Abstract To investigate the influence of high temperatures on the bond performance of recycled concrete and steel bar, this article considers the influence of different concrete types (ordinary concrete and recycled concrete) and different temperatures (20, 100, 150, 200, 250, and 300°C) on the concrete compressive strength and the bond performance of concrete and steel bar. On this basis, the calculation formula of bond strength and bond slip between concrete and steel bar after the high temperature is established. The test results show that the concrete compressive strength presents a downward trend with the increase in temperature; the compressive strength loss of recycled concrete is higher than that of ordinary concrete; when the temperature reached 300°C, the compressive strength loss of ordinary concrete is 24.4%, while that of recycled concrete is 41.6%. The bond strength of pull-out specimens decreases with the increase of temperature, while the bond slip increases with the increase of temperature; the bond strength between recycled concrete and steel bar is lower than that between ordinary concrete and steel bar, while the bond slip between recycled concrete and steel bar is higher than that between ordinary concrete and steel bar. This article can provide a theoretical basis for the application of recycled concrete in high-temperature environment.
{"title":"Bond performance between recycled concrete and steel bar after high temperature","authors":"Qihao Wang, Ting Wang, Xiaoyu Zhou, Qunyu Chen","doi":"10.1515/nleng-2022-0284","DOIUrl":"https://doi.org/10.1515/nleng-2022-0284","url":null,"abstract":"Abstract To investigate the influence of high temperatures on the bond performance of recycled concrete and steel bar, this article considers the influence of different concrete types (ordinary concrete and recycled concrete) and different temperatures (20, 100, 150, 200, 250, and 300°C) on the concrete compressive strength and the bond performance of concrete and steel bar. On this basis, the calculation formula of bond strength and bond slip between concrete and steel bar after the high temperature is established. The test results show that the concrete compressive strength presents a downward trend with the increase in temperature; the compressive strength loss of recycled concrete is higher than that of ordinary concrete; when the temperature reached 300°C, the compressive strength loss of ordinary concrete is 24.4%, while that of recycled concrete is 41.6%. The bond strength of pull-out specimens decreases with the increase of temperature, while the bond slip increases with the increase of temperature; the bond strength between recycled concrete and steel bar is lower than that between ordinary concrete and steel bar, while the bond slip between recycled concrete and steel bar is higher than that between ordinary concrete and steel bar. This article can provide a theoretical basis for the application of recycled concrete in high-temperature environment.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"329 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80442374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This article addresses the challenge of large error rate and low accuracy of the vibration signal collection of mechanical equipment failure, and proposes a mechanical equipment failure vibration signal collection and analysis based on computer simulation detection. Then, it uses the Kalman filter algorithm for data filtering, according to the mathematical model established by the system, thus choosing a suitable noise covariance calculation method. In the integration process after filtering, using a piecewise integration method between acceleration peaks, the integration calculation is optimized to obtain the vibration displacement. The simulation results of this article show the vibration data collected by the main controller, after Kalman filtering and piecewise trapezoidal integration method optimization. The error of the proposed method is 0.5% when the frequency is 80 Hz, relative to the displacement measurement method of the three-axis acceleration sensor at 8.3%, and the error of data calculation results is greatly reduced. The greater the amplitude of vibration, the smaller the error. This method significantly improves the accuracy of vibration signal collection of mechanical equipment.
