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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 271 records · Page 15

Nuclear Material Process Modeling at the Y-12 National Security Complex

Dynamic simulation modeling is used at Y-12 to evaluate and forecast nuclear material inventories and production capacities to ensure that future supply can meet mission demand. Model outputs are analyzed by numerous Y-12 organizations and programs and coordinated with NNSA’s Office of Secondary Stage Production Modernization. Data-driven decisions for both short-term and long-term strategic planning for Y-12 mission execution are informed by the model. Dynamic simulation modeling capabilities for Y-12 nuclear material production continue to be expanded and refined.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Space Systems Integrated Simulation (SPASIS)

Complex program models everything on user-defined space station, from control gyros to mass effect of astronaut moving along strut. Other features include plume impingement, attitude control, propellant slosh, docking, and gravity.

Stecklein, J. M.↗

Hardware Fault Simulator Generates Test Vectors For Complex IC's

Report describes technique using fault simulator implemented entirely in hardware to generate and optimize test vectors for microprocessor. Hardware fault simulator approach reduces test time, while maintaining high reliability in detecting faults.

Timoc, C. C.↗

Synergistic foam stabilization and transport improvement in simulated fractures with polyelectrolyte complex nanoparticles: Microscale observation using laser etched glass micromodels

Inaccessibility to direct pore scale observation in hydrocarbon recovery of tight shale formations poses a great challenge to water-energy nexus initiatives and necessitates the use of high throughput technologies to emulate environmentally friendly processes. Herein, we employ a precise glass micromodel fabrication and visualization method to isolate the supercritical CO 2 bubbles surrounded by CO 2 -water lamella prepared in saline produced water stabilized with molecular complexation of zwitterionic surfactants (ZS) and polyelectrolyte complex nanoparticles (PECNP). The Selective Laser Enhanced Etching (SLE) technique was selected for micromodel simulation of high-pressure flow. Two representative designs, (1) fracture/micro-crack network 28 and (2) fracture/matrix were etched on fused silica glass with a laser printing machine and scCO 2 foam was injected to study the foamability, propagation, stability, and fluid loss properties. The highly monodispersed and uniformly distributed array of scCO 2 bubbles were detected in flow of scCO 2 foam in highly saline brine containing ionic complexes of positively charged PECNPs and ZS, whereas foam flow with the lamella containing ZS in fractures offered a noticeably large and polydisperse array of scCO 2 bubbles. scCO 2 bubble motion and deformation were traced, and local description of foam flow was visually examined. The confined array of scCO 2 bubbles stabilized by ZS in microcracks was affected by bubble growth and coalescence, whereas the super-populated array of monodispersed scC O2 bubbles with lamella containing complexes of PECNP and ZS were able to fill the channels with stable configurations within the timeframe of comparative stability measurements. The ability of complex fluid to prevent the formation damage was evaluated through fluid loss visualization in micromodels. Probing scCO 2 foam transport in homogenous porous media revealed smaller volume leak-off for scCO 2 foam containing PECNP-ZS ionic complexes.

04 OIL SHALES AND TAR SANDS↗

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

Scientific data from precipitation driver response model intercomparison project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

54 ENVIRONMENTAL SCIENCES↗

Scientific Data From Precipitation Driver Response Model Intercomparison Project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project

Precipitation Driver Response Model Intercompariso↗

LongRunMIP - Motivation and Design for a Large Collection of Millennial-Length AO-GCM Simulations

LongRunMIP is the first collection of millennial-length simulations of complex coupled climate models and enables investigations of how these models equilibrate in response to radiative perturbations.We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1000+ year) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time-and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1000 years. LongRunMIP is a MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields, and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of summer 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submission of more simulations in the future.

Maria Rugenstein↗

Effects of Simulated Microgravity and LINC-Complex on Chromosome 8 of Human Mammary Cells

Previously, human breast epithelial cells were studied under simulated microgravity to determine the role of the LINC-complex in maintaining nuclear morphology and gene expression. Data from that study was used in this project to understand how the LINC-complex influences gene expression at chromosome 8 under simulated microgravity. Differentially expressed genes found in clusters typically indicate a molecular relationship amongst them. Visual and data analyses (GO, pathways) identified 51 genes within clusters on chromosome 8 across various simulated microgravity conditions that did not share any molecular relationship. Additional results also determined that cells with a disrupted LINC-complex experienced more differential gene expression than the control, and that extended periods of simulated microgravity exacerbated differential gene expression in chromosome 8 of LINC-disrupted cells. These results suggest that the stressful simulated microgravity environment coupled with disrupted biological processes, such as in the case of the LINC-complex, can increase differential gene expression in chromosomes. Future studies where additional analyses are performed to further analyze gene expression of clusters under simulated microgravity could potentially elucidate the molecular relationship amongst affected genes.

