Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Insights into Rad3 kinase recruitment from the crystal structure of the DNA damage checkpoint protein Rad26

Metabolic products and environmental factors constantly damage DNA. To protect against these insults and maintain genome integrity, cells have evolved mechanisms to repair DNA lesions. One such mechanism involves Rad3, a master kinase coordinating the DNA damage response. Rad26 is a functional subunit of the Rad3-Rad26 complex and is responsible for bringing the kinase to sites of DNA damage. Here, I present the crystal structure of Rad26 and identify the elements important for recruiting Rad3. The structure suggests that Rad26 is a dimer with a conserved interface in the N-terminal part of the protein. Biochemical data showed that Rad26 uses its C-terminal domain and the flanking kinase-docking motif to bind specific HEAT repeats in Rad3. Analysis of the reconstituted Rad3-Rad26 heterotetrameric complex with electron microscopy enabled me to propose a structural model for its quaternary structure. Lastly, these results suggest that Rad26 exists as a dimer and provide crucial insight into how Rad3 is recruited and incorporated into the Rad3-Rad26 DNA repair complex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CryoTEN: efficiently enhancing cryo-EM density maps using transformers

Abstract Motivation Cryogenic electron microscopy (cryo-EM) is a core experimental technique used to determine the structure of macromolecules such as proteins. However, the effectiveness of cryo-EM is often hindered by the noise and missing density values in cryo-EM density maps caused by experimental conditions such as low contrast and conformational heterogeneity. Although various global and local map-sharpening techniques are widely employed to improve cryo-EM density maps, it is still challenging to efficiently improve their quality for building better protein structures from them. Results In this study, we introduce CryoTEN—a 3D UNETR++ style transformer to improve cryo-EM maps effectively. CryoTEN is trained using a diverse set of 1295 cryo-EM maps as inputs and their corresponding simulated maps generated from known protein structures as targets. An independent test set containing 150 maps is used to evaluate CryoTEN, and the results demonstrate that it can robustly enhance the quality of cryo-EM density maps. In addition, automatic de novo protein structure modeling shows that protein structures built from the density maps processed by CryoTEN have substantially better quality than those built from the original maps. Compared to the existing state-of-the-art deep learning methods for enhancing cryo-EM density maps, CryoTEN ranks second in improving the quality of density maps, while running >10 times faster and requiring much less GPU memory than them. Availability and implementation The source code and data are freely available at https://github.com/jianlin-cheng/cryoten.

Biochemistry & Molecular Biology↗
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 OSTI2019

Atomically precise, custom-design origami graphene nanostructures

The construction of atomically precise carbon nanostructures holds promise for developing materials for scientific study and nanotechnology applications. Here, we show that graphene origami is an efficient way to convert graphene into atomically precise, complex nanostructures. By scanning tunneling microscope manipulation at low temperature, we repeatedly fold and unfold graphene nanoislands (GNIs) along an arbitrarily chosen direction. A bilayer graphene stack featuring a tunable twist angle and a tubular edge connection between the layers is formed. Folding single-crystal GNIs creates tubular edges with specified chirality and one-dimensional electronic features similar to those of carbon nanotubes, whereas folding bicrystal GNIs creates well-defined intramolecular junctions. Both origami structural models and electronic band structures are computed to complement analysis of the experimental results. The present atomically precise graphene origami provides a platform for constructing carbon nanostructures with engineered quantum properties and, ultimately, quantum machines.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed based on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.

25 ENERGY STORAGE↗
DOE OSTI2015

Rethinking the Default Construction of Multimodel Climate Ensembles

Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process. If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Kronecker-structured covariance models for multiway data

Many applications produce multiway data of exceedingly high dimension. Modeling such multi-way data is important in multichannel signal and video processing where sensors produce multi-indexed data, e.g. over spatial, frequency, and temporal dimensions. We will address the challenges of covariance representation of multiway data and review some of the progress in statistical modeling of multiway covariance over the past two decades, focusing on tensor-valued covariance models and their inference. We will illustrate through a space weather application: predicting the evolution of solar active regions over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Analysis of the NorthStar Inconel 718 Window

NorthStar Medical Radioisotopes, LLC, is planning to produce the important medical radioisotope molybdenum-99 (Mo-99) through photonuclear reactions in molybdenum-100 (Mo-100). In this approach, a target comprising multiple thin disks of enriched molybdenum metal will be bombarded with a 40-MeV electron beam. Because enriched Mo-100 is expensive, there is a desire to utilize as much beam power as possible to achieve maximum production yield and minimize the size of the target. This requirement leads to very high beam power density (heat deposition in the target), which sets challenging requirements for cooling of the target. In the latest concept developed by NorthStar, a stack of target (sintered molybdenum) disks is irradiated from two sides by a 40-MeV electron beam, with a total power of 240 kW (120 kW from each side). As shown in Figure 1, the target disks are cooled by pressurized helium gas flowing through channels between the disks. A housing encloses the target disks and helium coolant. Thinned regions on opposite sides of the housing act as windows, forming the pressure boundary between the helium within the housing and the evacuated beam tube. A pulsed (50-Hz) 40-MeV electron beam is used, with 120 kW total power and a 10% duty cycle. The pulsing beam creates a corresponding cyclic thermal load within the window material. To examine the effects of the cyclic thermal load on the window, a combination of analyses was performed, including computational fluid dynamics (CFD) and finite element analysis (FEA). The analyses presented in this report were primarily performed using the finite element method. However, because of the curved surface of the window, CFD analysis was used to calculate the convective cooling boundary included in the FEA model. Transient thermal and structural models were used to explore the window geometry, including thickness, radius of curvature, and diameter, while staying within the temperature and stress limits of the material as well as maintaining mechanical stability (i.e., avoiding buckling). Additionally, variations in the size and location of the electron beam were evaluated. Multiple parameters for the window and the electron beam were examined throughout the analysis. Upper and lower bounds were established for the window geometry parameters, and limitations were established for the size and position of the electron beam.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Structural analyses of macromolecules by solution scattering (CRADA Final Report)

New innovative Small Angle X-ray Scattering (SAXS) methods to visualized macromolecules in solution at low resolution has led the SIBYLS group at Lawrence Berkeley Lab in being a world leader in biological SAXS. This research is particularly important now as LBNL establishes high-priority research topics including molecular to mesoscale analysis. This new expanding area of research relies on and ties in with our efforts towards developing a solution structure modeling tool for RNA structure prediction. Due to the pandemic our efforts focused on the SARS-CoV-2 proteins and RNA interactions. Specifically, we characterized SARS-CoC-2 proteins interaction with RNA (Wilanowski et al. 2021 -Hammel group) and Nucleoprotein interaction with RNA (Schneidman group).

59 BASIC BIOLOGICAL SCIENCES↗