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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Optimizations on Designing High-Resolution Finite-Difference Schemes

We describe a general optimization procedure for both maximizing the resolution characteristics of existing finite differencing schemes as well as designing finite difference schemes that will meet the error tolerance requirements of numerical solutions. The procedure is based on an optimization process. This is a generalization of the compact scheme introduced by Lele in which the resolution is improved for single, one-dimensional spatial derivative, whereas in the present approach the complete scheme, after spatial and temporal discretizations, is optimized on a range of parameters of the scheme and the governing equations. The approach is to linearize and Fourier analyze the discretized equations to check the resolving power of the scheme for various wave number ranges in the solution and optimize the resolution to satisfy the requirements of the problem. This represents a constrained nonlinear optimization problem which can be solved to obtain the nodal weights of discretization. An objective function is defined in the parametric space of wave numbers, Courant number, Mach number and other quantities of interest. Typical criterion for defining the objective function include the maximization of the resolution of high wave numbers for acoustic and electromagnetic wave propagations and turbulence calculations. The procedure is being tested on off-design conditions of non-uniform mesh, non-periodic boundary conditions, and non-constant wave speeds for scalar and system of equations. This includes the solution of wave equations and Euler equations using a conventional scheme with and without optimization and the design of an optimum scheme for the specified error tolerance.

Liu, Yen↗
NASA NTRS2004

NASA Experimental Program to Stimulate Competitive Research: South Carolina

The use of an appropriate relationship model is critical for reliable prediction of future urban growth. Identification of proper variables and mathematic functions and determination of the weights or coefficients are the key tasks for building such a model. Although the conventional logistic regression model is appropriate for handing land use problems, it appears insufficient to address the issue of interdependency of the predictor variables. This study used an alternative approach to simulation and modeling urban growth using artificial neural networks. It developed an operational neural network model trained using a robust backpropagation method. The model was applied in the Myrtle Beach region of South Carolina, and tested with both global datasets and areal datasets to examine the strength of both regional models and areal models. The results indicate that the neural network model not only has many theoretic advantages over other conventional mathematic models in representing the complex urban systems, but also is practically superior to the logistic model in its capability to predict urban growth with better - accuracy and less variation. The neural network model is particularly effective in terms of successfully identifying urban patterns in the rural areas where the logistic model often falls short. It was also found from the area-based tests that there are significant intra-regional differentiations in urban growth with different rules and rates. This suggests that the global modeling approach, or one model for the entire region, may not be adequate for simulation of a urban growth at the regional scale. Future research should develop methods for identification and subdivision of these areas and use a set of area-based models to address the issues of multi-centered, intra- regionally differentiated urban growth.

Sutton, Michael A.↗
NASA NTRS1996

Sampling of prenatal and postnatal offspring from individual rat dams enhances animal use without compromising development

To assess prenatal and postnatal developmental status in the offspring of a group of animals, it is typical to examine fetuses from some of the dams as well as infants born to the remaining dams. Statistical limitations often arise, particularly when the animals are rare or especially precious, because all offspring of the dam represent only a single statistical observation; littermates are not independent observations (biologically or statistically). We describe a study in which pregnant laboratory rats were laparotomized on day 7 of gestation (GD7) to ascertain the number and distribution of uterine implantation sites and were subjected to a simulated experience on a 10-day space shuttle flight. After the simulated landing on GD18, rats were unilaterally hysterectomized, thus providing a sample of fetuses from 10 independent uteruses, followed by successful vaginal delivery on GD22, yielding postnatal samples from 10 uteruses. A broad profile of maternal and offspring morphologic and physiologic measures indicated that these novel sampling procedures did not compromise maternal well-being and maintained normal offspring development and function. Measures included maternal organ weights and hormone concentrations, offspring body size, growth, organ weights, sexual differentiation, and catecholamine concentrations.

