Lidozin
最新回复 发布由 Lidozin
-
-
8 hours ago, AeriaGloria said:
Well, Contact Lights EM of the previous flight model showed 18.1 deg/s sustained, 25.5 instant, so it’s markedly improved in both. That’s what I’m referencing. Your video talks about sustained rate also. It is the whole point of your center line on EM.
Also you got 21.0, not like 21.3 or 21.5 right?
And I assume for ITR you did turn off the AOA limiter COC-3 when testing?
Open Subsonic_Energy_Maneuverability_Diagrams_for_DCS_202304 6.pdf 13.44 MB · 0 downloads
null
-
5 hours ago, AeriaGloria said:
Very good job. It shows it hits the manual numbers, but it seems to me to be in very narrow windows. For example, you mention it achieves 9 G 30 kmh higher then manual chart says. Either way, it is huge improvement of nearly 3 degrees sustained over previous flight model, and shows how bad it does at high speed
This is interesting information. However, I’d really like to know (perhaps I simply missed the performance data for the earlier variant) where your figure of a 3-degrees-per-second difference in turn rate comes from, and why you’re referring to a sustained turn when the video was clearly discussing instantaneous turn rate.
-
-
“It ain’t what you don’t know that gets you into trouble.
It’s what you know for sure that just ain’t so.”— attributed to Mark Twain
-
2
-
7
-
-
"At last the Mouse, who seemed to be a person of authority among them, called out, “Sit down, all of you, and listen to me! I’ll soon make you dry enough!” They all sat down at once, in a large ring, with the Mouse in the middle. Alice kept her eyes anxiously fixed on it, for she felt sure she would catch a bad cold if she did not get dry very soon.
“Ahem!” said the Mouse with an important air, “are you all ready? This is the driest thing I know. Silence all round, if you please!"
Now I can rest easy and carry on exploring the new module, pausing from time to time to see whether its flight model is really quite as ‘monstrously far from the original’ as some would have it.-
5
-
2
-
-
Is it IAS or TAS you are discussing about
?
-
At a fixed manifold pressure (and mixture), engine shaft power generally rises with RPM and peaks at the maximum permitted RPM. Accordingly, thrust power at the propeller,
Pthrust=ηp Pengine, is also maximized there. However, in some cases a small RPM reduction (with a constant-speed prop) can increase net thrust power if the drop in helical/tip Mach moves the blades out of the transonic regime and boosts propeller efficiency enough to outweigh the modest loss in engine power. This is more likely at higher altitudes and higher true airspeeds, where the speed of sound is lower and tip Mach numbers are higher. -
The AI “breaks the laws of physics” only to the extent that the input data it is given contradict the laws of physics and basic common sense.
For example, take the AI’s data set for the F4U-1:
A zero-lift drag coefficient CD0 of 0.0155? Even the P-51 Mustang did not achieve such a figure.
CD0 of 0.018 at Mach 0.8 is pure fantasy for a straight-wing aircraft — as is a maximum CL of 1.0 at M=0.8.
Such numbers are physically unrealistic because straight wings experience strong compressibility effects as they approach transonic speeds: drag rises sharply, and the maximum achievable lift coefficient drops well below subsonic values. Assigning these “perfect” transonic coefficients effectively gives the AI a wing that defies real aerodynamic limitations.
The value of the induced drag quadratic coefficient in this data set is more in line with that of a low–aspect-ratio wing, such as on a MiG-21.
A value of 0.09 is far from what an aircraft with a straight wing of the Corsair’s aspect ratio should have.What’s fed in is exactly what it flies with.
This is data from a well-known U.S. NACA report, showing the variation of maximum lift coefficient (CLmaxC_{L_{max}}CLmax) with Mach number for several aircraft types and wing configurations, based on both flight tests and high-speed wind tunnel measurements.
-
1
-
1
-
-
4 hours ago, AJaromir said:
That's correct. If you know this, you can achieve the point when the stall is impossible. Even at 0 airspeed. I call it "decellerated stall"
Ballistic trajectory. An arrow, for example.
-
On 8/7/2025 at 5:30 AM, Nealius said:
P-47 stall speed with flaps up is 99kts or thereabouts. Going vertical for a 2000ft altitude gain then nosing over for level flight without losing much more than 100ft in the process at 83kts with flaps up, two bombs, and two bazooka rocket racks is a violation of physics.
