Relation between Modulus of Elasticity and Compressive Strength of Ultrahigh-Strength Mortar with Mixed Silicon Carbide as Fine Aggregate

Ultrahigh-strength mortar mixed surface-oxidized silicon carbide as a fine aggregate was prepared by means of press-casting followed by curing in an autoclave. The relation between modulus of elssticity up to 111 GPa and compressive strength up to 360 MPa of mortar mixed silicon carbide was discussed and it was revealed that the contributions of the aggregate hardness and of the interfacial strength between the aggregate and the cement paste on the elasticity of mortar were imporant.

Foaming biocompatible and biodegradable PBAT/PLGA as fallopian tube stent using supercritical carbon dioxide

Tubal pregnancy is a common abnormal pregnancy manifestation,and the ordinary conservative treatment of tubal adhesion usually leads to the rupture of fallopian tube,which increases the risk of a second ectopic pregnancy.To avoid this symptom,it is suitable to implant a stent to separate the adhesion.Here we prepared the PBAT/PLGA foam as the stent material using supercritical CO_(2) foaming technology.With uniform macroporous structure and thin-wall feature,the foam possessed low compressive modulus in prevention of the possible second injury to the fallopian tube.The introduction of PLGA 50/50 improved the biodegradable capability of the foam,with a mass loss about 20% after a 12-week hydrolysis.After implanted into the ruptured fallopian tube of the rabbit model,the foam displayed excellent biocompatibility,and provided a good support to prevent tubal adhesion.As such,this work provides the foam material as a promising candidate for fallopian tube stent to remedy the tubal adhesion.

Simulation of thermal stress in Er2O3 and Al2O3 tritium penetration barriers by finite-element analysis

The physical vapor deposition method is an effective way to deposit Al2O3 and Er2O3 on 316 L stainless steel substrates acting as tritium permeation barriers in a fusion reactor. The distribution of residual thermal stress is calculated both in Al2O3 and Er2O3 coating systems with planar and rough substrates using finite element analysis. The parameters influencing the thermal stress in the sputter process are analyzed, such as coating and substrate properties, temperature and Young＇s modulus. This work shows that the thermal stress in Al2O3 and Er2O3 coating systems exhibit a linear relationship with substrate thickness, temperature and Young＇s modulus.However, this relationship is inversed with coating thickness. In addition, the rough substrate surface can increase the thermal stress in the process of coating deposition. The adhesive strength between the coating and the substrate is evaluated by the shear stress. Due to the higher compressive shear stress, the Al2O3 coating has a better adhesive strength with a 316 L stainless steel substrate than the Er2O3 coating. Furthermore, the analysis shows that it is a useful way to improve adhesive strength with increasing interface roughness.

Mechanics Model to Determine Swelling Potential of Expansive Soils

The factors influencing on soil expansion are reviewed in the paper. A mechanics model to determine swelling potential of expansive soils is presented. The mechanics model is based on the softening of expansive soil following absorption of water. The constitutive relationships of the mechanics model include the relationship among swelling under free load, swelling under load, and vertical pressure, and the relationship of swelling under free loading and swelling pressure. A concept of additional compression modulus is introduced and the method determining the modulus is proposed. Finally, the predicted results of swelling potential using the mechanics model compare well with the measured data.

Selection of regression models for predicting strength and deformability properties of rocks using GA

Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.

Mechanical properties of cement mortar in sodium sulfate and sodium chloride solutions

To investigate the mechanical properties of cement mortar in sodium sulfate and sodium chloride solutions, uniaxial compression test and ultrasonic test were performed. Test results show that the relative dynamic elastic modulus, the mass variation,and the compressive strength of cement mortar increase first, and then decrease with increasing erosion time in sodium sulfate and sodium chloride solutions. The relative dynamic elastic moduli and the compressive strengths of cement mortars with water/cement ratios of 0.55 and 0.65 in sodium sulfate solution are lower than those in sodium chloride solution with the same concentration at the420 th day of immersion. The compressive strength of cement mortar with water/cement ratio of 0.65 is more sensitive to strain rate than that with water/cement ratio of 0.55. In addition, the strain-rate sensitivity of compressive strength of cement mortar will increase under attacks of sodium sulfate or sodium chloride solution.

