For seismic analyses of linear structural systems including soil-structure systems, the current practice (e.g., the U.S. Nuclear Regulatory Commission (NRC) Standard Review Plan (SRP) (NUREG-0800 [1], “Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR Edition”) and American Society of Civil Engineers (ASCE)/Structural Engineering Institute (SEI) Standard 4-16 [2], “Seismic Analysis of Safety-Related Nuclear Structures”) allows for estimating mean seismic responses by using as few as four or five input time histories. This paper examined whether this practice can achieve a stable mean response by explicitly considering the uncertainty in the Fourier phase spectra of the input time histories and exploring how this uncertainty can affect the coefficient of variation (CV) of the in-structure response spectra (ISRS). ISRS are the response spectra of the seismic response time history at a location in the structure subjected to an input seismic time history. We found that the maximum CV ISRS across all frequencies is around 40% purely due to the uncertainty in the Fourier phase spectra for a typical range of design earthquakes for U.S. nuclear power plants. To estimate a mean ISRS within ±10% of the true mean ISRS, our analyses showed that this level of CV ISRS may require a minimum of 16 input time histories for a confidence level (CL) of 68% and 61 for a CL of 95% for soil-structure systems of low fundamental frequencies. For stiffer systems (for example, with a fundamental frequency of 5 hertz (Hz)), the maximum CV ISRS is about 30%, and thus, the minimum required number of input time histories may be reduced to 9 for a CL of 68% and 35 for a CL of 95%. In summary, the four or five time histories in the current practice may not be sufficient for estimating stable mean responses, especially for soil-structure systems with very low frequencies.

Pressure vessel components subject to high temperature and pressure are susceptible to life-limiting creep and/or creep-induced failure. Traditional continuum damage mechanics (CDM) based creep-damage model are used extensively for the prediction and design against creep in these components. Conventional creep experiments show considerable uncertainty in the creep response of materials where scatter can span decades of creep life. The objective of this paper is to introduce the probabilistic methods into a deterministic creep-damage model in order to predict experimental uncertainty. In this study, a modified Wilshire model capable of creep deformation, damage, and rupture prediction is selected. Creep deformation data for 304 stainless steel is collected from the literature consisting of quintuplicate (five) tests at 600°C with varying stress levels. It is hypothesized that the scatter in creep data is due to: test condition (temperature fluctuations and eccentric loading), initial damage (pre-existing surface and sub-surface defects), and metallurgical (local variation in microstructure) uncertainties. Probability distribution functions (pdfs) and Monte Carlo simulations are applied to introduce the uncertainties into the modified Wilshire equations. The domain of each source of uncertainty must be defined. A systematic calibration approach is followed where the material constant for each creep curve (in the quintuple) are obtained and statistical analysis is performed on the material properties to assess the random distribution associated with each uncertain material parameter. The probabilistic calibration begins with the introduction of test condition randomness (±2°C and ±3.2% MPa of nominal temperature/stress) in accordance with the ASTM standards. Cross calibration of temperature-stress variability proceeds the approximation of initial damage uncertainty which captures the remaining scatter in the data. Deterministic calibration unveils the range of variabilities associated with the material properties. The best-fitted pdfs are assigned to each uncertain parameter and subsequently, the deterministic model is converted into a probabilistic model where reliability is a tunable factor. A large number of Monte Carlo simulation are conducted to generate probabilistic creep deformation, minimum-creep-strain-rate (MCSR), and stress-rupture (SR) predictions. It is demonstrated that the probabilistic model produces quantitatively and qualitatively good fits when compared with experimental data. Future work will be directed towards the inclusion of service condition related uncertainty (power plant, turbine blade, Gen IV nuclear reactor application) into the probabilistic framework where the uncertainties are more robust.

The ASME Section XI Working Groups on Operating Plant Criteria (WGOPC) and on Flaw Evaluation (WGFE) have undertaken an effort to develop a new Code Case (Record # 19-1113) to address the following inquiry: What method(s) are acceptable for obtaining RT NDT , RT To and/or T 0 that account for embrittlement for analytical evaluations performed in accordance with Nonmandatory Appendices A, E, G, or K in lieu of the current requirements of these Appendices? Accounting for embrittlement in Code calculations in an appropriate manner is a critical element to the operating safety of nuclear power plants. The intent of responding to this inquiry is to ensure that Code guidance on this matter is comprehensive, up-to-date with the current state of knowledge and applications, and appropriate for international use. The work on the Code Case aims to unify guidance on the following topics throughout the Code, and to fill gaps as needed: • Source of embrittlement data, • Forecasting of embrittlement trends, • Accounting for embrittlement in the inter-relationships between various toughness properties, and • Accounting for uncertainties associated with embrittlement. This paper outlines the overall structure of the Code Case, and summarizes the progress achieved to date.

