and is used for inquiring the decision information table according to the input sample data set, and performing attribute reduction and rule extraction by applying a rough set algorithm so as to establish a mapping relation between influence factors and relative dynamic elastic modulus loss rate and generate a salt-freezing-resistant durability assessment result;
After determining the relative dynamic elastic modulus as the decision attribute and establishing the mapping relation between the condition attribute and the decision attribute, the rough set analysis processing unit 3 needs to screen core influencing factors through an attribute reduction process, which not only receives the construction result of the decision information table, but also lays a foundation for the accuracy of the follow-up rule extraction, and the evaluation system can focus on factors playing a key role in the concrete salt-freezing resistance durability by quantifying the contribution weight of each condition attribute, and the specific implementation mode is as follows:
The rough set analysis processing unit 3 calculates the dependency of each condition attribute on the decision attribute. The degree of dependence is an index that measures whether a set of conditional attributes can fully interpret the change of a decision attribute, and the higher the value of the index, the more closely the association of the set of attributes with the decision attribute. During calculation, all 7 condition attributes in the decision information table are taken as an initial set, the initial dependency degree (marked as gamma 0 and usually set as a reference value 1.0) is obtained through a dependency degree analysis function of ROSETTA software, and an iterative process of sequentially removing single condition attributes is carried out:
Each time an attribute is removed from the set of conditional attributes (e.g., the "fly ash blend" is removed for the first time), a new subset of attributes is formed, the dependence of the subset on the decision attribute (denoted as γi) is recalculated by ROSETTA software, and the support change Δγi=γ 0 - γi is calculated. For example, after the freeze thawing-dry wetting cycle number is removed, the dependence is reduced from 1.0 to 0.65, Δγi=0.35, which indicates that the removal of the attribute greatly reduces the interpretation of the decision attribute by the conditional attribute, while after the fly ash doping amount is removed, the dependence remains at 0.96, Δγi=0.04, which indicates that the influence on the whole association is small, and the independent contribution weight of each factor is determined based on the support degree variation, namely, Δγi is normalized, that is, the contribution weight ωi=Δγi/ΣΔγi of a certain attribute (ΣΔγi is the sum of all attributes Δγi). Assuming that Δγi of 7 attributes is 0.35 (freeze thawing-dry and wet cycle number), 0.20 (compound salt concentration), 0.15 (air content), 0.10 (freeze thawing cycle number), 0.08 (dry and wet cycle number), 0.06 (long-term soaking time), and 0.04 (fly ash blending amount), respectively, the weight ω=0.35/(0.35+0.20+0.15+0.10+0.08+0.06+0.04) =0.35 of the freeze thawing-dry and wet cycle number becomes the core factor with the highest contribution weight, and the weight of the fly ash blending amount is only 0.04, which belongs to the minor factor, so that the subsequent rule extraction is focused only on the factor combination which has a dominant effect on the concrete salt-resistant durability, not only simplifies the analysis model, but also ensures the reliability of the evaluation result, forms a logical progression with the decision information table constructed in the foregoing, and provides a key support for the final generation of the accurate salt-resistant durability evaluation result.
