Related papers: Uncertainty quantification for CO2 sequestration a…
Uncertainties from model parameters and model discrepancy from small-scale models impact the accuracy and reliability of predictions of large-scale systems. Inadequate representation of these uncertainties may result in inaccurate and…
Accurately simulating coupled physical processes under uncertainty is essential for reliable modeling and design in performance-critical applications such as combustion systems. Ablative heat shield design, as a specific example of this…
The contamination impact and the migration of the contaminant into the surrounding environment due to the presence of a spilled oil pipeline will cause significant damage to the natural ecosystem. For this reason, it is decisive to develop…
Methods for model parameter estimation, uncertainty quantification and experimental design are summarized in this paper. They are based on the generalized least squares estimator and different approximations of its covariance matrix using…
In situ NMR spectroscopy is a powerful technique to investigate charge storage mechanisms in carbon-based supercapacitors thanks to its ability to distinguish ionic and molecular species adsorbed in the porous electrodes from those in the…
Quantum reservoir computing (QRC) harnesses driven quantum dynamics for time-series processing, yet the mechanisms behind the differing performance levels across its many implementations remain unclear. We show that apparently unrelated…
Interfaces between aqueous electrolytes and nanoporous carbons are involved in a number of technological applications such as energy storage and capacitive deionization. The disordered nature of the carbon materials makes it challenging to…
Aerosol scattering influences the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2). This is especially true for surfaces with reflectance close to a critical value where…
The dynamics for molecule formation, relaxation, diffusion, and desorption on amorphous solid water is studied in a quantitative fashion. We aim at characterizing, at a quantitative level, the formation probability, stabilization, energy…
The growing number of seismic and elastic attributes poses a challenge, making the full benefit from each attribute in characterizing geological formation very difficult, if not impossible. Various approaches are routinely employed to…
Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material's thermodynamic state variables -- specifically pressure, volume/density, energy, and temperature. EOS models are…
A novel method based on Fast Neutron Resonance Transmission Radiography is proposed for non-destructive, quantitative determination of the weight percentages of oil and water in cores taken from subterranean or underwater geological…
Much of uncertainty quantification to date has focused on determining the effect of variables modeled probabilistically, and with a known distribution, on some physical or engineering system. We develop methods to obtain information on the…
The accuracy and robustness of numerical models of geologic CO$_2$ sequestration are almost never quantified with respect to direct observations that provide a ground truth. Here, we conduct CO$_2$ injection experiments in meter-scale,…
We investigate statistical uncertainty quantification for reinforcement learning (RL) and its implications in exploration policy. Despite ever-growing literature on RL applications, fundamental questions about inference and error…
E-fuels are promising long-term energy carriers supporting the net-zero transition. However, the large combinatorial design-operation spaces under renewable uncertainty make the use of mathematical programming impractical for co-optimizing…
Equation-of-state (EOS) models underpin numerical simulations at the core of research in high energy density physics, inertial confinement fusion, laboratory astrophysics, and elsewhere. In these applications EOS models are needed that span…
Reliable uncertainty estimation for 3D object detection is critical for deploying safe autonomous systems, yet modern detectors remain poorly calibrated, especially under distribution shifts. Although post-hoc calibration methods address…
Quantum Reservoir Computing (QRC) uses quantum dynamics to efficiently process temporal data. In this work, we investigate a QRC framework based on two coupled Kerr nonlinear oscillators, a system well-suited for time-series prediction…
This paper presents a joint theoretical and numerical study of a stochastic version of the compressible Navier-Stokes equations within the location uncertainty (LU) framework, applied to problems related to upper ocean vertical mixing. This…