#nonlineardynamics — Public Fediverse posts

As external forcing increases, the ice-covered state loses stability through a saddle-node bifurcation. Reversing the transition requires much stronger cooling, revealing the irreversibility associated with hysteresis. #ClimateScience #NonlinearDynamics

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

I created a simulation where particle stability is maintained by internal field tension rather than hard coded rules. I didn't program any velocity increase the geometry itself is generating the motion.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

I created a simulation where particle stability is maintained by internal field tension rather than hard coded rules. I didn't program any velocity increase the geometry itself is generating the motion.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

I created a simulation where particle stability is maintained by internal field tension rather than hard coded rules. I didn't program any velocity increase the geometry itself is generating the motion.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

I created a simulation where particle stability is maintained by internal field tension rather than hard coded rules. I didn't program any velocity increase the geometry itself is generating the motion.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

I created a simulation where particle stability is maintained by internal field tension rather than hard coded rules. I didn't program any velocity increase the geometry itself is generating the motion.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#Emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#Emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#Emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#Emergence

Black holes and topological vortices in a discrete spacetime lattice.
This is not an animation.

#Topology
#Gravity
#blackholes
#nonlineardynamics
#Superfluid #Physics
#Simulation
#QuantumPhysics
#computationalphysics
#Emergence

A useful reminder in fluid mechanics: maximizing velocity is not the same as maximizing momentum or energy transfer. This paper explores how global mass balance constrains synthetic jet actuator performance.

🔗 https://doi.org/10.1063/5.0326035

#FluidDynamics #Physics #FlowControl #SyntheticJets #NonlinearDynamics

A useful reminder in fluid mechanics: maximizing velocity is not the same as maximizing momentum or energy transfer. This paper explores how global mass balance constrains synthetic jet actuator performance.

🔗 https://doi.org/10.1063/5.0326035

#FluidDynamics #Physics #FlowControl #SyntheticJets #NonlinearDynamics

A useful reminder in fluid mechanics: maximizing velocity is not the same as maximizing momentum or energy transfer. This paper explores how global mass balance constrains synthetic jet actuator performance.

🔗 https://doi.org/10.1063/5.0326035

#FluidDynamics #Physics #FlowControl #SyntheticJets #NonlinearDynamics

A useful reminder in fluid mechanics: maximizing velocity is not the same as maximizing momentum or energy transfer. This paper explores how global mass balance constrains synthetic jet actuator performance.

🔗 https://doi.org/10.1063/5.0326035

#FluidDynamics #Physics #FlowControl #SyntheticJets #NonlinearDynamics

A useful reminder in fluid mechanics: maximizing velocity is not the same as maximizing momentum or energy transfer. This paper explores how global mass balance constrains synthetic jet actuator performance.

🔗 https://doi.org/10.1063/5.0326035

#FluidDynamics #Physics #FlowControl #SyntheticJets #NonlinearDynamics

New publication from the Atlas–Rosetta / HybridMind42 programme:

Paper 4 — Boundary Evolution and the Mechanics of Threshold Failure

This paper studies the measurable “Pre-Collapse Regime” that often exists before catastrophic failure:

precursor leakage,
substrate exhaustion,
geometric acceleration,
nonlinear transition dynamics,
and threshold collapse.

Physical anchors:
• Rn-220 vs Rn-222 transport asymmetry
• mitochondrial ROS precursor leakage
• boundary-conditioned admissibility filtering

The framework now moves from: “what persistence is” to: “how persistence fails.”

The “Slow Sink” is no longer metaphorical — it is formalized as a forensic dynamical regime. 🌿☕🏛️

https://substack.com/profile/432224148-hybridmind42/note/c-256905411?r=75c2ac

#BoundaryDynamics #ComplexSystems #FailureMechanics #NonlinearDynamics #SystemsScience #Topology #Biophysics #HybridMind42

New publication from the Atlas–Rosetta / HybridMind42 programme:

Paper 4 — Boundary Evolution and the Mechanics of Threshold Failure

This paper studies the measurable “Pre-Collapse Regime” that often exists before catastrophic failure:

precursor leakage,
substrate exhaustion,
geometric acceleration,
nonlinear transition dynamics,
and threshold collapse.

