Prediction method of highway pavement rutting based on the grey theory

In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data,analysis of variance （ANOVA）was first used to study the influence of different factors on pavement rutting. Cluster analysis was then employed to investigate the rutting development trend.Based on the clustering results,the grey theory was applied to build pavement rutting models for each cluster, which can effectively reduce the complexity of the predictive model.The results show that axial load and asphalt binder type play important roles in rutting development.The prediction model is capable of capturing the uncertainty in the pavement performance prediction process and can meet the requirements of highway pavement maintenance,and,therefore,has a wide application prospects.

Risk Assessment of Diary Cattle Brucellosis Based on Systematic Multilevel Grey Relation Entropy Method

[Objective] The study was to explore the major factors affecting diary cattle brucellosis risk assessment,as well as their strong-to-weak sequence,so as to provide theoretical basis for assessing diary cattle brucellosis risk level in different regions.[Method] From 4 dimensions of feeding and importing,breeding,housing and polyculture situation,an evaluation index system was set up,and diary cattle brucellosis risk survey was conducted in 3 typical regions.Finally,systematic multilevel grey relation entropy method was applied to perform data analysis.[Result] The strong-to-weak sequence of Level 1 impact factor of diary cattle brucellosis was as follows：feeding and importinghousingpolyculture situationbreeding;the sequence of Level 2 impact factor was U32〉U12〉U11〉U31〉U21〉U42〉U43〉U23〉U22〉U41;the risk level sequence of 3 typical regions was Province A（County A1,A2,A3）Province B（County B1,B2,B3）Province C（County C1,C2,C3）.[Conclusion] According to the weight of Level 1 index strata,administrative departments at all levels and dairy cattle farmers should lay emphasis on the aspects of feeding,importing and housing;viewed from the perspective of Level 2 index strata,dairy cattle farmers should value the siting of cattle field,the brucellosis surveillance before importing and milking modes most.According to the diary cattle brucellosis risk level of 3 typical regions,if administrative departments at all levels strengthen peoples＇ awareness of their personal health and increase investment in this area,with new healthy cultured atmosphere built,the risk level of diary cattle brucellosis will surly decline.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Optimization of cutting parameters with Taguchi and grey relational analysis methods in MQL-assisted face milling of AISI O2 steel

This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.

An ideal point method adopting grey relational entropy to estimate life cycle cost with effectiveness of torpedo

To making the decision of the developing blue prints,ideal point method was selected to estimate the life cycle cost with effectiveness of torpedo.At the same time,the concept of grey relational entropy of the grey system theory was adopted to compute the distance between each blue print and the ideal point(or negative ideal point).The blue print,nearest to the ideal point and farthest to the negative ideal point,is the best one.As an example,four blue prints of torpedo were estimated.The result indicates the practical value of this method.

Priority-sequence of mineral resources' development and utilization based on grey relational analysis method

Generally, the sequence decision of the development and utilization of Chinese mineral resources is based on national and provincial overall plan of the mineral resources. Such plan usually cannot reflect the relative size of the suitability of the development and utilization of mineral resources. To solve the problem, the paper has selected the gift condition, the market condition, the technological condition,socio-economic condition and environmental condition as the starting-points to analyze the influential factors of the priority-sequence of mineral resources' development and utilization. The above 5 conditions are further specified into 9 evaluative indicators to establish an evaluation indicator system. At last,we propose a decision model of the priority sequence based on grey relational analysis method, and figure out the observation objects by the suitability index of development. Finally, the mineral resources of a certain province in China were analyzed as an example. The calculation results indicate that silver(2.0057), coal(1.9955), zinc(1.9442), cement limestone(1.9077), solvent limestone(1.5624) and other minerals in the province are suitable for development and utilization.

Optimization of back bead geometry in the PMAG-TIG twin arc hybrid root welding process using grey based Taguchi method

This study investigated multi-response optimization of the pulse metal active gas-tungsten inert gas( PMAG-TIG) twin arc hybrid root welding process for an optimal parametric combination to yield favorable back bead geometry of welded joints using grey relational analysis and Taguchi method.Eighteen experimental runs based on an orthogonal array following the Taguchi method were performed to derive objective functions to be optimized within the experimental domain.The objective functions were selected in relation to parameters of PMAG-TIG twin arc root welding back bead geometry: back bead width to root reinforcement ratio and deposited metal height.The Taguchi approach was followed by grey relational analysis to solve the multi-response optimization problem.The significance of factors on overall quality characteristics of the weld joint was also evaluated quantitatively using analysis of variance.Optimal results were verified through additional experiments,and showed to feasibility of applying grey relation analysis in combination with Taguchi technique for continuous improvement of product quality in the manufacturing industry.

