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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Reynolds number effects on mixing due to topological chaos

Topological chaos has emerged as a powerful tool to investigate fluid mixing. While this theory can guarantee a lower bound on the stretching rate of certain material lines, it does not indicate what fraction of the fluid actually participates in this minimally mandated mixing. Indeed, the area in which effective mixing takes place depends on physical parameters such as the Reynolds number. To help clarify this dependency, we numerically simulate the effects of a batch stirring device on a 2D incompressible Newtonian fluid in the laminar regime. In particular, we calculate the finite time Lyapunov exponent (FTLE) field for three different stirring protocols, one topologically complex (pseudo-Anosov) and two simple (finite-order), over a range of viscosities. After extracting appropriate measures indicative of both the amount of mixing and the area of effective mixing from the FTLE field, we see a clearly defined Reynolds number range in which the relative efficacy of the pseudo-Anosov protocol over the finite-order protocols justifies the application of topological chaos. More unexpectedly, we see that while the measures of effective mixing area increase with increasing Reynolds number for the finite-order protocols, they actually exhibit non-monotonic behavior for the pseudo-Anosov protocol.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Comprehensive computational design of ordered peptide macrocycles

Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with l -amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of l - and d -amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.

Hosseinzadeh, Parisa (ORCID:0000000231287433)↗
DOE OSTI2017

Polyphosphazene polymer development for mixed matrix membranes using SIFSIX-Cu-2 i as performance enhancement filler particles

Phosphazene-based polymers were synthesized by using different pendant groups such as trifluoroethoxy (TFE), phenoxy (PHO) and octafluoropentoxy (OFP). High performance methoxyethoxyethoxy/cyclohexoxy (MEE/CH) based polyphosphazene was developed for the first time in literature using a mixed-substitution method. The structural, chemical, and thermal properties of these polymers were analyzed using several techniques such as Gel Permeation Chromatography (GPC), Thermal Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), and Nuclear Magnetic Resonance (NMR). Significant differences in gas transport properties of gases have been observed between these pendant groups because of their differences in glass transition temperature and physical interaction with CO 2 . For the first time, we report on the high performance of TFE polyphophazene based mixed matrix membranes (MMMs) using a SIFSIX-Cu-2i (SIFSIX) metal organic framework (MOF) as the filler particles. These MMMs showed a significant improvement in both CO 2 permeability and CO 2 /N 2 selectivity compared to pure TFE polyphosphazene membranes. As a result, the excellent gas transport properties of these membranes make them very promising material for carbon capture applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Shear strain gradient in Cu/Nb nanolaminates: Strain accommodation and chemical mixing

Disentangling the intragranular and interfacial plasticity contribution to the overall strain accommodation is crucial to understanding the microstructural evolution and mass transport upon deformation in materials with the nanoscale feature size. In this study, we devise a new approach to tackle the issue by introducing shear strain gradients into Cu/Nb nanolaminates of different layer thicknesses with the shear perpendicular to the laminate interfaces. The measurement of the strain gradient and the resultant lattice disorientation enables a quantitative understanding of the intragranular and interfacial plasticity contribution. We found that intragranular slip entirely governs the deformation in the 300 nm-layer laminate and, unexpectedly, contributes ~80% of the total plasticity in the 30 nm-layer laminate. The high intragranular plasticity in the thin laminate is attributed to the large width of confined slip planes and their remnant potential for storing dislocations. In addition, substantial forced chemical mixing is observed in the top region of the 30 nm-layer laminate where the effective layer thickness is reduced below 8 nm. The transition of deformation mechanism from confined layer slip to dislocation transmission is largely responsible for the initiation of substantial mixing. Our method and findings shed light on the deformation mechanism and deformation-induced mass transport behavior in nanostructured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Energy and mobility impacts of connected autonomous vehicles with co-optimization of speed and powertrain on mixed vehicle platoons