Physical anchors:
• Rn-220 vs Rn-222 transport asymmetry
• mitochondrial ROS precursor leakage
• boundary-conditioned admissibility filtering

The framework now moves from: “what persistence is” to: “how persistence fails.”

The “Slow Sink” is no longer metaphorical — it is formalized as a forensic dynamical regime. 🌿☕🏛️

https://substack.com/profile/432224148-hybridmind42/note/c-256905411?r=75c2ac

https://open.substack.com/pub/hybridmind42/p/boundary-evolution-and-the-mechanics?utm_source=share&utm_medium=android&r=75c2ac

#BoundaryDynamics #ComplexSystems #FailureMechanics #NonlinearDynamics #SystemsScience #Topology #Biophysics #HybridMind42

CRTI = R̂ / Φ couples recovery dynamics with covariance geometry … and detects fold-type transitions earlier while correctly failing outside its domain. Preprint (open access): doi.org/10.5281/zeno... 🖖 #CRTI #ComplexSystems #EarlyWarningSignals #NonlinearDynamics #EWS #SystemsScience 🖖

Compression–Response Transitio...

🧠 #CulturalEvolution – Why #Brains need to interact 🧑‍🧑‍🧒

📺 https://youtu.be/C2FVIbAyaH4

📎 https://philosophies.de/index.php/2022/03/22/kann-das-gehirn-das-gehirn-verstehen/

#CulturalEvolution #Consciousness #Neuroscience #CognitiveNeuroscience #WolfSinger #PhilosophyOfMind #Interaction #SocialCognition #NeuralCorrelates #NCCP #Qualia #Self #I #Enactivism #ComplexSystems #NonlinearDynamics #FreeWill #Responsibility #ArtificialIntelligence #AI #QuantumPhysics #AntonZeilinger

🧠 #CulturalEvolution – Why #Brains need to interact 🧑‍🧑‍🧒

📺 https://youtu.be/C2FVIbAyaH4

📎 https://philosophies.de/index.php/2022/03/22/kann-das-gehirn-das-gehirn-verstehen/

#CulturalEvolution #Consciousness #Neuroscience #CognitiveNeuroscience #WolfSinger #PhilosophyOfMind #Interaction #SocialCognition #NeuralCorrelates #NCCP #Qualia #Self #I #Enactivism #ComplexSystems #NonlinearDynamics #FreeWill #Responsibility #ArtificialIntelligence #AI #QuantumPhysics #AntonZeilinger

🧠 #CulturalEvolution – Why #Brains need to interact 🧑‍🧑‍🧒

📺 https://youtu.be/C2FVIbAyaH4

📎 https://philosophies.de/index.php/2022/03/22/kann-das-gehirn-das-gehirn-verstehen/

#CulturalEvolution #Consciousness #Neuroscience #CognitiveNeuroscience #WolfSinger #PhilosophyOfMind #Interaction #SocialCognition #NeuralCorrelates #NCCP #Qualia #Self #I #Enactivism #ComplexSystems #NonlinearDynamics #FreeWill #Responsibility #ArtificialIntelligence #AI #QuantumPhysics #AntonZeilinger

🧠 #CulturalEvolution – Why #Brains need to interact 🧑‍🧑‍🧒

📺 https://youtu.be/C2FVIbAyaH4

📎 https://philosophies.de/index.php/2022/03/22/kann-das-gehirn-das-gehirn-verstehen/

#CulturalEvolution #Consciousness #Neuroscience #CognitiveNeuroscience #WolfSinger #PhilosophyOfMind #Interaction #SocialCognition #NeuralCorrelates #NCCP #Qualia #Self #I #Enactivism #ComplexSystems #NonlinearDynamics #FreeWill #Responsibility #ArtificialIntelligence #AI #QuantumPhysics #AntonZeilinger

🧠 #CulturalEvolution – Why #Brains need to interact 🧑‍🧑‍🧒

📺 https://youtu.be/C2FVIbAyaH4

📎 https://philosophies.de/index.php/2022/03/22/kann-das-gehirn-das-gehirn-verstehen/