To ensure an appropriate and/or conservative assessment of structural integrity it is essential to account for the uncertainties inherent to the various inputs and models that, collectively, contribute to a structural integrity assessment. While the methods used to account for uncertainties will differ, this applies equally to assessments performed using either deterministic or probabilistic approaches. Oftentimes the overall model used for a structural integrity assessment is itself comprised of multiple inputs and models, which themselves may be inter-related and/or correlated. In these circumstances the quest to ensure that all uncertainties are addressed can result in the same uncertainty — or uncertainty source — being accounted for multiple times. Such “double-counting” of uncertainties introduces un-needed conservatism to the assessment and should be avoided. In this paper we use the linked fracture toughness models contained in the recently proposed Revision 1 to ASME Section XI Code Case N-830 to provide examples of uncertainty treatment in analyses using multiple models. Identification of sources of uncertainty in each model used in a multi-model analysis can help to ensure that each source is accounted for appropriately and not multiple times. The CC N-830-1 models are used to demonstrate the effects of various uncertainty treatment strategies and the pitfalls that arise from treating sources of uncertainty twice.

Components that are subject to pressure, typical of the pressure vessel industry, can be designed using such calculation methods as “Design by Rule-DBF” or “Design by Analysis-DBA”. DBA, based on the FEM, is used increasingly often because, in addition to providing a reduction in thickness due to the lower uncertainty on the calculation, it helps to verify and study physical phenomena and complex geometry that are otherwise difficult to research while offering a more intuitive usability of the results. In this paper we wish to offer, in an educative and qualitative manner, a general overview of DBA from the creation of the model to obtaining the results, describing the types of analysis that can be carried out according to the constitutive model of the material used and the degree of accuracy that can be achieved. At the end, we cover some case studies in which DBA has been successfully used to verify design or particular conditions (such as heat treatments) for pressure vessels fabrication. The DBA calculation, described in this paper, is used with the same computational methods for high, medium or low pressure components, but it is clear that the most significant reduction in thickness is for high pressure components such as reactors, which is why the DBA calculation is particularly appreciated for this type of equipment. In the context of this paper “high pressure equipment” means when the ratio of the inner diameter to thickness of the walls is < 30.

The irradiation embrittlement of reactor pressure vessel steels can be predicted using the ductile-to-brittle transition temperature (DBTT) shift obtained from Charpy impact tests. For the structural integrity assessment considering irradiation embrittlement, it is necessary to set margins for various uncertainties. It is important to understand what and how much factors contribute to the uncertainty. In the present study, a 34% credible interval value of Charpy DBTT at a 41J energy level (T 41J ) was evaluated by estimating the probability distributions of Charpy test data using Bayesian statistics. To fit the Charpy transition curves, a hyperbolic tangent with coefficients whose uncertainties depend on the test temperature was used. The probability distribution of T 41J was estimated using Monte Carlo sampling and Bayesian inference. It was clarified that 34% of the credible-interval values of T 41J before and after irradiation unchanged for base and weld metals when the number of specimens and test temperature were equivalent under un-irradiated and irradiated conditions. When the Charpy transition curve was determined by 12 specimens loaded in a surveillance test capsule, the estimated uncertainty of T 41J was about 5 °C.

