Osmotic dehydration of food - energy and ecological aspects of sustainable production

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Osmotic dehydration of food - energy and ecological aspects of sustainable production (en)
Осмотска дехидратација хране - енергетски и еколошки аспекти одрживе производње (sr)
Osmotska dehidratacija hrane - energetski i ekološki aspekti održive proizvodnje (sr_RS)
Authors

Publications

Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling

Terzić, Anja; Pezo, Lato; Andrić, Ljubiša; Pavlović, Vladimir B.; Mitić, Vojislav V.

(Elsevier, 2017)

TY  - JOUR
AU  - Terzić, Anja
AU  - Pezo, Lato
AU  - Andrić, Ljubiša
AU  - Pavlović, Vladimir B.
AU  - Mitić, Vojislav V.
PY  - 2017
UR  - https://dais.sanu.ac.rs/123456789/2350
AB  - The properties of seven montmorillonite-rich bentonites of different geological origin were investigated prior and subsequent to mechano-chemical processing in an ultra-centrifugal mill. The objective of the experiment was altering the bentonite types and activation parameters in order to determine the optimal milling conditions that produce material which is physico-mechanically and microstructurally applicable as a binder replacement and sorbent in the construction composites. The efficiency of bentonite activation was assessed by chemometrics and Artificial neural networks mathematical modeling. Principal component analysis and analysis of variance were used in the observation of the influence of input variables (bentonite chemical composition) and process parameters (milling duration, rotor velocity) on the product characteristics: density, specific surface area, grain size and distribution, cation exchange capacity, melting point, compressive strength, shrinkage and porosity. When the ANN models for the observed responses, related to predicted bentonite characteristics and quality, were compared to experimental results, they correctly predicted the responses. The processed data also adequately fitted to the regression second order polynomial models. The SOP models, which showed r2 values from 0.357 to 0.948, and were able to predict the observed responses in a wide range of processing parameters, while ANN models performed high prediction accuracy (0.776–0.901) and can be considered as precise for response variables prediction. The combination of the conducted mathematical analyses showed that that increase/decrease in output values was stabilized after 30 min of activation. Mathematically attained interpretations were correlated with the results of the instrumental analyses (XRD, DTA/TG, SEM) to confirm the adoption of B6 bentonite as a preferable type and 30 min as an optimal milling time for acquiring quality of clay powder that will be used in structural and thermal applications.
PB  - Elsevier
T2  - Ceramics International
T1  - Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling
SP  - 2549
EP  - 2562
VL  - 43
IS  - 2
DO  - 10.1016/j.ceramint.2016.11.058
UR  - https://hdl.handle.net/21.15107/rcub_dais_2350
ER  - 
@article{
author = "Terzić, Anja and Pezo, Lato and Andrić, Ljubiša and Pavlović, Vladimir B. and Mitić, Vojislav V.",