Intersections are known to be traffic bottlenecks where a significant amount of energy consumption could be caused due to deceleration/acceleration in the presence of red signals. With an increased level of connectivity and automation of intelligent transportation systems, connected autonomous vehicles (CAVs) are expected to be able to proactively adjust their driving strategies subject to constraints imposed by the predicted future traffic. As a result, many potential benefits can be achieved, such as improved energy efficiency, enhanced traffic safety, among many others. Notably, the way CAVs are controlled affects the following legacy vehicles (LVs) due to complex traffic dynamics. Here, we are particularly interested in studying the energy and mobility impact of CAVs with an improved traffic prediction method on mixed vehicle platoons at various market penetration rates. Leveraging traffic prediction, CAVs are controlled with co-optimization of their speed and gear position. Specifically, a traffic prediction framework in a rolling horizon fashion is employed based upon a modified Payne–Whitham (PW) model capable of handling mixed traffic consisting of CAVs and LVs. The prediction error of the modified PW model is reduced by 53.62% compared to that of the standard PW model under test scenarios. According to the predicted traffic conditions, speed and gear position of CAVs are co-optimized with the primary goal of minimizing energy consumption when driving on a signalized arterial. The energy benefits achieved by CAVs and the impact of CAVs on LVs behind are studied comprehensively for mixed vehicle platoons. The lead LV follows a real-world speed profile collected on TH-55 in Minnesota. Numerical results show that energy benefits achieved by the vehicle platoon range from 2% to 16%, and a 1% to 5% reduction in travel time for LVs behind CAVs is also observed, at different penetration rates of CAVs in various traffic scenarios. Furthermore, it is observed that CAVs using the proposed eco-driving approach appear to have a positive impact on the LVs behind in terms of energy consumption, regardless of the driving styles of the LVs ahead.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1989

Implementation of equivalent domain integral method in the two-dimensional analysis of mixed mode problems

An equivalent domain integral (EDI) method for calculating J-intergrals for two-dimensional cracked elastic bodies is presented. The details of the method and its implementation are presented for isoparametric elements. The total and product integrals consist of the sum of an area of domain integral and line integrals on the crack faces. The line integrals vanish only when the crack faces are traction free and the loading is either pure mode 1 or pure mode 2 or a combination of both with only the square-root singular term in the stress field. The EDI method gave accurate values of the J-integrals for two mode I and two mixed mode problems. Numerical studies showed that domains consisting of one layer of elements are sufficient to obtain accurate J-integral values. Two procedures for separating the individual modes from the domain integrals are presented. The procedure that uses the symmetric and antisymmetric components of the stress and displacement fields to calculate the individual modes gave accurate values of the integrals for all problems analyzed. The EDI method when applied to a problem of an interface crack in two different materials showed that the mode 1 and mode 2 components are domain dependent while the total integral is not. This behavior is caused by the presence of the oscillatory part of the singularity in bimaterial crack problems. The EDI method, thus, shows behavior similar to the virtual crack closure method for bimaterial problems.

Raju, I. S.↗
DOE OSTI2017

Does vapor pressure deficit drive the seasonality of δ 13 C of the net land-atmosphere CO 2 exchange across the United States?: The Influence of VPD on δ 13 C of NEE

The seasonal pattern of the carbon isotope content (δ 13 C) of atmospheric CO 2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO 2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δ source at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ 13 C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δ source at the forest sites (0.5‰variation). We did not find a consistent seasonal relationship between VPD and δ source across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δ sourc e (5‰) dominated by seasonal transitions in C 3 /C 4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ 13 C of land-atmosphere CO 2 exchange (δ source ) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C 3 /C 4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δs ource when background atmospheric observations are remote and/or prone to anthropogenic influence.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Three-Dimensional (3D) Additive Construction: Printing with Regolith

