This paper documents the testing of six 20 ft × 4 ft × 8 in. (6.1 m × 1.2 m × 203.2 mm) precast, prestressed concrete sandwich panels constructed with continuous rigid insulation and a carbon-fiber-reinforced polymer grid shear transfer mechanism. All panels were identical except for foam type and were cast together on the same prestressing bed. Three of the six panels were fabricated with expanded polystyrene (EPS) foam insulation, and the remaining three panels were fabricated using sandblasted extruded polystyrene (XPS) foam. For each group of three panels, one was tested to failure as a control and two others were cycled 2 million times to 45% of their design ultimate load before failure testing. The tested EPS panels all failed when the applied lateral load was greater than or equal to 100 lb/ft² (4.79 kPa), which is 2.35 times their design load of 42.5 lb/ft² (2.03 kPa). The tested XPS panels all failed at the equivalent of 175 lb/ft² (8.38 kPa) of applied lateral pressure, which is more than 4.0 times their design load of 42.5 lb/ft². All four panels subjected to fatigue survived 2 million lateral load cycles without any visible signs of degradation.

The design procedure presented in the seventh edition of the PCI Design Handbook: Precast and Prestressed Concrete for ledges of L-shaped beams has been called into question by many engineers and researchers. Research findings from previous experimental studies have indicated that the PCI ledge design equations can overestimate ledge punching shear strength. This paper presents the development of the design procedure for the eighth edition of the PCI Design Handbook to evaluate the punching shear strength of ledges of L-shaped beams. Based on the failure surfaces observed throughout a comprehensive experimental program, an idealized failure surface was determined. The results of extensive finite element analyses and a large experimental program were used to evaluate the effects of global stress on ledge capacity, and a procedure to evaluate the punching shear strength of the ledge was developed. The proposed procedure is presented in this paper and is intended to provide an improved margin of safety for ledge capacity under a wide range of loading conditions. Consideration was given to ensure simplicity and practicality of the proposed design procedure.

The ledge design procedure in the seventh edition of the PCI Design Handbook: Precast and Prestressed Concrete has been called into question by several engineers and researchers since 1985. Specifically, the ledge punching-shear capacities predicted by the PCI procedure overestimate the failure loads observed in several previous laboratory tests and analytical studies. This paper presents the results of the second phase of an extensive experimental program conducted on nine fullscale, long-span, L-shaped beams with ledge heights from 8 to 18 in. (200 to 450 mm). The main objectives of this study were to investigate the effects on ledge capacity of several significant parameters, such as global stress, prestressing, ledge height, and concrete strength. In addition, the study also investigated the efficiency of selected special reinforcement details. The experimental results demonstrated that increasing the global stress significantly reduces ledge capacity, while the use of prestressing increases the capacity. The research also demonstrated that concentrating the ledge reinforcement at the load location can significantly increase the ledge capacity, offering a practical design alternative for carrying heavy loads.

The design procedure for ledges of L-shaped beams presented in the seventh edition of the PCI Design Handbook: Precast and Prestressed Concrete has been called into question by many engineers and researchers. Research findings from previous experimental studies have indicated that the ledge design equations provided in the seventh edition of the PCI Design Handbook overestimate the ledge punching-shear capacity. This paper presents the findings of the first phase of a comprehensive experimental program conducted with the objective of developing design guidelines for the ledges of L-shaped beams. In this first phase of study, short-span beams were used to minimize the effect of global stresses and the cost of testing, thus allowing for a larger number of parameters to be examined. The main objectives of this study were to investigate the ledge behavior and the configuration of the failure surface. In addition, the study also investigated the effect of various parameters believed to affect ledge behavior. The study also investigated the performance of special reinforcement details toward the development of detailing recommendations for ledge reinforcement. Research findings indicate that even with low levels of global stress, the ledge design procedure provided in the seventh edition of the PCI Design Handbook could overestimate the ledge capacity. Furthermore, the observed failure surface was generally larger than the assumed surface specified by the PCI procedure. The study also found that several parameters affected the ledge capacity but are not considered by the PCI procedure. Finally, the study also demonstrated that certain reinforcement details can be used to improve the ledge behavior and to enhance the ledge capacity.

Droop control has been widely used as a load-sharing method between paralleled power sources in DC microgrid due to its modularity and reliability. Existing droop gains design methods rely on computationally intensive supervisory control algorithms and knowledge of sub-system parameters.This paper presents a streamlined design approach for optimal droop gains, relying only on the knowledge of the parameters of the local converter power losses model in order to achieve minimum power losses for a More Electric Aircraft (MEA) DC microgrid. Additionally, a simplified, but sufficiently accurate, converter losses model is proposed in this paper for optimal droop gains design. The proposed converter losses model consists of two parts; no-load losses, and losses which are represented by Equivalent Series Resistance (ESR). The proposed design approach analyses show that setting the optimal droop gains equal to the converter ESR will achieve minimum overall DC microgrid power losses without the need for any additional information on the DC transmission line parameters. The effectiveness of the optimal droop gains design method is tested in a simulation environment and evaluated experimentally using a laboratory DC microgrid test rig.

