Modeling 3 variable equation
You want to fit the model $H = \beta_0 + \beta_1 T + \beta_2 H + \epsilon$

The standard way to enter the data to fit this problem is to enter 3 columns, one for T, one for F, one for H.

T    F     H
20  8179    40
30  8044    40
40  7923    40
20  8343    60
30  8250    60
40  8130    60
20  8528    80
30  8430    80
40  8320    80   

In R, the model can be fitted with the command:
lm(H~T+F)

Without checking the appropiatemes of the model, the result is:
Coefficients:
(Intercept)   $\;\;\;\;\;$         T     $\;\;\;\;\;\;\;\;\;\;\;\;\;$      F
  -845.4072 $\;\;\;\;\;$    1.1911   $\;\;\;\;\;$    0.1056
with Rsqr= 0.9958.

When F = 8179 and T = 20.5, the predicted value of H = -845.4072 + 1.1911*20.5 + 0.1056*8179 =  42.39791