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Mohammad Atikur Rahman AtikDepartment of Energy Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary

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Attila R. ImreDepartment of Energy Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary
Department of Thermohydraulics, Centre for Energy Research, Budapest, Hungary

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https://orcid.org/0000-0003-4604-5899
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Abstract

Carbon-dioxide-based trans-critical power cycle is a novel technology for waste heat recovery. This technology can handle the high-temperature exhaust gas and can be built in a compact size, which is an important feature for the auxiliary equipment for an internal combustion engine. To obtain the best output, four configurations were constructed: the basic system; one with preheater, another with regenerator and a fourth with preheater and regenerator. Special features of supercritical CO2 make these cycles able to recover more energy than the traditional organic Rankine cycle. According to this study, heat regeneration increases thermal efficiency while preheating influences the net power output. Thus, it is beneficial to add both regenerator and preheater to the basic cycle.

Abstract

Carbon-dioxide-based trans-critical power cycle is a novel technology for waste heat recovery. This technology can handle the high-temperature exhaust gas and can be built in a compact size, which is an important feature for the auxiliary equipment for an internal combustion engine. To obtain the best output, four configurations were constructed: the basic system; one with preheater, another with regenerator and a fourth with preheater and regenerator. Special features of supercritical CO2 make these cycles able to recover more energy than the traditional organic Rankine cycle. According to this study, heat regeneration increases thermal efficiency while preheating influences the net power output. Thus, it is beneficial to add both regenerator and preheater to the basic cycle.

1 Introduction

The emissions of greenhouse gases and other pollutants caused by the combustion of fossil fuels have an undeniable effect on the climate, including ozone depletion. As a result of fuel costs and environmental concerns, a recent study has focused on developing and deploying renewable energy sources (solar heat, geothermal energy, and different forms of waste heat). Among the retrieving of waste energy technologies, the promising heat-to-power conversion method is considered as a power cycle, which has sparked a lot of research interest due to its higher system integration, consistency, and versatility. Each year, about 60–70% of hydrocarbon fuel is consumed by engine sectors in an industrial country. However, under most operating conditions, the engine coolant and exhaust source could waste more than half of the heat produced by fuel combustion in an engine, resulting in waste of energy and emissions problems. Recycling of Waste Heat (RWH) is a technique for recuperating the energy from waste that can be transferred to the environment to attain some valuable functions. It can also minimize the fuel consumption in many cases that need additional fuel energy input. The main target of WHR is to produce additional work, and a large quantity of waste heat can be converted into work from a high-quality heat source. Generally, Organic Rankine Cycle (ORC) system [1, 2] and Steam Rankine Cycle (SRC) system [3, 4] are contemplated as the most fruitful RWH techniques in the domain of low-grade heat and power generation stations, although other methods, like hot air (Stirling) engines can be also good for this purpose [4].

However, regarding waste heat of engines, ORC and SRC cannot give satisfactory results due to some particular characteristics of the engine. One of the significant drawbacks of the ORC system is its characteristic of persistent evaporation temperature, which is not adjustable for the sensitive misused heat sources [5, 6]. Among different heat sources, exhaust-gas-engine is the major recovery target of waste heat. It possesses a high quantity of heat/energy and a high degree of temperature region. The temperature of this targeted source can be reached up to 773.15 K for the diesel engine and 1073.15 K for the gasoline engine, respectively. Most importantly, vehicles have limited space layouts, which is a big problem for the ORC and SRC. Thus, many authors proposed CO2-based Trans-critical Power Cycle (CO2TPC) technology to cover up these pressure and temperature-related issues. The major focus of this research was to compare the performance of Basic system CO2-based Trans-critical Power Cycle (B-CO2TPC), Preheater CO2-based Trans-critical Power Cycle (P-CO2TPC), Regenerator based CO2-based Trans-critical Power Cycle (R-CO2TPC) and Preheater and Regenerator CO2-based Trans-critical Power Cycle (PR-CO2TPC) from various aspects.