#CulturalEvolution #Consciousness #Neuroscience #CognitiveNeuroscience #WolfSinger #PhilosophyOfMind #Interaction #SocialCognition #NeuralCorrelates #NCCP #Qualia #Self #I #Enactivism #ComplexSystems #NonlinearDynamics #FreeWill #Responsibility #ArtificialIntelligence #AI #QuantumPhysics #AntonZeilinger

NewModelRelease: Compression–Resonance Thermodynamic Index (CRTI) A bounded dynamic phase framework describing structural overcompression, resonance attenuation,and tipping dynamics in adaptive systems. Zenodo DOI: doi.org/10.5281/zeno... #NonlinearDynamics #ComplexSystems Bernd von Mallinckrodt

Compression–Resonance Thermody...

NewModelRelease: Compression–Resonance Thermodynamic Index (CRTI) A bounded dynamic phase framework describing structural overcompression, resonance attenuation,and tipping dynamics in adaptive systems. Zenodo DOI: doi.org/10.5281/zeno... #NonlinearDynamics #ComplexSystems Bernd von Mallinckrodt

Compression–Resonance Thermody...

NewModelRelease: Compression–Resonance Thermodynamic Index (CRTI) A bounded dynamic phase framework describing structural overcompression, resonance attenuation,and tipping dynamics in adaptive systems. Zenodo DOI: doi.org/10.5281/zeno... #NonlinearDynamics #ComplexSystems Bernd von Mallinckrodt

Compression–Resonance Thermody...

When a thin interfacial layer reconfigures macroscopic flow.

🔗 https://journals.aps.org/prfluids/abstract/10.1103/hcyb-7nhz

#InterfacialPhysics #Hydrodynamics #NonlinearDynamics #Multiphase

In strategic terms: • Exploitation remains strong • Exploration becomes suppressed • Structural memory accumulates rigidity • The ambidextrous equilibrium disappears … Executive summary (strategy focus): doi.org/10.5281/zeno... #Strategy #NonlinearDynamics #Ambidexterity

Collapse through Hyper-Stabili...

Optimization does not always increase resilience. In a slow–fast dynamicalframework, I show how sustained efficiency pressure can eliminate adaptive switching capacity via a fold bifurcation. ExecutiveSummary (Strategic Management focus): doi.org/10.5281/zeno... #Strategy #NonlinearDynamics 🖖

Collapse through Hyper-Stabili...

Yeah Y'all know what this is.

#Zajey #Science #Research #ScientificMethod #SystemsThinking #Causality #CausalInference #DecisionScience #ComplexityScience #ComplexSystems #NonlinearDynamics #ChaosTheory #Probability #Statistics #Uncertainty #RiskAnalysis #Modeling #Inference
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Watching Waves on the Nanoscale

It’s tough to simulate nonlinear wave dynamics, so scientists often test theories in wave flumes, where they can create more controlled waves than what we see in the wild. But conventional wave flumes are big–meters-long, complicated equipment–and can only test a small range of conditions. To reach more extreme nonlinear dynamics, researchers have turned to a chip-based approach. These 100-micron-long wave flumes carry a film of superfluid helium less than 7 nanometers thick. But despite that tiny size, the system can reach levels of nonlinearity five orders of magnitude greater than their full-sized counterparts. (Image and research credit: M. Reeves et al.; via Physics Today)

Watching Waves on the Nanoscale

It’s tough to simulate nonlinear wave dynamics, so scientists often test theories in wave flumes, where they can create more controlled waves than what we see in the wild. But conventional wave flumes are big–meters-long, complicated equipment–and can only test a small range of conditions. To reach more extreme nonlinear dynamics, researchers have turned to a chip-based approach. These 100-micron-long wave flumes carry a film of superfluid helium less than 7 nanometers thick. But despite that tiny size, the system can reach levels of nonlinearity five orders of magnitude greater than their full-sized counterparts. (Image and research credit: M. Reeves et al.; via Physics Today)

