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Paper Citation Record · LEDGER

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network

As of 13 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2501.18078.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.18078 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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  • verified fuzzy14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f7bbc7b-41ca-47d4-8837-4c15ebf40d2b · outbound

This paper cites critical temperatures.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network critical temperatures

Reference 1

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This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 2

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This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 3

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Observation fe287353-db63-41f8-b183-bcbc2247ef0c · outbound

This paper cites critical temperature for the bottom side of the TPS.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network critical temperature for the bottom side of the TPS

Reference 4

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Observation c9207da6-89a2-4d52-855b-32c8011a8c65 · outbound

This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 5

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Observation 7258cebe-7a16-4619-be0b-ae77cad5b8f0 · outbound

This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 6

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Observation 851293e0-57ca-4ba8-aae0-3c2a11ff89b3 · outbound

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Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 7

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Observation 5d3bd7a4-0187-4f78-870d-2c1ed9e92af2 · outbound

This paper cites Keep sampling until the parameters stabilize and meet the critical temperature constraint.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Keep sampling until the parameters stabilize and meet the critical temperature constraint

Reference 8

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Observation b7790d5a-4185-4008-8ee5-09303819b2de · outbound

This paper cites Needs and Opportunities for Uncertainty-Based Multidisciplinary Design Methods for Aerospace Vehicles,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Needs and Opportunities for Uncertainty-Based Multidisciplinary Design Methods for Aerospace Vehicles,

Reference 9

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Observation 677a3fe2-a56e-4420-9397-0936a6b54a2d · outbound

This paper cites Adjust the parameters and constraints to improve performance if needed.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Adjust the parameters and constraints to improve performance if needed

Reference 10

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Observation 6f9a2798-40d5-4db2-be7b-293c1b97085e · outbound

This paper cites If not, continue adjusting and testing.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network If not, continue adjusting and testing

Reference 11

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Observation 5a974b30-159c-454d-8988-d27d34d5edbe · outbound

This paper cites The back temperature should not exceed a certain limit on the inside of the TPS.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network The back temperature should not exceed a certain limit on the inside of the TPS

Reference 12

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This paper cites The process begins with the selection of initial parameters, where geometric dimensions and material properties are chosen based on available materials or engineering estimates.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network The process begins with the selection of initial parameters, where geometric dimensions and material properties are chosen based on available materials or engineering estimates

Reference 13

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Observation 2f60c5a5-c135-4028-8769-92a5879740c7 · outbound

This paper cites The numerical solution of the Eq.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network The numerical solution of the Eq

Reference 14

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Observation 1cfac7ab-ab35-4d39-a5bd-6e6d6a278458 · outbound

This paper cites The PINN model showed good accuracy while running many times faster for parallel simulations.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network The PINN model showed good accuracy while running many times faster for parallel simulations

Reference 15

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Observation 7e1543d0-9371-4459-9321-d8274a104ea9 · outbound

This paper cites Probabilistic Design Method for Aircraft Thermal Protective Layers Based on Surrogate Models,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Probabilistic Design Method for Aircraft Thermal Protective Layers Based on Surrogate Models,

Reference 16

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Observation 52de5022-3eab-4abc-9a48-ec3b25f22fac · outbound

This paper cites Efficient strategy for reliability-based optimization design of multidisciplinary coupled system with interval parameters,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Efficient strategy for reliability-based optimization design of multidisciplinary coupled system with interval parameters,

Reference 17

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Observation db61543c-5f10-4856-b7e1-6b150ec6a25e · outbound

This paper cites Design of Thermal Protection System for Reusable Hypersonic Vehicle Using Inverse Approach,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Design of Thermal Protection System for Reusable Hypersonic Vehicle Using Inverse Approach,

Reference 18

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This paper cites Thermal Protection System and Thermal Management for Combined-Cycle Engine: Review and Prospects,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Thermal Protection System and Thermal Management for Combined-Cycle Engine: Review and Prospects,

Reference 19

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Observation 23d034bf-5e08-49fc-9350-d37801373538 · outbound

This paper cites A Parametric Physics-Informed Deep Learning Method for Probabilistic Design of Thermal Protection Systems,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A Parametric Physics-Informed Deep Learning Method for Probabilistic Design of Thermal Protection Systems,