Three dimensional (3D) printing is a new and booming topic in many realms of research and engineering technology. When it comes to space science and aerospace engineering, it can be useful in numerous ways. As humans travel deeper into space and farther from Earth, sending large quantities of needed supplies from Earth for a mission becomes astronomically expensive and less plausible. In order to reach further to new places, In Situ Resource Utilization (ISRU), a project that pushes for technologies to use materials already present in the destination's environment, is necessary. By using materials already available in space such as regolith from the Moon, Mars, or an asteroid's surface, fewer materials need to be brought into space on a launched vehicle. This allows a vehicle to be filled with more necessary supplies for a deep space mission that may not be found in space, like food and fuel. This project's main objective was to develop a 3D printer that uses regolith to "print" large structures, such as a dome, to be used as a heat shield upon a vehicle's reentry into the atmosphere or even a habitat. 3D printing is a growing technology that uses many different methods to mix, heat, and mold a material into a specific shape. In order to heat the regolith enough to stick together into a solid shape, it must be sintered at each layer of material that is laid. Sintering is a process that heats and compresses a powdered material until it fuses into a solid, which requires a lot of energy input. As an alternative, a polymer can be mixed with the regolith before or as it is sent to the 3D printer head to be placed in the specific shape. The addition of the polymer, which melts and binds at much lower temperatures than sintering temperatures, greatly decreases the required heating temperature and energy input. The main task of the project was to identify a functional material for the printer. The first step was to find a miscible. polymer/solvent solution. This solution was added to the regolith and the solvent was evaporated essentially leaving polymer-coated regolith particles. This material would be sent through the printer head and heated layer by layer to melt the polymer and bind the regolith. This method was one of many in a large goal to utilize materials in space with a custom-made 3D printer that builds dome-shaped habitats and other essential equipment for future deep space missions.

Tsoras, Alexandra↗
NASA NTRS2003

Mixing enhancement using axial flow

A method and an apparatus for enhancing fluid mixing. The method comprises the following: (a) configuring a duct to have an effective outer wall, an effective inner wall, a cross-sectional shape, a first cross-sectional area and an exit area, the first cross-sectional area and the exit area being different in size; (b) generating a first flow at the first cross-sectional area, the first flow having a total pressure and a speed equal to or greater than a local speed of sound; and (c) generating a positive streamwise pressure gradient in a second flow in proximity of the exit area. The second flow results from the first flow. Fluid mixing is enhanced downstream from the duct exit area.

Papamoschou, Dimitri↗
DOE OSTI2021

Comparing (stochastic-selection) ab initio multiple spawning with trajectory surface hopping for the photodynamics of cyclopropanone, fulvene, and dithiane

Ab Initio Multiple Spawning (AIMS) simulates the excited-state dynamics of molecular systems by representing nuclear wavepackets in a basis of coupled traveling Gaussian functions, called trajectory basis functions (TBFs). New TBFs are spawned when nuclear wavepackets enter regions of strong nonadiabaticity, permitting the description of non-Born–Oppenheimer processes. The spawning algorithm is simultaneously the blessing and the curse of the AIMS method: it allows for an accurate description of the transfer of nuclear amplitude between different electronic states, but it also dramatically increases the computational cost of the AIMS dynamics as all TBFs are coupled. Recently, a strategy coined stochastic-selection AIMS (SSAIMS) was devised to limit the ever-growing number of TBFs and tested on simple molecules. In this work, we use the photodynamics of three different molecules—cyclopropanone, fulvene, and 1,2-dithiane—to investigate (i) the potential of SSAIMS to reproduce reference AIMS results for challenging nonadiabatic dynamics, (ii) the compromise achieved by SSAIMS in obtaining accurate results while using the smallest average number of TBFs as possible, and (iii) the performance of SSAIMS in comparison to the mixed quantum/classical method trajectory surface hopping (TSH)—both in terms of its accuracy and computational cost. We show that SSAIMS can accurately reproduce the AIMS results for the three molecules considered at a much cheaper computational cost, often close to that of TSH. We deduce from these tests that an overlap-based criterion for the stochastic-selection process leads to the best agreement with the reference AIMS dynamics for the smallest average number of TBFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