Calibrating inelastic models for high temperature materials used in advanced reactor heat exchangers is a critical aspect in accurately predicting their deformation behavior under different loading conditions, and thus determining the corresponding failure times. The experimental data against which these models are calibrated often contains a wide degree of variability caused by heat-to-heat material property variations and general experimental uncertainty. Most often, model calibration is done against mean of these experimental data without considering this variability. In this work we aim to capture the bounds of the viscoplastic parameter uncertainties that enclose this observed scatter in the experimental data using Bayesian Markov Chain Monte Carlo (MCMC) methods. Bayesian inference provides a probabilistic framework that allows to coherently quantify parameter uncertainties based on some prior parameter distributions and the available data. To perform the statistical Bayesian MCMC analysis, a pre-calibrated model, fitted against mean of the experimental data, is used as an initial guess for the prior distribution and bounds, while further sampling is done using Meteropolis–Hastings algorithm for four Markov chains in tandem, to finally obtain the posterior distribution of the model parameters. Since different inelastic parameters are sensitive to different tests, data from multiple experimental conditions (tensile, and creep) are combined to capture the bounds in all the parameters. The developed statistical model reasonably captures the scatter observed in the experimental data. Quantifying uncertainty in inelastic models will improve high temperature engineering design practice and lead to safer, more effective component designs.

Pipelines carrying oil and gas are susceptible to fatigue failure (i.e., unstable fatigue crack propagation) due to fluctuating loading such as varying internal pressure and other external loadings. Fatigue crack growth (FCG) prediction through full-scale pipe tests can be expensive and time consuming, and experimental data is limited particularly in the face of large uncertainty involved. In contrast, numerical simulation techniques (e.g., XFEM) can be alternative to study the FCG, given that numerical models can be theoretically and/or experimentally validated with reasonable accuracy. In this study, capabilities and limitations of existing fatigue analysis code (e.g., direct cyclic approach with XFEM) in Abaqus for low cycle fatigue simulation are explored for compact-tension (CT) specimens and pipelines assuming linear elastic material behavior. The simulated FCG curve for a CT specimen is compared with that obtained from the analytical method using the stress intensity factor prescribed in ASTM E647. However, for real pipelines with elastic-plastic behavior, direct cyclic approach is not suitable, and an indirect cyclic approach is used based on the fracture energy parameters (e.g., J integral) calculated using XFEM in Abaqus. FCG law (e.g., power law relationship like Paris law) is used to generate the fatigue crack growth curve. For comparison, the FCG curve obtained through direct cyclic approach for pipelines assuming linear elastic material is also presented. The comparative studies here indicate that XFEM-based FCG simulation using appropriate techniques can be applied to pipelines for fatigue life prediction.

In the case of ASME Class 1 pressure vessels and piping code, as in other similar codes, the design adequacy for fatigue is based on the cumulative usage factor (CUF), with recent augmentation to account for possible environmental effects. This deterministic quantification utilizes several engineering parameters (inputs) and (multiplicative) empirical factors. Although the fixed values of some of these design factors and S–N curves are based on underlying experimental data, the associated uncertainties are not explicit in the resulting fatigue assessment that is effectively based on the singular, calculated quantities of CUF and F en , projected for a specified service. As such, the resulting fatigue margin and associated conservatism remain implicit or inconsistent and unquantifiable. At the same time, there is an increased demand for either extending the life of existing systems or for new systems with economically viable or better optimized fatigue designs. One approach to address this is to use a more realistic evaluation offered by probabilistic techniques that take into account the various uncertainties. Such an approach to supplement the deterministic analysis was recently proposed by the author keeping the existing and familiar framework of CUF based assessment, while satisfying acceptable component reliability to meet the fatigue design adequacy. The CUF formulation includes an explicit consideration of the k-factors (for material, loading history, surface and size effects) as adjustments to the S–N data. The objective of this paper is to assess the impact of k-factors and their uncertainty on the failure probability and on the number of load-cycles for specified target reliability. Also, similar assessment is made for the impact of strain-rate variable and its uncertainty on the allowable load-cycles. This is illustrated with a typical application of the CUF analysis of a safety injection nozzle safe-end. The approach taken consists of parametric analysis of the CUF-based probability of failure by individually removing the factors and/or their uncertainty, and comparing the results with the base case where all factors and associated uncertainties are maintained at their original values. Results of this analysis and their implications are discussed, along with a generally applicable relation between the deterministic CUF and the probability of failure.

