Heating temperature prediction of concrete structure damaged by fire using a Bayesian approach

A fire that occurs in a reinforced concrete (RC) structure accompanies a heating temperature, and this negatively affects the concrete material properties, such as the compressive strength, the bond between cement paste and aggregate, and the cracking and spalling of concrete. To appropriately measure the reduced structural performance and durability of fire-damaged RC structures, it is important to accurately estimate the heating temperature of the structure. However, studies in the literature on RC structures damaged by fire have focused mostly on structural member tests at elevated temperatures to ensure the fire resistance or fire protection material development; studies on estimating the heating temperature are very limited except for the very few existing models. Therefore, in this study, a heating temperature estimation model for a reinforced concrete (RC) structure damaged by fire was developed using a statistical Bayesian parameter estimation approach. For the model development, a total of 77 concrete test specimens were utilized; based on them, a statistically highly accurate model has been developed. The usage of the proposed method in the framework of the 500 ◦C isotherm method in Eurocode 2 has been illustrated through an RC column resistance estimation application

Evaluation on Egress Safety of Nursing Hospital Considering the Smoke Exhaust System

This study aimed to evaluate the egress safety in nursing hospitals based on the capacity of the smoke exhaust system. To this end, the available safe egress time was calculated by analyzing changes in visibility, carbon monoxide, carbon dioxide, oxygen contents, and temperature depending on the fire duration. In addition, an egress simulation was performed using the number of workers (egress guides) and egress delay time as variables, and the required safe egress time was estimated. Based on the results, the egress safety of a prototype nursing hospital was evaluated. In this study, egress safety criteria to evaluate egress safety in a typical nursing hospital were presented, which are expressed in terms of normalized egress guides, the capacity ratio of the smoke exhaust system, and egress delay time. The proposed criteria can be used to evaluate the egress safety of typical nursing hospitals and to prepare complementary measures

Experimental and Numerical Studies on the Structural Performance of a Double Composite Wall

In this study, experiments and numerical analyses were carried out to examine the flexural and shear performance of a double composite wall (DCW) manufactured using a precast concrete (PC) method. One flexural specimen and three shear specimens were fabricated, and the effect of the bolts used for the assembly of the PC panels on the shear strength of the DCW was investigated. The failure mode, flexural and shear behavior, and composite behavior of the PC panel and cast-in-place (CIP) concrete were analyzed in detail, and the behavioral characteristics of the DCW were clearly identified by comparing the results of tests with those obtained from a non-linear flexural analysis and finite element analysis. Based on the test and analysis results, this study proposed a practical equation for reasonably estimating the shear strength of a DCW section composed of PC, CIP concrete, and bolts utilizing the current code equations

Real-Time Egress Model for Multiplex Buildings under Fire Based on Artificial Neural Network

When fire occurs in a large multiplex building, the direction of smoke and flames is often similar to that of the evacuation of building occupants. This causes evacuation bottlenecks in a specific compartment, especially when the occupant density is very high, which unfortunately often leads to many fatalities and injuries. Thus, the development of an egress model that can ensure the safe evacuation of occupants is required to minimize the number of casualties. In this study, the correlations between fire temperature with visibility and toxic gas concentration were investigated through a fire simulation on a multiplex building, from which databases for training of artificial neural networks (ANN) were created. Based on this, an ANN model that can predict the available safe egress time was developed, and it estimated the available safe egress time (ASET) very accurately. In addition, an egress model that can guide rapid and safe evacuation routes for occupants was proposed, and the rationality of the proposed model was verified in detail through an application example. The proposed model provided the optimal evacuation route with the longest margin of safety in consideration of both ASET and the movement time of occupants under fire

Experimental and Numerical Investigations on Fire-Resistance Performance of Precast Concrete Hollow-Core Slabs

In this study, full-scale fire tests and finite element (FE) analyses are conducted to investigate the fire resistance performance of hollow-core slabs (HCSs) manufactured using the extrusion method. The deflection of the HCS specimens and the temperature distribution in the section according to the fire exposure time are measured and analyzed comprehensively, and the test results are compared with the FE analysis results. In addition, parametric analyses are conducted on 21 cases with the HCS depth, span length, hollow ratio in a section, cover thickness of concrete, and load ratio (i.e., the ratio of the external load to the ultimate load) as variables, based on which the fire resistance performance of the HCS according to each variable is investigated. The analysis results show that the load ratio is a key factor governing the fire resistance behavior of HCSs, whereas the effects of the cover thickness of concrete and the hollow ratio in a section are relatively slight within the range of variables examined in this study

Experimental Study on Shear Capacity of Reinforced Concrete Beams with Corroded Longitudinal Reinforcement

In this study, shear tests were conducted to investigate the effects of longitudinal reinforcement corrosion on the shear capacity of reinforced concrete (RC) members with transverse reinforcement. To this end, a total of eight test specimens were fabricated, and the corrosion rates and anchorage details of rebars were set as test variables. In addition, an accelerated corrosion technique was used to introduce corrosion into the longitudinal reinforcement without corroding shear reinforcement. The test results indicated that the capacities of the specimens in which tension reinforcement was not properly anchored at the ends of the members decreased rapidly at high corrosion rates, whereas the capacities of the specimens in which tension reinforcement was properly anchored by hooks were similar to or higher than those of the non-corroded specimens, despite bond loss caused by corrosion

Robot System of DRC-HUBO plus and Control Strategy of Team KAIST in DARPA Robotics Challenge Finals

This paper summarizes how Team KAIST prepared for the DARPA Robotics Challenge (DRC) Finals, especially in terms of the robot system and control strategy. To imitate the Fukushima nuclear disaster situation, the DRC performed eight tasks and degraded communication conditions. This competition demanded various robotic technologies, such as manipulation, mobility, telemetry, autonomy, and localization. Their systematic integration and the overall system robustness were also important issues in completing the challenge. In this sense, this paper presents a hardware and software system for the DRC-HUBO+, a humanoid robot that was used for the DRC; it also presents control methods, such as inverse kinematics, compliance control, a walking algorithm, and a vision algorithm, all of which were implemented to accomplish the tasks. The strategies and operations for each task are briefly explained with vision algorithms. This paper summarizes what we learned from the DRC before the conclusion. In the competition, 25 international teams participated with their various robot platforms. We competed in this challenge using the DRC-HUBO+ and won first place in the competition. (C) 2016 Wiley Periodicals, Inc