Worked examples — Inertia tensor — principal axes, principal moments
2.1.22 · D3· Physics › Analytical Mechanics › Inertia tensor — principal axes, principal moments
Yeh page parent topic ke liye drill-ground hai. Hum ek scenario matrix banate hain — ek checklist jo har tarah ki situation cover karti hai jo yeh topic exam mein daal sakta hai — phir examples karte hain jab tak har box tick na ho jaye. Agar "eigenvalue" ya "principal axis" jaisi phrases shaky lagti hain, toh Eigenvalues and eigenvectors aur Symmetric and orthogonal matrices kisi doosre tab mein khule rakho.
The scenario matrix
Kisi bhi number se pehle, yeh poora case-space hai. Har worked example us cell ke saath tagged hai jo woh cover karta hai.
| Cell | Case class | Isme kya tricky hai | Example |
|---|---|---|---|
| A | Masses on an axis (degenerate, ) | us line ke baare mein zero moment jis par woh hain | Ex 1 |
| B | Off-diagonal negative, tilted | product of inertia sign, non-parallel | Ex 2 |
| C | Off-diagonal positive (opposite quadrant layout) | ka sign quadrant ke saath flip karta hai | Ex 3 |
| D | Full symmetry (, spherical top) | har axis principal, isotropic | Ex 4 |
| E | Continuous body + Parallel axis theorem shift | aur axis centre se hokar nahin | Ex 5 |
| F | Symmetric top () real word problem | do equal, ek different; frisbee | Ex 6 |
| G | Fully asymmetric , exam twist | genuine cubic, trace/det checks | Ex 7 |
| H | Continuous box, 3 distinct + thin-rod limit | sab distinct, phir ek dimension | Ex 8 |
Matrix ke axes hain: off-diagonals ka sign (zero / plus / minus), eigenvalues ki degeneracy (sab distinct / do equal / sab equal), aur input type (point masses / continuous / limiting). Aath examples milke har woh combination hit karte hain jo exams mein aata hai.
Ex 1 — Cell A: masses sitting on an axis (the degenerate case)
Forecast: abhi andaza lagao — -axis (jis line par masses hain) ke baare mein moment of inertia kya hai?

Figure padho: do amber dots cyan horizontal line (-axis) par exactly baithe hain. Notice karo ki kisi bhi dot aur us line ke beech koi perpendicular gap nahin hai — yahi visible zero gap neeche banayega.
- compute karo. Dono masses ke liye aur hai, isliye har term hai aur . Yeh step kyun? mass ki squared-distance from the -axis measure karta hai; masses us axis par zero distance par hain — exactly wahi zero gap jo figure mein dikha.
- compute karo. Waisa hi . Yeh step kyun? -axis se distance hai; ke baare mein spin karne par masses radius par swing karte hain.
- Products of inertia: (sab hain); waisa hi . Yeh step kyun? Koi bhi product jisme ek coordinate uniformly zero ho, woh vanish karta hai.
- Assemble karo. Yeh already diagonal hai, isliye principal moments hain aur principal axes sirf hain.
Verify: upar bataya gaya trace property use karo (har mass ke liye ke saath), trace , aur yeh ke barabar hona chahiye. ✓
Ex 2 — Cell B: off-axis pair, tilted (negative product)
Forecast: agar tum isko -axis ke baare mein spin karo, toh kya , ke along point karta hai? Pehle haan/nahin andaza lagao.

Figure padho: amber dots dashed cyan line ke aas-paas hain. White arrow spin hai jo seedha ke along point kar raha hai; amber arrow resulting hai jo fourth quadrant mein neeche point kar raha hai. White aur amber arrows ke beech visible angle hi is example ka poora point hai — , se tilted hai.
- Diagonal entries. Full definition se shuru karo. Har mass ka hai (dono -plane mein hain), isliye term drop ho jaati hai aur . Waisa hi , aur . Yeh step kyun? Har diagonal apni axis se squared-distance hai; yahan sab masses ke liye hai, isliye general formula in-plane terms tak collapse ho jaata hai, aur dono masses same par hain.
- Product . Pehla mass: . Doosra: . Sum , isliye . Yeh step kyun? Dono masses aise quadrants mein hain jahan aur ka sign same hai, isliye har — product pile hota hai, aur definition mein minus sign ko negative banata hai.
