Abstract:In common design of long span bridges, dead load on outer piers was much smaller than that on inner piers. As a result, under seismic excitation, energy dissipation for friction pendulum bearings on outer piers was not effective. In this regard, a new transversal isolation system consisting of a hysteretic damper and sliding bearing was proposed. After that, the effectivity of this system was validated by a modern steel trussed arch bridge using fragility function. Displacement of sliding bearings, bending moment of outer piers and stress on the arch springing were taken as the engineering demand parameters. Cloud method was applied to build the probabilistic demand seismic model. The generated fragility curves show that the proposed transversal isolation system performs quite well under potential earthquakes.

Abstract:In order to check the performance of the new type of composite bridge deck proposed in this paper under the wheel load and its performance in the second system of the bridge deck, also to compare it with the performance of the normal bridge deck, 4 different types of bridge deck are designed and fabricated, one is concrete bridge deck, one is orthotropic steel bridge deck, and the other two are composite bridge decks with concrete slab and orthotropic steel plate with Tshape stiffener in different sizes. Static load test is conducted on these specimens to shed light on the cracking of concrete in the negative moment zone and measure the deformation and the strains in different locations on the decks. The result proves that the local stress level of the composite bridge deck is less than that of the orthotropic steel bridge deck, the loadcarrying capacity of the composite bridge deck in unit width is at least 2.36 and 1.57 times as many as that of the concrete deck and orthotropic steel plate deck, respectively, which, further validate that the composite bridge deck proposed in this paper has a higher fatigue strength.

Abstract:In this paper, based on the equivalent uniaxial stressstrain relationship for concretefilled Tshaped steel tube (CFTST) column without stiffening measures, a fiber element model computing program was adopted to investigate the effects of different parameters on the sectional strength of CFTST column under uniaxial eccentric load or biaxial eccentric load. The parameters in the analysis included the yield strength of steel, the compressive strength of concrete, the depth to thickness ratio of steel plate, the depth to width ratio of the sectional limb, the angle of the load and the axial load ratio. The results of theoretical analysis indicated that, the normalized strength interaction curve of axial load versus bending moment was obviously influenced by the load ratio carried by core concrete and the load angle; The normalized strength interaction curve of biaxial bending moments was distinctly influenced by the depth to width ratio of the sectional limb and the axial load ratio. On the assumption of full plastic stress distribution and the parametric regression analyses of a good many of numerical results, the simplified calculation methods were put forward to predict the sectional strength under uniaxial eccentric load or biaxial eccentric load. Good agreements between the values calculated by the simplified calculation methods and the values predicted by the fiber element model computing program were achieved, and the simplified calculation methods can be referred for practical engineering design.

Abstract:For the more accurate calculation of thermal strain, the change law of the thermal expansion coefficient of early concrete is studied. The change law of early concrete temperature and strain is obtained through the experiment. At the same time, the user subroutine, which to calculate concrete temperature and strain considering hydration degree theory, has been developed based on ABAQUS secondary development platform. And on this basis, The change models of different thermal expansion coefficients are used to simulate the experiment. The numerical simulation results show that simulation results with different thermal expansion coefficient change models are not the same. While the exponential decline change model of the thermal expansion coefficient fits the experimental results better.

Abstract:Taking the original triaxial test data as the basis, this study analyzed the relationship between the tangential modulus, or the tangent bulk ratio and the stress state. The corresponding relational expression were proposed, respectively. Then, the two new expressions were introduced into Shen’s elastoplastic model with double yield surfaces to replace the old ones. The triaxial simulated results of rockfill materials showed that the modified model can overcome the disadvantages of using the damage stress ratio to control the final strength, especially the inadequate characteristics of shear dilatation (contraction). And the simulated results of different stresspath triaxial tests confirmed the new model can well simulate the strength and deformation characteristics of rockfill.

Abstract:Through the passenger behavior survey of public transport corridor in Shanghai, this paper proposes a revealed preference/stated preference (RP/SP) combined Nested Logit model. Based upon the discrete choice theory, the proposed model analyzes qualitatively and quantitatively the travel behavior of differentregional passengers and some factors which influence their behavior. And then the paper researches the spatial transferability of this model. Finally, the model aims to simulate the travel behavior of differentregional passengers upon different policy scenarios. The results shows that in urban public transportation corridor, the factors which influence passenger travel behavior are different because they come from different regions. Secondly, for differentregional passengers, their preference of public mode may also be different. Thirdly, there are differences among the sensibilities of differentregional passengers to some factors which influence their travel behavior. Relying on data collection, modeling, parameter calibration and simulation, the paper provides a method of analyzing travel behavior for differentregional passengers, which may be a useful tool for function optimization and efficiency enhancement of urban public transport corridor.

