Static behavior of semi-rigid thin-walled steel-concrete composite beam-to-column joints with bolted partial-depth flush end plate:experimental study

A new type of semi-rigid thin-walled steel-concrete composite beam-to-column joint has been proposed in this paper.Five semi-rigid composite beam-to-column joint specimens subjected to hogging moments under monotonic loading were tested to study the static behavior of this new type of joint.The main variable parameters for the five joint specimens were the longitudinal reinforcement ratio and the joint type.The experimental results designated that the magnitude of extension of the longitudinal reinforcement is the most important factor that influenced the moment-rotation characteristic of the new type of joint.The concrete slabs could resist 3.8%-19.1% of the total shear load applied to the cross-sections near the beam-to-column connection.The edge stiffened elements,such as the flange of the lipped I-section thin-walled steel beam,were capable of having considerable inelastic deformation capacity although they had comparatively large width-to-thickness ratios.The shear failure of the concrete cantilever edge strip must be taken into account in practical design because it has significant influence on the anchorage of the longitudinal reinforcement in the new type of external joints.

Hot spot temperature prediction and operating parameter estimation of racks in data center using machine learning algorithms based on simulation data

In this paper,models to predict hot spot temperature and to estimate cooling air’s working parameters of racks in data centers were established using machine learning algorithms based on simulation data.First,simulation models of typical racks were established in computational fluid dynamics(CFD).The model was validated with field test results and results in literature,error of which was less than 3%.Then,the CFD model was used to simulate thermal environments of a typical rack considering different factors,such as servers’power,which is from 3.3 kW to 20.1 kW,cooling air’s inlet velocity,which is from 1.0 m/s to 3.0 m/s,and cooling air’s inlet temperature,which is from 16℃ to 26℃ The highest temperature in the rack,also called hot spot temperature,was selected for each case.Next,a prediction model of hot spot temperature was built using machine learning algorithms,with servers’power,cooling air’s inlet velocity and cooling air’s inlet temperature as inputs,and the hot spot temperatures as outputs.Finally,based on the prediction model,an operating parameters estimation model was established to recommend cooling air’s inlet temperatures and velocities,which can not only keep the hot spot temperature at the safety value,but are also energy saving.

Long dynamic range spread spectrum optical domain reflectometer

The performance of an optical time domain reflectometer(OTDR) is significantly improved using spread spectrum technology. The concept of spread spectrum OTDR(SSOTDR) is proposed, the theoretical basis and simulation results of the new method are given, and the problem of direct application of bipolar spread spectrum codes to OTDR and despreading in the optical domain are solved. The simulation results show the feasibility of the SSOTDR, which exhibits better dynamic range reported to date for a practical long-haul OTDR system without using conventional average technique.