Method for forecasting the flood risk in a tropical country

In this study, a novel method for forecasting the flood risk in a tropical country is proposed, called CIHAM-UC-FFR. The method is based on the rainfall–runoff process. The CIHAM-UC-FFR method consists of three stages: (1) calibration and validation for the effective precipitation model, called CIHAM-UC-EP model, (2) calibration of forecasting models for components of the CIHAM-UC-EP model, (3) proposed model for forecasting of gridded flood risk called CIHAM-UC-FR. The CIHAM-UC-EP model has a mathematical structure derived from a conceptual model obtained by applying the principle of mass conservation combined with the adapted principle of Fick's law. The CIHAM-UC-FR model is a stochastic equation based on the exceedance probability of the forecast effective precipitation. Various scenarios are shown for a future time where the flood risk is progressively decreased as the expected life parameter of the hydraulic structure is increased.

Increase in Efficiency of End Milling of Titanium Alloys Due to Tools with Multilayered Composite Nano-Structured Zr-ZrN-(Zr,Al)N and Zr-ZrN-(Zr,Cr,Al)N Coatings

The study deals with an increase in the tool life parameter for metal-cutting tools and efficiency of end milling for titanium alloys, due to the use of tools with multilayered composite nano-structured Zr–ZrN–(Zr,Al)N and Zr–ZrN–(Zr,Cr,Al)N coatings, deposited through the technology of the filtered cathodic vacuum arc deposition (FCVAD). The studies included the microstructured investigations using SEM, the analysis of chemical composition (Energy-dispersive X-ray spectroscopy, EDXS), the determination of the value of critical failure force (with the use of scratch testing), and the measurement of the microhardness of the coatings under study. The cutting tests were conducted in end milling of titanium alloys at various cutting speeds. The mechanisms of wear and failure for end milling cutters with the coatings under study were studied in milling. The studies determined the advantages of using a tool with the coatings under study compared to an uncoated tool, as well as to tools with the commercial Ti–TiN coating and the nano-structured Ti–TiN–(Ti,Al)N coating. Adding Cr to the composition of the coating can significantly increase the hardness, while the coating retains sufficient ductility and brittle fracture resistance, which allows for a best result when milling titanium alloys.

Continuous Closed-Loop Decoder Adaptation with a Recursive Maximum Likelihood Algorithm Allows for Rapid Performance Acquisition in Brain-Machine Interfaces

Closed-loop decoder adaptation (CLDA) is an emerging paradigm for both improving and maintaining online performance in brain-machine interfaces (BMIs). The time required for initial decoder training and any subsequent decoder recalibrations could be potentially reduced by performing continuous adaptation, in which decoder parameters are updated at every time step during these procedures, rather than waiting to update the decoder at periodic intervals in a more batch-based process. Here, we present recursive maximum likelihood (RML), a CLDA algorithm that performs continuous adaptation of a Kalman filter decoder's parameters. We demonstrate that RML possesses a variety of useful properties and practical algorithmic advantages. First, we show how RML leverages the accuracy of updates based on a batch of data while still adapting parameters on every time step. Second, we illustrate how the RML algorithm is parameterized by a single, intuitive half-life parameter that can be used to adjust the rate of adaptation in real time. Third, we show how even when the number of neural features is very large, RML's memory-efficient recursive update rules can be reformulated to also be computationally fast so that continuous adaptation is still feasible. To test the algorithm in closed-loop experiments, we trained three macaque monkeys to perform a center-out reaching task by using either spiking activity or local field potentials to control a 2D computer cursor. RML achieved higher levels of performance more rapidly in comparison to a previous CLDA algorithm that adapts parameters on a more intermediate timescale. Overall, our results indicate that RML is an effective CLDA algorithm for achieving rapid performance acquisition using continuous adaptation.

Method for Determining the Reliable Life Parameter of Turbine Wheel of Turbocharger with Over-Speed Failure Mode

For the over-speed failure mode, the method for determining the reliable life parameter of turbine wheel of turbocharger is proposed in this paper. The shortage of design criteria based on conventional safety factor for turbine wheel with over-speed failure mode is analyzed. In order to embody the characteristics of structure and over-speed failure mode, the turbine wheel is taken as a series system consisting of several blade symmetrical components in the reliability modeling process. The time-reliability models of turbine wheel are derived and the relationship between the reliability and failure rate of turbine wheel and life parameter is studied. Then, the method for determining the reliable life parameter of turbine wheel of turbocharger with over-speed failure mode is proposed based on the reliability model and reliability curve. As long as the design parameters including the number of blades, speed, stress, and strength are given, the reliable life of turbine wheel of turbocharger with over-speed failure mode can be determined with the method proposed.