- ke saath Assemble karo:
- ke baare mein spin karo: , isliye . Yeh step kyun? Matrix times a column vector; off-diagonal ek component ko existence mein khींch laata hai — yahi figure mein amber arrow ka downward tilt hai.
mein ek -component hai jabki humne sirf ke baare mein spin kiya — parallel nahin. Yahi Rigid body rotation hai jo tumhe kaatne aa jaata hai.
Verify: block ke eigenvalues aur hain; ke saath principal moments hain. Trace . ✓
Ex 3 — Cell C: opposite-quadrant layout product sign ko flip karta hai
Forecast: masses doosri diagonal () par move ho gaye. Andaza lagao ki apna sign rakhta hai ya flip karta hai.

Figure padho: pichle wale se compare karo — amber dots ab dashed cyan line (doosri diagonal) par hain, ek dot second quadrant mein aur ek fourth mein. Yeh mirror-image placement exactly wahi hai jo product of inertia ka sign flip karti hai, jaise figure mein amber caption batata hai.
- Diagonal entries unchanged hain. , , . Yeh step kyun? Squaring sign ko khatam kar deti hai: , isliye masses Ex 2 ki tarah hi har axis se same distance par hain.
- Product . Pehla mass: . Doosra: . Sum , isliye . Yeh step kyun? Ab masses wahan hain jahan aur ke opposite signs hain, isliye ; definition mein minus isko positive mein flip kar deta hai.
- Assemble karo:
- Eigenvectors switch diagonal karte hain. block ka eigenvalue hai ke liye aur hai ke liye. Yeh step kyun? Masses ab ke along line up hain; woh line zero-moment principal axis hai (uske bahar unka koi extent nahin) — figure mein dashed line.
Verify: eigenvalues ; trace . Ex 2 se compare karo, sirf off-diagonal sign aur isliye axis ki direction badli — geometry mirror, physics mirror. ✓
Ex 4 — Cell D: full symmetry, the spherical top
Forecast: is cube ke kitne principal axes hain — teen, ya infinitely many?
- Off-diagonals symmetry se vanish karte hain. kyunki par har mass element ke liye ek mirror wala par hai jo cancel karta hai. Yeh step kyun? Symmetric and orthogonal matrices: body ki ek reflection symmetry corresponding products ko zero force karti hai.
- Ek diagonal moment. . Yeh step kyun? Standard uniform-cube integral; per axis box-inertia result hai.
- Symmetry se teeno equal hain:
- Toh . Phir har ke liye. Yeh step kyun? Identity ka scalar multiple sab rotations ke saath commute karta hai, isliye centre se hoti har axis principal hai.
Verify: principal moments ; trace . ✓
Ex 5 — Cell E: continuous body + parallel axis shift
Forecast: kya end-axis moment centre wale se bada ya chhota hoga, aur kitna?
- Centre moment by integration. Linear density ke saath, Yeh step kyun? Har element -axis se distance par hai; squared-distance hai; rod par integrate karo.
- Number it:
- Parallel axis theorem se end par shift karo. End centre se door hai: Yeh step kyun? Theorem centre value reuse karne deta hai re-integrate kiye bina. Yeh sirf centre of mass se bahar ki taraf kaam karta hai.
Verify: , . End se direct integration ✓ — theorem se match karta hai.
Ex 6 — Cell F: symmetric top (word problem, a frisbee)
Forecast: ek disc ka ek obvious axis hai (centre se, flat face ke perpendicular). Andaza lagao ki do in-plane moments equal hain ya different.
- Setup confirm karo. Hamare chosen axes se disc -plane mein hai aur sab jagah hai, isliye perpendicular-axis theorem apply hota hai jisme -axis perpendicular wala hai. Yeh step kyun? Theorem sirf -plane mein ek lamina ke liye valid hai; placement batana hi ise use karne ka license deta hai.
- Perpendicular (spin) axis . Ek disc ke liye, . Yeh step kyun? Standard disc result; radius par har mass ring contribute karta hai.
