Channel
@Analysis_of_Structures
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
3,030subscribers
+34 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001266820109 |
|---|---|
| Type | Channel |
| Username | @Analysis_of_Structures |
| Created | Between 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 5 September 2026 |
| Measurements held | 11 |
| Confirmed unchanged | 1 time, most recently 5 September 2026 |
| On Telegram | t.me/Analysis_of_Structures |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Sept 2026, 05:36 | 3,030 | +5 |
| 1 Sept 2026, 19:25 | 3,025 | +5 |
| 29 Aug 2026, 13:37 | 3,020 | -3 |
| 26 Aug 2026, 04:42 | 3,023 | -1 |
| 23 Aug 2026, 08:08 | 3,024 | +2 |
| 19 Aug 2026, 11:16 | 3,022 | -6 |
| 16 Aug 2026, 18:45 | 3,028 | +10 |
| 13 Aug 2026, 01:24 | 3,018 | +24 |
| 9 Aug 2026, 18:13 | 2,994 | +2 |
| 7 Aug 2026, 03:05 | 2,992 | -4 |
| 6 Aug 2026, 13:21 | 2,996 | first reading |
20 posts held, back to 11 December 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 15 July 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
80 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 86.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 69 | 86.3% | |
| 👍 | 3 | 3.75% | |
| 🥰 | 3 | 3.75% | |
| 👏 | 2 | 2.50% | |
| 👌 | 1 | 1.25% | |
| 😍 | 1 | 1.25% | |
| 🙏 | 1 | 1.25% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 17 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 80 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 11 December 2024 to 15 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
شروع تحلیل 2 سرفصل تحلیل 2 ✅ روش شیب-فت: مفاهیم و مبانی اثبات چند نکته و. مثال مثال جالب و کاربردی و نکات تکمیلی ✅ روش تقریبی: تحلیل تحت بار ثقل تحلیل تحت بار ثقل، ادامه: تیرها و قابهای کوچک تحلیل قابها تحت بارهای ثقلی و جانبی تحلیل خرپاها تحت بارهای ثقلی و جانبی، تحلیل تقریبی سیستم مهاربندی، تحلیل تقریبی سیستم دوگانه ویدئو نه تحلیل سازه 2: ✅ تقارن در سازه ها و بارها ویدئو ده تحلیل سازه 2: ✅ روش پخش لنگ…
❤3
شروع سرفصل تحلیل 1: ویدئو یک تحلیل سازه 1: ✅ لزوم و ضرورت درس تحلیل سازهها ویدئو دو تحلیل سازه 1: ✅ پایداری و ناپایداری سازه ها ویدئو سه تحلیل سازه 1: ✅ معینی و درجه نامعنی سازه ها ✍🏻 تمرین از پایداری و درجه نامعنی سازه ها ویدئو چهار تحلیل سازه 1: ✅ رسم سریع دیاگرامها ویدئو پنج تحلیل سازه 1: ✅ رسم سریع دیاگرامها با کمک شکل تغییر یافته تیر تحت بار ویدئو شش تحلیل سازه 1: ✅ رسم سریع دیاگرامها با کمت…
❤9
سؤال بسیار هوشمندانهای است و ذهن بسیاری از دانشجویان مهندسی را درگیر کرده است. بیایید منطق پشت این تمرینها و نیاز واقعی آینده را با هم تحلیل کنیم: هدف واقعی تمرین روی تبدیل واحدها و تحلیل ابعادی چیست؟ ۱. تقویت درک شهودی و فیزیکی: هدف اصلی این است که شما به جای حفظ فرمول، حس فیزیکی کمیتها را درک کنید. اینکه بدانی یک پاسکال فشار چقدر است، یا یک نیوتن نیرو چقدر کوچک است، به شما در طراحی و تشخیص خطا کمک میکند. ه…
❤10👍2👏2
سوال من از دیپسیک: آیا واقعا با وجود هوش مصنوعی نیازه من دانشجوی مهندسی برم و در خصوص تبدیل واحدها و دیمانسیونها کلی تمرین بکنم که مثلا فوری بتونم کیلوگرم بر سانتی متر مربع رو به پاسکال تبدیل کنم؟ چون حس میکنم این مهارت واقعا نیاز نیست
❤7
پاسخ دیپسیک: این نگرانی کاملاً بهجا و قابل درک است، اما خبر خوب این است که شما با آگاهی از این چالش، اولین و مهمترین گام را برداشتهاید. هوش مصنوعی قرار نیست انسان را جایگزین کند، بلکه ابزاری است که نحوه کار و زندگی ما را متحول میکند. کلید موفقیت، سازگاری و تکامل مهارتهای شماست. در اینجا راهکارهای عملی برای آیندهproof شدن شما آورده شده: ۱. مهارتهایی که هوش مصنوعی به سختی جایگزین میکند را پرورش دهید: · ت…
❤9😍1
پرسش از دیپسیک: چکار کنم که هوش مصنوعی باعث نشه من در اینده ای نزدیک ادم بدردنخوری بشم؟
❤5
#هوش_مصنوعی با سرعت در حال متحول کردنه چگونه بهجای این که قربانی این ابزار بشیم اونو به خدمت بگیریم برای رشد بیشتر و درامد بیشتر و توانمندی بیشتر؟ امروز در کلاس تحلیل سازهها فرصتی پیش اومد تا بصورت مصداقی روی لزوم چند توانمندی صحبت کنیم: تبدیل سریع و درست یکاها به همدیگه مثلا در همین راستا بحث مفصلی در کلاس شد و در راستای تأیید برخی توصیهها توی کلاس بعدش چند سؤال از دیپسیک پرسیدم که اینجا به اشتراک میذارم.
❤10
Photo, posted without a caption
🥰3❤1
Photo, posted without a caption
❤3
در نیمه دوم این ویدئو یک مثال ساده ولی بسیار مهم حل شده است: سهم تغییرشکل برشی در تیرهای عمیق این موضوع کاربردهای زیادی دارد از جمله در دیوارهای با مصالح بنایی در ویدئوی زیر، انجام محاسبات دستی برای یک مثال که با نرمافزار حل شده، دقت زیاد نتایج مدل المان محدودی را با محاسبات دستی نشان میدهد. چنین مهارتی در محاسبات و مدلسازی لازمهی کارهای حرفهای و طراحی میباشد: https://t.me/tabeshpour
❤2
https://t.me/Analysis_of_Structures
❤1
https://t.me/Analysis_of_Structures
❤4
Showing the 12 most recent of 20 posts we hold for @Analysis_of_Structures. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 5 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 5 September 2026 — this entry's latest reading, not the date you are reading this.
“تحلیل سازهها (۱و۲)” (@Analysis_of_Structures), 3,030 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/Analysis_of_Structures.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.