```python import numpy as np from scipy.integrate import odeint def model(y, t, m, g): h, v = y dhdt = v dvdt = (m*g - 5*v - 120*h) / m return [dhdt, dvdt] t = np.linspace(0, 10, 1000) # time grid m = 1.0 # mass h0 = 100.0 # initial height v0 = 0.0 # initial velocity g = 9.8 # acceleration due to gravity # solve ODE y0 = [h0, v0] sol = odeint(model, y0, t, args=(m, g)) # extract h(t) and v(t) h = sol[:, 0] v = sol[:, 1] ``` ### Explanation This code snippet is designed to simulate the motion of an object under the influence of gravity and a damping force. Here's a breakdown of the components: 1. **Imports**: - `numpy` as `np` for numerical operations. - `odeint` from `scipy.integrate` to solve ordinary differential equations (ODEs). 2. **Function Definition**: - `model(y, t, m, g)`: Defines the differential equations governing the system. - `y` is the state vector `[h, v]`, where `h` is height and `v` is velocity. - `t` is time. - `m` is mass. - `g` is gravitational acceleration. - The function returns `[dhdt, dvdt]`, which are the derivatives of height and velocity. 3. **Parameters and Initialization**: - `t`: A time grid from 0 to 10 seconds with 1000 points. - `m`: Mass of the object (1.0 kg). - `h0`: Initial height (100 meters). - `v0`: Initial velocity (0 m/s). - `g`: Gravitational acceleration (9.8 m/s²). 4. **Solving the ODE**: - `y0`: Initial conditions `[h0, v0]`. - `sol`: Solution of the ODE system using `odeint` with `model`, initial