An Advanced Discrete Fracture Methodology for Fast, Robust, and Accurate Simulation of Energy Production From Complex Fracture Networks

Fracture networks are abundant in subsurface applications (e.g., geothermal energy production, CO₂ sequestration). Fractured reservoirs often have a very complex structure, making modeling flow and transport in such networks slow and unstable. Consequently, this limits our ability to perform uncertainty quantification and increases...

Uncertainty Tracking and Geotechnical Reliability Updating Using Bayesian Networks

Bayesian networks are proposed as a tool to integrate reliability and influential variables relating to the slope stability of an idealized embankment. The site investigation (extent) and slope geometry, as well as the material properties and their spatial variability, are considered within a Bayesian network. The random finite element method ...

From Deterministic to Generative: Multimodal Stochastic RNNs for Video Captioning

Video captioning, in essential, is a complex natural process, which is affected by various uncertainties stemming from video content, subjective judgment, and so on. In this paper, we build on the recent progress in using encoder-decoder framework for video captioning and address what we find to be a critical deficiency of the existing...

Strategic Modeling of Global Container Transport Networks: Exploring the future of port-hinterland and maritime container transport networks

Uncertainties in future global trade flows due to changes in trade agreements, transport technologies or sustainability policies, will affect the patterns of global freight transport and, as a consequence, also affect the demand for major freight transport infrastructures such as ports and hinterland networks. Policy makers face the challenge of...

Uncertainty assessment in coastal morphology prediction with a bayesian network

In the present time of sea-level rise and climate change a global shift has occurred toward sandy coastal protection measures and Building with Nature. These type of protection measures impose extra uncertainty on the instantaneous state of the coastal system over time for which present deterministic forecasting techniques are not capable of...

Non-deterministic networked infrastructure design of multiple sources and multiple sinks

Networked infrastructures such as gas and water pipelines, roads, railroads or power grids provide essential utilities and services to society. Common characteristics of such infrastructures include high capital costs, generally long lifetimes and irreversibility once the construction of such networks have finished. In the design of these...

Designing Networked Energy Infrastructures with Architectural Flexibility

Development of networked energy infrastructures (like gas pipe networks), generally requires a significant amount of capital investment under resources, market and institutional uncertainties. Several independent suppliers and consumers are to be connected into these networks. However, the actual commitment of these parties and the capacities...

Development of a system for 'Sustainable Fuel from Digested Manure' Financial feasibility study for the Salland region

A financial feasibility study into the development of a 'sustainable fuel from digested manure' system for the Salland region within the Province of Overijssel in the Netherlands. This is a specific variant of a green gas hub system, which produces sustainable fuel as end product. To deal with challenges and uncertainties in the development the ...

Using an agent-based model for analysing the robustness of a syngas cluster

Future price developments and availability of energy resources are uncertain. Therefore, developers of energy infrastructures will have to consider different scenarios in their planning. Moreover, the implementation of large infrastructures requires the cooperation of several actors, which adds to the uncertainty. In this paper we describe the...

Discovery of high-level tasks in the operating room

Recognizing and understanding surgical high-level tasks from sensor readings is important for surgical workflow analysis. Surgical high-level task recognition is also a challenging task in ubiquitous computing because of the inherent uncertainty of sensor data and the complexity of the operating room environment. In this paper, we present a...