Unreacted equation of states of typical energetic materials under static compression:A review

The unreacted equation of state（EOS） of energetic materials is an important thermodynamic relationship to characterize their high pressure behaviors and has practical importance. The previous experimental and theoretical works on the equation of state of several energetic materials including nitromethane, 1,3,5-trinitrohexahydro-1,3,5-triazine（RDX）,1,3,5,7-tetranitro-1,3,5,7-tetrazacyclooctane（HMX）, hexanitrostilbene（HNS）, hexanitrohexaazaisowurtzitane（HNIW or CL-20）, pentaerythritol tetranitrate（PETN）, 2,6-diamino-3,5-dinitropyrazine-1-oxide（LLM-105）, triamino-trinitrobenzene（TATB）, 1,1-diamino-2,2-dinitroethene（DADNE or FOX-7）, and trinitrotoluene（TNT） are reviewed in this paper. The EOS determined from hydrostatic and non-hydrostatic compressions are discussed and compared. The theoretical results based on ab initio calculations are summarized and compared with the experimental data.

Settlement prediction and behaviour of pile foundations in deep clayey soil deposits

A new measurement technique is used to determine the settlement of bridge pile foundation and the thickness of deep compressed soft layer. The finite element Plaxis 3D foundation program is used in the analysis with a proposed empirical equation to modify the input parameters represented by the soil compression modulus. The results of the numerical analysis using the proposed empirical equation provide insight to the settlement analysis of pile groups in soft clayey soils; consequently, the finite element Plaxis 3D program can be a useful tool for numerical analysis. The numerical analysis is modified by adjusting the calculation of compression modulus from those obtained under pressure between 100-200 kPa by which the results of the settlement are modified and thus matching the realistic measurements. The absolute error is 3 mm which is accepted compared with the last researches. This scenario can be applied for the similar problems in the theoretical applications of deep foundations.

Influence of Freeze-thaw Cycles on Properties of Integral Water Repellent Concrete

Service life of reinforced concrete structures usually was designed on the basis of one selected deteriorating mechanism as for instance carbonation,chloride penetration,and frost action.It could be shown in the meantime by numerous authors,however,that combined actions such as chloride penetration under mechanical load or chloride penetration in combination with freeze-thaw cycles may shorten the service life of reinforced concrete structures more than individual processes acting alone.We have found that chloride penetration is accelerated significantly by freeze-thaw cycles.Frost damage not only reduces mechanical strength and elastic modulus but migration of chloride is facilitated in the damaged pore structure.Chloride penetration can be retarded by the addition of silane emulsion to the fresh concrete.In this way Integral Water Repellent Concrete（IWRC） can be produced.Migration of water and ions dissolved in water can not be prevented by integral water repellent treatment but it is slowed down.The combination of damage mechanisms and the protective measures by integral water repellent treatment have to be taken into consideration in realistic service life prediction and design.

Corrugated Graphene Paper Reinforced Silicone Resin Composite for Efficient Interface Thermal Management