The 99-knot stall speed for the P-47 (flaps up) applies to level, 1 g flight, where the wings must generate lift equal to the aircraft’s full weight.
Stall is fundamentally an angle-of-attack phenomenon, not a specific speed. The published stall speed is simply the speed at which that critical angle of attack is reached in a 1 g, steady-state condition.
If the aircraft is unloaded — for example, near the top of a zoom climb or during the pitch-over from vertical — the required lift is much less than its weight. That means the wing can maintain the necessary (lower) angle of attack at a much lower airspeed, so you can see IAS values well below 99 kts without stalling.
In your example, if the P-47 went pure vertical, then pitched over into level flight, it would be in a near-ballistic or very low-g state for part of the maneuver. In that state, the “stall speed” number doesn’t apply, and the aircraft can regain speed with minimal altitude loss — even with bombs and rocket racks attached — as long as there’s enough initial energy and thrust to carry it through.
-
2
-
-
9 minutes ago, Nealius said:
My experience with the AI is that the FM is so deplorable that they're not even worth fighting. I've seen P-47s go pure vertical from 200ft to 2000ft, info bar showing 83KCAS, no stall behavior whatsoever, and just accelerate back to normal 200KCAS flight with no loss in altitude.
If the aircraft was flying purely vertically, as described, then stall behavior in the conventional sense wouldn’t be expected — because the wings are not generating lift in the traditional way during a vertical ascent. Stall is a function of exceeding the critical angle of attack while attempting to produce lift; in vertical flight, the aircraft is no longer attempting to balance its weight with lift but is instead relying entirely on thrust and inertia.
If, after this vertical segment, the aircraft transitioned into level flight by gradually reducing pitch angle, it would have done so in a partially unloaded state, producing lift below 1g. In that case, as long as it had retained sufficient energy, it could re-establish normal flight once its speed increased above the minimum sustainable airspeed.
This sort of behavior — while seemingly unusual — is consistent with known energy-state transitions and doesn’t inherently indicate that the FM is being violated.
Additionally, it's worth noting that low-speed unloaded flight (i.e., with load factor below 1g) is actually one of the most energy-efficient modes of flight for propeller-driven aircraft. This is primarily because:
Since induced drag is directly related to lift (and increases with the square of load factor), reducing lift demand below 1g sharply reduces drag — especially important at low speeds, where induced drag dominates. Unlike jet engines, piston engines and propellers are well-suited to producing useful thrust even when the aircraft is slow, allowing for continued acceleration or climb, provided excess power is available.
When not fighting against gravity with full lift, the aircraft retains more of its kinetic and potential energy, allowing it to convert between the two more gradually — for example, by accelerating in a shallow dive back to sustainable flight conditions.
This makes unloaded low-speed flight a perfectly valid and sometimes optimal maneuvering regime, especially when trying to recover from steep climbs or regain speed after vertical maneuvers — assuming the aircraft has sufficient power to avoid settling into an unrecoverable descent.
It would also be possible to replicate the same maneuver manually, starting from identical initial conditions. If the aircraft’s configuration and power allow, entering a vertical climb followed by unloaded low-speed flight and gradual pitch-down can result in a smooth transition back to controlled level flight — just as seen in the AI’s case.-
1
-
-
On 7/8/2025 at 4:15 PM, Raven (Elysian Angel) said:
On top of any manoeuvring characteristics, there's the problem of their omniscient situational awareness through vision that's unobstructed by canopy frames and aircraft structures, and vastly overperforming sensor abilities in general. This allows the AI to perform their manoeuvres as perfectly as their FM allows since their decision making will always be perfect.
To verify the claim that the AI has 100% situational awareness and no blind spots, there is absolutely no need for advanced flight testing skills. The procedure takes no more than five minutes: simply enter a known blind zone of the AI—one programmed to unconditionally engage any airborne target—and remain there briefly. Then transition into an area where a human pilot would immediately recognize a threat. This is exactly what was done.