NASA Discipline Developmental Biology↗
NASA NTRS2008

Modifications to Axially Symmetric Simulations Using New DSMC (2007) Algorithms

Several modifications aimed at improving physical accuracy are proposed for solving axially symmetric problems building on the DSMC (2007) algorithms introduced by Bird. Originally developed to solve nonequilibrium, rarefied flows, the DSMC method is now regularly used to solve complex problems over a wide range of Knudsen numbers. These new algorithms include features such as nearest neighbor collisions excluding the previous collision partners, separate collision and sampling cells, automatically adaptive variable time steps, a modified no-time counter procedure for collisions, and discontinuous and event-driven physical processes. Axially symmetric solutions require radial weighting for the simulated molecules since the molecules near the axis represent fewer real molecules than those farther away from the axis due to the difference in volume of the cells. In the present methodology, these radial weighting factors are continuous, linear functions that vary with the radial position of each simulated molecule. It is shown that how one defines the number of tentative collisions greatly influences the mean collision time near the axis. The method by which the grid is treated for axially symmetric problems also plays an important role near the axis, especially for scalar pressure. A new method to treat how the molecules are traced through the grid is proposed to alleviate the decrease in scalar pressure at the axis near the surface. Also, a modification to the duplication buffer is proposed to vary the duplicated molecular velocities while retaining the molecular kinetic energy and axially symmetric nature of the problem.

Liechty, Derek S.↗
NASA NTRS2004

Ultrasonic Apparatus for Pulverizing Brittle Material

The figure depicts an apparatus that pulverizes brittle material by means of a combination of ultrasonic and sonic vibration, hammering, and abrasion. The basic design of the apparatus could be specialized to be a portable version for use by a geologist in collecting powdered rock samples for analysis in the field or in a laboratory. Alternatively, a larger benchtop version could be designed for milling and mixing of precursor powders for such purposes as synthesis of ceramic and other polycrystalline materials or preparing powder samples for x-ray diffraction or x-ray fluorescence measurements to determine crystalline structures and compositions. Among the most attractive characteristics of this apparatus are its light weight and the ability to function without need for a large preload or a large power supply: It has been estimated that a portable version could have a mass <0.5 kg, would consume less than 1 W h of energy in milling a 1-cm3 volume of rock, and could operate at a preload <10 N. The basic design and principle of operation of this apparatus are similar to those of other apparatuses described in a series of prior NASA Tech Briefs articles, the two most relevant being Ultrasonic/ Sonic Drill/Corers With Integrated Sensors (NPO-20856), Vol. 25, No. 1 (January 2001), page 38 and Ultrasonic/ Sonic Mechanisms for Deep Drilling and Coring (NPO-30291), Vol. 27, No. 9 (September 2003), page 65. As before, vibrations are excited by means of a piezoelectric actuator, an ultrasonic horn, and a mass that is free to move axially over a limited range. As before, the ultrasonic harmonic motion of the horn drives the free-mass in a combination of ultrasonic harmonic and lower-frequency hammering motion. In this case, the free-mass is confined within a hollow cylinder that serves as a crushing chamber, and the free-mass serves as a crushing or milling tool. The hammering of the free-mass against a material sample at the lower end of the chamber grinds the sample into powder in a relatively short time. The restriction of the free-mass to axial motion only makes the grinding very efficient. The free-mass can be fabricated to have teeth on its lower face to enhance the grinding effect. Optionally, there can be a hole at the bottom of the chamber covered with a sieve to tailor the size distribution of the powder leaving the crushing chamber.

Sherrit, Stewart↗
NASA NTRS2016

Multifunctional Graphene-Silicone Elastomer Nanocomposite, Method of Making the Same, and Uses Thereof

A nanocomposite composition having a silicone elastomer matrix having therein a filler loading of greater than 0.05 weight percentage, based on total nanocomposite weight, wherein the filler is functional graphene sheets (FGS) having a surface area of from 300 square meters per gram to 2630 square meters per gram; and a method for producing the nanocomposite and uses thereof.

Pan, Shuyang↗
NASA NTRS2019

Astronaut Mass Balance for Long Duration Missions

Human spaceflight logistics requirements are strongly driven by the daily living needs of the astronauts, including their biological functions. Oxygen, water and food are absolute requirements to sustain life and must be supplied at adequate rates. However, these rates can vary from day to day and from person to person. Beyond the body's immediate physical needs, water is also required for important health and hygiene functions within the spacecraft. Undesirable weight loss or gain aside, human waste product mass outputs will equal the inputs over time, resulting in an average astronaut mass balance. Best values, as well as range of variability for inputs and outputs are explored at both the individual physiological level and the spacecraft level. These values are important for design of life support and habitability systems as well as for mission planning of consumables. Current spacecraft life support systems are not fully closed loop, but the International Space Station (ISS) does recycle most of its air and water. The astronaut mass balances at the personal and vehicle level can have different impacts at different levels of system closure. Recommendations are made for a consistent set of values representing a realistic average astronaut mass balance over reasonable durations for exploration missions.

