Application of Differential Equation

Application of Differential Equation

Komal MiglaniUpdated on 02 Jul 2025, 06:37 PM IST

Differential equations have various applications across various fields due to their ability to model systems and processes. Here, we will discuss the growth and decay problems because this is very helpful in analyzing the growth of bacteria and in the decay of radioactive materials. Differential equations are used in various disciplines, such as biology, economics, physics, chemistry, and engineering.

This Story also Contains

  1. What is a Differential Equation?
  2. Applications of differential equation
  3. Solved Examples Based On Applications of Differential Equations
  4. Summary
Application of Differential Equation
Application of Differential Equation

In this article, we will cover the applications of differential equations. This concept falls under the broader category of differential equations. It is not only essential for board exams but also for competitive exams like the Joint Entrance Examination (JEE Main), and other entrance exams such as SRMJEE, BITSAT, WBJEE, BCECE, and more. Over the last ten years of the JEE Main exam (from 2013 to 2023), a total of six questions have been asked on this concept, including one in 2013, one in 2014, one in 2020, one in 2021, and two in 2022.

$$
\begin{aligned}
& x^2+x+1=0 \\
& \sin x+\cos x=0 \\
& x+y=9 \\
& x \frac{d y}{d x}+2 y=0
\end{aligned}
$$
... (1)

What is a Differential Equation?

A differential equation is an equation involving one or more terms and the derivatives of one dependent variable with respect to the other independent variable.

Differential equation: dy/dx = f(x)

Where “x” is an independent variable and “y” is a dependent variable

Example of differential equation: $x \frac{d y}{d x}+2 y=0$
The above-written equation involves variables as well as the derivative of the dependent variable $\mathrm{y}$ with respect to the independent variable $\mathrm{x}$. Therefore, it is a differential equation.

Applications of differential equation

Differential equations are used in a variety of disciplines, such as biology, economics, physics, chemistry, and engineering.

Growth and Decay Problem:

Let the amount of substance (or population) that is either growing or decaying is denoted by N(t). if we assume the time rate of change of this amount of substance, dN / dt, is proportional to the amount of substance present, then

$\frac{d N}{d t}=k N \quad$ or $\quad \frac{d N}{d t}-k N=0$

Where k is the constant of proportionality, we are assuming that N(t) is a differentiable, hence continuous, function of time.

Newton's Law of Cooling:

According to Newton, the cooling of a hot body is proportional to the temperature difference between its temperature T and the temperature T0 of its surroundings. This statement can be written as:

dT/dt ∝ (T – T0)…………(1)

This is the form of a linear differential equation.

Introducing a proportionality constant k, the above equation can be written as:

dT/dt = k(T – T0) …………(2)

Here, T is the temperature of the body and t is the time,

T0 is the temperature of the surroundings,

dT/dt is the rate of cooling of the body

Some other applications are:

1) They are also used to describe the change in return on investment over time.

2) They are used in the field of medical science for modelling cancer growth or the spread of disease in the body.

3) The movement of electricity can also be described with the help of it.

4) They help economists in finding optimum investment strategies.

5) The motion of waves or a pendulum can also be described using these equations.

Recommended Video Based on Applications of Differential Equations


Solved Examples Based On Applications of Differential Equations

Example 1: In which of the following, a differential equation will not be formed?

(1) The temperature of the body increases at a rate proportional to its instantaneous temperature.

(2) The population of a country increases at a constant rate.

(3) A point moves in a plane such that its distance from its origin is constant.

(4) None of these

Solution:

As we have learned

Application of Homogeneous Differential Equations-

For option (1) $\rightarrow \frac{d T}{d t}=K T$
For option (2) $\rightarrow \frac{d p}{d t}=K$
For option (3) $\rightarrow x^2+y^2=K$

Here, (1) and (2) are differential equations but (3) is not.

Hence, the answer is the option (3).

Example 2: The rate at which a substance cools in moving air is proportional to the difference between the temperature of substance0 and that of the surroundings. If the temperature of the surrounding is 290 K and the substance cools from 370 K to 330 K in 10 min, then after what time from the initial, temperature will be 295 K?

Solution:

As we have learnt,

Temperature Problems -

$\frac{d T}{d t}=-k\left(T-T_m\right)$

- wherein

K is the proportionality constant

T = Temperature of body

$T_m=$ Temperature of Surrounding
Let at time ' $t$ ', temperature is $T$.
So,
$
-\frac{\mathrm{d} T}{\mathrm{~d} t}=k(T-290) \Rightarrow \frac{d T}{T-290}=-k d t
$

On integrating, we get

$\begin{aligned} & \ln (T-290)=k t+c \\ & \text { At } t=0, T=370 \Rightarrow c=\ln 80 \\ & \Rightarrow \ln (T-290)=-k t+\ln (80) \\ & \text { Also, at } t=10, T=330 \Rightarrow \ln 40=-10 k+\ln 80 \\ & \Rightarrow 10 k=\ln 2 \Rightarrow K=\frac{1}{10} \ln 2 \\ & \Rightarrow \ln (T-290)=\left(-\frac{1}{10} \ln 2\right) t+\ln 80 \\ & \text { Now when } T=295 K \text { then } \ln 5=-\frac{t \ln 2}{10}+\ln 80 \\ & \Rightarrow \frac{t \ln 2}{10}=\ln 16 \Rightarrow t=40\end{aligned}$

Hence, the required answer is 40 mins.