NB-3600 provides methods for assessing the structural integrity of piping systems. One of the major loading types in piping systems is the moments generated within the pipework to react relative movement of components, thermal expansion and external loads such as gravity or seismic loading. When assessing a pipe tee or branch, there are three sources of moments that must be considered: from the branch and from the run on both sides of the junction; each of these sets of moments has three components. The three components of the branch moment can be easily combined using the square root sum of the squares approach to determine a single resultant moment. For the run, the process is more complex as the moments from either side of the junction need to be converted into a single set of component moments before the resultant run moment is obtained. The method for doing this is given in Subparagraph NB-3683.1 of ASME BPVC Section III. Once the three components run moments have been obtained, they are also combined to determine the resultant. The resultant run and branch moments are then multiplied by geometry-dependent stress indices and summed to give a stress range. For fatigue and shakedown assessments, it is unclear whether the “sign rule” should be applied to the individual load sets before ranging or to the range of each individual component. This potentially results in uncertainty in calculations, leading to unnecessary conservatism and/or repeat calculations. For this study, 10 randomly generated sets of moments have been applied in a 3D finite element model of a typical pipe tee. The stress intensity ranges obtained from the FE results have been compared with the stress range obtained using the NB-3600 stress indices with the sign rule implemented in three different ways. The study shows that the sign rule should be applied after ranging the individual moment components; a change to the wording of the code is recommended to confirm this. However, given the levels of conservatism in other parts of the calculation, it is unlikely that any calculations carried out using the sign rule first are non-conservative.

Uncertainty in the prediction of lower tail fatigue life behavior is a combination of many causes, some of which are aleatoric and some of which are systemic. The error cannot be entirely eliminated or quantified due to microstructural variability, manufacturing processing, approximate scientific modeling, and experimental inconsistencies. The effect of uncertainty is exacerbated for extreme value estimation for fatigue life distributions because by necessity those events are rare. In addition, typically, there is a sparsity of data in the region of smaller stress levels in stress–life testing where the lives are considerably longer, extending to giga cycles for some applications. Furthermore, there is often over an order of magnitude difference in the fatigue lives in that region of the stress–life graph. Consequently, extreme value estimation is problematic using traditional analyses. Thus, uncertainty must be statistically characterized and appropriately managed. The primary purpose of this paper is to propose an empirically based methodology for estimating the lower tail behavior of fatigue life cumulative distribution functions, given the applied stress. The methodology incorporates available fatigue life data using a statistical transformation to estimate lower tail behavior at much smaller probabilities than can be estimated by traditional approaches. To assess the validity of the proposed methodology confidence bounds will be estimated for the stress–life data. The development of the methodology and its subsequent validation will be illustrated using extensive fatigue life data for 2024–T4 aluminum alloy specimens readily available in the open literature.

Current approaches of fatigue evaluation of nuclear reactor components or other safety critical structural systems use S∼N curve based empirical relations which may have large uncertainty. This uncertainty may be reduced by using a more mechanistic approach. In the proposed mechanistic approach, material models are developed based on the evolution of material behavior under uniaxial fatigue experiments and implement those models into 3D finite element (FE) calculations for fatigue evaluation under multiaxial loading. However, this approach requires simulating structures under thousands of fatigue cycles which necessitates the use of high performance computing (HPC) to determine fatigue life of a large component/system within reasonable time frame. Speeding up the FE simulation of large systems requires the use of a higher number of cores, which is extremely costly, particularly when a commercial FE code is used. Also, commercial software is not necessarily optimized for use in an HPC environment. In this work, an open source parallel computing solver along with a multi-core cluster is used to scale up the number of cores. The HPC-based mechanistic fatigue modeling framework is validated through evaluating fatigue life of a pressurized water reactor surge line pipe under idealistic loading cycles and comparing the simulation results with observations from uniaxial fatigue experiment of 316 stainless steel specimen.

Structural integrity assessments typically aim to calculate the integrity of a component under nominal or best estimate conditions. To account for potential variability and uncertainty present in the system, safety factors are often applied to assessment inputs and outputs. This approach does not allow the level of conservatism present to be quantified, often leading to over-conservatism or inadvertent non-conservatism. Probabilistic assessments explicitly calculate the probability of failure based on distributions of the input parameters and hence quantify the margin present in the assessment, leading to a greater understanding of the system. In this study a creep-fatigue damage assessment of a transiently loaded piping component is used as a vehicle to investigate some of the challenges and benefits of probabilistic assessments. A probabilistic assessment of the component life is compared to a lower-bound deterministic calculation to identify the mismatch in margin between the two results. The potential inaccuracies introduced when reducing the computational burden of Monte Carlo simulations with response surface methodologies are explored and tested. Finally, two challenges when attempting to underwrite a very low probability of failure are tackled: the inference of the shape of a distribution’s tails from limited experimental data and the uncertainty of extreme percentiles of finite Monte Carlo samples.

