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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Stress-controlled medium-amplitude oscillatory shear (MAOStress) of PVA–Borax

We report the first-ever complete measurement of MAOStress material functions, which reveal that stress can be more fundamental than strain or strain rate for understanding linearity limits as a function of Deborah number. The material used is a canonical viscoelastic liquid with a single dominant relaxation time: polyvinyl alcohol (PVA) polymer solution cross-linked with tetrahydroborate (Borax) solution. We outline experimental limit lines and their dependence on geometry and test conditions. These MAOStress measurements enable us to observe the frequency dependence of the weakly nonlinear deviation as a function of stress amplitude. The observed features of MAOStress material functions are distinctly simpler than MAOStrain, where the frequency dependence is much more dramatic. The strain-stiffening transient network model was used to derive a model-informed normalization of the nonlinear material functions that accounts for their scaling with linear material properties. Moreover, we compare the frequency dependence of the critical stress, strain, and strain-rate for the linearity limit, which are rigorously computed from the MAOStress and MAOStrain material functions. While critical strain and strain-rate change by orders of magnitude throughout the Deborah number range, critical stress changes by a factor of about 2, showing that stress is a more fundamental measure of nonlinearity strength. This work extends the experimental accessibility of the weakly nonlinear regime to stress-controlled instruments and deformations, which reveal material physics beyond linear viscoelasticity but at conditions that are accessible to theory and detailed simulation.

Mechanics↗
DOE OSTI2020

Locally adaptive activation functions with slope recovery for deep and physics-informed neural networks

Here we propose two approaches of locally adaptive activation functions namely, layer-wise and neuron-wise locally adaptive activation functions, which improve the performance of deep and physics-informed neural networks. The local adaptation of activation function is achieved by introducing a scalable parameter in each layer (layer-wise) and for every neuron (neuron-wise) separately, and then optimizing it using a variant of stochastic gradient descent algorithm. In order to further increase the training speed, an activation slope-based slope recovery term is added in the loss function, which further accelerates convergence, thereby reducing the training cost. On the theoretical side, we prove that in the proposed method, the gradient descent algorithms are not attracted to sub-optimal critical points or local minima under practical conditions on the initialization and learning rate, and that the gradient dynamics of the proposed method is not achievable by base methods with any (adaptive) learning rates. We further show that the adaptive activation methods accelerate the convergence by implicitly multiplying conditioning matrices to the gradient of the base method without any explicit computation of the conditioning matrix and the matrix–vector product. The different adaptive activation functions are shown to induce different implicit conditioning matrices. Furthermore, the proposed methods with the slope recovery are shown to accelerate the training process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Graphite Lithiation under Fast Charging Conditions: Atomistic Modeling Insights

The charging of lithium ion batteries in a fast and safe manner is critical for promoting the mass adoption of electric vehicles. Li intercalation in graphite electrodes is known to be one of the bottlenecks during the fast charging process. The mechanism of Li diffusion in highly polarized graphite anode at high current rates remains, however, not well understood. In this work, Density Functional Theory (DFT) calculations are used to gain insights into the Li diffusion process in graphite when it is far from equilibrium under fast charging conditions. The effect of uncompensated charges on Li mobility is determined in the highly polarized regions of the anode close to the interfaces. The extra charge was found to increase the interlayer spacing in the diffusion layer and adjacent channels, increasing the diffusivity and promoting the formation of Li clusters. A concerted diffusion mechanism at the edge of high-concentration Li domains is proposed to enhance the diffusion of Li.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Catalytic Resonance Theory: The Catalytic Mechanics of Programmable Ratchets

