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Beyond the Second Law: An Overview

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Beyond the Second Law

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

The Second Law of Thermodynamics governs the average direction of all non-equilibrium dissipative processes. However it tells us nothing about their actual rates, or the probability of fluctuations about the average behaviour. The last few decades have seen significant advances, both theoretical and applied, in understanding and predicting the behaviour of non-equilibrium systems beyond what the Second Law tells us. Novel theoretical perspectives include various extremal principles concerning entropy production or dissipation, the Fluctuation Theorem, and the Maximum Entropy formulation of non-equilibrium statistical mechanics. However, these new perspectives have largely been developed and applied independently, in isolation from each other. The key purpose of the present book is to bring together these different approaches and identify potential connections between them: specifically, to explore links between hitherto separate theoretical concepts, with entropy production playing a unifying role; and to close the gap between theory and applications. The aim of this overview chapter is to orient and guide the reader towards this end. We begin with a rapid flight over the fragmented landscape that lies beyond the Second Law. We then highlight the connections that emerge from the recent work presented in this volume. Finally we summarise these connections in a tentative road map that also highlights some directions for future research.

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Notes

  1. 1.

    Equilibrium is used here in the thermodynamic sense, and not in the dynamic sense of stationarity.

  2. 2.

    Strictly speaking, the Navier–Stokes equation is only approximate; the (linear) expression for the stress tensor is only valid close to equilibrium.

  3. 3.

    However, Paltridge’s energy balance model still contained a number of ad hoc assumptions and parameterizations (see Herbert and Paillard Chap. 9).

  4. 4.

    The ensemble average is over the probability distribution of microscopic trajectories in phase space (see Sect. 1.4.1).

  5. 5.

    Here L ij is the inverse of the matrix R ij in Table 1.1.

  6. 6.

    An equivalent orthogonality condition for the direction of the generalised fluxes J in force space can be stated in terms of the contours of σ(X).

  7. 7.

    The regime of linear force-flux relations.

  8. 8.

    In Paltridge’s zonally-averaged climate model [4], thermal dissipation is given by σ = Σi J i X i where J i = material heat transport between meridional zones i and i + 1, and X i = 1/T i+1−1/T i is the corresponding inverse temperature difference.

  9. 9.

    The notation is simplified here for clarity. In terms of the notation of Chap. 2, for example, p Γ = p(Γ(0), 0) is the probability of observing the system in an infinitesmal region around Γ(0) at time t = 0, where Γ(t) denotes the phase space vector at time t, and p Γ* = p(Γ*(τ), 0) where Γ*(τ) is obtained from Γ(τ) by reversing all the particle velocities.

  10. 10.

    If δ(i,j) denotes the Kronecker delta function [0 if i ≠ j, 1 if i = j], Eq. (1.2) follows from p(ΩΓ = A) = ΣΓ p Γδ(ΩΓ, A) = [change of variable] ΣΓ p Γ*δ(ΩΓ*, A) = (from Eq. 1.1) ΣΓ p Γexp(–ΩΓ)δ(–ΩΓ, A) = e AΣΓ p Γδ(ΩΓ, –A) = e A p(ΩΓ = –A). Equation (1.3) follows from Gibbs’ inequality: –Σi p ilnp i ≤ –Σi p ilnq i for any probability distributions p i and q i, with equality if and only if p i = q i for all i.

  11. 11.

    In Chap. 3, MaxEnt is used to construct p(f), the probability distribution of macroscopic fluxes f, rather than p Γ; the formalism can be re-expressed in terms of p Γ as shown in [42].

  12. 12.

    Specifically (see Chap. 3), when the non-equilibrium driving force is such that \( \left\langle \Upomega \right\rangle^{\text{C}} > \left\langle \Upomega \right\rangle^{\text{C}}_{ \hbox{min} } , \) then MaxEnt implies \( \left\langle \Upomega \right\rangle = \left\langle \Upomega \right\rangle_{ \hbox{max} } \). Here C denotes a restricted set of stationarity constraints, the nature of which determines the physical nature of \( \left\langle \Upomega \right\rangle^{\text{C}} \) as an entropy production or dissipation functional; \( \left\langle \Upomega \right\rangle^{\text{C}}_{ \hbox{min} } \) and \( \left\langle \Upomega \right\rangle^{\text{C}}_{ \hbox{max} } \) are the lower and upper bounds on \( \left\langle \Upomega \right\rangle^{\text{C}} \).

  13. 13.

    In Chap. 8 and [28], only a spatially-averaged momentum balance constraint is imposed, rather than the full Navier–Stokes equation.

  14. 14.

    The restriction of the analysis in [43] to near-equilibrium systems was pointed out in [46, 47].

  15. 15.

    For an alternative perspective, see Chap. 5.

  16. 16.

    The minimum is along a path in the space of flux states.

