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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Applications of Thermochemical Modeling in Molten Salt Reactors

The extensively evaluated and consistent thermodynamic database, the Molten Salt Thermal Properties Database—Thermochemical (MSTDB-TC), was used along with additional thermodynamic values from other sources as examples of ways to examine molten salt reactor (MSR) fuel behavior. Relative stability with respect to halide potential and temperature for likely fuel and fission product components were mapped in Ellingham diagrams for the chloride and fluoride systems. The Ellingham diagrams provide a rich, visual means for identifying halide-forming components in proposed fuel/solvent salt systems. Thermochemical models and values from MSTDB-TC and ancillary sources were used in global equilibrium calculations to provide compositions for a close analysis of the behavior of a possible Molten Chloride Salt Fast Reactor and a Molten Salt Reactor Experiment-type system at high burnup (100 GWd/t). The results illustrated the oxidative nature of burnup in MSRs and provided information about redox behavior and possible control.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Protective effects of intravitreal administration of mesenchymal stem cell-derived exosomes in an experimental model of optic nerve injury

Traumatic optic neuropathy results in the loss of retinal ganglion cells (RGCs), leading to unavoidable visual impairment. However, there is no effective therapy by far. Accumulated studies support the perception that mesenchymal stem cells (MSCs) secrete exosomes that serve as a protective paracrine factor. The study aimed to explore and evaluate the potential therapeutic effects of intravitreal transplantation of MSC-derived exosomes (MSC-exos) in an experimental model of optic nerve crush (ONC). Exosomes were isolated from rat MSCs and characterized by transmission electron microscope and western blotting. At the onset of ONC, a single intravitreal injection of exosomes or PBS was administered to the rats. At day 30, hematoxylin and eosin staining, immunohistochemistry, and βIII-tubulin staining were performed to evaluate the survival of RGCs. Moreover, TUNEL assay was used to examine the apoptosis of RGCs. Inflammation-relevant factors were identified via quantitative polymerase chain reaction. The expression levels of cell apoptosis-related molecules and key members of the PI3K/AKT signaling pathway were determined via western blot analysis. We found that MSC-exos exhibited typical characteristic morphologies (cup-shaped) and sizes (peak size of 93 nm). Furthermore, they exhibited substantial expression of the exosome markers CD63 and TSG101, but lacked the expression of the cellular marker GM130. Treatment with intravitreal MSC-exos notably promoted the survival of RGCs in ONC rats. The level of pro-inflammatory cytokines, including TNF-α, IL-1β, IL-6, IL-8, and MCP-1, were reduced, whereas those of the anti-inflammatory factor IL-10 were increased. Moreover, the apoptosis induced by ONC was decreased by the administration of MSC-exos via upregulation of the Bcl-2/Bax ratio and downregulation of caspase-3 activity. Furthermore, MSC-exos significantly stimulated AKT phosphorylation, whereas LY294002 restored the apoptosis-preventing effects of MSC-exos. The results of our results demonstrated that intravitreal administration of MSC-exos ameliorates ONC-induced injury in a rat model. These findings might aid in the development of effective exosome-based therapeutic strategies for the treatment of optic nerve degeneration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

2023 Real-time Optimization Workflow Status Update

Nuclear integrated energy systems are composed of a diverse set of energy generation sources and exist in dynamic and competitive electricity markets. With the inclusion of thermal energy storage, nuclear power systems can store heat for future use through various processes, such as water desalination or hydrogen generation. This heat storage can be managed in such a way as to economically optimize its usage. By combining real-time price data from the day-ahead and real-time markets with predictive and intelligent models, the charging and discharging of the thermal energy storage may be determined and optimized. This research details an approach through models and systems for the real-time optimization (RTO) of capacity allocation. Virtual models of the energy system and its physics phenomenon and component interactions provide intelligence to verification and prediction of operations. An optimization framework can use data generated from both a set of physical assets as well as the virtual models to predict future performance and create optimization and control workflows. Data warehouse technologies can be used to combine data across models, optimization workflows, market price data, and sensor data to intuitively store various types of data and provide integrations to physical control systems as well as user visualizations. Put together, these components can create a system for the RTO of nuclear integrated energy systems. Various virtual models and bench-scale physical demonstrations have been successfully performed and verified using this system. Larger scale testbeds that include thermal energy storage systems have been identified as future opportunities. A gap analysis that details the steps necessary to reach a physical demonstration at this scale is provided, along with conclusions on the current effort and future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2012