Catalytic reaction networks of multiple elementary steps operating under dynamic conditions via a programmed input oscillation are difficult to interpret and optimize due to reaction system complexity. To understand these dynamic systems, individual elementary catalytic reactions oscillating between catalyst states were evaluated to identify their three fundamental characteristics that define their ability to promote reactions away from equilibrium. First, elementary catalytic reactions exhibit directionality to promote reactions forward or backward from equilibrium as determined by a ratchet directionality metric comprised of the input oscillation duty cycle and the reaction rate constants. Second, catalytic ratchets are defined by the catalyst state of strong or weak binding that permit reactants to proceed through the transition state. Third, elementary catalytic ratchets exhibit a cutoff frequency which defines the transition in applied frequency for which the catalytic ratchet functions to promote chemistry away from equilibrium. All three ratchet characteristics are calculated from chemical reaction parameters including rate constants derived from linear scaling parameters, reaction conditions, and catalyst state. The characteristics of the reaction network’s constituent elementary catalytic reactions provided an interpretation of complex reaction networks and a method of predicting the behavior of dynamic surface chemistry on oscillating catalysts.

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

The modeling of the turbulent reaction rate under high-pressure conditions: A priori evaluation of the Conditional Source-term Estimation concept

With the goal of obtaining an accurate model of the turbulent reaction rate for Large Eddy Simulations (LESs), the modeling of turbulence-chemistry-thermodynamic interaction is addressed through an a priori study of a Direct Numerical Simulation (DNS) database representing high-pressure turbulent combustion. The DNS database consists of simulations of a temporal mixing layer in which a single-step chemical reaction occurs. The potential of the single-conditioned Conditional Source-term Estimation (CSE) approach to model the filtered turbulent reaction rate needed for conducting LES is examined. Evaluations conducted with the mixture fraction as a conditioning variable at two filter widths and with the probability density function (PDF) extracted from the DNS database that represents the mixture fraction, show that the deviation between the model and template is large and substantially increases with filter width. To address this deviation, the Double-conditioned CSE (DCSE) approach is explored with two different second conditioning variables, the first conditioning variable still being the mixture fraction; four filter widths are considered. The first choice of the second conditioning variable is a normalized progress variable based on the CO 2 mass fraction and the second choice of the second conditioning variable is a normalized temperature. With each second conditional variable, the DCSE results represent a substantial improvement over CSE, by as much as an order of magnitude when measured by the relative error from the DNS-extracted filtered reaction rate. A quantitative test based on a root mean square identifies the reason for the DCSE success compared to CSE: unlike in CSE, the DCSE is able to substantially reduce the fluctuations of the modeled reaction rate from the filtered reaction rate over the entire range of the filtered reaction rate values, and particularly at the larger reaction rate values for which the DCSE model has higher fidelity. The results are shown to be equally favorable for the two conditioning variables. Consideration of DNS realizations at higher free-stream pressure or larger Reynolds number shows that the results are essentially equally successful at other pressure or Reynolds number values.

42 ENGINEERING↗
NASA NTRS2009

Study of Electro-Cyclonic Filtration and Pneumatic Transfer of Lunar Regolith Simulants under 1/6-g and 1-g Gravity Conditions

NASA has built a prototype oxygen production plant to process the lunar regolith using the hydrogen reduction chemical process. This plant is known as "ROxygen - making oxygen from moon rocks". The ROxygen regolith transfer team has identified the flow and transfer characteristics of lunar regolith simulant to be a concern for lunar oxygen production efforts. It is important to ISRU lunar exploration efforts to develop hardware designs that can demonstrate the ability to flow and transfer a given mass of regolith simulant to a desired vertical height under lunar gravity conditions in order to introduce it into a reactor. We will present results obtained under both 1/6-g and 1-g gravity conditions for a system that can pneumatically convey 16.5 kg of lunar regolith simulant (NU-LHT-2M, Mauna Kea Tephra, and JSC-1A) from a flat-bottom supply hopper to a simulated ISRU reactor (dual-chambered receiving hopper) where the granular material is separated from the convey gas (air) using a series of cyclone separators, one of which is an electrically enhanced cyclone separator (electrocyclone). The results of our study include (1) the mass flow rate as a function of input air pressure for lunar regolith simulants that are conveyed pneumatically as a dusty gas in a vertical direction against gravity under lunar gravity conditions (for NU-LHT-2M and Mauna Kea Tephra), and under earth gravity conditions (for NU-LHT-2M, Mauna Kea Tephra and JSC-1A), and (2) the efficiency of the cyclone/electrocyclone filtration system in separating the convey gas (air) from the granular particulates as a function of particle size.

