Exercises — Heat equation (parabolic) 1D — derivation from Fourier's law
4.7.8 · D4· Maths › Partial Differential Equations › Heat equation (parabolic) 1D — derivation from Fourier's law

Upar di gayi figure is poore page ke liye mental picture hai: horizontal axis rod ke saath position (metres) hai jisme length m hai, vertical axis ek frozen instant par temperature (kelvin, K) hai. Ek hill par curvature negative hoti hai isliye (yeh thanda hota hai, red arrow neeche); ek valley par curvature positive hoti hai isliye (yeh garm hota hai, mint arrow upar); ek straight stretch par curvature zero hoti hai isliye time mein kuch bhi nahi badalta.
Level 1 — Recognition
Problem 1.1 (L1)
In mein se kaun sa PDE 1D heat equation hai? Har ek ke liye batao kyun hai ya kyun nahi.
Recall Solution
(a) ✅ Yeh heat equation hi hai: ek time derivative , curvature , positive diffusivity . (b) ❌ Do time derivatives — yeh wave equation hai; yeh oscillate karta hai, smooth nahi karta. (c) ❌ Backward heat equation. Minus sign curvature ko galat direction mein drive karta hai (hills badhte hain, valleys gehri hoti hain) — yeh bahut zyada unstable hai aur heat ko time mein ulta chalata hai. (d) ❌ Time bilkul nahi — yeh Laplace equation hai, steady state.
Problem 1.2 (L1)
Ek rod ki diffusivity hai. Ek point par temperature graph ek bump hai jisme curvature hai. Kya woh point garm ho raha hai ya thanda, aur kitni tez?
Recall Solution
Apply karo . Kyunki hai, point K/s ki dar se thanda ho raha hai. Ek bump () hamesha thanda hota hai — iske neighbours thande hain, isliye heat bahar nikl jaati hai.
Level 2 — Application
Problem 2.1 (L2)
Diya gaya aur , par nikalo.
Recall Solution
Step 1 — curvature. . (Do baar kyun? Kyunki equation par feed karti hai.) Step 2 — evaluate. par, , isliye . Step 3 — time rate. K/s. Thanda ho raha hai (ek bump ke rising flank par).
Problem 2.2 (L2)
Verify karo ki , ko satisfy karta hai.
Recall Solution
Step 1 — time derivative. (exponential par chain rule). Step 2 — space derivatives. Space mein do baar differentiate kyun karein? Kyunki equation ko curvature ke against compare karti hai, aur curvature second spatial derivative hai — isliye hume do steps deep jaana padega. Pehla step: ( ka derivative hai; inner se chain-rule factor hai). Doosra step: ( ka derivative hai). Sine/cosine ka har differentiation wavenumber ka ek aur factor nikalta hai, isliye constant tak badh jaata hai. Step 3 — compare. . ✅ Decay rate exactly hai.
Problem 2.3 (L2)
Ek copper rod: W/m·K, kg/m³, J/kg·K. compute karo (dekho Thermal Diffusivity and Material Properties).
Recall Solution
Copper bahut achha conduct karta hai lekin energy bhi bahut store karta hai, isliye moderate hai, bahut bada nahi.
Level 3 — Analysis
Problem 3.1 (L3)
Decaying mode ke liye, dikhao ki decay rate ki tarah badhti hai. Kaun sa mode sabse tez marta hai: ya ? Kis factor se?
Recall Solution
Step 1 — plug in. aur , isliye ✅. kya hai? Notice karo ki poora solution hai jisme number exponent mein baitha hai. Hum ko decay rate kehte hain kyunki ek shrinking exponential hai: jitna bada , utni tez factor zero ki taraf collapse hoti hai. Isliye literally measure karta hai "yeh mode kitni tezi se marta hai." Step 2 — rates compare karo. . Conclusion: mode 9 guna tez decay karta hai. Physically kyun? Bada = tighter wiggles = tez curvature ; tez curvature faster smoothing drive karta hai. Heat equation pehle fine detail mitaata hai.
Problem 3.2 (L3)
Steady state , satisfy karta hai. par , aur koi source nahi, nikalo.
