TY  - CONF
AU  - Janković, Ksenija
AU  - Stojanović, Marko
AU  - Bojović, Dragan
AU  - Terzić, Anja
AU  - Stanković, Srboljub
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11172
AB  - This study compared the performance of self-compacting concrete (SCC) based on fly ash addition and limestone filler. A SCC prepared with Portland cement, river sand, and limestone filler was used as a reference sample. Additional experimental self-compacting concretes with different types of fine aggregates, fillers, and special additives for increasing freeze-thaw resistance were prepared and optimized. The correlation between mix design, i.e., percentage of barite sand and additives, and properties of fresh SCC (slump-flow test, V-funnel test, and L-box test), as well as properties of hardened SCC (compressive strengths), were investigated and discussed.
C3  - International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures
T1  - Influence of Aggregate Type on the Properties on SCC with Fly Ash
SP  - 47
EP  - 54
DO  - 10.1007/978-3-031-33187-9_5
ER  - 

@conference{
author = "Janković, Ksenija and Stojanović, Marko and Bojović, Dragan and Terzić, Anja and Stanković, Srboljub",
year = "2023",
abstract = "This study compared the performance of self-compacting concrete (SCC) based on fly ash addition and limestone filler. A SCC prepared with Portland cement, river sand, and limestone filler was used as a reference sample. Additional experimental self-compacting concretes with different types of fine aggregates, fillers, and special additives for increasing freeze-thaw resistance were prepared and optimized. The correlation between mix design, i.e., percentage of barite sand and additives, and properties of fresh SCC (slump-flow test, V-funnel test, and L-box test), as well as properties of hardened SCC (compressive strengths), were investigated and discussed.",
journal = "International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures",
title = "Influence of Aggregate Type on the Properties on SCC with Fly Ash",
pages = "47-54",
doi = "10.1007/978-3-031-33187-9_5"
}

Janković, K., Stojanović, M., Bojović, D., Terzić, A.,& Stanković, S.. (2023). Influence of Aggregate Type on the Properties on SCC with Fly Ash. in International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures, 47-54.
https://doi.org/10.1007/978-3-031-33187-9_5

Janković K, Stojanović M, Bojović D, Terzić A, Stanković S. Influence of Aggregate Type on the Properties on SCC with Fly Ash. in International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures. 2023;:47-54.
doi:10.1007/978-3-031-33187-9_5 .

Janković, Ksenija, Stojanović, Marko, Bojović, Dragan, Terzić, Anja, Stanković, Srboljub, "Influence of Aggregate Type on the Properties on SCC with Fly Ash" in International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures (2023):47-54,
https://doi.org/10.1007/978-3-031-33187-9_5 . .

TY  - JOUR
AU  - Terzić, Anja
AU  - Pezo, Milada
AU  - Pezo, Lato
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11103
AB  - The machine learning technique for prediction and optimization of building material performances became an essential feature in the contemporary civil engineering. The Artificial Neural Network (ANN) prognosis of mortar behavior was conducted in this study. The model appraised the design and characteristics of seventeen either building or high-temperature mortars. Seven different cement types were employed. Seventeen mineral additives of primary and secondary origin were embedded in the mortar mixtures. Cluster Analysis and Principal Component Analysis designated groups of similar mortars assigning them a specific purpose based on monitored characteristics. ANN foresaw the quality of designed mortars. The impact of implemented raw materials on the mortar quality was assessed and evaluated. ANN outputs highlighted the high suitability level of anticipation, i.e., 0.999 during the training period, which is regarded appropriate enough to correctly predict the observed outputs in a wide range of processing parameters. Due to the high predictive accuracy, ANN can replace or be used in combination with standard destructive tests thereby saving the construction industry time, resources, and capital. Good performances of altered cement mortars are positive sign for widening of economical mineral additives application in building materials and making progress towards achieved carbon neutrality by reducing its emission.
T2  - Science of Sintering
T1  - Application of artificial neural networks in performance prediction of cement mortars with various mineral additives
VL  - 55
IS  - 1
SP  - 11
EP  - 27
DO  - 10.2298/SOS2301011T
ER  - 

