Flood hazard risk forecasting index (FHRFI) for urban areas: the Hurricane Harvey case study

Hurricane Harvey caused at least 70 confirmed deaths, with estimated losses in the Houston urban area of Texas reaching above US$150 billion, making it one of the costliest natural disasters ever in the United States. The study tests two types of forecast index to provide surface flooding (inundation) warning over the Houston area: a meteorological index based on a global numerical weather prediction (NWP) system, and a new combined meteorological and land surface index, the flood hazard risk forecasting index (FHRFI), where land surface is used to condition the meteorological forecast. Both indices use the total precipitation extreme forecast index (EFI) and shift of tails (SoT) products from the European Centre for Medium‐Range Weather Forecasts (ECMWF) medium‐range ensemble forecasting system (ENS). Forecasts at the medium range (3–14 days ahead) were assessed against 153 observed National Weather Service (NWS) urban flood reports over the Houston urban area between August 26 and 29, 2017. It is shown that the method provides skilful forecasts up to four days ahead using both approaches. Moreover, the FHRFI combined index has a hit ratio of up to 74% at 72 hr lead time, with a false‐alarm ratio of only 45%. This amounts to a statistically significant 20% increase in performance compared with the meteorological indices. This first study demonstrates the importance of including land‐surface information to improve the quality of the flood forecasts over meteorological indices only, and that skilful flood warning in urban areas can be obtained from the NWP using the FHRFI

INTEGRATION OF VISION AND INERTIAL SENSORS FOR A SURGICAL TOOL TRACKING

ABSTRACT This paper represents a hybrid Vision/INS system in a microsurgical tool tracking application. Surgical MEMS devices must not only cope with all of the challenges that conventional MEMS devices have, but also address the integration of electronics and signal processing, calibration, reliability, accuracy and testing. A hybrid Vision/INS system with the integration of the Extended Kalman Filter precisely calculates 6D positionorientation of a microsurgical tool during surgery. This configuration guarantees the real-time tracking of the instrument. Ultimately, the vision system supports the IMU to deal with the drift problem but the position error increases dramatically in the absence of the vision system. In this paper, the tool motion modeling is proposed to bind the error in the acceptable range for a short period of missing data. The motion of the tool is modeled and updated at any time that the instrument is in the camera view field. This model is applied to the estimation algorithm whenever the camera is not in line of site and the optical data is missing. INTRODUCTION Over the past few decades, micro-electromechanical systems (MEMS) have been used in a wide range of research areas. Recently, interest in the use of MEMS for surgical applications has been growing. It is a technology that allows performance enhancement of the surgical instruments. This technology enables hospitals to add new facilities, allowing surgeons to develop new methods and advanced techniques. MEMS can decrease the risk to patients by providing the realtime feedback for surgeons to control the surgical procedure

Sensitivity analysis of frequency response of a piecewise linear system in frequency island

In this paper, we analyze the frequency response of a piecewise linear suspension system. Dynamical characteristics of the suspension will suddenly change when its relative displacement exceeds a clearance. Piecewise linear characteristics occur, for example, wherever we use stoppers to prevent the system from excessive relative displacement. A modified averaging method is used to find the frequency response of the system to a harmonic base excitation. A frequency island is observed, which corresponds to large amplitude vibration for a certain range of system parameters. The island is an isolated region that cannot be reached by the variation of excitation frequency and depends upon initial conditions. On the frequency island, the isolator amplifies the amplitude of vibration rather than suppressing it. This will be dangerous in applications where stoppers are installed to ensure relative displacement is limited. The ranges of system parameters causing the frequency island are determined. The results obtained by an analytical method are verified using numerical simulation

Root mean square optimization criterion for vibration behaviour of linear quarter car using analytical methods

In this paper, a linear two-degree-of-freedom quarter car model is used to derive a number of analytical formulae describing the dynamic behaviour of passively suspended vehicles running on a harmonically bumped road. The linearity of the system allows us to analytically investigate the steady-state response characteristics. We derive analytical expressions for the root mean square (RMS) of the sprung mass absolute acceleration and relative displacement. This paper demonstrates the shortcomings of existing classical optimization methods. Hence we introduce a new optimization method based on minimizing the absolute acceleration RMS with respect to the relative displacement RMS. The RMS optimization method is applied for the symbolic derivation of analytical formulae featuring the best compromise among conflicting performance indices pertaining to the vehicle suspension system, i.e ., sprung mass acceleration and working space. The proposed optimization technique is utilized to find the optimal damping and stiffness curves for the main suspension. The RMS optimal values are used to create design charts for suspension parameters, which are very useful particularly in the presence of physical constraints such as a limit on relative displacement. We introduce a numerical example to illustrate the optimality of the obtained solutions

Frequency response and jump avoidance in a nonlinear passive engine mount

This paper explores a model for a nonlinear one-degree of freedom passive vibration isolator system, known as a smart engine mount. Nonlinearities are employed to analyze and possibly improve the behavior of the optimal linear mount. Nonlinear damping and stiffness rates of the isolator have interacting effects on the dynamic behavior of the mount. The frequency response of the system is obtained using the averaging perturbation method, and a parametric analysis shows that the effect of nonlinear stiffness rate on frequency response is opposite to that of the nonlinear damping rate. Stability of the steady state periodic response has also been analyzed. Jump avoidance criteria are introduced, and the conditions for jump avoidance are studied. Closed form solutions for the absolute acceleration and relative displacement frequency responses are derived, since they are essential to use of the RMS optimization method