With the rapid development of high-power-density electronic devices,interface thermal resistance has become a critical barrier for effective heat management in high-performance electronic products.Therefore,there is an urgent demand for advanced thermal interface materials(TIMs)with high cross-plane thermal conductivity and excellent compressibility to withstand increasingly complex operating conditions.To achieve this aim,a promising strategy involves vertically arranging highly thermoconductive graphene on polymers.However,with the currently available methods,achieving a balance between low interfacial thermal resistance,bidirectional high thermal conductivity,and large-scale production is challenging.Herein,we prepared a graphene framework with continuous filler structures in in-plane and cross-plane directions by bonding corrugated graphene to planar graphene paper.The interface interaction between the graphene paper framework and polymer matrix was enhanced via surface functionalization to reduce the interface thermal resistance.The resulting three-dimensional thermal framework endows the polymer composite material with a cross-plane thermal conductivity of 14.4 W·m^(-1)·K^(-1)and in-plane thermal conductivity of 130W·m^(-1)·K^(-1)when the thermal filler loading is 10.1 wt%,with a thermal conductivity enhancement per 1 wt%filler loading of 831%,outperforming various graphene structures as fillers.Given its high thermal conductivity,low contact thermal resistance,and low compressive modulus,the developed highly thermoconductive composite material demonstrates superior performance in TIM testing compared with TFLEX-700,an advanced commercial TIM,effectively solving the interfacial heat transfer issues in electronic systems.This novel filler structure framework also provides a solution for achieving a balance between efficient thermal management and ease of processing.

Machine learning-based prediction of soil compression modulus with application of ID settlement

The compression modulus(Es)is one of the most significant soil parameters that affects the compressive deformation of geotechnical systems,such as foundations.However,it is difficult and sometime costly to obtain this parameter in engineering practice.In this study,we aimed to develop a non-parametric ensemble artificial intelligence(AI)approach to calculate the Es of soft clay in contrast to the traditional regression models proposed in previous studies.A gradient boosted regression tree(GBRT)algorithm was used to discern the non-linear pattern between input variables and the target response,while a genetic algorithm(GA)was adopted for tuning the GBRT model's hyper-parameters.The model was tested through 10-fold cross validation.A dataset of 221 samples from 65 engineering survey reports from Shanghai infrastructure projects was constructed to evaluate the accuracy of the new model5 s predictions.The mean squared error and correlation coefficient of the optimum GBRT model applied to the testing set were 0.13 and 0.91,respectively,indicating that the proposed machine learning(ML)model has great potential to improve the prediction of Es for soft clay.A comparison of the performance of empirical formulas and the proposed ML method for predicting foundation settlement indicated the rationality of the proposed ML model and its applicability to the compressive deformation of geotechnical systems.This model,however,cannot be directly applied to the prediction of Es in other sites due to its site specificity.This problem can be solved by retraining the model using local data.This study provides a useful reference for future multi-parameter prediction of soil behavior.

Effect of formulation of alginate beads on their mechanical behavior and stiffness

The aim of this work was to determine the effect of formulation of alginate beads on their mechanical behavior and stiffness when compressed at high speed. The alginate beads were formulated using different types and concentrations of alginate and gelling cations and were produced using an extrusiondripping method, Single wet beads were compressed at a speed of 40 mm/min, and their elastic limits were investigated, and the corresponding force versus displacement data were obtained. The Young＇s moduli of the beads were determined from the force versus displacement data using the Hertz＇s contact mechanics theory. The alginate beads were found to exhibit plastic behavior when they were compressed beyond 50% with the exception of copper-alginate beads for which yield occured at lower deformation, Alginate beads made of higher guluronic acid contents and gelling cations of higher chemical affinity were found to have greater stiffness. Increasing the concentration of alginate and gelling ions also generated a similar effect. At such a compression speed, the values of Young＇s modulus of the beads were found to be in the range between 250 and 900 kPa depending on the bead formulation.

Compressibility and Structural Properties of Jadeite, NaAlSi_2O_6 at High Pressure

The structural properties of jadeite at high pressures （0.000 1-30 GPa） are investigated using plane-wave pseudopotential density functional theory method. As a function of pressure, the monoclinic cell parameters were calculated and the compressibility coefficients are 0.002 6, 0.002 3 and 0.002 6 GPal, respectively. The bond length, bond angle and distortion variation were studied in order to obtain the information of polyhedral compression. The pressure-volume equation of state was con- sidered in order to obtain the bulk modulus K0. Comparison between the calculated K0 values and the experimental data suggested that the model provides reasonable insights into crystallographic and physical properties of jadeite.