Design of Permanent Sensor Fault Tolerance Algorithms by Sliding Mode Observer for Smart Hybrid Powerpack

In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode

Bacillus subtilis spores as adjuvants against avian influenza H9N2 induce antigen-specific antibody and T cell responses in White Leghorn chickens

Low-pathogenicity avian influenza H9N2 remains an endemic disease worldwide despite continuous vaccination, indicating the need for an improved vaccine strategy. Bacillus subtilis (B. subtilis), a gram-positive and endospore-forming bacterium, is a non-pathogenic species that has been used in probiotic formulations for both animals and humans. The objective of the present study was to elucidate the effect of B. subtilis spores as adjuvants in chickens administered inactivated avian influenza virus H9N2. Herein, the adjuvanticity of B. subtilis spores in chickens was demonstrated by enhancement of H9N2 virus-specific IgG responses. B. subtilis spores enhanced the proportion of B cells and the innate cell population in splenocytes from chickens administered both inactivated H9N2 and B. subtilis spores (Spore + H9N2). Furthermore, the H9N2 and spore administration induced significantly increased expression of the pro-inflammatory cytokines IL-1β and IL-6 compared to that in the H9N2 only group. Additionally, total splenocytes from chickens immunized with inactivated H9N2 in the presence or absence of B. subtilis spores were re-stimulated with inactivated H9N2. The subsequent results showed that the extent of antigen-specific CD4+ and CD8+ T cell proliferation was higher in the Spore + H9N2 group than in the group administered only H9N2. Taken together, these data demonstrate that B. subtilis spores, as adjuvants, enhance not only H9N2 virus-specific IgG but also CD4+ and CD8+ T cell responses, with an increase in pro-inflammatory cytokine production. This approach to vaccination with inactivated H9N2 together with a B. subtilis spore adjuvant in chickens produces a significant effect on antigen-specific antibody and T cell responses against avian influenza virus.This study and medical writing support were funded by Sanofi Genzyme and Regeneron Pharmaceuticals, Inc

Seismic resilience estimation of water transmission networks by considering flow-based network analysis

In this study, the comprehensive framework for seismic resilience estimation of water transmission networks was proposed by considering the flow-based network analysis. The proposed model consists of three phases including spatially correlated ground motion prediction equation, hydraulic analysis of damaged network, and recovery analysis of network facility. For numerical simulation of the damaged network, the MATLAB-based computer code was developed to enable the pressure driven analysis in EPANET analysis. The performance of the network system was evaluated based on system serviceability index and the direct and indirect cost were calculated according to damage states of the network facility. Numerical results showed that the slope of the resilience curve tends to decrease as the earthquake magnitude and interdependency increases

Accelerated Monte Carlo analysis of flow-based system reliability through artificial neural network-based surrogate models

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error

Optimal system design of urban water transmission network for seismic performance enhancement

In this study, an optimal system design of a water transmission network was proposed. The main purpose of the optimal system design is to maximize the seismic performance with a limited construction cost. The proposed optimal model evaluates network performance through the spatially correlated seismic attenuation law, determination of the failure status of the network component, and numerical modeling of water networks. For numerical simulations, a MATLAB code has also been developed to enable the EPANET analysis with pressure driven analysis and numerical modeling of network systems. In order to verify the proposed optimal system design model, a real water network was adopted and the location and magnitude of the earthquake were determined. In addition, two performance indices (system serviceability index, nodal serviceability index) were introduced for the network performance evaluation. Numerical results showed that the optimized network model increased system serviceability and nodal serviceability by 9.9% and 11%, respectively, and the average nodal pressure of the network increased by 3.6 m compared to existing models

Optimal decision-making on pipeline sizes of water networks under seismic conditions

