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Modern high-rise buildings may be configured into spaces of widely varying specifications. This situation creates a diverse building environment with multiple variables that make fire hazards difficult to predict and monitor accurately. Therefore, developing and implementing an integrated fire disaster prevention system is necessary in order to effectively prevent fire disasters and adequately protect life and property. In Taiwan, the response to an organization of fire prevention and disaster relief as well as evacuation planning and rescue guidance continue to rely primarily on human-provided intelligence. This method makes disaster-response decision-making inherently prone to error due to the inaccuracy, incompleteness, and poor communication of this intelligence. However, Building Information Modeling (BIM) and wireless sensor networks have been widely discussed in many aspects of building disaster-prevention management as approaches to increasing the accuracy and effectiveness of disaster-response decision-making. The present study uses BIM to construct a BIM-based Intelligent Fire Prevention and Disaster Relief System. This system integrates information on personal localization, on evacuation/rescue route optimization with Bluetooth-based technology, and on a mobile guidance device to create an intelligent and two-way fire disaster prevention system framework that displays the real-time and dynamic fire information in three dimensions (3D). The results of applying the BIM-based system demonstrate that it may effectively provide 3D visualization to support the assessment and planning of fire safety, to provide early detection and alarm responses, to direct efficient evacuation, and to facilitate fire rescue and control efforts in order to increase overall building safety and disaster-response capabilities.

The maintenance planning of deteriorating bridges is to find a balance between obtained performance and incurred cost. Because the planning horizon spans tens of years, a certain amount of uncertai...

Automated monitoring systems are important in civil engineering industry. Existing utilities and infrastructures are monitored when their safety is of concern. These monitoring data also provide key indicators for their health and information for the life cycle management. With the prevalence of wireless sensor network (WSN) technology and the availability of various wireless communication technologies, large-scale automated monitoring systems can be deployed easily, and the cost of such systems are dropping owing to the use of Micro-Electro-Mechanical System (MEMS) technology. In this work, potential technologies for next-generation automated monitoring systems are first visited. A scalable IT (Information Technology) infrastructure for supporting large-scale automated monitoring systems capable of handling multiple projects is then proposed. Scalability, reliability, and extensibility are main considerations when designing the system and when choosing the technology for the system. Some scenarios are presented to demonstrate the characteristics and capabilities of the proposed infrastructure and information systems.

Localization (position tracking) inside tunnels is difficult. GPS signal is not available inside tunnels, and installation of wireless access points is expensive. In this work, we propose the use machine vision for localization in tunnels. The advantage for such approach is that it requires no installation of any infrastructure, needed with radio triangulation approach. Prior researches have shown that machine vision can successfully identify positions in both outdoor and indoor environments. However, such application has never been tried inside tunnels. In this paper, we present our work on developing appropriate algorithms for localization in tunnels. One potential application for localization in tunnels is to help tunnel maintainers acquire accurate location information in tunnels when they do tunnel

Parameter or system identification is a useful tool in civil engineering. They have wide applications across many disciplines. However, due to the lack of generalpurpose tools for such analyses, researchers need to develop their own codes with duplicated efforts. Yet, it is sometime difficult to adopt other people’s code due to different modeling methods used. Thus, there is a need for general-purpose tools to resolve problems of this kind. This paper describes a general-purpose system for such purpose. The system has three features. First, it uses cloud-computing technology to provide large-scale capabilities. Second, the system uses a JavaScript engine for developing extensions. Third, it employs multi-objective particle swarm optimization for its applicability on wide range of problems. These features allow the system provide general capabilities to solve problems with similar needs. The design is validated and demonstrated by identifying constitutive model parameters in geotechnical engineering.