Simulated microgravity↗

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗

Computational engine structural analysis

A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for problem-specific application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include: (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3) blade-loss transient response, (4) rotor/stator/squeeze-film/bearing interaction, (5) blade-fragment/rotor-burst containment, and (6) structural behavior of advanced swept turboprops. These representative case studies are selected to demonstrate the breath of the problems analyzed and the role of the computer including post-processing and graphical display of voluminous output data.

Chamis, C. C.↗

Computational engine structural analysis

A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for problem-specific application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include: (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3) blade-loss transient response, (4) rotor/stator/squeeze-film/bearing interaction, (5) blade-fragment/rotor-burst containment, and (6) structural behavior of advanced swept turboprops. These representative case studies are selected to demonstrate the breath of the problems analyzed and the role of the computer including post-processing and graphical display of voluminous output data.

Chamis, C. C.↗

In Silico Methods for Space System Analysis: Optical Link Coding Performance and Lunar Terrain Masks

As deep space links migrate toward higher frequency bands like 𝐾𝑎 and optical, thor- ough trade-space exploration becomes increasingly valuable for designing reliable and efficient communications systems. In this contribution, we leveraged high-performance, concurrent simulations when the run-time complexity of simulation software overwhelms capabilities of ordinary desktop machines. The first part of this manuscript describes how to run error correcting code simulations concurrently on a high-performance supercomputer. The second part of this study describes a framework to produce azimuth and elevation terrain masks from imagery of the Lunar South Pole.

Michels, Dominik L↗

Simulations of Instabilities in Complex Valve and Feed Systems

CFD analyses are playing an increasingly important role in identifying and characterizing flow induced instabilities in rocket engine test facilities and flight systems. In this paper, we analyze instability mechanisms that range from turbulent pressure fluctuations due to vortex shedding in structurally complex valve systems to flow resonance in plug cavities to large scale pressure fluctuations due to collapse of cavitation induced vapor clouds. Furthermore, we discuss simulations of transient behavior related to valve motion that can serve as guidelines for valve scheduling. Such predictions of valve response to varying flow conditions is of crucial importance to engine operation and testing.

Ahuja, Vineet↗

The Laboratory Production of Complex Organic Molecules in Simulated Interstellar Ices

Much of the volatiles in interstellar dense clouds exist in ices surrounding dust grains. Their low temperatures preclude most chemical reactions, but ionizing radiation can drive reactions that produce a suite of new species, many of which are complex organics. The Astrochemistry Lab at NASA-Ames studies the UV radiation processing of interstellar ice analogs to better identify the resulting products and establish links between interstellar chemistry, the organics in meteorites, and the origin of life on Earth. Once identified, the spectral properties of the products can be quantified to assist with the search for these species in space. Of particular interest are findings that UV irradiation of interstellar ice analogs produces molecules of importance in current living organisms, including quiriones, amphiphiles, and amino acids. Quinones play a variety of roles including electron transport and are used by all organisms. Studies show that quinones should be made wherever polycyclic aromatic hydrocarbons are irradiated in interstellar ices (Bernstein et al. 2001). Amphiphiles are also made when mixed molecular ices are irradiated. These amphiphiles self-assemble into membrane-walled vesicles when put in liquid water (Dworkin et al. 2001). Ice irradiation can also produce (Bernstein et al. 2002) and destroy amino acids (Ehrenfreund et al. 2001). Many of the same processes thought to make organics in space should yield products highly enriched in deuterium (D) (Sandford et al. 2001). The high D/H ratios in some interstellar species, and the knowledge that many of the organics in primitive meteorites are D-enriched, suggests that such linkages do exist. By using D as a tracer, we expect to learn more about the different chemical processes occurring in space and their relative importance in the production of different organic compounds and delivery to planetary surfaces.