The pressure surge in pipes due to change in operating conditions exerts an axial load on elbows proportional to the change in momentum of fluid and unbalanced pressure forces. The response of piping structure to such load needs the full time history analysis in three dimensional spaces which is cumbersome process due to high computing memory requirements and long simulation time. In present work it has been shown that using Rayleigh energy balance for each elbow-load configuration, the system can be reduced to equivalent 1D spring mass system and the response can be estimated by solving 1D equation of motion. Then it has been recommended to simulate the response of each elbow which gives good approximation of dynamic amplification of displacement also called as Dynamic Load Factor (DLF). These dynamic load factors for each elbow can be used for the interaction of forces using static equivalent response in 3D space. This approach is pseudo static equivalent analysis where the load amplifications factors DLF are estimated from the dynamic force profile and system response in one-dimensional space. An algorithm is developed for the above explained process. Most of the engineers are using the DLF = 2 for the load estimation due to absence of method to estimate the dynamic load factor. The approach was proposed by Goodling in 1989 and still widely followed in the industry. The present paper discusses uncertainty and inaccuracy involved in performing approximate analysis and shows the significance and need of performing full force time history analysis. The proposed method shows very good agreement with the time consuming 3D full force time history results. There are also limitations for the proposed method. As the spring mass system is simulated with dimensional reduction to single frequency domain, the pipe supports and guides should be properly placed before applying the present approach. It has been shown that with proper support configuration, this simplified approach yields very good approximation of surge load on pipes with reduced time.

Integrity assessment of reactor pressure vessels (RPVs) can be performed either by deterministic fracture mechanics (DFM) or/and by probabilistic fracture mechanics (PFM) analyses. In European countries and Switzerland, only DFM analyses are required. However, in order to establish the probabilistic approach in Switzerland, the advantages and shortcomings of the PFM are investigated in the frame of a national research project. Both, the results from DFM and PFM depend strongly on the previous calculated thermal-hydraulic boundary conditions. Therefore, complete integrity analyses involving several integrated numerical codes and methods were performed for a reference pressurized water reactor (PWR) RPV subjected to pressurized thermal shock (PTS) loads. System analyses were performed with the numerical codes RELAP5 and TRACE, whereas for structural and fracture mechanics calculations, the FAVOR and ABAQUS codes were applied. Additional computational fluid dynamics analyses were carried out with ANSYS/FLUENT, and the plume cooling effect was alternatively considered with GRS-MIX. The results from the different analyses tools are compared, to judge the expected overall uncertainty and reliability of PTS safety assessments. It is shown that the scatter band of the stress intensities for a fixed crack configuration is rather significant, meaning that corresponding safety margins should be foreseen. The conditional probabilities of crack initiation and RPV failure might also differ, depending on the considered random parameters and applied rules.

Waterhammer analysis (herein referred to as Hydraulic Transient Analysis or simply “HTA”) becomes more complicated when transient cavitation occurs (also known as liquid column separation). This complication is exacerbated when trying to predict imbalanced forces as this often involves comparing pressure times area (“PxA”) forces at two locations (for example at elbow pairs). Whereas the pressure at each elbow location has increased uncertainty because of transient cavitation, the difference in PxA forces at elbow pairs involves subtracting one potentially uncertain pressure from another uncertain pressure. Exacerbating this uncertainty yet further, the existence of vapor in a liquid system can dramatically affect the fluid wavespeed and, hence, the timing of the pressure wave travel between two locations such as elbow pairs; so the pressure calculated at each location would not actually occur at exactly the same time. This Part 2 discusses methods of accounting for uncertainty in HTA imbalanced force predictions due to cavitation. The criteria in this paper assume that cavitation in the HTA has been assessed and accepted per the criteria in Part 1 of this paper. A guideline is proposed for accepting and applying such results and, in particular, makes recommendations on safety factors to use in pipe stress analysis for different cases. The specific recommendations depend on numerous factors including: • Presence or absence of cavitation in hydraulically connected or isolated parts of the system • If cavitation occurs, whether the peak forces occur before or after cavitation first occurs • Size of the cavitation vapor volumes with respect to the computing volumes • Use of point forces as a conservative substitute in place of potentially less certain elbow pair forces or the manual assessment of maximum envelope values for the force. Situations are discussed where waterhammer abatement is recommended to reduce hydraulic transient forces, and for increasing confidence in HTA results in specific cases. The result is a proposed comprehensive and pragmatic guideline which practicing engineers can use to perform waterhammer analysis and apply imbalanced force predictions to pipe stress analysis.