Application of Remote Sensing for Ex-Ante Decision Support and Evaluating Impact

Deforestation is an environmental stressor that dramatically threatens biodiversity while having adverse, deep-rooted socioeconomic impacts. Interventions to address deforestation require considerable long-term investments; therefore, assessing their impact is crucial. The UN Convention on Biological Diversity encourages establishing Protected Areas (PAs) as a strategy to conserve biodiversity, secure ecosystem services, support local livelihoods, and reduce climate change impacts. The Global Environment Facility (GEF) has supported the conservation and management of PAs, yet site accessibility and data availability present challenges in assessing PAs using traditional evaluation methods. We present a novel application of satellite Earth observations for evaluating the effectiveness and impact of PAs as a deforestation mitigation strategy. Geospatial analysis and ecological forecasting methodologies provide an efficient way to quantify land cover change, estimate above-ground carbon stock, and evaluate ecosystem services provided by the PAs ex-ante. We demonstrate the value of a geospatial approach through evaluation of GEF-supported PAs in Kenya.

Remote sensing↗
DOE OSTI2022

Integrating Spatial and Ethnographic Methods for Resilience Research: A Thick Mapping Approach for Hurricane Maria in Puerto Rico

Hurricane Maria left unprecedented impacts on Puerto Rican communities, leaving some without infrastructure services and unable to communicate with family for several months. Here, to understand the forms of community-level resilience that emerged while hard infrastructure systems took time recover, this article (1) abductively explores resilience as an emergent phenomenon of complex adaptive systems; (2) identifies subsequent forms of social capital, local adaptive capacities, and manifestations of quantifiable variables, such as infrastructure performance, in community experiences; and (3) demonstrates a framework to integrate disparate methodologies for resilience assessments via a multiplicity of mappings of space and place. We combine ethnographic and geospatial methods into an interactive GeoApp for analysis using participant-coded narratives and a series of geospatial indicators as a thick map. Thick mapping facilitates quantitative and qualitative data analysis at several scales, while enabling qualitative query of collected narratives. Results highlight local innovation, community bonding and bridging, and nuances in the role of public institutions as emergent elements of resilience. The thick map shows how top-down assessments can be augmented by thick data and how multiple framings can be anchored in the same system or place. These findings are important to inform and integrate community-oriented and technocentric solutions toward resilience-enhancing measures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Scalable Simulation of Pressure Gradient-Driven Transport of Rarefied Gases in Complex Permeable Media Using Lattice Boltzmann Method

Accurate representations of slip and transitional flow regimes present a challenge in the simulation of rarefied gas flow in confined systems with complex geometries. In these regimes, continuum-based formulations may not capture the physics correctly. This work considers a regularized multi-relaxation time lattice Boltzmann (LB) method with mixed Maxwellian diffusive and halfway bounce-back wall boundary treatments to capture flow at high Kn. The simulation results are validated against atomistic simulation results from the literature. We examine the convergence behavior of LB for confined systems as a function of inlet and outlet treatments, complexity of the geometry, and magnitude of pressure gradient and show that convergence is sensitive to all three. The inlet and outlet boundary treatments considered in this work include periodic, pressure, and a generalized periodic boundary condition. Compared to periodic and pressure treatments, simulations of complex domains using a generalized boundary treatment conserve mass but require more iterations to converge. Convergence behavior in complex domains improves at higher magnitudes of pressure gradient across the computational domain, and lowering the porosity deteriorates the convergence behavior for complex domains.

42 ENGINEERING↗
DOE OSTI2024

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Leon, Sami↗
DOE OSTI2023

Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials

The investigation of finite temperature properties using Monte-Carlo (MC) methods requires a large number of evaluations of the system’s Hamiltonian to sample the phase space needed to obtain physical observables as function of temperature. DFT calculations can provide accurate evaluations of the energies, but they are too computationally expensive for routine simulations. To circumvent this problem, machine-learning (ML) based surrogate models have been developed and implemented on high-performance computing (HPC) architectures. In this paper, we describe two ML methods (linear mixing model and HydraGNN) as surrogates for first principles density functional theory (DFT) calculations with classical MC simulations. These two surrogate models are used to learn the dependence of target physical properties from complex compositions and interactions of their constituents. We present the predictive performance of these two surrogate models with respect to their complexity while avoiding the danger of overfitting the model. An important aspect of our approach is the periodic retraining with newly generated first principles data based on the progressive exploration of the system’s phase space by the MC simulation. The numerical results show that HydraGNN model attains superior predictive performance compared to the linear mixing model for magnetic alloy materials.