Dworkin, Jason P.↗

The Laboratory Production of Complex Organic Molecules in Simulated Interstellar Ices

Much of the volatiles in interstellar dense clouds exist in ices surrounding dust grains. Their low temperatures preclude most chemical reactions, but ionizing radiation can drive reactions that produce a suite of new species, many of which are complex organics. The Astrochemistry Lab at NASA Ames studies the UV radiation processing of interstellar ice analogs to better identify the resulting products and establish links between interstellar chemistry, the organics in meteorites, and the origin of life on Earth. Once identified, the spectral properties of the products can be quantified to assist with the search for these species in space. Of particular interest are findings that UV irradiation of interstellar ice analogs produces molecules of importance in current living organisms, including quinones, amphiphiles, and amino acids.

Dworkin, J. P.↗

On the large eddy simulation of turbulent flows in complex geometry

Application of the method of Large Eddy Simulation (LES) to a turbulent flow consists of three separate steps. First, a filtering operation is performed on the Navier-Stokes equations to remove the small spatial scales. The resulting equations that describe the space time evolution of the 'large eddies' contain the subgrid-scale (sgs) stress tensor that describes the effect of the unresolved small scales on the resolved scales. The second step is the replacement of the sgs stress tensor by some expression involving the large scales - this is the problem of 'subgrid-scale modeling'. The final step is the numerical simulation of the resulting 'closed' equations for the large scale fields on a grid small enough to resolve the smallest of the large eddies, but still much larger than the fine scale structures at the Kolmogorov length. In dividing a turbulent flow field into 'large' and 'small' eddies, one presumes that a cut-off length delta can be sensibly chosen such that all fluctuations on a scale larger than delta are 'large eddies' and the remainder constitute the 'small scale' fluctuations. Typically, delta would be a length scale characterizing the smallest structures of interest in the flow. In an inhomogeneous flow, the 'sensible choice' for delta may vary significantly over the flow domain. For example, in a wall bounded turbulent flow, most statistical averages of interest vary much more rapidly with position near the wall than far away from it. Further, there are dynamically important organized structures near the wall on a scale much smaller than the boundary layer thickness. Therefore, the minimum size of eddies that need to be resolved is smaller near the wall. In general, for the LES of inhomogeneous flows, the width of the filtering kernel delta must be considered to be a function of position. If a filtering operation with a nonuniform filter width is performed on the Navier-Stokes equations, one does not in general get the standard large eddy equations. The complication is caused by the fact that a filtering operation with a nonuniform filter width in general does not commute with the operation of differentiation. This is one of the issues that we have looked at in detail as it is basic to any attempt at applying LES to complex geometry flows. Our principal findings are summarized.

Ghosal, Sandip↗

Complex Organics from Laboratory Simulated Interstellar Ices

Many of the volatiles in interstellar dense clouds exist in ices surrounding dust grains. The low temperatures of these ices (T < 50 K) preclude most chemical reactions, but photolysis can drive reactions that produce a suite of new species, many of which are complex organics. We study the UV and proton radiation processing of interstellar ice analogs to explore links between interstellar chemistry, the organics in comets and meteorites, and the origin of life on Earth. The high D/H ratios in some interstellar species, and the knowledge that many of the organics in primitive meteorites are D-enriched, suggest that such links are plausible. Once identified, these species may serve as markers of interstellar heritage of cometary dust and meteorites. Of particular interest are our findings that UV photolysis of interstellar ice analogs produce molecules of importance in current living organisms, including quinones, amphiphiles, and amino acids. Quinones are essential in vital metabolic roles such as electron transport. Studies show that quinones should be made wherever polycyclic aromatic hydrocarbons are photolyzed in interstellar ices. In the case of anthracene-containing ices, we have observed the production of 9-anthrone and 9,10 anthraquinone, both of which have been observed in the Murchison meteorite. Amphiphiles are also made when mixed molecular ices are photolyzed. These amphiphiles self-assemble into fluorescent vesicles when placed in liquid water, as do Murchison extracts. Both have the ability to trap an ionic dye. Photolysis of plausible ices can also produce alanine, serine, and glycine as well as a number of small alcohols and amines. Flash heating of the room temperature residue generated by such experiments generates mass spectral distributions similar to those of IDPs. The detection of high D/H ratios in some interstellar molecular species, and the knowledge that many of the organics, such as hydroxy and amino acids, in primitive meteorites are D-enriched provides evidence for a connection between intact organic material in the interstellar medium and in meteorites. Thus, some of the oxidized aromatics, amphiphiles, amino acids, hydroxy acids, and other compounds found in meteorites may have had an interstellar ancestry and not solely a product of parent body aqueous alteration. Such compounds should also be targeted for searches of organics in cometary dust.

Dworkin, J. P.↗