Subcritical cycle means (see, for example, by Jahar-Sarkar et al. [7]) that the process is performed at subcritical pressures when both addition and rejection of heat occurs; also, the temperatures also stay below the critical temperature in all steps (except in cycles with super-heaters). When heat inclusion and exclusion occur at supercritical pressure, the process is known as supercritical power cycle. In this case, the temperatures are above the critical temperature all along the cycle. At very high pressures and temperatures, the supercritical fluid will be similar to gas [8]; therefore, the supercritical cycle (under those conditions) technically - although not thermodynamically - will be identical to a Brayton cycle. When heat addition occurs at supercritical pressure and heat rejection occurs at subcritical pressure, the cycle is trans-critical, although sometimes it is also referred as supercritical Rankine cycle [5]. Due to the so-called supercritical anomalies (like Widom-lines, pseudo-boiling [89] a trans- or supercritical CO2 cycle can give better efficiency than other, similar gas cycles (like Brayton cycle).

In the recovery of waste heat for Internal Combustion Engines (ICE), it is significant to inspect the performance of four CO2TPC configurations, giving a reference of applications for the system. Currently, a number of theoretical analyses about carbon dioxide trans-critical power cycle systems can be found in the literature [10, 11], which concludes that CO2TPC is more and more appealing in the engine sector (ICE). According to Chen et al. [12], approximately one-fifth of the energy in the exhaust gas can be extracted into work by a model developed using the CO2TPC system's bottoming period. Autier and Kouadri-David [13] initiated an optimum study of a CO2TPC with or without a regenerator using exhaust gas from a fishing boat diesel engine to reduce fuel dependency. The two optimized parameters in this study were pressure and temperature, and results stated that a convenient temperature had existed for each pressure in CO2TPC system only with the regenerator. A 250 kW CO2TPC system with a regenerator completed by Echogen Power System (EPS) in a pilot project, with temperature varying from 473.15 to 813.15 K, which also suggests the probability of recycling the waste heat of engines exhaust gas in an initial test [14]. Pan et al. [15], used a rolling piston expander to experiment on a carbon dioxide-based CO2TPC power loop. At high pressure (11 MPa) and low pressure (4.6 MPa), the thermal efficiency was 5%, and the corresponding maximum electric power reached about 1,100 W. Furthermore, Farzaneh-Gord et al. [11] conducted a comparative study of the four CO2TPC configurations, finding that PR-CO2TPC would attain a maximum net power output of 18 kW, implying that adding a preheater and regenerator could theoretically improve the net power output. Influential previous research led by Shu [10] convinced us to select four CO2TPC configurations. Three selection maps were created for various states depending on three attributes: net power generation, energy efficiency, and the cost of electricity production. The result of his research revealed that for a 43.8 kW gasoline engine, the net power output was 9.1 kW, the exergy efficiency was 0.48, and the economic performance was 0.431 $/kWh with PR-CO2TPC being one of the most advantageous options with outstanding thermodynamic performances [10].

2 System structure and methodology

2.1 CO2TPC structure

The graphical representation of the CO2TPC system a diesel engine is illustrated in Fig. 1a. In the system, mainly three parts are described: CO2TPC system, exhaust source (a diesel engine), coolant source loop. The topping system in this work is a diesel engine. Major technical parameters of an engine (with turbocharger) can be found in [10, 16]. Let discuss PR-CO2TPC (Fig. 1b) as an example of CO2-based systems. The process starts with a pump and ends with a condenser; each point is marked by letters. In the first step, the working fluid (CO2) is pumped to a supercritical pressure (p-q), where the pump acts as a drive component. Secondly, the engine coolant in the preheater at the pump outlet (q-a) warms up the pressurized CO2 fluid, the point (a-b) marked as the turbine outlet in the regenerator of CO2 fluid. The high-temperature exhaust gas enters the heating coils of the evaporator (b-x). After that, the heated CO2 fluid (already in a fully supercritical state, where both pressure and temperature are above the critical values) flows in the turbine, and the expansion work is generated (x-y). CO2 fluid exits the turbine and reaches the heat exchanger called regenerator, which serves as regenerated thermal storage (y-z). The working fluid gets access to the condenser while coming out from the regenerator and condenses the fluid into a liquid state (z-p), making the structure p-q-a-b-x-y-z. Similarly, the flow structure of the B-CO2TPC system is q-x-y-p, P-CO2TPC is q-a-x-y-p, and R-CO2TPC is q-b-x-y-z-p. On a mass basis, the mass fractions of CO2, H2O, and N2 in exhaust gas compounds measured were 19.84%, 8.26%, and 71.49% [16], respectively. The temperature of the acid dew point of the engine exhaust was set at 393.15 K, and the exhaust temperature had to reach this limit in operation. The engine coolant fluid is considered in this paper as pure water.

