Focused ion beam (FIB) microscopy, in combination with scanning electron microscopy (SEM) has been used to characterise the porosity through the oxide scale of an experimental martensitic 9Cr-1Mo steel exposed for 3325 h to a CO2-rich environment at 600 °C. A typical magnetite outer layer forms with a small fraction of spherical pores, but no interconnectivity between them. A complex mixed middle layer is observed which consists of larger magnetite grains, smaller spinel grains and some pore interconnectivity, but typically the porosity is present in localised regions, inhibited from coalescence by the different grain types. A spinel layer also shows greater pore interconnectivity with three large pores spanning the total distance through this layer, but no single pore spans the total oxide scale thickness. A mechanism linking the substrate microstructure to the variation in oxide structure between ferritic and martensitic material is proposed which explains the formation of the magnetite, the complex oxide and spinel oxide layers.
Determining creep-fatigue damage formation is critical for elevated temperature components integrity. This study evaluates creep-fatigue assessments with emphasis on differences between creep damage models. Evaluated are the time-fraction model and the classical and stress-modified ductility exhaustion creep damage models. This work extends the domain of stress-modified ductility exhaustion models by introducing and validating such formalism to Ni-based alloys. The fidelity of the assessments was benchmarked against uniaxial creep-fatigue and multiaxial feature tests of Alloy 617. For uniaxial specimens, best estimate predictions rank ductility exhaustion as the most accurate and precise and time-fraction as markedly conservative. For feature tests, ductility exhaustion predictions are within < 4.0 times difference, whereas time-fraction underpredicts life by factors of 7-14. The observations suggest ductility exhaustion models as alternative to time-fraction models in design codes for situations requiring characterization of the design margin. Further work in employing such models to assess other relevant phenomena (e.g., stress relaxation cracking) is discussed.
BUTTON-30 is a neutrino detector demonstrator located in the STFC Boulby underground facility in the north-east of England. The main goal of the project is to deploy and test the performance of the gadolinium-loaded water-based liquid scintillator for neutrino detection in an underground environment. This will pave the way for a future large-volume neutrino observatory that can also perform remote monitoring of nuclear reactors for nonproliferation. This paper describes the design and construction of the watertight optical modules of the experiment.
This study demonstrates how surface preparation and mechanical loading affect oxidation and carburisation in 316 H stainless steel exposed to CO/CO2 environments. OPS-polished surfaces exhibited the greatest susceptibility, forming thick duplex oxides that enabled carbon ingress and substantial hardening, particularly under creep at 350 MPa. The permeability of the duplex oxide allowed carbon to accumulate at the metal-oxide interface, where dislocation activity introduced by pre-straining and sustained creep facilitated transport; under creep, continued dislocation motion enabled deeper subsurface penetration compared with pre-strained specimens. In contrast, 600-grit ground surfaces initially formed a thin chromia film and, when this film was disrupted, developed a discontinuous duplex oxide. The associated near-surface deformation and high dislocation density are proposed to promote local trapping of carbon close to the interface; once the--1-2 mu m ultrafine-grained layer (UFGL) is consumed, carbon diffusion into the bulk proceeds more slowly, such that only very limited carburisation is observed even under creep. Overall, the results highlight that dislocation activity and loading history govern both oxidation behaviour and the extent of carbon ingress.
Probabilistic Seismic Hazard Analysis (PSHA) is the standard methodology for estimating the likelihood of exceeding ground-motion intensity thresholds at a given site, accounting for both aleatory and epistemic uncertainties, yet remains subject to criticism due to the high uncertainty and the limited observational data for validation. This study proposes a novel framework for the direct evaluation and Bayesian updating of PSHA logic-tree weights using observed ground-motion records, explicitly addressing spatial correlation among multiple observation sites. The methodology combines event-based simulations of branch-consistent ground-motion fields, site-effect corrections, and operational-period modeling to ensure comparability with empirical data. Correlated exceedance counts are modeled using the Pólya (negative binomial) distribution, which preserves the expected total number of exceedances of the classical Poisson reference while capturing the variance inflation induced by spatial dependence. At the same time, joint multi-IML updating employs a Bernstein copula to represent dependence across intensity measure levels. The framework is applied to a PSHA model for metropolitan France using a reference database spanning 1977–2020 and comprising EDF industrial sites and EPOS-France stations. Results confirm the adequacy of the Pólya distribution for correlated exceedance modeling, with spatial correlation observed consistently at monthly resolution. EDF sites provide nearly the same effective observation time as the full network due to their wide spatial distribution, while EPOS-France stations contribute limited additional statistical power due to site clustering. Bayesian updating of logic-tree branch weights improves model consistency, particularly when applied jointly across multiple IMLs. Results highlight systematic overestimation at low thresholds, and sensitivity analyses reveal that station operability uncertainties, while influential, cannot fully account for the discrepancy between predicted and observed exceedances. A fundamental contributing factor is that observations reflect a non-ergodic, site- and path-specific reality, whereas simulated fields are at best site-specific approximations—a mismatch inherent to current PSHA practice that sets an irreducible limit on model-data agreement. This correlation-aware, multi-IML evaluation framework enhances the statistical robustness of PSHA validation and provides a principled approach for data-informed logic-tree weighting, offering clear pathways for methodological refinement and regulatory application.
