Paulina Zajdel - Academia.edu (original) (raw)
Papers by Paulina Zajdel
Inżynieria i Budownictwo, Dec 15, 2023
ce/papers
The results of post‐fire brittle cracking susceptibility tests conducted on samples made of selec... more The results of post‐fire brittle cracking susceptibility tests conducted on samples made of selected duplex type stainless steel grades exhibiting austenitic‐ferritic structure, in particular on standard duplex X2CrNiMoN22‐5‐3 steel and on lean duplex X2CrMnNiN21‐5‐1 steel, are presented and widely discussed. General conclusions are based on the force‐displacement graphs obtained by the instrumented Charpy impact test. Prior to the test all samples have been subjected to simulated fire action following the steady‐state heating regime and then cooled down to room temperature. Two heating levels have been considered, namely 600°C and 800°C. The first of these levels has been considered as to low, while the second as sufficiently high, to induce in the considered steel structural changes of permanent character. For comparison, two groups of samples have been tested. Samples belonging to the first group have been heated for one hour (simulation of a short fire), while the ones belonging...
Materials, Jul 14, 2021
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Materials
The results of experimental research on forecasting post-fire resistance to brittle failure of se... more The results of experimental research on forecasting post-fire resistance to brittle failure of selected steel grades used in construction are presented and discussed in this paper. The conclusions are based on detailed analysis of fracture surfaces obtained in instrumented Charpy tests. It has been shown that the relationships formulated based on these tests agree well with conclusions drawn based on precise analysis of appropriate F–s curves. Furthermore, other relationships between lateral expansion LE and energy Wt required to break the sample constitute an additional verification in both qualitative and quantitative terms. These relationships are accompanied here by values of the SFA(n) parameter, which are different, depending on the character of the fracture. Steel grades differing in microstructure have been selected for the detailed analysis, including: S355J2+N—representative for materials of ferritic-pearlitic structure, and also stainless steels such as X20Cr13—of martens...
Case Studies in Construction Materials
Materials
The change in the value of the breaking energy is discussed here for selected steel grades used i... more The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600 °C (first series) and 800 °C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action and cooling in water mist simulating an extinguishing action by a fire brigade. The temperature of the tes...
Materials
The article presents changes in the microstructure of hot-rolled unalloyed structural steel after... more The article presents changes in the microstructure of hot-rolled unalloyed structural steel after the arc welding process and in the state after long-term exposure to 600 °C during operation. These studies enable a clear assessment of the effects of long-term exposure to elevated temperature relative to the as-welded condition, which has not been reported. The microstructure examination was carried out on welded joints in eight different zones of the joint. Studies have shown that the welding thermal cycle causes significant changes in the microstructure in the area of the base material heated above the A1 temperature—the heat-affected zone (HAZ)—and in the weld area in the case of multi-pass welding. The long-term exposure of the subcritical temperature of 600 °C on the welded joint leads to the phenomenon of cementite spheroidization in the pearlite in all zones of the joint, while preserving the band structure of the steel after rolling and the structural structure. In the case o...
Materials
In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl al... more In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl alcohol) (PVOH) were prepared using the electrospinning technique. Based on the Taguchi DOE (design of experiment) method, the effects of electrospinning parameters, i.e., needle tip to collector distance, polymer solution concentration, applied voltage, polymer solution feed rate and polymer type, on the diameter and morphology of polymer nanofibers were evaluated. Analyses of the experiments for the diameters of the polymer nanofibers showed that the type of polymer was the most significant factor. The optimal combination to obtain the smallest diameters with minimum deviations for electrospun polymer nanofibers was also determined. For this purpose, the appropriate factor levels were determined as follows: polymer PAAm, applied voltage 10 kV, delivery rate 0.1 mL/h, needle tip to collector distance 10 cm, and polymer solution concentration 8%, to obtain the thinnest nanofibers. This com...