@article{
author = "Terzić, Anja and Pezo, Milada and Pezo, Lato",
year = "2023",
abstract = "The machine learning technique for prediction and optimization of building material performances became an essential feature in the contemporary civil engineering. The Artificial Neural Network (ANN) prognosis of mortar behavior was conducted in this study. The model appraised the design and characteristics of seventeen either building or high-temperature mortars. Seven different cement types were employed. Seventeen mineral additives of primary and secondary origin were embedded in the mortar mixtures. Cluster Analysis and Principal Component Analysis designated groups of similar mortars assigning them a specific purpose based on monitored characteristics. ANN foresaw the quality of designed mortars. The impact of implemented raw materials on the mortar quality was assessed and evaluated. ANN outputs highlighted the high suitability level of anticipation, i.e., 0.999 during the training period, which is regarded appropriate enough to correctly predict the observed outputs in a wide range of processing parameters. Due to the high predictive accuracy, ANN can replace or be used in combination with standard destructive tests thereby saving the construction industry time, resources, and capital. Good performances of altered cement mortars are positive sign for widening of economical mineral additives application in building materials and making progress towards achieved carbon neutrality by reducing its emission.",
journal = "Science of Sintering",
title = "Application of artificial neural networks in performance prediction of cement mortars with various mineral additives",
volume = "55",
number = "1",
pages = "11-27",
doi = "10.2298/SOS2301011T"
}

Terzić, A., Pezo, M.,& Pezo, L.. (2023). Application of artificial neural networks in performance prediction of cement mortars with various mineral additives. in Science of Sintering, 55(1), 11-27.
https://doi.org/10.2298/SOS2301011T

Terzić A, Pezo M, Pezo L. Application of artificial neural networks in performance prediction of cement mortars with various mineral additives. in Science of Sintering. 2023;55(1):11-27.
doi:10.2298/SOS2301011T .

Terzić, Anja, Pezo, Milada, Pezo, Lato, "Application of artificial neural networks in performance prediction of cement mortars with various mineral additives" in Science of Sintering, 55, no. 1 (2023):11-27,
https://doi.org/10.2298/SOS2301011T . .

TY  - JOUR
AU  - Pezo, Lato
AU  - Pezo, Milada L.
AU  - Terzić, Anja
AU  - Jovanović, Aca P.
AU  - Lončar, Biljana
AU  - Govedarica, Dragan
AU  - Kojić, Predrag
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10037
AB  - The numerical model of the granular flow within an aggregate mixture, conducted in the vertical static and/or the conveyor blender, was explored using the discrete element method (DEM) approach. The blending quality of limestone fine aggregate fractions binary mixture for application in self-compacting concrete was studied. The potential of augmenting the conveyor mixer working efficiency by joining its operation to a Komax-type vertical static mixer, to increase the blending conduct was investigated. In addition the impact of the feed height on the flow field in the cone-shaped conveyor mixer was examined using the DEM simulation. Applying the numerical approach enabled a deeper insight into the quality of blending actions, while the relative standard deviation criteria ranked the uniformity of the mixture. The primary objective of this investigation was to examine the behavior of mixture for two types of blenders and to estimate the combined blending action of these two mixers, to explore the potential to augment the homogeneity of the aggregate fractions binary mixture, i.e., mixing quality, reduce the blending time and to abbreviate the energy-consuming.
T2  - Processes
T1  - Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture
VL  - 9
IS  - 11
SP  - 1991
DO  - 10.3390/pr9111991
ER  - 

@article{
author = "Pezo, Lato and Pezo, Milada L. and Terzić, Anja and Jovanović, Aca P. and Lončar, Biljana and Govedarica, Dragan and Kojić, Predrag",
year = "2021",
abstract = "The numerical model of the granular flow within an aggregate mixture, conducted in the vertical static and/or the conveyor blender, was explored using the discrete element method (DEM) approach. The blending quality of limestone fine aggregate fractions binary mixture for application in self-compacting concrete was studied. The potential of augmenting the conveyor mixer working efficiency by joining its operation to a Komax-type vertical static mixer, to increase the blending conduct was investigated. In addition the impact of the feed height on the flow field in the cone-shaped conveyor mixer was examined using the DEM simulation. Applying the numerical approach enabled a deeper insight into the quality of blending actions, while the relative standard deviation criteria ranked the uniformity of the mixture. The primary objective of this investigation was to examine the behavior of mixture for two types of blenders and to estimate the combined blending action of these two mixers, to explore the potential to augment the homogeneity of the aggregate fractions binary mixture, i.e., mixing quality, reduce the blending time and to abbreviate the energy-consuming.",
journal = "Processes",
title = "Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture",
volume = "9",
number = "11",
pages = "1991",
doi = "10.3390/pr9111991"
}

Pezo, L., Pezo, M. L., Terzić, A., Jovanović, A. P., Lončar, B., Govedarica, D.,& Kojić, P.. (2021). Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture. in Processes, 9(11), 1991.
https://doi.org/10.3390/pr9111991

Pezo L, Pezo ML, Terzić A, Jovanović AP, Lončar B, Govedarica D, Kojić P. Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture. in Processes. 2021;9(11):1991.
doi:10.3390/pr9111991 .