Eisenbach, Markus↗
DOE OSTI2013

Continuous Precipitation of Ceria Nanoparticles from a Continuous Flow Micromixer

Cerium oxide nanoparticles were continuously precipitated from a solution of cerium(III) nitrate and ammonium hydroxide using a micro-scale T-mixer. Findings show that the method of mixing is important in the ceria precipitation process. In batch mixing and deposition, disintegration and agglomeration dominates the deposited film. In T-mixing and deposition, more uniform nanorod particles are attainable. In addition, it was found that the micromixing approach reduced the exposure of the Ce(OH)3 precipates to oxygen, yielding hydroxide precipates in place of CeO2 precipitates. Advantages of the micro-scale T-mixing approach include shorter mixing times, better control of nanoparticle shape and less agglomeration.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Microfluidic Fabrication of Nanoparticles Based on Ethyl Acrylate-Functionalized Chitosan for Adsorption of Methylene Blue from Aqueous Solutions

The adsorption of nanoparticle (NP)-based adsorbents especially those made of polymers to remove dyes as toxic substances from pollutants is yet remained as a critical issue. The objective of this work was to prepare microfluidic (MF) fabrication of NPs based on ethyl acrylate (EA)-functionalized chitosan (CS) for methylene blue (MB) dye removal from aqueous solutions. For this purpose, a series of experiments such as FTIR, SEM alongside DLS, and UV–vis spectrophotometry were carried out to investigate the physicochemical properties of the samples. The FTIR spectra showed that the amine (–NH{sub 2}) and hydroxyl (–OH) groups on CS structure were replaced with EA, appropriately. The SEM and DLS results depicted that EA-functionalized CS NPs fabricated using MF technique had uniform shapes, and the diameters as small as 70 nm compared to those samples produced via bulk mixing (BM) method (~ 300 nm). Moreover, the surface charge of MF-assisted CS NPs after functionalization exhibited the lower zeta potential value (~ + 11) than that of samples based on BM (~ + 14) due to occurring the laminar flow through the micro-channels embedded in the MF chip, leading to an increase in the MB adsorption. Subsequently, at the optimized amounts of the dye concentration (89.12 mg L{sup −1}), the adsorbent concentration (1.38 g L{sup −1}), and pH (10.58) by means of Box-Behnken design (BBD) method, the maximum percentage of MB removal by the use of MF-fabricated EA-functionalized CS NPs was 98.4%. By fitting the obtained adsorption data to the isotherm models such as Lagmuir, Freundlich, and Temkin, it has been found that the adsorption mechanism followed the Langmuir model (maximum capacity of the adsorption 384.61 mg/g), which assumed a monolayer coverage of MB molecules as adsorbates over a homogeneous adsorbent surface.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Gamma-ray spectrometry analysis methods for radioisotope dissolution and mixing for nuclear forensics applications

We report the production of surrogate nuclear explosive debris involves the dissolution of irradiated fissile material, elemental isolation, and recombination based on required fission product ratios. Gamma-ray spectrometry is used following each step to assess the radioactive fission product inventory. A high-purity germanium detector is used to measure each sample, and the detector efficiencies are determined prior to sample measurements. Through radiochemical techniques, elements are isolated and recombined into samples with specific fission product ratios. As a result, a matrix-based approach can account for imperfect chemical separations to calculate the proper mixture volumes to obtain intended volatile-to-refractory fission product ratios, or R-values.

07 ISOTOPE AND RADIATION SOURCES↗