{"title":"Vibration signal collection and analysis of mechanical equipment failure based on computer simulation detection","authors":"Chiyue Qin, Rana Gill, Ravi Tomar, K. Ghafoor","doi":"10.1515/nleng-2022-0040","DOIUrl":"https://doi.org/10.1515/nleng-2022-0040","url":null,"abstract":"Abstract This article addresses the challenge of large error rate and low accuracy of the vibration signal collection of mechanical equipment failure, and proposes a mechanical equipment failure vibration signal collection and analysis based on computer simulation detection. Then, it uses the Kalman filter algorithm for data filtering, according to the mathematical model established by the system, thus choosing a suitable noise covariance calculation method. In the integration process after filtering, using a piecewise integration method between acceleration peaks, the integration calculation is optimized to obtain the vibration displacement. The simulation results of this article show the vibration data collected by the main controller, after Kalman filtering and piecewise trapezoidal integration method optimization. The error of the proposed method is 0.5% when the frequency is 80 Hz, relative to the displacement measurement method of the three-axis acceleration sensor at 8.3%, and the error of data calculation results is greatly reduced. The greater the amplitude of vibration, the smaller the error. This method significantly improves the accuracy of vibration signal collection of mechanical equipment.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"24 1","pages":"387 - 394"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72764221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Concrete is one of the most extensively utilized building materials that can be produced, and has the potential to release a significant quantity of CO2 into the environment. In this research, through studying lightweight (LW) concrete, attempts are made to produce environmentally friendly LW concrete with high strength using nanosilica rather than part of the cement and waste glass powder instead of aggregates. Recycled polypropylene fibers are used to increase the concrete’s compressive strength and nonlinear behavior. The use of glass powder was 20, 25, and 30% of the weight of aggregates, the consumption of nanosilica was 1, 2, and 3% of the weight of cement, and the consumption of recycled fibers (FORTA Ferro-Green) was 0.5, 1, and 1.5% of the weight of cement. Leca is also utilized as a LW aggregate. According to 7- and 28-day experimentation results and field emission scanning electron microscope analysis, the best sample had 1.5% fiber, 3% nanosilica, and 25% waste glass powder, and had a compressive and tensile strengths of roughly 1.7 and 1.6 times, respectively, those of the control specimen after 28 days. Also, using 3% nanosilica instead of cement can reduce greenhouse gas emissions by about 3%.
{"title":"Improving nonlinear behavior and tensile and compressive strengths of sustainable lightweight concrete using waste glass powder, nanosilica, and recycled polypropylene fiber","authors":"Erfan Najaf, Maedeh Orouji, S. M. Zahrai","doi":"10.1515/nleng-2022-0008","DOIUrl":"https://doi.org/10.1515/nleng-2022-0008","url":null,"abstract":"Abstract Concrete is one of the most extensively utilized building materials that can be produced, and has the potential to release a significant quantity of CO2 into the environment. In this research, through studying lightweight (LW) concrete, attempts are made to produce environmentally friendly LW concrete with high strength using nanosilica rather than part of the cement and waste glass powder instead of aggregates. Recycled polypropylene fibers are used to increase the concrete’s compressive strength and nonlinear behavior. The use of glass powder was 20, 25, and 30% of the weight of aggregates, the consumption of nanosilica was 1, 2, and 3% of the weight of cement, and the consumption of recycled fibers (FORTA Ferro-Green) was 0.5, 1, and 1.5% of the weight of cement. Leca is also utilized as a LW aggregate. According to 7- and 28-day experimentation results and field emission scanning electron microscope analysis, the best sample had 1.5% fiber, 3% nanosilica, and 25% waste glass powder, and had a compressive and tensile strengths of roughly 1.7 and 1.6 times, respectively, those of the control specimen after 28 days. Also, using 3% nanosilica instead of cement can reduce greenhouse gas emissions by about 3%.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"20 1","pages":"58 - 70"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85084843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In the present study, nonlinear dynamic process data are mapped into the kernel state space by kernel gauge variable analysis method to obtain decorrelated state data. The time-lapse covariance matrix of the state data is weighted and summed to obtain the time-lapse structure matrix of the state data, and then supervised kernel independent component analysis (SKICA) is established, the independent component feature data is extracted from the status data and the monitoring statistics are constructed to detect the process faults. The data show that kernel independent component analysis (ICA) method (KICA) method can detect slow fault faster than the ICA method, except that the statistical detection ability of F3 and FS is reduced, and the KICA method can significantly improve the detection performance of other faults and statistics. By analyzing the detection results of SKICA method, it is obvious that in the detection process of all five kinds of slow faults, the fault detection capability of SKICA is better than that of ICA and KICA. The results of continuous stirred reactor simulation system show that, compared with the basic linear process, the slow fault detection has a good monitoring performance, it can detect the small deviation in the process sensitively and give alarm information to the slow fault in time, to improve the fault detection rate.