year = "2017",
abstract = "The properties of seven montmorillonite-rich bentonites of different geological origin were investigated prior and subsequent to mechano-chemical processing in an ultra-centrifugal mill. The objective of the experiment was altering the bentonite types and activation parameters in order to determine the optimal milling conditions that produce material which is physico-mechanically and microstructurally applicable as a binder replacement and sorbent in the construction composites. The efficiency of bentonite activation was assessed by chemometrics and Artificial neural networks mathematical modeling. Principal component analysis and analysis of variance were used in the observation of the influence of input variables (bentonite chemical composition) and process parameters (milling duration, rotor velocity) on the product characteristics: density, specific surface area, grain size and distribution, cation exchange capacity, melting point, compressive strength, shrinkage and porosity. When the ANN models for the observed responses, related to predicted bentonite characteristics and quality, were compared to experimental results, they correctly predicted the responses. The processed data also adequately fitted to the regression second order polynomial models. The SOP models, which showed r2 values from 0.357 to 0.948, and were able to predict the observed responses in a wide range of processing parameters, while ANN models performed high prediction accuracy (0.776–0.901) and can be considered as precise for response variables prediction. The combination of the conducted mathematical analyses showed that that increase/decrease in output values was stabilized after 30 min of activation. Mathematically attained interpretations were correlated with the results of the instrumental analyses (XRD, DTA/TG, SEM) to confirm the adoption of B6 bentonite as a preferable type and 30 min as an optimal milling time for acquiring quality of clay powder that will be used in structural and thermal applications.",
publisher = "Elsevier",
journal = "Ceramics International",
title = "Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling",
pages = "2549-2562",
volume = "43",
number = "2",
doi = "10.1016/j.ceramint.2016.11.058",
url = "https://hdl.handle.net/21.15107/rcub_dais_2350"
}
Terzić, A., Pezo, L., Andrić, L., Pavlović, V. B.,& Mitić, V. V.. (2017). Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling. in Ceramics International
Elsevier., 43(2), 2549-2562.
https://doi.org/10.1016/j.ceramint.2016.11.058
https://hdl.handle.net/21.15107/rcub_dais_2350
Terzić A, Pezo L, Andrić L, Pavlović VB, Mitić VV. Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling. in Ceramics International. 2017;43(2):2549-2562.
doi:10.1016/j.ceramint.2016.11.058
https://hdl.handle.net/21.15107/rcub_dais_2350 .
Terzić, Anja, Pezo, Lato, Andrić, Ljubiša, Pavlović, Vladimir B., Mitić, Vojislav V., "Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling" in Ceramics International, 43, no. 2 (2017):2549-2562,
https://doi.org/10.1016/j.ceramint.2016.11.058 .,
https://hdl.handle.net/21.15107/rcub_dais_2350 .
15
8
17

