Abstract

Within the context of finite-time thermodynamics (FTTs) some models of convective atmospheric cells have been proposed to calculate the efficiency of the conversion of solar energy into wind energy and also for calculating the surface temperature of the planets of the solar system. One of these models is the Gordon and Zarmi (GZ) model, which consists in taking the sun-earth-wind system as a FTT-cyclic heat engine where the heat input is solar radiation, the working fluid is the earth's atmosphere and the energy in the winds is the work produced. The cold reservoir to which the engine rejects heat is the 3K surrounding universe. In the present work we apply the GZ-model to investigate some features of the convective zone of the sun by means of a possible structure of successive convective cells along the well-established convective region of the sun. That is, from 0.714 𝑅𝑆 up to 𝑅𝑆 being 𝑅𝑆 the radius of the sun. Besides, we estimate the number of cells of the model, the possible size of the cells, their thermal efficiency, and also their average power output. Our calculations were made by means of two FTT regimes of performance: the maximum power regime and the maximum ecological function regime. Our results are in reasonable agreement with others reported in the literature.

1. Introduction

The problem of thermal balance between the planets of the solar system and the sun under a finite-time thermodynamics approach has been treated by several authors [1–8]. In some of these articles the question of the conversion of solar energy into wind energy is also treated. In particular, De Vos [3] demonstrated that cosmic radiation, starlight, and moonlight can be neglected for the thermal balance of any of the planets of the solar system and only the following quantities have an influence: the incident solar influx or solar constant 𝐼sc, the planet’s albedo 𝜌, and the greenhouse effect of the planet’s atmosphere crudely evaluated by means of a coefficient 𝛾. This coefficient can be taken as the normalized greenhouse effect introduced by Raval and Ramanathan in [9]. When only the global thermal balance between the sun and a planet is considered, one can roughly obtain the planet’s surface temperature assumed as a uniform temperature 𝑇𝑝. If the conversion of solar energy into wind energy is to be modeled, it is necessary to involve at least two representative atmospheric temperatures for making the creation of work possible; that is, to take the planet’s atmosphere as a working fluid that converts heat into mechanical work. In 1989, Gordon and Zarmi [1] introduced a FTT-model taking the sun-earth-wind system as a FTT-cyclic heat engine where the heat input is solar radiation, the working fluid is the earth’s atmosphere, and the energy in the winds is the work produced; the cold reservoir to which the engine rejects heat is the 3K surrounding universe. By means of this simplified model, Gordon and Zarmi were able to obtain reasonable values for the annual average power in the earth’s winds and for the average maximum and minimum temperatures of the atmosphere, without resorting to detailed dynamic models of the earth’s atmosphere, and without considering any other effect (such as earth’s rotation, earth’s orbital motion around the Sun, and ocean currents). Later, De Vos and Flater [2] extended the GZ model to take into account the wind energy dissipation by means of a maximum power criterion. This model was extended by De Vos and van der Wel [4, 5] by constructing a model based in convective Hadley cells. All the models used in [1–5] are endoreversible ones in the sense of FTT [10], that is, all irreversibilities are located in the exchanges between the engine and the external world. The GZ model was later studied under a nonendoreversible approach and by using the so-called ecological optimization criterion [6, 7]. This approach [11] consists of maximizing a function 𝐸 that represents a good compromise between high-power output and low-entropy production. The function 𝐸 is given by𝐸=π‘ƒβˆ’π‘‡extΔ𝑆𝑒,(1) where 𝑃 is the power output of the cycle, Δ𝑆𝑒 the total entropy production (system plus surroundings) per cycle, and 𝑇ext is the temperature of the cold reservoir. This optimization criterion for the case of the so-called Curzon-Ahlborn cycle [12], for instance, leads to a cycle configuration such that for maximum 𝐸 it produces around 75% of the maximum power and only about 25% of the entropy produced in the maximum power regime [13]. By means of employing this criterion in a nonendoreversible GZ model, the authors of [6] also found reasonable values for the annual average power of the winds and for the extreme temperatures of the earth’s troposphere. Later, the non-endoreversible GZ model was applied to calculate the surface temperature of planets of the solar system [8], considering two regimes of performance: maximum power regime and maximum ecological function regime. In this work, we apply the GZ model to the convective zone of the sun which is located between 0.714 𝑅𝑆 and 𝑅𝑆 [14]. Our FTT approach leads to a possible structure of the convective region of the sun consisting in approximately sixteen coupled cells. It is important to remark that these sixteen convective Carnotian cells are only a kind of idealized cells, thermodynamically equivalent to the complex structure of the actual convective zone of the sun. The paper is organized as follows: in Section 2, we present a brief review of the GZ model for the convective cells under both the maximum power and the ecological function regimes. In Section 3, we applied the GZ model to the convective zone of the sun and finally in Section 4 we present some concluding remarks.

