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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling assisted synthesis of Zr-doped Li 3-x In 1-x Zr x Cl 6 with ultrahigh ionic conductivity for lithium-ion batteries

All-solid-state lithium-ion batteries (ASSLBs) are an important milestone for the future of energy storage because of their capability of impressive energy density and outstanding safety. However, oxide and sulfide solid-state electrolytes (SSEs) suffer from either low ionic conductivity or poor chemical stability. In contrast, halide-based SSEs, are promising as candidate materials owing to high conductivity, good stability, and broad cathode compatibility. Though element doping of the SSEs is an effective and common approach to further improve their electrochemical properties, dopant exploration and optimization through solely experimental trials are both costly and time-consuming. For this aspect, computational simulations for dopant element and concentration screening are adopted in this research and zirconium is selected as a suitable dopant for Li 3 InCl 6 . Further, the synthesized Li 2.75 In 0.75 Zr 0.25 Cl 6 exhibited Li ionic conductivity of 5.82 x 10 -3 Scm -1 at room temperature, which is the highest among reported halide SSEs. The ASSLB formed with Li 2 CoO 2 -Li 2.75 In 0.75 Zr 0.25 Cl 6 -Li/In delivers a high initial capacity of 129.3 mAh∙g -1 . Conclusively, this work provides an effective approach which combines computational modeling and experimental verification for the development of halide SSEs with improved stability and conductivity. The successful design approach and compelling results provide further possibilities and capabilities in future SSE research.

25 ENERGY STORAGE↗
DOE OSTI2020

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Finally, future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1976

Payload/orbiter contamination control requirement study: Computer interface

A preliminary assessment of the computer interface requirements of the Spacelab configuration contamination computer model was conducted to determine the compatibility of the program, as presently formatted, with the computer facilities at MSFC. The necessary Spacelab model modifications are pointed out. The MSFC computer facilities and their future plans are described, and characteristics of the various computers as to availability and suitability for processing the contamination program are discussed. A listing of the CDC 6000 series and UNIVAC 1108 characteristics is presented so that programming requirements can be compared directly and differences noted.

Bareiss, L. E.↗
NASA NTRSDate not supplied

AMMPER: a user-friendly agent-based model that recapitulates simple metabolic responses of yeast to deep-space radiation

For humans venturing to deep space, radiation exposure poses a major health risk. Fundamental research into the biological effects of space radiation are essential for enabling exploration, and the first experimental organisms we send to deep space will be microbial. Yet there are many ways in which microorganisms are likely to experience the effects of high-energy particle radiation (such as Galactic Cosmic Rays) differently from multicellular animals, partly due to the simple fact that microbes are small and unicellular-- less likely to get hit in the first place, and less likely to communicate damage between cells. Computational modeling can aid in designing experiments and predicting the biological effects of radiation, but thus far particle radiation models have not focused on microbes. Here we present the latest developments in AMMPER, the Agent-based Model for Microbial Populations Exposed to Radiation. Originally written in 2021, AMMPER is a Python-based model that incorporates radiation track data from NASA's RITRACKS software and simulates the growth, damage, and death of yeast cells in 3D. It is now freely available as an open-source package on NASA's GitHub repository. Recent improvements include the ability to simulate the dynamics of alamarBlue, a color-changing redox dye commonly used to track metabolic activity in microbial spaceflight experiments. We demonstrate that a simple blue-pink-clear transition model is able to recapitulate key features observed in empirical data from ground studies. AMMPER also includes a new graphical user interface and introductory tutorial to facilitate ease of use by a wider audience. AMMPER can help us to understand how spatially heterogeneous particle radiation damage at the single-cell level can translate to growth differences at the population level, ultimately allowing us to better interpret experiments using microbes as model organisms and how well their results apply to humans.

yeast↗
NASA NTRS2016

A Dual-Plane PIV Study of Turbulent Heat Transfer Flows

Thin film cooling is a widely used technique in turbomachinery and rocket propulsion applications, where cool injection air protects a surface from hot combustion gases. The injected air typically has a different velocity and temperature from the free stream combustion flow, yielding a flow field with high turbulence and large temperature differences. These thin film cooling flows provide a good test case for evaluating computational model prediction capabilities. The goal of this work is to provide a database of flow field measurements for validating computational flow prediction models applied to turbulent heat transfer flows. In this work we describe the application of a Dual-Plane Particle Image Velocimetry (PIV) technique in a thin film cooling wind tunnel facility where the injection air stream velocity and temperatures are varied in order to provide benchmark turbulent heat transfer flow field measurements. The Dual-Plane PIV data collected include all three components of velocity and all three components of vorticity, spanning the width of the tunnel at multiple axial measurement planes.