Artificial fly ash based aggregates properties influence on lightweight concrete performances

Terzić, Anja; Pezo, Lato; Mitić, Vojislav V.; Radojević, Zagorka

(Elsevier, 2015)

TY  - JOUR
AU  - Terzić, Anja
AU  - Pezo, Lato
AU  - Mitić, Vojislav V.
AU  - Radojević, Zagorka
PY  - 2015
UR  - https://dais.sanu.ac.rs/123456789/3536
AB  - The effect of the application of pelletized fly ash based aggregates obtained through different processing techniques on the behavior of lightweight concretes was analyzed. Experimental program implied production of four lightweight artificial aggregates - cold bonded and sintered pellets based on either mechanically activated or non-activated low-calcium fly ash and water glass. The lightweight concrete behavior was compared to that of normal-weight concrete through compressive strength, flexural strength, porosity, shrinkage, and modulus of elasticity investigation. Differences in concretes characteristics were discussed with SEM imagining support. The statistical analysis of lightweight aggregate and ash properties contribution on concrete performances was realized by analysis variance model (ANOVA). Optimal production combination that maximizes lightweight concrete performance was determined by employing response surface methodology. An increase in concrete strength induced by the increase in ash fineness was noticed. Mechanical activation also had effect on the pellets sintering period and sintering temperature reduction. The 28- and 56-day lightweight concrete specimens exhibited properties that met the requirements for normal-weight concretes. Finally, the ideal combinations of ash pellets production parameters and properties that gave the lightweight concrete with behavior matching to that of standard concrete were established. The production capability of lightweight concrete with advanced performances based on artificial aggregate approves the principle of waste material reusing and enables cleaner and economically sustainable concrete manufacturing procedure. © 2014 Elsevier Ltd and Techna Group S.r.l. All rights reserved.
PB  - Elsevier
T2  - Ceramics International
T1  - Artificial fly ash based aggregates properties influence on lightweight concrete performances
SP  - 2714
EP  - 2726
VL  - 41
IS  - 2
DO  - 10.1016/j.ceramint.2014.10.086
UR  - https://hdl.handle.net/21.15107/rcub_dais_3536
ER  - 
@article{
author = "Terzić, Anja and Pezo, Lato and Mitić, Vojislav V. and Radojević, Zagorka",
year = "2015",
abstract = "The effect of the application of pelletized fly ash based aggregates obtained through different processing techniques on the behavior of lightweight concretes was analyzed. Experimental program implied production of four lightweight artificial aggregates - cold bonded and sintered pellets based on either mechanically activated or non-activated low-calcium fly ash and water glass. The lightweight concrete behavior was compared to that of normal-weight concrete through compressive strength, flexural strength, porosity, shrinkage, and modulus of elasticity investigation. Differences in concretes characteristics were discussed with SEM imagining support. The statistical analysis of lightweight aggregate and ash properties contribution on concrete performances was realized by analysis variance model (ANOVA). Optimal production combination that maximizes lightweight concrete performance was determined by employing response surface methodology. An increase in concrete strength induced by the increase in ash fineness was noticed. Mechanical activation also had effect on the pellets sintering period and sintering temperature reduction. The 28- and 56-day lightweight concrete specimens exhibited properties that met the requirements for normal-weight concretes. Finally, the ideal combinations of ash pellets production parameters and properties that gave the lightweight concrete with behavior matching to that of standard concrete were established. The production capability of lightweight concrete with advanced performances based on artificial aggregate approves the principle of waste material reusing and enables cleaner and economically sustainable concrete manufacturing procedure. © 2014 Elsevier Ltd and Techna Group S.r.l. All rights reserved.",
publisher = "Elsevier",
journal = "Ceramics International",
title = "Artificial fly ash based aggregates properties influence on lightweight concrete performances",
pages = "2714-2726",
volume = "41",
number = "2",
doi = "10.1016/j.ceramint.2014.10.086",
url = "https://hdl.handle.net/21.15107/rcub_dais_3536"
}
Terzić, A., Pezo, L., Mitić, V. V.,& Radojević, Z.. (2015). Artificial fly ash based aggregates properties influence on lightweight concrete performances. in Ceramics International
Elsevier., 41(2), 2714-2726.
https://doi.org/10.1016/j.ceramint.2014.10.086
https://hdl.handle.net/21.15107/rcub_dais_3536
Terzić A, Pezo L, Mitić VV, Radojević Z. Artificial fly ash based aggregates properties influence on lightweight concrete performances. in Ceramics International. 2015;41(2):2714-2726.
doi:10.1016/j.ceramint.2014.10.086
https://hdl.handle.net/21.15107/rcub_dais_3536 .
Terzić, Anja, Pezo, Lato, Mitić, Vojislav V., Radojević, Zagorka, "Artificial fly ash based aggregates properties influence on lightweight concrete performances" in Ceramics International, 41, no. 2 (2015):2714-2726,
https://doi.org/10.1016/j.ceramint.2014.10.086 .,
https://hdl.handle.net/21.15107/rcub_dais_3536 .
62
31
64

Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis

Terzić, Anja; Pezo, Lato; Andrić, Ljubiša; Mitić, Vojislav

(Elsevier, 2015)

