Assystem is an independent engineering group based in Paris. It provides services in the design, construction supervision, commissioning and operation of a client's industrial infrastructure. It had revenues of over €470M in 2020, down from €871.4M in 2013. It had over 7100 employees as of 2021, down from over 11,000 in 2013.
Title block compliance checking requires interpreting irregular tabular layouts and reporting structural inconsistencies, not only extracting metadata. This paper introduces a user-in-the-loop, template-based method that leverages a graphical annotation workflow to encode title block structure as a hierarchical annotation graph combining detected primitives (cells/text) with user-defined semantic entities (key-value pairs, tables, headers). The resulting template is matched onto target title blocks using relative positional constraints and category-specific rules that distinguish acceptable variability from non-compliance (e.g., variable-size tables versus missing fields). The system outputs extracted key-value information and localized warning logs for end-user correction. On a real industrial example from the nuclear domain, the approach achieves 98-99% compliant annotation matching and 84% accuracy in flagging structural/content deviations, while remaining tolerant to moderate layout changes. Limitations and extensions are discussed, including support for additional fields, improved key similarity metrics, operational deployment with integrated feedback and broader benchmarking.
Physical infrastructure is essential for urban functioning, as it supports socio-economic activities and ensures public well-being. It includes transportation, energy, water supply, stormwater, wastewater, and solid waste management systems, all of which are critical for achieving sustainability. Efficient and seamless infrastructure provision is vital for rapidly urbanizing cities. This study assesses the physical infrastructure of Puducherry, a coastal city in India experiencing increasing pressures from urbanization. A comprehensive literature review was conducted to understand the local context, followed by Service Level Benchmarking (SLB) and detailed on-site surveys to evaluate the current status of three key infrastructure sectors: water supply, drainage and sewage (D&S), and solid waste management (SWM). The assessment examines the demand–supply gaps using a five-point sustainability scale, ranging from high to low, based on availability, operation and maintenance (O&M), and green aspects. A set of indicators was employed for each sector, water supply (13), D&S (11), and SWM (8). Cumulative indexing reveals that Puducherry demonstrates high to moderate sustainability in water supply, while D&S, and SWM exhibit moderately low to low sustainability levels. The study proposes a strategic roadmap incorporating intelligent practices to enhance infrastructure sustainability to improve infrastructure in other coastal cities.
This study has presented an enhanced methodology for the safety assessment of marine nuclear reactor systems using probabilistic model checking within the SAFEST toolchain. By reconstructing and extending the DFT models originally proposed by Zhao et al., we re-evaluated a critical severe accident scenario-specifically a reactor response following a Loss of Coolant Accident (LOCA)-with significantly greater temporal and logical fidelity. In contrast to the Cut Sequence (CS) and Extended Cut Sequence (ECS) methods used by Zhao et al., our approach translates dynamic fault trees into Markov Automata, enabling formal verification of time-bounded safety properties, precise computation of Mean Time to Failure (MTTF), and realistic analysis of failure propagation over time. The results highlight important discrepancies between static and dynamic modeling approaches: while ECS offered conservative unreliability estimates over a one-year time frame, our SAFEST-based dynamic analysis revealed significantly higher unreliability values and more complex degradation behaviors across all major subsystems. Key findings from our analysis include: center dot The top-level reactor failure after LOCA (T2) shows an unreliability of 2.5 x 10(-5) using SAFEST, compared to 8.1 x 10(-6) from Zhao et al.-a threefold increase, primarily due to SAFEST accounting for time-ordered dependencies and probabilistic control logic. center dot The water make- up system (W1) exhibits a one-year unreliability of 0.054 in SAFEST, as opposed to 3.25 x 10(-3) reported by Zhao-indicating a more than 16-fold underestimation in the ECS-based model. center dot The charging pump and pump subsystems in SAFEST show unreliability of 1.48 x 10(-3) at one year, closely matching Zhao's values, but SAFEST further reveals their steep degradation beyond year one-insights that ECS does not provide. center dot MTTF values 98,500 hours for the water make-up system showing the earliest expected failure, emphasizing its need for design and operational redundancy. Beyond these numerical results, our methodology underscores the importance of integrating formal verification techniques in dynamic probabilistic safety assessments (DPSA) for nuclear systems, particularly in marine environments where operational conditions are highly variable and access for maintenance is limited. The work sets a new precedent in risk-informed, time-resolved nuclear safety analysis, advocating for a transition from approximation-based methods to rigorous, modelchecking-powered evaluations.
The nuclear safety demonstration aims to demonstrate that a Nuclear Facility respects all the requirements specified in standards from safety authorities, which is a key objective for the licensing of a nuclear installation. It requires, firstly, supporting the necessary collaborative work involving various stakeholders. Secondly, it should be able to use a common and shared requirements repository. However, it is still the so-called “classic” working methods that are put forward. Almost all the documents are in written form. Due to the complexity of the Nuclear Facility of interest, it is proposed to move from this document-oriented system engineering to a model-based system engineering approach which would improve the performance, delay, and qualities of the engineering processes. Models would allow a better cognition and sharing without ambiguities of information by the engineering teams. Subject of this paper is a hybrid MBSE/AI approach facilitating collaborative work on nuclear safety demonstration processes.
