Prioritization of Factors Affecting Sustainability Property Improvement by Using Analytical Hierarchy Process and Important-Satisfaction Model: The Case of TAIPEI 101 Tower

Almost without exceptions office buildings in the world investigate the approaches of optimizing the building operation and property facilities in order to maintain the best conditions of the building from the first day of opening. For sustainable buildings, how to make continuous profit must rely on the maintenance and improvement of facilities to satisfy users. However, building managers often have trouble prioritizing improvement projects toward their sustainable objectives due to the large number of facilities that have different durability years and the importance and satisfaction of these facilities to users are also different. In the past, financial consideration was usually the only one that matters when improvement of facilities was brought up. Users feedback of satisfaction was not taken into consideration, resulting in huge expenditures did not bring in high user satisfaction. This research, by scientific analysis of the data from user feedback, applies the Analytic Hierarchy Process (AHP) using TAIPEI 101 Tower as a case study to explore the key factors affecting tenants’ willingness to lease office buildings by distributing questionnaires to real estate experts. By filtering out key indicators related to property facilities that users care about, this study used Importance and Satisfaction Analysis (IS Analysis) to identify items that need urgent improvement. This innovative analysis methodology can systematically and logically find out the priority of improvement projects, assisting building managers effectively invest limited resources in projects with substantial benefit, which is helpful for sustainable property management.

Time-Aware and Temperature-Aware Fire Evacuation Path Algorithm in IoT-Enabled Multi-Story Multi-Exit Buildings

Temperature sensors with a communication capability can help monitor and report temperature values to a control station, which enables dynamic and real-time evacuation paths in fire emergencies. As compared to traditional approaches that identify a one-shot fire evacuation path, in this paper, we develop an intelligent algorithm that can identify time-aware and temperature-aware fire evacuation paths by considering temperature changes at different time slots in multi-story and multi-exit buildings. We first propose a method that can map three-dimensional multi-story multi-exit buildings into a two-dimensional graph. Then, a mathematical optimization model is proposed to capture this time-aware and temperature-aware evacuation path problem in multi-story multi-exit buildings. Six fire evacuation algorithms (BFS, SP, DBFS, TABFS, TASP and TADBFS) are proposed to identify the efficient evacuation path. The first three algorithms that do not address human temperature limit constraints can be used by rescue robots or firemen with fire-proof suits. The last three algorithms that address human temperature limit constraints can be used by evacuees in terms of total time slots and total temperature on the evacuation path. In the computational experiments, the open space building and the Taipei 101 Shopping Mall are all tested to verify the solution quality of these six algorithms. From the computational results, TABFS, TASP and TADBF identify almost the same evacuation path in open space building and the Taipei 101 Shopping Mall. BFS, SP DBFS can locate marginally better results in terms of evacuation time and total temperature on the evacuation path. When considering evacuating a group of evacuees, the computational time of the evacuation algorithm is very important in a time-limited evacuation process. Considering the extreme case of seven fires in eight emergency exits in the Taipei 101 Shopping Mall, the golden window for evacuation is 15 time slots. Only TABFS and TADBFS are applicable to evacuate 1200 people in the Taipei 101 Shopping Mall when one time slot is setting as one minute. The computational results show that the capacity limit for the Taipei 101 Shopping Mall is 800 people in the extreme case of seven fires. In this case, when the number of people in the building is less than 700, TADBFS should be adopted. When the number of people in the building is greater than 700, TABFS can evacuate more people than TADBFS. Besides identifying an efficient evacuation path, another significant contribution of this paper is to identify the best sensor density deployment at large buildings like the Taipei 101 Shopping Mall in considering the fire evacuation.

PESONA MENARA KEMBAR PETRONAS DI MALAYSIA

Malaysia is a small country that is advanced in every field. In addition to the economy, the tourism sector is growing by leaps and bounds. One supporter of economic development and tourism in Malaysia are Petronas twin towers which is the tallest building in the world before in the past by building taipei 101. However this Petronas twin towers are still the tallest twin skyscrapers in the world. Under this Petronas twin towers are KLCC (Kuala Lumpur City Centre) which houses exhibitions and shopping, so tourists who visit here can be shopped for souvenirs at KLCC.

Ground Motion Distribution Analysis about Taipei-101 in Earthquake

It is important for tall building to infer seismic hazard analysis. Recently, researchers paid great efforts to study the seismic hazard analysis using the method of probabilistic seismic hazard analysis (PSHA), and PSHA has been proved to be sound and popular. The PSHA method is not new. However, the use of PSHA in China is not extensive. The purpose of this paper is to explore the use of ground motion distribution analysis about one typical tall building Taipei-101. Based on the earthquake catalog around Taiwan with more than 50,000 events over 100-years of recording, the author takes Taipei-101’s geographic coordination as object to do ground motion distribution analysis. The research shows that ground motion is affected significantly by service year, and the chi-square test applied in testing Annual ground motion distribution better than K-S test, In addition, Bernoulli distribution is verified reasonable in evaluating the entire service year ground motion distribution.