Example 3: The rate of growth of bacteria in a culture is proportional to the number of bacteria present and the bacteria count is 1000 at the initial time $t=0$. The number of bacteria is increased by $20 \%$ in 2 hours. If the population of bacteria is 2000 after $\frac{k}{l o g}\left(\frac{6}{5}\right)$ hours, then $\left(\frac{k}{\log _e 2}\right)^2$ is equal to:
Solution:

Initial bacteria count = 1000

20% bacteria increased in 2 hours = 1200

$
\begin{aligned}
& \frac{\mathrm{dB}}{\mathrm{dt}}=\lambda \mathrm{B} \\
& \Rightarrow \int_{1000}^{1200} \frac{\mathrm{dB}}{\mathrm{B}}=\lambda \int_0^2 \mathrm{dt} \\
& \Rightarrow \lambda=\frac{1}{2} \ln \left(\frac{6}{5}\right) \\
& \int_{1000}^{2000} \frac{\mathrm{dB}}{\mathrm{B}}=\frac{1}{2} \ln \left(\frac{6}{5}\right) \int_0^{\mathrm{T}} \mathrm{dt} \\
& \Rightarrow \mathrm{T}=\frac{2 \ln 2}{\ln \left(\frac{6}{5}\right)} \\
& \Rightarrow \mathrm{k}=2 \ln 2 \\
& \left(\frac{\mathrm{k}}{\log _{\mathrm{e}} 2}\right)^2=\left(\frac{2 \ln 2}{\log _{\mathrm{e}} 2}\right)^2=4
\end{aligned}
$
$\ln 2 a$ and $\log _e 2$ is same thing

Hence, the answer is 4.

$\text { Example 4: At present, a firm is manufacturing } 2000 \text { items. It is estimated that the rate of change of production } \mathrm{P} \text { w.r.t. additional number of workers } x \text { is given by } \frac{d P}{d x}=100-12 \sqrt{x} \text {. If the firm employs } 25 \text { more workers, then the new level of production of items is: } $

Solution:

$\begin{aligned} & \frac{d P}{d x}=100-12 \sqrt{x} \\ & \Rightarrow \int d P=\int 100 d x-\int 12 \sqrt{x} d x \\ & \Rightarrow P=100 x-\frac{12 x^{3 / 2}}{3 / 2}+C \\ & \Rightarrow P=100 x-8 x^{3 / 2}+C \\ & \text { For } \mathrm{x}=0, \mathrm{P}=2000 \\ & 2000=C \ldots(1)\end{aligned}$
$\begin{aligned} & \text { and for } \mathrm{x}=25 \\ & P^{\prime}=100(25)-8(25)^{3 / 2}+2000=3500\end{aligned}$

Hence, the required answer is 3500.

Example 5: The population of a certain country is known to increase at a rate proportional to the number of people presently living in the country. If after two years, the population has doubled and after four years population is 20,000, then initially population was

Solution:

Let at time $t$, and $N$ be the number of population at that time, So
$
\begin{aligned}
\frac{\mathrm{d} N}{\mathrm{~d} x} & =k N \\
\Rightarrow \frac{\mathrm{d} N}{N} & =k d t
\end{aligned}
$

So, on integrating we get,
$
\ln N=k t+c
$

Let the initial population is $N_0$ at $t=0$
$
\Rightarrow c=\ln N_0 \Rightarrow \ln N-\ln N_0=k t \Rightarrow \frac{N}{N_0}=e^{k t} \Rightarrow N=N_0 e^{k t}
$

It is given, after two years, the population is doubled, So
$
\begin{aligned}
& 2 N_0=N_0 e^{k \cdot 2} \Rightarrow e^{2 k}=2 \Rightarrow 2 k=\ln 2 \Rightarrow k=\frac{1}{2} \ln 2 \\
& \therefore N=N_0 \cdot e^{\frac{1 \ln 2}{2}}
\end{aligned}
$

Given, after four years population is 20,000 , So
$
20000=N_0 \cdot e^{2 \ln 2} \Rightarrow 4 N_0=20000 \Rightarrow N_0=5000
$

Hence, the required answer is 5000.

Summary

We concluded that the differential equation is very important in real life. It helps to simplify complex algorithms and provides a detailed view of how the process occurs at every step. Differential equations play an important role in scientific research and in economics.

