A Data-Driven Fuzzy Approach for Predicting the Remaining Useful Life in Dynamic Failure Scenarios of a Nuclear Power Plant

This paper presents a similarity-based approach for prognostics of the Remaining Useful Life (RUL) of a system, i.e. the lifetime remaining between the present and the instance when the system can no longer perform its function. Data from failure dynamic scenarios of the system are used to create a library of reference trajectory patterns to failure. Given a failure scenario developing in the system, the remaining time before failure is predicted by comparing by fuzzy similarity analysis its evolution data to the reference trajectory patterns and aggregating their times to failure in a weighted sum which accounts for their similarity to the developing pattern. The prediction on the failure time is dynamically updated as time goes by and measurements of signals representative of the system state are collected. The approach allows for the on-line estimation of the RUL. For illustration, a case study is considered regarding the estimation of RUL in failure scenarios of the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS

An anisotropic numerical model for thermal hydraulic analyses: application to liquid metal flow in fuel assemblies

A CFD analysis has been carried out to study the thermal–hydraulic behavior of liquid metal coolant in a fuel assembly of triangular lattice. In order to obtain fast and accurate results, the isotropic two-equation RANS approach is often used in nuclear engineering applications. A different approach is provided by Non-Linear Eddy Viscosity Models (NLEVM), which try to take into account anisotropic effects by a nonlinear formulation of the Reynolds stress tensor. This approach is very promising, as it results in a very good numerical behavior and in a potentially better fluid flow description than classical isotropic models. An Anisotropic Shear Stress Transport (ASST) model, implemented into a commercial software, has been applied in previous studies, showing very trustful results for a large variety of flows and applications. In the paper, the ASST model has been used to perform an analysis of the fluid flow inside the fuel assembly of the ALFRED lead cooled fast reactor. Then, a comparison between the results of wall-resolved conjugated heat transfer computations and the results of a decoupled analysis using a suitable thermal wall-function previously implemented into the solver has been performed and presented

Early warning system for the prevention and control of unauthorized accesses to air navigation services infrastructures

Early warning systems are fundamental instruments for the management of critical situations since they are able to signal in advance any anomaly with respect to ordinary situations. The purpose of this paper is to present an early warning system, based on artificial neural networks, for the prevention and control of unauthorized accesses to the air navigation services infrastructure in Italy

A sensitivity analysis for the adequacy assessment of a multi-state physics modeling approach for reliability analysis

In this work, a moment-independent Sensitivity Analysis (SA) based on Hellinger distance and Kullback-Leibler divergence is proposed to identify the component of a system most affecting its reliability (Diaconis et al., 1982; Gibbs et al., 2002; Di Maio et al., 2014). This result is used to adequately allocate modeling efforts on the most important component that, therefore, deserves a component-level Multi-State Physics Modeling (MSPM) to be integrated into a system-level model, to estimate the system failure probability

Towards a common object model and API for accelerator controls

An Object-Oriented Application Programming Interface (OO API) can provide applications with an abstract model of the components of an accelerator. The main question is how to encapsulate different control systems into one single abstract model. The abstract model of an 00 API can be described in a formal way via object models in order to clarify the semantic issues, to describe the important concepts (device, attributes, ...), and to decompose the objects up to the granularity where the model of some objects can be shared between labs. A C++ API (as well as C API) can be derived from the object-model. This paper presents a common object model which is derived from the object-model. This paper presents a common object model which is derived from both the current CERN-PS model and the current ERSF model. We describe the technical difficulties we encountered in migrating existing control systems into a shared but usable model. We also aim to increase the universality of the model by taking into account the CDEV library, as well as CORBA. A high-level description of the model will be presented with examples of the derived API

Robust multi-objective optimization of safety barriers performance parameters for NaTech scenarios risk assessment and management