Fig. 1.
Fig. 1.

a) Schematic diagram of PR-CO2TPC system; b) T-s diagram of the system

Citation: Pollack Periodica 2022; 10.1556/606.2022.00522

2.2 Methods

MATLAB was used to create the mathematical model, while RefProp was used to test the fluids' thermodynamic properties. In order to build this waste heat recovery model, a few assumptions were taken, similarly to other studies on this field [9, 16, 17, 18 ]. Furthermore, stable states, steady-flow systems and equilibrium conditions were assumed during the process. The pressure drops in the pipe were neglected as well as heat loss by the radiation. The generator's efficiency was set to 0.9, the turbine's isentropic efficiency was set to 0.7, and the pump's efficiency was set to 0.8, with the condensation temperature set to 298.15 K, which allows CO2 to be converted to a saturated liquid state.

The determination of the thermodynamic condition of each point is the basis of this model; hence, it is important to quantify the mass flow rate of the working fluid in advance for this case. The usual method to calculate the mass flow rate mfr and thermodynamic state condition is called “Temperature Difference at Pinch Point (TD@PP)” [18]. For the heat exchange in the evaporator, the TD@PP is set at 30 K.

The calculation approach used for both ORC and CO2TPC had been developed by other authors [17, 18]. Generally, PR-CO2TPC and P-CO2TPC contained two waste heat sources, which mean there are two mass flow rates. One is exhaust gas (mfr,1), and another is engine coolant (mfr,2) which can be obtained by TD@PP method when both are supposed to approach maximum heat recovery rate. Generally, two mass flow rates can be represented by the following Eqs [17, 18]:
mfr,1=mcCpec(tc,intc,out)(hahq),
mfr,2=mgCpeg(tg,intg,out)(hxhb).
where m is the mass, cp is the isobaric specific heat, t is the temperature, h is the enthalpy and concerning indices, fr is the flow rate (1 for coolant, 2 for exhaust), c is the coolant, in and out is the inlet and the outlet, a, q, x and b are states marked in Fig. 1b.

From Eqs (1) and (2), when mfr,1 and mfr,2 is equal, this quantity of mass flow rate fulfils both the highest usage of exhaust gas and the engine coolant. But, generally, mfr1 and mfr2 are often dissimilar. Therefore, choose the lowest number between mfr,1 and mfr,2 as the final mass flow rate to meet one complete usage among the two waste heats. On the other hand, this mass flow rate adjustment is unnecessary for the regenerator-based system and the basic system that uses exhaust gas as the only heat source.

2.3 Calculation by 1st law of thermodynamics

In this study, the cycle components' performance and energy stability are examined according to the first law of thermodynamics. Coding was done based on the system's mathematical model by using the MATLAB software. The equations of each component for the entire scheme are shown in Eqs (3)(9),
Wpmp=mfr(hqhp)=mfr(hqshp)/ηpmp,
Qph=mfr(hahq)=mcCp,c(Tc,inTc,out),
Qrg=mfr(hbha)=mfr(hyhz),
Qghe=mgcpg(tg,intg,out)=mfr(hxhb),
Qcnd=mfr(hzhp),
Power=mfr(hxhy)ηgen=mfr(hxhys)ηtrbηgen,
Wnpo=PowerWpmp,
ηte=WnpoQghe+Qph,
where, in Eq. (3)Wpmp represents the pump, the subscript qs means the outlet state of the pump after isentropic compression, the subscript fl is the CO2 fluid, hq and hp is the enthalpy difference between q and p. Equation (4)Qph represents the heat in preheater, subscript c means the engine coolant and c,in and c,out are the state of inlet and outlet of preheater, respectively. In Eq. (5)Qrg represents the heat in the regenerator, in Eq. (6)Qghe is the heat in gas heater, subscript g,in and g,out are the entry and outer state of exhaust gas in gas heater. In Eq. (7), Qcnd represents the condenser. In Eq. (8) the Power represents turbine and generator, the subscript ys is the outlet state of turbine after isentropic expansion. In Eqs (9) and (10)Wnpo is the net power output and ηte is the thermal efficiency.