-
In addition to all else, the video demonstrated that a qualitative comparison of energy performance between AI and human pilots (i.e., “who caught up or overtook whom”) can produce highly variable and non-repeatable results — even when the net energy gain at the end of the maneuver differs by no more than ±5%. As previously mentioned, maintaining position in close formation behind an AI lead is inherently problematic due to its constantly varying load factor.
For this reason, it is more reasonable to move toward an analytical comparison of energy performance across three configurations: the default SFM, Curly's mod, and a minimal tweak that adjusts thrust at low speeds to match values from the reference documentation.
Setting aside the entirely justified reduction in the maximum lift coefficient (CL or Cy, in Soviet notation), which only affects performance in non-steady maneuvers and may actually lead to slightly better energy retention, we can focus purely on the energy characteristics.
We begin again with specific energy rate. The graphs show that both mods reduce energy rate at low speeds; however, Curly’s mod grants the AI an unjustified bonus in the 500–800 km/h range, and at altitudes from 0 to 5000 m — precisely where the aircraft is most efficient in gaining energy.
These same modifications also lead to a slight overstatement of sustained turn performance. In both cases, the default SFM data remains a closer approximation of the flight characteristics documented in the reference material.
Finally, we consider the graph of longitudinal acceleration vs. true airspeed. Unlike video comparisons, this type of plot could more effectively prompt developers to revisit the model data — since it clearly reveals a discrepancy from reference values at low speeds.
One particularly interesting detail in the reference documentation is that the airspeed values on the graphs correspond to raw cockpit instrument readings, not corrected for compressibility effects. For example, at 5000 m altitude, a true airspeed of 1044 km/h would correspond to a corrected indicated airspeed of 809 km/h, while the graph shows 830 km/h — exactly matching the uncorrected table value. This means that deviations of the calculated curves from the acceleration graph at high Mach numbers should not be taken as significant.
Returning to the observed change in AI behavior — specifically, when it stops climbing slowly at speeds around 350 km/h — this aligns well with the reduction in available thrust at low airspeeds, as reflected in the thrust curves. It is plausible that the AI logic recognizes the diminishing return of continuing such a maneuver and instead opts for a different course of action.-
1
-
-
-
With sincere thanks to Katmandu for kindly providing both the mission and the AI mod data file, I conducted a series of tests using only this mission setup. In these tests, the AI aircraft flew using three configurations in sequence:
-
the default SFM data,
-
the same data but with engine thrust corrected according to the reference curve in the low Mach number region,
-
the data set from Curly’s AI mod.
For all cases, the time interval measured was from the moment the aircraft entered a climb by establishing a 1.5g load factor, until it began rapidly decreasing its pitch angle. This time, 58 seconds, was adopted as the reference for both AI and human-piloted aircraft.
Since it is virtually impossible for the human pilot to match the AI’s exact initial airspeed at the moment of climb onset, the comparison was based on specific energy height:
He = H + V² / 2g,
which reflects the aircraft’s total mechanical energy and offers a more accurate basis for analysis.The human pilot followed the AI’s climb profile as closely as possible, keeping the entry load factor below 2.5g and maintaining a pitch angle near 35 degrees. The result was somewhat unexpected, yet entirely explainable: the human-piloted aircraft outperformed even the default AI with increased thrust. This illustrates a point mentioned earlier — that the exact climb profile can significantly affect energy performance and the resulting He gain over the climb segment.
While it is difficult to pinpoint the exact source of the additional energy gain, it most likely resulted from a smoother pull into the climb. A more definitive answer would require time-stamped recordings of flight parameters for both AI and player aircraft, allowing for a detailed comparison of dHe/dt during the climb phase.
The influence of flight profile on energy climb rate was further highlighted in the final test, where the player attempted to follow the AI in a zoom climb (see video). The result was even more surprising — and again, entirely explainable.
-
1
-
-
As far as I understand, the forum thread was discussing a recording from an online session, since the aircraft names match the nicknames of forum participants. Are there any references showing such large TacView discrepancies occurring exclusively in offline missions?
-
Thanks for the materials!
