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This paper introduces a novel methodology for the optimum design of linear tuned mass dampers (TMDs) to improve the seismic safety of structures through a novel Whale Optimization Algorithm (WOA). The algorithm is aimed to reduce the maximum horizontal peak displacement of the structure, and the root mean square (RMS) response of displacements as well. Furthermore, four additional objective functions, derived from multiple weighted linear combinations of the two previously mentioned parameters, are also studied in order to obtain the most efficient TMD design configuration. The differential evolution method (DEM), whose effectiveness has been previously demonstrated for TMD applications, and an exhaustive search (ES) process, with precision to two decimal positions, are used to compare and validate the results computed through WOA. Then, the proposed methodology is applied to a 32-story case-study derived from an actual building, and multiple ground acceleration time histories are considered to assess its seismic performance in the linear-elastic range. The numerical results show that the proposed methodology based on WOA is effective in finding the optimal TMD design configuration under earthquake loads. Finally, practical design recommendations are provided for TMDs, and the robustness of the optimization is demonstrated.

Infrastructure development is a common feature of emerging countries. As a result, the design and construction of complex structures susceptible to damage is becoming increasingly common. Over the years, multiple advances in Structural Health Monitoring (SHM) haven allowed researchers and engineers to detect, locate, and quantify structural damage in critical components of civil engineering structures. Frequency-based methods have demonstrated their reliability in multiple numerical and experimental applications. This study presents a brief chronological literature review of methodologies based on frequency analysis that have been used in the detection ofstructural damage over the last forty years. It is worth noting that the paper focuses on computer-aided techniques such as artificial neuronal networks (ANN), genetic algorithms (GAs), and metaheuristics that have been employed to solve the inverse damage detection problem.

Introduction:There are an estimated 15,600 nursing homes with a total of 1.4 million residents in the United States. The number of residents will continue to increase due to the aging population, and the associated morbidities will make it difficult to evacuate them safely.Aim:This study is the first of its kind to provide an analysis of the number of nursing home deaths caused by external and internal events following evacuations.Methods:Information from the databases Lexis Nexis and PubMed were compiled and limited to news articles from 1995-2017. The gathered information included the reason for evacuation, injuries, deaths, and locations within the United States.Results:From 1995 to 2017, there was a total of 51 evacuations and 141 deaths in nursing homes. 27 (53%) evacuations were due to external events which resulted in a combined 121 (86%) deaths, and 24 (47%) evacuations were due to internal events which resulted in a combined 20 (14%) deaths. Hurricanes were responsible for the majority of deaths during evacuations, followed by fires and floods. The number of evacuations and deaths increased the greatest between 2005 to 2008.Discussion:External events have the greatest impact on loss of life. Internal disasters are about equal in the number of incidents, however, external events have a much greater mortality rate. Exact numbers on injuries, morbidity, and mortality are difficult to ascertain, but it appears to be related to natural disasters. In view of the increasing likelihood of natural disasters related to global warming, a drastic improvement of standard evacuation procedures of long-term nursing homes is critical to decreasing mortality of nursing home residents. There also needs to be a nationally standardized method of reporting evacuations in order to better analyze data on nursing homes.

Controlling wind-induced vibrations as well as aerodynamic forces is an essential part of the structural design of tall buildings in order to guarantee the serviceability limit state of the structure. This paper presents a numerical investigation focused on finding the optimal design parameters of a Tuned Inerter Damper (TID) based system for the control of wind-induced vibration in tall buildings. The control system is based on the conventional TID, with the main difference that its location is changed from the ground level to the last two story-levels of the structural system. The TID tuning procedure is based on an evolutionary cultural algorithm in which the optimum design variables defined as the frequency and damping ratios are searched according to the optimization criteria of minimizing the root mean square (RMS) response of displacements at the nth story of the structure. A Monte Carlo simulation is used to represent the dynamic action of the wind in the time domain in which a time-series derived from the Davenport spectrum using eleven harmonic functions with randomly chosen phase angles was reproduced. The above-mentioned methodology is then applied on a case-study derived from a 37-story prestressed concrete building with 144 m height, in which the wind action overcomes the seismic action. The results showed that the optimally TID is effective to reduce the RMS response of displacements up to 37.12% which demonstrates the feasibility of the system for the control of wind-induced vibrations in tall buildings.