The sensitivity analysis of the translation and the rotation angle of the first-order mode shape of the joints in frame structures

When damage occurs, there are changes in the structural stiffness. This causes changes in the vibrational information, such as translation and rotation angle of the joints in the structure. This paper presents a sensitivity study of translation and slope of the first-order mode shape of the joints in the frame structure, and which will contribute to structural damage identification further. Starting from the equation of natural vibration of frame structure, and according to the characteristics of the stiffness matrix, derive sensitivity coefficient expression of translation and slope of first-order mode shape of the joints in the structure, and obtain the first-order relative sensitivity coefficient of the first story is always smaller than zero when single column of the first story damage occurs. The numerical analysis of the four stories three spans frame shows consistent results with the formula derivation

The status of the energy calibration, polarization and monochromatization of the FCC-ee

The Future Circular electron-positron Collider, FCC- ee, is designed for unprecedented precision for particle physics experiments from the Z-pole up to above the top-pair-threshold, corresponding to a beam energy range from 45.6 to 182.5 GeV. Performing collisions at various particle-physics resonances requires precise knowledge of the centre-of-mass energy (ECM) and collision boosts at all four interaction points. Measurement of the ECM by resonant depolarization of transversely polarized pilot bunches in combination with a 3D polarimeter, aims to achieve a systematic uncertainty of 4 and 100 keV for the Z-pole and W-pair-threshold energies respectively. The ECM itself depends on the RF-cavity locations, beamstrahlung, longitudinal impedance, the Earth’s tides, opposite sign dispersion and possible collision offsets. Application of monochromatization schemes are envisaged at certain beam energies to reduce the energy spread. The latest results of studies of the energy calibration, polarization and monochromatization are reported here

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

Dense velocity reconstruction from particle image velocimetry/particle tracking velocimetry using a physics-informed neural network

The velocities measured by particle image velocimetry (PIV) and particle tracking velocimetry (PTV) commonly provide sparse information on flow motions. A dense velocity field with high resolution is indispensable for data visualization and analysis. In the present work, a physics-informed neural network (PINN) is proposed to reconstruct the dense velocity field from sparse experimental data. A PINN is a network-based data assimilation method. Within the PINN, both the velocity and pressure are approximated by minimizing a loss function consisting of the residuals of the data and the Navier-Stokes equations. Therefore, the PINN can not only improve the velocity resolution but also predict the pressure field. The performance of the PINN is investigated using two-dimensional (2D) Taylor's decaying vortices and turbulent channel flow with and without measurement noise. For the case of 2D Taylor's decaying vortices, the activation functions, optimization algorithms, and some parameters of the proposed method are assessed. For the case of turbulent channel flow, the ability of the PINN to reconstruct wall-bounded turbulence is explored. Finally, the PINN is applied to reconstruct dense velocity fields from the experimental tomographic PIV (Tomo-PIV) velocity in the three-dimensional wake flow of a hemisphere. The results indicate that the proposed PINN has great potential for extending the capabilities of PIV/PTV

An improved cell transmission model of traffic considering electric vehicles and charging stations

International audience; In this paper, we extend a previously introduced traffic cell transmission model (CTM) to take electric vehicles (EVs) and charging stations (CSs) into account. The CTM is improved in the following aspects: firstly, traffic demand of multiple origins-destinations (O-D) is considered, whereas the original CTM can not simulate the specific traffic demand of each O-D pair; secondly, CSs are integrated into CTM by developing new queueing cells and charging cells, which could also describe the specific configurations of each CS and model the queueing phenomenon in CSs; third, EVs at different states of charge are considered and, thus, the spatial-temporal charging demands in CSs can be estimated with good approximation

Resilience-based optimal post-disruption reconfiguration for traffic-power systems

The increasing penetration of grid-enabled electric vehicles (EVs) renders road networks (RNs) and power networks (PNs) increasingly interdependent for normal operation. For this reason, recently few studies have started to investigate the vulnerability of a highly coupled traffic-power system in the presence of disruptive events. Actually, however, only very few of these studies have considered the impact of EVs on the interdependent traffic-power system during restoration from a disruptive event. In an attempt to fill this gap, in this study, we investigate the restoration planning of both independent RNs and PNs, and interdependent traffic-power systems. A mixed integer program model is formulated to provide optimal reconfiguration and operational solutions for post-disruption traffic-power systems recovery. The objective of the model is to minimize the total cost incurred by system performance loss, which is quantified by the cumulative unmet traffic demand for RNs and load shedding cost for PNs. Several reconfiguration strategies are considered, including links reversing in RNs and line switching in PNs, to optimize system resilience. In the proposed model, the integrated problem of system optimal dynamic traffic assignment and optimal power flow is solved to derive the optimal traffic-power flow. RNs and PNs are coupled through the coordinately allocated spatio-temporal charging demand of EVs. A partial highway network in North Carolina (NC), USA, and a modified IEEE-14 bus system are used to illustrate the application of the model. The numerical results obtained show the added value of coordinately planning restoration for traffic-power systems and the effects of different levels of EV penetration

Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems

International audienceThe increasing penetration of grid-enabled electric vehicles (EVs) renders road networks (RNs) and power networks (PNs) increasingly interdependent for normal operation. For this reason, recently few studies have started to investigate the vulnerability of a highly coupled traffic-power system in the presence of disruptive events. Actually, however, only very few of these studies have considered the impact of EVs on the interdependent traffic-power system during restoration from a disruptive event. In an attempt to fill this gap, in this study, we investigate the restoration planning of both independent RNs and PNs, and interdependent traffic-power systems. A mixed integer program model is formulated to provide optimal reconfiguration and operational solutions for post-disruption traffic-power systems recovery. The objective of the model is to minimize the total cost incurred by system performance loss, which is quantified by the cumulative unmet traffic demand for RNs and load shedding cost for PNs. Several reconfiguration strategies are considered, including links reversing in RNs and line switching in PNs, to optimize system resilience. In the proposed model, the integrated problem of system optimal dynamic traffic assignment and optimal power flow is solved to derive the optimal traffic-power flow. RNs and PNs are coupled through the coordinately allocated spatio-temporal charging demand of EVs. A partial highway network in North Carolina (NC), USA, and a modified IEEE-14 bus system are used to illustrate the application of the model. The numerical results obtained show the added value of coordinately planning restoration for traffic-power systems and the effects of different levels of EV penetration

Risk Assessment of Electrical Power Systems Considering Traffic Congestion

With the increasing penetration of electric vehicles in the transportation system, more and more interactions appear between the transportation and power systems. This requires considering the impact of disturbances in the electrified transportation system onto the stability of the power system. This paper addresses this issue by proposing a method based on a cell transmission model (CTM) of the electrified transportation system and an alternative current (AC) model of the power system. Specifically, CTM is used to simulate the dynamic realtime traffic under congestion disturbances and evaluate the charging demands in the areas of the electrified transportation system. The charging demands are input to the AC model of the power system to calculate the fluctuations in power flow distributions. The proposed method can simulate the dynamic interactions between the electrified transportation system and the power system, and quantitatively measure the impacts of traffic disturbances on the stability of the power system. A numerical example is used to illustrate the proposed method

Risk Assessment of an Electrical Power System Considering the Influence of Traffic Congestion on a Hypothetical Scenario of Electrified Transportation System in New York State

International audienceWith the increasing penetration of electric vehicles (EVs), more and more interactions appear between the transportation system and the power system, which might provide new hazards and channels for the proliferation of failures across the boundaries of the individual systems. In this context, this paper proposes an integrated risk assessment framework for an electric power system, considering scenarios that involve the electrified transportation system enabled by EVs charging technology in New York (NY) State. Firstly, scenarios in the transportation network of NY State, e.g. of reduced capacity and incident, are generated by a Monte Carlo non-sequential algorithm. Then, the cell transmission model (CTM) is used to simulate the evolution of the traffic flows under such scenarios. This allows evaluating the spatial-temporal EV charging loads in different areas of the electrified transportation system of NY State. Correspondingly, the running parameters in the studied power system are updated by the alternative current (AC) power flow model. Finally, the risk for the power system coming from the transportation system scenarios is assessed within a probabilistic risk analysis framework. The proposed integrated risk assessment framework is able to model the propagation of the effects of scenarios in the transportation system onto the power system of NY State and quantify the consequences. A real test case is used to illustrate the proposed framework

Mass-Conserved Solution to the Ffowcs-Williams and Hawkings Equation for Compact Source Regions

A mass-conserved formulation for the Ffowcs-Williams–Hawkings (FW–H) integral is proposed to suppress contributions of spurious mass flux to the far-field sound at very low Mach numbers. The far-field condition and compact-source region assumptions are employed. By using higher-order derivatives of Green’s function, an expansion of the integrand in the monopole term is performed. This expansion transforms the mass-flux like monopole term into a series including different orders of velocity moment. At very low Mach numbers, the zero-order term is exactly the contribution from the spurious mass flux. The proposed mass-conserved formulation is confirmed by using an unsteady dipole, a two-dimensional (2D) incompressible convecting vortex, a circular-cylinder flow, and a co-rotating vortex pair. Additional spurious mass flux is added to the unsteady dipole, 2D incompressible convecting vortex, and flows over a circular cylinder; and the spurious mass flux of the co-rotating vortex pair comes from the residual of an incompressible-flow simulation. The far-field sound is found to be sensitive to spurious mass flux in the unsteady dipole and 2D incompressible convecting vortex cases. Then, the computation of the monopole-term expansion with the flow over a circular cylinder is presented. Fast convergence performance was observed, suggesting that the expansion requires little extra computational resources. Finally, FW–H boundary dependence is observed in the co-rotating vortex-pair case and eliminated by using the proposed mass-conserved formulation