劣化鋼筋混凝土建築物生命週期維護管理決策支援系統

Decision-Making Supporting System of Life-Cycle Maintenance Strategies for Deteriorating Reinforced Concrete Buildings

10.3966/101632122014060088001

邱建國(Chien-Kuo Chiu)；林宜鋒(Yi-Feng Lin)

維護策略 ； 粒子群演算法 ； 多目標最佳化 ； 生命週期成本 ； 地震風險 ； Maintenance Strategy ； Particle Swarm Optimization ； Multi-Objectives Optimization ； Life-Cycle Cost ； Seismic Risk

建築學報

88期（2014 / 06 / 30）

1 - 18

繁體中文

藉由適當維護或補強使建築物之性能維持或長壽命化之一事，於「永續發展」或「永續工程」中是有其必要性，然而目前尚未有一量他系統供管理者能清楚了解各種維護策略之優劣，而僅能單憑管理者之經驗或外觀有明顯劣化警訊才進行維修或補強，難以實踐具預防性之維護管理策略及考量管理者需求設定維護計畫。因此，本文依前篇文章所介紹之考慮鹽害影響劣化鋼筋混凝土建築物生命週期地震風險評估方法，將分析所得之地震風險將納入建築物之生命週期成本為擬定維護策略之重要指標。此外，結合粒子群最佳t演算法，以經濟性、安全性、使用性、合理性及維護次數為目標擬定維護策略，管理者亦能依需求設定最佳化目標以決定適當之生命週期維護策略。本研究所建置之劣化RC建築物生命週期維護管理決策支援系統主要由四個模組所組成：（1）劣化評估模組：梁、柱構件之劣化分析；（2）耐震能力評估模組：劣化建築物之耐震能力評估；（3）護策略建立模組：確定建築物適用之維護策略；（4）多目標最佳化模組：使用多目標最佳t演算法擬定最佳之維護策略。

Appropriate repair or retrofit for maintaining the required performance or extending the specified service period for a building is essential in ＂Sustainable Development＂ or ＂Sustainable Construction＂. Therefore there is a need for a decision-making supporting system that can help engineers to comprehend the benefit of maintenance strategies. Based on past research, this study uses the ＂Truss and Arch＂ model theory to evaluate the shear capacity of chloride-induced corrosion RC columns in the assessment of the seismic performance of a deteriorating RC building. Moreover, using particle swarm optimization (PSO) of the multi-objectives (including economical, usability, safety, rationality and maintenance times), appropriate maintenance strategies are suggested. The proposed system consists of four main modules, as follows: 1. Deterioration evaluation; mechanical analysis of deteriorating RC beams and columns. 2. Seismic performance assessment; assessment of the seismic performance of a deteriorating RC building. 3. Setting of maintenance strategies; determining maintenance strategies of a deteriorating RC building 4. Multi-objectives optimization; appropriate maintenance strategies can be suggested using PSO. Finally, a case study is conducted to discuss the application of the proposed system.

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