Mechanical Properties of Layered Steel Fiber and Hybrid Fiber Reinforced Concrete

To explore a new structure form of fiber reinforced concrete, namely, the layered steel fiber and layered hybrid fiber reinforced concrete （LSFRC and LHFRC）, the mechanical properties of LSFRC and LHFRC, such as compressive strength, tensile strength, flexural strength, fatigue and durability were focused on. The experimental results show that LSFRC and LHFRC can improve the flexural strength of concrete by 20%-50%. In the aspect of improving the flexural strength of concrete, adulterant rate has more obvious effect than length/diameter ratio. Double logarithmic fatigue equation considered liveability was founded. The impermeability of LHFRC is superior to LSFRC and plain concrete （C）. However, the porosity of LHFRC is lower than LSFRC and C. The shrinkage of LHFRC at every age is obviously lower than C. The antifreeze durability of LHFRC is also better than C.

Mechanical Properties of Layered Hybrid Fiber Reinforced Concrete

To improve the mechanical properties of concrete,Layered Hybrid Fiber Reinforced Concrete (LHFRC) was developed in this paper.Through comparative tests,the effects of layered hybrid fibers on a series of mechanical properties of concrete were discussed.The mechanical properties include compressive strength,tensile strength,flexural strength,compressive stress-strain relationship,flexural toughness and cracking resistance of concrete.The testing results and analysis demonstrate that layered hybrid fibers can significantly improve the flexural strength,toughness and cracking resistance of concrete while the cost of concrete increases slightly.

Competitive precipitation behavior of hybrid reinforcements in copper matrix composites fabricated by powder metallurgy

Copper matrix composites reinforced by in situ-formed hybrid titanium boride whiskers(TiB_(w))and titanium diboride particles(TiB_(2p))were fabricated by powder metallurgy.Microstructural observations showed competitive precipitation behavior between TiB_(w) and TiB_(2p),where the relative contents of the two reinforcements varied with sintering temperature.Based on thermodynamic and kinetic assessments,the precipitation mechanisms of the hybrid reinforcements were discussed,and the formation of both TiB_(w) and TiB_(2p) from the local melting zone was thermodynamically favored.The precipitation kinetics were mainly controlled by a solid-state diffusion of B atoms.By forming a compact compound layer,in situ reactions were divided into two stages,where Zener growth and Dybkov growth prevailed,respectively.Accordingly,the competitive precipitation behavior was attributed to the transition of the growth model during the reaction process.

Dynamic Compression Behavior of Ultra-high Performance Cement-based Composite with Hybrid Steel Fiber Reinforcements

Ultra-high performance cement-based composites (UHPCC) is promising in construction of concrete structures that suffer impact and explosive loads.In this study,a reference UHPCC mixture with no fiber reinforcement and four mixtures with a single type of fiber reinforcement or hybrid fiber reinforcements of straight smooth and end hook type of steel fibers were prepared.Split Hopkinson pressure bar (SHPB) was performed to investigate the dynamic compression behavior of UHPCC and X-CT test and 3D reconstruction technology were used to indicate the failure process of UHPCC under impact loading.Results show that UHPCC with 1% straight smooth fiber and 2% end hook fiber reinforcements demonstrated the best static and dynamic mechanical properties.When the hybrid steel fiber reinforcements are added in the concrete,it may need more impact energy to break the matrix and to pull out the fiber reinforcements,thus,the mixture with hybrid steel fiber reinforcements demonstrates excellent dynamic compressive performance.

Flexural Fatigue Behavior of Layered Hybrid Fiber Reinforced Concrete

In order to obtain the fatigue life of layered hybrid fiber reinforced concrete （LHFRC） at different stress levels, flexural fatigue tests were carried out on specimens. The relation between fatigue lives and stress levels was simulated using the two-parameter Weibull distribution. Furthermore, both single- logarithmic and double-logarithmic regressive equations of various reliabilities were derived. It is evident that LHFRC gets the advantage of longer fatigue life over common concrete.

Stochastic pedestrian avoidance for autonomous vehicles using hybrid reinforcement learning

Ensuring the safety of pedestrians is essential and challenging when autonomous vehicles are involved.Classical pedestrian avoidance strategies cannot handle uncertainty,and learning-based methods lack performance guarantees.In this paper we propose a hybrid reinforcement learning(HRL)approach for autonomous vehicles to safely interact with pedestrians behaving uncertainly.The method integrates the rule-based strategy and reinforcement learning strategy.The confidence of both strategies is evaluated using the data recorded in the training process.Then we design an activation function to select the final policy with higher confidence.In this way,we can guarantee that the final policy performance is not worse than that of the rule-based policy.To demonstrate the effectiveness of the proposed method,we validate it in simulation using an accelerated testing technique to generate stochastic pedestrians.The results indicate that it increases the success rate for pedestrian avoidance to 98.8%,compared with 94.4%of the baseline method.