2. Endoreversible GZ Model for Atmospheric Convection

The endoreversible GZ model is based on annual average quantities and thus it does not represent actual convective cells but a kind of annual virtual cell that takes into account the global thermodynamic restrictions over the convection as a dominant energy transfer mechanism in the air (which has a large Rayleigh number). Besides, this kind of model must only be taken as one that producing better upper bounds than those calculated by means of classical equilibrium thermodynamics, which is one of the main purposes of FTT.

2.1. Maximum Power Regime

In Figure 1, a schematic view of a simplified sun-earth-winds system as a heat engine cycle is depicted. This cycle consists of four branches: (1) two isothermal branches, one in which the atmosphere absorbs solar radiation at low altitudes and one in which the atmosphere rejects heat at high altitudes to the universe and (2) two intermediate instantaneous adiabats [10] with rising and falling currents. In [15], it was shown that a Curzon-Ahlborn FTT cycle in the endoreversible limit with instantaneous adiabats is reached for large compression ratios. In the GZ virtual cells, it is feasible to consider that this condition is fulfilled. According to GZ, this oversimplified Carnot-like engine corresponds very approximately to the global scale motion of wind in convective cells. Below, we use all of GZ model’s assumptions.

For example, the work performed by the working fluid in one cycle π‘Š, the internal energy of the working fluid π‘ˆ, and the yearly average solar radiation flux π‘žπ‘  are expressed per unit area of the earth’s surface. The temperatures of the four-branch cycle are taken as follows: 𝑇1 is the working fluid temperature in the isothermal branch at the lowest altitude, where the working fluid absorbs solar radiation for half of the cycle. During the second half of the cycle, heat is rejected via black-body radiation from the working fluid at temperature 𝑇2 (highest altitude of the cell) to the cold reservoir at temperature 𝑇ext (the surrounding 3K universe). In the GZ model, the objective is to maximize the work per cycle (average power) subjected to the endoreversibility constraint [10], that is,Δ𝑆int=ξ€œπ‘‘π‘œ0ξƒ―π‘žπ‘ ξ€Ίπ‘‡(𝑑)βˆ’πœŽ4(𝑑)βˆ’π‘‡4extξ€»(𝑑)𝑇(𝑑)𝑑𝑑=0,(2) where Δ𝑆int is the change