EOS-Bench creates thousands of satellite scheduling test cases spanning small to large scales and evaluates multiple solver types across five performance metrics.
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8 Pith papers cite this work. Polarity classification is still indexing.
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A polynomial optimization method with reduced-order weighting and zero-solution avoidance achieves roughly three orders of magnitude better accuracy in angles-only initial relative orbit determination than baseline approaches.
A Faster R-CNN detector paired with a Transformer-augmented MLP reconstructs parent-child lineages during ligament fragmentation from impinging jet images, achieving 0.872 F1 for detection and 86.1% association accuracy with perfect fragmentation recall.
BlendedNet++ provides a new dataset of 12,492 BWB geometries with RANS-derived Cp and Cf fields and benchmarks geometric deep learning for field prediction plus conditional diffusion models for inverse design achieving R^2 > 0.99 on lift-to-drag targets verified by CFD.
Two general-purpose methods transcribe multi-dimensional Gaussian chance constraints for trajectory optimization with reduced conservatism, paired with a quadratic-complexity risk estimator that remains accurate in high dimensions.
A latent-space reduced-order model using autoencoders and learned dynamics enables Bayesian recovery of initial density and pressure in Sod shock tube simulations, with posterior uncertainty contracting substantially as observation density increases.
A discrete adjoint GKS is developed and verified for efficient aerodynamic shape optimization in turbulent flows, achieving design goals in few cycles.
Prescribed wall heating in a rarefied converging-diverging micro-nozzle increases specific impulse from 156 s to 201 s by thermal and pressure thrust gains that exceed the mass-flow penalty from increased blockage.
citing papers explorer
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EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling
EOS-Bench creates thousands of satellite scheduling test cases spanning small to large scales and evaluates multiple solver types across five performance metrics.
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Robust Angles-Only Initial Relative Orbit Determination Using Polynomial Optimization
A polynomial optimization method with reduced-order weighting and zero-solution avoidance achieves roughly three orders of magnitude better accuracy in angles-only initial relative orbit determination than baseline approaches.
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Deep Learning-Based Tracking and Lineage Reconstruction of Ligament Breakup
A Faster R-CNN detector paired with a Transformer-augmented MLP reconstructs parent-child lineages during ligament fragmentation from impinging jet images, achieving 0.872 F1 for detection and 86.1% association accuracy with perfect fragmentation recall.
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BlendedNet++: A dataset and benchmark for field-resolved aerodynamics and inverse design of blended wing body aircraft
BlendedNet++ provides a new dataset of 12,492 BWB geometries with RANS-derived Cp and Cf fields and benchmarks geometric deep learning for field prediction plus conditional diffusion models for inverse design achieving R^2 > 0.99 on lift-to-drag targets verified by CFD.
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Chance constraints transcription and failure risk estimation for stochastic trajectory optimisation
Two general-purpose methods transcribe multi-dimensional Gaussian chance constraints for trajectory optimization with reduced conservatism, paired with a quadratic-complexity risk estimator that remains accurate in high dimensions.
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The impact of observation density on Bayesian inversion of latent dynamics in shock-dominated flows
A latent-space reduced-order model using autoencoders and learned dynamics enables Bayesian recovery of initial density and pressure in Sod shock tube simulations, with posterior uncertainty contracting substantially as observation density increases.
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A Discrete Adjoint Gas-Kinetic Scheme for Aerodynamic Shape Optimization in Turbulent Continuum Flows
A discrete adjoint GKS is developed and verified for efficient aerodynamic shape optimization in turbulent flows, achieving design goals in few cycles.
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Prescribed Wall-Heat-Flux Control of Blockage and Impulse in a Rarefied Micro-Nozzle
Prescribed wall heating in a rarefied converging-diverging micro-nozzle increases specific impulse from 156 s to 201 s by thermal and pressure thrust gains that exceed the mass-flow penalty from increased blockage.