LCO2 shipping network planning for onboard carbon capture and storage: A hub location and vessel scheduling optimization framework
オンボード炭素回収・貯蔵（OCCS）のためのLCO2輸送ネットワーク計画：ハブ立地と船舶スケジューリング最適化フレームワーク (AI 翻訳)
Lebing Wang, Chao Chen, Jian Gang Jin, Yuan Song, Shengtang Yu, Chenlu Wang, Yaoyao Wang
🤖 gxceed AI 要約
日本語
本研究は、オンボード炭素回収・貯蔵（OCCS）実証プロジェクトに基づき、LCO2輸送のネットワーク計画と船舶スケジューリングを最適化する2段階フレームワークを提案する。第1段階でネットワークフローモデルにより輸送コストを最小化し、第2段階で船隊規模を決定する。実際のケーススタディで大幅なコスト削減と運用効率向上を実証し、OCCSの大規模展開に貢献する。
English
This study proposes a two-stage optimization framework for LCO2 shipping network planning and vessel scheduling within an OCCS demonstration project. It uses a network flow model to minimize transport cost and a fleet deployment model to determine fleet size. A real case shows significant cost reductions and operational improvements, supporting large-scale OCCS deployment.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でも海事分野の脱炭素化が急務であり、CCUS技術の一環としてOCCSの導入が検討されている。本論文のLCO2輸送ネットワーク最適化手法は、日本の港湾インフラや船舶設計に示唆を与えるが、中国の事例に基づくため、日本への適用には調整が必要。
In the global GX context
OCCS is a key technology for maritime decarbonization under IMO targets. This framework addresses the logistical bottleneck of CO2 shipping, providing quantitative methods applicable to any country developing CCUS infrastructure. It offers actionable insights for policymakers and industry on transport network design.
👥 読者別の含意
🔬研究者:Provides a novel optimization method for CCUS logistics, combining network design and fleet deployment.
🏢実務担当者:Shipping companies and port operators can use the framework to plan LCO2 transport networks and vessel requirements.
🏛政策担当者:Informs infrastructure investment decisions for CO2 transport, supporting large-scale CCUS deployment.
📄 Abstract（原文）
To meet global decarbonization targets, onboard carbon capture and storage (OCCS) has emerged as a viable strategy for maritime emission reduction. However, the shipping of captured liquid CO 2 (LCO 2 ) remains a critical bottleneck due to a lack of systematic coordination, which leads to systemic inefficiencies such as redundant routing, idle capacity, and cost inefficiency. This study, undertaken within an OCCS demonstration project, proposes a two-stage optimization framework to enhance the efficiency and economy of LCO 2 shipping. In the first stage, a network flow model optimizes shipping network configuration and volume allocation to minimize transport cost. In the second stage, a voyage generation algorithm and a fleet deployment model determine the minimum fleet size required to fulfill transport demand, providing a quantitative basis for new-build LCO 2 transport vessel design. A real-world case study demonstrates substantial cost reductions and enhanced operational performance. The findings support the large-scale deployment of OCCS by offering actionable insights for LCO 2 shipping system planning.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.multra.2026.100320first seen 2026-05-17 06:40:20 · last seen 2026-05-20 05:13:55
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。