Comparison of MSL RCS Jet Computations With Flow Visualization and Velocimetry

Numerical predictions of the Mars Science Laboratory (MSL) reaction control system (RCS) jets interacting with a Mach 10 hypersonic flow are compared to experimental nitric oxide (NO) planar laser-induced fluorescence (PLIF) data. The steady Reynolds Averaged Navier Stokes (RANS) equations using the Baldwin-Barth one-equation turbulence model were solved using the OVERFLOW code. The experimental PLIF data used for comparison consists of qualitative two-dimensional visualization images, qualitative reconstructed three-dimensional flow structures, and quantitative two-dimensional distributions of streamwise velocity. Through modeling of the PLIF signal equation, computational flow images (CFI) were produced and directly compared to the qualitative PLIF data. Post processing of the experimental and simulation data enabled the jet trajectory to be extracted for a more quantitative comparison. The two-dimensional velocity fields were reconstructed through interpolation of a series of single-component velocity profiles. Each distribution of single-component velocity was obtained using molecular tagging velocimetry (MTV). After validating the numerical model, the numerical solution was further examined to gain insight into hypersonic jet-in-crossflow interaction. Future NO-PLIF experiments are proposed based on this analysis.

Johansen, Craig T.↗
NASA NTRS1985

Correlation and analysis of oil flow data for an air-breathing missile model

This paper will present the results of an oil flow investigation on an airbreathing missile model. This oil flow study examined the flow around the model, which can be configured with both axisymmetric and two-dimensional inlets. Flow visualization analyses were conducted for both types of geometries by examining the surface flow patterns made visible by the oil flows for Mach numbers of 2.5 and 3.95. The analysis has shown the extent of flow spillage around the inlet which has helped explain the force and moment data collected during previous testing of the model. The oil flow data has also been used to develop guidelines for modeling the location of the crossflow separation line along inlet fairings. Finally, the oil flow analysis has been used to identify unique features of the boattail flow. These boattail flow characteristics have been correlated with previous oil flow analysis of noncircular body models. This paper demonstrates the use of this type of oil flow analysis in developing missile flow field analysis and aerodynamic predictions ranging from impact angle methods through Navier-Stokes methods.

Stoy, S. L.↗
NASA NTRSDate not supplied

A Theoretical Model of Static and Dynamic Field-of-View (FOV) using NASA's Neutral Buoyancy Laboratory (NBL)

Developing an objective field-of-view methodology for studying vehicle window placement has been somewhat difficult. It is not surprising that considerable effort has been directed at specific problems of visibility from vehicles. Aeronautical design engineers know when designing an aircraft cockpit, the pilot must have an adequate view for approaching and landing on an airfield. However, compromise between the ergonomic preference for the largest possible viewing envelope and the practicalities of arranging a structure that is lightweight and strong will always plague the cockpit’s transparent area’s size and shape. The human’s visual sense, when operating any kind of vehicle, is the main source of the vast majority of information needed to drive or fly safely. However, vehicle design can affect a driver’s visual performance for satisfying their need for information. For any vehicle, be it an automobile or a spacecraft, the visibility quantity is the sum total of the visual access to the environment as defined by the window placement of that vehicle. The Alternate Multiple Mission Space Exploration Vehicle (AMMSEV) configuration is much like a large cargo truck where there is no direct visual access to the rear of the vehicle or the rear sides of the vehicle; thus, making the forward and side views of greater importance to the situational awareness of the crew if obstructions are creating visual issues. The National Aeronautics and Space Administration (NASA) tested a new theoretical model for Field-of-View (FOV) of spacecraft windows in NASA’s own Neutral Buoyancy Laboratory (NBL). The NBL is an essential tool for design, testing and development of future space exploration hardware for upcoming NASA operational missions. Using water, with its natural propensity for giving a human the perception of dynamic body motion under a weightless or partial gravity conditions, gives human factors investigators a vigorous space-like environment to study new methods of collecting dynamic field-of-view for future exploration vehicle designs.