Safety barriers are to be designed to bring the largest benefit in terms of accidental scenarios consequences mitigation at the most reasonable cost. In this paper, we formulate the problem of the identification of the optimal performance parameters of the barriers that can at the same time allow for the consequences mitigation of Natural Technological (NaTech) accidental scenarios at reasonable cost as a Multi-Objective Optimization (MOO) problem. The MOO is solved for a case study of literature, consisting in a chemical facility composed by three tanks filled with flammable substances and equipped with six safety barriers (active, passive and procedural), exposed to NaTech scenarios triggered by either severe floods or earthquakes. The performance of the barriers is evaluated by a phenomenological dynamic model that mimics the realistic response of the system. The uncertainty of the relevant parameters of the model (i.e., the response time of active and procedural barriers and the effectiveness of the barriers) is accounted for in the optimization, to provide robust solutions. Results for this case study suggest that the NaTech risk is optimally managed by improving the performances of four-out-of-six barriers (three active and one passive). Practical guidelines are provided to retrofit the safety barriers design

Adding PD-1/PD-L1 inhibitors to chemotherapy for the first-line treatment of extensive stage small cell lung cancer (Sclc): A meta-analysis of randomized trials

Survival outcomes in extensive-stage small cell lung cancer (ES SCLC) are dismal, with median overall survival (OS) less than 12 months. The combination of PD-1/PD-L1 immune checkpoint inhibitors (ICIs) with first-line platinum-etoposide chemotherapy has been recently evaluated in randomized clinical trials. We performed a systematic literature review through PubMed and conference proceedings. Randomized trials evaluating chemotherapy +/− PD-1/PD-L1 ICIs were included in the meta-analysis. Efficacy (OS), activity [progression-free survival (PFS) and objective response rate (ORR)] outcomes and toxicities were analyzed. For selected endpoints, we focused on patients’ subgroups (OS) and on landmark analyses (OS, PFS). Four randomized trials were identified; globally, 1553 patients were randomized to receive chemotherapy +/− PD-1/PD-L1 ICIs. Adding a PD-1/PD-L1 ICI to chemotherapy led to a significant benefit in OS [hazard ratio (HR) 0.76, 95% confidence interval (CI) 0.68–0.85, p < 0.00001), PFS [HR 0.75, 95% CI 0.68–0.84, p < 0.00001] and ORR [odds ratio 1.28, 95% CI 1.04–1.57, p = 0.02]. No unexpected toxicity emerged. At 12, 18, 24 months for OS, and at 12, 18 months for PFS, experimental arms retained significant improvement in event-free rates, with absolute gain of approximately 10% compared with standard treatment. Albeit the magnitude of the benefit is less impacting compared to other settings of immunotherapy, the addition of PD-1/PD-L1 ICIs to chemotherapy in ES SCLC provided significant improvements in survival outcomes with the known toxicity profile. Biomarkers predicting which patients are suitable to derive long-term benefits are eagerly awaited

A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply

The Operation & Maintenance (O&M) of Cyber-Physical Energy Systems (CPESs) is driven by reliable and safe production and supply, that need to account for flexibility to respond to the uncertainty in energy demand and also supply due to the stochasticity of Renewable Energy Sources (RESs); at the same time, accidents of severe consequences must be avoided for safety reasons. In this paper, we consider O&M strategies for CPES reliable and safe production and supply, and develop a Deep Reinforcement Learning (DRL) approach to search for the best strategy, considering the system components health conditions, their Remaining Useful Life (RUL), and possible accident scenarios. The approach integrates Proximal Policy Optimization (PPO) and Imitation Learning (IL) for training RL agent, with a CPES model that embeds the components RUL estimator and their failure process model. The novelty of the work lies in i) taking production plan into O&M decisions to implement maintenance and operate flexibly; ii) embedding the reliability model into CPES model to recognize safety related components and set proper maintenance RUL thresholds. An application, the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED), is provided. The optimal solution found by DRL is shown to outperform those provided by state-of-the-art O&M policies

Treatment of end-of-life concrete in an innovative heating-air classification system for circular cement-based products