TY  - JOUR
AU  - Terzić, Anja
AU  - Pezo, Lato
AU  - Andrić, Ljubiša
AU  - Mitić, Vojislav
PY  - 2015
UR  - https://dais.sanu.ac.rs/123456789/3525
AB  - The impact of the mechanical processing parameters on the alumina grain-size distribution affiliated characteristics and on the γ to α phase transformation rate was investigated. The moderation in the alumina samples behavior has been correlated to the granulometric and mineralogical changes induced by activation via an ultra-centrifugal mill. The assessment of the activation process variables influence on the final quality of the product parameters was conveyed in order to optimize the mechanical treatment of the alumina, which otherwise could be regarded as either energetically or economically unsustainable procedure. The Response Surface Method, Standard Score Analysis and Principal Component Analysis were applied as means of the mechanical activation optimization. The r 2 values obtained by developed models were in range from 0.816 to 0.988. The established mathematical models were able to precisely predict the quality parameters in a broad range of processing parameters. The Standard Score Analysis emphasized that the optimal output sample was obtained using a sieve mesh of 120μm set of processing parameters (SS=0.96). Diverse comparison analyses disclosed that the optimal set of activation process parameters could reduce the negative effect of γ-alumina samples immanent properties on the final score, and furthermore to enhance the rate of γ to α transition which would improve energetic and economic sustainability of the alumina phase transformation procedure. © 2015 Elsevier Ltd and Techna Group S.r.l.
PB  - Elsevier
T2  - Ceramics International
T1  - Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis
SP  - 11908
EP  - 11917
VL  - 41
IS  - 9, Part B
DO  - 10.1016/j.ceramint.2015.05.158
UR  - https://hdl.handle.net/21.15107/rcub_dais_3525
ER  - 
@article{
author = "Terzić, Anja and Pezo, Lato and Andrić, Ljubiša and Mitić, Vojislav",
year = "2015",
abstract = "The impact of the mechanical processing parameters on the alumina grain-size distribution affiliated characteristics and on the γ to α phase transformation rate was investigated. The moderation in the alumina samples behavior has been correlated to the granulometric and mineralogical changes induced by activation via an ultra-centrifugal mill. The assessment of the activation process variables influence on the final quality of the product parameters was conveyed in order to optimize the mechanical treatment of the alumina, which otherwise could be regarded as either energetically or economically unsustainable procedure. The Response Surface Method, Standard Score Analysis and Principal Component Analysis were applied as means of the mechanical activation optimization. The r 2 values obtained by developed models were in range from 0.816 to 0.988. The established mathematical models were able to precisely predict the quality parameters in a broad range of processing parameters. The Standard Score Analysis emphasized that the optimal output sample was obtained using a sieve mesh of 120μm set of processing parameters (SS=0.96). Diverse comparison analyses disclosed that the optimal set of activation process parameters could reduce the negative effect of γ-alumina samples immanent properties on the final score, and furthermore to enhance the rate of γ to α transition which would improve energetic and economic sustainability of the alumina phase transformation procedure. © 2015 Elsevier Ltd and Techna Group S.r.l.",
publisher = "Elsevier",
journal = "Ceramics International",
title = "Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis",
pages = "11908-11917",
volume = "41",
number = "9, Part B",
doi = "10.1016/j.ceramint.2015.05.158",
url = "https://hdl.handle.net/21.15107/rcub_dais_3525"
}
Terzić, A., Pezo, L., Andrić, L.,& Mitić, V.. (2015). Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis. in Ceramics International
Elsevier., 41(9, Part B), 11908-11917.
https://doi.org/10.1016/j.ceramint.2015.05.158
https://hdl.handle.net/21.15107/rcub_dais_3525
Terzić A, Pezo L, Andrić L, Mitić V. Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis. in Ceramics International. 2015;41(9, Part B):11908-11917.
doi:10.1016/j.ceramint.2015.05.158
https://hdl.handle.net/21.15107/rcub_dais_3525 .
Terzić, Anja, Pezo, Lato, Andrić, Ljubiša, Mitić, Vojislav, "Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis" in Ceramics International, 41, no. 9, Part B (2015):11908-11917,
https://doi.org/10.1016/j.ceramint.2015.05.158 .,
https://hdl.handle.net/21.15107/rcub_dais_3525 .
10
7
10

Prediction and Optimization of Heavy Clay Products Quality

Arsenović, Milica; Pezo, Lato; Mančić, Lidija; Radojević, Zagorka

(Wiley Blackwell, 2014)

