921集集地震對台灣中部的醫院建築造成極為嚴重的震害，建築物結構體雖不致於倒塌傷及人命，院內諸多非結構物的損壞卻使得醫療空間的使用性不良，甚至已將緊急醫療救護工作移至院外實施，導致院內醫療資源無法被充分利用，可知非結構物的損壞是否決災區醫療體系原有醫療功能的主要因素之一。台灣目前的建築物耐震設計規範雖然將醫院歸屬為第一類建築物以提高其建築物結構體的設計地震力，卻沒能將非結構物也一併納入耐震設計考量，所以當遭遇規模較大的地震時，可能會再度發生因為非結構物的損壞致使醫院的緊急醫療救護中斷之窘境。有鑑於此，本研究即以問卷方式調查921集集地震之受災醫院內非結構物的損壞情形，並以非結構物之易損性曲線來檢視損壞程度與發生機率之關係。
921集集地震非結構物損壞問卷調查表係以FEMA356之非結構物分類系統為設計藍本；醫院篩選程序係於行政院衛生署提供之736家醫療院所中，選取震度階級5強以上的41家醫院為訪查對象。並利用中央氣象局提供之453個地震測站資料，從操作Surfer繪圖軟體繪製而成的三向度等震度圖中，應用Kriging內插法求得41家醫院的三向度PGA，分析時取數值最大者代表醫院的場址PGA，而非取其平均值。
彙整問卷調查表內各項非結構物的損壞情形後，將之分為輕度、中度、重度損壞以進行損壞比率分析，結果顯示醫院建築的室內設備物多數並無適當的耐震措施，耐震能力明顯不足。再以PGA為工程需求參數，應用對數常態分佈、MCEER存活率分析、非線性曲線迴歸之觀念來繪製問卷調查表內各項非結構物之易損性曲線，然後選擇四項非結構物進行數據驗證。數據驗證係將易損性曲線之PGAHCLPF乘以加速度樓高放大倍數之後與實驗數據PFA比對，比對結果顯示平均誤差比率約為14%左右，表示進行非結構物震害之災損評估時，應用存活率分析方法繪製而成的易損性曲線具有一定的可靠度。從易損性曲線的數據判讀中吾人可以得知非結構物在經歷某PGA時，某損壞程度的發生機率，所以可於地震前預判非結構物的災損情況，提早對非結構物實施耐震補強措施以減輕震害。

The Chi-Chi earthquake caused severe damage to hospital buildings in central Taiwan. Although the damage of hospital structure wasn’t severe, damaged nonstructural components made medical space unavailable. Emergency medical care was evacuated to the parking lots of hospitals to administer; therefore, medical resources inside hospitals weren’t used to the full capacity. Obviously, the damage of nonstructural components is one of the reasons for failing medical system function in disaster areas. In Taiwan, building code requires hospitals to be the first type building in order to raise and improve seismic-resistant capacity of building. But nonstructural components were never taken into account. So, the damage of nonstructural components resulting in interruption of emergency medical care would occur again when hospitals experience a larger seismic intensity scale. Considering the above, we investigated hospital buildings in the Chi-Chi earthquake with damaged nonstructural components by means of questionnaire, and examined the relationship between damage levels and probability expressed with fragility curves.
According to the nonstructural performance levels and damage table in FEMA356, we designed the Chi-Chi earthquake nonstructural damage questionnaire sheets. The steps is first to select 41 hospitals, whose derived site ground motion are larger than seismic intensity 5+, from 736 medical facilities provided by the Department of Health. Second, adopting the recorded data of 453 earthquake observation stations provided by the Central Weather Bureau, we drew three directional shake maps by using Surfer and then obtained three directional PGAs of each hospital by way of Kriging interpolation method. Finally, the maximum of three directional PGAs represents the hospital’s analytic site PGA.
After classifying damage states of each nonstructural component listed in questionnaire sheets into minor, moderate, and severe damage level, we carried out the analysis of component damage ratios. The result shows that the seismic capacity of in-house equipment in hospital buildings is apparently insufficient due to the lack of appropriate aseismatic measures. Taking PGA as engineering demand parameter and applying lognormal distribution, we used survival analysis, introduced by MCEER, and nonlinear least squares curve fitting method to derive fragility curves of each nonstructural component listed in questionnaire sheets. In order to verify the data of derived fragility curves, we chose 4 nonstructural components and compared PGAHCLPF multiplied by the floor response acceleration coefficient with PFA obtained from experimentation. The result indicates that the average percentage of error is 14%, so the fragility curves derived by applying survival analysis are reliable when proceeding the seismic damage assessment of nonstructural components. By understanding the damage level probability of a certain nonstructural component experiencing some PGA from fragility curves, we can predict the probability of damage states of each nonstructural component before earthquakes and then implement nonstructural aseismatic enforcement measures to alleviate seismic damage.

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