Grey GM(1,1) Model with Function-Transfer Method for Wear Trend Prediction and its Application

Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the ondemand necessity to perform surgery during space missions.Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing.Among all 3D printing techniques,fused deposition modelling(FDM)is a low-cost and more rapid printing technique.This article proposes the fabrication of surgical instruments,namely,forceps and hemostat using the fused deposition modeling(FDM)process.Excellent mechanical properties are the only indicator to judge the quality of the functional parts.The mechanical properties of FDM-processed parts depend on various process parameters.These parameters are layer height,infill pattern,top/bottom pattern,number of top/bottom layers,infill density,flow,number of shells,printing temperature,build plate temperature,printing speed,and fan speed.Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid(PLA)parts printed by FDM.The experiments have performed through Taguchi’s L27orthogonal array(OA).Variance analysis(ANOVA)ascertains the significance of the process parameters and their percent contributions to the evaluation indexes.Finally,as a multiobjective optimization technique,grey relational analysis(GRA)obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties.Scanning electron microscopy(SEM)examines the types of defects and strong bonding between rasters.The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength(42.6 MPa)and modulus of elasticity(3274 MPa).

Optimization of Tribological Performance of Al-6061T6-15% SiCp-15% Al₂O₃Hybrid Metal Matrix Composites Using Taguchi Method &Grey Relational Analysis

In this investigation, optimization of tribological performance parameters of Al-6061T6 alloy reinforced with SiC (15% by weight) and Al2O3 (15% by weight) particulates having particle size of 37 μm each has been presented. The wear and frictional properties of the hybrid metal matrix composites have been studied by performing dry sliding wear test using pin-on-disc wear tester. A L27 orthogonal array is selected for the analysis of the data. From the test results it is observed that sliding distance has the significant contribution in controlling the friction and wear behaviour of hybrid composites. A confirmation test is also carried out to verify the accuracy of the results obtained through the optimization. In addition an optical micrograph test is also performed on the wear tracks to study the wear mechanism.

Optimizing the Glass Fiber Cutting Process Using the Taguchi Methods and Grey Relational Analysis

This paper mainly describes a new approach to optimizing of the cutting glass fiber with multiple performance characteristics, based on reliability analysis, Taguchi and Grey methods. During the cutting process, the speed, the volume and the cutting load are optimized cutting parameters when the performance characteristics, which include Weibull modulus and blade wear, are taken into consideration. In this paper, optimization with multiple performance characteristics is found to be the highest cutting speed and the smallest cutting volume, and the medium cutting load. An analysis of the variance of the blade wear indicates that the cutting speed (47.21%), the cutting volume (14.62%) and the cutting load (12.20%) are the most significant parameters in the cutting process of glass fibers. In summary, the most optimal cutting parameter should be A3B1C2. The results of experiments have shown that the multiple performance characteristics of cutting glass fiber are improved effectively through this approach.

Study on the evaluation index system and evaluation method for self-elevating drilling unit design

In the process of designing self-elevating drilling unit, it is important, yet complicated, to use comparison and filtering to select the optimum scheme from the feasible ones. In this research, an index system and methodology for the evaluation of self-elevating drilling unit was proposed. Based on this, a multi-objective combinatorial optimization model was developed, using the improved grey relation Analysis （GRA）, in which the analytic hierarchy process （AHP） was used to determine the weights of the evaluating indices. It considered the connections within the indices, reflecting the objective nature of things, and also considered the subjective interests of ship owners and the needs of designers. The evaluation index system and evaluation method can be used in the selection of an optimal scheme and advanced assessment. A case study shows the index system and evaluation method are scientific, reasonable, and easy to put into practice. At the same time, such an evaluation index system and evaluation method will be helpful for making decisions for other mobile platforms.

A New Modified GM (1,1) Model: Grey Optimization Model

Based on the optimization method, a new modified GM (1,1) model is presented, which is characterized by more accuracy prediction for the grey modeling.