Attention to be paid to the aging of industrial facilities has been growing in the last ten years, both by public authorities and industrial executives. Many process plants, operating in Europe, have reached or exceeded their project nominal life and the safe management of aging is an urgent question. Failures, due to aged chemical process plants, cause the release of hazardous materials with severe consequences for people and workers. To counteract this phenomenon, plant operators carry out many technical activities, including non-destructive controls on piping and vessels, by adopting sophisticated methods (e.g. Risk Based Inspection RBI). The European Directive 2012/18/UE (Seveso III) for the control of Major Accident Hazard (MAH) introduced a few requirements for the safe aging of critical equipment, which must be verified during mandatory audits. The aim of this work is to present a synthetic methodology that can be useful for both Seveso auditors and industrial managers for evaluating the adequacy of the measures to control the aging of critical equipment. To achieve a synthetic assessment of the adequacy of the aging management programs, a compensated index method has been developed, which is a simple and easy-to-use tool. The use of an index method inevitably introduces a degree of uncertainty. However, if it is compared to other qualitative methods, such a tool offers the advantage of a major clarity in the assessment process. This paper discusses a practical application of the method within inspection programs, as required by the art. 27 of Seveso III Directive.

The Electric Power Research Institute (EPRI) with Électricité de France (EDF) developed the Integrated Life Cycle Management (ILCM) computer code to provide a standard methodology to support effective decision making for the long-term management of selected nuclear station components. In 2016, a Likelihood of Replacement (LoR) expert elicitation was developed to provide reliability curves for determination of replacement options for components that were not initially included in ILCM. The LoR methodology required expert’s to estimate future replacement probabilities which were then combined with historical failures using Bayesian analysis. Although this methodology was effective, parts of the industry were accustomed to providing a High/Medium/Low (HML) probability categorization for selected periods of operation. This paper presents an approach for calculating Weibull replacement probability curves from HML categorical replacement probability estimates. Additional questions beyond the initial HML categorization were developed. These focused on the timing of category transitions to refine parameter likelihood functions, reduce parameter uncertainty, and offset the significant Weibull parameter uncertainty introduced by using categorical estimates.

This paper presents a methodology for identifying blunt flaws in piping using in-service data from ultrasonic inspection tools. The method is applicable to data obtained from predetermined inspection grids, or directly from bracelet or array type inspection tools. The flaw edge and size are identified by calculating the three-dimensional slope vector (i.e., magnitude and direction) of each point in the kriging interpolated wall thickness profile. The transition from a steeper slope to a relatively flat profile is then used by a search algorithm to determine the flaw edge. The method is applied to the flaw assessment of feeder piping in CANDU nuclear reactors. The results show that in addition to identifying blunt flaws, the developed methodology also provides a convenient way for characterizing the flaw dimensions for structural integrity assessment. The uncertainty in the results is mainly attributed to the signal loss and coverage error associated with the inspection data.

The main objective and mission of the ATLAS+ project is to develop advanced structural assessment tools to address the remaining technology gaps for the safe and long term operation of nuclear reactor pressure coolant boundary systems. This is achieved by development and validation of: • innovative quantitative methodologies to transfer laboratory material properties to assess the structural integrity of large components, • enhanced treatment of weld residual stresses when subjected to long term operation, • advanced simulation tools based on fracture mechanics methods using physically based mechanistic models, • improved engineering methods to assess components under long term operation taking into account specific operational demands, • integrated probabilistic assessment methods to reveal uncertainties and justify safety margins. Additionally, the objective is to disseminate the findings of the work through special training sessions and links to the NUGENIA association. The project scope of work focuses on piping systems of the reactor coolant pressure boundary components (RCPB) excluding the reactor pressure vessel (RPV). The project is aimed on an experimental proof of concept and validates the developed methodology both at the laboratory scale and the full scale level. The ATLAS+ project contains 4 main technical work packages and one training and dissemination package. These are summarised here.