{"title":"Research on fault detection and identification methods of nonlinear dynamic process based on ICA","authors":"Chao Xie, Rui Zhang, J. Bhola","doi":"10.1515/nleng-2022-0003","DOIUrl":"https://doi.org/10.1515/nleng-2022-0003","url":null,"abstract":"Abstract In the present study, nonlinear dynamic process data are mapped into the kernel state space by kernel gauge variable analysis method to obtain decorrelated state data. The time-lapse covariance matrix of the state data is weighted and summed to obtain the time-lapse structure matrix of the state data, and then supervised kernel independent component analysis (SKICA) is established, the independent component feature data is extracted from the status data and the monitoring statistics are constructed to detect the process faults. The data show that kernel independent component analysis (ICA) method (KICA) method can detect slow fault faster than the ICA method, except that the statistical detection ability of F3 and FS is reduced, and the KICA method can significantly improve the detection performance of other faults and statistics. By analyzing the detection results of SKICA method, it is obvious that in the detection process of all five kinds of slow faults, the fault detection capability of SKICA is better than that of ICA and KICA. The results of continuous stirred reactor simulation system show that, compared with the basic linear process, the slow fault detection has a good monitoring performance, it can detect the small deviation in the process sensitively and give alarm information to the slow fault in time, to improve the fault detection rate.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"44 1","pages":"13 - 19"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83156257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In order to realize and design a software monitoring and early warning system for the Internet of Things (IoT), this paper establishes a “trinity” control platform integrating PLC, WINCC, and MATLAB based on nonlinear technology and realizes the proportion integration differentiation (PID) control based on the RBF neural network tuning on this platform. Based on the framework of the trinity control platform, the PID control system set by the radial basis function (RBF) neural network and the STEP7 virtual object programming of the control platform are designed and realized. The experimental data update cycle is 0.5 s to record 1,000 data item objects, U is the control quantity, which is associated with the U communication driver variable in WINCC, and the corresponding storage address in the PLC is MD200; Yout is the controlled quantity, which is related to the Yout communication driver variable in WINCC, and the corresponding storage address in the PLC is MD100; start is the control switch, associated with the start communication driver variable in WINCC, corresponding to the storage address in the PLC of M0.1; reset is the reset control switch, It is associated with the reset communication driver variable in WINCC, and corresponds to the storage address in the PLC as M0.0. KP, KI, KD, and TIME correspond to three real-time PID parameters and are the cycle time in MATLAB (used for the X-axis of trend graphing), and are the variables of the communication driver. The addresses in the PLC are MD20, MD24, MD28, and MD32. It shows that for these three software programs, the update cycle of the data in the respective storage areas must be consistent, the program control cycles in MATLAB and PLC need to be consistent, and the transmission of parameters must be correctly implemented in a control cycle according to the programming logic sequence, in order to realize the design of an IoT software monitoring and early warning system.
{"title":"Design and implementation of Internet-of-Things software monitoring and early warning system based on nonlinear technology","authors":"Haifeng Ma, A. Pljonkin, Pradeep Kumar Singh","doi":"10.1515/nleng-2022-0036","DOIUrl":"https://doi.org/10.1515/nleng-2022-0036","url":null,"abstract":"Abstract In order to realize and design a software monitoring and early warning system for the Internet of Things (IoT), this paper establishes a “trinity” control platform integrating PLC, WINCC, and MATLAB based on nonlinear technology and realizes the proportion integration differentiation (PID) control based on the RBF neural network tuning on this platform. Based on the framework of the trinity control platform, the PID control system set by the radial basis function (RBF) neural network and the STEP7 virtual object programming of the control platform are designed and realized. The experimental data update cycle is 0.5 s to record 1,000 data item objects, U is the control quantity, which is associated with the U communication driver variable in WINCC, and the corresponding storage address in the PLC is MD200; Yout is the controlled quantity, which is related to the Yout communication driver variable in WINCC, and the corresponding storage address in the PLC is MD100; start is the control switch, associated with the start communication driver variable in WINCC, corresponding to the storage address in the PLC of M0.1; reset is the reset control switch, It is associated with the reset communication driver variable in WINCC, and corresponds to the storage address in the PLC as M0.0. KP, KI, KD, and TIME correspond to three real-time PID parameters and are the cycle time in MATLAB (used for the X-axis of trend graphing), and are the variables of the communication driver. The addresses in the PLC are MD20, MD24, MD28, and MD32. It shows that for these three software programs, the update cycle of the data in the respective storage areas must be consistent, the program control cycles in MATLAB and PLC need to be consistent, and the transmission of parameters must be correctly implemented in a control cycle according to the programming logic sequence, in order to realize the design of an IoT software monitoring and early warning system.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"23 1","pages":"355 - 363"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84724546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maojie Zhou, A. Akbulut, M. Kaplan, Mohammed K. A. Kaabar, Xiaolu Yue
Abstract Various new exact solutions to ( 3 + 1 ) left(3+1) -dimensional Wazwaz–KdV equations are obtained in this work via two techniques: the modified Kudryashov procedure and modified simple equation method. The 3D plots, contour plots, and 2D plots of some obtained solutions are provided to describe the dynamic characteristics of the obtained solutions. Our employed techniques are very helpful in constructing new exact solutions to several nonlinear models encountered in ocean scientific phenomena arising in stratified flows, shallow water, plasma physics, and internal waves.