Pezo, Lato, Pezo, Milada L., Terzić, Anja, Jovanović, Aca P., Lončar, Biljana, Govedarica, Dragan, Kojić, Predrag, "Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture" in Processes, 9, no. 11 (2021):1991,
https://doi.org/10.3390/pr9111991 . .

TY  - JOUR
AU  - Terzić, Anja
AU  - Radulović, Dragan
AU  - Pezo, Milada L.
AU  - Stojanović, Jovica
AU  - Pezo, Lato
AU  - Radojević, Zagorka
AU  - Andrić, Ljubiša
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9042
AB  - The optimal outputs of pyrophyllite mechano-chemical activation in an ultra-centrifugal mill performing under different technological conditions were determined by analytical modeling and verified via Artificial Neural Network in order to be employed in the production of cement-based binders. Cluster Analysis and Principal Component Analysis were utilized in assessment of the effect of activation process parameters on the activated pyrophyllite quality. Artificial Neural Network which performed with high prediction accuracy, i.e. 0.914 during the training period, was sufficient for precise prediction of activated pyrophyllite quality in a wide range of processing parameters. The probability of utilization of observed activation products was estimated through interrelation of technological parameters (mesh size sieve, activation period, specific energy consumption) and acquired characteristics of pyrophyllite (grain diameter, specific surface area). The optimal products singled out from each activation sequence were used as mineral additives in the mix-designs of four cement binders (cement replacement portion was 30%). Influence of activated pyrophyllite additions on the cement chemistry, mineral phase compositions and microstructures of the cement binders were monitored by instrumental techniques (DTA/TGA, XRD, SEM). Activated pyrophyllite showed characteristics of pozzolana as it slightly accelerated early stages of hydration, decreased cement hydration energy and increased the quantity of cement mineral alite at later hydration stages. Micron-sized crystalline foila characteristic for mechanically activated pyrophyllite formed micro-reinforcement within cement binder microstructure.
T2  - Construction and Building Materials
T1  - Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders
VL  - 258
SP  - 119721
DO  - 10.1016/j.conbuildmat.2020.119721
ER  - 

@article{
author = "Terzić, Anja and Radulović, Dragan and Pezo, Milada L. and Stojanović, Jovica and Pezo, Lato and Radojević, Zagorka and Andrić, Ljubiša",
year = "2020",
abstract = "The optimal outputs of pyrophyllite mechano-chemical activation in an ultra-centrifugal mill performing under different technological conditions were determined by analytical modeling and verified via Artificial Neural Network in order to be employed in the production of cement-based binders. Cluster Analysis and Principal Component Analysis were utilized in assessment of the effect of activation process parameters on the activated pyrophyllite quality. Artificial Neural Network which performed with high prediction accuracy, i.e. 0.914 during the training period, was sufficient for precise prediction of activated pyrophyllite quality in a wide range of processing parameters. The probability of utilization of observed activation products was estimated through interrelation of technological parameters (mesh size sieve, activation period, specific energy consumption) and acquired characteristics of pyrophyllite (grain diameter, specific surface area). The optimal products singled out from each activation sequence were used as mineral additives in the mix-designs of four cement binders (cement replacement portion was 30%). Influence of activated pyrophyllite additions on the cement chemistry, mineral phase compositions and microstructures of the cement binders were monitored by instrumental techniques (DTA/TGA, XRD, SEM). Activated pyrophyllite showed characteristics of pozzolana as it slightly accelerated early stages of hydration, decreased cement hydration energy and increased the quantity of cement mineral alite at later hydration stages. Micron-sized crystalline foila characteristic for mechanically activated pyrophyllite formed micro-reinforcement within cement binder microstructure.",
journal = "Construction and Building Materials",
title = "Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders",
volume = "258",
pages = "119721",
doi = "10.1016/j.conbuildmat.2020.119721"
}

Terzić, A., Radulović, D., Pezo, M. L., Stojanović, J., Pezo, L., Radojević, Z.,& Andrić, L.. (2020). Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders. in Construction and Building Materials, 258, 119721.
https://doi.org/10.1016/j.conbuildmat.2020.119721

Terzić A, Radulović D, Pezo ML, Stojanović J, Pezo L, Radojević Z, Andrić L. Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders. in Construction and Building Materials. 2020;258:119721.
doi:10.1016/j.conbuildmat.2020.119721 .

