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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Growing B Lymphocytes in a Three-Dimensional Culture System

A three-dimensional (3D) culture system for growing long-lived B lymphocytes has been invented. The capabilities afforded by the system can be expected to expand the range of options for immunological research and related activities, including testing of immunogenicity of vaccine candidates in vitro, generation of human monoclonal antibodies, and immunotherapy. Mature lymphocytes, which are the effectors of adaptive immune responses in vertebrates, are extremely susceptible to apoptotic death, and depend on continuous reception of survival-inducing stimulation (in the forms of cytokines, cell-to-cell contacts, and antigen receptor signaling) from the microenvironment. For this reason, efforts to develop systems for long-term culture of functional, non-transformed and non-activated mature lymphocytes have been unsuccessful until now. The bone-marrow microenvironment supports the growth and differentiation of many hematopoietic lineages, in addition to B-lymphocytes. Primary bone-marrow cell cultures designed to promote the development of specific cell types in vitro are highly desirable experimental systems, amenable to manipulation under controlled conditions. However, the dynamic and complex network of stromal cells and insoluble matrix proteins is disrupted in prior plate- and flask-based culture systems, wherein the microenvironments have a predominantly two-dimensional (2D) character. In 2D bone-marrow cultures, normal B-lymphoid cells become progressively skewed toward precursor B-cell populations that do not retain a normal immunophenotype, and such mature B-lymphocytes as those harvested from the spleen or lymph nodes do not survive beyond several days ex vivo in the absence of mitogenic stimulation. The present 3D culture system is a bioreactor that contains highly porous artificial scaffolding that supports the long-term culture of bone marrow, spleen, and lymph-node samples. In this system, unlike in 2D culture systems, B-cell subpopulations developing within 3D cultures that have been modified to foster lymphopoiesis retain an immunophenotype that closely recapitulates cells in fresh bone marrow harvests. The 3D culture system has been found to be capable of supporting long-lived (8 weeks) populations of B and T lymphocytes from peripheral lymphoid organs, in the absence of activation signals, to an extent not achievable by conventional culture techniques. Interestingly, it has been found that 3D-culture B cells display a phenotype that has characteristics of both B1a and B2 cells. These promising preliminary observations suggest that the 3D culture system could be used with success in the study of peripheral-B-lymphocyte biology and in the development of biotechnological techniques and processes.

Wu, J. H. David↗
NASA NTRS2003

Earth-Space Link Attenuation Estimation via Ground Radar Kdp

A method of predicting attenuation on microwave Earth/spacecraft communication links, over wide areas and under various atmospheric conditions, has been developed. In the area around the ground station locations, a nearly horizontally aimed polarimetric S-band ground radar measures the specific differential phase (Kdp) along the Earth-space path. The specific attenuation along a path of interest is then computed by use of a theoretical model of the relationship between the measured S-band specific differential phase and the specific attenuation at the frequency to be used on the communication link. The model includes effects of rain, wet ice, and other forms of precipitation. The attenuation on the path of interest is then computed by integrating the specific attenuation over the length of the path. This method can be used to determine statistics of signal degradation on Earth/spacecraft communication links. It can also be used to obtain real-time estimates of attenuation along multiple Earth/spacecraft links that are parts of a communication network operating within the radar coverage area, thereby enabling better management of the network through appropriate dynamic routing along the best combination of links.

Bolen, Steven M.↗
NASA NTRS2012

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

Mixed Integer Programming↗
DOE OSTI2023

Reversible Reactions, Mesh Size, and Segmental Dynamics Control Penetrant Diffusion in Ethylene Vitrimers

The diffusion of two aromatic dyes with nearly identical sizes was measured in ethylene vitrimers with precise linker lengths and borate ester cross-links using fluorescence recovery after photobleaching (FRAP). One dye possessed a reactive hydroxyl group, while the second was inert. The reaction of the hydroxyl group with the network is slow relative to the hopping times of the dye, resulting in a large slowdown by a factor of 50 for a reactive probe molecule. A kinetic model was fit to the fluorescence intensity data to determine rate constants for the reversible reaction of the dye from the network, which confirms the role of slow reaction kinetics. A second network cross-linker was also investigated with a substituted boronic ester showing ∼10,000 times faster exchange kinetics. In this system, the two dyes show the same diffusion coefficient, as the reaction is no longer the rate-limiting step. The role of dense meshes on small and large dyes is also discussed in the context of the existing theories. Finally, these results highlight the potential of dynamic networks to control penetrant transport through synergistic effects of the mesh size, dynamic bond kinetics, and penetrant–network interactions.