Small modifications to the aerodynamic polars — especially within the low-to-mid Mach range — have minimal impact on overall energy performance compared to relatively larger changes in thrust. That said, it’s reasonable to acknowledge that changes in thrust, and thus in the bot’s energy potential, can under certain conditions influence its combat logic or maneuvering behavior.-
1
-
-
2 hours ago, Katmandu said:
Tacview is very inaccurate, with error margin up to 100%, ED don't even accept it as evidence in threads about FM. Standard replay taskbar readings are sufficient for ED, and therefore for us also.
Climb rate at high pitch angle and angle of attack is not JUST about the thrust curve, it's also very much about the airframe- the lift and drag coefficients, Cymax stall coefficient and so on. Which is why I love Curly's mod of the AI Mig-15 SFM so much, he's changed most of the aerodynamics parameters in Mig-15's SFM, not just the thrust at low Mach values (like I did - before discovering his mod).
Here is his mod in action, the 35deg zoom climb rate is very similar for both player and AI. I've recorded the climb to 7K as the AI changes to shallower pitch angle after this. The true zoom climb is to 6900m or there about.
PS Here is a link to Curly's AI Mig-15 SFM Mod for people who might want to try it
This is quite interesting, but judging by the graphs posted by Curly, the aircraft's aerodynamics (i.e., the polars), which are solely responsible for energy performance along with thrust, were barely changed in the low-to-mid Mach number region where your test took place.
Therefore, in our case, thrust is essentially the dominant factor in energy gain.
The maximum lift coefficient, unfortunately, has the opposite effect on energy: if you reduce it for the AI — as was done in the mod based on the reference document — the AI will actually preserve energy better than the default version.
Unfortunately, I haven't been able to locate the mod file to try it myself. Would you be willing to share it?
If you still have the track from your test, it would be quite valuable to see video of both runs — one using the default data file, and the other using the modified one. In that case, your piloting should remain the same, and the AI’s trajectory should presumably change.
And, by the way, how can I make the AI perform such a maneuver in a mission? -
On 6/13/2025 at 8:45 PM, Kang said:
I'd say the worst offender to me is the MiG-15 actually. To the point that dogfighting it in the Sabre - mind you, pretty much the only 'pairing' that ED ever really released - is so little fun that I had taken to tangling with more modern enemies instead during my Sabre era.
The problem of the simplified flight models of the AI being rather inaccurate in these regards obviously becomes more and more visible when you are actually dogfighting. DCS seems to much prefer BVR engagements of modern jets in which this doesn't matter much. But what is worse is that ED in all their combined wisdom have decided to include AI that pretty much exclusively and constantly sticks to manoeuvres and tactics that exploit/showcase this weakness of the simulation to the max.
22 minutes ago, Dragon1-1 said:I think ED actually has some debugging tools to analyze tracks, in addition to what the sim normally provides. They might be able to pull better data than we do with them.
Does this refer to online TacView sessions, or are there known cases of such 100% mismatch in offline missions as well?
-
10 hours ago, Katmandu said:
Nice video! So, at pitch angle below 20 deg and above 500km/h the SFM and PFM have good correspondence - this is cool and finally some good news for Mig -15 SFM haha!
But!
In my vid, the pitch angle was about 35 deg, so both planes were losing speed, all the way to around 200km/h - and the AI had big advantage in climb rate. This kind of zoom climb is actually more reflective of actual combat, as planes do not do shallow climbs when fighting.
So your vid does not seem to disprove anything with regards to combat/steep climbs for AI, but does prove that SFM and PFM do have good correspondence for shallow climbs.
Thank you — I agree it's good to see that SFM and PFM align well under stable conditions. However, zoom climbs of the type shown in your video are difficult to verify without detailed data. The results depend heavily on maintaining the same speed-energy profile and minimizing oscillations or excess control input.
To make conclusive statements about energy performance in steep climbs, a TacView recording or a comparable export of time history for TAS, altitude, and G-load would be ideal — for both aircraft. That would allow direct comparison of energy rates and drag profiles.
Even if we assume that the thrust curve in the low-speed regime was deliberately adjusted for some internal purpose (though I’d argue that it's not simply a "no-loss" curve, since the shape doesn't fully match that either), the difference in equivalent vertical velocity at the worst point (IAS ~250 km/h) does not exceed 8–9%. Given that the AI spends almost no time at those speeds, the contribution to its total energy gain is negligible. At higher speeds, the difference becomes virtually zero.