Watching Waves on the Nanoscale

It’s tough to simulate nonlinear wave dynamics, so scientists often test theories in wave flumes, where they can create more controlled waves than what we see in the wild. But conventional wave flumes are big–meters-long, complicated equipment–and can only test a small range of conditions. To reach more extreme nonlinear dynamics, researchers have turned to a chip-based approach. These 100-micron-long wave flumes carry a film of superfluid helium less than 7 nanometers thick. But despite that tiny size, the system can reach levels of nonlinearity five orders of magnitude greater than their full-sized counterparts. (Image and research credit: M. Reeves et al.; via Physics Today)

Watching Waves on the Nanoscale

It’s tough to simulate nonlinear wave dynamics, so scientists often test theories in wave flumes, where they can create more controlled waves than what we see in the wild. But conventional wave flumes are big–meters-long, complicated equipment–and can only test a small range of conditions. To reach more extreme nonlinear dynamics, researchers have turned to a chip-based approach. These 100-micron-long wave flumes carry a film of superfluid helium less than 7 nanometers thick. But despite that tiny size, the system can reach levels of nonlinearity five orders of magnitude greater than their full-sized counterparts. (Image and research credit: M. Reeves et al.; via Physics Today)

Watching Waves on the Nanoscale

It’s tough to simulate nonlinear wave dynamics, so scientists often test theories in wave flumes, where they can create more controlled waves than what we see in the wild. But conventional wave flumes are big–meters-long, complicated equipment–and can only test a small range of conditions. To reach more extreme nonlinear dynamics, researchers have turned to a chip-based approach. These 100-micron-long wave flumes carry a film of superfluid helium less than 7 nanometers thick. But despite that tiny size, the system can reach levels of nonlinearity five orders of magnitude greater than their full-sized counterparts. (Image and research credit: M. Reeves et al.; via Physics Today)

Toward Predicting Rogue Waves

Rogue waves were once the stuff of nautical legend. Tales of giant lone waves were considered sailors’ tall tales, until an oil rig in the North Sea was hit by a 25.6-meter wave on 1 January 1995. The wave was more than twice the height of any others around it and much steeper, too. Since then, scientists have been working to understand how and why these rogue waves form.

A recent study, like many others, attributes rogue waves to the subtle nonlinearities of ocean waves, which don’t match a smooth sinusoid even though they are sometimes modeled that way. When it comes to rogue waves, the sharpness of a wave’s peak and flattening of its trough affect whether waves come together into a lone giant.

The study is based on 18 years worth of wave data collected at an offshore platform in the North Sea. With such an extensive data set, researchers were able to find patterns in the waves that precede the arrival of a rogue wave. That’s an important step toward being able to predict a rogue wave, which would help protect platforms, ships, and personnel. (Image credit: C. Wou; research credit: S. Knobler et al.; via SciAm)

Toward Predicting Rogue Waves

Rogue waves were once the stuff of nautical legend. Tales of giant lone waves were considered sailors’ tall tales, until an oil rig in the North Sea was hit by a 25.6-meter wave on 1 January 1995. The wave was more than twice the height of any others around it and much steeper, too. Since then, scientists have been working to understand how and why these rogue waves form.

A recent study, like many others, attributes rogue waves to the subtle nonlinearities of ocean waves, which don’t match a smooth sinusoid even though they are sometimes modeled that way. When it comes to rogue waves, the sharpness of a wave’s peak and flattening of its trough affect whether waves come together into a lone giant.

The study is based on 18 years worth of wave data collected at an offshore platform in the North Sea. With such an extensive data set, researchers were able to find patterns in the waves that precede the arrival of a rogue wave. That’s an important step toward being able to predict a rogue wave, which would help protect platforms, ships, and personnel. (Image credit: C. Wou; research credit: S. Knobler et al.; via SciAm)

Toward Predicting Rogue Waves

Rogue waves were once the stuff of nautical legend. Tales of giant lone waves were considered sailors’ tall tales, until an oil rig in the North Sea was hit by a 25.6-meter wave on 1 January 1995. The wave was more than twice the height of any others around it and much steeper, too. Since then, scientists have been working to understand how and why these rogue waves form.