Turbulent heat transfer↗
NASA NTRS1995

VRA Modeling, phase 1

The destruction of organic contaminants in waste water for closed systems, such as that of Space Station, is crucial due to the need for recycling the waste water. A co-current upflow bubble column using oxygen as the gas phase oxidant and packed with catalyst particles consisting of a noble metal on an alumina substrate is being developed for this process. The objective of this study is to develop a plug-flow model that will predict the performance of this three phase reactor system in destroying a multicomponent mixture of organic contaminants in water. Mass balances on a series of contaminants and oxygen in both the liquid and gas phases are used to develop this model. These mass balances incorporate the gas-to-liquid and liquid-to-particle mass transfer coefficients, the catalyst effectiveness factor, and intrinsic reaction rate. To validate this model, a bench scale reactor has been tested at Michigan Technological University at elevated pressures (50-83 psig,) and a temperature range of 200 to 290 F. Feeds consisting of five dilute solutions of ethanol (approx. 10 ppm), chlorobenzene (approx. 20 ppb), formaldehyde (approx. 100 ppb), dimethyl sulfoxide (DMSO approx. 300 ppb), and urea (approx. 20 ppm) in water were tested individually with an oxygen mass flow rate of 0.009 lb/h. The results from these individual tests were used to develop the kinetic parameter inputs necessary for the computer model. The computer simulated results are compared to the experimental data obtained for all 5 components run in a mixture on the differential test column for a range of reactor contact times.

Kindt, Louis M.↗
DOE OSTI2023

X-ray induced electron and ion fragmentation dynamics in IBr

Characterization of the inner-shell decay processes in molecules containing heavy elements is key to understanding x-ray damage of molecules and materials and for medical applications with Auger-electron-emitting radionuclides. The 1s hole states of heavy atoms can be produced by absorption of tunable x rays and the resulting vacancy decays characterized by recording emitted photons, electrons, and ions. The 1s hole states in heavy elements have large x-ray fluorescence yields that transfer the hole to intermediate electron shells that then decay by sequential Auger-electron transitions that increase the ion’s charge state until the final state is reached. In molecules, the charge is spread across the atomic sites, resulting in dissociation to energetic atomic ions. We have used x-ray/ion coincidence spectroscopy to measure charge states and energies of Iq+ and Brq′+ atomic ions following 1s ionization at the I and Br K-edges of IBr. We present the charge states and kinetic energies of the two correlated fragment ions associated with core-excited states produced during the various steps of the cascades. Here, to understand the dynamics leading to the ion data, we develop a computational model that combines Monte-Carlo/Molecular-Dynamics (MC/MD) simulations with a classical over-the-barrier model to track inner-shell cascades and redistribution of electrons in valence orbitals and nuclear motion of fragments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Modelling and experiments to identify high-risk failure scenarios for testing the safety of lithium-ion cells

Intentionally inducing worst-case thermal runaway scenarios in Li-ion cells on-demand is a definitive way to test the efficacy of battery systems in safely mitigating the consequences of catastrophic failure. An internal short-circuiting (ISC) device is implanted into three 18650 cell designs: one standard, one with a bottom vent, and one with a thicker casing. Through an extensive study of 228 cells, the position at which thermal runaway initiates is shown to greatly affect the tendency of cells to rupture and incur side-wall breaches at specific locations. The risks associated with each failure mechanism and position of the ISC device are quantified using a custom calorimeter that can decouple the heat from ejected and non-ejected contents. Furthermore the causes of high-risk failure mechanisms, such as bursting and side-wall breaches, are elucidated using high-speed synchrotron X-ray imaging at 2000 frames per second and image-based 3D thermal runaway computational models, which together are used to construct a comprehensive description of external risks based on internal structural and thermal phenomena.

25 ENERGY STORAGE↗
DOE OSTI2017

Model Calibration with Censored Data

Here, the purpose of model calibration is to make the model predictions closer to reality. The classical Kennedy-O'Hagan approach is widely used for model calibration, which can account for the inadequacy of the computer model while simultaneously estimating the unknown calibration parameters. In many applications, the phenomenon of censoring occurs when the exact outcome of the physical experiment is not observed, but is only known to fall within a certain region. In such cases, the Kennedy-O'Hagan approach cannot be used directly, and we propose a method to incorporate the censoring information when performing model calibration. The method is applied to study the compression phenomenon of liquid inside a bottle. The results show significant improvement over the traditional calibration methods, especially when the number of censored observations is large.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Long non-coding subgenomic flavivirus RNAs have extended 3D structures and are flexible in solution

Most mosquito-borne flaviviruses, including Zika virus (ZIKV), Dengue virus (DENV), and West Nile virus (WNV), produce long non-coding subgenomic RNAs (sfRNAs) in infected cells that link to pathogenicity and immune evasion. Until now, the structural characterization of these lncRNAs remains limited. Here, we studied the 3D structures of individual and combined subdomains of sfRNAs, and visualized the accessible 3D conformational spaces of complete sfRNAs from DENV2, ZIKV, and WNV by small angle X-ray scattering (SAXS) and computational modeling. The individual xrRNA1s and xrRNA2s adopt similar structures in solution as the crystal structure of ZIKV xrRNA1, and all xrRNA1-2s form compact structures with reduced flexibility. While the DB12 of DENV2 is extended, the DB12s of ZIKV and WNV are compact due to the formation of intertwined double pseudoknots. All 3' stem-loops (3'SLs) share similar rod-like structures. Complete sfRNAs are extended and sample a large conformational space in solution. Our work not only provides structural insight into the function of flavivirus sfRNAs, but also highlights strategies of visualizing other lncRNAs in solution by SAXS and computational methods.

