Chemical sulphate corrosion on cement composites in various model environments

Background: Cementitious composites, which are subject to increasing demands, are often exposed to various external attacks, such as aggressive groundwater and surface water, chemicals in the soil, gas penetration, or phenomena related to water freezing and melting. One of the most common reasons for the deterioration of cement composites is the corrosion process. Corrosion results in irreversible damage that occurs during the chemical reaction of the material with the components of the environment. Methods: The paper deals with experimental study of chemical sulphate corrosion of cement composites prepared from three types of cement: ordinary Portland cement; sulphate-resistant cement; and special hybrid cement, and industrial by-products and wastes: silica fume, zeolite and a special mineral admixture based on blast furnace granular slag as cement partial substitutes. Samples of cement composites were subjected to corrosion experiments in a sulphate environment, which took place in the laboratory under model conditions for 180 resp. 270 days. Results: The deterioration parameters: changes in the weight and thickness of the samples, surface and mineralogical changes, leachability of the basic components of the cement matrix as well as changes in the liquid phase proved the degradation process due to chemical sulphate corrosion, model solutions of H2SO4 with pH 3 and 4, and solution of MgSO4 with c (SO4 2 - ) = 3 and 10 g /L. Conclusion: By comparing the leachability of the alkali components from cement composites, it can be concluded that for the most aggressive model solution (H2SO4 with pH 3), both slagcontaining formulations are the most stable in terms of the total ratio of leached calcium and silicon. This finding is also supported by the results of water absorbency tests, which confirmed that despite the increase in absorbency after chemical corrosion, cement composites with slag content reach the lowest values.

The Influence of Wedge Body Surface Relief on Quality Indicators of Pulse Variable Transmission

In this paper, we research the relief of surfaces of wedge bodies of freewheeling mechanisms. The results obtained by scanning probe microscope let us correct predicted deterioration parameters of a wedge body and consider the effect of surfaces’ altitude quality indicators while designing mechanisms. Mark out relative area of bearing.

Application of TRIZ and Universal Design in the Design of Pressure Sensing Pacifier

This study proposed an innovative design of pressuresensing pacifier to solve the problem of lack of sucking ability of newborninfants or premature infants, as well as the problem of caregivers lacking inthe knowledge of when to feed the infants. TRIZ was adopted as the researchmethod. The modification and deterioration parameters of contradiction matrixwere used to identify the invention principles for systematic innovationdesign. Moreover, the seven techniques of the universal design were used toapply the proposed pressure sensing pacifier on infants. The pressure of thepressure sensing pacifier was in the range from -50 to -75mmHg. Bymodifications of these data, the infants are allowed to receive better care.This study also designed a set of pressure sensing device for clinical medicalpersonnel and researchers to measure the sucking ability of premature infants.The objective assessment tool is expected to help medical personnel to masterthe development stage of the sucking ability of premature infants to identifythe best feeding opportunity.

Particle Filter Approach for IGBT Remaining Useful Life

With the increasingly widespread application, the requirement for PHM of IGBT is becoming gradually urgent. Based on particle filter theory, a method for remaining useful life (RUL) prediction of IGBT is proposed. Firstly, the deterioration parameters on-state VCE and ICE are extracted by temperature cycling test, then a model is developed based on the degradation trend exhibited by deterioration parameters. In the end, PF approach is applied to the IGBT's RUL prediction with the mentioned model. The results show that the proposed prediction method can achieve high prediction accuracy.

Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures, I: Methodology

The state-of-the-practice in seismic network reliability assessment of highway bridges often ignores bridge failure correlations imposed by factors such as the network topology, construction methods, and present-day condition of bridges, among others. Additionally, aging bridge seismic fragilities are typically determined simply using historical estimates of deterioration parameters. This research presents a methodology to estimate bridge fragilities using spatially interpolated and updated deterioration parameters from a limited set of instrumented bridges in the network, while incorporating the impacts of overlooked correlation factors in bridge fragility estimates. Simulated samples of correlated bridge failures are used in an enhanced Monte Carlo method to assess bridge network reliability, and the impact of different correlation structures on the network reliability is discussed. The presented methodology aims to provide more realistic estimates of seismic reliability of aging transportation networks and to potentially help network stakeholders to more accurately identify critical bridges for maintenance and retrofit prioritization.

Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures, II: Application

The bridge reliability in networks (BRAN) methodology introduced in the companion paper is applied to evaluate the reliability of part of the highway bridge network in South Carolina under a selected seismic scenario. The case study demonstrates Bayesian updating of deterioration parameters across bridges after spatial interpolation of data acquired from limited instrumented bridges. The updated deterioration parameters inform aging bridge seismic fragility curves through multi-dimensional integration of parameterized fragility models, which are utilized to derive bridge failure probabilities. The paper establishes the correlation structure among bridge failures from three information sources to generate realizations of bridge failures for network-level reliability assessments by Monte Carlo analysis. Positive correlations improve the reliability of the case study network, as predicted from network topology. The benefits of the BRAN methodology are highlighted in its applicability to large networks, while addressing some of the existing gaps in bridge network reliability and prioritization studies.