Terzić, Anja, Radulović, Dragan, Pezo, Milada L., Stojanović, Jovica, Pezo, Lato, Radojević, Zagorka, Andrić, Ljubiša, "Prediction model based on artificial neural network for pyrophyllite mechano-chemical activation as an integral step in production of cement binders" in Construction and Building Materials, 258 (2020):119721,
https://doi.org/10.1016/j.conbuildmat.2020.119721 . .

TY  - JOUR
AU  - Pezo, Milada L.
AU  - Pezo, Lato
AU  - Jovanović, Aca
AU  - Terzić, Anja
AU  - Andrić, Ljubiša
AU  - Lončar, Biljana
AU  - Kojić, Predrag
PY  - 2018
UR  - https://linkinghub.elsevier.com/retrieve/pii/S0032591018304480
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7719
AB  - In this paper, five types of horizontal single-pitch screw conveyors with modified geometry, with three different lengths (400, 600 and 800 mm) were investigated for transport and auxiliary mixing action of two materials: natural zeolite and quartz aggregate (sand) with particle sizes 3, 4 and 5 mm. The geometry of the screw transporter is changed by welding three additional helices oriented in the same or the opposite direction from screw cutting edges, enabling the premixing of materials, during the transport. The proper mixing of the observed materials provides an adequate disposition of zeolite particles within the composite and prevents agglomeration and interference with cement hydration. Zeolite application as a binder in a building material is a possible solution to environmental pollution problems caused by cement production. The influences of screw length, particle diameter, the studied geometry variations of screw design, on the mixing performances of the screw conveyor-mixer during material transport were explored. All investigations were performed experimentally and numerically, by using Discrete Element Method (DEM). The experimental results and the results of the DEM investigation were used for the development of mathematical models for the prediction of mixing quality, which are presented in the form of second order polynomial and artificial neural network model.
T2  - Powder Technology
T1  - Discrete element model of particle transport and premixing action in modified screw conveyors
VL  - 336
SP  - 255
EP  - 264
DO  - 10.1016/j.powtec.2018.06.009
ER  - 

@article{
author = "Pezo, Milada L. and Pezo, Lato and Jovanović, Aca and Terzić, Anja and Andrić, Ljubiša and Lončar, Biljana and Kojić, Predrag",
year = "2018",
abstract = "In this paper, five types of horizontal single-pitch screw conveyors with modified geometry, with three different lengths (400, 600 and 800 mm) were investigated for transport and auxiliary mixing action of two materials: natural zeolite and quartz aggregate (sand) with particle sizes 3, 4 and 5 mm. The geometry of the screw transporter is changed by welding three additional helices oriented in the same or the opposite direction from screw cutting edges, enabling the premixing of materials, during the transport. The proper mixing of the observed materials provides an adequate disposition of zeolite particles within the composite and prevents agglomeration and interference with cement hydration. Zeolite application as a binder in a building material is a possible solution to environmental pollution problems caused by cement production. The influences of screw length, particle diameter, the studied geometry variations of screw design, on the mixing performances of the screw conveyor-mixer during material transport were explored. All investigations were performed experimentally and numerically, by using Discrete Element Method (DEM). The experimental results and the results of the DEM investigation were used for the development of mathematical models for the prediction of mixing quality, which are presented in the form of second order polynomial and artificial neural network model.",
journal = "Powder Technology",
title = "Discrete element model of particle transport and premixing action in modified screw conveyors",
volume = "336",
pages = "255-264",
doi = "10.1016/j.powtec.2018.06.009"
}

Pezo, M. L., Pezo, L., Jovanović, A., Terzić, A., Andrić, L., Lončar, B.,& Kojić, P.. (2018). Discrete element model of particle transport and premixing action in modified screw conveyors. in Powder Technology, 336, 255-264.
https://doi.org/10.1016/j.powtec.2018.06.009

Pezo ML, Pezo L, Jovanović A, Terzić A, Andrić L, Lončar B, Kojić P. Discrete element model of particle transport and premixing action in modified screw conveyors. in Powder Technology. 2018;336:255-264.
doi:10.1016/j.powtec.2018.06.009 .

