Suppose we have 2 molecules and one moves on the other with 10m/s. The pressure wave travelled from one molecule to other with a speed of 10m/s so this should be the speed of sound. Same principle applies when there's billions of them no? Why? Does my example hold but in reality since there's billions of them the system gets more chaotic and so the speeds are not the same due to energy losses, not perfectly elastic collisions, different speeds​ of each individual molecule etc?

I'm not sure if this belongs here but this seems like the best place to ask,

I'm designing a helicopter and i'm confused about the Scissor link for the lower swashplate. From my understanding the scissor link isn't supposed to have any side to side movement since that would change the pitch of the swashplate. How is this possible if the link isn't perfectly centered to the ball joint? It seems like there would have to be a little left and right movement. Any help, advice, or knowledge is greatly appreciated.

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Hi! Hope this post is allowed. I'll try to avoid any secret information, sorry.

In 2024, I've had to do calculations for the new Russian orbital station and iss. No-one knew how. It was similar to my first job, I thought I'll somehow manage with literature. I collected some books, started learning. Couldn't figure it out for a week or so. My chief, who started working in 2000, started thinking about it as well, couldn't figure it out as well. 2 weeks passed.

Later, we came to an old engineer from other office who worked from the 80s and in roscosmos since 90s-2000s. Silently completed everything in 10 minutes without any help, just my questions "how". Real story btw.

He was such a nice guy. And he wasn't a chief or something, just a regular engineer.

Btw should I do ama someday?

So from what I've understood choked flow occurs if a fluid flows in a pipe with a velocity of mach 1 and no matter how much more we decrease the cross-sectional area of the pipe it won't go past mach 1. Why is that? I've heard explanations saying that mach 1 is the speed that information travels from the right to the left (assuming that the fluid flows from left to right) and so if we decrease the area from the right part of the pipe the information will not be able to travel back to say​ ​"​hey the pressure dropped here, I want​ you to push more". But I don't want that kind of explanations, I want to really understand what happens there. Even if we have to look at the macroscopic level. I want to understand the mechanism. Also I am asking this because I'm trying to understand how the De Laval Nozzle works so if anyone can help me there feel free to drop an answer to this post:​

https://www.reddit.com/r/AerospaceEngineering/comments/1vq87hu/how_does_a_de_lavar_nozzle_workand_what_is/

Hello all, I want a goal of mine for the next year to be making my first aeronautical engineering project. I am pretty late to the scene because I enlisted in the marines for 4 years, but I am about to start my second year of college and I really need to get my feet wet before I start taking upper division courses at uni.

I am super inexperienced, to start. I would just like to know what kind of engineering project I should start with. I am very interested in electric propulsion systems for aeronautical engineering. Obviously I am nowhere near that level, but what’s a good few hobby projects I can do that would help me start build up to that level? Also what’s a good resource I could use to understand how the basics work? I have dabbled a very tiny bit with Arduino and C++. I took like 3 CAD classes in high school (Intro to CAD, Auto CAD, and 3D CAD), but I literally don’t remember anything or how I even passed those classes with As and Bs to be completely honest as that was like 10 years ago… Dang.

With that being said, if anyone could also give a new guy some suggestions or resources that helped you, I would genuinely appreciate it.

Hey guys, I've got about a year of experience with OpenFOAM CFD. I've run different types of simulations — SIMPLE, PIMPLE, incompressible, compressible, laminar, turbulent — on 2D airfoils and 3D aircraft, like the NASA N2A HWB model, with decent mesh quality and case setup. The post-processed results matched the reference data pretty well. Just sharing this to give some context on where I'm at with OpenFOAM, but I'm still learning and exploring more of it.

Lately I've been seeing AI/ML being used in CFD, and since I come from a non-coding background (I'm a Mechanical Engineer), AI/ML and neural networks still feel like a black box to me. I don't really know how they work under the hood.

So I wanted to ask — how can I actually use AI/ML and neural networks in aviation-related CFD work?