Typical engineering design processes involve an initial design, followed by iterations of analyses, interpreting and evaluating analyses results, and proposing new design or modifying existing design. The final design often results from intuitions obtained during this iterative process. Most computer-aided engineering (CAE) software focuses on the computer-aided analysis by advancing capabilities in pre-processing, computation, and post-processing. However, little attention has been paid to the support of the aforementioned iterative design process, which is the common practice in engineering design. Authors believe the next-generation CAE software should evolve into CAID (ComputerAided Iterative Design) software to help engineers go through the iterative design process and develop better engineering designs. In this paper, key software requirements for the iterative design process are discussed in this work. Furthermore, prototype CAID software developed using C, Qt, and VTK is demonstrated. The analyzing capability of the developed CAID software is based on an essential software framework for meshfree methods (ESFM). The proposed CAID concept and prototype software shall provide guidelines for future CAE software development.

Computational efficiency is of critical importance in the application of large-scale finite element simulations for solving complex geotechnical problems. This paper summarizes the formulation and implementation of a FETI domain decomposition technique for parallel finite element computations, highlighting the parallel efficiency and scalability of the software using a cluster of 16 interconnected commodity computers. The program is then used to simulate ground movements caused by the construction of a shallow cavern for a new subway station using a stacked-drift tunneling method which involved hand-excavation of a sequence of 15, 3m-square-section drifts through weathered alluvial soils. Figure 1 shows the cross-section of the cavern for the recently completed Rio Piedras station, part of the new Tren Urbano system in San Juan, Puerto Rico. The horseshoe-shaped cavern (17m wide, 16m high, and 150m long) was constructed in weathered alluvial soils. The crown of the cavern was located less than 5.5m below existing build- ings in a busy historic shopping district. Structural support for the cavern was provided by a series of 15 stacked drifts. These rectangular-section galleries (each typically 3m square) were excavated mainly by hand between two 30m deep access shafts and were then in-filled with concrete, while a primary compensation grouting system was designed to mitigate effects of excavation-induced ground movements on the overlying structures. Unexpectedly large settlements occurred during the early stages of drift construction and overwhelmed the original grouting sys- tem. As a result, an extensive consolidation grouting system was installed (to enable grouting closer to the tunnel heading). Despite these remedial measures, building settlements above the cavern at the end of construction ranged from 70mm to 130mm. In principle, non-linear finite element methods can be used to evaluate/predict the ground deformations caused by the stacked-drift construction. However, the complexity of the project presents a major challenge both in details of the modeling and in the scale of the computation. A comprehensive numerical model of the cavern would require detailed modeling of the unusual engineering properties and spatial variability of the weathered alluvium (Zhang et al. 2003), simulation of grout injections (and their effects on the surrounding soil), as well as the primary details of the drift excavation, lining and concrete infilling for each of the 15 drifts. The actual construction proce- dure involved concurrent excavation of between two and four drifts, Figure 1b (sometimes advancing in opposite directions), while concrete infilling took place from 3 to 60 days after excavation. Preliminary calculations found that very large 3-D finite element models (O(10 5 ) degrees of freedom) would be necessary to represent even these basic details of the stacked-drift construction. When non-linear soil behavior (with marginal face stability) was in- cluded in the finite element analyses, it soon became apparent that solutions using conventional direct equilibrium equation solvers or iterative (Krylov sub-space etc.) methods with single-processor machines would exceed practical limits on computational time and hence, a more efficient approach was required.

Publisher Summary There are many examples of transportation projects involving underground construction of shallow tunnels in soft ground conditions within congested urban environments. One of the key design criteria for such projects is to assess the impacts of the proposed tunnel construction methods (either by tunnel boring machines or by open-face excavation methods) on existing facilities and to control the construction procedures to limit deformations within the surrounding soil. Realistic modeling of these problems represents a very challenging problem that must typically simulate the following five conditions: (1) the complex sequence of excavation and support conditions at the advancing tunnel heading ; (2) the interaction between soil and the structural lining system; (3) the nonlinear behavior of the soil; (4) the coupled effects of groundwater seepage and deformations; and (5) ancillary activities ranging from grouting (either around the lining or within the soil mass) to soil nailing (reinforcement ahead of excavated face). Although many of these processes clearly require modeling in three dimensions, the great majority of analyses reported to date represent tunnel constructions using simplified plane strain models (using artificial concepts such as equivalent ground loss to represent 3D effects around the tunnel heading).