References

  1. Schrödinger, E.: What is life? (With mind and matter and autobiographical sketches). CUP, Cambridge (1992)

    Book  Google Scholar 

  2. Maxwell, J.C.: Letter to John William Strutt (1870). In: PM Harman (ed) The scientific letters and papers of James Clerk Maxwell. CUP, Cambridge UK 2, 582–583 (1990)

    Google Scholar 

  3. Paltridge, G.W.: Global dynamics and climate-a system of minimum entropy exchange. Q. J. Roy. Meteorol. Soc. 101, 475–484 (1975)

    Article  Google Scholar 

  4. Paltridge, G.W.: The steady-state format of global climate. Q. J. Roy. Meteorol. Soc. 104, 927–945 (1978)

    Article  Google Scholar 

  5. Paltridge, G.W.: Thermodynamic dissipation and the global climate system. Q. J. Roy. Meteorol. Soc. 107, 531–547 (1981)

    Article  Google Scholar 

  6. Lorenz, R.D., Lunine, J.I., Withers, P.G., McKay, C.P.: Titan, mars and earth: entropy production by latitudinal heat transport. Geophys. Res. Lett. 28, 415–418 (2001)

    Article  Google Scholar 

  7. Hill, A.: Entropy production as a selection rule between different growth morphologies. Nature 348, 426–428 (1990)

    Article  Google Scholar 

  8. Martyushev, L.M., Serebrennikov, S.V.: Morphological stability of a crystal with respect to arbitrary boundary perturbation. Tech. Phys. Lett. 32, 614–617 (2006)

    Article  Google Scholar 

  9. Juretić, D., Županović, P.: Photosynthetic models with maximum entropy production in irreversible charge transfer steps. Comp. Biol. Chem. 27, 541–553 (2003)

    Article  MATH  Google Scholar 

  10. Dewar, R.C., Juretić, D., Županović, P.: The functional design of the rotary enzyme ATP synthase is consistent with maximum entropy production. Chem. Phys. Lett. 430, 177–182 (2006)

    Article  Google Scholar 

  11. Dewar, R.C.: Maximum entropy production and plant optimization theories. Phil. Trans. R. Soc. B 365, 1429–1435 (2010)

    Article  Google Scholar 

  12. Franklin, O., Johansson J., Dewar, R.C. Dieckmann, U., McMurtrie, R.E., Brännström, Å, Dybzinski, R.: Modeling carbon allocation in trees: a search for principles. Tree Physiol. 32, 648--666 (2012)

    Google Scholar 

  13. Martyushev, L.M., Seleznev, V.D.: Maximum entropy production principle in physics, chemistry and biology. Phys. Rep. 426, 1–45 (2006)

    Article  MathSciNet  Google Scholar 

  14. Evans, D.J., Searle, D.J.: The fluctuation theorem. Adv. Phys. 51, 1529–1585 (2005)

    Article  Google Scholar 

  15. Seifert, U.: Stochastic thermodynamics: principles and perspectives. Eur. Phys. J. B 64, 423–431 (2008)

    Article  MATH  Google Scholar 

  16. Sevick, E.M., Prabhakar, R., Williams, S.R., Searles, D.J.: Fluctuation theorems. Ann. Rev. Phys. Chem. 59, 603–633 (2008)

    Article  Google Scholar 

  17. Onsager, L.: Reciprocal relations in irreversible processes I. Phys. Rev. 37, 405–426 (1931)

    Google Scholar 

  18. Onsager, L.: Reciprocal relations in irreversible processes II. Phys. Rev. 38, 2265–2279 (1931)

    Article  MATH  Google Scholar 

  19. Prigogine, I.: Introduction to thermodynamics of irreversible processes. Wiley, New York (1967)

    Google Scholar 

  20. Kohler, M.: Behandlung von Nichtgleichgewichtsvorgängen mit Hilfe eines Extremalprinzips. Z. Physik. 124, 772–789 (1948)

    Article  MathSciNet  MATH  Google Scholar 

  21. Ziman, J.M.: The general variational principle of transport theory. Can. J. Phys. 34, 1256–1273 (1956)

    Article  MathSciNet  Google Scholar 

  22. Ziegler, H.: An Introduction to Thermomechanics. North-Holland, Amsterdam (1983)

    MATH  Google Scholar 

  23. Malkus, W.V.R.: The heat transport and spectrum of thermal turbulence. Proc. R. Soc. 225, 196–212 (1954)

    Article  MathSciNet  MATH  Google Scholar 

  24. Malkus, W.V.R.: Outline of a theory for turbulent shear flow. J. Fluid Mech. 1, 521–539 (1956)

    Article  MathSciNet  MATH  Google Scholar 

  25. Malkus, W.V.R.: Statistical stability criteria for turbulent flow. Phys. Fluids 8, 1582–1587 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  26. Kerswell, R.R.: Upper bounds on general dissipation functionals in turbulent shear flows: revisiting the ‘efficiency’ functional. J. Fluid Mech. 461, 239–275 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  27. Ozawa, H., Shimokawa, S., Sakuma, H.: Thermodynamics of fluid turbulence: a unified approach to the maximum transport properties. Phys. Rev. E 64, 026303 (2001)

    Article  Google Scholar 

  28. Malkus, W.V.R.: Borders of disorders: in turbulent channel flow. J. Fluid Mech. 489, 185–198 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  29. Pascale, S., Gregory, J.M., Ambaum, M.H.P., Tailleux, R.: A parametric sensitivity study of entropy production and kinetic energy dissipation using the FAMOUS AOGCM. Clim. Dyn. 38, 1211–1227 (2012)