Recall Solution
Step 1 — steady matlab koi time change nahi. . Step 2 — do baar integrate karo. (ek straight line — yahi ek curvature-free profile hai). Step 3 — ends fit karo. ; . Answer: . par, K.
Level 4 — Synthesis
Problem 4.1 (L4)
Equation ko rescale karo. se shuru karke length ki rod par, dimensionless variables , introduce karo. Dikhao ki equation ban jaati hai (diffusivity gayab ho jaati hai).
Recall Solution
Step 1 — time mein chain rule. . Step 2 — space mein chain rule (do baar). , isliye . Step 3 — substitute karo. . cancel karo: . Matlab: har rod same rod hai jab tum time ko (natural diffusion time) ki units mein measure karo. Isliye bade objects equilibrate hone mein zyada time lete hain — yeh Separation of Variables for the Heat Equation ki ek headline hai.
Problem 4.2 (L4)
Do known solutions combine karo. Dikhao ki solve karta hai, aur , par evaluate karo.
Recall Solution
Step 1 — linearity. Heat equation linear hai, isliye solutions ka sum bhi solution hai; har term pehle se ise satisfy karta hai (rates aur Problem 3.1 se). Step 2 — term one check karo. ke liye: ; aur , isliye ✅. Step 3 — term two explicitly check karo. ke liye, hand-wave mat karo — wohi do derivatives chalaao. Time: (exponent saamne aa jaata hai). Space, do baar: , phir ( ka har -derivative ek factor nikalta hai, isliye do se milta hai). se multiply karo: ✅. Rate exactly ka case hai. Step 4 — , par evaluate karo. , : K. Yeh superposition exactly ek two-term Fourier series hai.
Level 5 — Mastery
Problem 5.1 (L5)
Fundamental solution. Dikhao ki Gaussian satisfy karta hai. Yeh origin par heat ke point-burst ka temperature hai.
Recall Solution
Exactly yeh shape kyun? Ek point-burst mein koi built-in length scale nahi hoti, isliye profile sirf natural diffusion width se spread ho sakta hai (Problem 4.1 se, lengths ki tarah scale hote hain). Do consequences bake in hain: exponent mein width honi chahiye, aur prefactor hona chahiye taaki total heat constant rahe jab bump flatten aur widen ho. Ab hum ise directly verify karte hain — koi ansatz gymnastics nahi, bas woh do derivatives jo equation maangti hai. Step 1 — time derivative. Likho constant ke saath. Product differentiate karo ( se milta hai; exponent ka -derivative hai): Step 2 — space derivatives. , aur phir se differentiate karo ( aur ka product): Step 3 — se multiply karo. . ✅ Edge case . Shape dekho: width , isliye bump infinitely narrow ho jaata hai, jabki prefactor , isliye infinitely tall ho jaata hai — phir bhi uske neeche area fixed rehta hai. Yeh limiting object Dirac delta hai: "saari heat ek point par dher ki gayi." Isliye Gaussian woh solution hai jiska initial condition ek point-burst hai, aur kisi bhi ke liye yeh ek smooth spread-out bump hai. Isliye ise fundamental solution / heat kernel kehte hain — woh building block jisse Fourier Series Solutions aur general initial data assemble kiye jaate hain.
Problem 5.2 (L5)
Energy kabhi nahi badhti (stability). par insulated ends ( dono ends par) wali rod ke liye, define karo . Dikhao ki .
Recall Solution
Step 1 — energy differentiate karo. (PDE use ki). Step 2 — integrate by parts. . Step 3 — boundary term khatam karo. Insulated ends se milta hai par, isliye . Step 4 — conclude karo. , kyunki aur . Matlab: temperature profile ka "size" sirf shrink ho sakta hai ya stable reh sakta hai — diffusion smooths, never sharpens ka ek rigorous chehra. Yeh Conservation Laws and Continuity Equation ka energy-method cousin hai.
Connections
- Parent: Heat equation derivation
- Fourier's Law of Conduction
- Conservation Laws and Continuity Equation
- Classification of PDEs (elliptic, parabolic, hyperbolic)
- Separation of Variables for the Heat Equation
- Fourier Series Solutions
- Wave Equation (hyperbolic) 1D
- Laplace Equation (steady-state heat)
- Thermal Diffusivity and Material Properties