The rule extraction stage distributes weight coefficients based on attribute importance ranking results, and the rule extraction stage comprises the following specific steps:
After the independent contribution weights of all the condition attributes are determined by about degeneracy of the attributes, the rule extraction stage is required to distribute weight coefficients based on the attribute importance ranking result, and the process is further quantized on the action intensity of core influence factors, so that the attribute importance difference obtained by the support degree variation analysis is accepted, a numerical basis is provided for constructing a weighted evaluation rule set, the actual influence of each factor can be reflected more accurately by the subsequent evaluation of the concrete salt freezing resistance durability, and the concrete implementation mode is as follows:
The support degree reduction amplitude (delta gamma i) calculated in the attribute reduction process is taken as a direct basis of the importance degree score. The larger the support degree is reduced, the more critical the interpretation of the attribute to the decision attribute is, and the higher the importance score is. For example, the delta gamma i of the freeze thawing-dry and wet cycle times is calculated to be 0.35, the concentration of the compound salt is calculated to be 0.20, the air content is calculated to be 0.15, the freeze thawing cycle times is calculated to be 0.10, the dry and wet cycle times are calculated to be 0.08, the long-term soaking time is calculated to be 0.06, the fly ash doping amount is calculated to be 0.04, the numerical values are directly used as importance scores of all the attributes, the core position of the freeze thawing-dry and wet cycle times in all the factors is clearly reflected, the influence of the fly ash doping amount on the minor effect is reflected, and the importance scores are normalized to obtain weight coefficients, namely the importance scores of all the attributes are divided by the sum of the importance scores of all the attributes, so that the final weight coefficient sum is 1. Taking the above values as examples, the sum is 0.35+0.20+0.15+0.10+0.08+0.06+0.04=1.0, so the weight coefficient of each attribute is the same as the importance score value, that is, the weight of freeze thawing-dry and wet cycle number is 0.35, the concentration of the compound salt is 0.20, the air content is 0.15, the freeze thawing cycle number is 0.10, the dry and wet cycle number is 0.08, the long-term soaking time is 0.06, and the fly ash mixing amount is 0.04. The result accords with the actual erosion mechanism, the coupling effect of freeze thawing and dry and wet is the main driving force of concrete salt freezing damage in northeast frozen soil area, so the weight is highest, while the mixing amount of fly ash can influence by improving compactness, but under the superposition of multiple severe environmental factors, the effect is relatively limited, so the weight is lowest, and when the weight distribution result is used for constructing a weighted evaluation rule set, the system can blend the weight coefficient of each condition attribute into each extracted rule. For example, if the number of freeze thawing dry and wet cycles is not less than 3 and the concentration of the compound salt is not less than 3, the relative dynamic elastic modulus is not more than 70%, the confidence of the rule is enhanced according to the weight (0.35+0.20=0.55) of two factors, so that the rule has higher priority in evaluation, and the confidence of the rule containing the fly ash mixing amount is properly adjusted due to the lower weight of the factors. The weighting mode ensures that each rule in the rule set can play a corresponding role according to the actual importance of the factors, so that the durability evaluation result based on the rule meets the rule of test data, the contribution difference of different factors to the concrete anti-salt-freezing performance can be accurately reflected, the rules are tightly connected with the attribute reduction logic, and a solid rule base is provided for finally generating a reliable evaluation result.
After rule extraction is completed and weight coefficients of all condition attributes are determined, a mapping relation between a condition attribute combination and decision attributes is established through a double verification mechanism, the process is to strictly verify the reliability of a rule base, an initial rule base generated based on the weight coefficients is accepted, the accuracy of the mapping relation is ensured through dynamic optimization, and finally generated evaluation results of the salt-freezing resistance durability can truly reflect the performance state of concrete in a complex environment, and the concrete implementation mode is as follows:
Generating an initial rule base according to the assigned weight coefficients, taking a core condition attribute combination as input, calculating the influence intensity on a decision attribute (relative dynamic elastic modulus grade) by combining the weight coefficients of the initial rule base to form a rule set of ' if the condition attribute A is x-grade and the condition attribute B is y-grade, then the decision attribute is z-grade ', for example, based on the highest-weight ' freeze thawing-dry and wet cycle times ' (0.35) and ' compound salt concentration ' (0.20), generating a rule ' if the freeze thawing-dry and wet cycle times are more than or equal to 4-grade and the compound salt concentration is more than or equal to 3-grade ', then the relative dynamic elastic modulus grade is 4-grade (difference) ', labeling the confidence level obtained by accumulation of the weight coefficients for each rule (for example, the rule confidence level is 0.55), and reversely verifying the initial rule base by a MATLAB program:
And selecting 30% of samples which do not participate in rule training (such as 100 groups of independent data under salt corrosion-freeze thawing-dry and wet working conditions) from the test data set, inputting the condition attribute values of the samples into a rule base to obtain corresponding decision attribute predicted values, extracting the measured relative dynamic elastic modulus percentage and the corresponding grade in the samples, and calculating the deviation of the predicted values and the measured values. The deviation calculation adopts a weighted average value of a level difference absolute value (such as a predicted level is 4, the actual measurement is 5, the deviation is 1) and a relative error (such as a predicted relative dynamic elastic modulus is 65%, the actual measurement is 58% and the relative error is 12%), the prediction accuracy of a rule base is comprehensively evaluated, a deviation threshold (such as the level difference absolute value is less than or equal to 1 and the relative error is less than or equal to 10%) is set, if the sample deviation exceeding 30% in a verification result exceeds the threshold, the reliability of the initial rule base is insufficient, and the genetic algorithm is immediately triggered to carry out attribute reduction again. When the method is simplified again, the genetic algorithm can adjust an attribute selection strategy (such as increasing the attention degree of the 'gas content' and the like on the attributes directly related to the freezing resistance), optimize the core attribute combination, further generate a new rule base, repeat the reverse verification process until the standard reaching rate of the sample deviation is more than or equal to 90% in the continuous 3 times of verification, ensure that the prediction error is stable within a preset range (such as the average relative error is less than or equal to 8%), and can judge that the mapping relation between the conditional attribute combination and the decision attribute is established, so that the mapping relation can adapt to the performance data rules under different test working conditions, form organic connection with the rule extraction process, and provide solid guarantee for finally outputting the accurate salt freezing resistance durability assessment result.
The evaluation output unit 4 is used for outputting the evaluation result of the salt-freezing resistance durability, and comprises the predicted value of the relative dynamic elastic modulus and the corresponding durability grade classification.
After the condition attribute combination and decision attribute mapping relation verification is completed, the evaluation output unit 4 generates an anti-salt freezing durability evaluation result, and the link is the result presentation of the whole analysis process, which not only accepts the mapping relation established by the double verification mechanism, but also meets the overall requirement on concrete durability evaluation in practical application through multi-dimensional output, so that the evaluation result has quantization precision, can intuitively reflect the performance state and key influence factors, and the specific output content and implementation modes are as follows:
First, the generation of the relative dynamic elastic modulus predictive value is based on a weighted calculation of the weight coefficient and the input influence factor value. For a composite green concrete sample to be evaluated, discretized values of 7 influence factors are obtained, the values are multiplied by corresponding weight coefficients and summed to obtain a weighted total score, and the weighted total score is converted into a specific relative dynamic elastic modulus predicted value through a preset linear mapping formula. For example, the weighted total of a certain sample is divided into 0.45, the corresponding predicted value is 77.5%, and the value directly quantifies the retention degree of the dynamic elastic modulus of the concrete under the combined action of the current influencing factors;
and secondly, marking the durability grade classification according to the grade interval to which the predicted value belongs. In combination with established grading standards, the corresponding intervals within which the relative dynamic elastic modulus predicted values fall are respectively rated as 1 grade (excellent) of more than or equal to 90 percent, 2 grade (good) of 80 to 90 percent, 3 grade (medium) of 70 to 80 percent, 4 grade (poor) of 60 to 70 percent and 5 grade (inferior) of <60 percent. Taking 77.5% of the predicted value as an example, the predicted value belongs to a 70% -80% interval, so that the durability grade is marked as grade 3, and the current performance degradation degree of the concrete is intuitively reflected;
Thirdly, the key factor contribution rank lists the influence intensity of each influence factor on the current prediction result from high to low according to the weight coefficient. Based on the weight distribution determined in the rule extraction stage, 7 influencing factors are arranged in descending order of weight coefficients, and the actual input values (discretization level) of the factors are marked at the same time so as to determine which factors are main driving factors for causing the current durability state. For example, the sequencing result of a certain sample is that the freeze thawing-dry and wet cycle times (0.35,3 grade) > the compound salt concentration (0.20,2 grade) > the air content (0.15,2 grade) > the freeze thawing cycle times (0.10,2 grade) > the dry and wet cycle times (0.08,1 grade) > the long-term soaking time (0.06,2 grade) > the fly ash mixing amount (0.04,3 grade), the sequencing clearly shows that the freeze thawing-dry and wet coupling effect and the compound salt concentration are core factors influencing the durability of the sample, the pertinence direction is provided for the subsequent material optimization or maintenance measures, and the whole evaluation system can provide scientific, comprehensive and practical reference basis for the salt freezing durability evaluation of the compound green concrete in northeast frozen soil areas.
According to the invention, a data input unit 1 is used for receiving a sample data set containing freeze thawing cycle times, dry and wet cycle times, freeze thawing-dry and wet cycle times, long-term soaking time, compound salt concentration, gas content and fly ash doping amount, a decision information table storage unit 2 is used for storing a decision information table constructed based on a rough set theory, a rough set analysis processing unit 3 is used for establishing a mapping relation through attribute reduction and rule extraction, quantifying the weights of all factors, and an evaluation output unit 4 is used for outputting a relative dynamic elastic modulus predicted value, durability grade classification and key factor contribution sorting, and accurately evaluating the salt-resistant freeze durability of concrete under the multi-factor coupling effect.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
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