A stronger commitment towards Green Building and circular economy, in response to environmental concerns and economic trends, is evident in modern industrial cement and concrete production processes. The critical demand for an overall reduction in the environmental impact of the construction sector can be met through the consumption of high-grade supplementary raw materials. Advanced solutions are under development in current research activities that will be capable of up-cycling larger quantities of valuable raw materials from the fine fractions of End-of-Life (EoL) concrete waste. New technology, in particular the Heating-Air classification System (HAS), simultaneously applies a combination of heating and separation processes within a fluidized bed-like chamber under controlled temperatures (±600 °C) and treatment times (25–40 s). In that process, moisture and contaminants are removed from the EoL fine concrete aggregates (0–4 mm), yielding improved fine fractions, and ultrafine recycled concrete particles (<0.125 mm), consisting mainly of hydrated cement, thereby adding value to finer EoL concrete fractions. In this study, two types of ultrafine recycled concrete (either siliceous or limestone EoL concrete waste) are treated in a pilot HAS technology for their conversion into Supplementary Cementitious Material (SCM). The physico-chemical effect of the ultrafine recycled concrete particles and their potential use as SCM in new cement-based products is assessed by employing substitutions of up to 10% of the conventional binder. The environmental viability of their use as SCM is then evaluated in a Life Cycle Assessment (LCA). The results demonstrated accelerated hydration kinetics of the mortars that incorporated these SCMs at early ages and higher mechanical strengths at all curing ages. Optimal substitutions were established at 5%. The results suggested that the overall environmental impact could be reduced by up to 5% when employing the ultrafine recycled concrete particles as SCM in circular cement-based products, reducing greenhouse gas emissions by as much as 41 kg CO2 eq./ton of cement (i.e. 80 million tons CO2 eq./year). Finally, the environmental impacts were reduced even further by running the HAS on biofuel rather than fossil fuel.The authors of the present paper, prepared in the framework ofthe Project VEEP "Cost-Effective Recycling of C&DW in High AddedValue Energy Efficient Prefabricated Concrete Components forMassive Retrofitting of our Built Environment", wish to acknowl-edge the European Commission for its support. This project hasreceived funding from the European Union’s Horizon 2020 researchand innovation programme under grant agreement No 723582.This paper reflects only the author’s view and the European Com-mission is not responsible for any use that may be made of theinformation it contains.The authors are also grateful to the Spanish Ministry of Science,Innovation and Universities (MICIU) and the European RegionalDevelopment Fund (FEDER) for funding this line of research(RTI2018-097074-B-C21)

Selective gold and palladium adsorption from standard aqueous solutions

The intensive exploitation of resources on a global level has led to a progressive depletion of mineral reserves, which were proved to be insufficient to meet the high demand for high-technological devices. On the other hand, the continuous production of Waste from Electrical and Electronic Equipment (WEEE) is causing serious environmental problems, due to the complex composition of WEEE, which makes the recycling and reuse particularly challenging. The average metal content of WEEE is estimated to be around 30% and varies depending on the manufacturing period and brand of production. It contains base metals and precious metals, such as gold and palladium. The remaining 70% of WEEEs is composed of plastics, resins, and glassy materials. The recovery of metals from WEEEs is characterized by two main processes well represented by the literature: Pyrometallurgy and hydrometallurgy. Both of them require the pre-treatment of WEEEs, such as dismantling and magnetic separation of plastics. In this work, the selective adsorption of precious metals has been attempted, using copper, gold, and palladium aqueous solutions and mixtures of them. A screening on different adsorbent materials such as granular activated carbons and polymers, either as pellets or foams, has been performed. Among these, PolyEther Block Amide (PEBA) was elected as the most performing adsorbent in terms of gold selectivity over copper. Spent PEBA has been then characterized using scanning electron microscope, coupled with energy dispersive spectroscopy, demonstrating the predominant presence of gold in most analyzed sites, either in the pellet or foam form