    Article  Google Scholar 

  30. Boltzmann, L.: Über die Beziehung zwischen dem zweiten Hauptsatze der mechanischen Wärmetheorie und der Wahrscheinlichkeitsrechnung respektive den Sätzen über das Wärmegleichgewicht. Wien. Ber. 76, 373–435 (1877)

    Google Scholar 

  31. Gibbs, J.W.: Elementary principles of statistical mechanics. Ox Bow Press, Woodridge (1981). Reprinted

    Google Scholar 

  32. Jaynes, E.T.: Information theory and statistical mechanics. Phys. Rev. 106, 620–630 (1957)

    Article  MathSciNet  MATH  Google Scholar 

  33. Jaynes, E.T.: Information theory and statistical mechanics II. Phys. Rev. 108, 171–190 (1957)

    Article  MathSciNet  Google Scholar 

  34. Jaynes, E.T.: Probability Theory: The Logic of Science. In: Bretthorst, G.L. (ed.). CUP, Cambridge (2003)

    Google Scholar 

  35. Houlsby, G.T., Puzrin, A.M.: Principles of hyperplasticity. Springer, London (2006)

    Google Scholar 

  36. Shannon, C.E.: A mathematical theory of communication. Bell Sys. Tech. J. 27, 379–423 and 623–656 (1948)

    Google Scholar 

  37. Shannon, C.E., Weaver, W.: The mathematical theory of communication. University of Illinois Press, Urbana (1949)

    MATH  Google Scholar 

  38. Grandy, W.T. Jr.: Foundations of Statistical Mechanics. Volume II: Nonequilibrium Phenomena. D. Reidel, Dordrecht (1987)

    Google Scholar 

  39. Grandy, W.T. Jr.: Entropy and the time evolution of macroscopic systems. International series of monographs on physics, vol. 141, Oxford University Press, Oxford (2008)

    Google Scholar 

  40. Niven, R.K.: Steady state of a dissipative flow-controlled system and the maximum entropy production principle. Phys. Rev. E 80, 021113 (2009)

    Article  Google Scholar 

  41. Dewar, R.C.: Maximum entropy production as an inference algorithm that translates physical assumptions into macroscopic predictions: Don’t shoot the messenger. Entropy 11, 931–944 (2009)

    Article  Google Scholar 

  42. Dewar, R.C.: Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states. J. Phys. A: Math. Gen. 36, 631–641 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  43. Dewar, R.C.: Maximum entropy production and the fluctuation theorem. J. Phys. A: Math. Gen. 38, L371–L381 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  44. Jaynes, E.T.: The minimum entropy production principle. Ann. Rev. Phys. Chem. 31, 579–601 (1980)

    Article  Google Scholar 

  45. Jupp, T.E., Cox, P.M.: MEP and planetary climates: insights from a two-box climate model containing atmospheric dynamics. Phil. Trans. R. Soc. B. 365, 1355–1365 (2010)

    Article  Google Scholar 

  46. Bruers, S.A.: Discussion on maximum entropy production and information theory. J. Phys. A: Math. Theor. 40, 7441–7450 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  47. Grinstein, G., Linsker, R.: Comments on a derivation and application of the ‘maximum entropy production’ principle. J. Phys. A: Math. Theor. 40, 9717–9720 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  48. Agmon, N., Alhassid, Y., Levine, R.D.: An algorithm for finding the distribution of maximal entropy. J. Comput. Phys. 30, 250–258 (1979)

    Article  MATH  Google Scholar 

  49. Dyson, F.J.: Energy in the universe. Sci. Amer. 225, 51–59 (1971)

    Article  Google Scholar 

  50. Herbert, C., Paillard, D., Dubrulle, B.: Entropy production and multiple equilibria: the case of the ice-albedo feedback. Earth Syst. Dynam. 2, 13–23 (2011)

    Article  Google Scholar 

  51. Thomas, T.Y.: Qualitative analysis of the flow of fluids in pipes. Am. J. Math. 64, 754–767 (1942)

    Article  MATH  Google Scholar 

  52. Paulus, D.M., Gaggioli, R.A.: Some observations of entropy extrema in fluid flow. Energy 29, 2487–2500 (2004)

    Article  Google Scholar 

  53. Martyushev, L.M.: Some interesting consequences of the maximum entropy production principle. J. Exper. Theor. Phys. 104, 651–654 (2007)

    Article  Google Scholar 

  54. Niven, R.K.: Simultaneous extrema in the entropy production for steady-state fluid flow in parallel pipes. J. Non-Equil. Thermodyn. 35, 347–378 (2010)

    Article  MATH  Google Scholar 

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Dewar, R.C., Lineweaver, C.H., Niven, R.K., Regenauer-Lieb, K. (2014). Beyond the Second Law: An Overview. In: Dewar, R., Lineweaver, C., Niven, R., Regenauer-Lieb, K. (eds) Beyond the Second Law. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40154-1_1

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