3D structure↗
DOE OSTI2020

Cross-code comparison of the impact of the fill tube on high yield implosions on the National Ignition Facility

Fill tubes are used to inject deuterium and tritium fuel into inertial confinement fusion capsules fielded on the National Ignition Facility. These fill tubes have been shown to have a detrimental effect on capsule performance, primarily by introducing a low-density pathway into the central fuel region that enables the jetting of ablation material into the hot spot. Due to the complexity of the highly nonlinear flow associated with the fill tube and the challenge of diagnosing the evolution of the fill tube jet late in the implosion experiments, the uncertainty in how this perturbation source evolves is great. In this work, we report on the results of a detailed code comparison performed to understand uncertainties in computational modeling of the impact of fill tubes on implosion performance. The study employed two radiation-hydrodynamics codes, HYDRA and xRAGE, which employ very different meshing strategies and hydrodynamics solvers, as well as two radiation transport methodologies, discrete ordinates and multi-group diffusion. Our results demonstrate generally good agreement between codes through most of the implosion although they indicate sensitivity to opacity averaging methods. Late in the implosion, differences arise in the distribution and amount of contaminant although these differences have a remarkably small impact on the amount of yield reduction due to the fill tube. While these results demonstrate sensitivity in fill tube modeling to algorithmic choices, the observed differences between codes are small relative to known sensitivities due to expected variations in the fill tube geometry. Finally, we have developed a methodology for performing multi-group diffusion simulations that show good agreement with the more accurate discrete ordinates method

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

BARC Element Classifier (barc)

SAND2024-02120O This program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. The method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Frank, Michael↗
NASA NTRS2014

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Supercomputing↗
DOE OSTI2022

The effect of polymer stiffness on magnetization reversal of magnetorheological elastomers

Ultrasoft magnetorheological elastomers (MREs) offer convenient real-time magnetic field control of mechanical properties that provides a means to mimic mechanical cues and regulators of cells in vitro. Here, we systematically investigate the effect of polymer stiffness on magnetization reversal of MREs using a combination of magnetometry measurements and computational modeling. Poly-dimethylsiloxane-based MREs with Young’s moduli that range over two orders of magnitude were synthesized using commercial polymers Sylgard™ 527, Sylgard 184, and carbonyl iron powder. The magnetic hysteresis loops of the softer MREs exhibit a characteristic pinched loop shape with almost zero remanence and loop widening at intermediate fields that monotonically decreases with increasing polymer stiffness. A simple two-dipole model that incorporates magneto-mechanical coupling not only confirms that micrometer-scale particle motion along the applied magnetic field direction plays a defining role in the magnetic hysteresis of ultrasoft MREs but also reproduces the observed loop shapes and widening trends for MREs with varying polymer stiffnesses.

36 MATERIALS SCIENCE↗
DOE OSTI2018

On the Information in Spike Timing: Neural Codes Derived from Polychronous Groups

There is growing evidence regarding the importance of spike timing in neural information processing, with even a small number of spikes carrying information, but computational models lag significantly behind those for rate coding. Experimental evidence on neuronal behavior is consistent with the dynamical and state dependent behavior provided by recurrent connections. This motivates the minimalistic abstraction investigated in this paper, aimed at providing insight into information encoding in spike timing via recurrent connections. We employ information-theoretic techniques for a simple reservoir model which encodes input spatiotemporal patterns into a sparse neural code, translating the polychronous groups introduced by Izhike-vich into codewords on which we can perform standard vector operations. Finally, we show that the distance properties of the code are similar to those for (optimal) random codes. In particular, the code meets benchmarks associated with both linear classification and capacity, with the latter scaling exponentially with reservoir size.

computational modeling↗
DOE OSTI2020

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

How do operating conditions affect As(III) removal by iron electrocoagulation?

Iron electrocoagulation (Fe-EC) has been shown to effectively remove arsenic from contaminated groundwater at low cost and has the potential to improve access to safe drinking water for millions of people. Understanding how operating conditions, such as the Fe dosage rate and the O 2 recharge rate, affect arsenic removal at different pH values is crucial to maximize the performance of Fe-EC under economic constraints. In this work, we improved upon an existing computational model to investigate the combined effects of pH, Fe dosage rate, and O 2 recharge rate on arsenic removal in Fe-EC. We showed that the impact of the Fe dosage rate strongly depends on pH and on the O 2 recharge rate, which has important practical implications. We identified the process limiting arsenic removal (As(III) oxidation versus As(V) adsorption) at different pH values, which allowed us to interpret the effect of operating conditions on Fe-EC performance. Finally, we assessed the robustness of the trends predicted by the model, which assumes a constant pH, against lab experiments reproducing more realistic conditions where pH is allowed to drift during treatment as a result of equilibration with atmospheric CO 2 . Furthermore, our results provide a nuanced understanding of how operating conditions impact arsenic removal by Fe-EC and can inform decisions regarding the operation of this technology in a range of groundwaters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