""" Knowledge Base Initialization Script Loads initial nuclear energy domain knowledge from various sources. """ import os import json from typing import List, Dict, Any from loguru import logger # Sample nuclear energy knowledge base NUCLEAR_KNOWLEDGE_BASE = { "nuclear_physics": { "fission": { "description": "Nuclear fission is a reaction in which the nucleus of an atom splits into two or more smaller nuclei.", "key_concepts": [ "Chain reaction", "Critical mass", "Neutron multiplication factor", "Prompt neutrons vs delayed neutrons" ], "applications": ["Nuclear power generation", "Nuclear weapons", "Medical isotopes"], "equations": [ "E = mc²", "k_eff = (neutrons produced) / (neutrons absorbed or leaked)" ] }, "fusion": { "description": "Nuclear fusion is a reaction in which two or more atomic nuclei combine to form one or more different atomic nuclei.", "key_concepts": [ "Plasma confinement", "Coulomb barrier", "Reaction rate", "Triple product (nTτ)" ], "applications": ["Future power generation", "Hydrogen bombs", "Stellar processes"], "challenges": [ "Achieving sustained fusion reaction", "Plasma instability", "Tritium breeding", "Materials damage" ] }, "neutron_physics": { "description": "Study of neutron behavior in nuclear systems.", "topics": [ "Neutron transport", "Cross-sections", "Moderation", "Absorption", "Scattering" ] } }, "reactor_engineering": { "gen2_reactors": { "description": "Second generation reactors (1970s-1990s)", "types": ["PWR (Pressurized Water Reactor)", "BWR (Boiling Water Reactor)", "CANDU"], "characteristics": { "thermal_power": "1000-1500 MWth", "efficiency": "33-35%", "lifetime": "40 years (extended to 60-80)" } }, "gen3_reactors": { "description": "Third generation reactors (1990s-present)", "types": ["AP1000", "EPR", "ESBWR", "ACR-1000"], "improvements": [ "Enhanced safety systems", "Passive safety features", "Reduced construction time", "Higher efficiency (38-40%)" ] }, "gen4_reactors": { "description": "Fourth generation reactors (future)", "types": [ "Sodium-cooled fast reactors (SFR)", "Molten salt reactors (MSR)", "Very high temperature reactors (VHTR)", "Supercritical water reactors (SCWR)" ], "advantages": [ "Improved safety", "Reduced waste", "Better fuel utilization", "Process heat applications" ] }, "smr_microreactors": { "description": "Small Modular Reactors and Microreactors", "characteristics": { "power_output": "10-300 MWe", "applications": [ "Remote locations", "Industrial heat", "Desalination", "Hydrogen production", "District heating" ] } } }, "safety_management": { "defense_in_depth": { "description": "Multi-layered safety approach", "levels": [ "Prevention of abnormal operation", "Control of abnormal operation", "Mitigation of accident consequences", "Containment of radioactive material" ] }, "waste_management": { "description": "Nuclear waste handling and disposal", "categories": [ "Low-level waste (LLW)", "Intermediate-level waste (ILW)", "High-level waste (HLW)" ], "solutions": [ "Deep geological repositories", "Transmutation", "Partitioning and transmutation (P&T)", "Interim storage" ] }, "non_proliferation": { "description": "Preventing misuse of nuclear materials", "mechanisms": [ "IAEA safeguards", "Export controls", "Fuel bank concepts", "Spent fuel repositories" ] } }, "economics": { "lcoe": { "description": "Levelized Cost of Electricity", "components": [ "Capital costs", "Operations & maintenance", "Fuel costs", "Decommissioning costs", "Financing costs" ], "nuclear_lcoe": "60-100 USD/MWh (depending on region and reactor type)" }, "ppa_contracts": { "description": "Power Purchase Agreements", "types": [ "Fixed-price PPA", "Escalating PPA", "Indexed PPA" ] }, "tokenization": { "description": "Converting energy assets into blockchain tokens", "applications": [ "Uranium tokenization", "Energy credit trading", "Fractional ownership", "Decentralized energy markets" ] } }, "modern_applications": { "ai_data_centers": { "description": "Nuclear power for AI computing infrastructure", "advantages": [ "High reliability for 24/7 operation", "Low carbon footprint", "Predictable costs", "On-site generation" ], "examples": ["Google-NuScale partnership", "Microsoft-SMR exploration"] }, "desalination": { "description": "Using nuclear heat for water desalination", "technologies": [ "Multi-effect distillation (MED)", "Reverse osmosis (RO)", "Thermal desalination" ] }, "hydrogen_production": { "description": "Nuclear-powered hydrogen generation", "methods": [ "Electrolysis with nuclear electricity", "Thermochemical water splitting", "High-temperature steam electrolysis" ] }, "load_following": { "description": "Flexible nuclear power generation", "benefits": [ "Grid stability", "Renewable integration", "Reduced curtailment", "Improved economics" ] } } } def initialize_knowledge_base() -> Dict[str, Any]: """Initialize the knowledge base with nuclear energy domain knowledge.""" logger.info("Initializing Nuclear Intelligence knowledge base...") # Create knowledge base directory kb_dir = os.path.join(os.path.dirname(__file__), "..", "knowledge_base") os.makedirs(kb_dir, exist_ok=True) # Save knowledge base as JSON kb_file = os.path.join(kb_dir, "nuclear_knowledge_base.json") with open(kb_file, "w", encoding="utf-8") as f: json.dump(NUCLEAR_KNOWLEDGE_BASE, f, indent=2, ensure_ascii=False) logger.info(f"Knowledge base saved to {kb_file}") # Create index file index_file = os.path.join(kb_dir, "knowledge_index.json") index = { "categories": list(NUCLEAR_KNOWLEDGE_BASE.keys()), "total_entries": count_entries(NUCLEAR_KNOWLEDGE_BASE), "last_updated": __import__("datetime").datetime.now().isoformat(), "version": "0.1.0" } with open(index_file, "w", encoding="utf-8") as f: json.dump(index, f, indent=2) logger.info(f"Knowledge index saved to {index_file}") return index def count_entries(data: Dict[str, Any]) -> int: """Count total entries in knowledge base.""" count = 0 for key, value in data.items(): if isinstance(value, dict): count += 1 + count_entries(value) else: count += 1 return count def load_knowledge_base() -> Dict[str, Any]: """Load the knowledge base from file.""" kb_file = os.path.join( os.path.dirname(__file__), "..", "knowledge_base", "nuclear_knowledge_base.json" ) if os.path.exists(kb_file): with open(kb_file, "r", encoding="utf-8") as f: return json.load(f) else: logger.warning("Knowledge base file not found, initializing...") initialize_knowledge_base() return load_knowledge_base() if __name__ == "__main__": logger.info("Starting knowledge base initialization...") index = initialize_knowledge_base() logger.info(f"Knowledge base initialized with {index['total_entries']} entries")