Traditional design methods for engineering applications aim to achieve optimal performance for specific conditions or moderate performance for a broader range of conditions. However, the optimal performance for a wide spectrum of situations can be facilitated if such systems possess reconfiguration capability. It can be illustrated in the example of structures with steerable joints, which is a popular approach in robotics. By rotating the joints to a different degree, a plethora of resulting configurations can be achieved – configurations that might be specifically suited for the required conditions. Systems based on these principles can be implemented on the macroscopic level in adaptive facades, on the mesoscopic level in mechanical metamechanisms, and at the microscopic level in microelectromechanical devices. In general, adaptive structures often require numerous actuators to facilitate a wide range of reachable configurations, leading to increasing energy demands as the system size increases. This can be seen in the case of robotics when each joint can be independently actively rotated to drive the motion corresponding to the specific degree of freedom. This paper analyzes an alternative situation, when the joins are semi-active and can exist only in either a locked or unlocked state, with only one (last joint) being actively steered. In the ideal case, the energy should be consumed only for switching between states, while maintaining the state should be free with locking achieved via switchable friction. While theoretically improving energy efficiency, such a system makes it much more challenging to control the resulting shape of the structure as compared with its counterpart with actively rotating joints. In this paper, we develop a motion planning algorithm to facilitate the achievement of the desired shape via control over the state of the joints and the position of the last link. In particular, the change of shape is performed by a sequence of single-degree- of-freedom motions determined by a motion planning algorithm based on Rapidly exploring Random Trees and sub-slider-crank systems (RRT-SC). One application of the proposed method is evaluated for reconfigurable building facades and paves the way for the next generation of structures in smart cities.
Effective Damage Identification (DI) plays a critical role in protecting structures against local or global failures caused by hazards. Real-time DI provides instant damage data and increases the safety and serviceability of civil structures. Real-time DI helps to understand the structure's behavior during extreme events that may be unknown at the design stage. This field needs innovative solutions for training supervised machine learning classifiers in the absence of measured damaged data. This research proposes an unconventional deep learning algorithm for vibration-based DI. The proposed real-time data-driven DI methodology does not require any manual feature extraction and uses Artificial Neural Networks (ANNs) to identify the presence and location of damage in discrete structural systems. The input is the response signals measured through sensors (no model-based input information required). A dropout technique regularizes the network and avoids co-adaptation in hidden layers. The neural network is optimized through 10-fold cross-validation. The proposed method's effectiveness in identifying the presence and location of damages is studied using a 4-story 2D structure subjected to artificial accelerograms. The recorded response signals create the feature space in the dataset. The lateral stiffness of columns is reduced randomly by different percentages resembling different damage severities. Considering the validation dataset results, the accuracy of the damage detection task varies from 84 to 99% for different damage severities, and accuracy for the localization task ranges from 78-98%. The results show the promising performance of ANNs for real-time DI and pave the way for training the classifiers using real-life data from undamaged structures and simulate data from damage scenarios.
Natural hazards are among the largest construction challenges today. By taking dynamic building envelopes designed using origami and kirigami principles, a more comprehensive structure can be built to sustain impacts by high winds. By combining a wind tunnel for small-scale simulation of hurricane conditions and computational analysis for full-scale buildings, a comparison can be made to find differences between experimental data collected and the results from computational fluid dynamics simulations. Results show that by increasing the number of facets at an angle to wind flow and decreasing the size of the facets, the size of the body direct to wind flow can be minimized and wind resistance can be decreased.
While dealing with structures equipped with operating mechanical devices, keeping the machinery-induced vibrations below the acceptable limits is of enormous importance. The fundamental step to controlling undesirable vibrations in such structures is to localize the vibration source. The accuracy of locating the source of vibration using different methods, e.g., Time Difference of Arrival (TDOA) or Steered Response Power (SRP) method, depends on accurate estimation of the propagation speed. The propagation speed is a function of vibration frequency. The objective of this study is to investigate a nonlinear regression model to obtain the relationship between Wave Propagation Speed (WPS) and the vibration frequency on a concrete floor. The development of this relationship is based on a series of experiments on a concrete floor in a building using a shaker as a vibration exciter, and four accelerometers to record vertical vibration. First, the shaker generates sinusoid forces with a specific frequency and the accelerometers, configured collinearly, record acceleration measurements. Then, the WPS is estimated using cross-correlation to measure the time difference of arrival between pairs of accelerometers. This process is repeated for a range of frequencies resulting in a dataset that includes the vibration frequency as independent and the WPS as dependent variables. The relationship between speed and frequency is then optimally estimated using a nonlinear regression model.
Natural disasters, such as hurricanes, cyclones, and other high-speed windstorm events, pose a threat to the built environment. The damage of the nonstructural components due to high winds, flooding, hurricane surge and rainwater intrusion surrounding a building structure such as the fa¸cade accounts for the majority of the financial loss. The increased interest in the sustainable design of buildings gives forward to the development of creative low energy alternatives for the adaptive fa¸cade. This paper studies five fa¸cade configurations subjected to wind loading. An adaptive diagrid fa¸cade (ADF) is modeled using a panel system of four equilateral triangles: one panel is actuated at the nodes using linear actuators and controls the other three panels in the system. The proposed ADF can be adapted to fit various building heights and shapes and can be chosen due to their structural efficiency that results in material savings and flexibility in designing of complex buildings. This paper makes advances towards an adaptive origami-inspired diagrid fa¸cade has the potential to redistribute wind loads in real-time. With sustainable design becoming an important factor in design, low energy options for the adaptive fa¸cades were considered. This research performs computational fluid dynamic analysis of five threedimensional building structures: a conventional regular building structure, a diagrid building structure without corner columns, and three origami-inspired fa¸cade configurations on diagrid building structures. The purpose of this study is to understand effects of the different building envelope geometries on the fluid dynamics and explore the potential use in optimal shape configuration for real-time morphing adaptation of high-rise buildings subjected to extreme wind loading.
Cities are built and designed to encompass many considerations and needs. When compared to multi-celled organisms, single structures imitate individual cells while communities and cities embody the organisms. For the organism to survive and thrive, all of its individual cells need to operate together. Appropriately, the next step in civic smart design is to apply smart organization to benefit a community’s collective ability to survive storms rather than simply its pieces. This paper presents a design method for the protection of communities from severe windstorm events. The design method is inspired by the biomimicry of the school of fish. The method of smart organization for fluid survivability is inspired by aquatic life and school of fish. Some of the identified adaptations to marine life include the layout of a community in terms of spacing between building structures, the shape of the overall community and roof systems that can be designed mimicking the school of the fish cross-section. This paper presents seven adaptations that have been identified from fluid-structure envelope design (nano-level) to single building structure geometry (micro-level) to community layout design (macro-level).
Inspired by evolutionary game theory, the biological game of replicator dynamics is investigated for vibration control of bridge structures subjected to earthquake excitations. Replicator dynamics can be interpreted economically as a model of imitation of successful individuals. This paper uses replicator dynamics to reduce vibrations while optimally allocating the control device forces. The control algorithm proposed is integrated with a patented neural dynamic optimization algorithm to find optimal growth rate values with the goal of achieving satisfactory structural performance with minimum energy consumption. A model is described for hybrid vibration control of smart highway bridge structures subjected to earthquake loading.
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