of entropy per unit area, 𝑑0 is the time of one cycle, 𝜎 is the Stefan-Boltzmann constant (5.67Γ—10βˆ’8W/m2K4), and π‘žπ‘ , and 𝑇 are functions of time 𝑑, taken as [1] ⎧βŽͺ⎨βŽͺβŽ©π‘‡π‘‡(𝑑)=1𝑑;if0≀𝑑≀02,𝑇2𝑑;if02≀𝑑≀𝑑0,π‘žπ‘ (⎧βŽͺ⎨βŽͺβŽ©π‘‘π‘‘)=0;if02≀𝑑≀𝑑0,𝐼sc(1βˆ’πœŒ)2𝑑;if0≀𝑑≀02,(3) in the same way, 𝑇ext=3K for 0≀𝑑≀𝑑0, with 𝐼sc the yearly average solar constant (1373 W/m2) and 𝜌=0.35 [2], the effective average albedo of the earth’s atmosphere. The GZ model maximizes the work per cycle π‘Š, taken from the first law of thermodynamics:ξ€œΞ”π‘ˆ=βˆ’π‘Š+𝑑00ξ€½π‘žπ‘ (𝑇𝑑)βˆ’πœŽ4(𝑑)βˆ’π‘‡4ext(𝑑)𝑑𝑑=0,(4) by denoting average values as,𝑇𝑇=1+𝑇22,𝑇𝑛=𝑇𝑛1+𝑇𝑛22,π‘žπ‘ =𝐼𝑠𝑐(1βˆ’πœŒ)4,(5) where 𝑛 is an integer with values 𝑛=3 or 4. The factor of 1/4 arises from a factor of 1/2 to account for the day/night difference and a geometric factor of 1/2 to account for the earth’s cross section, which is intercepted by solar radiation, as opposed to the corresponding hemispherical surface area of the earth. From (4) and (5) and taking into account the constraint given by (2), GZ construct the following Lagrangian 𝐿; 𝐿=𝑇4ξ‚Έπ‘ž(𝑑)+πœ†π‘ (𝑑)𝑇(𝑑)βˆ’πœŽπ‘‡3ξ‚Ή(𝑑),(6) where πœ† is a Lagrange multiplier. The Euler-Lagrange formalism will be used, by using πœ•πΏ(𝑑)/πœ•π‘‡(𝑑)=0, GZ found the following values for the earth’s atmosphere: 𝑇1=277K, 𝑇2=192K, and 𝑃max=π‘Šmax/𝑑0=17.1W/m2. These numerical values are not so far from β€œactual” values, which are π‘ƒβ‰ˆ7W/m2 [16], 𝑇1=290K (at ground level), and 𝑇2β‰ˆ195K (at an altitude of around 75–90 Km). However, as GZ assert, their power calculation must be taken as an upper bound due to several idealizations in their model. In [6], another endoreversible case was analyzed in which the tropopause layer with 𝑇ext=200K was used as cold reservoir. In this case, the following Lagrangian was used:𝐿(𝑑)=π‘žπ‘ +πœŽπ‘‡4extβˆ’πœŽπ‘‡4ξƒ¬βˆ’π›Όπ‘žπ‘ π‘‡1βˆ’πœŽξ€·π‘‡31+𝑇32ξ€Έ2βˆ’πœŽπ‘‡4extξ‚΅1𝑇1+1𝑇2ξ‚Άξƒ­,(7) with 𝛼 a Lagrange multiplier. By numerically solving πœ•πΏ(𝑑)/πœ•π‘‡(𝑑)=0, they obtained 𝑇1=293.387K and 𝑇2=239.267K, which are excellent values for convective cells restricted to the troposphere. If these temperature values are substituted in the expression for the average power (see [6])𝑃=π‘žπ‘ +πœŽπ‘‡4extβˆ’πœŽπ‘‡4,(8) a value of 𝑃=10.758W/m2 is obtained, which is a good value for the wind power [16].