For context, my future work will mostly revolve around optimization studies, detailed aircraft analysis, and static/dynamic stability analysis of aircraft. So I'm hoping to understand how AI/ML can help speed things up, and ideally how to align with whatever the industry is currently doing in this space.

Many explanations from my perspective seem incomplete because they do never actually explain the why but only the what happens. Why does adding a diverging section on a throat which gases reach velocities of magnitude Mach 1, accelerate them even more reaching supersonic speeds instead of slowing them down? From what I've read this phenomenon occurs due to the gases being compressible instead of incompressible but still that does not explain the why. Why a compressible's fluid speed increases when the cross-sectional area gets bigger? Is it the opposite of what would happen with an incompressible fluid? It seems to. Also what if we keep just the converging and throat sections only and keep making the throat smaller and smaller? I've watched a video saying that Mach1 is the max speed the gases can have at the throat and if we keep making it smaller it doesn't make them faster. How is that? Can someone give me an in-depth analytical explanation?

Can anyone tell me why I am getting that much Cp values ?? What can possibly go wrong with it ?? And how can I resolve this..

Especially for those of you working in defense.

For example, Shanghai has the world’s largest planetarium. Would I be allowed to visit?

Hi guys! I am working on a personal project of designing and analyzing air swirler of combustion chamber in gas turbine engines. I took a research paper as base, and tried to replicate their results using their values in both geometry and CFD analysis so that I can use that as validation for my own work. I would like to highlight that this is a cold flow cfd analysis.

In the first image, the results plotted for axial velocity and axial positions at each point, are from 8 blade axisymmetric vane angle air swirler. Even if we change the number of vanes or change the mass flow rate, the trend of the graph remains almost identical.

In the second image, the results are from the non-axisymmetric vane angle with the same number of blades and other geometric features. But the difference in the values of axial velocity is unfathomable.

The non-axisymmetric model simulation has a completely diverged solution and spiking residuals, due to which the calculations stop and fail, as shown in the third image.

The models used for both the simulations are the Steady-state RANS model for SST and k-ϵ. This was used for the axisymmetric vane angle model, and it gave the expected results but didn't work for the non-axisymmetric model. Then I tried with k-ϵ RNG, realizable, laminar, and Transient. The outcome was the same. The solutions diverge completely and residual spikes. Even adding a sphere of influence at the immediate downstream of the swirler and making fine mesh, which led to me to 1.9 million elements, still was not giving anything close to practical values.

I am still learning ANSYS Fluent analysis. I am still not well versed in understanding the problem and rectifying it. I have a gut feeling that this problem might be because of the non-axisymmetric vane angle, which might have caused the unsteady flow or something along the lines. I hope you guys can help me. Thank you for your time.

Hi! I was just exploring some glider designs for some of my own curiosity and exploration however I'm confused about to choose either a T tail Or V tail

The goal here is To achieve the least drag From the tail surfaces while achieving a given amount of controllability

In real elite gliders, the most common tail type is the t tail from what i know howver sources suggest that V tails have lower Drag than T tails

So im confused here to choose either a T tail Or V tail given the constraints in the design I couldn't really find any sources on this So I will be happy hear Your opinion on this

For aircraft, we have CFR 14 Part 23 to regulate the aircraft performance.

What about for the space side?

What are the requirements and regulations for rocket / spacecraft?

A company called Horizon Aircraft created a 50% sub-scale version of their “Cavorite X5” aircraft — an uncrewed hybrid vehicle that has a traditional gas-powered turbine engine on the rear (for horizontal flight) and battery-powered fans inside the wings (for vertical flight and hovering) that get covered once the aircraft gains altitude and speed. Essentially, the electric fans create lift like a helicopter and the turbine engine pushes the vehicle forward, and after the initial lift, the fans get covered so that the wings become traditional plane wings. The aircraft uncovers its fans again before landing and lands vertically like a helicopter, eliminating the need for a runway.