A recent study, like many others, attributes rogue waves to the subtle nonlinearities of ocean waves, which don’t match a smooth sinusoid even though they are sometimes modeled that way. When it comes to rogue waves, the sharpness of a wave’s peak and flattening of its trough affect whether waves come together into a lone giant.

The study is based on 18 years worth of wave data collected at an offshore platform in the North Sea. With such an extensive data set, researchers were able to find patterns in the waves that precede the arrival of a rogue wave. That’s an important step toward being able to predict a rogue wave, which would help protect platforms, ships, and personnel. (Image credit: C. Wou; research credit: S. Knobler et al.; via SciAm)

Toward Predicting Rogue Waves

Rogue waves were once the stuff of nautical legend. Tales of giant lone waves were considered sailors’ tall tales, until an oil rig in the North Sea was hit by a 25.6-meter wave on 1 January 1995. The wave was more than twice the height of any others around it and much steeper, too. Since then, scientists have been working to understand how and why these rogue waves form.

A recent study, like many others, attributes rogue waves to the subtle nonlinearities of ocean waves, which don’t match a smooth sinusoid even though they are sometimes modeled that way. When it comes to rogue waves, the sharpness of a wave’s peak and flattening of its trough affect whether waves come together into a lone giant.

The study is based on 18 years worth of wave data collected at an offshore platform in the North Sea. With such an extensive data set, researchers were able to find patterns in the waves that precede the arrival of a rogue wave. That’s an important step toward being able to predict a rogue wave, which would help protect platforms, ships, and personnel. (Image credit: C. Wou; research credit: S. Knobler et al.; via SciAm)

Toward Predicting Rogue Waves

Rogue waves were once the stuff of nautical legend. Tales of giant lone waves were considered sailors’ tall tales, until an oil rig in the North Sea was hit by a 25.6-meter wave on 1 January 1995. The wave was more than twice the height of any others around it and much steeper, too. Since then, scientists have been working to understand how and why these rogue waves form.

A recent study, like many others, attributes rogue waves to the subtle nonlinearities of ocean waves, which don’t match a smooth sinusoid even though they are sometimes modeled that way. When it comes to rogue waves, the sharpness of a wave’s peak and flattening of its trough affect whether waves come together into a lone giant.

The study is based on 18 years worth of wave data collected at an offshore platform in the North Sea. With such an extensive data set, researchers were able to find patterns in the waves that precede the arrival of a rogue wave. That’s an important step toward being able to predict a rogue wave, which would help protect platforms, ships, and personnel. (Image credit: C. Wou; research credit: S. Knobler et al.; via SciAm)

🧠 New preprint on adaptive contagion dynamics on #hypergraphs by Mancastroppa, Karsai, & Barrat.

The key result: adaptive, locally informed behavior can neutralize explosive phase transitions in higher-order contagion. Group-level awareness suppresses nonlinear reinforcement, shrinks bistability, and can turn a discontinuous transition into a continuous one. A nice mechanistic link between adaptivity, higher-order interactions, and phase transitions.

#ComplexSystems #NonlinearDynamics

🧠 New preprint on adaptive contagion dynamics on #hypergraphs by Mancastroppa, Karsai, & Barrat.

The key result: adaptive, locally informed behavior can neutralize explosive phase transitions in higher-order contagion. Group-level awareness suppresses nonlinear reinforcement, shrinks bistability, and can turn a discontinuous transition into a continuous one. A nice mechanistic link between adaptivity, higher-order interactions, and phase transitions.

#ComplexSystems #NonlinearDynamics

🧠 New preprint on adaptive contagion dynamics on #hypergraphs by Mancastroppa, Karsai, & Barrat.

The key result: adaptive, locally informed behavior can neutralize explosive phase transitions in higher-order contagion. Group-level awareness suppresses nonlinear reinforcement, shrinks bistability, and can turn a discontinuous transition into a continuous one. A nice mechanistic link between adaptivity, higher-order interactions, and phase transitions.