Mantovani, James G.↗
DOE OSTI2025

Dynamic Features of Cu-Ceria Interface under CO 2 Hydrogenation to Methanol

It is generally accepted that metal–support interaction is very important for the hydrogenation of CO 2 to methanol, but little has been revealed about the feature of interfacial active sites under real reaction conditions since there are only limited techniques that can be applied under high-pressure conditions. Here, in this work, by combining multiple in situ and operando techniques on a model Cu/ceria catalyst, we have tracked Cu and ceria sites for methanol formation. Under the reaction condition, it is found that upon reaching the reaction temperature, oxidized Cu species in the as-synthesized catalyst immediately change into metallic Cu species. Following this, it is the gradual formation of methanol, the changing rate of which coincides with the formation of a unique Ce 3+ species. The combined experimental results and density functional theory (DFT) calculations have determined that the formed Ce 3+ sites driven by the reaction conditions are bound to hydrides, adsorbed carbonate species, and interfacial active Cu sites. The Cu-ceria interaction in this complex moiety is weak and can be easily disturbed with reaction environment variations, leading to dynamic changes at the interface upon the hydrogenation of active carbonate intermediates, which are precursors for the formation of methanol. The formation of this unique Cu–Ce 3+ interface and its dynamicity lead to an increase of methanol selectivity from less than 20% to 60%. These results suggest that reactant-derived species (H – and carbonate in this work) can be essential components of the active center with the functions of manipulating the metal−oxide interaction and directing reaction pathways.

CO2 hydrogenation to methanol↗
DOE OSTI2019

Quantifying mortality and injury susceptibility for two morphologically disparate fishes exposed to simulated turbine blade strike

Passage of fishes through hydropower turbines and water pumping stations may cause mortal injury as the result of exposure to blade strike impact. Laboratory trials of simulated blade strike on two morphologically distinct fishes, American eel ( Anguilla rostrata ) and bluegill sunfish ( Lepomis macrochirus ) were undertaken to assess injury and mortality rates. We hypothesized that bluegill would have comparable rates of injury and mortality to other laterally compressed fishes while anguilliform American eel would be more resistant to injury. American eel had low observed mortality rates at the highest velocity tested (13.6 m/s), but many fish were observed with vertebral fractures which we categorized as functionally dead individuals. Bluegill were more susceptible to blade strike with high rates of mortality regardless of blade thickness, velocity, or impact conditions (location, angle, or fish orientation). These data have broadened our understanding of the range of responses among entrained fishes exposed to blade strike and represent species with low (American eel) and high (bluegill) susceptibility to injury and mortality. Furthermore, our blade strike data can help inform safer turbine designs or prioritization of pumps that minimize traumatic injury and mortality of fishes during non-volitional passage through hydropower turbines or water pumping stations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Conforming window functions for meshfree methods

Window functions provide a base for the construction of approximation functions in many meshfree methods. They control the smoothness and extent of the approximation functions and are commonly defined using Euclidean distances which helps eliminate the need for a meshed discretization, simplifying model development for some classes of problems. However, for problems with complicated geometries such as nonconvex or multi-body domains, poor solution accuracy and convergence can occur unless the extents of the window functions, and thus approximation functions, are carefully controlled, often a time consuming or intractable task. Here in this paper, we present a method to provide more control in window function design, allowing efficient and systematic handling of complex geometries. “Conforming” window functions are constructed using Bernstein–Bézier splines defined on local triangulations with constraints imposed to control smoothness. Graph distances are used in conjunction with Euclidean metrics to provide adequate information for shaping the window functions. The conforming window functions are demonstrated using the Reproducing Kernel Particle Method showing improved accuracy and convergence rates for problems with challenging geometries. Conforming window functions are also demonstrated as a means to simplify the imposition of essential boundary conditions.

