Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T22:21:17.161599Z
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2607.04009.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T22:21:17.161599Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
47 of 47 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 2ebf8a5d-a000-4e2a-a514-3d3457772c2d · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics SimpleEuleriantimecorrelationoffull-andnarrow-bandvelocitysignalsingrid-generated, ‘isotropic’ turbulence,
Reference 1
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Observation c2c56c3d-89b5-48d1-b974-e1847bd22619 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Direct numerical simulation of turbulent channel flow up to,
Reference 2
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Observation b517f4d4-f4f3-4123-8bdf-90767cab51cf · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Combined heat transfer and fluid dynamic measurements downstream of a backward-facing step,
Reference 3
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Observation dfbb9d77-79f1-4954-86b1-8417f4d9fa74 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Flow over periodic hills–numerical and experimental study in a wide range of Reynolds numbers,
Reference 4
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Observation eb333b78-ed0e-4e2c-bc0a-dd04aebdc214 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Anisotropy of turbulence at the core of the tip and hub vortices shed by a marine propeller,
Reference 5
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Observation f91cbf29-3f60-4a3c-8866-00591a5a055b · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics K.,An Introduction to Fluid Dynamics, Cambridge University Press, Cambridge, UK, 2000
Reference 6
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Observation 1c7b3323-82f2-4ce8-9d67-6be1072a1a21 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Vortex identification: New requirements and limitations,
Reference 7
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Observation d95701cd-89c5-456e-9957-2261f995c150 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Rortex—Anewvortexvectordefinitionandvorticitytensorandvectordecompositions,
Reference 8
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Observation 60b0f2a0-cafe-4e0f-9043-b35f50c4a574 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics The Schur decomposition of the velocity gradient tensor for turbulent flows,
Reference 9
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Observation 9a07e8aa-6316-4851-841c-28b6e6baf82b · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics The triple decomposition of the velocity gradient tensor as a standardized real Schur form,
Reference 10
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Observation 9f2991e8-0109-48e2-b3e1-47924d38ff3e · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Rortex based velocity gradient tensor decomposition,
Reference 11
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Observation a211311a-cec3-47b2-866d-a42224ae389f · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Can vortex criteria be objectivized?
Reference 12
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Observation 13349021-2cbc-4893-acc7-6f2c8a69d81f · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Revisiting turbulence small-scale behavior using velocity gradient triple decomposition,
Reference 13
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Observation 5aa9c382-9e96-4645-be08-025e9491064b · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Statistical properties of shear and nonshear velocity components in isotropic turbulence and turbulent jets,
Reference 14
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Observation a72dbd04-7baf-4970-916e-7bf1594a805d · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Velocity gradient partitioning in turbulent flows,
Reference 15
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Observation 7cf3ad2e-0e80-4594-9307-6c1d16b91f0c · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Numericalinvestigationofdiscontinuousiceeffectsonsweptwings,
Reference 16
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Observation 0232ad51-34f2-4f69-9274-6a77eca3f8fa · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics OpenFOAMGPT: A retrieval-augmented large language model (LLM) agent for OpenFOAM-based computational fluid dynamics,
Reference 17
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Observation 9d366719-109e-40ae-bc39-c483b97e0e78 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics OpenFOAMGPT 2.0: end-to-end, trustworthy automation for computational fluid dynamics
Reference 18
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Observation e6c29a56-9fef-45d9-a16a-1c2c7be3650d · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Foam-Agent 2.0: An End-to-End Composable Multi-Agent Framework for Automating CFD Simulation in OpenFOAM,
Reference 19
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Observation 862d571d-f874-48a3-b1f5-03cbedc84409 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Automating Computational Fluid Dynamics with LLM-based Multi-Agent Systems,
Reference 20
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Observation 76f70635-62a5-4c27-ad65-96e4b9f78eae · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics FoamGPT: Fine-Tuning Large Language Model for Agentic Automation of CFD Simulations with OpenFOAM,
Reference 21
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Observation 0272deca-5d11-4de2-b7cd-9f8a2481c807 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics CFDAgent: A language-guided, zero-shot multi-agent system for complex flow simulation,
Reference 22
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Observation cf644a79-9436-404a-8116-b7437e6bae51 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics ChatCFD: An LLM-Driven Agent for End-to-End CFD Automation with Domain-Specific Structured Reasoning,
Reference 23