Ewert, Michael K.↗
NASA NTRSDate not supplied

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth-Moon system. Using Multi-Reward Proximal Policy Optimization, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Christopher J Sullivan↗
NASA NTRS2021

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth- Moon system. Using Multi-Reward Proximal Policy Optimiza- tion, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Mashiku, Alinda K.↗
NASA NTRS2022

A Generalized Dual-Frequency Ratio (DFR) Approach for Rain Retrievals

The dual-frequency ratio of radar reflectivity factors (DFR) has been shown to be a useful quantity as it is independent of the number concentration of the particle size distribution and primarily a function of the mass-weighted particle diameter, Dm. A drawback of DFR-related methods for rain estimation, however, is the non-unique relationship between Dm and DFR. At Ku- and Ka-band frequencies, two solutions for Dm exist when DFR is less than zero. This ambiguity generates multiple solutions for the range profiles of the particle size parameters. We investigate characteristics of these solutions for both the initial-value (forward) and final-value (backward) forms of the equations. To choose one of among many possible range profiles of Dm, number concentration and rain rate, R, independently measured path attenuations are used. For the backward approach the possibility exists of dispensing with externally measured path attenuations by achieving consistency between the input and output path attenuations. The methods are tested by means of a simulation based on disdrometer-measured raindrop size distributions and the results are compared with a simplified version of the operational R-Dm method.

Robert Meneghini↗
NASA NTRSDate not supplied

Multi-Agent Search and Rescue Applied to a Swarm of Ground Vehicles

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used as a weight for the attractiveness of these points in the potential field. The reward value increases while the point is not being observed, and decreases while the point is observed. Collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. Gradient descent of the potential field results in persistent surveillance of the search area. The algorithm generates position commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. The algorithm is applied to a swarm of ground robots, and experimental data is presented showing that the swarm effectively searches the entire area and self-allocates search regions to individual vehicles.

multi-agent↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2022

A Classification of G -invariant Shallow Neural Networks

When trying to fit a deep neural network (DNN) to a G-invariant target function with G a group, it only makes sense to constrain the DNN to be G-invariant as well. However, there can be many different ways to do this, thus raising the problem of “G-invariant neural architecture design”: What is the optimal Ginvariant architecture for a given problem? Before we can consider the optimization problem itself, we must understand the search space, the architectures in it, and how they relate to one another. In this paper, we take a first step towards this goal; we prove a theorem that gives a classification of all G-invariant single-hidden-layer or “shallow” neural network (G-SNN) architectures with ReLU activation for any finite orthogonal group G, and we prove a second theorem that characterizes the inclusion maps or “network morphisms” between the architectures that can be leveraged during neural architecture search (NAS). The proof is based on a correspondence of every G-SNN to a signed permutation representation of G acting on the hidden neurons; the classification is equivalently given in terms of the first cohomology classes of G, thus admitting a topological interpretation. The G-SNN architectures corresponding to nontrivial cohomology classes have, to our knowledge, never been explicitly identified in the literature previously. Using a code implementation, we enumerate the G-SNN architectures for some example groups G and visualize their structure. Lastly, we prove that architectures corresponding to inequivalent cohomology classes coincide in function space only when their weight matrices are zero, and we discuss the implications of this for NAS.

Agrawal, Devanshu↗
NASA NTRS2000

Centrifugation of Cultured Osteoblasts And Macrophages as a Model To Study How Gravity Regulates The Function of Skeletal Cells