Reference 20

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This paper cites Thermal protection systems for space vehicles: A review on technology development, current challenges and future prospects,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Thermal protection systems for space vehicles: A review on technology development, current challenges and future prospects,

Reference 21

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Observation c2d8e1c2-3a87-4630-94f7-e446f6010c5e · outbound

This paper cites Probabilistic transient thermal analysis of an atmospheric reentry vehicle structure,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Probabilistic transient thermal analysis of an atmospheric reentry vehicle structure,

Reference 22

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Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 23

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This paper cites Monte Carlo Treatment of Data Uncertainties in Thermal Analysis,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Monte Carlo Treatment of Data Uncertainties in Thermal Analysis,

Reference 24

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Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 25

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This paper cites Reliability-Based Optimization for Multidisciplinary System Design,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Reliability-Based Optimization for Multidisciplinary System Design,

Reference 26

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This paper cites Probabilistic Design of a Mars Sample Return Earth Entry Vehicle Thermal Protection System,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Probabilistic Design of a Mars Sample Return Earth Entry Vehicle Thermal Protection System,

Reference 27

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Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 28

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This paper cites Heat Conduction Plate Layout Optimization Using Physics-Driven Convolutional Neural Networks,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Heat Conduction Plate Layout Optimization Using Physics-Driven Convolutional Neural Networks,

Reference 29

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This paper cites On Machine-Learning-Driven Surrogates for Sound Transmission Loss Simulations,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network On Machine-Learning-Driven Surrogates for Sound Transmission Loss Simulations,

Reference 30

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This paper cites Uncertainty Analysis of Integrated Thermal Protection System with Rigid Insulation Bars,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Uncertainty Analysis of Integrated Thermal Protection System with Rigid Insulation Bars,

Reference 31

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This paper cites Uncertainty Quantification of Aero-Thermal Performance of a Blade Endwall Considering Slot Geometry Deviation and Mainstream Fluctuation,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Uncertainty Quantification of Aero-Thermal Performance of a Blade Endwall Considering Slot Geometry Deviation and Mainstream Fluctuation,

Reference 32

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This paper cites Thermo-mechanical optimization of metallic thermal protection system under aerodynamic heating,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Thermo-mechanical optimization of metallic thermal protection system under aerodynamic heating,

Reference 33

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This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 34

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Observation 000864ae-6bb6-4e2a-9f9b-f76d1dae1a68 · outbound

This paper cites Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam,

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0f7c2269-50d0-4f3a-b85a-5e25889d12ca · outbound

This paper cites A PINN Surrogate Modeling Methodology for Steady- State Integrated Thermofluid Systems Modeling,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A PINN Surrogate Modeling Methodology for Steady- State Integrated Thermofluid Systems Modeling,

Reference 36

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 500fdaa4-12c1-4ba9-81f3-505ee0eac099 · outbound

This paper cites PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d4b5abb7-ba90-4011-9628-cb69f2860318 · outbound

This paper cites Physics-Informed Deep Learning- Based Modeling of a Novel Elastohydrodynamic Seal for Supercritical CO2 Turbomachinery,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Physics-Informed Deep Learning- Based Modeling of a Novel Elastohydrodynamic Seal for Supercritical CO2 Turbomachinery,

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 3b071b8c-3330-4f1c-b15e-d78922a98e01 · outbound

This paper cites Apollo thermal- protection system development,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Apollo thermal- protection system development,

Reference 39

Resolution
verified exact
doi, observed 2026-08-10T00:50:57.325060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1a327d80-8cca-45f1-8233-9e2989a6d316 · outbound

This paper cites Probabilistic Modeling of Aerothermal and Thermal Protection Material Response Uncertainties,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Probabilistic Modeling of Aerothermal and Thermal Protection Material Response Uncertainties,

Reference 40

Resolution
verified exact
doi, observed 2026-08-10T00:50:57.292830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a56c3563-48aa-41fc-ad7c-845f2ba128d1 · outbound

This paper cites A survey of Monte Carlo methods for parameter estimation,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A survey of Monte Carlo methods for parameter estimation,

Reference 41

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no resolver link, observed 2026-08-10T00:50:57.067403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:50:57.067403Z digest=sha256:e558deeeadb90aecea22b8858a1d505ad09ead05c0377c22d82a45fcfbef1a42

Observation 8d75a644-dcfe-4f5d-acd3-ed03c67ec06d · outbound

This paper cites Efficient Sequential Monte-Carlo Samplers for Bayesian Inference.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Efficient Sequential Monte-Carlo Samplers for Bayesian Inference

