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2026
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| Online Access: | https://doi.org/10.5281/zenodo.20323222 |
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| author | Özbil, Halil |
| author_facet | Özbil, Halil |
| contents | <h2>Short Description</h2> <p>This work presents a stability-theoretic framework for adaptive noise harvesting in stochastic dynamical systems.<br>The proposed approach combines Lyapunov stability analysis, entropy-regulated adaptive harvesting, Fokker–Planck stationary distribution analysis, and reproducible Monte Carlo simulations within a unified stochastic-control framework.</p> <p>The study demonstrates that externally supplied stochastic fluctuations can be adaptively redistributed into useful energetic behavior while preserving mean-square stability under bounded entropy conditions.</p> <p>The package includes:</p> <ul> <li>full research manuscript,</li> <li>reproducible Python simulation code,</li> <li>Monte Carlo datasets,</li> <li>generated figures,</li> <li>Fokker–Planck analysis,</li> <li>and reproducibility documentation.</li> </ul> <p>This work does not claim perpetual energy generation or violation of thermodynamic laws.<br>Instead, it studies controlled stochastic energy redistribution under adaptive stability constraints.</p> <h1>Long Description</h1> <p>Adaptive Noise Harvesting and Stability-Preserving Stochastic Energy Redistribution introduces a unified mathematical and computational framework for controlled stochastic energy redistribution in nonlinear dynamical systems.</p> <p>The work integrates:</p> <ul> <li>stochastic differential equations,</li> <li>Lyapunov-based stability guarantees,</li> <li>entropy-regulated adaptive harvesting,</li> <li>Fokker–Planck stationary distribution analysis,</li> <li>and Monte Carlo reproducibility protocols.</li> </ul> <p>A stochastic harmonic oscillator with adaptive harvesting-aware feedback is used as the reference system.<br>The study proposes:</p> <ul> <li>a Noise Harvesting Functional,</li> <li>an entropy-aware adaptive efficiency model,</li> <li>the Stability–Harvesting Score (SHS),</li> <li>and the concept of an Optimal Noise Ridge.</li> </ul> <p>The framework demonstrates that stochastic fluctuations can contribute constructively to adaptive energetic utilization when bounded stability conditions are enforced.</p> <p>The package contains:</p> <ul> <li>full HTML/PDF research manuscript,</li> <li>reproducible Python source code,</li> <li>generated simulation figures,</li> <li>Monte Carlo statistical outputs,</li> <li>JSON result archives,</li> <li>and reproducibility metadata.</li> </ul> <p>Main contributions include:</p> <ol> <li>Stability-preserving stochastic redistribution framework</li> <li>Lyapunov mean-square stability theorem</li> <li>Entropy-regulated adaptive harvesting efficiency</li> <li>Fokker–Planck stationary variance analysis</li> <li>SHS metric and normalization discussion</li> <li>Monte Carlo reproducibility protocol</li> <li>Piezoelectric electromechanical coupling interpretation</li> </ol> <p>This research is presented as a theoretical and computational research demonstrator.<br>No claim is made regarding perpetual motion, free-energy systems, or violations of thermodynamic conservation laws.</p> <p>Author: Halil Özbil<br>Independent Researcher<br>Bergama, İzmir, Türkiye</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20323222 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
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| spellingShingle | Adaptive Noise Harvesting and Stability-Preserving Stochastic Energy Redistribution A Lyapunov–Fokker–Planck Framework with Entropy Regulation and Monte Carlo Validation Özbil, Halil <h2>Short Description</h2> <p>This work presents a stability-theoretic framework for adaptive noise harvesting in stochastic dynamical systems.<br>The proposed approach combines Lyapunov stability analysis, entropy-regulated adaptive harvesting, Fokker–Planck stationary distribution analysis, and reproducible Monte Carlo simulations within a unified stochastic-control framework.</p> <p>The study demonstrates that externally supplied stochastic fluctuations can be adaptively redistributed into useful energetic behavior while preserving mean-square stability under bounded entropy conditions.</p> <p>The package includes:</p> <ul> <li>full research manuscript,</li> <li>reproducible Python simulation code,</li> <li>Monte Carlo datasets,</li> <li>generated figures,</li> <li>Fokker–Planck analysis,</li> <li>and reproducibility documentation.</li> </ul> <p>This work does not claim perpetual energy generation or violation of thermodynamic laws.<br>Instead, it studies controlled stochastic energy redistribution under adaptive stability constraints.</p> <h1>Long Description</h1> <p>Adaptive Noise Harvesting and Stability-Preserving Stochastic Energy Redistribution introduces a unified mathematical and computational framework for controlled stochastic energy redistribution in nonlinear dynamical systems.</p> <p>The work integrates:</p> <ul> <li>stochastic differential equations,</li> <li>Lyapunov-based stability guarantees,</li> <li>entropy-regulated adaptive harvesting,</li> <li>Fokker–Planck stationary distribution analysis,</li> <li>and Monte Carlo reproducibility protocols.</li> </ul> <p>A stochastic harmonic oscillator with adaptive harvesting-aware feedback is used as the reference system.<br>The study proposes:</p> <ul> <li>a Noise Harvesting Functional,</li> <li>an entropy-aware adaptive efficiency model,</li> <li>the Stability–Harvesting Score (SHS),</li> <li>and the concept of an Optimal Noise Ridge.</li> </ul> <p>The framework demonstrates that stochastic fluctuations can contribute constructively to adaptive energetic utilization when bounded stability conditions are enforced.</p> <p>The package contains:</p> <ul> <li>full HTML/PDF research manuscript,</li> <li>reproducible Python source code,</li> <li>generated simulation figures,</li> <li>Monte Carlo statistical outputs,</li> <li>JSON result archives,</li> <li>and reproducibility metadata.</li> </ul> <p>Main contributions include:</p> <ol> <li>Stability-preserving stochastic redistribution framework</li> <li>Lyapunov mean-square stability theorem</li> <li>Entropy-regulated adaptive harvesting efficiency</li> <li>Fokker–Planck stationary variance analysis</li> <li>SHS metric and normalization discussion</li> <li>Monte Carlo reproducibility protocol</li> <li>Piezoelectric electromechanical coupling interpretation</li> </ol> <p>This research is presented as a theoretical and computational research demonstrator.<br>No claim is made regarding perpetual motion, free-energy systems, or violations of thermodynamic conservation laws.</p> <p>Author: Halil Özbil<br>Independent Researcher<br>Bergama, İzmir, Türkiye</p> |
| title | Adaptive Noise Harvesting and Stability-Preserving Stochastic Energy Redistribution A Lyapunov–Fokker–Planck Framework with Entropy Regulation and Monte Carlo Validation |
| url | https://doi.org/10.5281/zenodo.20323222 |