Mechanical loading helps define the architecture of weight-bearing bone via the tightly regulated process of skeletal turnover. Turnover occurs by the concerted activity of osteoblasts, responsible for bone formation. and osteoclasts, responsible for bone resorption. Osteoclasts are specialized megakaryon macrophages, which differentiate from monocytes in response to resorption stimuli, such as reduced weight-bearing. Habitation in space dramatically alters musculoskeletal loading, which modulates both cell function and bone structure. Our long-term objective is to define the molecular and cellular mechanisms that mediate skeletal adaptations to altered gravity environments. Our experimental approach is to apply hypergravity loads by centrifugation to rodents and cultured cells. As a first step, we examined the influence of centrifugation on the structure of cancellous bone in rats to test the ability of hypergravity to change skeletal architecture. Since cancellous bone undergoes rapid turnover we expected the most dramatic structural changes to occur in the shape of trabeculae of weight-bearing, cancellous bone. To define the cellular responses to hypergravity loads, we exposed cultured osteoblasts and macrophages to centrifugation. The intraosseous and intramedullary pressures within long bones in vivo reportedly range from 12-40 mm Hg, which would correspond to 18-59 gravity (g) in our cultures. We assumed that hydrostatic pressure from the medium above the cell layer is at least one major component of the mechanical load generated by centrifuging cultured cells. and therefore we exposed the cells to 10-50g. In osteoblasts, we examined the structure of their actin and microtubule networks, production of prostaglandin E2 (PGE2), and cell survival. Analysis of the shape of the cytoskeletal networks provides evidence for the ability of centrifugation to affect cell structure, while the production of PGE2 serves as a convenient marker for mechanical stimulation. We examined cell survival, reasoning that osteoblasts might mold skeletal structure in a hypergravity environment in part by regulating apoptosis and thus the duration of osteoblast productivity. Finally, we tested the influence of centrifugation on microbial activation of a macrophage cell line (RAW264.7). In response to the appropriate hormonal stimulation, this cell line is reportedly capable of undergoing differentiation to express osteoclast markers. In addition, a component of the cell wall of gram-negative bacteria, lipopolysaccaride (LPS), stimulates the formation of osteoclasts in vivo. Thus we tested the influence on centrifugation on RAW264.7 cells stimulated with LPS to provide an index of the function of osteoclast precursors.

Globus, Ruth K.↗
DOE OSTI2022

Novel Mutant Alleles Reveal a Role of the Extra-Large G Protein in Rice Grain Filling, Panicle Architecture, Plant Growth, and Disease Resistance

Plant growth and grain filling are the key agronomical traits for grain weight and yield of rice. The continuous improvement in rice yield is required for a future sustainable global economy and food security. The heterotrimeric G protein complex containing a canonical α subunit (RGA1) couples extracellular signals perceived by receptors to modulate cell function including plant development and grain weight. We hypothesized that, besides RGA1, three atypical, extra-large GTP-binding protein (XLG) subunits also regulate panicle architecture, plant growth, development, grain weight, and disease resistance. Here, we identified a role of XLGs in agronomic traits and stress tolerance by genetically ablating all three rice XLGs individually and in combination using the CRISPR/Cas9 genome editing in rice. For this study, eight (three single, two double, and three triple) null mutants were selected. Three XLG proteins combinatorically regulate seed filling, because loss confers a decrease in grain weight from 14% with loss of one XLG and loss of three to 32% decrease in grain weight. Null mutations in XLG2 and XLG4 increase grain size. The mutants showed significantly reduced panicle length and number per plant including lesser number of grains per panicle compared to the controls. Loss-of-function of all individual XLGs contributed to 9% more aerial biomass compared to wild type (WT). The double mutant showed improved salinity tolerance. Moreover, loss of the XLG gene family confers hypersensitivity to pathogens. Our findings suggest that the non-canonical XLGs play important roles in regulating rice plant growth, grain filling, panicle phenotype, stress tolerance, and disease resistance. Genetic manipulation of XLG s has the potential to improve agronomic properties in rice.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Spectral properties of ice-particulate mixtures and implications for remote sensing. I - Intimate mixtures

From laboratory spectra of many ice-particulate mixtures with high, medium, and low albedo particulates, the band depths, continuum reflectance, and ratio of band depth to continuum reflectance are derived as a function of the logarithm of thef particulate weight fraction in the sample. Ice band depths are dependent on the particulate albedo, and increase with smaller weight fractions of particulates until the bands saturate and their depths decrease. While the continuum reflectance is a complex function of the particulate albedo and wavelength of light, the band depth-to-continuum reflectance ratios appear independent of particulate albedo in such a fashion that, for a given grain size of particulate, a calibration curve to the abundance of ice and particulates is derived. Theoretically produced frost spectra show similar curves of growth for band depth, continuum reflectance, and corresponding ratio vs the photon mean optical path length.

Clark, R. N.↗
NASA NTRS1922

The dead weight of the airship and the number of passengers that can be carried

In order to determine an approximate formula giving the weight of a dead load as a function of the volume (V) of the envelope and of the maximum velocity (v), we will take the relative weight of the various parts of the airship (P(sub v), M, V, A, T(sup 34)), adopting a mean value of the coefficients determined. This formula may be adopted both for semi-rigid airships with suspended nacelle and non-rigid envelope, with or without internal suspensions. It may also be adapted to airships with rigid longitudinal beam, with power units on external supports or in nacelles, and with non-rigid envelopes, with or without internal bracing cables.

CROCCO↗