- In-plane axes perpendicular-axis theorem se: flat lamina ke liye , aur circular symmetry se , isliye . Yeh step kyun? Disc flat hai, isliye perpendicular-axis theorem apply hota hai; symmetry phir ko do in-plane axes ke beech evenly split kar deti hai.
- Numbers ke saath:
- Interpretation. Do equal, ek distinct: ek symmetric top. Perpendicular axis distinguished wala hai — wahan spin karo aur flight stable hai (isliye ek thrown frisbee face-flat spin karta hai, Euler's equations of rigid body motion ke according).
Verify: , ; check karo ✓ (perpendicular-axis theorem holds).
Ex 7 — Cell G: fully asymmetric tensor, exam twist
Forecast: ek axis already decoupled hai. Andaza lagao kaun sa, aur kya baaki do mix karte hain.
- Block structure padho. Pehli row/column clean hai (sirf diagonal par ), isliye direction already ek principal axis hai moment ke saath. Yeh step kyun? Ek zero row aur column ka matlab hai mix nahin karta — , yahi ke liye eigenvalue equation hai.
- block diagonalize karo. Characteristic equation ya . Yeh step kyun? eigenvalue condition hai; block cubic ko isolated (step 1 se) aur is quadratic mein factorise karta hai.
- Block ke eigenvectors. ke liye: , direction . ke liye: , direction . Normalise karo: (moment ) aur (moment ). Yeh step kyun? Axis direction nikalne ke liye har root ke liye solve karo, phir unit length mein normalise karo.
- Collect aur order karo. Convention ke saath:
- along ,
- along ,
- along . Yeh step kyun? Har eigenvalue ko uske normalised eigenvector ke saath pair karna diagonalization complete karta hai; teen principal axes hain.
Verify: trace ko ke barabar hona chahiye ✓. Determinant ko ke barabar hona chahiye ✓.
Ex 8 — Cell H: general box (3 distinct moments) aur uska thin-rod limit
Forecast: teen different side lengths ke saath, andaza lagao ki koi do moments equal aate hain. Phir andaza lagao kaun sa moment collapse karta hai jab do sides wire ban jaate hain.
(a) The general box — Cell G-style but continuous, sab distinct.
- Off-diagonals zero hain. Har coordinate plane ek symmetry plane hai, isliye ; face-parallel axes already principal hain. Yeh step kyun? Wahi reflection argument jo cube (Ex 4) mein tha, lekin unequal sides ka matlab diagonal entries alag hongi.
- Numbers plug karo ke saath: Yeh step kyun? Direct substitution. Teeno alag hain — yahi woh "three distinct eigenvalues, zero off-diagonals" cell hai jo matrix ne promise kiya tha.
- Order karo: — ek asymmetric top (sab moments distinct).
(b) The thin-rod limit.
- bhejo (wire along mein collapse karo). . Yeh step kyun? -axis se squared-distance hai; -axis par padi ek wire ki woh distance zero hoti hai — wahi degeneracy jo Ex 1 mein mili thi.
- Do transverse moments. aur . Yeh step kyun? Jab toh sirf length bachti hai; dono perpendicular axes ab ek identical thin rod of length dekhte hain, isliye unhe same moment dena hi hoga — top symmetric ho gaya.
- Conclusion. ke saath box ke three-distinct moments collapse ho kar ban jaate hain: ek zero (wire ki apni line ke baare mein spin) aur do equal — exactly thin-rod result. Degeneracy limit se create hoti hai.
Verify: box moments (sab distinct); limit mein , milta hai, jo ke saath hai. ✓
Recap
Recall Kaun si cell mein sign flip tha, aur kyun?
Cells B vs C ::: same distances (isliye equal diagonals) lekin masses same-sign vs opposite-sign quadrants mein, ko se mein flip karte hue aur principal axis ko se par rotate karte hue.
Recall Har "Verify" ne kaun sa invariant use kiya?
The trace ::: frame-independent hai, saath mein — dono quick sanity checks hain jo diagonalization ke baad bhi survive karte hain.
Recall Kab
har axis principal hoti hai? Jab (Ex 4 cube) ::: tab aur sab ke liye.
Scenario matrix ka har cell A–H ab worked hai. Agle, inhe Euler's equations of rigid body motion se connect karo yeh dekhne ke liye ki yeh principal moments spin ki time evolution ko kaise drive karte hain.