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- Disposal (1)
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Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a general reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
The container of high-level radioactive waste (HLRW) being in deep geological disposal, the backfill material is needed to serve as the second defense for HLRW and the highly compacted bentonite is generally selected. As the time goes, the underground water will infiltrate the backfill, causing the corrosion of materials for the building of containers in the formed electrolyte. Carbon steel, titanium and its alloy are the potential candidate materials for the fabrication of HLRW containers.
The current investigation aims at assessing the safety of HLRW container in deep geological disposal for hundreds of thousands of years and facilitating the material selection for future Container fabrication by estimating their corrosion behavior in compacted bentonite with a series of moisture content at different temperatures through electrochemical methods including open circuit potential (OCP), electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curve (PC) measurements. The corrosion rates were estimated for a carbon steel, a pure titanium and a titanium alloy in compacted Gaomiaozi Bentonite infiltrated with simulated underground water in Beishan area of China over an expected disposal period up to 106 years respectively, showing that titanium and its alloy are more reliable materials for building HLRW containers than carbon steel.
Industrial fires and explosions initiating from self-ignition of combustible porous dust deposits represent a serious hazard for human beings, environment and industry. Understanding the fundamental basis of combustible dust ignition behaviours at different geometries is of importance to prevent and mitigate the accidental risks. A correlation of self-ignition temperatures (SITs) measured by hot-oven tests and minimum ignition temperatures of dust layers (MITLs) determined by hot-plate tests has been established previously. However, this analogy approach based on Frank-Kamenetzkii model is limited by ignoring the influence of oxygen diffusion. In this work, an improved method is developed by implementing a correction factor for the pre-exponential factor caused by the boundary geometry. This method is testified by comparing with experimental data, previous analogy method and numerical simulation. Results show that our proposed method performs a better predictability of MITLs and simplicity. The improved analogy method indicates that the different boundary geometries of a dust deposit significantly impact the apparent pre-exponential factor, while have an ignorable influence on the activation energy, which is also verified by numerical investigations. Furthermore, the numerical model with the corrected kinetic parameters provides a satisfactory explanation compared with experimental observations regarding to temperature and concentration evolutions of dust layers.