Digital twins, Industry 4.0 and Industrial Internet of Things are becoming ever more important in the process industry. The Semantic Web, linked data, knowledge graphs and web services/agents are key technologies for implementing the above concepts. In this paper, we present a comprehensive semantic agent composition framework. It enables automatic agent discovery and composition to Highlights • The light-weight ontology, OntoAgent, has been developed based on MSM
This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture.
In this paper, we demonstrate through
examples how the concept
of a Semantic Web based knowledge graph can be used to integrate combustion
modeling into cross-disciplinary applications and in particular how
inconsistency issues in chemical mechanisms can be addressed. We discuss
the advantages of linked data that form the essence of a knowledge
graph and how we implement this in a number of interconnected ontologies,
specifically in the context of combustion chemistry. Central to this
is OntoKin, an ontology we have developed for capturing both the content
and the semantics of chemical kinetic reaction mechanisms. OntoKin
is used to represent the example mechanisms from the literature in
a knowledge graph, which itself is part of the existing, more general
knowledge graph and ecosystem of autonomous software agents that are
acting on it. We describe a web interface, which allows users to interact
with the system, upload and compare the existing mechanisms, and query
species and reactions across the knowledge graph. The utility of the
knowledge-graph approach is demonstrated for two use-cases: querying
across multiple mechanisms from the literature and modeling the atmospheric
dispersion of pollutants emitted by ships. As part of the query use-case,
our ontological tools are applied to identify variations in the rate
of a hydrogen abstraction reaction from methane as represented by
10 different mechanisms.
The chemical industry is increasingly relying on agents for data acquisition, optimization, and simulation. In order to enable efficient management of agents, Knowledge Graphs (KG) together with agent composition frameworks are therefore applied. However, a method to assess the reliability of agents for such systems is absent. Therefore, this paper proposes a Smart Contract-based agent marketplace for composition frameworks to estimate the reliability of agents.In this agent marketplace, we improved the feedback-based reputation system by leveraging Smart Contracts to eliminate fraudulent ratings and to enable automation. The marketplace incorporates a rating-dependent payment mechanism as well, to further enhance trust. The paper also illustrates how this marketplace is integrated into the J-Park Simulator (JPS) agent composition framework for the automated agent selection and transaction.
Highlights• A novel agent marketplace is built on top of blockchain-based Smart Contracts.
Abstract. This paper demonstrates the development of a moving point source (MPS) model for simulating the atmospheric dispersion of pollutants emitted from ships under movement. The new model is integrated into the chemistry transport model EPISODE–CityChem v1.3. In the new model, ship parameters, especially speed and direction, are included to simulate the instantaneous ship positions and then the emission dispersion at different simulation time. The model was first applied to shipping emission dispersion modeling under simplified conditions, and the instantaneous and hourly averaged emission concentrations predicted by the MPS model and the commonly used line source (LS) and fixed point source (FPS) models were compared. The instantaneous calculations were quite different due to the different ways to treat the moving emission sources by different models. However, for the hourly averaged concentrations, the differences became smaller, especially for a large number of ships. The new model was applied to a real configuration from the seas around Singapore that included hundreds of ships, and their dispersion was simulated over a period of a few hours. The simulated results were compared to measured values at different locations, and it was found that reasonable emission concentrations were predicted by the moving point source model.
This Article illustrates how a dynamic
knowledge graph approach
in the context of The World Avatar (TWA) project can support the decarbonization
of energy systems by leveraging the existing energy storage system
(ESS) selection framework to assist in the selection and optimal placement
of the ESS. TWA is a dynamic knowledge graph based on the Semantic
Web and its associated technologies, with intelligent agents operating
on it. The agents act autonomously to update and extend TWA, and thus
it evolves in time. TWA also provides the ability to consider different
scenarios, referred to as parallel worlds, allowing for scenario analysis
without mutual interference. A use casethe addition of a battery
energy storage system to the Singapore Jurong Island electrical networkis
introduced to demonstrate the application of this approach. The domain
ontology, OntoPowSys, was extended to describe and instantiate the
relevant ESSs considered in the use case. This extension is described
in the Article using the description logic syntax. The Article also
outlines the details of how the various agents involved in the use
case are being integrated into TWA. The use case also highlights how
the parallel world framework can facilitate scenario analysis by considering
different scenarios without affecting the real-world representation.
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