Pezo, Milada L., Pezo, Lato, Jovanović, Aca, Terzić, Anja, Andrić, Ljubiša, Lončar, Biljana, Kojić, Predrag, "Discrete element model of particle transport and premixing action in modified screw conveyors" in Powder Technology, 336 (2018):255-264,
https://doi.org/10.1016/j.powtec.2018.06.009 . .

TY  - JOUR
AU  - Terzić, Anja
AU  - Đorđević, Nataša
AU  - Mitrić, Miodrag
AU  - Marković, Smilja
AU  - Dordevic, Katarina
AU  - Pavlović, Vladimir B.
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1512
AB  - Due to pozzolanic characteristics, fly ash is commonly used as a cement replacement in construction composites. Addition of natural clays with sorption ability (i.e. zeolite and bentonite) in to the fly ash based construction materials is of both scientific and industrial interest. Namely, due to the application of sorptive clay minerals, it is possible to immobilize toxic heavy metals from the composite structure. The thermal compatibility of fly ash and zeolite, as well as fly ash and bentonite, within the composite was observed during sintering procedure. The starting components were used in 1: 1 ratio and they were applied without additional mechanical treatment. The used compaction pressure for the tablets was 2 t.cm(-2). The sintering process was conducted at 1000 degrees C and 1200 degrees C for two hours in the air atmosphere. The mineralogical phase composition of the non-treated and sintered samples was analyzed using X-ray diffraction method. Scanning electron microscopy was applied in the analysis of the microstructure of starting and sintered samples. The thermal behavior was observed via DTA method. The influence of temperature on the properties of fly ash-zeolite and fly ash-bentonite composites was investigated.
T2  - Science of Sintering
T1  - Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials
VL  - 49
IS  - 1
SP  - 23
EP  - 37
DO  - 10.2298/SOS1701023T
ER  - 

@article{
author = "Terzić, Anja and Đorđević, Nataša and Mitrić, Miodrag and Marković, Smilja and Dordevic, Katarina and Pavlović, Vladimir B.",
year = "2017",
abstract = "Due to pozzolanic characteristics, fly ash is commonly used as a cement replacement in construction composites. Addition of natural clays with sorption ability (i.e. zeolite and bentonite) in to the fly ash based construction materials is of both scientific and industrial interest. Namely, due to the application of sorptive clay minerals, it is possible to immobilize toxic heavy metals from the composite structure. The thermal compatibility of fly ash and zeolite, as well as fly ash and bentonite, within the composite was observed during sintering procedure. The starting components were used in 1: 1 ratio and they were applied without additional mechanical treatment. The used compaction pressure for the tablets was 2 t.cm(-2). The sintering process was conducted at 1000 degrees C and 1200 degrees C for two hours in the air atmosphere. The mineralogical phase composition of the non-treated and sintered samples was analyzed using X-ray diffraction method. Scanning electron microscopy was applied in the analysis of the microstructure of starting and sintered samples. The thermal behavior was observed via DTA method. The influence of temperature on the properties of fly ash-zeolite and fly ash-bentonite composites was investigated.",
journal = "Science of Sintering",
title = "Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials",
volume = "49",
number = "1",
pages = "23-37",
doi = "10.2298/SOS1701023T"
}

Terzić, A., Đorđević, N., Mitrić, M., Marković, S., Dordevic, K.,& Pavlović, V. B.. (2017). Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials. in Science of Sintering, 49(1), 23-37.
https://doi.org/10.2298/SOS1701023T

Terzić A, Đorđević N, Mitrić M, Marković S, Dordevic K, Pavlović VB. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials. in Science of Sintering. 2017;49(1):23-37.
doi:10.2298/SOS1701023T .

Terzić, Anja, Đorđević, Nataša, Mitrić, Miodrag, Marković, Smilja, Dordevic, Katarina, Pavlović, Vladimir B., "Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials" in Science of Sintering, 49, no. 1 (2017):23-37,
https://doi.org/10.2298/SOS1701023T . .