2.2. Ecological Function Regime

As De Vos and Flater [2] state, no mechanism guarantees that the atmosphere maximizes the wind power. In fact, some authors [17–19] have recognized that the earth’s atmosphere operates at nearly its maximum efficiency; thus, from an FTT point of view, an ecological-type criterion seems feasible. This is due to the properties of the 𝐸 function, which at its maximum value represents an austere compromise between power and entropy production, additionally leading to a high efficiency [11, 13]. This ecological criterion, as previously occurred with the concepts of power output and efficiency [20], has also been used in the context of irreversible thermodynamics [21–23]. In particular, in [7] the so-called ecological criterion was applied to the GZ model. This criterion consists in maximizing equation (1). By means of the second law of thermodynamics, first, we calculate Δ𝑆𝑒, the total entropy change per cycle (system plus surroundings),Δ𝑆𝑒=ξ€œπ‘‘00ξƒ―βˆ’π‘žπ‘ ξ€Ίπ‘‡(𝑑)+𝜎4(𝑑)βˆ’π‘‡4extξ€»(𝑑)𝑇(𝑑)𝑑𝑑.(9) From (3), we obtainΔ𝑆𝑒=ξ€œπ‘‘00/2ξƒ―βˆ’π‘žπ‘ (𝑑)𝑇1𝑇+𝜎31βˆ’π‘‡4ext𝑇1βˆ’ξ€œξƒͺ𝑑𝑑𝑑0𝑑0/2ξƒ―πœŽξƒ©π‘‡42βˆ’π‘‡4ext𝑇extξƒͺ𝑑𝑑.(10) Thus, the total entropy production is given by [7, 8],Ξ£=Δ𝑆𝑒𝑑0β‰ˆπ‘žπ‘ π‘‡1+𝜎2𝑇31+𝑇42𝑇extξƒͺ,(11) here, we have used the approximation π‘žπ‘ β‰«πœŽπ‘‡4ext(223W/m2≫4.59Γ—10βˆ’6W/m2) with 𝑇ext=3K. So, the ecological function 𝐸 for this case is𝐸=π‘žπ‘ βˆ’πœŽπ‘‡4+𝑇extπ‘žπ‘ π‘‡1βˆ’πœŽπ‘‡ext2𝑇31+𝑇42𝑇extξƒͺ.(12) By using (12) and the constraint given by (2), we proposed the following Lagrangian function 𝐿𝐸:𝐿𝐸=π‘žπ‘ βˆ’πœŽπ‘‡4+𝑇extπ‘žπ‘ π‘‡1βˆ’πœŽπ‘‡ext2×𝑇31+𝑇42𝑇extξƒͺξ‚Έβˆ’π›Όπ‘žπ‘ π‘‡1βˆ’πœŽπ‘‡3ξ‚Ή,(13) with 𝛼 being the Lagrange multiplier. By substituting the values of π‘žπ‘ , 𝜎, and 𝑇ext and numerically solving πœ•πΏ(𝑑)/πœ•π‘‡(𝑑)=0, we find 𝑇1=294.08K,𝑇2=109.54K and 𝑃=6.89W/m2, which are reasonable values for 𝑇1 and 𝑃, but not for 𝑇2. However, if we use as a cold reservoir, the tropopause layer with 𝑇ext=200K, we can now use the Lagrangian function: [24],𝐿𝐸=π‘žπ‘ +πœŽπ‘‡4extβˆ’πœŽπ‘‡4+ξƒ©π‘žπ‘ +πœŽπ‘‡4ext2ξƒͺ𝑇ext𝑇1βˆ’πœŽπ‘‡ext2𝑇31+𝑇42𝑇extξƒͺβˆ’πœŽπ‘‡4ext2ξƒ¬βˆ’π›½π‘žπ‘ π‘‡1βˆ’πœŽξ€·π‘‡31+𝑇32ξ€Έ2+πœŽπ‘‡4extξ‚΅1𝑇1+1𝑇2ξ‚Άξƒ­,(14) with 𝛽 a Lagrange multiplier. By using again the Euler-Lagrange formalism, we numerically obtain 𝑇1=303K,𝑇2=219K, and 𝑃=7W/m2 which are very good values, for 𝑇1, 𝑇2, and 𝑃. Besides, these values are restricted to typical values in the troposphere, where the climatic phenomena occurs. It is important to note that the power values (6.89W/m2 and 7W/m2), which were calculated by the means of the ecological function, were deduced without considering the greenhouse effect (𝛾 coefficient). When the later is taken into account, the values of 𝑃 are bigger than 7W/m2 [7, 8]. These scenarios lead to larger upper bounds for the wind’s power permitting an energy excess for other relevant dissipative processes such as ocean currents and biological structuring.