TY  - CHAP
AU  - Arsenović, Milica
AU  - Pezo, Lato
AU  - Mančić, Lidija
AU  - Radojević, Zagorka
PY  - 2014
UR  - https://dais.sanu.ac.rs/123456789/15206
AB  - The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products parameters was evaluated by second order polynomial regression models (SOPs) and artificial neural networks (ANNs), and aft erwards compared to experimental results. SOPs showed high r2 values (0.897-0.913 for compressive strength models, 0.942-0.962 for water absorption, 0.928 for firing shrinkage, 0.988-0.991 for water loss during firing, and 0.941 for volume mass of cubes models). An ANN model, coupled with sensitivity analysis, was obtained with high prediction accuracy: 0.866-0.939 for compressive strength models, 0.954-0.974 for water absorption, 0.882 for firing shrinkage, 0.982-0.988 for water loss during firing, and 0.920 for volume mass of cubes models. The optimal samples' chemical composition and firing temperature were chosen depending on a final usage of the raw material in heavy clay brick industry.
PB  - Wiley Blackwell
T2  - Advanced Materials for Agriculture, Food and Environmental Safety
T1  - Prediction and Optimization of Heavy Clay Products Quality
SP  - 87
EP  - 120
DO  - 10.1002/9781118773857.ch4
UR  - https://hdl.handle.net/21.15107/rcub_dais_15206
ER  - 
@inbook{
author = "Arsenović, Milica and Pezo, Lato and Mančić, Lidija and Radojević, Zagorka",
year = "2014",
abstract = "The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products parameters was evaluated by second order polynomial regression models (SOPs) and artificial neural networks (ANNs), and aft erwards compared to experimental results. SOPs showed high r2 values (0.897-0.913 for compressive strength models, 0.942-0.962 for water absorption, 0.928 for firing shrinkage, 0.988-0.991 for water loss during firing, and 0.941 for volume mass of cubes models). An ANN model, coupled with sensitivity analysis, was obtained with high prediction accuracy: 0.866-0.939 for compressive strength models, 0.954-0.974 for water absorption, 0.882 for firing shrinkage, 0.982-0.988 for water loss during firing, and 0.920 for volume mass of cubes models. The optimal samples' chemical composition and firing temperature were chosen depending on a final usage of the raw material in heavy clay brick industry.",
publisher = "Wiley Blackwell",
journal = "Advanced Materials for Agriculture, Food and Environmental Safety",
booktitle = "Prediction and Optimization of Heavy Clay Products Quality",
pages = "87-120",
doi = "10.1002/9781118773857.ch4",
url = "https://hdl.handle.net/21.15107/rcub_dais_15206"
}
Arsenović, M., Pezo, L., Mančić, L.,& Radojević, Z.. (2014). Prediction and Optimization of Heavy Clay Products Quality. in Advanced Materials for Agriculture, Food and Environmental Safety
Wiley Blackwell., 87-120.
https://doi.org/10.1002/9781118773857.ch4
https://hdl.handle.net/21.15107/rcub_dais_15206
Arsenović M, Pezo L, Mančić L, Radojević Z. Prediction and Optimization of Heavy Clay Products Quality. in Advanced Materials for Agriculture, Food and Environmental Safety. 2014;:87-120.
doi:10.1002/9781118773857.ch4
https://hdl.handle.net/21.15107/rcub_dais_15206 .
Arsenović, Milica, Pezo, Lato, Mančić, Lidija, Radojević, Zagorka, "Prediction and Optimization of Heavy Clay Products Quality" in Advanced Materials for Agriculture, Food and Environmental Safety (2014):87-120,
https://doi.org/10.1002/9781118773857.ch4 .,
https://hdl.handle.net/21.15107/rcub_dais_15206 .

Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry

Arsenović, Milica; Pezo, Lato; Mančić, Lidija; Radojević, Zagorka

(Elsevier, 2014)

TY  - JOUR
AU  - Arsenović, Milica
AU  - Pezo, Lato
AU  - Mančić, Lidija
AU  - Radojević, Zagorka
PY  - 2014
UR  - https://dais.sanu.ac.rs/123456789/640
AB  - This paper describes a study of 11 selected samples of loess soil from Serbia, by using differential scanning calorimetry, simultaneously with thermogravimetry and its differential calculation, known as simultaneous thermal analysis (STA). This survey is supplemented by chemical and mineralogical analysis, particle size distribution, and plasticity and drying susceptibility tests. Correlation analysis of major oxides content and certain technological test results were used for better understanding of the raw material composition and product physical properties. The results indicate that the samples were rich in carbonates, with the highest content of alevrite fraction and variable content of clay-sized particles. Mineralogical analysis confirms significant correlations between major oxides content and reveals that the most common non-clay mineral present is quartz, followed by calcite, dolomite and sodium feldspar. Major clay minerals include illite, chlorite, smectite and, in some cases, low quantities of kaolinite. Although STA method is well-known, this is the first time that it was used for discussion about its practical aspect, for characterization of the loess deposits, in terms of exploitation in brick industry.
PB  - Elsevier
T2  - Thermochimica Acta
T1  - Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry
SP  - 38
EP  - 45
VL  - 20
DO  - 10.1016/j.tca.2014.01.026
UR  - https://hdl.handle.net/21.15107/rcub_dais_640
ER  - 
@article{
author = "Arsenović, Milica and Pezo, Lato and Mančić, Lidija and Radojević, Zagorka",
year = "2014",
abstract = "This paper describes a study of 11 selected samples of loess soil from Serbia, by using differential scanning calorimetry, simultaneously with thermogravimetry and its differential calculation, known as simultaneous thermal analysis (STA). This survey is supplemented by chemical and mineralogical analysis, particle size distribution, and plasticity and drying susceptibility tests. Correlation analysis of major oxides content and certain technological test results were used for better understanding of the raw material composition and product physical properties. The results indicate that the samples were rich in carbonates, with the highest content of alevrite fraction and variable content of clay-sized particles. Mineralogical analysis confirms significant correlations between major oxides content and reveals that the most common non-clay mineral present is quartz, followed by calcite, dolomite and sodium feldspar. Major clay minerals include illite, chlorite, smectite and, in some cases, low quantities of kaolinite. Although STA method is well-known, this is the first time that it was used for discussion about its practical aspect, for characterization of the loess deposits, in terms of exploitation in brick industry.",
publisher = "Elsevier",
journal = "Thermochimica Acta",
title = "Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry",
pages = "38-45",
volume = "20",
doi = "10.1016/j.tca.2014.01.026",
url = "https://hdl.handle.net/21.15107/rcub_dais_640"
}
Arsenović, M., Pezo, L., Mančić, L.,& Radojević, Z.. (2014). Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry. in Thermochimica Acta
Elsevier., 20, 38-45.
https://doi.org/10.1016/j.tca.2014.01.026
https://hdl.handle.net/21.15107/rcub_dais_640
Arsenović M, Pezo L, Mančić L, Radojević Z. Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry. in Thermochimica Acta. 2014;20:38-45.
doi:10.1016/j.tca.2014.01.026
https://hdl.handle.net/21.15107/rcub_dais_640 .
Arsenović, Milica, Pezo, Lato, Mančić, Lidija, Radojević, Zagorka, "Thermal and mineralogical characterization of loess heavy clays for potential use in brick industry" in Thermochimica Acta, 20 (2014):38-45,
https://doi.org/10.1016/j.tca.2014.01.026 .,
https://hdl.handle.net/21.15107/rcub_dais_640 .
35
23
33

Optimization of the production process through response surface method: Bricks made of loess

Arsenović, Milica; Stanković, Slavka; Pezo, Lato; Mančić, Lidija; Radojević, Zagorka

(Elsevier, 2013)