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Observation 417911a6-1a19-4431-abaf-bef7b4eb3cb6 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Towards LLM-enabled autonomous combustion research: A literature-aware agent for self-corrective modeling workflows,
Reference 24
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Observation 5f2814c1-6a83-4f83-b6e5-39ef8306ade1 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics From Natural-Language to Simulation: An Intermediate Representation for Computational Fluid Dynamics,
Reference 25
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Observation d3f74881-f200-4e5f-9fe8-08c366e84972 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Aerodynamic Design and Optimization via a Specialized Agentic Generative AI Framework,
Reference 26
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Observation 11c963ee-ae1b-4c7e-8661-a4b31054abca · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics AirfoilAgent: Airfoil aerodynamics optimization design via large language model multi-agent collaborations,
Reference 27
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Observation dc522d68-86d0-44e6-b2ef-c3ecea1beee9 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Agentic AI for Conversational Aerodynamic Analysis and Optimization of Airfoils and Wings,
Reference 28
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Observation 4720e390-596e-4540-b892-3d3528c163c3 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics A Multidisciplinary Design and Optimization (MDO) Agent Driven by Large Language Models,
Reference 29
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Observation 01d966b4-454f-456c-9e16-b6512e92392e · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Fromconcepttomanufacturing: Evaluating vision-language models for engineering design,
Reference 30
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Observation 8db44c68-8d20-43c7-8a67-7dbc99616e89 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics AI agents in engineering design: a multi-agent framework for aesthetic and aerodynamic car design,
Reference 31
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Observation 4ff0fded-97b7-4c7f-889f-c059402e4a51 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Agentic Risk-Aware Set-Based Engineering Design
Reference 32
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Observation e7ee19c3-35bd-4813-8129-dc8e7a4bc6be · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics AutoTurb: Using large language models for automatic algebraic turbulence model discovery,
Reference 33
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Observation 8c42a291-2877-4d1b-9daa-9d1113679f25 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Large language model driven development of turbulence models,
Reference 34
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Observation 89f8e96e-cbb6-4fb7-b3d8-f661368ffe78 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Code2MCP: Transforming Code Repositories into MCP Services,
Reference 35
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Observation 8d870484-8dcc-4ee6-84f7-15da241aae7b · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics ToolRosella: Translating Code Repositories into Standardized Tools for Scientific Agents
Reference 36
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Observation 08a5cef6-d4fc-42f7-952b-22e8f4b6a910 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics From static templates to dynamic runtime graphs: A survey of workflow optimization for llm agents,
Reference 37
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Observation 76b0829d-6eac-41d8-abb8-bdbc5ca32055 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations
Reference 38
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Observation 25dfa72a-3b74-4ab7-b75c-36340a4a6679 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics ALiutex-basedsubgridstressmodelforlarge-eddy simulation,
Reference 39
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Observation 535e74e8-7111-4f7f-8369-7f028bf7504f · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Liutex-Based Sub-Grid Model for Large Eddy Simulation of Turbulent Flow,
Reference 40
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Observation 54681eb4-d950-4795-a9f0-7ad6658990a8 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Near-Wall Scaling and Separation Prediction of a Rotation-Based Subgrid-Scale Stress Model
Reference 41
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Observation a69f2b59-8a3f-45b5-85f5-4c32d691e355 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics A Relative Liutex Method for Vortex Identification,
Reference 42
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Observation 0558a38e-2a5d-43ba-9f84-084d0beb7450 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics A Dynamic Subgrid-Scale Model Based on Liutex Theory for Wall-Bounded Turbulent Flows,
Reference 43
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Observation e489e841-7204-46ee-af7d-90fabbeeb9c2 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics OpenFOAM:AC++libraryforcomplexphysicssimulations,
Reference 44
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Observation 54142f37-842b-478c-b3f2-fcc209777329 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Explicit formula for the Liutex vector and physical meaning of vorticity based on the Liutex-Shear decomposition,
Reference 45
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Observation bb6ee2c7-9d7e-4df6-a708-91f4da0baa11 · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics Identifying the tangle of vortex tubes in homogeneous isotropic turbulence,
Reference 46
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Observation 683045de-e309-4da5-a2c4-77bdc3d64dce · outbound
PhysMiner: An Agentic AI Framework for Discovering Turbulence Physics A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers,
Reference 47
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No inbound Pith citation observations are available.