3. The GZ Model Applied to the Convective Zone of the Sun

The core of the sun goes from 0 to 0.2 𝑅𝑆, where 𝑅𝑆 (6.96Γ—108m[14]) is the radius of the sun. The radiative zone embraces the region between 0.2 𝑅𝑆 and 0.714 𝑅𝑆 and beyond that lies the convective zone. The later is estimated to have a width of approximately 0.286 𝑅𝑆 [14]. In (8) and (11) the input data were π‘žπ‘  and 𝑇ext, the thermal energy and the temperature of the surrounding cold thermal bath for the earth’s atmospheric cells, respectively. In the case of the convective zone of the sun, first we will use the maximum power criterion. In Figure 2, we show the heat fluxes balance for the convective zone of the sun. Then, by using (2), (3), (4), and (5) we obtain the following Lagrangian functional: 𝐿𝑇1,𝑇2ξ€Έ=π‘ž,πœ†π‘ 2+πœŽπ‘‡4ext2βˆ’πœŽ2𝑇41+𝑇42ξ€Έξƒ¬π‘žβˆ’πœ†π‘ 2𝑇1βˆ’πœŽ2𝑇31+𝑇32ξ€Έ+πœŽπ‘‡4ext2ξ‚΅1𝑇1+1𝑇2ξ‚Άξƒ­,(15) where πœ† is a Lagrange multiplier, 𝑇ext=3K, 𝑇1=2.18Γ—106K [14] is the temperature of the spherical layer at 0.714 𝑅𝑠 and π‘žπ‘ =πœŽπ‘‡41 the input thermal energy at the lower layer of the convective zone. The energy transport through the sun can be considered as a β€œsandwich”, that is, there are two regions in which radiation transports the energy separated by a region where convection transports it [25]. Strictly speaking, π‘žπ‘  should be calculated by means of a diffusive model based on kinetic theory of gases [25]. However, for simplicity, in our thermodynamic model we take the 0.714 𝑅𝑠 layer at 𝑇1β‰ˆ2Γ—106K as a blackbody radiant system (π‘žπ‘ =πœŽπ‘‡41, see Figure 2). The radiation emitted by this layer is rapidly absorbed by the gases at the bottom of the convective zone. For the definition of 𝑇2, see Figure 2. By using the Euler-Lagrange formalism over the Lagrangian of (15), that is, πœ•πΏ(𝑑)/πœ•π‘‡(𝑑)=0, we obtain the following equations:𝑇51βˆ’πœ†πœŽξƒ©π‘žπ‘ 4+3𝜎4𝑇41+πœŽπ‘‡4ext4ξƒͺ𝑇=0,523βˆ’πœ†4𝑇42+𝑇4ext4ξƒͺ=0.(16) By eliminating πœ† from these equations and by using the restriction given by (2), we obtain 𝑇42ξ€·4𝑇31𝑇2+𝑇42βˆ’3𝑇41ξ€Έβˆ’π‘‡4ext𝑇41+𝑇42ξ€Έ=0.(17) In this equation, the only unknown variable is 𝑇2. Then, we numerically solve (17) to obtain 𝑇2, the temperature of the upper bound for the first convective cell starting from 𝑇1=2.187761Γ—106K [14]. Our next step is to take the obtained 𝑇2 value of the first cell as the temperature of the lower layer of the following successive cell. This new 𝑇2 value is taken as 𝑇1 in (17) and then we calculate a new 𝑇2 for the second cell. For the following successive cells we use the same recursive procedure until to reach a final 𝑇2 coinciding approximately with the well-known value of the average surface temperature of the sun, which is π‘‡π‘†β‰ˆ5780K [14].

