Abstract
This chapter deals with the validity/limits of the integral transform technique on finite domains. The integral transform technique based upon eigenvalues and eigenfunctions can serve as an appropriate tool for solving the Fourier heat equation, in the case of both laser and electron beam processing. The crux of the method consists in the fact that the solutions by mentioned technique demonstrate strong convergence after the 10 eigenvalues iterations, only. Nevertheless, the method meets with difficulties to extend to the case of non-Fourier equations. A solution is however possible, but it is bulky with a weak convergence and requires the use of extra-boundary conditions. To surpass this difficulty, a new mix approach is proposed with this chapter resorting to experimental data, in order to support a more appropriate solution. The proposed method opens in our opinion a beneficial prospective for either laser or electron beam processing.
Keywords
- non-Fourier equation
- integral transforms technique
- eigenfunctions and values
- experimental data
1. Introduction
1.1 Mathematical background
The heat equation can be solved in a simpler mode
The solution of Fourier equations can be inferred using different mathematical techniques via Green function, integral, Laplace transform, or complex analysis. The predictions of the solutions given by the mentioned methods are of analytical or semianalytical nature and confirm the experimental data for certain situations such as laser–metal interaction.
One basically assumes that the heat waves propagation speed is inversely proportional to the square root of the relaxation time. A smaller relaxation time leads to higher heat speed waves, resulting in a good Fourier approximation. If one requires however a more accurate description of experimental data, one should introduce a more exact method to solve the non-Fourier equation involving a finite heat wave speed.
A mixed solution of the non-Fourier equation combines the theoretical method of finite integral transforms with information from experimental data. Thus, two additional boundary conditions can be imposed, which will lead to a semianalytical solution of the non-Fourier equation. The finite domains of the integral transform method for Fourier equations are eigenfunctions and values, which reach after 10 iterations a quite conform solution for the Fourier equation [3, 4, 5, 6]. This method is applied to the non-Fourier equation, and the final form is obtained, with the support of experimental results.
A new heat transfer model was adopted in order to unify the thermal field distribution in both laser and electron beam processing. An analytical solution using non-Fourier heat equation has been developed corresponding to boundary conditions in the case of material processing. The model has been compared with the experimental data obtained using an in-house developed facility. A simplified and easy-to-use model via MATHEMATICA software stands for the novelty of the current work.
2. Non-Fourier equation
The non-Fourier equation is hyperbolic and can be written as:
Here,
The corresponding boundary conditions are:
Here
and
where
This applies to Eq. (1) with the boundary conditions:
and
Eqs. (7) and (8) corroborate to Eq. (9):
One can deduce, based upon the theory of finite integral transforms, the eigenfunction
where the normalization constant is given by:
One defines:
and
Eq. (1) in this case converts to:
One obtains for
and
as well as:
The − and + signs for
and
Here,
and
Note that Eqs. (12) and (13) discuss the eigenvalues along the
and
Eq. (1) becomes now:
We next applied the direct and inverse Laplace integral transform to solve Eq. (1) in relation to time. C[1] and C[2] stand for the normalizing coefficients with respect to the experimental data. The results are as follows:
and
We finally mention that for an intermediate point in the experimental curve, one has:
With the boundary conditions:
3. Two-temperature model in the non-Fourier version
The two-temperature model (TTM) is based upon two coupled equations:
Here
where
According to the Nolte model [2], one has:
where
Here,
Eq. (3) can be rewritten as:
It follows that:
with
Under the most general form, the heat source reads as:
Here,
In order to make a comparison with experiments, one needs besides analytical description, concrete numerical values. The next step is therefore to estimate the eigenvalues, numerically. For this purpose, Eq. (7) can be solved using the integral transform technique, and eigenfunctions and eigenvalues could be calculated. One has three differential equations as follows (
The final solutions could be achieved on the basis of Eqs. (41)–(43):
The boundary conditions are:
Here,
The solution is obtained via integral transform technique as:
The advantage of Eq. (53) in our model is related to a quick converging series. Thus, after 10 iterations, the solution’s accuracy reaches already 10−2 K in the case of thermal distribution [11].
4. Experimental details
The experimental setup is operated by a Nd:YAG pulsed laser source (
5. Results and discussion
Experiments and simulations were carried out during the heating of a metallic target. The boundary conditions were described by Eq. (28). In all figures, the experimental data are plotted with dots while the simulations are represented by a continuous line. Relaxation time,
The best agreement between theory and experiment was achieved for a relaxation time,
6. Conclusions and outlook
The two-temperature model was generalized to the case of the non-Fourier approach via the electron-phonon relaxation time. Boundary conditions, Eq. (28) for heating and Eq. (29) for cooling, were considered to this purpose. The obtained solutions prove useful for experimental data analysis. The mathematical method belongs to the eigenvalues and functions family, while details on software are available from Ref. [6].
The exact nature of the metallic target (in our case aluminum) could be detected from the electron-phonon relaxation time using integral transform technique mix via acquired experimental data. The method can be extended to any experimental sample (metal) with the high accuracy.
Acknowledgments
CNM, MO, NM, and CR acknowledge for financial support by Romanian Ministry of Research, Innovation and Digitalization, under Romanian National NUCLEU Program LAPLAS VI–contract no. 16N/2019. CNM, NM, CR, and INM thank for the financial support from a grant of the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number ID code RO-NO-2019-0498 and UEFISCDI under the TE_196/2021 and PED_306/2020. M.A.M. received financial support from the European Union’s Horizon 2020 (H2020) research and innovation program under the Marie Skłodowska–Curie grant agreement no. 764935.
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