TY  - JOUR
AU  - Arsenović, Milica
AU  - Stanković, Slavka
AU  - Pezo, Lato
AU  - Mančić, Lidija
AU  - Radojević, Zagorka
PY  - 2013
UR  - https://dais.sanu.ac.rs/123456789/341
AB  - Loess clays are commonly used to produce bricks. Heavy clays, taken at location near Zrenjanin, Serbia, are used as a representative raw material in this study. The sample, containing about 28% of clay sized particles, is enriched using two more plastic heavy clays from neighboring locations. Chemical and mineralogical content of clays is determined, as well as particle size distribution. Optimization of the processing parameters during the bricks production, i. e. temperature (900–1100 °C), and concentration of 2 clays combined addition (both in the range of 0–10%), is done based on the following independent parameters: compressive strength (CS), water absorption (WA), firing shrinkage (FS), weight loss during firing (WLF) and apparent density expressed as volume mass of cubes (VMC). Developed models showed r2 values in the range of 0.822–0.998, and they were able to accurately predict CS, WA, FS, WLF and VMC in a wide range of processing parameters. The optimum conditions are determined by the response surface method (RSM), coupled with the fuzzy synthetic evaluation (FSE) algorithm, using membership trapezoidal function, with defined optimal interval values, depending on a final usage of the raw material in heavy clay brick industry.
PB  - Elsevier
T2  - Ceramics International
T1  - Optimization of the production process through response surface method: Bricks made of loess
SP  - 3065
EP  - 3075
VL  - 39
IS  - 3
DO  - 10.1016/j.ceramint.2012.09.086
UR  - https://hdl.handle.net/21.15107/rcub_dais_341
ER  - 
@article{
author = "Arsenović, Milica and Stanković, Slavka and Pezo, Lato and Mančić, Lidija and Radojević, Zagorka",
year = "2013",
abstract = "Loess clays are commonly used to produce bricks. Heavy clays, taken at location near Zrenjanin, Serbia, are used as a representative raw material in this study. The sample, containing about 28% of clay sized particles, is enriched using two more plastic heavy clays from neighboring locations. Chemical and mineralogical content of clays is determined, as well as particle size distribution. Optimization of the processing parameters during the bricks production, i. e. temperature (900–1100 °C), and concentration of 2 clays combined addition (both in the range of 0–10%), is done based on the following independent parameters: compressive strength (CS), water absorption (WA), firing shrinkage (FS), weight loss during firing (WLF) and apparent density expressed as volume mass of cubes (VMC). Developed models showed r2 values in the range of 0.822–0.998, and they were able to accurately predict CS, WA, FS, WLF and VMC in a wide range of processing parameters. The optimum conditions are determined by the response surface method (RSM), coupled with the fuzzy synthetic evaluation (FSE) algorithm, using membership trapezoidal function, with defined optimal interval values, depending on a final usage of the raw material in heavy clay brick industry.",
publisher = "Elsevier",
journal = "Ceramics International",
title = "Optimization of the production process through response surface method: Bricks made of loess",
pages = "3065-3075",
volume = "39",
number = "3",
doi = "10.1016/j.ceramint.2012.09.086",
url = "https://hdl.handle.net/21.15107/rcub_dais_341"
}
Arsenović, M., Stanković, S., Pezo, L., Mančić, L.,& Radojević, Z.. (2013). Optimization of the production process through response surface method: Bricks made of loess. in Ceramics International
Elsevier., 39(3), 3065-3075.
https://doi.org/10.1016/j.ceramint.2012.09.086
https://hdl.handle.net/21.15107/rcub_dais_341
Arsenović M, Stanković S, Pezo L, Mančić L, Radojević Z. Optimization of the production process through response surface method: Bricks made of loess. in Ceramics International. 2013;39(3):3065-3075.
doi:10.1016/j.ceramint.2012.09.086
https://hdl.handle.net/21.15107/rcub_dais_341 .
Arsenović, Milica, Stanković, Slavka, Pezo, Lato, Mančić, Lidija, Radojević, Zagorka, "Optimization of the production process through response surface method: Bricks made of loess" in Ceramics International, 39, no. 3 (2013):3065-3075,
https://doi.org/10.1016/j.ceramint.2012.09.086 .,
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