So, even replacing the base thrust table with one that strictly matches the theoretical curve would not result in any substantial change to the outcome of dogfights against the AI.
-
2 hours ago, Pikey said:
I'm going to play with this sarcastically. I'm going to parody the ideas in Comic Sans. Once more, its not personal, I'm sure I'd like you as a person, just the ideas don't sit well with me and its got to a point where its a bit funny now. Heres the sracasm highlights.
We see an SFM table in the coremods of the plane lua. This means that the AI uses this when calculating its dogfight state table. We know that the existence of the SFM means we only need to look at the actual model, not how its executed or used in the software. The fact that the table exists means DCS uses it. It doesnt matter that the C code is encrypted and unreadable, its only the LUA. And anyway, I can read the program, I know things for sure. Just use a stopwatch.
We can rule out misuse of the SFM data because that doesnt make sense. Why would a game need to force the AI to do something at all, when it flies realistically? Stupid.
There is no evidence of the AI not using the SFM data. Apart from the times when it doesnt, like when its following the player in line abreast perfectly and can turn at the same time and aero brake stop 100kts in 1 second. But this doesnt actually matter because we know because of the SFM data that the AI doesnt behave like that during dogfights. SFM = dogfight and climb. Everything else can be scripted, thats ok, but we know for sure its not breaking this rule.
We can prove this by looking at when the AI isn't doing something stupid, like climbing. If we examine the climbing then we know for sure this must apply to the dogfight data.
When we look at tacview, we can see the moment to moment forces and speeds and alpha recorded for the AI. It's OK to see things here that are within the SFM data. Look, the plane is going at 500kts straight up. That's perfectly OK, so the entire fight must be fine here. I don't need to see the plane doign these 500kt climbs again and again, because its just flying perfectly, there is no issue over time with the energy state.
We havent seen any evidence of the AI using scripted behaviour. At least not between 3.30pm and 3.45pm in the afternoon of June 12th 2025. The AI would tell us he is using scripted behaviour through the comms menu.
We haven't seen the Scripts folder of the DCS application where the AI routines are kept. At least, the ones that apply to normal flight. The dogfight ones got moved some years ago to protect people keep on arguing about this non existent problem because they are just bad fliers and need to stop wasting their time looking for excuses.
We know the DCS AI is very good so the routines can be shared from MiG pilots to the Luftwaffe, so they can use boom and zoom too. Its a special trick, it might look the same, but actually each plane type, jet or prop can use the identical vertical manouvers and energy. But the SFM is what decides how it really is different.
We also know that ED eventually gave up their special Flight model in development after realising it was pointless. It was pointless because the AI already was perfect. Why develop something to make it different when it is already the best?
Also we know a lot of things about planes and so we've marked ourself as the solution very early on in this thread. Quite simply, they dont understand about SFM, its only for aeronautical engineers and high IQ. So being the solution saves time and is more effective in conversations.
Thank you for the entertaining interlude — sincerely. It's always refreshing to see people stay engaged, even in parody. However, as enjoyable as it was to read, I couldn’t find in it anything resembling a technical counterpoint to the tested climb profile or the data comparison with the real-world reference chart.
Regarding the 500 knots straight up — if that was a serious remark, I would kindly ask for clarification. A well-trimmed MiG-15 starting from 950+ km/h (which is about 510 knots) absolutely can convert kinetic energy into altitude for a short time — that's basic energy conservation and directly tied to its dynamic ceiling. There's nothing unnatural about it unless you're claiming the AI sustains it indefinitely, which is easily testable in TacView or even with a stopwatch and status bar, as already demonstrated.
You’re very welcome to propose a reproducible test that demonstrates any claimed violation of physics. If it's testable, measurable, and repeatable — I'm all ears.
Otherwise, I’d suggest we let the data speak. Because ten minutes of quiet measurement saves hours of speculative back-and-forth.
-
On 7/15/2025 at 3:05 PM, Pikey said:
@Lidozin I'm not picking on you, i'm defintiely picking on your argument, its got more reversals than an IL2 Sopwith Camel dogfight. Here's your 3 page argument condensed down and fall apart, summarized, with quotes since you like empirical data.
Step 1. Claim the FM is fine.