Fatigue shear performance of concrete beams reinforced with hybrid(glass-fiber-reinforced polymer+steel)rebars and stirrups

Reinforced concrete beams consisting of both steel and glass-fiber-reinforced polymer rebars exhibit excellent strength,serviceability,and durability.However,the fatigue shear performance of such beams is unclear.Therefore,beams with hybrid longitudinal bars and hybrid stirrups were designed,and fatigue shear tests were performed.For specimens that failed by fatigue shear,all the glass-fiber-reinforced polymer stirrups and some steel stirrups fractured at the critical diagonal crack.For the specimen that failed by the static test after 8 million fatigue cycles,the static capacity after fatigue did not significantly decrease compared with the calculated value.The initial fatigue level has a greater influence on the crack development and fatigue life than the fatigue level in the later phase.The fatigue strength of the glass-fiber-reinforced polymer stirrups in the specimens was considerably lower than that of the axial tension tests on the glass-fiber-reinforced polymer bar in air and beam-hinge tests on the glass-fiber-reinforced polymer bar,and the failure modes were different.Glass-fiber-reinforced polymer stirrups were subjected to fatigue tension and shear,and failed owing to shear.

An artificial neural network model on tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag power

The tensile behavior of hybrid fiber reinforced concrete(HFRC)is important to the design of HFRC and HFRC structure.This study used an artificial neural network(ANN)model to describe the tensile behavior of HFRC.This ANN model can describe well the tensile stress-strain curve of HFRC with the consideration of 23 features of HFRC.In the model,three methods to process output features(no-processed,mid-processed,and processed)are discussed and the mid-processed method is recommended to achieve a better reproduction of the experimental data.This means the strain should be normalized while the stress doesn’t need normalization.To prepare the database of the model,both many direct tensile test results and the relevant literature data are collected.Moreover,a traditional equation-based model is also established and compared with the ANN model.The results show that the ANN model has a better prediction than the equation-based model in terms of the tensile stress-strain curve,tensile strength,and strain corresponding to tensile strength of HFRC.Finally,the sensitivity analysis of the ANN model is also performed to analyze the contribution of each input feature to the tensile strength and strain corresponding to tensile strength.The mechanical properties of plain concrete make the main contribution to the tensile strength and strain corresponding to tensile strength,while steel fibers tend to make more contributions to these two items than PVA fibers.

An efficient hyper-elastic model for the preforming simulation of Carbon-Kevlar hybrid woven reinforcement

An efficient hyper-elastic model that can reflect the primary mechanical behaviors of Carbon-Kevlar hybrid woven reinforcement was developed and implemented with VUMAT constitutive code for preforming simulation.The model parameters were accurately determined through the uniaxial and bias-extension tests.To calibrate the simulation code,preforming experiments of hybrid woven reinforcement over the hemisphere mold and tetrahedron mold were respectively conducted to validate the proposed hyper-elastic model.The comparison between the simulations and experiments shows that the model can not only accurately capture shear angle distribution and geometry shape after deformation,but also accurately predict the force–displacement curve and potential fiber tensile failure during the preforming process.This result indicates that the proposed model can be used to predict the preforming behavior of Carbon-Kevlar hybrid woven reinforcement,and simulate its manufacturing process of complicated geometry.

Laser welding process and strength enhancement of carbon fiber reinforced thermoplastic composites and metals dissimilar joint:A review

Carbon fiber reinforced thermoplastic composites(CFRTP)and metals hybrid structures have been widely used in aircraft lightweight manufacturing.However,due to the significant difference in physical and chemical properties between CFRTP and metals,there are lots of challenges to connect them with high quality.Laser welding has a good application prospect in CFRTP and metals connection,and a significant research progress has been made in the exploration of CFRTP-metal laser joining mechanism,joining process optimization,joining strength improvement and joining defects controlling.However,there are still some problems need to be solved for this technology application.In this paper,the research progress of CFRTP-metal laser joining was summarized in three major aspects:theoretical modeling and simulation analysis,process exploration and parameter optimization,joint performance improvement and process innovation.And,problems and challenges of this technology were discussed,and the outlook of this research was provided.

An enhanced eco-driving strategy based on reinforcement learning for connected electric vehicles:cooperative velocity and lane-changing control

Purpose–This study aims to propose an enhanced eco-driving strategy based on reinforcement learning(RL)to alleviate the mileage anxiety of electric vehicles(EVs)in the connected environment.Design/methodology/approach–In this paper,an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed for connected EVs.The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving.Moreover,this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.Findings–To illustrate the performance for the EEDC-HRL,the controlled EV was trained and tested in various traffic flow states.The experimental results demonstrate that the proposed technique can effectively improve energy efficiency,without sacrificing travel efficiency,comfort,safety and lane-changing performance in different traffic flow states.Originality/value–In light of the aforementioned discussion,the contributions of this paper are two-fold.An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs.A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.