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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structural dynamics modeling of spent nuclear fuel during hypothetical package drop events

The response of spent nuclear fuel (SNF) to hypothetical package drop events is of particular interest in the scope of spent fuel storage and transportation because of the mechanical shock encountered in such scenarios. Previous testing and modeling by the U.S. Department of Energy has demonstrated that the shock and vibration environment of normal shipping and handling conditions (excluding package drop events) is relatively benign and does not challenge the integrity of spent nuclear fuel. Cask drop events are worth considering because SNF packages are required to withstand free drops onto unyielding surfaces as part of their licensing basis. The acceleration experienced during drop events can be orders of magnitude higher, and thus more advanced models are needed to encompass potential nonlinear behavior of the fuel, such as spacer grid buckling and rod-to-rod impact. This work describes a number of finite element models developed to calculate the response of spent nuclear fuel to various hypothetical drop events that have been validated by package and fuel assembly drop tests conducted in the last decade. Sensitivity of the model response to factors such as package drop orientation, secondary impacts, and irradiated material properties as well as their potential impacts to fuel cladding integrity, was also investigated. Cask drops are not expected as a regular occurrence during SNF transportation, but this work helps raise the understanding of SNF mechanical loads to the point of consistency with the package design requirements.

Kadooka, Kevin↗
DOE OSTI2025

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

**SACLA** A crystallographic pump-power titration was first carried-out with pump laser fluences of 12, 30, 60 and 120 uJ.cm-2 and a time delay of 3 us. Then, a time-series was performed with a pump-laser fluence of 30 uJ.cm-2 (~2.4 absorbed photon per chromophore) and time-delays of 10 ns, 300 ns, 3 µs, 100 us and 3 ms. Finally, two time-delays (10 ns and 3 us) were collected with a pump laser fluence of 12 uJ.cm-2. Raw images, crystFEL streams and merged mtzs are available for all collected dat **SwissFEL** A time series with a pump laser fluence of 30 mJ.cm-2 was performed at time delys of 3 µs and 10 ms. Raw images, crystFEL streams and merged mtzs are available for all collected datasets. Refined detector geometry for each experimental campaign is also provided (crystFEL format)

RIOS-SANTACRUZ, Ronald↗
DOE OSTI2025

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

**SACLA** A crystallographic pump-power titration was first carried-out with pump laser fluences of 12, 30, 60 and 120 ??J.cm-2 and a time delay of 3 ??s. Then, a time-series was performed with a pump-laser fluence of 30 ??J.cm-2 (~2.4 absorbed photon per chromophore) and time-delays of 10 ns, 300 ns, 3 ??s, 100 ??s and 3 ms. Finally, two time-delays (10 ns and 3 ??s) were collected with a pump laser fluence of 12 ??J.cm-2. Raw images, crystFEL streams and merged mtzs are available for all collected dat **SwissFEL** A time series with a pump laser fluence of 30 mJ.cm-2 was performed at time delys of 3 ??s and 10 ms. Raw images, crystFEL streams and merged mtzs are available for all collected datasets. Refined detector geometry for each experimental campaign is also provided (crystFEL format)

RIOS-SANTACRUZ, Ronald↗
DOE OSTI2024

Machine-Learned Linear Structural Dynamics

The tension between accuracy and computational cost is a common thread throughout computational simulation. One such example arises in the modeling of mechanical joints. Joints are typically confined to a physically small domain and yet are computationally expensive to model with a high-resolution finite element representation. A common approach is to substitute reduced-order models that can capture important aspects of the joint response and enable the use of more computationally efficient techniques overall. Unfortunately, such reduced-order models are often difficult to use, error prone, and have a narrow range of application. In contrast, we propose a new type of reduced-order model, leveraging machine learning, that would be both user-friendly and extensible to a wide range of applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Pragmatic Uncertainty Quantification and Propagation in Inverse Estimation of Structural Dynamics Parameters given Material Property Uncertainties and Limited Sensor Data

In this report we demonstrate some relatively simple and inexpensive methods to effectively account for various sources of epistemic lack-of-knowledge type uncertainty in inverse problems. The demonstration problem involves inverse estimation of six parameters of a bolted joint that attaches a kettlebell shaped object to a thick plate. The parameters are efficiently inverted in a modal-based model calibration using gradient-based optimization. Two material properties of the kettlebell are treated as uncertain to within given epistemic uncertainty bounds. We apply and test interval and sparse-sample probabilistic approaches to account for uncertainty in the estimated parameters (and various scalar functionals of the parameters as generic quantities of interest, QOIs) due to uncertainties in the material properties. We also investigate the error effects of limited numbers of vibration sensors (accelerometers) on the kettlebell and plate, and therefore abbreviated excitation/response information in the parameter inversions. We propose and demonstrate a Leave-K-Sensors-Out “cross-prediction” UQ approach to estimate related uncertainties on the parameters and QOI functionals. We indicate how uncertainties from material properties and limited sensors are treated in a combined manner. The economical combined UQ approach involves just three to five samples (i.e. three to five inverse simulations), with no added complication or error/uncertainty from use of surrogate models for affordability. Finally, we describe a related economical UQ approach for handling potential parameter solution non-uniqueness and numerical optimization related precision uncertainties in the estimated parameter values. Indicated further research is identified.

36 MATERIALS SCIENCE↗