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-10T00:50:57.266519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 54fd52ce-744e-4452-987c-c167fc9a365b · outbound

This paper cites A probabilistic fatigue life prediction for adhesively bonded joints via ANNs-based hybrid model,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A probabilistic fatigue life prediction for adhesively bonded joints via ANNs-based hybrid model,

Reference 43

Resolution
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arxiv_id_nonexistent, observed 2026-08-10T00:50:57.913628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9fe1be49-6000-4d4a-8cf2-0766681883b2 · outbound

This paper cites SpaceX to use LG Energy batteries for Starship rocket,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network SpaceX to use LG Energy batteries for Starship rocket,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:50:58.527288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation cf0d45e0-7e89-4977-9a84-8b5fffc3ff5f · outbound

This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 45

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2a91bcb7-6603-4068-8805-c26a5c2ba18a · outbound

This paper cites Implicit-explicit Runge-Kutta methods for time- dependent partial differential equations,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Implicit-explicit Runge-Kutta methods for time- dependent partial differential equations,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T00:50:57.092258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2965f89d-08e3-44d8-80f5-3a3151a707e0 · outbound

This paper cites Automatic differentiation in machine learning: a survey.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Automatic differentiation in machine learning: a survey

Reference 47

Resolution
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no resolver link, observed 2026-08-10T00:50:57.097070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:50:57.097070Z digest=sha256:c59d694f8207e393dac10fe048b829aed9319bca6e7b5c5bf914577ab0b6f515

Observation 359eb79f-9069-4d6b-979d-a86430f2d3e0 · outbound

This paper cites Deep learning | Nature.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Deep learning | Nature

Reference 48

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5101f2ca-784c-4657-8009-09c7e0b6f034 · outbound

This paper cites A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics - ScienceDirect.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics - ScienceDirect

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:50:58.480542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T00:50:57.107046Z digest=sha256:b422c3719a3bc48b4a2526b7a38d28c152eadb2930ea2dfc0cc984f6766406c0

Observation 17d341be-9377-45a0-832c-ad0f25c4b15e · outbound

This paper cites Deep Sparse Rectifier Neural Networks,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Deep Sparse Rectifier Neural Networks,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:50:58.464001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f7d2c267-ec46-4ec7-a3e6-1e776ee9fec5 · outbound

This paper cites The Metropolis-Hastings algorithm.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network The Metropolis-Hastings algorithm

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T00:50:57.117016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:50:57.117016Z digest=sha256:d807d84519324dabff844b1d044402dc3f5814b313402587c047578a249a80b3

Observation a9efd52f-27ae-4cee-929f-81be4e67249d · outbound

This paper cites A Cloud-based Real-time Probabilistic Remaining Useful Life (RUL) Estimation using the Sequential Monte Carlo (SMC) Method.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network A Cloud-based Real-time Probabilistic Remaining Useful Life (RUL) Estimation using the Sequential Monte Carlo (SMC) Method

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-10T00:50:57.201049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0dbf2544-2a3a-474e-ab55-5bb7699b8e34 · outbound

This paper cites Sequential monte carlo: Enabling real-time and high-fidelity prognostics,.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Sequential monte carlo: Enabling real-time and high-fidelity prognostics,

Reference 53

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T00:50:57.128358Z digest=sha256:3f405e35835bc14b2c7e6d0184ddb18801b6ce0589e283d9aab372d0fe324862

Observation 1f9cda53-e094-4b1c-8151-acefba5b3bf5 · outbound

This paper cites Thermal Characterization of Carbon Fiber-Reinforced Carbon Composites (C/C),.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Thermal Characterization of Carbon Fiber-Reinforced Carbon Composites (C/C),

Reference 54

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malformed identifier
doi_truncated, observed 2026-08-10T00:50:57.177607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T00:50:57.132656Z digest=sha256:bf7ec40ff13048add6d6b6c38c0a1ce1ce131dad5edf2fb6d97278529c74d1ec

Observation 4a4daee0-da5b-4ce2-ac65-580b4a903199 · outbound

This paper cites an unresolved cited work.

Statistical Design of Thermal Protection System Using Physics-Informed Neural Network Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-10T00:50:58.448009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

No inbound Pith citation observations are available.