Optimization of an active heat engine

被引:14
|
作者
Gronchi, Giulia [1 ]
Puglisi, Andrea [1 ,2 ]
机构
[1] Univ Roma Sapienza, Dipartimento Fis, Piazzale Aldo Moro 2, I-00185 Rome, Italy
[2] CNR, Ist Sistemi Complessi, Piazzale Aldo Moro 5, I-00185 Rome, Italy
关键词
MAXIMUM POWER; COLORED-NOISE; EFFICIENCY; SYSTEMS; MODEL;
D O I
10.1103/PhysRevE.103.052134
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
Optimization of heat engines at the microscale has applications in biological and artificial nanotechnology and stimulates theoretical research in nonequilibrium statistical physics. Here we consider noninteracting overdamped particles confined by an external harmonic potential, in contact with either a thermal reservoir or a stochastic self-propulsion force (active Ornstein-Uhlenbeck model). A cyclical machine is produced by periodic variation of the parameters of the potential and of the noise. An exact mapping between the passive and the active model allows us to define the effective temperature T-eff (t), which is meaningful for the thermodynamic performance of the engine. We show that T-eff (t) is different from all other known active temperatures, typically used in static situations. The mapping allows us to optimize the active engine, regardless of the values of the persistence time or self-propulsion velocity. In particular, through linear irreversible thermodynamics (small amplitude of the cycle), we give an explicit formula for the optimal cycle period and phase delay (between the two modulated parameters, stiffness and temperature) achieving maximum power with Curzon-Ahlborn efficiency. In the quasistatic limit, the formula for T-eff (t) simplifies and coincides with a recently proposed temperature for stochastic thermodynamics, bearing a compact expression for the maximum efficiency. A point, which has been overlooked in recent literature, is made about the difficulty in defining efficiency without a consistent definition of effective temperature.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Design and optimization of a thermoacoustic heat engine using reinforcement learning
    Mumith, Jurriath-Azmathi
    Karayiannis, Tassos
    Makatsoris, Charalampos
    INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES, 2016, 11 (03) : 431 - 439
  • [42] Heat transfer analysis and optimization of engine fins of varying geometry
    Sagar, Pulkit
    Teotia, Puneet
    Sahlot, Akash Deep
    Thakur, H. C.
    MATERIALS TODAY-PROCEEDINGS, 2017, 4 (08) : 8558 - 8564
  • [43] Multi-objective optimization of Stirling heat engine with various heat and mechanical losses
    Xu, Haoran
    Chen, Lingen
    Ge, Yanlin
    Feng, Huijun
    Energy, 2022, 256
  • [44] Multi-objective optimization of Stirling heat engine with various heat and mechanical losses
    Xu, Haoran
    Chen, Lingen
    Ge, Yanlin
    Feng, Huijun
    ENERGY, 2022, 256
  • [45] Performance optimization of a solar driven heat engine with finite-rate heat transfer
    Sogut, OS
    Durmayaz, A
    RENEWABLE ENERGY, 2005, 30 (09) : 1329 - 1344
  • [46] POWER OPTIMIZATION OF AN EXTRATERRESTRIAL, SOLAR-RADIANT STIRLING HEAT ENGINE
    BLANK, DA
    WU, C
    ENERGY, 1995, 20 (06) : 523 - 530
  • [47] Modelling of a spark ignition engine for power-heat production optimization
    Descieux, Damien
    Feidt, Michel
    ECOS 2006: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, VOLS 1-3, 2006, : 1137 - +
  • [48] Optimization of a Thermomagnetic Heat Engine for Harvesting Low Grade Thermal Energy
    Zeeshan
    Mehmood, Muhammad Uzair
    Cho, Sungbo
    ENERGIES, 2021, 14 (18)
  • [49] A dynamic model for the efficiency optimization of an oscillatory low grade heat engine
    Markides, Christos N.
    Smith, Thomas C. B.
    ENERGY, 2011, 36 (12) : 6967 - 6980
  • [50] Optimization of heat transfer and efficiency of engine via air bubble injection inside engine cooling system
    Zavaragh, Hadi Ghasemi
    Kaleli, Aliriza
    Afshari, Faraz
    Amini, Ali
    APPLIED THERMAL ENGINEERING, 2017, 123 : 390 - 402