Abstract:Based on the historic data from Hillsborough County, Florida, U.S., the zonelevel factors including crashes counts, road network, traffic pattern, and various social economic factors were explicitly collected for four different zoning schemes, i.e. block groups, traffic analysis zones, census tracts, and zone improvement plan codes. Then, a Bayesian negative binomial model with conditional autoregressive prior was developed for each spatial units, respectively. The impacts of zonal variations on macrolevel safety modeling were investigated mainly from three aspects, i.e. model performance, model parameter estimates, as well as crash hotspots identification. Results revealed that statistical results based on different aggregation configurations could be significantly different. Zoning schemes with less number of zones tend to have higher crash prediction precision. Compared with block groups, census tracts, and zone improvement plan codes, traffic analysis zones level model preforms worst in terms of model goodness of fit. The variable of median household income shows consistently significant effects on crash frequency and is robust to variation in data aggregation.

Abstract:This paper presents a roadside landscapes evaluation model (RLEM) based on big website data about web hotspots, such as web searching data, web checkin data and web voting data. Then, Road beauty degree(RBD) is calculated by the proposed RLEM and the roadside landscapes’ visual ranges along road. Finally, the most beautiful route planning algorithm is designed and realized based on road networks RBD. An experiment was applied in Wuhan (China), where twentyeight landscapes were measured by RLEM, and the road networks RBD were calculated. Comparing between the proposed model and the traditional shortest path model, the results show us that routes planned by the proposed method have higher RBD than the routes planned by the traditional shortest method.

Abstract:In this paper, the polycarboxylate superplasticizers (PCE) were synthesized with allyl polyethylene glycol (APEG) and maleic anhydride diethylene glycol butyl ether monoester (MADGBE) as main raw materials using the method of bulk polymerization. And the influence of the ratio of monomer, the polymerization temperature and the mode of adding polymerization initiator on the performance of polycarboxylate superplasticizers were investigated. The results showed that the synthesized PCE, under the optimum polymerization conditions: the ratio of MADGBE and APEG is 3.5∶1, the polymerization temperature is 90 ℃ and the polymerization initiator is added in three times equally, performs excellent slumpmaintaining and shrinkagereducing. But the PCE extended the setting time of concrete. At the last, the molecular structure of the PCE was characterized using Fourier transform infrared spectromet (FTIR) analysis.

Abstract:By using small ball mill as the shaping source, the change of basic characteristics of coarse aggregate after particle shaping was studied and correlation analysis was conducted between the aggregate characteristics and its application performance. The results show that according to the change of the coarse aggregate particles, the shaping process is divided into three stages: transformation stage of elongated and flaky particles, roundness improve stage and particle crushing stage. Appropriate particle shaping process can make the aggregate use in the concrete to increase significantly the flowability of concrete and not to reduce the strength, but excessive shaping will be harmful to the flowability and strength. In the early stage of the particle shaping, packing density increasing caused by needle flake transformation is the key parameters affecting the concrete flowability. In the latter particle shaping process, roundness of coarse aggregate is the main factors influencing the concrete flowability. As a comprehensive parameter to evaluate the friction between the coarse aggregate particles, angle of repose of aggregate particles has high correlation with the flowability of concrete.

Abstract:A half car model with four degrees of freedom is built, and the sliding mode control theory is applied to prevent vehicle rollover which using magnetorheological fluid dampers as their actuators. Based on the study of stable area on sideslip angle phase portraits, the control algorithm of electronic stability control (ESC) system is set up. Considering the rollover index, the integrated control algorithm with semiactive suspension and ESC is designed. The algorithm is verified by simulation with doublelane change maneuver and fish hook test, and the simulation results indicate that the integrated control algorithm can improve vehicle handling stability and decrease roll angle, which reduces the danger of rollover efficiently

Abstract:The article designed a fault diagnosis algorithm based on analytic model to achieve the selfdiagnosis function of sensors signals. Firstly the article established the fundamental frame, Then two fault diagnosis algorithms were designed based on parity equations and observer. Parity equation algorithm was designed by linear vehicle model and kinematic equations which show the relations among the different key sensors signals of vehicle stability control system, and was used for them to diagnose each other. Observer algorithm was designed by nonlinear vehicle model to obtain fault information by Dragon Berger observer. Considering sensitivity and false warning rate, the fusion of the two algorithms were proposed to improve diagnosis effect, and the diagnosis rules were also reset. Finally, the fault diagnosis algorithm was testified through several kinds of onroad tests with different working conditions. The results showed that the algorithm can provide accurate different types fault information of different sensors as well as the fault degree.