Technical Transactions, 2021
In this article, changes occurring in structural steel after exposure to fire are described and d... more In this article, changes occurring in structural steel after exposure to fire are described and discussed. The steel structure before and after fire determines its susceptibility to brittle cracking. The individual phases of cracking are described and interpreted on the basis of a load-displacement graph, directly obtained from the Charpy impact test. The relationship between the intensity of individual fracture energies and the type and appearance of the sample fractures are demonstrated. The program of planned Charpy impact tests and expected hazards after the exposure to fire of selected steel grades are presented. Standard simplified load-displacement graphs are assigned to the steel transition curve. The course of various cracking mechanisms occurring in the case of brittle fractures and plastic fractures are discussed. The aim of this article is to evaluate the possibility of the assessment of structural steel after a fire based on results obtained during the Charpy impact test.
Materials, 2022
In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tr... more In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tree), Random Forest (RF), and Support Vector Regression (SVR) techniques have been evaluated and compared with the multiple linear regression-based model (MLR) to be used for prediction of the compressive strength of bacterial concrete. For this purpose, 128 experimental observations have been collected. The total data set has been divided into two segments such as training (87 observations) and testing (41 observations). The process of data set separation was arbitrary. Cement, Aggregate, Sand, Water to Cement Ratio, Curing time, Percentage of Bacteria, and type of sand were the input variables, whereas the compressive strength of bacterial concrete has been considered as the final target. Seven performance evaluation indices such as Correlation Coefficient (CC), Coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Bias, Nash-Sutcliffe Efficiency (...
Materials, 2021
The casting and testing specimens for determining the mechanical properties of concrete is a time... more The casting and testing specimens for determining the mechanical properties of concrete is a time-consuming activity. This study employed supervised machine learning techniques, bagging, AdaBoost, gene expression programming, and decision tree to estimate the compressive strength of concrete containing supplementary cementitious materials (fly ash and blast furnace slag). The performance of the models was compared and assessed using the coefficient of determination (R2), mean absolute error, mean square error, and root mean square error. The performance of the model was further validated using the k-fold cross-validation approach. Compared to the other employed approaches, the bagging model was more effective in predicting results, with an R2 value of 0.92. A sensitivity analysis was also prepared to determine the level of contribution of each parameter utilized to run the models. The use of machine learning (ML) techniques to predict the mechanical properties of concrete will be be...
Polymers, 2021
The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environme... more The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R2 equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. ...
Case Studies in Construction Materials, 2021
Inżynieria i Budownictwo, Dec 15, 2023
ce/papers
The results of post‐fire brittle cracking susceptibility tests conducted on samples made of selec... more The results of post‐fire brittle cracking susceptibility tests conducted on samples made of selected duplex type stainless steel grades exhibiting austenitic‐ferritic structure, in particular on standard duplex X2CrNiMoN22‐5‐3 steel and on lean duplex X2CrMnNiN21‐5‐1 steel, are presented and widely discussed. General conclusions are based on the force‐displacement graphs obtained by the instrumented Charpy impact test. Prior to the test all samples have been subjected to simulated fire action following the steady‐state heating regime and then cooled down to room temperature. Two heating levels have been considered, namely 600°C and 800°C. The first of these levels has been considered as to low, while the second as sufficiently high, to induce in the considered steel structural changes of permanent character. For comparison, two groups of samples have been tested. Samples belonging to the first group have been heated for one hour (simulation of a short fire), while the ones belonging...
Materials, Jul 14, 2021
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Materials
The results of experimental research on forecasting post-fire resistance to brittle failure of se... more The results of experimental research on forecasting post-fire resistance to brittle failure of selected steel grades used in construction are presented and discussed in this paper. The conclusions are based on detailed analysis of fracture surfaces obtained in instrumented Charpy tests. It has been shown that the relationships formulated based on these tests agree well with conclusions drawn based on precise analysis of appropriate F–s curves. Furthermore, other relationships between lateral expansion LE and energy Wt required to break the sample constitute an additional verification in both qualitative and quantitative terms. These relationships are accompanied here by values of the SFA(n) parameter, which are different, depending on the character of the fracture. Steel grades differing in microstructure have been selected for the detailed analysis, including: S355J2+N—representative for materials of ferritic-pearlitic structure, and also stainless steels such as X20Cr13—of martens...
Case Studies in Construction Materials
Materials
The change in the value of the breaking energy is discussed here for selected steel grades used i... more The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600 °C (first series) and 800 °C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action and cooling in water mist simulating an extinguishing action by a fire brigade. The temperature of the tes...