, rapid design-to-analysis↗
DOE OSTI2023

Functional variability in specific root respiration translates to autotrophic differences in soil respiration in a temperate deciduous forest

CO 2 release from forest soils (R s ) is a prominent flux in the global carbon cycle. Rs is derived from roots (autotrophic respiration, R a ) and microbial (heterotrophic) respiration and is highly dynamic, as it depends on edaphic and environmental conditions as well as root functional traits and microbial community composition. It is unclear how root functional traits affect root and microbial respiration rates; however, their consideration may help parse out the relative contributions of root and microbial respiration to R s . At a temperate forest site, root systems of 3–4 functional root orders and their surrounding surface soil were carefully excavated and placed into custom trays designed to repeatedly measure R s in situ on eight temperate tree species that varied in their root functional strategies and mycorrhizal affinity. R s was measured bi-weekly to monthly for nearly one year using a custom chamber attached to a gas exchange system. R s varied over time, ranging from 0.3 to 12 µmol m -2 s -1 . Comparable root systems of the same species were excised from the soil and specific root respiration rates (R r ) were measured. Rr ranged from 2.5 to 9.0 nmol g -1 s -1 and was negatively correlated with root tissue density and positively related to root tissue nitrogen concentration. Using R r to estimate R a , we estimate that R a accounts for <10%, on average 2–3%, of R s for individual root systems (averaging 1.2 g dry biomass) housed in surrounding soil (average 1.3 kg dry mass) in situ; thus, Ra was roughly 20 times greater than Rh per unit mass. The contribution of R a peaked in the fall and coincided with leaf senescence of the forest canopy. A soil-sterilizing experimental treatment designed to help isolate R a in situ reduced bacterial biomass and shifted fungal community composition, but there was no reduction in Rs of the in-situ root-soil tray systems. The relative R a to R s ratio increased with root functional strategies characterized by greater specific root length and tip abundance, but also to greater root tissue density. The ratio of R a to R s also increased with warmer soil temperatures and decreased slightly with increasing soil moisture. We discuss how incorporating root functional traits as modulators of the autotrophic contribution to R s could be considered when modeling total soil CO 2 efflux from forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Predicting metal–metal interactions. II. Accelerating generalized schemes through physical insights

Operando-computational frameworks that integrate descriptors for catalyst stability within catalyst screening paradigms enable predictions of rates and selectivity on chemically faithful representations of nanoparticles under reaction conditions. These catalyst stability descriptors can be efficiently predicted by density functional theory (DFT)-based models. The alloy stability model, for example, predicts the stability of metal atoms in nanoparticles with site-by-site resolution. In this work, we use physical insights to present accelerated approaches of parameterizing this recently introduced alloy-stability model. These accelerated approaches meld quadratic functions for the energy of metal atoms in terms of the coordination number with linear correlations between model parameters and the cohesive energies of bulk metals. By interpolating across both the coordination number and chemical space, these accelerated approaches shrink the training set size for 12 fcc p- and d-block metals from 204 to as few as 24 DFT calculated total energies without sacrificing the accuracy of our model. We validate the accelerated approaches by predicting adsorption energies of metal atoms on extended surfaces and 147 atom cuboctahedral nanoparticles with mean absolute errors of 0.10 eV and 0.24 eV, respectively. This efficiency boost will enable a rapid and exhaustive exploration of the vast material space of transition metal alloys for catalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗
DOE OSTI2022

Energy relaxation dynamics in a nodal-line semimetal

Here we study the temperature relaxation dynamics of nodal-line semimetals after a sudden excitation in the presence of acoustic and optical phonon modes. We find that the nodal line constrains the electron momenta in scattering processes, and as a result, the temperature relaxation due to acoustic phonons is exponential as a function of time. However, depending on initial conditions, other functional forms are possible. In typical pump-probe experiments, the temperature relaxation is linear due to acoustic phonons with rates that vary as ~n 1/2 with density. The temperature relaxation due to optical phonons is also linear with rates ~n -1/2 or ~n .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling Redshift-space Clustering with Abundance Matching