Frequently Asked Questions (FAQs)

Q: What is the role of differential equations in modeling economic growth and business cycles?
A:
Differential equations are crucial in modeling economic growth and business cycles. The Solow-Swan model, a fundamental growth model, uses a differential equation to describe how capital accumulation, labor force growth, and technological progress affect economic output over time. More complex models like the IS-LM model use systems of differential equations to represent the interactions between interest rates, investment, and national income. These models help economists understand long-
Q: How are differential equations applied in the study of neural networks and brain function?
A:
Differential equations play a vital role in modeling neural networks and brain function. The Hodgkin-Huxley model, a system of nonlinear differential equations, describes how action potentials are initiated and propagated in neurons. On a larger scale, neural field theories use integro-differential equations to model the activity of large populations of neurons. These models help neuroscientists understand how information is processed and transmitted in the brain, how neural oscillations arise, and how different brain regions interact. By analyzing these equations, researchers gain insights into cognitive processes, neurological disorders, and the development of artificial neural networks for machine learning applications.
Q: How do differential equations help in understanding population dynamics in ecology?
A:
Differential equations are fundamental in modeling population dynamics in ecology. Beyond simple exponential growth models, more complex equations like the logistic growth model, dN/dt = rN(1-N/K), account for carrying capacity (K) and provide insights into how populations approach equilibrium. Predator-prey models, like the Lotka-Volterra equations, use systems of differential equations to describe interactions between species. These models help ecologists understand and predict population trends, assess the impact of environmental changes, and develop conservation strategies.
Q: How do differential equations apply to the study of waves and acoustics?
A:
In the study of waves and acoustics, differential equations describe how waves propagate through different media. The wave equation, ∂²u/∂t² = c²∇²u, where u is the wave amplitude, t is time, and c is wave speed, is a fundamental PDE in this field. It models various types of waves, including sound waves, electromagnetic waves, and water waves. In acoustics, more specific equations like the Helmholtz equation are used to analyze sound fields in enclosed spaces. By solving these equations, engineers and physicists can design concert halls with optimal acoustics, develop noise reduction technologies, and understand complex wave phenomena like interference and diffraction.
Q: What is the role of differential equations in understanding and predicting weather patterns?
A:
Differential equations are at the core of numerical weather prediction. The Navier-Stokes equations, along with thermodynamic equations and the continuity equation, form a system of PDEs that describe atmospheric dynamics. These equations model how air pressure, temperature, humidity, and wind velocities change over time and space. By solving these equations numerically using initial conditions from current weather observations, meteorologists can forecast future weather conditions. The complexity of these equations and the chaotic nature of weather systems explain why long-term predictions become less accurate and why small changes in initial conditions can lead to significantly different outcomes.
Q: How are differential equations used in modeling traffic flow?
A:
Differential equations are fundamental in traffic flow modeling. Continuum models use PDEs to describe how traffic density and velocity change over time and space. For example, the LWR (Lighthill-Whitham-Richards) model uses a conservation law equation to relate traffic flow to density. More complex models might include systems of PDEs accounting for multiple lanes or driver behavior. These models help traffic engineers optimize road designs, develop efficient traffic control strategies, and predict congestion patterns. By solving these equations, researchers can simulate traffic scenarios and evaluate the impact of various interventions, contributing to smarter urban planning and traffic management.
Q: What is the significance of eigenvalues and eigenvectors in solving systems of differential equations?
A:
Eigenvalues and eigenvectors are crucial in analyzing systems of linear differential equations. They help in understanding the long-term behavior of solutions without explicitly solving the equations. Eigenvalues determine the rates of growth or decay of different components of the solution, while eigenvectors indicate the directions of these components. This analysis is particularly important in stability analysis, where negative eigenvalues indicate stable solutions. In applications like vibration analysis or population dynamics, eigenvalues and eigenvectors provide insights into natural frequencies and modes of the system, helping engineers and scientists predict and control system behavior.
Q: How do differential equations help in understanding and designing control systems?
A:
In control systems engineering, differential equations model the dynamics of systems and their responses to inputs. For example, a simple position control system might be described by a second-order differential equation relating position to input force. The transfer function, a key concept in control theory, is derived from these differential equations. Engineers use techniques like the Laplace transform to analyze these equations and design controllers that ensure stability and desired performance. This application of differential equations is crucial in developing everything from thermostats to complex industrial processes and autonomous vehicles.
Q: What is the role of differential equations in modeling climate change?
A:
Differential equations are essential in climate modeling. They describe how various factors like temperature, atmospheric composition, and ocean currents change over time and interact with each other. For example, energy balance models use differential equations to relate the Earth's temperature to factors like solar radiation and greenhouse gas concentrations. More complex climate models involve systems of PDEs that account for atmospheric and oceanic circulation patterns. By solving these equations numerically, climate scientists can make predictions about future climate trends, assess the impact of human activities, and evaluate potential mitigation strategies.
Q: How are differential equations applied in signal processing?
A:
In signal processing, differential equations model how signals change over time or space. The heat equation, for instance, can be used to model the diffusion of a signal. Fourier analysis, which decomposes signals into sums of sinusoidal components, is closely related to solving certain differential equations. In digital signal processing, difference equations (discrete analogs of differential equations) are used to design filters and analyze discrete-time signals. Understanding and applying differential equations in this context is crucial for developing communication systems, audio processing algorithms, and image enhancement techniques.