Step 2. Be told its not applied consistently and thus it is in doubt.
Step 3. Argue that you were only talking about Combat routines and not non combat routines like land/takeoff, follow/escort
Step 4. Show that by verifying non combat routines like climb performance, it proves the AI is following physical models and limits all the time in combat!
Am I the only one here noticing this?
You can say the FM observes the rules sometimes: Accepted. You cannot say that because it uses physics soemtimes that it always does.
You know, and everyone knows here that the software chooses when to use flight models, but the key to knowing that its using a flight model is to wether the moment to moment decisions are natural, or its a repeat of a sequenced set of events sewn together to look like its real. And that is what you miss. WHich is why I say you dont play the game enough to notice. Those loops. I see the WW2 planes also using them. Its just canned sequential responses, not a real FM and its not staying within physics between these sequences. They can do it forever.
You can be 100% correct, 1% of the time. But you can't use the example of being right once as evidence that you are always right!
The point is that AI strings together canned tracks and puts them together. You need to look at the enitre picture holistically. Its software, its simplified, its designed to work well enough for casual scrutiny, but when you put the whole picture together, it collapses, along with your argument that the AI observes physics.
Where is ED's GFM they talked about? The one that should react properly to physics, they said. By your reckoning, we dont even need it!
I can get you your empirical data that AI doesnt observe physics, but its more fun listening to the various ways you avoid finding that important.
Most of the frustration and speculation expressed in this thread seems to stem from combat-related behavior. I haven’t come across many complaints about AI taxiing, takeoff, or landing. And to be honest, those phases don’t particularly interest me either, since I primarily view the AI as a sparring partner in aerial combat.
Now, climb performance represents a critical component of combat behavior ( it’s energy gain at 1g, and while it doesn’t occur in isolation that often, it fully defines acceleration in level flight and in shallow dives) both of which are common in real engagements.
What I’ve shown is that in this regime, the AI follows the physics defined in its data tables and behaves exactly as the real aircraft would according to flight test documentation. That alone should dispel many doubts.
What do we observe more often in dogfights? Sustained or transient turning flight with increased load factors, where energy is either lost or traded in ways governed by well-known aerodynamic relationships. I also showed that the aerodynamic data used for the FM (lift, drag, thrust) supports correct energy behavior in those turning regimes. So far, everything lines up.
However, to completely rule out the suspicion that the AI is “cheating” in these cases, the next logical step would be to analyze a 1v1 fight recording where both the player and AI aircraft are of the same type. Specifically, you’d export the time history of TAS, altitude, and G-load for both. Using known energy equations, one can compute the specific excess power and compare it to the observed load factor.
If the AI is cheating — by bypassing the FM or using hidden scripts — it would become immediately obvious. Either its energy behavior would be physically implausible, or you'd see clear discontinuities or artifacts in the data.
I believe this type of empirical comparison would cut through all the theoretical debate and provide developers with a solid foundation for any investigation or follow-up.
-
2 hours ago, Katmandu said:
But in our case the leader was ahead - as per my climb test video, the AI starts ahead. So, in his journey towards the hill, he floors the throttle first. I react and floor the throttle second - yes. But, since I was behind him, I was also further away from the hill than he - at the instant that he applies the throttle. By the time I floored the throttle I was approximately the same distance from the hill as he was. (it is also possible to be more precise, the AI starts the climb at 685km/h IAS, so it's a matter of doing the same and maintaining his angle )
Your logic would apply if we were side by side - then yes, my reaction time would delay the throttle application and I would start rolling onto the hill at slower speed that the AI "car" and thus would run out of energy sooner. There is some margin for error there, but I could not outclimb the AI to 10km, no matter what profile (speed, angles) I used.
PS Anyway, I am super happy with Curly's awesome SFM mod for AI Mig-15, so it's all academic now
I wish I found it earlier...
This mod is unlikely to make a meaningful difference, if only because the thrust has been adjusted in the TAS region below 300 km/h — a regime the AI almost never flies in, even at low altitude. During climb, the AI typically maintains a TAS around 700 km/h, where the thrust values in the mod remain essentially unchanged. So any claimed improvements are unlikely to impact the AI’s actual climb behavior in a measurable way.
