Phase Stability and Segregation in Alloy 22 Base Metal and Weldments

The current design of the waste disposal containers relies heavily on encasement in a multi-layered container, featuring a corrosion barrier of Alloy 22, a Ni-Cr-Mo-W based alloy with excellent corrosion resistance over a wide range of conditions. The fundamental concern from the perspective of the Yucca Mountain Project, however, is the inherent uncertainty in the (very) long-term stability of the base metal and welds. Should the properties of the selected materials change over the long service life of the waste packages, it is conceivable that the desired performance characteristics (such as corrosion reistance) will become compromised, leading to premature failure of the system. To address this, we will study the phase stability and solute segregation characteristics of Alloy 22 base metal and welds. A better understanding of the underlying microstructural evolution tendencies, and their connections with corrosion behavior will (in turn) produce a higher confidence in the extrapolated behavior of the container materials over time periods that are not feasibly tested in a laboratory. Additionally, the knowledge gained here may potentially lead to cost savings through development of safe and realistic design constraints and model assumptions throughout the entire disposal system

Evaluation of Verification Approaches Applied to a Nonlinear Control System

As the demand for increasingly complex and autonomous systems grows, designers may consider computational and artificial intelligence methods for more advanced, re- active control. While the performance gained by such increasingly intelligent systems may be superior to traditional control techniques, the lack of transparency in the systems and opportunity for emergent behavior limits their application in the field. New verification and validation methods must be developed to ensure the output of such controllers do not put the system or any people interacting with it in danger. This challenge was highlighted by the former Air Force Chief Scientist in his 2010 Technology Horizons Report, stating \It is possible to develop systems having high levels of autonomy, but it is the lack of suitable [verification and validation] (V&V) methods that prevents all but relatively low levels of autonomy from being certified for use

Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process

This paper outlines real-world control challenges faced by modern-day biopharmaceutical facilities through the extension of a previously developed industrial-scale penicillin fermentation simulation (IndPenSim). The extensions include the addition of a simulated Raman spectroscopy device for the purpose of developing, evaluating and implementation of advanced and innovative control solutions applicable to biotechnology facilities. IndPenSim can be operated in fixed or operator controlled mode and generates all the available on-line, off-line and Raman spectra for each batch. The capabilities of IndPenSim were initially demonstrated through the implementation of a QbD methodology utilising the three stages of the PAT framework. Furthermore, IndPenSim evaluated a fault detection algorithm to detect process faults occurring on different batches recorded throughout a yearly campaign. The simulator and all data presented here are available to download at www.industrialpenicillinsimulation.com and acts as a benchmark for researchers to analyse, improve and optimise the current control strategy implemented on this facility. Additionally, a highly valuable data resource containing 100 batches with all available process and Raman spectroscopy measurements is freely available to download. This data is highly suitable for the development of big data analytics, machine learning (ML) or artificial intelligence (AI) algorithms applicable to the biopharmaceutical industry

Compositional verification of industrial control systems : methods and case studies

The main obstacles in the formal verification of industrial control systems are the lack of precise semantics for its programming languages, and the complexity problems which arise during the verification process. This work addresses both issues by defining an operational semantics for Sequential Function Charts, a widely-used language for Programmable Logic Controllers (PLCs), and by presenting modular and compositional methods to reduce the complexity arising from parallel structures in the system. These methods are illustrated by the verification of two PLC-controlled chemical batch plants

A framework for Model-Driven Engineering of resilient software-controlled systems

AbstractEmergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones