Aircraft Tail-Specific Performance Modeling for Fuel Efficient Flight Operations in the Cruise Phase

Fuel-efficient flight operations and improved Air Traffic Management (ATM) operations are identified as one of the main pillars in achieving net-zero CO2 emissions by 2050. While considerable research has focused on airspace management and ATM operations, flight operations as managed by airlines have received little attention. <br/><br/>Accurate...

Effect of different uncertainties in medical image segment error estimation: Interactive segmentation of 3D medical images

Although automated segmentation of 3D medical images produce near-ideal results, they encounter limitations and occasional errors, necessitating manual intervention for error correction. Recent studies introduce an active learning pipeline as an efficient solution for this, requiring user corrections only on some of the most uncertain parts of...

Validation of the SU2 Fluid Dynamic Solver for Isentropic Non-Ideal Compressible Flows

This work assessed the accuracy of the SU2 flow solver in predicting the isentropic expansion of Siloxane MM through the converging-diverging nozzle test section of the Organic Rankine Cycle Hybrid Integrated Device (ORCHID) [9]. The expansion is modeled using compressible Euler equations, and assuming adiabatic flow, while the fluid...

Mach Number Estimation and Pressure Profile Measurements of Expanding Dense Organic Vapors

This paper describes an experiment conducted within the nozzle test section of the Organic Rankine Cycle Hybrid Integrated Device (ORCHID) aimed at providing accurate data for the validation of NICFD flow solvers [5]. A supersonic flow of the dense vapor siloxane MM established in the nozzle of the setup was characterized by means of the...

Application of a maritime CFD code to a benchmark problem for non-Newtonian fluids: the flow around a sphere

The ship’s resistance and manoeuvrability in shallow waters can be adversely influenced by the presence of fluid mud layers on the seabed of ports and waterways. Fluid mud exhibits a complex non-Newtonian rheology that is often described using the Herschel–Bulkley model. The latter has been recently implemented in a maritime finite-volume CFD...

Efficient Bayesian Uncertainty Estimation for nnU-Net

The self-configuring nnU-Net has achieved leading performance in a large range of medical image segmentation challenges. It is widely considered as the model of choice and a strong baseline for medical image segmentation. However, despite its extraordinary performance, nnU-Net does not supply a measure of uncertainty to indicate its possible...

Know what it does not know: Improving Offline Deep Reinforcement Learning with Uncertainty Estimation

Offline reinforcement learning, or learning from a fixed data set, is an attractive alternative to online reinforcement learning. Offline reinforcement learning promises to address the cost and safety implications of taking numerous random or bad actions online, which is a crucial aspect of traditional reinforcement learning that makes it...

First Experiments and Commissioning of the ORCHID Nozzle Test Section

This paper reports one of the initial NICFD experiments in the nozzle test section of the ORCHID aimed at providing accurate data for the validation of flow solvers, albeit, at this stage of the research, the focus is limited to inviscid phenomena. Notably, a series of schlieren photographs displaying Mach waves in the supersonic flow of the...

Uncertainty-based Interactive Machine Learning

Interactive machine learning describes a collection of methodologies in which a human user actively participates in a novice agent’s learning process, through providing corrective or evaluate feedback or demonstrative actions. A primary assumption in these methods is that user input is at worst nearoptimal, however a realistic set of...

Ranking uncertainty: Wave climate variability versus model uncertainty in probabilistic assessment of coastline change

Sand nourishments are increasingly applied as adaptive coastal protection measures. Predictions of the evolution of these nourishments and their impact on the surrounding coastline contain many uncertainties. The sources that add to this uncertainty can be delineated between intrinsic and epistemic uncertainty, i.e. inevitably in the system or...

Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of models. One of multi modelling approaches called ...

Bayesian model averaging using particle filtering and Gaussian mixture modeling: Theory, concepts, and simulation experiments

Bayesian model averaging (BMA) is a standard method for combining predictive distributions from different models. In recent years, this method has enjoyed widespread application and use in many fields of study to improve the spread-skill relationship of forecast ensembles. The BMA predictive probability density function (pdf) of any quantity of...

Model and full-scale free-surface viscous flows around fully-appended ships

Two appended hull configurations have been simulated using all hexahedral unstructured grids. Numerical uncertainty is assessed with grid refinement. Influence of turbulence model and wall function approach have also been investigated. Scale effect is also studied for one configuration. Numerical results are validated both with measurement data...