In the 1980s, studying the effect of neutron irradiation and temper embrittlement on structural materials for the fusion and fission programmes was a major challenge. In this context the development of small specimen test techniques began, allowing the characterization of structural materials for nuclear applications with small amounts of material. The small punch technique is of one these small specimen test approaches. It is widely used for the development and monitoring of structural materials, however there is currently no comprehensive international standard for small punch testing. An EN standard on small punch testing is currently being developed under the auspices of ECISS/TC101/WG1. Besides describing the apparatus, procedures, and specimens, it will include recommendations for the estimation of tensile, fracture and creep properties from small punch testing as well as machine readable formats for representing and transferring test data. This paper describes the current status of the standard and highlights some of the changes with regard to the current CWA 15672 (2007).

A model that describes creep behavior is essential in the design or life assessment of components and systems that operate at high temperatures. Using the RCC-MRx data and the LCSP (logistic creep strain prediction) model, processed design data were generated over the whole creep regime of 316L(N) steel—i.e., primary, secondary, and tertiary creep. The processed design data were used to develop three models with different approaches for the creep rate: a phenomenological approach; an artificial neural network; and an artificial intelligence method based on symbolic regression and genetic programming. It was shown that all three models are capable of describing the true creep rate as a function of true creep strain and true stress over a wide range of engineering stresses and temperatures without the need of additional micro-structural information. Furthermore, the results of finite element simulations reproduce the trends of experimental data from the literature.

NiMH batteries are the most used technology of rechargeable batteries sold directly to consumers. Herein, we study the performance of the most common sizes of portable NiMH batteries (AA, AAA, D, C, and 9V). The performance and durability parameters—capacity, charge retention, charge recovery, and endurance in cycles—are measured for these types of batteries, according to the standard IEC 61951-2:2017 NiMH batteries. The purpose of this study is to create a basis for setting minimum performance requirements for the parameters in the European Regulation concerning batteries and waste batteries, EU 2023/1542, Annex III, Part B. Results show that the charging time of 16 h could be reduced to 8 h for verifying the rated capacity. The performance of commercial batteries with regard to charge retention, charge recovery, and endurance in cycles is often found to be 25–30% better than required in the relevant IEC standard. Furthermore, we present a short comparative analysis of an application test (IEC 60086-2:2021 “toy”) for portable NiMH batteries with primary batteries. Such data allow comparing the performance of portable NiMH batteries compared to primary batteries in the application test “toy”.

A substantial amount of research effort has been applied to the field of environmentally assisted fatigue (EAF) due to the requirement to account for the EAF behaviour of metals for existing and new build nuclear power plants. We present the results of the European project INcreasing Safety in NPPs by Covering Gaps in Environmental Fatigue Assessment (INCEFA-PLUS), during which the sensitivities of strain range, environment, surface roughness, mean strain and hold times, as well as their interactions on the fatigue life of austenitic steels has been characterized. The project included a test campaign, during which more than 250 fatigue tests were performed. The tests did not reveal a significant effect of mean strain or hold time on fatigue life. An empirical model describing the fatigue life as a function of strain rate, environment and surface roughness is developed. There is evidence for statistically significant interaction effects between surface roughness and the environment, as well as between surface roughness and strain range. However, their impact on fatigue life is so small that they are not practically relevant and can in most cases be neglected. Reducing the environmental impact on fatigue life by modifying the temperature or strain rate leads to an increase of the fatigue life in agreement with predictions based on NUREG/CR-6909. A limited sub-programme on the sensitivity of hold times at elevated temperature at zero force conditions and at elevated temperature did not show the beneficial effect on fatigue life found in another study.

The mean stress effect on the fatigue life of 304L austenitic steel was evaluated at 300 °C in air and pressurized water reactor (PWR) environments. Uniaxial tests were performed in strain-control and load-control modes, with zero mean stress and a positive mean stress of 50 MPa. A specific procedure was used for the strain-controlled experiments to maintain the strain amplitude and mean stress constant. The strain-controlled data indicate that the application of positive mean stress decreases the fatigue life for a given strain amplitude in air and PWR environments. The data also show that the life reduction is independent of the environments, suggesting that no synergistic effects between the mean stress and the LWR environment occur. The load-controlled experiments confirm that the application of positive mean stress increases fatigue due to cyclic hardening processes. This observation is much less pronounced in the PWR environment. All data were analyzed using the Smith–Watson–Topper (SWT) stress–strain function, which was shown to correlate well with all strain- and load-controlled data with and without mean stress in each environment. In the SWT–life curve representation, the life reduction in the PWR environment was found fully consistent with the NUREG-CR6909 predictions.