confinement↗
NASA NTRS1998

Neural Networks for Rapid Design and Analysis

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

Sparks, Dean W., Jr.↗
DOE OSTI2022

Distribution Cutoff for Clusters near the Gel Point

The mechanical and dynamic properties of developing networks near the gel point are susceptible to the distribution of clusters coexisting with percolating networks. The distribution of cluster numbers follows a broad power law, wrapped by a cutoff function that rapidly decays at a characteristic size. The form of the cutoff function has been speculated based on known results from lattice percolation and, in certain cases, solved. We obtained this cutoff function from simulated dynamic clusters of polymeric precursor chains using a hybrid Monte Carlo algorithm. The results obtained from three different precursor chain lengths are consistent with each other and are consistent with the expectation from lattice percolation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Creative-Dynamics Approach To Neural Intelligence

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Zak, Michail A.↗
DOE OSTI2024

Point spread function deconvolution using a convolutional autoencoder

A major issue in optical astronomical image analysis is the combined effect of the instrument’s point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation dependent. In this work we present a very simple neural network based approach to nonblind image deconvolution that relies on feeding a convolutional autoencoder (CAE) input images that have been preprocessed by convolution with the corresponding PSF and its regularized inverse, a method which is both conceptually simple and computationally less intensive. We also present here, a new approach for dealing with limited input dynamic range of neural networks compared to the dynamic range present in astronomical images.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A generalized Flory-Stockmayer kinetic theory of connectivity percolation and rigidity percolation of cytoskeletal networks

Actin networks are essential for living cells to move, reproduce, and sense their environments. The dynamic and rheological behavior of actin networks is modulated by actin-binding proteins such as α-actinin, Arp2/3, and myosin. There is experimental evidence that actin-binding proteins modulate the cooperation of myosin motors by connecting the actin network. In this work, we present an analytical mean field model, using the Flory-Stockmayer theory of gelation, to understand how different actin-binding proteins change the connectivity of the actin filaments as the networks are formed. We follow the kinetics of the networks and estimate the concentrations of actin-binding proteins that are needed to reach connectivity percolation as well as to reach rigidity percolation. We find that Arp2/3 increases the actomyosin connectivity in the network in a non-monotonic way. We also describe how changing the connectivity of actomyosin networks modulates the ability of motors to exert forces, leading to three possible phases of the networks with distinctive dynamical characteristics: a sol phase, a gel phase, and an active phase. Thus, changes in the concentration and activity of actin-binding proteins in cells lead to a phase transition of the actin network, allowing the cells to perform active contraction and change their rheological properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Software-Defined Data Center Network Architecture using VXLAN-based BGP EVPN for Dynamic Workflows in a Supercomputing Environment (VXLAN-based BGP EVPN Fabric for HPC) v1

This software repository automates the deployment of a multi-vendor VXLAN-based BGP EVPN architecture, leveraging Containerlab to instantiate a stretched CLOS topology. It integrates Linux, Nokia SR Linux, and Arista cEOS, using BGP for underlay, overlay, and topology extension. The software enables rapid prototyping and testing of advanced network configurations. Its key advantage lies in providing a dynamic, programmable environment for research and development of critical technologies supporting dynamic workflows within supercomputing environments, surpassing the limitations of static, vendor-locked alternatives by fostering interoperability and agility.

Kumar, Ronal [Lawrence Berkeley National Laborator↗
DOE OSTI2020

Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands, e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with different processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deciphering the Cofilin Oligomers via Intermolecular Disulfide Bond Formation: A Coarse-Grained Molecular Dynamics Approach to Understanding Cofilin’s Regulation on Actin Filaments