In Table 1 we show that after 16 successive Carnotian convective cells we reach a final 𝑇2β‰ˆ6000K. Table 1 shows our results for Carnotian cells performing in the maximum power regime. As one can see in this Table (third column), the widths of the cells are decreasing toward the outer regions. The total width is around 0.280 𝑅𝑠 which is not so far of the value 0.286 𝑅𝑠 given by other sun models [26]. If we take as the mode of thermodynamic performance of the sun’s convective cells the so-called maximum ecological regime [11], in a similar way as (15), then we obtain the following Lagrangian functional:𝐿𝐸𝑇1,𝑇2ξ€Έ=π‘ž,πœ†π‘ 2𝑇1βˆ’ext𝑇1ξ‚Ά+πœŽπ‘‡4extξ€·π‘‡βˆ’πœŽ41+𝑇42ξ€Έ+πœŽπ‘‡ext2𝑇31+𝑇32ξ€Έβˆ’πœŽπ‘‡ext2𝑇41𝑇2+𝑇42𝑇1ξƒͺβˆ’πœŽπ‘‡5ext2ξ‚΅1𝑇1+1𝑇2ξ‚Άξƒ¬π‘žβˆ’πœ†π‘ 2𝑇1βˆ’πœŽ2𝑇31+𝑇32ξ€Έβˆ’πœŽπ‘‡4ext2ξ‚΅1𝑇1+1𝑇2ξ‚Άξƒ­.(18) By using the Euler-Lagrange formalism over the Lagrangian of (18), that is, πœ•πΏπΈ(𝑑)/πœ•π‘‡(𝑑)=0 and following a similar procedure as in the case of (17), we obtain8𝑇4ext𝑇1𝑇2𝑇41+𝑇42ξ€Έ+3𝑇5ext𝑇51+𝑇52ξ€Έ+𝑇ext𝑇2ξ€·4𝑇81+13𝑇51𝑇32βˆ’16𝑇31𝑇52βˆ’7𝑇82ξ€Έβˆ’π‘‡1𝑇52ξ€·32𝑇31𝑇2+8𝑇42βˆ’24𝑇41ξ€Έ=0.(19) Similarly to (15), the only unknown variable in this equation is 𝑇2. Following a similar numerical procedure as in the case of maximum power conditions, we can calculate a convective cell structure. In Table 2 we present the numerical results for the maximum ecological function. We can see in Table 2 that with 16 successive Carnotian convective cells we can reach a final 𝑇2β‰ˆ6000K.

Our results in Table 2 again show that the width of the cells decrease with increasing radius. The total width in this case is around 0.2859 𝑅𝑠 which is practically the value 0.286 𝑅𝑠 given by other sun models [26].

A remarkable fact observed in Tables 1 and 2 (third column) is that between the cell number 10 and 16, the vertical linear sizes are between 2247 Km and 247 Km, respectively. These are values near to those reported for the linear sizes of granules in [25], which are typically around 900–1000 Km, reaching their largest values up to 2000 Km in diameter. On the other hand, in the highest convective cell of our model, the average power has a value of 5.7Γ—109erg/cm2s, which is of the order of the power reported in [25] for convection in the photosphere (which is 7Γ—109erg/cm2s). Our highest cell overlaps with photosphere. This result is also of the order of the power reported for a mixing length theory of convection in [25], which is 10-20Γ—109erg/cm2s. Clearly, our oversimplified model coincides with those reported in [25] in that the energy transported by convection must increase rapidly as we go below the surface region of the convective zone. Finally, it is very interesting that all 16 cells in Tables 1 and 2 have practically the same thermal efficiency, πœ‚β‰ˆ0.307.

4. Concluding Remarks

In the present work we have used a simplified finite-time thermodynamic method to describe the global thermal properties of the convective zone of the sun. This method was previously used by Gordon and Zarmi to describe convective motions of the air in the earth’s atmosphere. These authors assert that this FTT-approach corresponds very approximately to the global scale motion of the wind in convective cells. However, it is necessary to remark that convective cells of this kind of FTT-models are only virtual cells performing by unit area and yearly averages. Thus, they only represent the global thermodynamic properties stemming from the first and second laws of thermodynamics; that is, kind of thermodynamically equivalent cells that only captures global average quantities and discards any other dynamical detail. Nevertheless, all these simplifications permit to obtain reasonable values for some thermal quantities associated to the convective zone of the sun. Our simplification is mainly based in taking several spherical virtual layers as black-body radiant surfaces, whose emitted radiation is rapidly absorbed by the opaque gases of the convective zone. This radiant energy is taken as the driver energy of convective cells.

Acknowledgments

This work was supported in part by CONACYT, COFAA, and EDI-IPN-MΓ©xico.