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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mesoscale system feedback-induced dissipation and noise suppression

A high-gain and low-noise negative feedback control (“feedback control”) system can detect charge transfer in quantum systems at room temperatures. The feedback control system can attenuate dissipative coupling between a quantum system and its thermodynamic environment. The feedback control system can be integrated with standard commercial voltage-impedance measurement system, for example, a potentiostat. In one aspect, the feedback control system includes a plurality of electrodes that are configured to electrically couple to a sample, and a feedback mechanism coupled to a first electrode of the plurality of electrodes. The feedback mechanism is configured to detect a potential associated with the sample via the first electrode. The feedback mechanism provides a feedback signal to the sample via a second electrode of the plurality of electrodes, the feedback signal is configured to provide excitation control of the sample at a third electrode of the plurality of electrode.

Gupta, Chaitanya↗
DOE OSTI2023

Understanding grain boundary segregation under irradiation: A mesoscale modeling study

Grain boundaries (GBs) are an important component in the design of irradiation resistant materials as they play a crucial role as point defect sinks for non-equilibrium vacancies and self-interstitials. However, in the presence of sustained point defect fluxes, the coupled transport of atomic components with inherently different diffusivities often leads to radiation-induced segregation (RIS), with undesired effects on properties such as intergranular corrosion and stress-assisted cracking. In this talk, we investigate the fundamental mechanisms leading to GB segregation in BCC FeCr-based alloys using multiscale modeling and experiments. A phase-field model is employed to account for both thermodynamic and kinetic segregation mechanisms. The full Onsager transport matrix is derived using kinetic Monte Carlo, molecular dynamics, and kinetic cluster expansion (KineCluE) calculations. The thermodynamics of GB segregation is described via an atomic density-based modification to the CALPHAD free energy. The modeling predictions are then compared against segregation data from atom probe characterization for various temperatures, compositions, and neutron irradiation conditions. We will conclude by discussing the utility of the multiscale modeling approach to shed light on the fundamental mechanisms leading to solute-GB interaction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗
DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