However, a percentage of waste heat recovery consumption is also measured to assess the degree of waste heat recovery. According to Shu and Shi [15], if the exhaust gas temperature is reduced to the acid dew point and the engine coolant temperature is lowered to the engine coolant's return temperature, the exhaust gas and engine coolant may be used properly. That is why the utilization rates were also investigated in this work.

3 Results discussion

The main simulation work output and performance comparison among the four CO2TPC system configurations (e.g. B-CO2TPC, P-CO2TPC, R-CO2TPC and PR-CO2TPC) was discussed in this part. Comparative performance of net power production and efficiency in terms of heat has been evaluated with some other indicators. In addition, turbine inlet pressure (P3) had been considered as the variation input (ranging from 10 to 20 kPa), while turbine inlet temperature (T3) was chosen as 500 K and 700 K for all the discussions.

3.1 Waste heat utilization

Reduction and utilization of waste heat in general can significantly reduce the power consumption. It is important to calculate the utilization rate due to its positive impact on the environment. This could be possible when the exhaust gas utilization rate is maximal, resulting in a lower exhaust temperature. The cooling load of the engine can be minimized by using engine coolant (Uce) at a higher rate, as this allows the engine cooling system to hit a lower temperature. The total use of exhaust heat source and coolant source of the engine is defined as the temperature of the exhaust gas being reduced to the acid dew point and the temperature of the coolant being reduced to the returning temperature of the engine coolant. Among four CO2TPC systems, basic configuration (B-CO2TPC) is not included in this analysis due to its structure. In this system, the consumption rate of both exhaust gas Ueg and engine coolant Uce expanded as turbine inlet pressure increased (with Ueg increasing and Uce decreasing). The distinction was made between the exhaust and coolant (R-CO2TPC and P-CO2TPC with the PR-CO2TPC) configurations for constant turbine inlet temperatures of 700 and 550 K. Table 1 summarizes the utilization rate results for all scenarios. Overall, R-CO2TPC obtained higher Ueg than PR-CO2TPC system in both conditions. But, PR-based CO2 system showed higher Uce than P-based system for the same conditions.

Table 1.

Summary of waste heat utilization rates by exhaust and engine coolant supply

Utilization rate by Ueg, Uce
Configurations550 K, 10 kPa550 K, 20 kPa700 K, 10 kPa700 K, 20 kPa
R-CO2TPC (Ueg)0.930.9350.550.66
PR-CO2TPC (Ueg)0.350.890.250.58
P-CO2TPC (Uce)0.860.270.510.17
PR-CO2TC (Uce)1.000.380.640.23

3.2 Thermal efficiency and net electricity output

In Fig. 2a, the net power output of all devices increases as the turbine inlet pressure improves, which is attributed to an increase in the enthalpy gap at the expander. Here, PR-CO2TPC, R-CO2TPC, P-CO2TPC, and B-CO2TPC initially shows around 12.80 kW, 11.50 kW, 10.0 kW, and 7.0 kW (for P3 = 10 kPa) for turbine inlet temperature state 700 K. Consecutively, for P3 = 20 kPa they reached around 23.05 kW, 22.5 kW, 18.0 kW and 15.6 kW, respectively, where PR-CO2TPC dominated over other configurations in the whole pressure range. In the case of the low-pressure range, R-CO2TPC was slightly higher than the other CO2TPC configurations, and this was caused due to low turbine inlet pressure where the gas heater mainly used up the exhaust gas. In addition, the mass flow rate intensity of the working fluid slowly decreases by proceeding forward. As a result, the net power output steadily declines. On the other hand, the variance of thermal efficiency demonstrated an upward trend with the increase of turbine inlet pressure. According to Fig. 2b, the thermal efficiency acquired by R-CO2TPC is 0.229, while PR-CO2TPC achieved 0.197, and both B-CO2TPC and P-CO2TPC remain constant throughout the range. Here, R-CO2TPC dominates due to adding the regenerator; also, the percentage of the recovered heat is elevated with the increase of pressure. Moreover, the regenerator itself can be able to recover some internal heat, which is the main reason for its higher thermal efficiency output. Despite the fact that PR-CO2TPC had a greater net power yield, but it adsorbs the heat energy from the cooling jacket and gets inferior to R-CO2TPC in terms of thermal efficiency. Interestingly, both the B-CO2TPC and P-CO2TPC remain constant as both possessed similar mfr (mass flow rate) of the working fluid (CO2) on the basis of their configurations.

