Hybrid Petri nets with multiple stochastic transition firings

This paper introduces an algorithm for the efficient computation of transient measures of interest in Hybrid Petri nets in which the stochastic transitions are allowed to fire an arbitrary but finite number of times. Each firing increases the dimensionality of the underlying discrete/continuous state space. The algorithm evolves around a partitioning of the multi-dimensional state-space into regions, making use of advanced algorithms (and libraries) for computational geometry. To bound the number of stochastic transition firings the notion of control tokens is newly introduced. While the new partitioning algorithm is general, the implementation is currently limited to only two stochastic firings. The feasibility and usefulness of the new algorithm is illustrated in a case study of a water refinery plant with cascading failures

Methodologies synthesis

This deliverable deals with the modelling and analysis of interdependencies between critical infrastructures, focussing attention on two interdependent infrastructures studied in the context of CRUTIAL: the electric power infrastructure and the information infrastructures supporting management, control and maintenance functionality. The main objectives are: 1) investigate the main challenges to be addressed for the analysis and modelling of interdependencies, 2) review the modelling methodologies and tools that can be used to address these challenges and support the evaluation of the impact of interdependencies on the dependability and resilience of the service delivered to the users, and 3) present the preliminary directions investigated so far by the CRUTIAL consortium for describing and modelling interdependencies

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

YesSystem safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive and accurate analysis of complex systems, different characteristics such as functional dependencies among components, temporal behaviour of systems, multiple failure modes/states for components/systems, and uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity in risk assessment applications due to their flexible structure and capability of incorporating most of the above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis. Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over other classical approaches, and relative strengths and weaknesses in different practical application scenarios.This work was funded by the DEIS H2020 project (Grant Agreement 732242)

NASA thesaurus. Volume 1: Hierarchical Listing

There are over 17,000 postable terms and nearly 4,000 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary and Volume 3 - Definitions

NASA Thesaurus. Volume 1: Hierarchical listing

There are 16,713 postable terms and 3,716 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

STRESS-STRAIN CAPACITY ANALYSIS FOR THE IMPACT OF NATURAL DISASTERS ON COUPLED INFRASTRUCTURE FACILITIES

Infrastructure facilities serve as the backbone of the communities and industries by sustaining social and economic activities through their services. However, the physical impact of a disaster can have an adverse effect on the functioning of the infrastructure. In addition, the affected infrastructure facilities are unable to adequately meet the needs of the community immediately after the disaster. Thus, to compensate for gaps in services, infrastructure facilities are likely to run their systems, such that it puts additional stress on their resources that exceeds their designed capacities at the expense of level of service. For example, after the devastating earthquake in Haiti in 2010, disrupted utility services, limited available road networks, and the lack of civic governance influenced the capacity of all essential service providers such as hospitals. Furthermore, the hospitals that were impacted by the earthquake had limited resources, such as water and power utility for operating the hospitals, beds for patients, medical staff, and medical supplies, to meet the increased health needs of the community. As a result, the hospitals in Haiti had to put excessive stress on their available resources, as their remaining capacities were not enough to accommodate the increased number of patients without assistance from NGOs or other external entities. If the emergency managers of the hospitals were able to evaluate their remaining capacities based on the excessive stress so that they could make appropriate strategies for mitigating the excessive stress ahead of time, the infrastructure facility would have serviced the affected communities more efficiently

2023 - The Fourth Annual Fall Symposium of Student Scholars

The full program book from the Fall 2023 Symposium of Student Scholars, held in November 2023. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1028/thumbnail.jp

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine