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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding Multi-Ion Transport Mechanisms in Bipolar Membranes

Bipolar membranes (BPMs) have the potential to become critical components in electrochemical devices for a variety of electrolysis and electrosynthesis applications. Because they can operate under large pH gradients, BPMs enable favorable environments for electrocatalysis at the individual electrodes. Critical to the implementation of BPMs in these devices is understanding the kinetics of water dissociation that occurs within the BPM as well as the co- and counter-ion crossover through the BPM, which both present significant obstacles to developing efficient and stable BPM-electrolyzers. In this study, a continuum model of multi-ion transport in a BPM is developed and fit to experimental data. Specifically, concentration profiles are determined for all ionic species, and the importance of a water-dissociation catalyst is demonstrated. The model describes internal concentration polarization and co- and counter-ion crossover in BPMs, determining the mode of transport for ions within the BPM and revealing the significance of salt-ion crossover when operated with pH gradients relevant to electrolysis and electrosynthesis. Lastly, a sensitivity analysis reveals that the performance and lifetime of BPMs can be improved substantially by using of thinner dissociation catalysts, managing water transport, modulating the thickness of the individual layers in the BPM to control salt-ion crossover, and increasing the ion-exchange capacity of the ion-exchange layers in order to amplify the water-dissociation kinetics at the interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Invited article: X-ray phase contrast imaging in inertial confinement fusion and high energy density research

X-ray phase contrast imaging (XPCI) provides enhanced image contrast beyond absorption-based x-ray imaging alone due to refraction and diffraction from gradients in the object material density. It is sensitive to small variations in density, such as internal voids, cracks, grains, defects, and material flow, as well as to stronger density variations such as from a shock wave. Beyond its initial use in biology and materials science, XPCI is now routinely used in inertial confinement fusion (ICF) and high energy density (HED) research, first to characterize ICF capsules and targets, and later applied in dynamic experiments, where coherent x-ray sources, ultrafast x-ray pulses, and high temporal and spatial resolution are required. In this Review article, XPCI image formation theory is presented, its diverse use in ICF and HED research is discussed, the unique requirements for ultrafast XPCI imaging are given, as well as current challenges and issues in its use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

EvoProtGrad (Directed Evolution for Proteins with Gradients) [SWR-23-48]

A Python package for directed evolution on a protein sequence with gradient-based discrete Markov chain monte carlo (MCMC). Users are able to compose custom models that map sequence to function with pretrained models, including protein language models (PLMs), to guide and constrain search. Our package natively integrates with the HuggingFace platform and supports PLMs from transformers. Our MCMC sampler identifies promising amino acids to mutate via model gradients taken with respect to the input (i.e., sensitivity analysis). We allow users to compose their own custom target function for MCMC by leveraging the Product of Experts MCMC paradigm. Each model is an "expert" that contributes its own knowledge about the protein's fitness landscape to the overall target function. The sampler is designed to be more efficient and effective than brute force and random search while maintaining most of the generality and flexibility. Additional information can be found in the related publication: https://iopscience.iop.org/article/10.1088/2632-2153/accacd

Emami, Patrick↗
DOE OSTI2020

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Despite the great achievements of the modern deep neural networks (DNNs), the vulnerability/robustness of state-of-the-art DNNs raises security concerns in many application domains requiring high reliability. Various adversarial attacks are proposed to sabotage the learning performance of DNN models. Among those, the black-box adversarial attack methods have received special attentions owing to their practicality and simplicity. Black-box attacks usually prefer less queries in order to maintain stealthy and low costs. However, most of the current black-box attack methods adopt the first-order gradient descent method, which may come with certain deficiencies such as relatively slow convergence and high sensitivity to hyper-parameter settings. In this paper, we propose a zeroth-order natural gradient descent (ZO-NGD) method to design the adversarial attacks, which incorporates the zeroth-order gradient estimation technique catering to the black-box attack scenario and the second-order natural gradient descent to achieve higher query efficiency. The empirical evaluations on image classification datasets demonstrate that ZO-NGD can obtain significantly lower model query complexities compared with state-of-the-art attack methods.

Zhao, Pu↗
NASA NTRS1976

Plasma diagnostic techniques in the ultraviolet - The C III density-sensitive lines in the sun

Spectra and spectroheliograms of the C III transitions at 977 and 1176 A are obtained with the Harvard extreme-ultraviolet spectrometer on Skylab. Analysis of the intensities of these lines, and of their density-sensitive ratio, indicates a wide range of temperature gradients and electron densities in the transition region of various solar features. From values of the observed ratio, we suggest necessary revisions to the excitation rates, and propose a relationship between the ratio and density. The significantly higher ratio found in active regions indicates a density increase of about a factor 2 relative to the network. In the quiet sun, there is no significant difference in density between network and cell interiors, but the uncertainty is as large as a factor 3. The very central 10% of the areas of cell interiors shows a significantly higher density than the mean value for cell interiors.

Dupree, A. K.↗
NASA NTRS1990

Performance analysis of structured gradient algorithm

The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.

Godara, Lal C.↗
NASA NTRS1996

Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

Newman, Perry A.↗
NASA NTRS1998

Modeling the Plasmasphere

The plasmasphere has often been considered one of the more boring regions in the magnetosphere. Its low energy plasma doesn't begin to compete against the free sources of energy available in the ring current, auroral zone, or plasma sheet. Its best known feature is its relatively highly density, archived as a result of prolonged accumulation of ionospheric outflow onto corotating flux tubes. On second look, however, the plasmasphere can be found to exhibit a remarkable influence on its more energetic cousins and display convection behavior indicative of physical processes acting throughout the magnetosphere for which we have no explanation. Plasmaspheric plasma densities and composition of heavy ions are particularly sensitive to heating by processes active in the ionosphere and all along field lines. Wave propagation and instabilities, collisional losses in the ring current, and heat transport from superthermal electrons are all equally sensitive to dense, heavy plasmaspheric densities and density gradients. It is in this context that we seek to characterize plasmaspheric populations using event based, empirical, and physical modeling methods. The modeling approaches, the challenges, and some of the results of these efforts will be presented.

Gallagher, Dennis L↗
NASA NTRS1994

Characterization of the association of nitrate reductase with barley (Hordeum vulgare L.) root membranes

The nature of the association between nitrate reductase (NR) and membranes was examined. Nitrate reductase activity (NRA) associated with the microsomal fraction of barley (Hordeum vulgare L.) roots amounted to 0.6 to 0.8% of soluble NRA following sonication in the presence of 250 mM KI and repeated osmotic shock. This treatment removed all contaminating soluble NRA from microsomes of uninduced barley roots that had been homogenized in a soluble extract from roots of NO3(-)-induced plants. On continuous sucrose gradients, NRA co-migrated specifically with VO4(-)-sensitive ATPase activity, a plasma membrane (PM) marker; activity of glucose-6-phosphate dehydrogenase, assayed as cytosolic marker, co-migrated with NRA. Microsomal NRA was absent in barley deficient in soluble NR. Perturbation and trypsinolysis experiments with PM vesicles isolated by aqueous two-phase partitioning indicated that NR is associated with the periphery of the cytoplasmic face of the bilayer. These results demonstrate that PM and soluble NRs are essentially the same protein but that the membrane-associated form is tightly bound. Although it is possible that PM-associated NR exists in vivo, unequivocal evidence for this has yet to be shown. However, PM NR is definitely present in vitro.

Non-NASA Center↗
NASA NTRS2011

Climate Change Impacts on North Dakota: Agriculture and Hydrology

North Dakota is one of the principal producers of agricultural commodities in the USA, including over half of the total spring wheat production. While the region includes some of the best agricultural lands in the world, the steep temperature and precipitation gradients also make it one of the most sensitive to climate change. Over the 20th century, both the temperature and the pattern of precipitation in the state have changed; one of the most dramatic examples of the consequences of this change is the Devils Lake flooding. In two studies, we estimated the climate change impacts on crop yields and on the hydrology of the Devils Lake basin. The projections of six GCMs, driven by three SRES scenarios were statistically downscaled for multiple locations throughout the state, for the 2020s, 2050s, and 2080s climate. Averaged over all GCMs, there is a small increase in precipitation, by 0.6 - 1.1% in 2020s, 3.1 - 3.5% in 2050s, and 3.0 - 7.6% in 2080s. This change in precipitation varies with the seasons, with cold seasons becoming wetter and warm seasons not changing.

FROM↗
NASA NTRS2012

Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment

The determination of risk from infectious disease during spaceflight missions is composed of several factors including both the concentration and characteristics of the microorganisms to which the crew are exposed. Thus, having a good understanding of the microbial ecology aboard spacecraft provides the necessary information to mitigate health risks to the crew. While preventive measures are taken to minimize the presence of pathogens on spacecraft, medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a specific culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. To address this bias in our understanding of the ISS environment, the Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment was designed to investigate and develop monitoring technology to provide better microbial characterization. For the SWAB flight experiment, we hypothesized that environmental analysis using non-culture-based technologies would reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. Key findings during this experiment included: a) Generally, advanced molecular techniques were able to reveal a few organisms not recovered using culture-based methods; however, there is no indication that current monitoring is "missing" any medically significant bacteria or fungi. b) Molecular techniques have tremendous potential for microbial monitoring, however, sample preparation and data analysis present challenges for spaceflight hardware. c) Analytical results indicate that some molecular techniques, such as denaturing gradient gel electrophoresis (DGGE), can be much less sensitive than culture-based methods. d) More sensitive molecular techniques, such as quantitative polymerase chain reaction (QPCR), were able to identify viral DNA from ISS environments, suggesting potential transfer of the organism between crewmembers. In addition, the hardware selected for this experiment represented advances for next-generation sample collection. The advanced nature of this collection hardware was noted, when the Sartorius MD8 Air Port air sampler from the SWAB experiment remained on board ISS at the request of JAXA investigators, who intend to use it in completion of their microbial ecology experiment.

Castro, V. A.↗
NASA NTRS2019

High-fidelity Multidisciplinary Sensitivity Analysis and Design Optimization for Rotorcraft Applications

A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. A sensitivity-enabled fluid dynamics solver and a nonlinear flexible multibody dynamics solver are coupled to predict aerodynamic loads and structural responses of helicopter rotor blades. A discretely consistent adjoint-based sensitivity analysis available in the fluid dynamics solver provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Accuracy of the coupled system is validated by conducting simulations for a benchmark rotorcraft model and comparing solutions with established analyses and experimental data. Sensitivities of lift computed by the multidisciplinary sensitivity analysis are verified by comparison with the sensitivities obtained by complex-variable simulations. Finally the multidisciplinary sensitivity analysis is applied to a constrained gradient-based design optimization for a HART-II rotorcraft configuration.

Wang, Li↗
DOE OSTI2019

Learning nonlinear level sets for dimensionality reduction in function approximation

We developed a Nonlinear Level-set Learning (NLL) method for dimensionality reduction in high-dimensional function approximation with small data. This work is motivated by a variety of design tasks in real-world engineering applications, where practitioners would replace their computationally intensive physical models (e.g., high-resolution fluid simulators) with fast-to-evaluate predictive machine learning models, so as to accelerate the engineering design processes. There are two major challenges in constructing such predictive models: (a) high-dimensional inputs (e.g., many independent design parameters) and (b) small training data, generated by running extremely time-consuming simulations. Thus, reducing the input dimension is critical to alleviate the over-fitting issue caused by data insufficiency. Existing methods, including sliced inverse regression and active subspace approaches, reduce the input dimension by learning a linear coordinate transformation; our main contribution is to extend the transformation approach to a nonlinear regime. Specifically, we exploit reversible networks (RevNets) to learn nonlinear level sets of a high-dimensional function and parameterize its level sets in low-dimensional spaces. A new loss function was designed to utilize samples of the target functions' gradient to encourage the transformed function to be sensitive to only a few transformed coordinates. The NLL approach is demonstrated by applying it to three 2D functions and two 20D functions for showing the improved approximation accuracy with the use of nonlinear transformation, as well as to an 8D composite material design problem for optimizing the buckling-resistance performance of composite shells of rocket inter-stages.

Zhang, Guannan↗
NASA NTRS1989

Gravitropism in higher plant shoots. VI. Changing sensitivity to auxin in gravistimulated soybean hypocotyls

Although the Cholodny-Went model of auxin redistribution has been used to explain the transduction phase of gravitropism for over 60 years, problems are apparent, especially with dicot stems. An alternative to an auxin gradient is a physiological gradient in which lower tissues of a horizontal stem become more sensitive than upper tissues to auxin already present. Changes in tissue sensitivity to auxin were tested by immersing marked Glycine max Merrill (soybean) hypocotyl sections in buffered auxin solutions (0, 10(-8) to 10(-2) molar indoleacetic acid) and observing bending and growth of upper and lower surfaces. The two surfaces of horizontal hypocotyl sections responded differently to the same applied auxin stimulus; hypocotyls bent up (lower half grew more) in buffer alone or in low auxin levels, but bent down (upper half grew more) in high auxin. Dose-response curves were evaluated with Michaelis-Menten kinetics, with auxin-receptor binding analogous to enzyme-substrate binding. Vmax for the lower half was usually greater than that for the upper half, which could indicate more binding sites in the lower half. Km of the upper half was always greater than that of the lower half (unmeasurably low), which could indicate that upper-half binding sites had a much lower affinity for auxin than lower-half sites. Dose-response curves were also obtained for sections scrubbed' (cuticle abraded) on top or bottom before immersion in auxin, and gravitropic memory' experiments of L. Brauner and A. Hagar (1958 Planta 51: 115-147) were duplicated. [1-14C]Indoleacetic acid penetration was equal into the two halves, and endogenous plus exogenously supplied (not radiolabeled) free auxin in the two halves (by gas chromatography-selected ion monitoring-mass spectrometry) was also equal. Thus, differential growth occurred without free auxin redistribution, contrary to Cholodny-Went but in agreement with a sensitivity model.

NASA Discipline Number 29-20↗
NASA NTRS2011

Simulations of Recovery of Time-Varying Gravity from DECIGO Pathfinder

We simulated time-varying Earth's gravity field recovered from DPF to evaluate an impact of DPF and future satellite gradiometry mission on earth science. From hydrological water movement data and orbit information, gravity gradients to be measured at altitude about ~500km were generated. Errors caused by atmospheric and oceanic variations and instrumental noise were added. Monthly gravity fields were estimated solving normal equations between spherical harmonic coefficients and simulated gravity gradient data. Simulation results show that DPF likely provides monthly hydrological water storage change with spatial scale between 400 and 1000km. Sensitivities to large scale estimates depends on long-term stability of gravity gradient measurement, and errors in short scale estimates are caused by instrumental noise and imperfections in atmospheric and ocean model. With acceleration noise level is lower than ~5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 3mHz, water storage changes at limited small basins will be provided by DPF. To monitor continental scale hydrological water movement, noise level must be lower than ~5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 1mHz.

Hasegawa, Takashi↗
DOE OSTI2021

Fault location in High Voltage Multi-terminal dc Networks Using Ensemble Learning

Precise location of faults for large distance power transmission networks is essential for faster repair and restoration process. High Voltage direct current (HVdc) networks using modular multi-level converter (MMC) technology has found its prominence for interconnected multi-terminal networks. This allows for large distance bulk power transmission at lower costs. However, they cope with the challenge of dc faults. Fast and efficient methods to isolate the network under dc faults have been widely studied and investigated. After successful isolation, it is essential to precisely locate the fault. The post-fault voltage and current signatures are a function of multiple factors and thus accurately locating faults on a multi-terminal network is challenging. In this paper, we discuss a novel data-driven ensemble learning based approach for accurate fault location. Here we utilize the eXtreme Gradient Boosting (XGB) method for accurate fault location. The sensitivity of the proposed algorithm to measurement noise, fault location, resistance and current limiting inductance are performed on a radial three-terminal MTdc network designed in Power System Computer Aided Design (PSCAD)/Electromagnetic Transients including dc (EMTdc).

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

An Integrated Control and Minimum Mass Structural Optimization Algorithm for Large Space Structures

A new approach is discussed for solving dual structural control optimization problems for high-order flexible space structures, where reduced-order structural models are employed and minimum mass designs are sought. For a given initial structural design, a quadratic control cost is minimized subject to a constant-mass constraint. The sensitivity of the optimal control cost with respect to the structural design variables is then determined and used to obtain successive structural redesigns, using a constrained gradient optimization algorithm. This process is repeated until the constrained control cost sensitivity becomes negligible. The minimum mass design is obtained by solving a sequence of neighboring optimal constant mass designs, where the sequence of optimal performance indices has a minimum at the optimal minimum mass design. A numerical example is presented which demonstrates that this new approach effectively addresses the problem of dual optimization for potentially very high-order structures.

Messac, A.↗