Theoretical Issues and Conceptual Framework for Physical Facilities Design in Hospital Buildings

This study reviewed the theoretical issues relating to morphological and psychological design issues in hospital building design evaluation.The study of morphological configurations design issues,concentrates on the elements of building,shape/form,the structure of the environment,the structural efficiency and the architectural appearance of the hospital building forms.The psychological design issues focused on the essential issues relating to Proximity,Privacy and Wayfindings.Through the literature review of previous models such as,Khan(2012)Operational Efficiency Model,Haron,Hamid and Talib Usability Framework,(2012),Zhao,Mourshed&Wright(2009)Model,Alalouch,Aspinall&Smith Model(2016)and Hill&Kitchen(2009).A conceptual framework for physical facilities design evaluation and satisfaction in hospital buildings was developed.The study,however,provides useful information for the development of a design framework that can inform policy on hospital buildings.

Reduced order observer based identification of base isolated buildings

The objective of this study is to identify system parameters from the recorded response of base isolated buildings,such as USC hospital building,during the 1994 Northridge earthquake.Full state measurements are not available for identification.Additionally,the response is nonlinear due to the yielding of the lead-rubber bearings.Two new approaches are presented in this paper to solve the aforementioned problems.First,a reduced order observer is used to estimate the unmeasured states.Second,a least squares technique with time segments is developed to identify the piece-wise linear system properties.The observer is used to estimate the initial conditions needed for the time segmented identification.A series of equivalent linear system parameters are identified in different time segments.It is shown that the change in system parameters,such as frequencies and damping ratios,due to nonlinear behavior of the lead-rubber bearings,are reliably estimated using the presented technique.It is shown that the response was reduced due to yielding of the lead-rubber bearings and period lengthening.

A Power Load Prediction by LSTM Model Based on the Double Attention Mechanism for Hospital Building

This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power load into each department of the hospital.Firstly,the key influencing factors of the power loads were screened based on the grey relational degree analysis.Secondly,in view of the characteristics of the power loads affected by various factors and time series changes,the feature attention mechanism and sequential attention mechanism were introduced on the basis of LSTM network.The former was used to analyze the relationship between the historical information and input variables autonomously to extract important features,and the latter was used to select the historical information at critical moments of LSTM network to improve the stability of long-term prediction effects.In the end,the experimental results from the power loads of Shanxi Eye Hospital show that the LSTM model based on the double attention mechanism has the higher forecasting accuracy and stability than the conventional LSTM,CNN-LSTM and attention-LSTM models.

Energy consumption and carbon emissions of hospitals in Tianjin

An energy audit of 22 tertiary hospitals was conducted in Tianjin. The detailed content included design data, basic information, energy bills and equipment lists. It was shown that during the study, the energy intensity of hospitals in Tianjin was approximately stable and the average level of energy consumption was 348kW.h/（m2.a）. From the date collected, it was calculated that the energy intensity of general hospitals was 380 kW.h/（m2.a）, and the average carbon emissions was 157kgCO2/（m2.a）; While the energy intensity of specialized hospitals was 309kW＇h/（m2.a）, and the average carbon emissions was 131 kgCO2/（m2. a）. By breaking the energy consumption down into several items, it was found that the heating system consumed the highest amount of energy （42.12%）, followed by the cooling system （6.78%）, the medical equipment （4.98%） and the lighting system （3.63%）. The main factors that affect the hospital energy consumption were determined, and some feasible technology and management measures to save energy and reduce carbon emissions were proposed.