Materials
The article presents changes in the microstructure of hot-rolled unalloyed structural steel after... more The article presents changes in the microstructure of hot-rolled unalloyed structural steel after the arc welding process and in the state after long-term exposure to 600 °C during operation. These studies enable a clear assessment of the effects of long-term exposure to elevated temperature relative to the as-welded condition, which has not been reported. The microstructure examination was carried out on welded joints in eight different zones of the joint. Studies have shown that the welding thermal cycle causes significant changes in the microstructure in the area of the base material heated above the A1 temperature—the heat-affected zone (HAZ)—and in the weld area in the case of multi-pass welding. The long-term exposure of the subcritical temperature of 600 °C on the welded joint leads to the phenomenon of cementite spheroidization in the pearlite in all zones of the joint, while preserving the band structure of the steel after rolling and the structural structure. In the case o...
Materials
In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl al... more In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl alcohol) (PVOH) were prepared using the electrospinning technique. Based on the Taguchi DOE (design of experiment) method, the effects of electrospinning parameters, i.e., needle tip to collector distance, polymer solution concentration, applied voltage, polymer solution feed rate and polymer type, on the diameter and morphology of polymer nanofibers were evaluated. Analyses of the experiments for the diameters of the polymer nanofibers showed that the type of polymer was the most significant factor. The optimal combination to obtain the smallest diameters with minimum deviations for electrospun polymer nanofibers was also determined. For this purpose, the appropriate factor levels were determined as follows: polymer PAAm, applied voltage 10 kV, delivery rate 0.1 mL/h, needle tip to collector distance 10 cm, and polymer solution concentration 8%, to obtain the thinnest nanofibers. This com...
Technical Transactions, 2021
In this article, changes occurring in structural steel after exposure to fire are described and d... more In this article, changes occurring in structural steel after exposure to fire are described and discussed. The steel structure before and after fire determines its susceptibility to brittle cracking. The individual phases of cracking are described and interpreted on the basis of a load-displacement graph, directly obtained from the Charpy impact test. The relationship between the intensity of individual fracture energies and the type and appearance of the sample fractures are demonstrated. The program of planned Charpy impact tests and expected hazards after the exposure to fire of selected steel grades are presented. Standard simplified load-displacement graphs are assigned to the steel transition curve. The course of various cracking mechanisms occurring in the case of brittle fractures and plastic fractures are discussed. The aim of this article is to evaluate the possibility of the assessment of structural steel after a fire based on results obtained during the Charpy impact test.
Materials, 2022
In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tr... more In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tree), Random Forest (RF), and Support Vector Regression (SVR) techniques have been evaluated and compared with the multiple linear regression-based model (MLR) to be used for prediction of the compressive strength of bacterial concrete. For this purpose, 128 experimental observations have been collected. The total data set has been divided into two segments such as training (87 observations) and testing (41 observations). The process of data set separation was arbitrary. Cement, Aggregate, Sand, Water to Cement Ratio, Curing time, Percentage of Bacteria, and type of sand were the input variables, whereas the compressive strength of bacterial concrete has been considered as the final target. Seven performance evaluation indices such as Correlation Coefficient (CC), Coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Bias, Nash-Sutcliffe Efficiency (...
Materials, 2021
The casting and testing specimens for determining the mechanical properties of concrete is a time... more The casting and testing specimens for determining the mechanical properties of concrete is a time-consuming activity. This study employed supervised machine learning techniques, bagging, AdaBoost, gene expression programming, and decision tree to estimate the compressive strength of concrete containing supplementary cementitious materials (fly ash and blast furnace slag). The performance of the models was compared and assessed using the coefficient of determination (R2), mean absolute error, mean square error, and root mean square error. The performance of the model was further validated using the k-fold cross-validation approach. Compared to the other employed approaches, the bagging model was more effective in predicting results, with an R2 value of 0.92. A sensitivity analysis was also prepared to determine the level of contribution of each parameter utilized to run the models. The use of machine learning (ML) techniques to predict the mechanical properties of concrete will be be...
Polymers, 2021
The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environme... more The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R2 equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. ...
Case Studies in Construction Materials, 2021