Human Factors↗
NASA NTRS2007

A Conceptual Aerospace Vehicle Structural System Modeling, Analysis and Design Process

A process for aerospace structural concept analysis and design is presented, with examples of a blended-wing-body fuselage, a multi-bubble fuselage concept, a notional crew exploration vehicle, and a high altitude long endurance aircraft. Aerospace vehicle structures must withstand all anticipated mission loads, yet must be designed to have optimal structural weight with the required safety margins. For a viable systems study of advanced concepts, these conflicting requirements must be imposed and analyzed early in the conceptual design cycle, preferably with a high degree of fidelity. In this design process, integrated multidisciplinary analysis tools are used in a collaborative engineering environment. First, parametric solid and surface models including the internal structural layout are developed for detailed finite element analyses. Multiple design scenarios are generated for analyzing several structural configurations and material alternatives. The structural stress, deflection, strain, and margins of safety distributions are visualized and the design is improved. Over several design cycles, the refined vehicle parts and assembly models are generated. The accumulated design data is used for the structural mass comparison and concept ranking. The present application focus on the blended-wing-body vehicle structure and advanced composite material are also discussed.

Mukhopadhyay, Vivek↗
DOE OSTI2021

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗
NASA NTRS1975

Flow visualization study of close-coupled canard wing and strake wing configuration

The Langley 1/8-scale V/STOL model tunnel was used to qualitatively determine the flow fields associated with semi-span close coupled canard wing and strake wing models. Small helium filled bubbles were injected upstream of the models to make the flow visible. Photographs were taken over the angle-of-attack ranges of -10 deg to 40 deg.

Miner, D. D.↗
NASA NTRS1994

Parallelization and visual analysis of multidimensional fields: Application to ozone production, destruction, and transport in three dimensions

Atmospheric modeling is a grand challenge problem for several reasons, including its inordinate computational requirements and its generation of large amounts of data concurrent with its use of very large data sets derived from measurement instruments like satellites. In addition, atmospheric models are typically run several times, on new data sets or to reprocess existing data sets, to investigate or reinvestigate specific chemical or physical processes occurring in the earth's atmosphere, to understand model fidelity with respect to observational data, or simply to experiment with specific model parameters or components.

Schwan, Karsten↗
NASA NTRS1988

Tropical synoptic signatures in composited 6.7 micrometer water vapor imagery

A model of the signatures of a synoptic development as seen in 6.7-micron water vapor channel imagery has been constructed from a composite of cases for a moisture burst over the eastern Pacific Ocean. The characteristics revealed in these composites are discussed and compared with the signatures of the moisture bursts as seen in satellite-derived visual and window channel IR imagery. A test of the forecast capability of the model was performed on 120 consecutive days, including 29 moisture bursts. After 2 hours of training, a meteorologist was able to forecast 19 (65 percent) of the bursts at least 24 hours in advance. In 6 cases, bursts were forecast when none occurred.

Thompson, A. H.↗
DOE OSTI2022

Towards Net Zero: Modeling Approach to the Right-Sized Facilities

As the concentration of greenhouse gases (GHGs) in the atmosphere increases, the concerns about carbon emissions are growing. Several net-zero initiatives are taking place around the globe to achieve a balance between the GHGs put into the atmosphere and those taken out. While most efforts present a sectorized approach, this paper describes the importance of integrating information across different sectors for effective modeling of carbon emissions and holistic reduction opportunity analysis. Using the Idaho National Laboratory (INL) campus as a test case, this work provides a web-based tool for INL stakeholders to use when engaging in strategic planning to achieve carbon emissions reduction. This net-zero engineering support tool (NEST) uses historical data as foundational information for applying the modeling framework. Prediction of CO 2 emissions throughout project completion integrates various approaches and schedules aimed at energy conservation, fleet decarbonization, and other GHG reduction activities. Using NEST, stakeholders can visualize carbon emissions, electricity consumption, and costs for decision making when planning the pathway for reaching carbon net zero. The INL’s initiative to transition into an EV fleet was used to demonstrate the developed framework and the advantages of using NEST. It was shown that electrifying different fossil-fueled campus vehicles before 2030 with aggressive replacement schedules require high annual capital expenditure (CAPEX), which may not be available. The tool allows decision makers to test different replacement schedules and prioritize those that yield CAPEX below a certain threshold while meeting target milestones. While the demonstration focused on vehicle electrification, the developed framework lays the foundation for further quantitative analysis of other GHG reduction activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Some Basic GN&C Modeling-and-Design Gap Areas for Low-Gee Slosh: Comparisons to Powered Flight Slosh