In this study, an optimal decision-making model on pipeline sizes of a water transmission network has been proposed. The purpose of the optimal decision-making model is to maximize seismic performance with limited construction cost. The proposed model estimates network performance using spatially correlated seismic attenuation law, determination of the failure status of the network component, and numerical modeling of water networks. For this purpose, MATLAB code has also been developed to enable EPANET analysis using pressure-based analysis and numerical modeling of network systems. To verify the proposed model, an actual urban water network has been adopted, taking into account the location and magnitude of the historical earthquake. In addition, two performance indices were introduced to assess network performance. The numerical results show that the optimized network model increased system serviceability and node serviceability by 9.9% and 11%, respectively, and the average node pressure of the network increased 3.6m over the existing model

Flow-based optimal system design of urban water transmission network under seismic conditions

In this paper, an optimal system design for the seismic performance enhancement of a water transmission network was proposed. The main purpose of the optimal design is to maximize the system performance within a limited construction cost. The proposed model evaluates network performance through the spatially correlated seismic attenuation law, determination of the failure status of the network facility, and numerical modeling of water networks. For hydraulic simulation, a MATLAB computer code was developed to enable the EPANET program with pressure-driven analysis. To demonstrate the proposed model, an actual water transmission network of A-city, South Korea was adopted, and a water network map was constructed based on the geographic information system data. Numerical results showed that the optimized network model increased system serviceability and nodal serviceability by 9.9% and 11%, respectively, and the average nodal pressure of the network increased by 3.6 m compared to existing models. In addition, the result of the optimal pipeline design was utilized to compare the performance against interdependencies and the elapsed time of pipelines. The optimized network exhibited higher performance than the existing network, depending on the elapsed time and interdependence. Therefore, to maximize the performance of the water network, it is necessary to use optimized network design parameters according to the appropriate construction budget

A comprehensive approach to flow-based seismic risk analysis of water transmission network

Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration

Flow-based seismic risk assessment of a water transmission network employing probabilistic seismic hazard analysis

In this study, a seismic risk assessment model was proposed to evaluate the seismic reliability of a water transmission network. The proposed risk assessment model involves earthquake generation and hydraulic analysis modules. To consider a comprehensive approach, the numerical simulation strategy includes probabilistic seismic hazard analysis, buried pipeline deterioration, numerical modeling of network facilities, and the interdependency between pumping plant and substation. For this purpose, a flow-based MATLAB code has been developed that enables iterative hydraulic analysis using EPANET software. For numerical simulation, the epicenter and earthquake magnitudes were determined based on probabilistic seismic hazard analysis, and a real water transmission network in South Korea was constructed. From the numerical results, two performance indicators (system serviceability and nodal serviceability) and four mean normal status ratios of facilities were adopted to evaluate the network performance. In addition, a component importance measure of facilities in a network system was calculated by introducing a reduction factor. The numerical results using the proposed flow-based model show that the system performance is affected by buried pipeline deterioration and network interdependency, as well as the location and magnitude of the input earthquake. It is thus concluded that the seismic risk assessment of a water transmission network should be performed using a model with a comprehensive approach

Flow-based seismic resilience assessment of urban water transmission networks

In this study, a new framework of seismic resilience estimation for urban water transmission networks was developed. The proposed resilience estimation model consists of three phases: input earthquake generation, hydraulic analysis, and recovery of network facilities. In the earthquake generation phase, the uncertainty of the ground motion is determined using the spatially correlated seismic attenuation law. In the hydraulic analysis phase, a hydraulic simulation is performed in conjunction with EPANET analysis. In the recovery phase, network components are restored, and the performance of the recovered network is evaluated through hydraulic analysis. Then, the seismic resilience curve and recovery costs are calculated. For a numerical simulation, a MATLAB-based computer code was developed for pressure-driven analysis in EPANET simulation. To demonstrate the proposed model, an actual water transmission network in South Korea was reconstructed based on geographic information system data. The performance of the network system was evaluated according to two performance indices: system and nodal serviceability. Finally, the cost of repairing the network facilities and water loss are estimated according to earthquake magnitude and interdependency. Numerical results show that the recovery slope of the resilience curve tends to decrease as the earthquake magnitude and interdependency with the power facilities increase