{"title":"A new computational investigation to the new exact solutions of (3 + 1)-dimensional WKdV equations via two novel procedures arising in shallow water magnetohydrodynamics","authors":"Maojie Zhou, A. Akbulut, M. Kaplan, Mohammed K. A. Kaabar, Xiaolu Yue","doi":"10.1515/nleng-2022-0041","DOIUrl":"https://doi.org/10.1515/nleng-2022-0041","url":null,"abstract":"Abstract Various new exact solutions to ( 3 + 1 ) left(3+1) -dimensional Wazwaz–KdV equations are obtained in this work via two techniques: the modified Kudryashov procedure and modified simple equation method. The 3D plots, contour plots, and 2D plots of some obtained solutions are provided to describe the dynamic characteristics of the obtained solutions. Our employed techniques are very helpful in constructing new exact solutions to several nonlinear models encountered in ocean scientific phenomena arising in stratified flows, shallow water, plasma physics, and internal waves.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"8 1","pages":"478 - 484"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75443073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In order to explore the influence of cold heading equipment based on polyvinylidene fluoride (PVDF) polymer sensing material on steel ball stamping, a new method was proposed to reflect the defects of cold heading forming of steel ball by load signal. PVDF piezoelectric film is used as the sensor design of force and support structure of steel ball cold heading electromechanical sensor model. PVDF piezoelectric thin film force sensor is used for the structural optimization and simulation. The structural parameters affecting the natural frequency are numerically analyzed by MATLAB software. The mapping relationship between the external load and the output load of the sensor is obtained by using ANSYS software, and the simulation curve of the natural frequency of the sensor is compared with the theoretical curve to verify the factors affecting the natural frequency. The results show that the nonlinear error of sensors refers to the measured curve and the maximum deviation between the fitting line and the percentage of full-scale output.
{"title":"On-line monitoring of steel ball stamping by mechatronics cold heading equipment based on PVDF polymer sensing material","authors":"Xing Wang, Mingming Wu, Jianglong Wang","doi":"10.1515/nleng-2022-0014","DOIUrl":"https://doi.org/10.1515/nleng-2022-0014","url":null,"abstract":"Abstract In order to explore the influence of cold heading equipment based on polyvinylidene fluoride (PVDF) polymer sensing material on steel ball stamping, a new method was proposed to reflect the defects of cold heading forming of steel ball by load signal. PVDF piezoelectric film is used as the sensor design of force and support structure of steel ball cold heading electromechanical sensor model. PVDF piezoelectric thin film force sensor is used for the structural optimization and simulation. The structural parameters affecting the natural frequency are numerically analyzed by MATLAB software. The mapping relationship between the external load and the output load of the sensor is obtained by using ANSYS software, and the simulation curve of the natural frequency of the sensor is compared with the theoretical curve to verify the factors affecting the natural frequency. The results show that the nonlinear error of sensors refers to the measured curve and the maximum deviation between the fitting line and the percentage of full-scale output.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"8 1","pages":"168 - 174"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84228675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The strength of soil can significantly increase by stabilisation with binders. Adding binders in correct proportions to improve soil parameters is of paramount importance for earthworks. In this article, we presented a framework to explore strength characteristics of soil stabilised by several binders and evaluated using applied geophysical methods by estimated P-wave velocities. The core of our work is a systematic assessment of the effects on clay stabilisation from various binders on shear and compressive strength. The binders were combined from four stabilising agents: (i) CEM II/A, a Portland limestone cement; (ii) burnt lime; (iii) lime