Potential gaps between powered-flight slosh and near-zero-gee slosh modeling intuition ... - Extremely-basic items like inertia (which is a strong function of frequency and liquid depth) - Visualization of response – ability to form a physical picture via mechanical analog - Availability of frequency-domain design insight from open-loop plant - Sense for edge-of model-validity – how does it behave “at the edges” And some suggestions on how NASA can help

Guidance Navigation and Control Modeling and Desig↗
NASA NTRS1978

A surface flow visualisation technique for use in cryogenic wind tunnels

A method of surface flow visualization for use in cryogenic wind tunnels is described which requires injection of a cryogenic liquid onto the model while the tunnel is running. This necessitates the use of a substance that remains liquid over a large range of cryogenic wind tunnel operating temperatures. It is found that propane (C3H8) is a suitable substance. Experiments are conducted in a subsonic cryogenic wind tunnel to assess the practical application of liquid propane flow visualization. The propane is stored in a chamber cooled by liquid nitrogen and when required is pumped through pipes to a gallery inside the model and then out onto the surface through small holes. To color the liquid a suspension of pigment particles is used. Propane is supplied to the cooled chamber in gaseous form from a standard liquefied gas cylinder. The sequence of events is illustrated on a propane temperature-entropy diagram. The use of liquefied propane for flow visualization in a cryogenic tunnel operating at pressures up to 40 atm appears to be feasible. Illustrative examples are provided.

Kell, D. M.↗
DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Review of planar laser-induced fluorescence measurements in the NASA Langley 31-Inch Mach 10 Air Tunnel

In 2003 a mobile planar laser-induced fluorescence (PLIF) system was constructed at NASA Langley Research Center to visualize and quantify high speed flow fields containing fluorescent species such as nitric oxide (NO). Thereafter, a series of test entries utilizing NO PLIF were conducted in the NASA Langley Research Center’s 31 Inch Mach 10 air wind tunnel, which is a hypersonic blowdown wind tunnel located in Hampton, Virginia. This paper briefly reviews laser-based measurements previously performed in hypersonic blowdown wind tunnel facilities and then details NO PLIF measurement campaigns performed at this facility in the 20 years to date. Measurements were performed to develop 2D and 3D visualization capabilities and quantitatively measure velocity and temperature. Applications described herein include historical models (e.g., Apollo, X-33 and X-43), flight vehicles under development at the time (e.g., Mars Science Lab (MSL), Orion, and LOFTID), as well as fundamental research (e.g., flat plates with and without discrete roughness).

PLIF↗
NASA NTRS2009

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Zaychik, Kirill↗
DOE OSTI2021

A Modularized Urban Scale Building Energy Modeling Framework Designed with An Open Mind

In recent years, physics-based building energy modeling (BEM) has started being used to evaluate the performance of buildings in the context of connected communities and on an urban scale to study their aggregated energy use, interactions, and impacts on the energy supply infrastructure and environment. The development of urban-scale BEM solutions needs extensive effort. Existing attempts tend to focus on different aspects of BEM on an urban scale, such as collecting as-built building data from different information sources, integrating geometry modeling with geographic information systems (GISs), representing operational and occupancy profiles, automating workflow, processing and visualizing the results, and conducting large-scale simulations. Urban-scale BEM development would benefit from multi-disciplinary research areas and from an open platform to adopt advancements on data sources and tools. For these purposes, this research proposes a modularized bottom-up model creation and simulation framework that is built on the state-of-the-art BEM tools and can accommodate different building stock data. This framework uses a standardized schema to describe building design and operational characteristics, and it can be instantiated from different building survey datasets with heterogeneous structures. The paper demonstrates how thousands of surveyed buildings from the 2012 U.S. Energy Information Administration’s Commercial Buildings Energy Consumption Survey (CBECS) were one-to-one converted to EnergyPlus models through the schema and the model generation process, then simulated with distributed computing, and their results are summarized.

Lei, Xuechen↗