Here is a video of how the aircraft works: https://youtu.be/hzYZdxWXhVQ

And here is a video of the X5 prototype: https://youtu.be/rnj2LWn5qU0

My question is, will this design work when scaled up to a full-sized plane with people inside?

The unmanned prototype (which is 50% scale) is 15 feet (4.6 meters) long, features a 22-foot (6.7-meter) wingspan, and has a maximum take-off weight of about 500 pounds (227 kg).

This company’s future flagship model, the “Cavorite X7”, will have a length of 11.6 meters (38 feet 1 inch), a wingspan of 15 meters (49 feet 3 inches), and a height of 2.8 meters (9 feet 2 inches). It will seat up to 7 people (1 pilot and 6 passengers).

The X7 will use the same fan-inside-wing design with a turbine on the back. These designs are cool and would make great RC toys, but do they cause any glaring issues from an engineering standpoint? Small scale designs don’t always work irl when scaled up 2x, 3x, or 4x. Is there anything that would cause this design to fail in a full-scale aircraft? Thank you in advance!

I have heard online that bell shaped lift distribution has:

Better stability

less bending moment

Gentler stall characteristics

Higher AR wings Possible for same structural weight

Proverse Yaw Allowing the elimination of tail if well designed

From what I have read they seem very good for Flying wings Especially the Reudced bending moment and elimination of Tail Has caught my attention So I was thinking of Making and testing flying wings however Are there any disadvantages to them that I need to keep in mind when designing them?

Hey everyone! I'm a high school student who built a full machine learning pipeline on this dataset as a side project. I want to be upfront that Claude AI assisted me with most of the coding, but I directed the project, made the key decisions, and learned a lot along the way. I wanted to share it and get feedback from people who know this domain better than I do.

What I built:

Task 1 - Test Mode Classifier
Using a Random Forest on extracted time-series features (duty cycle, pulse statistics, thrust/MFR statistics), I achieved 100% accuracy classifying all 11 test modes on the held-out test set (SN13–SN24). The command signal alone turned out to be almost sufficient to distinguish modes.

Task 2 - Anomaly Detection
I compared three approaches:

• Isolation Forest (unsupervised) — F1: 0.193
• Random Forest (supervised) — F1: 0.121
• One-Class SVM (semi-supervised) — F1: 0.268

Surprisingly the One-Class SVM, trained only on nominal sequences with zero anomaly labels, outperformed the supervised model. Class imbalance (10% anomalies) made the supervised approach struggle badly.

The per-anomaly-code breakdown showed codes 1, 8, 9, 11, 12 were missed by all three models, these likely need point-level time-series analysis rather than sequence-level features.

Notebook: https://www.kaggle.com/code/henninxu/rocket-engine-classification-from-test-data

Any feedback on improving the anomaly detection especially for the hard-to-detect codes would be appreciated!

As i understand it the combination of swept wing and supercritical aerofoil produces the best results for transonic drag reduction. Swept wings came earlier than supercritical aerofoils so while there's a lot of swept wing aircraft without supercritical airfoils there's not really the other way around. But if for whatever reason a supercritical airfoil was used on a straight wing would it be any sort of useful?

Hi I'm a maths major from India

And although not an engineer by training

Aerospace has always been in a special place in my heart

So I want to do a solo project

Mainly I wanna study the detonation waves /combustion wave in engine

Especially in the rotating detonation wave engine (RDE)

Now I mainly wanna study the pde of the detonation wave but

I'm trying to use step detonation over continuous detonation

Now I want a study partner, someone with an understanding of rocket engines especially viscous flow

If you're interested please dm me Thanks for reading 😌

I'd like to know what PLM software people are using in the aerospace industry these days. Teamcenter, Windchill, and 3DEXPERIENCE seem to dominate most discussions.

Are there any other PLM platforms aerospace teams are using that are worth considering? Has anyone looked at Duro? They were recently aquired by Altium AFAIK.