Fig. 2.
Fig. 2.

a) Variations of net power output and b) thermal efficiency with turbine inlet pressure

Citation: Pollack Periodica 2022; 10.1556/606.2022.00522

3.3 Performance of CO2TPC under various engine conditions

When adopting waste heat recovery systems on the particle application, the operation status of the engine differs most of the time. The different engine conditions may cause a great effect on the waste heat recovery system. Thus, a detailed analysis should also be considered when working conditions of engine changes. The detailed parameters of engine conditions are 211, 316.2, 422, 526, 631.2, 736.4 and 841 Nm (torques) and 48.16, 72.36, 96.74, 120.72, 145.02, 169.08 and 193.38 kW (powers), respectively. With the increase of engine torque (from conditions 1–7), both engine coolant and exhaust gas have increased thermal power, ranging 40.0-190.5 kW with the engine torque changing from 211 to 841 Nm. In contrast to exhaust gas, the rise in heat energy of the engine coolant is more unstable. The temperature of the exhaust source reaches around 370°C with a constant rising as engine torque increases, while the temperature of the engine coolant at first increases randomly then decreases to nearly 81°C.

Considering the discussion above, the relative CO2TPC performance had analyzed based on first law of thermodynamics. The power output from the turbine increases with the increase of engine torque (Fig. 3a). Here, PR-CO2TPC owned the highest turbine power output, while the basic one performed the worst. When engine torque increases from 211 to 841 Nm, the power output in the turbine also increases from 6.6-25.9 kW, mainly due to the increase of mfr of CO2 as well as enthalpy difference.

Fig. 3.
Fig. 3.

Variance of a) net power output, b) thermal efficiency (%) with the engine torque

Citation: Pollack Periodica 2022; 10.1556/606.2022.00522

Meanwhile, in Fig. 3b, it can be seen that the thermal efficiencies of B-CO2TPC and P-CO2TPC are equal under the entire working range of the engine. The explanation for this is that in B-CO2TPC and P-CO2TPC, the mass flow rate of the operating fluid is determined by the exhaust gas, and the engine coolant consumption rate has reached its limit. Another interesting point is that the thermal efficiency of R-CO2TPC are higher than for PR-CO2TPC although the PR-CO2TPC attains the maximum net power output.

4 Conclusions

The theoretical performances among the four CO2-based configurations, namely: basic, preheater, regenerator, and preheater-regenerator-based system compared extensively in the field of waste heat recovery of internal combustion engines, especially in the case of heavy-duty diesel engines. The study of analysis focuses on the rate of waste heat consumption and net power generation, and the performance of CO2TPC under various engine operating conditions was compared. The following major conclusions can be distinguished:

  • The waste heat utilization rate was investigated for both the exhaust (Ueg) and engine coolant (Uce). In the case of exhaust gas, R-CO2TPC outraced PR-CO2TPC (0.66 > 0.58, for 700 K, 20 MPa). Whereas, for engine coolant (Uce), PR-CO2TPC achieved higher than P-CO2TPC (0.23 > 0.17, for 700 K, 20 MPa);