kiln dust (LKD) limited up to 50%; and (iv) cement kiln dust (CKD). Shear strength has shown a nonlinear dependence as an exponential curve with P-waves. Natural frequency analysis was modelled to simulate resonant frequencies as eigen values. Variations in strength proved that CEM II/A-M (Recipe A, 100% CEM II) has the best performance for weak soil stabilisation followed by the combinations: Recipe B (70% CEM II/A-M, 30% LKD), Recipe C with added 80% CEM II/A-M and 20% CKD, and Recipe D (70% CEM II/A-M 30% CKD). Recipe B has shown high values with maximum uniaxial compressive strength (UCS) at 13.8 MPa. The Recipe C was less effective with the highest value of UCS as 8.8 MPa. The least strength was shown in Recipe D, where UCS has maximal values of 3.7 MPa. The specimens stabilised by Recipe B demonstrated the highest P-wave velocity at 2,350 m/s, while Recipe C and Recipe D showed the highest P-wave velocity at 1,900 and 1,550 m/s. All specimens shown a gain of UCS with sharply increased P-wave speed during the 3 days of curing. The study contributes to the development of methods of soil testing in civil engineering.
摘要粘结剂的稳定可以显著提高土的强度。在土方工程中，正确配比添加粘结剂以改善土壤参数是至关重要的。在本文中，我们提出了一个框架来探索由几种粘合剂稳定的土壤的强度特征，并通过估计的纵波速度使用应用地球物理方法进行评估。我们工作的核心是系统地评估各种粘合剂对粘土稳定的剪切和抗压强度的影响。粘合剂由四种稳定剂组合而成:(i) CEM II/A，一种波特兰石灰石水泥;(ii)烧石灰;(iii)石灰窑粉尘(LKD)上限为50%;(四)水泥窑粉尘。抗剪强度与p波呈指数曲线的非线性关系。对固有频率分析进行建模，模拟谐振频率作为本征值。强度的变化证明，CEM II/A- m(配方A, 100% CEM II)对弱土的稳定效果最好，其次是配方B (70% CEM II/A- m, 30% LKD)、配方C (80% CEM II/A- m, 20% CKD)和配方D (70% CEM II/A- m, 30% CKD)。配方B显示出较高的值，最大单轴抗压强度(UCS)为13.8 MPa。配方C效果较差，UCS最大值为8.8 MPa。配方D的强度最小，UCS最大值为3.7 MPa。配方B稳定试样的最高纵波速度为2350 m/s，配方C和配方D的最高纵波速度分别为1900和1550 m/s。在3天的养护过程中，所有试件的单抗强度均有所增加，纵波速度急剧增加。该研究对土木工程中土测试方法的发展具有重要意义。
{"title":"Shear bond and compressive strength of clay stabilised with lime/cement jet grouting and deep mixing: A case of Norvik, Nynäshamn","authors":"P. Lindh, Polina Lemenkova","doi":"10.1515/nleng-2022-0269","DOIUrl":"https://doi.org/10.1515/nleng-2022-0269","url":null,"abstract":"Abstract The strength of soil can significantly increase by stabilisation with binders. Adding binders in correct proportions to improve soil parameters is of paramount importance for earthworks. In this article, we presented a framework to explore strength characteristics of soil stabilised by several binders and evaluated using applied geophysical methods by estimated P-wave velocities. The core of our work is a systematic assessment of the effects on clay stabilisation from various binders on shear and compressive strength. The binders were combined from four stabilising agents: (i) CEM II/A, a Portland limestone cement; (ii) burnt lime; (iii) lime kiln dust (LKD) limited up to 50%; and (iv) cement kiln dust (CKD). Shear strength has shown a nonlinear dependence as an exponential curve with P-waves. Natural frequency analysis was modelled to simulate resonant frequencies as eigen values. Variations in strength proved that CEM II/A-M (Recipe A, 100% CEM II) has the best performance for weak soil stabilisation followed by the combinations: Recipe B (70% CEM II/A-M, 30% LKD), Recipe C with added 80% CEM II/A-M and 20% CKD, and Recipe D (70% CEM II/A-M 30% CKD). Recipe B has shown high values with maximum uniaxial compressive strength (UCS) at 13.8 MPa. The Recipe C was less effective with the highest value of UCS as 8.8 MPa. The least strength was shown in Recipe D, where UCS has maximal values of 3.7 MPa. The specimens stabilised by Recipe B demonstrated the highest P-wave velocity at 2,350 m/s, while Recipe C and Recipe D showed the highest P-wave velocity at 1,900 and 1,550 m/s. All specimens shown a gain of UCS with sharply increased P-wave speed during the 3 days of curing. The study contributes to the development of methods of soil testing in civil engineering.