Abstract:Frictional brake groan is selfexcited lowfrequency structural vibration and associated airborne noise, which has obvious intermittent and impulsive characterizations. Hence, a comprehensive literature survey on brake groan is conducted from the aspects of experimental studies, generation mechanisms and related theories, modeling and simulation analysis. These researchs'results suggest that in order to study the mechanism of brake groan and restrain it, the focus of the following researches should be taking the multidimension in space motion of the brake system and suspension system into consideration.

Abstract:In order to quickly optimize a passenger vehicle’s interior stationary noise samples’ sound distraction levels with active noise equalization, the traditional enumeration method used to search for optimal gain coefficient vector of active noise equalization system and to optimize sound quality was analyzed; subjective evaluation was used to evaluate the distraction levels of the passenger vehicle’s interior stationary noise samples within 20500 Hz; Back Propagation (BP) neural network using the barks’ total sound pressure linear amplitudes within 20500 Hz as inputs was used to fit the noise samples’ sound distraction levels; the trained BP neural network’s weights were used to deduce the network’s inputs’ sensitivities and contributions to the sound distraction levels; an equation was deduced to predict the total sound pressure linear amplitude of a bark after active noise equalization with a given gain coefficient, the original sound pressure amplitude spectrum and the reference signal of the active equalization system; based on this equation, the sound distraction levels’ sensitivities and contributions, an advance gradient optimization method was designed to search for optimal gain coefficient vector and to optimize sound distraction levels of the noise samples. The time consumption of the optimization process is low. Active noise equalization using the gain coefficient vectors acquired by the advance gradient optimization method was executed and the equalized noise samples’ sound distraction levels were evaluated with subjective evaluation. The result shows good accuracy and the sound distraction levels are improved significantly.

Abstract:In order to monitor tool wear condition（TWC）, the powersensorbased monitoring system on the state of machining tool wear was designed. The monitoring model of TWC was proposed based on principal component analysis（PCA）and Csupport vector machine（CSVM）. Current and power signals were obtained from power sensor during cutting process. After that, the features of these signals were extracted using PCA. The principal components，mainly affecting TWC, were chosen as the input samples of CSVM to carry out monitoring the tool condition with accuracy. The results of computerized numerical control（CNC） turning machine tool show that the model is effective even in the case of a small samples. Moreover, a comparison about the monitoring and prognostics capability between the presented method and back propagation（BP）neural network has been made.

Abstract:In order to analyze the problem of straw shortage from the perspective of farmers, an investigation was conducted. Among the respondents, 59.3% burned the straw, and 82.3% did not sell the straw to any enterprise. Four scenarios with three stubble heights are established. An mathematical model about straw harvesting, collection, transportation, and storage is established. Parameters are selected basing on one biomass power plant in Jiangsu Province. The results show that the cost of straw selling is 186250 CNY?t-1. The machinery collection reduces the total cost finitely. The relation between the labor price and the cost is examined. The labor price affects the manpower collection scenarios more obviously than the machinery collection scenarios. The cost model is made without considering the information problem.

Abstract:This paper presented a new linear regression method where the errors of dependent and independent variables and correlations of errors were adequately captured. The iteration formulae for calculating the regression parameters were derived at the same time. Taking univariate linear regression problem as an example, analytical formulas for linear regression parameters that similar to those from leastsquares method were derived, with which the essential difference between leastsquares method and new method were demonstrated. In addition, for the multiple linear regression that with multiple independent variables, the corresponding method, which considers the errors of both independent and dependent variables and the correlations of errors, for calculating the linear regression parameters were also shown. The experiment results shown that the new method and leastsquares method were equivalent to each other when independent variables were nonrandom; whereas, the regressive parameters from new method were more closer to the true values than those from the leastsquares method when both independent and dependent variables were all random (no matter their errors were correlated or not).

