Enhanced heat transfer in a heat exchanger square-duct with discrete V-finned tape inserts

The article presents an experimental and numerical study on thermal performance enhancement in a constant heatfluxed square-duct inserted diagonally with 45° discrete V-finned tapes(DFT).The experiments were carried out by varying the airflow rate through the tested square duct with DFT inserts for Reynolds number from 4000 to 25000.The effect of the DFT with V-tip pointing upstream at various relative fin heights and pitches on heat transfer and pressure drop characteristics was experimentally investigated.Both the heat transfer and pressure drop were presented in terms of Nusselt number and friction factor respectively.Several V-finned tape characteristics were introduced such as fin- to duct-height ratio or blockage ratio(R_B=e/H = 0.075,0.1,0.15 and 0.2),fin pitch to duct height ratio(R_P= P/H=0.5,1.0,1.5 and 2.0) and fin attack angle,α = 45°.The experimental results reveal that the heat transfer and friction factor values with DFT inserts increase with the increment of R_B but the decrease of R_P.The inserted square-duct at R_B = 0.2 and R_P = 0.5 provides the highest heat transfer and friction factor while the one with R_B= 0.1 and R_P= 1.5 yields the highest thermal performance.Also,a numerical simulation was conducted to investigate the flow structure and heat transfer mechanism inside the tested duct with DFT inserts.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Linear Quadratic Integral Control for the Active Suspension of Vehicle

The quarter model of an active suspension is established in the form of controllable autoregressive moving average （CARMA） model. An accelerometer can be mounted on the wheel hub for measuring road disturbance; this signal is used to identify the CARMA model parameters by recursive forgetting factors least square method. The linear quadratic integral （LQI） control method for the active suspension is presented. The LQI control algorithm is fit for vehicle suspension control, for the control performance index can comprise multi controlled variables. The simulation results show that the vertical acceleration and suspension travel both are decreased with the LQI control in the low frequency band, and the suspension travel is increased with the LQI control in the middle or high frequency band. The suspension travel is very small in the middle or high frequency band, the suspension bottoming stop will not happen, so the vehicle ride quality can be improved apparently by the LQI control.

Sensitivity of coercivity and squareness factor of a Nd-Fe-B sintered magnet on post-sintering annealing temperature

An N38SH-grade magnet with low oxygen content was used to study the evolution of magnetic properties upon post-sin-tering annealing. Phase transformation of as-sintered magnet was investigated by differential scanning calorimetry （DSC）. Three low temperature eutectic transition points were detected. Little change could be found when annealed below the lowest eutectic transition point. A wide annealing temperature range （460–560 oC） between the lowest and highest eutectic transition point was available for this magnet to achieve a relatively high coercivity （~1671 kA/m） at a relatively low Dy content （~3 wt.%）. However, squareness fac-tor （SF） of the demagnetizing curve and its temperature stability were found to decrease after annealing above the highest eutectic transition point. This was attributed to the change of Cu content in the Nd-rich phase under different annealing temperatures.

A CLASS OF FACTORIZED QUASI-NEWTON METHODS FOR NONLINEAR LEAST SQUARES PROBLEMS

This paper gives a class of descent methods for nonlinear least squares solution. A class of updating formulae is obtained by using generalized inverse matrices. These formulae generate an approximation to the second part of the Hessian matrix of the objective function, and are updated in such a way that the resulting approximation to the whole Hessian matrix is the convex class of Broyden-like up-dating formulae. It is proved that the proposed updating formulae are invariant under linear transformation and that the class of factorized quasi-Newton methods are locally and superlinearly convergent. Numerical results are presented and show that the proposed methods are promising.

REAL-TIME FLOOD FORECASTING METHOD WITH 1-D UNSTEADY FLOW MODEL

A real-time forecasting method coupled with the I-D unsteady flow model with the recursive least-square method was developed. The 1-D unsteady flow model was modified by using the time-variant parameter and revising it dynamically through introducing a variable weighted forgetting factor, such that the output of the model could be adjusted for the real time forecasting of floods. The application of the new real time forecasting model in the reach from Yichang to Luoshan of the Yangtze River was demonstrated. Computational result shows that the forecasting accuracy of the new model is much higher than that of the original 1-D unsteady flow model. The method developed is effective for flood forecasting, and can be used for practical operation in the flood forecasting.

Modeling and state of charge estimation of lithium-ion battery

Modeling and state of charge （SOC） estimation of lithium-ion （Li-ion） battery are the key techniques of battery pack management system （BMS） and critical to its reliability and safety operation. An auto-regressive with exogenous input （ARX） model is derived from RC equivalent circuit model （ECM） due to the discrete-time characteristics of BMS. For the time-varying environmental factors and the actual battery operating conditions, a variable forgetting factor recursive least square （VFFRLS） algorithm is adopted as an adaptive parameter identifica- tion method. Based on the designed model, an SOC estimator using cubature Kalman filter （CKF） algorithm is then employed to improve estimation performance and guarantee numerical stability in the computational procedure. In the battery tests, experimental results show that CKF SOC estimator has a more accuracy estimation than extended Kalman filter （EKF） algorithm, which is widely used for Li-ion battery SOC estimation, and the maximum estimation error is about 2.3%.

Nonnegative tensor factorizations using an alternating direction method

The nonnegative tensor （matrix） factorization finds more and more applications in various disciplines including machine learning, data mining, and blind source separation, etc. In computation, the optimization problem involved is solved by alternatively minimizing one factor while the others are fixed. To solve the subproblem efficiently, we first exploit a variable regularization term which makes the subproblem far from ill-condition. Second, an augmented Lagrangian alternating direction method is employed to solve this convex and well-conditioned regularized subproblem, and two accelerating skills are also implemented. Some preliminary numerical experiments are performed to show the improvements of the new method.

Design, Implementation and Control of an Amphibious Spherical Robot

We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim was to improve the kinematic performance of spherical robots.We developed mechanical and dynamic models so that we could analyze the motions of the robot on land and in water.The robot was equipped with an Inertial Measurement Unit(IMU)that provided inclination and motion information.We designed three types of walking gait for the robot,with different stabilities and speeds.Furthermore,we proposed an online adjustment mechanism to adjust the gaits so that the robot could climb up slopes in a stable manner.As the system function changed continuously as the robot moved underwater,we implemented an online motion recognition system with a forgetting factor least squares algorithm.We proposed a generalized prediction control algorithm to achieve robust underwater motion control.To ensure real-time performance and reduce power consumption,the robot motion control system was implemented on a Zynq-7000 System-on-Chip(SoC).Our experimental results show that the robot’s motion remains stable at different speeds in a variety of amphibious environments,which meets the requirements for applications in a range of terrains.