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"44 1","pages":"693 - 710"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84028362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Geometrically nonlinear analysis is required for resolving issues such as loading causes failure and structure buckling analysis. Although numerical methods are recommended for estimating the exact solution, they lack the necessary convergence in the presence of bifurcation points, making it challenging to find the equilibrium path using these methods. Thus, the modified energy method is employed instead of the numerical method, frequently used to solve quasi-static problems with nonlinear nature and bifurcation points. The ultimate goal of this study is to determine the critical load of structures through the modified energy method rather than other methods in which the relationship between force, displacement, and constraint is used to solve the problem. This study first describes the energy method for this type of problem and then details its computational steps progressively. This method yields numerical results when applied to numerical examples such as truss and frame structures and coded in MATLAB software. These findings are compared to the analytical results. The energy method is more precise than the alternative methods and superior to the Newton–Raphson method at crossing the load–displacement curve’s bifurcation points.
{"title":"Investigation of critical load of structures using modified energy method in nonlinear-geometry solid mechanics problems","authors":"Ahmad Razaghi, J. A. Marnani, M. S. Rohanimanesh","doi":"10.1515/nleng-2022-0018","DOIUrl":"https://doi.org/10.1515/nleng-2022-0018","url":null,"abstract":"Abstract Geometrically nonlinear analysis is required for resolving issues such as loading causes failure and structure buckling analysis. Although numerical methods are recommended for estimating the exact solution, they lack the necessary convergence in the presence of bifurcation points, making it challenging to find the equilibrium path using these methods. Thus, the modified energy method is employed instead of the numerical method, frequently used to solve quasi-static problems with nonlinear nature and bifurcation points. The ultimate goal of this study is to determine the critical load of structures through the modified energy method rather than other methods in which the relationship between force, displacement, and constraint is used to solve the problem. This study first describes the energy method for this type of problem and then details its computational steps progressively. This method yields numerical results when applied to numerical examples such as truss and frame structures and coded in MATLAB software. These findings are compared to the analytical results. The energy method is more precise than the alternative methods and superior to the Newton–Raphson method at crossing the load–displacement curve’s bifurcation points.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"5 1","pages":"637 - 653"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78983379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zheng Sun, Xina Li, Hongtao Zhang, M. Ikbal, A. R. Farooqi
Abstract Neural network modeling for nonlinear time series predicts modeling speed and computational complexity. An improved method for dynamic modeling and prediction of neural networks is proposed. Simulations of the nonlinear time series are performed, and the idea and theory of optimizing the initial weights and threshold of the GA algorithm are discussed in detail. It has been proved that the use of GA-BP neural network in cigarette sales forecast is 80% higher than before, and this method has higher accuracy and accuracy than the gray system method.
{"title":"A GA-BP neural network for nonlinear time-series forecasting and its application in cigarette sales forecast","authors":"Zheng Sun, Xina Li, Hongtao Zhang, M. Ikbal, A. R. Farooqi","doi":"10.1515/nleng-2022-0025","DOIUrl":"https://doi.org/10.1515/nleng-2022-0025","url":null,"abstract":"Abstract Neural network modeling for nonlinear time series predicts modeling speed and computational complexity. An improved method for dynamic modeling and prediction of neural networks is proposed. Simulations of the nonlinear time series are performed, and the idea and theory of optimizing the initial weights and threshold of the GA algorithm are discussed in detail. It has been proved that the use of GA-BP neural network in cigarette sales forecast is 80% higher than before, and this method has higher accuracy and accuracy than the gray system method.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":"8 1","pages":"223 - 231"},"PeriodicalIF":8.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89179158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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