  • PR-CO2TPC has obtained the highest net power output among the four CO2TPC configurations. It achieved 23.05 kW under 700 K and 20 MPa, which was followed by R-CO2TPC, P-CO2TPC and B-CO2TPC, respectively. But at lower T3 (500 K) and P3 (10 MPa), R-CO2TPC owned slightly higher than PR-CO2TPC;

  • The performance of CO2TPC configurations on various engine's factors had also been evaluated. In other words, PR-CO2TPC demonstrated higher attributes in the turbine's overall productivity and working fluid's mass flow rate. In terms of thermal efficiency, however, R-CO2TPC outperformed the other devices;

  • Finally, PR-CO2TPC has the most profound characteristics compared to the basic system in the field of WHR of internal combustion engines. However, this system can be improved in further study under sophisticated supervision by switching trans-critical to supercritical state or modifying components pump or turbine, reducing system size etc.

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  • [1]

    P. Heidrich and T. Krisch, “Assessment of waste heat recovery options in passenger car applications by various Rankine cycles,” Heat Transfer Eng., vol. 36, nos 14–15, pp. 13211331, 2015.

    • Search Google Scholar
    • Export Citation
  • [2]

    A. M. Ahmed and A. R. Imre, “Effect of heat source temperature on ORC and TFC efficiency,” Pollack Period., vol. 16, no. 2, pp. 7379, 2021.

    • Search Google Scholar
    • Export Citation
  • [3]

    T. A. Horst, H. S. Rottengruber, M. Seifert, and J. Ringler, “Dynamic heat exchanger model for performance prediction and control system design of automotive waste heat recovery systems,” Appl. Energ., vol. 105, pp. 293303, 2013.

    • Search Google Scholar
    • Export Citation
  • [4]

    G. Kramer, G. Szepesi, and Z. Simenfalvi, “Novel hot air engine and its mathematical model- experimental measurements and numerical analysis,” Pollack Period., vol. 14, no. 1, pp. 4758, 2018.

    • Search Google Scholar
    • Export Citation
  • [5]

    C. Sproude and C. Depcik, “Review of organic Rankine cycles for internal combustion engine exhaust waste heat recovery,” Appl. Therm. Eng., vol. 51, nos 1-2, pp. 711722, 2013.

    • Search Google Scholar
    • Export Citation
  • [6]

    H. Chen, D. Y. Goswami, and E. K. Stefanakos, “A review of thermodynamic cycles and working fluids for the conversion of low-grade heat,” Renew. Sustainable Energ. Rev., vol. 14, no. 9, pp. 30593067, 2010.

    • Search Google Scholar
    • Export Citation
  • [7]

    J. Sarkar, “Review and future trends of supercritical CO2 Rankine cycle for low grade heat conversion,” Renew. Sustainable Energ. Rev., vol. 48, pp. 434451, 2015.

    • Search Google Scholar
    • Export Citation
  • [8]

    A. R. Imre, U. K. Deiters, T. Kraska, I. Tiselj, “The pseudocritical regions for supercritical water,” Nucl. Eng. Des., vol. 252, pp. 179183, 2012.

    • Search Google Scholar
    • Export Citation
  • [9]

    D. T. Banuti, “Crossing the Widom-line - Supercritical pseudo-boiling,” J. Supercrit. Fluids, vol. 98, pp. 1216, 2015.

  • [10]

    H. Tian, L. Chang, G. Shu, and L. Shi, “Configurations selection maps of CO2-based transcritical Rankine cycle (CTRC) for thermal energy management of engine waste heat,” Appl. Energ., vol. 186, pp. 423435, 2016.

    • Search Google Scholar
    • Export Citation
  • [11]

    M. Farzaneh-Gord, S. Mirmohammadi, M. Behi, and A. Yahyaie, “Heat recovery from a natural gas powered internal combustion engine by CO2 transcritical power cycle,” Therm. Sci., vol. 14, pp. 897911, 2010.

