The route by which gas-phase molecules in hydrocarbon flames form condensed-phase
carbonaceous nanoparticles (incipient soot) is reviewed. These products of incomplete …

The field of machine learning is comprised of techniques, which have proven powerful
approaches to knowledge discovery and construction of 'digital twins' in the highly …

This paper introduces a dynamic knowledge-graph approach for digital twins and illustrates
how this approach is by design naturally suited to realizing the vision of a Universal Digital …

Heterogeneous data, different definitions and incompatible models are a huge problem in
many domains, with no exception for the field of energy systems analysis. Hence, it is hard to …

Modern research methods produce large amounts of scientifically valuable data. Tools to
process and analyze such data have advanced rapidly. Yet, access to large amounts of high …

Coke oven gas (COG) is an important energy resource that rich in hydrogen and methane,
which is conventionally used for industrial heating but is embarking on high-quality …

This paper presents a dynamic geospatial knowledge graph as part of The World Avatar
project, with an underlying ontology based on CityGML 2.0 for three-dimensional …

Web ontologies are important tools in modern scientific research because they provide a
standardized way to represent and manage web-scale amounts of complex data. In …

This paper investigates the usage of knowledge graphs to bridge the gap between current
data silos in deriving a holistic perspective on the impact of flooding. It builds on the idea of …

Digitalization and concepts such as digital twins (DT) are expected to have huge potential to
improve efficiency in industry, in particular, in the energy sector. Although the number and …