Expansion modelling of discrete grey model based on multi-factor information aggregation

This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model （GM （1, h））, always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method （abbreviated as FDGM （1, h））, is proposed accordingly. Then the feedback control equation and the parameters＇ solution of the FDGM （1, h） model are given. Finally, a real application is used to test the modelling accuracy of the FDGM （1, h） model. Results show that the FDGM （1, h） model is much better than the nonhomogeneous discrete grey forecasting model （NDGM） and the GM （1, h） model.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation method

A typical electronic communication system, such as GPS receiver, unmanned aerial vehicle＇s （UAV＇s） data link, and radar, faces multi-dimensional and complicated electromagnetic interference in operating environment. To measure the anti- interference performance of the electronic communication system in the complicated electromagnetic interference environment, a method of multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation in an anechoic room is proposed. It takes into account the characteristics of interference signals and the positional relationship among interference, the receiver and the transmitter of the electronic communication system. It uses the grey relational method and the angular domain mapping error correction method to control the relevant parameters, the microwave switch and so on, thus achieving the approximately actual mapping of the outdoor multi-dimensional and complicated electromagnetic interference in the anechoic room. To verify the effectiveness of this method, the multi-dimensional and complicated electromagnetic interference of the UAV＇s data link is simulated as an example. The results show that the degree of correlation between the calculated signal to interference ratio of the data link receiver in the actual scene and the measured signal to interference ratio of the data link receiver simulated with this method in the anechoic room is 0.968 1, proving that the method is effective for simulating the complicated electromagnetic interference.

A strip thickness prediction method of hot rolling based on D_S information reconstruction

To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.

On the Flood Disasters in the Lower Jingjiang Reaches: Grey Prediction Model and Application

In the light of the historical substantial data (covering a 70-year period) collected in the Lower Jingjiang segment and aided by topological grey method, here we attempt to characterize the occurrence and future trend of flood calamities in the study area. Our findings indicate that overall the high-frequent flood disasters with middle to lower damage prevail at present. A series of dramatic flood waves will appear in the years of 2016, 2022, 2030 and 2042, particularly a destructive flood will occur between 2041 and 2045 in the Lower Jingjiang reaches. Typical of sensitive response to flood hazards in close association with its special geographical location, the lower Jingjiang segment hereby can reflect the development trend of floods in the middle Yangtze reaches. According to the results, a good fitness was revealed between the prediction and practical values. This actually hints that the topological grey method is an effective mathematical means of resolving problems containing uncertainty and indetermination, thus providing valuable information for the flood prediction in the middle Yangtze catchment.

Study on Corrosion Protection Method of Reinjection Water Treatment System in a Natural Gas Processing Plant

The research investigated the corrosion of the reinjection water system to ensure the safe production of the system.By analyzing the composition of the methanol-containing wastewater,the corrosion status of the injection water system was studied by the on-site materials 20#steel,Q235B steel and L316 steel for that the methanol-containing wastewater of a natural gas processing plant in northern Shaanxi had high acidity,Cl-and sulfide contents,salinity and corrosion.Then the grey system theory modeling software 3.0 was used to study the influence degree of various corrosion factors on the corrosion rate and depth of Q235B steel.The most important factors were determined,and countermeasures against corrosion were proposed.The results showed that L316 steel was more resistant to corrosion,and the corrosion rate was 0.0015 mm/a,which was less than the national standard(0.0760 mm/a).The maximum corrosion depth was 47.63μm,which was the lowest among the three materials.The corrosion rate and depth were the parent factors.Among the four factors of sulfide,Cl-,salinity and pH,grey relational degrees of sulfide were 0.75 and 0.80,respectively,which was the most important factor causing corrosion;using sulfur corrosion inhibitor protection method,TS-792C was selected by electrochemical method from three corrosion inhibitors.The impedance data simulation software ZSimpWin was used to simulate the equivalent circuit diagram,and the impedance of Q235B steel was the largest.The corrosion inhibition rate was up to 90.26%when corrosion rate was 0.0130 mm/a under the fitting of Tafel polarization curve,with the best anti-sulfur effect.At 80℃and a sulfide content of 300 mg/L,the corrosion rate of Q235B steel was less than 0.0760 mm/a.When the added amount was 100 mg/L,the corrosion current density and corrosion rate of the reinjection sewage was 0.462 mA/cm 2 and 0.0505 mm/a,both at the lowest values and with good temperature and sulfur resistance.