    • Search Google Scholar
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Senior editors

Editor(s)-in-Chief: Iványi, Amália

Editor(s)-in-Chief: Iványi, Péter

 

Scientific Secretary

Miklós M. Iványi

Editorial Board

  • Bálint Bachmann (Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Jeno Balogh (Department of Civil Engineering Technology, Metropolitan State University of Denver, Denver, Colorado, USA)
  • Radu Bancila (Department of Geotechnical Engineering and Terrestrial Communications Ways, Faculty of Civil Engineering and Architecture, “Politehnica” University Timisoara, Romania)
  • Charalambos C. Baniotopolous (Department of Civil Engineering, Chair of Sustainable Energy Systems, Director of Resilience Centre, School of Engineering, University of Birmingham, U.K.)
  • Oszkar Biro (Graz University of Technology, Institute of Fundamentals and Theory in Electrical Engineering, Austria)
  • Ágnes Borsos (Institute of Architecture, Department of Interior, Applied and Creative Design, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Matteo Bruggi (Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Italy)
  • Petra Bujňáková (Department of Structures and Bridges, Faculty of Civil Engineering, University of Žilina, Slovakia)
  • Anikó Borbála Csébfalvi (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Mirjana S. Devetaković (Faculty of Architecture, University of Belgrade, Serbia)
  • Szabolcs Fischer (Department of Transport Infrastructure and Water Resources Engineering, Faculty of Architerture, Civil Engineering and Transport Sciences Széchenyi István University, Győr, Hungary)
  • Radomir Folic (Department of Civil Engineering, Faculty of Technical Sciences, University of Novi Sad Serbia)
  • Jana Frankovská (Department of Geotechnics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
  • János Gyergyák (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Kay Hameyer (Chair in Electromagnetic Energy Conversion, Institute of Electrical Machines, Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Germany)
  • Elena Helerea (Dept. of Electrical Engineering and Applied Physics, Faculty of Electrical Engineering and Computer Science, Transilvania University of Brasov, Romania)
  • Ákos Hutter (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technolgy, University of Pécs, Hungary)
  • Károly Jármai (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
  • Teuta Jashari-Kajtazi (Department of Architecture, Faculty of Civil Engineering and Architecture, University of Prishtina, Kosovo)
  • Róbert Kersner (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Rita Kiss  (Biomechanical Cooperation Center, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary)
  • István Kistelegdi  (Department of Building Structures and Energy Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Stanislav Kmeť (President of University Science Park TECHNICOM, Technical University of Kosice, Slovakia)
  • Imre Kocsis  (Department of Basic Engineering Research, Faculty of Engineering, University of Debrecen, Hungary)
  • László T. Kóczy (Department of Information Sciences, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, University of Győr, Hungary)
  • Dražan Kozak (Faculty of Mechanical Engineering, Josip Juraj Strossmayer University of Osijek, Croatia)
  • György L. Kovács (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Balázs Géza Kövesdi (Department of Structural Engineering, Faculty of Civil Engineering, Budapest University of Engineering and Economics, Budapest, Hungary)
  • Tomáš Krejčí (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
  • Jaroslav Kruis (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
  • Miklós Kuczmann (Department of Automations, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, Széchenyi István University, Győr, Hungary)
  • Tibor Kukai (Department of Engineering Studies, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Maria Jesus Lamela-Rey (Departamento de Construcción e Ingeniería de Fabricación, University of Oviedo, Spain)
  • János Lógó  (Department of Structural Mechanics, Faculty of Civil Engineering, Budapest University of Technology and Economics, Hungary)
  • Carmen Mihaela Lungoci (Faculty of Electrical Engineering and Computer Science, Universitatea Transilvania Brasov, Romania)
  • Frédéric Magoulés (Department of Mathematics and Informatics for Complex Systems, Centrale Supélec, Université Paris Saclay, France)
  • Gabriella Medvegy (Department of Interior, Applied and Creative Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Tamás Molnár (Department of Visual Studies, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Ferenc Orbán (Department of Mechanical Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Zoltán Orbán (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Dmitrii Rachinskii (Department of Mathematical Sciences, The University of Texas at Dallas, Texas, USA)
  • Chro Radha (Chro Ali Hamaradha) (Sulaimani Polytechnic University, Technical College of Engineering, Department of City Planning, Kurdistan Region, Iraq)
  • Maurizio Repetto (Department of Energy “Galileo Ferraris”, Politecnico di Torino, Italy)
  • Zoltán Sári (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Grzegorz Sierpiński (Department of Transport Systems and Traffic Engineering, Faculty of Transport, Silesian University of Technology, Katowice, Poland)
  • Zoltán Siménfalvi (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
  • Andrej Šoltész (Department of Hydrology, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
  • Zsolt Szabó (Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Hungary)
  • Mykola Sysyn (Chair of Planning and Design of Railway Infrastructure, Institute of Railway Systems and Public Transport, Technical University of Dresden, Germany)
  • András Timár (Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Barry H. V. Topping (Heriot-Watt University, UK, Faculty of Engineering and Information Technology, University of Pécs, Hungary)