#ComplexSystems #NonlinearDynamics

🧠 New preprint on adaptive contagion dynamics on #hypergraphs by Mancastroppa, Karsai, & Barrat.

The key result: adaptive, locally informed behavior can neutralize explosive phase transitions in higher-order contagion. Group-level awareness suppresses nonlinear reinforcement, shrinks bistability, and can turn a discontinuous transition into a continuous one. A nice mechanistic link between adaptivity, higher-order interactions, and phase transitions.

#ComplexSystems #NonlinearDynamics

🧠 New preprint on adaptive contagion dynamics on #hypergraphs by Mancastroppa, Karsai, & Barrat.

The key result: adaptive, locally informed behavior can neutralize explosive phase transitions in higher-order contagion. Group-level awareness suppresses nonlinear reinforcement, shrinks bistability, and can turn a discontinuous transition into a continuous one. A nice mechanistic link between adaptivity, higher-order interactions, and phase transitions.

#ComplexSystems #NonlinearDynamics

Predicting Sea States

Transferring cargo between ships and landing aircraft on carriers requires predicting how the waves will behave for the next few minutes. That’s a notoriously difficult task for several reasons: rough seas can hide a ship radar’s view and the inherent nonlinearity of ocean waves means that they can occasionally coalesce unexpectedly large (“rogue“) waves, seemingly from nowhere.

A new study describes a technique for improving sea state predictions. In their model, the team first use multiple radar returns to average out gaps in the current wave state data, then feed that interpolated data into a prediction algorithm that includes nonlinearities up to the third-order. The results, they found, gave far better predictions than current techniques, some of which had errors 3 times as high. (Image credit: R. Ding; research credit: J. Yao et al.; via APS News)

#fluidDynamics #nonlinearDynamics #oceanWaves #physics #science

Predicting Sea States

Transferring cargo between ships and landing aircraft on carriers requires predicting how the waves will behave for the next few minutes. That’s a notoriously difficult task for several reasons: rough seas can hide a ship radar’s view and the inherent nonlinearity of ocean waves means that they can occasionally coalesce unexpectedly large (“rogue“) waves, seemingly from nowhere.

A new study describes a technique for improving sea state predictions. In their model, the team first use multiple radar returns to average out gaps in the current wave state data, then feed that interpolated data into a prediction algorithm that includes nonlinearities up to the third-order. The results, they found, gave far better predictions than current techniques, some of which had errors 3 times as high. (Image credit: R. Ding; research credit: J. Yao et al.; via APS News)

#fluidDynamics #nonlinearDynamics #oceanWaves #physics #science

Predicting Sea States

Transferring cargo between ships and landing aircraft on carriers requires predicting how the waves will behave for the next few minutes. That’s a notoriously difficult task for several reasons: rough seas can hide a ship radar’s view and the inherent nonlinearity of ocean waves means that they can occasionally coalesce unexpectedly large (“rogue“) waves, seemingly from nowhere.

A new study describes a technique for improving sea state predictions. In their model, the team first use multiple radar returns to average out gaps in the current wave state data, then feed that interpolated data into a prediction algorithm that includes nonlinearities up to the third-order. The results, they found, gave far better predictions than current techniques, some of which had errors 3 times as high. (Image credit: R. Ding; research credit: J. Yao et al.; via APS News)

#fluidDynamics #nonlinearDynamics #oceanWaves #physics #science

Predicting Sea States

Transferring cargo between ships and landing aircraft on carriers requires predicting how the waves will behave for the next few minutes. That’s a notoriously difficult task for several reasons: rough seas can hide a ship radar’s view and the inherent nonlinearity of ocean waves means that they can occasionally coalesce unexpectedly large (“rogue“) waves, seemingly from nowhere.

A new study describes a technique for improving sea state predictions. In their model, the team first use multiple radar returns to average out gaps in the current wave state data, then feed that interpolated data into a prediction algorithm that includes nonlinearities up to the third-order. The results, they found, gave far better predictions than current techniques, some of which had errors 3 times as high. (Image credit: R. Ding; research credit: J. Yao et al.; via APS News)

#fluidDynamics #nonlinearDynamics #oceanWaves #physics #science