Instead of relying on modifications, you can perform a direct test using the standard setup:
-
Place the AI-controlled MiG-15 ahead of your aircraft at a distance of 600 meters, both starting at sea level with a TAS of 700 km/h.
-
Assign the AI a route with waypoints that require a continuous climb to 11,000 meters at full power.
-
Position your own aircraft directly behind the AI (600 m), matching its speed and heading.
At mission start, apply full throttle and maintain level flight. Let your aircraft accelerate naturally until it reaches 700–705 km/h TAS, then initiate a gradual climb, maintaining 710 ± 10 km/h TAS throughout. Use trim gently to hold pitch; avoid aggressive control inputs. The goal is not to match the AI’s pitch angle, but to fly a clean, energy-efficient climb profile.
-
-
48 minutes ago, Dragon1-1 said:
You're not getting it - flying aerodynamic tables exactly in an analog bird like MiG-15 is superhuman. It's like you're dogfighting a wind tunnel model, not an aircraft flown by a real human with real controls. Aerodynamics are only one part of the aircraft's performance, another critical factor is the human-machine interface. Yes, it's theoretically possible to fly the MiG-15 that way, but in practice, you'd need to build a piloting robot, or retrofit an FBW system (same thing, really, if you think about it).
A human pilot needs to physically move the control column to maneuver, actuate the trim switch to adjust the trim, physically look at the gauges to determine airspeed, keep tally, and so on. In a MiG-15, all those tasks are somewhat complicated by poor cockpit ergonomics (a somewhat notorious issue with all Soviet fighters), in addition to the normal delays and imperfections from making those actions. AI models none of this, which makes it superhuman. We're effectively fighting a MiG-15 equipped with modern FBW controls, a force sensing stick and a modern HMD.
In fact, it seems to be exactly the same case as with climbing with warbirds. Until they got WEP restricted, most people couldn't do it, but Reflected found a way by the means of unrealistically tight trimming and very hard, but doable precision flying. Yes, it follows the tables, but it does not follow either real WWII practice or normal ways to fly a warbird. This is also why complaints about fighters which are supposed to have FBW are much less frequent.
What you’re describing is exactly what separates a well-trained pilot — or a skilled virtual one — from someone just “flying it by feel.”
Yes, it's hard. Yes, it takes discipline. That’s why real-world flight and combat manuals emphasize very specific energy management techniques:
Climbing at the most efficient airspeed.
Maintaining coordinated, smooth flight.
Avoiding unnecessary g-loading.
Turning at corner velocity.
Trimming properly and flying clean.
These aren't theoretical details — they're core to real-world air combat doctrine, because that’s what allows you to stay fast, stay high, and stay alive.
You don’t need to be a robot. But you do need to avoid wasting energy through unnecessary control inputs. And even if your airspeed control is only accurate to ±30–40 km/h, that’s often enough, as long as you don’t induce drag by chasing the fight with abrupt pitch changes.
As for the AI: it simply flies by the tables with clean logic and no wasted motion. That’s not superhuman — it’s what happens when someone (or something) doesn’t bleed energy.
In fact, I suspect that when some players meet another human online who does understand energy fighting, timing, and aerodynamic discipline — they’re likely to call them a cheater, too.
That said, I’d like to remind everyone that the original goal of this analysis was not to examine AI behavior in terms of tactics or input realism, but simply to test the claim that the AI “doesn’t obey physics, or has physical performance beyond what a player-controlled aircraft can achieve.” The flight test results suggest otherwise. Let’s avoid shifting the discussion away from that specific and measurable question.
WOW!
在 DCS: MiG-29A Fulcrum
发布于
Now that you know the speed range where the sustained turn rate reaches its maximum and remains nearly flat, set the aircraft mass to each of the two values you mentioned and run the test directly in the simulator at those same speeds. Then compare the results.
If maintaining a full 360° sustained turn is difficult, just capture the most stable portion of the turn instead. Use the heading change shown in the status bar together with the elapsed time to calculate the turn rate. That will give you a clear, quantitative difference between the two masses.
And just as a reminder, there’s a reason why every Ps diagram and every ROT chart always specifies the exact aircraft mass for the given case — mass is a fundamental parameter that directly shapes the sustained turn envelope.