POLLACK PERIODICA
Pollack Mihály Faculty of Engineering
Institute: University of Pécs
Address: Boszorkány utca 2. H–7624 Pécs, Hungary
Phone/Fax: (36 72) 503 650

E-mail: peter.ivanyi@mik.pte.hu 

or amalia.ivanyi@mik.pte.hu

Indexing and Abstracting Services:

  • SCOPUS

 

2021  
Web of Science  
Total Cites
WoS
not indexed
Journal Impact Factor not indexed
Rank by Impact Factor

not indexed

Impact Factor
without
Journal Self Cites
not indexed
5 Year
Impact Factor
not indexed
Journal Citation Indicator not indexed
Rank by Journal Citation Indicator

not indexed

Scimago  
Scimago
H-index
12
Scimago
Journal Rank
0,26
Scimago Quartile Score Civil and Structural Engineering (Q3)
Materials Science (miscellaneous) (Q3)
Computer Science Applications (Q4)
Modeling and Simulation (Q4)
Software (Q4)
Scopus  
Scopus
Cite Score
1,5
Scopus
CIte Score Rank
Civil and Structural Engineering 232/326 (Q3)
Computer Science Applications 536/747 (Q3)
General Materials Science 329/455 (Q3)
Modeling and Simulation 228/303 (Q4)
Software 326/398 (Q4)
Scopus
SNIP
0,613

2020  
Scimago
H-index
11
Scimago
Journal Rank
0,257
Scimago
Quartile Score
Civil and Structural Engineering Q3
Computer Science Applications Q3
Materials Science (miscellaneous) Q3
Modeling and Simulation Q3
Software Q3
Scopus
Cite Score
340/243=1,4
Scopus
Cite Score Rank
Civil and Structural Engineering 219/318 (Q3)
Computer Science Applications 487/693 (Q3)
General Materials Science 316/455 (Q3)
Modeling and Simulation 217/290 (Q4)
Software 307/389 (Q4)
Scopus
SNIP
1,09
Scopus
Cites
321
Scopus
Documents
67
Days from submission to acceptance 136
Days from acceptance to publication 239
Acceptance
Rate
48%

 

2019  
Scimago
H-index
10
Scimago
Journal Rank
0,262
Scimago
Quartile Score
Civil and Structural Engineering Q3
Computer Science Applications Q3
Materials Science (miscellaneous) Q3
Modeling and Simulation Q3
Software Q3
Scopus
Cite Score
269/220=1,2
Scopus
Cite Score Rank
Civil and Structural Engineering 206/310 (Q3)
Computer Science Applications 445/636 (Q3)
General Materials Science 295/460 (Q3)
Modeling and Simulation 212/274 (Q4)
Software 304/373 (Q4)
Scopus
SNIP
0,933
Scopus
Cites
290
Scopus
Documents
68
Acceptance
Rate
67%

 

Pollack Periodica
Publication Model Hybrid
Submission Fee none
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Subscription fee 2022 Online subsscription: 327 EUR / 411 USD 321
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Pollack Periodica
Language English
Size A4
Year of
Foundation
2006
Volumes
per Year
1
Issues
per Year
3
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1788-1994 (Print)
ISSN 1788-3911 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Jun 2022 0 0 0
Jul 2022 0 0 0
Aug 2022 0 0 0
Sep 2022 0 0 0
Oct 2022 0 0 0
Nov 2022 0 112 50
Dec 2022 0 2 1