Abstract We explore the degrees of freedom required to jointly fit projected and redshift-space clustering of galaxies selected in three bins of stellar mass from the Sloan Digital Sky Survey Main Galaxy Sample (SDSS MGS) using a subhalo abundance matching (SHAM) model. We employ emulators for relevant clustering statistics in order to facilitate our analysis, leading to large speed gains with minimal loss of accuracy. We are able to simultaneously fit the projected and redshift-space clustering of the two most massive galaxy samples that we consider with just two free parameters: scatter in stellar mass at fixed SHAM proxy, and the dependence of the SHAM proxy on dark matter halo concentration. We find some evidence for models that include velocity bias, but including orphan galaxies improves our fits to the lower-mass samples significantly. We also model the clustering signals of specific star formation rate (sSFR) selected samples using conditional abundance matching (CAM). We obtain acceptable fits to projected and redshift-space clustering as a function of sSFR and stellar mass using two CAM variants, although the fits are worse than for stellar-mass-selected samples alone. By incorporating nonunity correlations between the CAM proxy and sSFR, we are able to resolve previously identified discrepancies between CAM predictions and SDSS observations of the environmental dependence of quenching for isolated central galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Gust alleviation for a STOL transport by using elevator, spoilers, and flaps

Control laws were developed to investigate methods of alleviating the response of a STOL transport to gusty air. The transport considered in the study had triple-slotted, externally blown jet flaps and a large T-tail. The control devices used were the elevator, spoilers, and flaps. A hybrid computing system was used to simulate linearized longitudinal dynamics of the aircraft and to implement a conjugate gradient optimal search algorithm. The aircraft was simulated in the low-speed approach condition only. Feedback control matrices were found which minimized the average of a quadratic functional involving passenger compartment accelerations, pitch angle and rate, flight path angle and speed variations. The optimization was performed for artificially designed gust inputs in the form of predetermined rectangular waveforms. Results were obtained for elevator, spoilers, and flaps acting singly and in combination. Additional results were obtained for unit sinusoidal gust inputs by using the gain matrices computed for the artificial test gusts. Various sensor configurations were also investigated.

Lallman, F. J.↗
NASA NTRS1979

Flight test of a VTOL digital autoland system along complex trajectories

The objective of this research is the development and flight test of a digital multi-rate VTOL autoland system. This autoland system provided the NASA/Army Fly-by-Wire CH-47 helicopter with an automatic 4-D trajectory following and landing capability. Flight tests were conducted along complex trajectories with descending, turning, and decelerating segments. The flight software consists of a trajectory generator and guidance algorithm operating at two iterations per second and a set of sensor filters and an advanced controller operating at 10 iterations per second. This low iteration rate digital controller has a proportional-integral structure that provides an autotrim function. The control gains, scheduled as a function of flight condition, are updated every two seconds. All flight software, except input/output routines, are coded in FORTRAN using floating point arithmetic and are exercised in a ROLM 1664 flight computer. The flight software, the ground and flight hardware, the autoland system's position tracking performance, and the controller's velocity and heading tracking performance are presented.

Downing, D. R.↗
NASA NTRS1980

Ice crystal growth in a dynamic thermal diffusion chamber

Ice crystals were grown in a supersaturated environment produced by a dynamic thermal diffusion chamber, which employed two horizontal plates separated by a distance of 2.5 cm. Air was circulated between and along the 1.2 m length of the plates past ice crystals which nucleated and grew from a fiber suspended vertically between the two plates. A zoom stereo microscope with a magnification which ranged from 3X to 80X and both 35 mm still photographs and 16 mm time lapse cine films taken through the microscope were used to study the variation of the shape and linear growth rate of ice crystals as a function of the ambient temperature, the ambient supersaturation, and the forced ventilation velocity. The ambient growth conditions were varied over the range of temperature 0 to -40 C, over the range of supersaturation 4% to 50% with respect to ice, and over the range of forced ventilation velocities 0 cm/s to 20 cm/s.

Keller, V. W.↗