TianJi-Environ is a WRF-Chem-based multi-agent AI framework for autonomous validation of atmospheric chemistry mechanisms through executable experiments and evidence assessment.
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5 Pith papers cite this work, alongside 2,312 external citations. Polarity classification is still indexing.
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Mat2Boundary treats boundary conditions as sparse matrix-vector products and uses multi-stage compilation with polyhedral analysis to generate efficient matrix-free kernels and communication schedules for distributed block-structured PDE solvers.
Atmosphere functions as steam engine with global power 4.4±0.9 W/m² from water cycle, matching total atmospheric power 4.3±0.6 W/m² and explaining condensation-driven dynamics via precipitation.
FRAMe combines an LLM planner with RAG-based memory and a multi-modal coach agent to generate valid, preference-aligned eVTOL flight plans, achieving up to 93.8% validity across four LLMs.
High-resolution WRF atmospheric models show that wind-induced shifts in meteorite ground positions are typically 143-307 m, exceeding observational uncertainties, with successful use in recovering 12 meteorites and open release of 1107 models for 302 events.
citing papers explorer
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TianJi-Environ: An Autonomous AI Scientist for Atmospheric Environmental Research
TianJi-Environ is a WRF-Chem-based multi-agent AI framework for autonomous validation of atmospheric chemistry mechanisms through executable experiments and evidence assessment.
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Mat2Boundary: Treating User-Defined Boundary Condition as SpMV for Distributed PDE Solvers on Block-Structured Grids
Mat2Boundary treats boundary conditions as sparse matrix-vector products and uses multi-stage compilation with polyhedral analysis to generate efficient matrix-free kernels and communication schedules for distributed block-structured PDE solvers.
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Atmosphere as a steam engine
Atmosphere functions as steam engine with global power 4.4±0.9 W/m² from water cycle, matching total atmospheric power 4.3±0.6 W/m² and explaining condensation-driven dynamics via precipitation.
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End-to-End LLM Flight Planning with RAG-based Memory and Multi-modal Coach Agent
FRAMe combines an LLM planner with RAG-based memory and a multi-modal coach agent to generate valid, preference-aligned eVTOL flight plans, achieving up to 93.8% validity across four LLMs.
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Freo Doctor: Atmospheric Modelling for Meteorite Falls and Spacecraft Re-Entries
High-resolution WRF atmospheric models show that wind-induced shifts in meteorite ground positions are typically 143-307 m, exceeding observational uncertainties, with successful use in recovering 12 meteorites and open release of 1107 models for 302 events.