Cofilin, a key actin-binding protein, orchestrates the dynamics of the actomyosin network through its actin-severing activity and by promoting the recycling of actin monomers. Recent experimental work suggests that cofilin also forms functionally distinct oligomers through thiol post-translational modification (PTM) that encourages actin nucleation and assembly. Despite these advances, the structural conformations of cofilin oligomers that modulate actin activity remain elusive because there are combinatorial ways to oxidize thiols in cysteines to form disulfide bonds rapidly. This study employs molecular dynamics simulations to investigate human cofilin 1 as a case study for exploring cofilin dimers via disulfide bond formation. Using the free energy profiling, our simulations unveil a range of probable cofilin dimer structures not represented in current Protein Data Bank entries. These candidate dimers are characterized by their distinct population distributions and relative free energies. Of particular note is a dimer featuring an interface between cysteines 139 and 147 residues, which demonstrates stable free energy characteristics and intriguingly symmetrical geometry. In contrast, the experimentally proposed dimer structure exhibits a less stable free energy profile. Here, we also evaluate frustration quantification based on the energy landscape theory in the protein-protein interactions at the dimer interfaces. Notably, the 39-39 dimer configuration emerges as a promising candidate for forming cofilin tetramers, as substantiated by frustration analysis. Additionally, docking simulations with actin filaments further evaluate the stability of these cofilin dimer-actin complexes. Our findings thus offer a computational framework for understanding the role of thiol post-translational modification cofilin proteins in regulating oligomerization, and the subsequent cofilin-mediated actin dynamics in the actomyosin network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Topology induced crossover between Langevin, subdiffusion, and Brownian diffusion regimes in supercooled water

Despite extensive studies of supercooled water, it remains challenging to understand its peculiar dynamic anomalous properties. In this work, we integrated full atomistic simulations of supercooled water over the temperature range of room temperature to 200 K using a quantum-mechanics-based polarizable force field with the dressed dynamics method that couples fast collision events and slow reorganization dynamics of hydrogen-bond networks. Our analysis unveils the salient multiscale features in the transient relaxation dynamics of supercooled water. A classical Langevin behavior dominates at fast timescales, while long-time relaxations unveil two different activation barriers in two temperature regions: below and above 230 K. The modulation of the entropy spectrum by temperature is elucidated in terms of a three-state model underlined by the complexity of the water dynamics associated with a topological transition of a strong hydrogen-bond network. This state-dependent network topology is quantitatively characterized by power-law exponents of inverse network connectivity from 200 to 298 K. Finally, this work provides valuable guidance for further studies on the transient relaxation dynamics of supercooled water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Buffer Management Simulation in ATM Networks

This paper presents a simulation of a new dynamic buffer allocation management scheme in ATM networks. To achieve this objective, an algorithm that detects congestion and updates the dynamic buffer allocation scheme was developed for the OPNET simulation package via the creation of a new ATM module.

simulations Asynchronous Transfer Mode ATM Switch ↗
DOE OSTI2023

Physics informed machine learning for chemistry tabulation

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent transport. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two sub-systems evolve, the two sub-systems are typically (re)solved separately. Popular approaches such as the Flamelet Generated Manifolds (FGM) use a two-step strategy where the governing reaction kinetics are pre-computed and mapped to a low-dimensional manifold, characterized by a few reaction progress variables (model reduction) and the manifold is then “looked-up” during the run-time to estimate the high-dimensional system state by the turbulent transport system. While existing works have focused on these two steps independently, in this work we show that joint learning of the progress variables and the look-up model, can yield more accurate results. Here, we build on the base formulation and implementation to include the dynamically generated Thermochemical State Variables (Lower Dimensional Dynamic Source Terms). We discuss the challenges in the implementation of this deep neural network architecture and experimentally demonstrate its superior performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗
NASA NTRS1984

Inversion Algorithms for Water Vapor Radiometers Operating at 20.7 and 31.4 Ghz

Eight water vapor radiometers (WVRs) were constructed as research and development tools to support the Advanced System Programs in the Deep Space Network and the Crustal Dynamics Project. These instruments are intended to operate at the stations of the Deep Space Network (DSN), various radio observatories, and obile facilities that participate in very long baseline interferometric (VLBI) experiments. It is expected that the WVRs will operate in a wide range of meteorological conditions. Several algorithms are discussed that are used to estimate the line-of-sight path delay due to water vapor and columnar liquid water rom the observed microwave brightness temperatures provided by the WVRs. In particular, systematic effects due to site and seasonal variations are examined. The accuracy of the estimation as indicated by a simulation calculation is approximately 0.3 cm for a noiseless WVR in clear and moderately cloudy weather. With a realistic noise model of WVR behavior, the inversion accuracy is approximately 0.6 cm.

Resch, G. M.↗