Abstract:Traditional sparse representation based classifiers ignore interconnections among pixels and have high computational complexity when applied in hyperspectral imagery (HSI) field. Therefore, a multiple measurement vectors based sparse representation classifier (MMVSRC) model is proposed to solve the above problems. The model introduces a balance parameter to control the sparsity of coefficient vectors, and estimates sparse coefficient vectors of all testing pixels by minimizing reconstruction errors using the L2norm constraint. Experiments on two HSI datasets are implemented to test the performance of MMVSRC, and the results are compared with those of five stateoftheart classifiers. The results show that MMVSRC achieves best classification accuracies among all whereas taking the second shortest computational time.

Abstract:Based on the algorithm of singledifferencing for short baseline, this paper adopts the rate of phasedifferencing between two antennas as the indicator of cycleslip detection. We estimated the normal range of the rate and examined the effect of clock jump on it. Our theoretical analysis demonstrates that this indicator is able to detect cycleslip effectively. A numerical method for detecting and correcting cycleslip is provided. The experiments with real short baseline data from the clocksynchronized dualantenna receiver show that this method is valid in detecting and repairing the cycle slips, and it is immune to the disturbance of clock jumps.

Abstract:For two given graphs G and H, Ramsey number R(G,H) is the smallest integer N such that any red/blue edgecoloring of KN contains a red copy of G or a blue copy of H. Let a bistar B(m,n) be a tree of diameter three with two central vertices of degree m+1 and n+1, respectively. It is shown that R(B(m,n))<2n+m+2 for n>m; and R(B(m,n))=2m+n+2 for n=m or n=m+1. Key words： Ramsey number; tree; bistar

Abstract:Ramsey number is the smallest integer N such that for any redblue edgecoloring of KN, there is a red subgraph G or a blue subgraph H. In this paper, we use a theorem of Burr and the method of partitioning graphs to prove that if n≥|G|2+2χ(G)α(G), then R(Pn,G)=(χ(G)－1)(n－1)+σ(G).

Abstract:Based on the theory of innovation ecosystem and system dynamics, this paper constructs the model of automotive industry innovation ecosystem. Using the Vensim PLE to optimize the model, with Shanghai automotive industry for example, this paper analyzes the development trend of automotive industry innovation ecosystem, under the different level of government guidance, research and development spending, and industrial investment within a certain range. The results show that: the rank of effects of three indicators from strong to weak is research and development spending, industrial investment, and government guidance. In the early stage of industry development, the industry added value was sensitive with the change of government guidance, but excessive government guidance would cause negative impact. With the improvement of market mechanism, the effect of governance factors will be weak gradually.

Abstract:A thorough review of literature on DesignBuild (DB) and DesignBidBuild (DBB) project cost growth performance comparison indicates that existing studies focus on different types of projects, and most studies build on limited samples of projects. As a result, the conclusions of previous studies are diverse, and no general consensus has been reached on whether DB outperformed DBB in terms of cost growth. This paper employs random effect metaanalysis model to statistically integrate results in previous studies. Based on the integrated large sample, the gap between cost growth in DB and DBB projects is evaluated. The metaanalysis results, verified by the robust tests, show that DB projects achieve significantly lower cost growth on average. Further metaanalyses on different groups of studies reflect that DB system performs worse in public projects but better in unique projects. DBB is more conducive to cost growth control under complex project conditions. Cost growth improvements induced by DB system experienced growth initially, followed by shrinkage afterwards due to policy changes. This reminds clients that PDS should be selected according to specific project conditions. Hence, clients should consider both project conditions and performance history of different PDSs when selecting PDS. Clients may find this paper helpful in supporting their PDS selection decisions.

Abstract:For the three main problems remaining to be solved in the construction process of deep excavation engineering: building a risk index system, distributing the weight of evaluation indexes and evaluating the risk, this article builds a risk evaluation system based on the DS(DempsterShafer) evidence theory combined with interval number theory. Firstly we identify the risk factors by “WBSRBS” and “01” methods to build the risk index system based on the construction principle and management process of deep excavation. In order to decrease the subjectivity of the process of deep excavation risk quantification, then we combine the advantages of interval number theory and DS evidence theory to specify the methods and procedures about how to build identifying framework, choose the reliability function and synthesize information. At last, the rationality and feasibility of the risk evaluation system are manifested by analyzing the example.