Routing protocols are responsible for discovering and maintaining energy-efficient routes in wireless sensor networks (WSNs) to make reliable and efficient communication. The main aim of the routing protocol design is collecting data of the sensor field efficiently. In general, routing in WSNs can be classified into three groups: flat routing, hierarchical routing, and location routing. According to the literature, hierarchical routing has more advantages compared to other types, for example, hierarchical routing reduces the redundant data transmission and balances the load among the sensor nodes in an efficient way. Recently, many intelligent-based hierarchical routing protocols are developed for controlling the consumption power of WSNs. Selecting an appropriate routing protocol for specific applications is an important and difficult task for the designer of WSNs. Therefore, this chapter presents a comprehensive survey of the recently intelligent-based hierarchical routing protocols that are developed based on Particle Swarm Optimization, Ant Colony Optimization, Fuzzy Logic, Genetic Algorithm, and Artificial Immune Algorithm. These protocols will review in detail according to different metrics such as WSN type, node deployment, control manner, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated here depending on delay, network size, energy efficiency, and scalability with mentioning the advantages and drawbacks of each protocol.

Wireless sensor networks (WSNs) integrate sensor technology, microelectromechanical systems, and wireless network technologies. Saving energy and ensuring network connectivity are the most important challenges to extend the lifetime of WSNs, and optimal coverage and routing are the keys to it. The deployment strategy of sensor nodes is the most important factor for ensuring network coverage. In this chapter, two centralized energy-efficient deployment algorithms are proposed depending on one of the inspired computing algorithms called multi-objective immune algorithm (MOIA) to optimize the trade-off between the network coverage and the energy cost. The first deployment algorithm is called an immune-based node deployment algorithm (INDA). The INDA considers the dissipated energy in the mobility besides the network coverage during the relocation operation with considering the effect of the obstacles and field’s boundaries, while the second deployment algorithm is called a centralized Voronoi-based immune deployment algorithm (CVIDA) that mixes the MOIA and the Voronoi diagram. The CVIDA considers the dissipated energy in the mobility, the sensing, and the redundant coverage in its objective function besides the network coverage. CVIDA finds the locations of the sensor nodes and the optimal working nodes based on reducing the mobility cost, adjusting the sensing range, and controlling the communication radio of each node. Many experiments are conducted to validate the performance of the proposed algorithms compared to the state of the art.

Detection of interictal epileptic discharges (IED) events in the EEG recordings is a critical indicator for detecting and diagnosing epileptic seizures. We propose a key technology to extract the most important features related to epileptic seizures and identifies the IED events based on the interaction between frequencies of EEG with the help of a two-level recurrent neural network. The proposed classification network is trained and validated using the largest publicly available EEG dataset from Temple University Hospital. Experimental results clarified that the interaction between β and β bands, β and γ bands, γ and γ bands, δ and δ bands, θ and α bands, and θ and β bands have a significant effect on detecting the IED discharges. Moreover, the obtained results showed that the proposed technique detects 95.36% of the IED epileptic events with a false-alarm rate of 4.52% and a precision of 87.33% by using only 25 significant features. Furthermore, the proposed system requires only 164 ms for detecting a 1-s IED event which makes it suitable for real-time applications.

Recently, mobile wireless sensor network has drawn attention widely. In this paper, Joint Nodes and Sink Mobility based Immune routing-Clustering protocol (JNSMIC) is proposed to support the mobility of the sink and the sensor nodes together. It depends on using the mobile sink for solving the hot spot problem and the Multi-Objective Immune Algorithm (MOIA) for clustering the network and finding the visiting locations of the mobile sink. The JNSMIC protocol considers diferent objectives during the clustering process, namely the consumption energy, network coverage, link connection time (LCT), residual energy and mobility. Also, it reduces the computational time of finding cluster heads (CHs) by dividing it into two phases. In the frst phase, the candidate CHs set is formed based on residual energy, mobility factor and LCT of sensor nodes. While in the second phase, the MOIA algorithm is utilized to determine the final CHs subject to reducing the communication cost, improving the packet delivery ratio and ensuring network stability. JNSMIC performs the clustering process only if the remaining energy is below a threshold value thus the computational time and overhead control packets are reduced. In JNSMIC, the deputy CH concept is considered to perform the task of CH during CH failure. Furthermore, the proposed protocol performs a fault-tolerance process after transmitting each frame to maintain the link stability among CHs and their members which improves the throughput. Simulation results show that the JNSMIC protocol can effectively ameliorate the throughput while simultaneously giving lower energy expenditure and end-to-end delay.