Hypersonic turbulent quantities in support of Morkovin’s hypothesis
TL;DR
Imagine a super-fast airplane flying, five or six times the speed of sound. The air flowing over its skin is incredibly chaotic and turbulent, like a raging river. Back in the 1960s, a scientist named Morkovin proposed a clever idea: if you just account for how the air gets squeezed and stretched (its density changes), this super-fast, chaotic air actually behaves a lot like the slow-moving, well-understood flow of water in a pipe. This makes it much easier to predict things like friction and heat. The problem was, nobody could properly measure one of the key 'up-and-down' wobbles in this chaotic flow to prove it. This study used a special laser technique with krypton gas to finally measure that wobble. They found it matched Morkovin's old idea perfectly, confirming a foundational principle of high-speed flight.
This paper presents boundary-layer profiles of streamwise mean and streamwise/wall-normal fluctuation data ( \(\overline{u},{u}_{\,{{\rm{RMS}}}}^{{\prime} },{v}_{{{\rm{RMS}}}\,}^{{\prime} }\) ) recorded with Krypton Tagging Velocimetry (KTV) at 100 kHz in a hypersonic, turbulent, zero-pressure-gradient boundary layer. The edge Mach number, wall-to-recovery temperature ratio, and friction Reynolds number are (\(M∞ = 6.4, Tw/Tr = 0.54, Reτ = 450\), and (\(M∞ = 6.0, Tw/Tr = 0.17, Reτ = 780\)), for the ‘cold-flow’ and ‘enthalpy-matched’ conditions, respectively. The KTV data agrees with direct numerical simulation (DNS) within the error bounds of the experiment down to as low as 10% of the boundary-layer thickness (\(y/δ ≈ 0.1\)). The KTV and DNS data agree with incompressible laser-doppler anemometry (LDA) data after applying the Morkovin scaling, which accounts for mean density differences across the boundary layer. Therefore, the experimental data presented are supportive of Morkovin’s hypothesis, which is fundamental to our understanding of supersonic and hypersonic compressible turbulence. These are the first such wall-normal fluctuation measurements to support the hypothesis first proposed in 1962. Morkovin’s hypothesis establishes a comparison between incompressible and compressible flows and is essential for understanding supersonic and hypersonic turbulence. In this work, the authors present the measurements of wall-normal fluctuations that support the hypothesis proposed in 1962.
- 1First wall-normal fluctuation measurements supporting Morkovin’s hypothesis.
- 2Krypton Tagging Velocimetry used to measure hypersonic turbulent boundary layers.
- 3Agreement with DNS and LDA data underlines the validity of Morkovin scaling.
- 4Findings are essential for understanding compressible turbulence in supersonic flows.
Adversarial AI reveals mechanisms and treatments for disorders of consciousness
Imagine your brain is like a city with millions of roads and traffic systems. When you're awake and conscious, traffic flows in complex, coordinated patterns. In a coma, something has gone wrong — but we've never had a great way to figure out exactly which roads are broken or how to fix them. This study built a very smart AI that learned to tell the difference between 'awake brain' and 'coma brain' by studying hundreds of thousands of brainwave recordings. Then, like a detective, the AI was pitted against a simulated model of the brain to figure out: what changes in the brain's wiring would explain the difference? The AI figured out — on its own, without being told — that two key things go wrong in a coma: a specific circuit deep in the brain (called the basal ganglia indirect pathway) gets disrupted, and the brain's 'braking system' (inhibitory neurons) starts working too hard in the wrong places. The researchers then checked these predictions against real patient data, and both checked out. The AI also suggested that zapping a specific deep brain region with high-frequency electrical pulses might help wake people up — and early evidence from human patients supports this idea.
Gene conversion empowers natural selection in a clonal fish species
Unfortunately, the content of this research abstract could not be accessed due to paywall restrictions. Without being able to read the actual findings about gene conversion in clonal fish species, I cannot provide an accurate explanation of what the researchers discovered or why it matters.
Direct detection of an asteroid’s heliocentric deflection: The Didymos system after DART
NASA crashed a spacecraft into an asteroid moon called Dimorphos in 2022, and scientists have now measured that this impact actually nudged the entire asteroid system slightly off its path around the Sun. This is the first time humans have measurably changed how a celestial body orbits the Sun, proving that we can potentially deflect dangerous asteroids heading toward Earth.
The dynamics of AMPA receptors underlies the efficacy of ketamine in treatment resistant patients with depression
Think of your brain as having billions of tiny locks and keys. One particular lock — called the AMPA receptor — sits on brain cells and helps them talk to each other using the chemical glutamate. In people with hard-to-treat depression, this study found that those locks are less plentiful than normal, especially in emotional brain regions. When doctors gave these patients ketamine, it actually changed how many of those locks were available on the cell surface — and the bigger that change was, the better the patient felt. So ketamine isn't just temporarily numbing pain; it appears to be physically restoring a broken communication system in the brain. The scientists confirmed this by using a special brain scan (PET scan) with a radioactive tracer that literally glows where those AMPA receptor locks are located, letting them count them in real time in living people.
