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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Multi-Physics Topology Optimization for Dual Flow Heat Exchangers

Current heat exchanger (HX) designs are subjected to strict constraints pertaining to their manufacturability through conventional lengthy and expensive processes consisting of subtractive, forming and brazing processes. Therefore, existing HXs are typically restricted to the classical and rather simple geometries, such as plate-fin or shell-tube geometries, with lower efficiency and larger size. To increase HX efficiencies, novel designs are needed. Recent advances in topology optimization (TO) and additive manufacturing (AM) offer significant flexibility in design and fabrication of complex geometries, with potentially superior thermo-mechanical performance and high-power density. On the other hand, there is no commercially available software tool that addresses the combined coupling of structural, fluid dynamics, and thermal with multiple materials (hot and cold streams, solid, and void space) in TO of HXs. The goal of this project is to develop a multi-physics multi-phase TO approach to enhance the performance of HXs. The optimized design will be additively manufactured and tested in a physical environment to quantify its performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions

Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Laboratory Plasma Source as an MHD Model for Astrophysical Jets

The significance of the work described herein lies in the demonstration of Magnetized Coaxial Plasma Gun (MCG) devices like CPS-1 to produce energetic laboratory magneto-flows with embedded magnetic fields that can be used as a simulation tool to study flow interaction dynamic of jet flows, to demonstrate the magnetic acceleration and collimation of flows with primarily toroidal fields, and study cross field transport in turbulent accreting flows. Since plasma produced in MCG devices have magnetic topology and MHD flow regime similarity to stellar and extragalactic jets, we expect that careful investigation of these flows in the laboratory will reveal fundamental physical mechanisms influencing astrophysical flows. Discussion in the next section (sec.2) focuses on recent results describing collimation, leading flow surface interaction layers, and turbulent accretion. The primary objectives for a new three year effort would involve the development and deployment of novel electrostatic, magnetic, and visible plasma diagnostic techniques to measure plasma and flow parameters of the CPS-1 device in the flow chamber downstream of the plasma source to study, (1) mass ejection, morphology, and collimation and stability of energetic outflows, (2) the effects of external magnetization on collimation and stability, (3) the interaction of such flows with background neutral gas, the generation of visible emission in such interaction, and effect of neutral clouds on jet flow dynamics, and (4) the cross magnetic field transport of turbulent accreting flows. The applicability of existing laboratory plasma facilities to the study of stellar and extragalactic plasma should be exploited to elucidate underlying physical mechanisms that cannot be ascertained though astrophysical observation, and provide baseline to a wide variety of proposed models, MHD and otherwise. The work proposed herin represents a continued effort on a novel approach in relating laboratory experiments to astrophysical jet observation. There exists overwhelming similarity among these flows that has already produced some fascinating results and is expected to continue a high pay off in future flow similarity studies.

Mayo, Robert M.↗
NASA NTRS2008

Numerical Investigation of Plasma Detachment in Magnetic Nozzle Experiments

At present there exists no generally accepted theoretical model that provides a consistent physical explanation of plasma detachment from an externally-imposed magnetic nozzle. To make progress towards that end, simulation of plasma flow in the magnetic nozzle of an arcjet experiment is performed using a multidimensional numerical simulation tool that includes theoretical models of the various dispersive and dissipative processes present in the plasma. This is an extension of the simulation tool employed in previous work by Sankaran et al. The aim is to compare the computational results with various proposed magnetic nozzle detachment theories to develop an understanding of the physical mechanisms that cause detachment. An applied magnetic field topology is obtained using a magnetostatic field solver (see Fig. I), and this field is superimposed on the time-dependent magnetic field induced in the plasma to provide a self-consistent field description. The applied magnetic field and model geometry match those found in experiments by Kuriki and Okada. This geometry is modeled because there is a substantial amount of experimental data that can be compared to the computational results, allowing for validation of the model. In addition, comparison of the simulation results with the experimentally obtained plasma parameters will provide insight into the mechanisms that lead to plasma detachment, revealing how they scale with different input parameters. Further studies will focus on modeling literature experiments both for the purpose of additional code validation and to extract physical insight regarding the mechanisms driving detachment.

Sankaran, Kamesh↗
NASA NTRS2012

Compositional Effects on Nickel-Base Superalloy Single Crystal Microstructures

Fourteen nickel-base superalloy single crystals containing 0 to 5 wt% chromium (Cr), 0 to 11 wt% cobalt (Co), 6 to 12 wt% molybdenum (Mo), 0 to 4 wt% rhenium (Re), and fixed amounts of aluminum (Al) and tantalum (Ta) were examined to determine the effect of bulk composition on basic microstructural parameters, including gamma' solvus, gamma' volume fraction, volume fraction of topologically close-packed (TCP) phases, phase chemistries, and gamma - gamma'. lattice mismatch. Regression models were developed to describe the influence of bulk alloy composition on the microstructural parameters and were compared to predictions by a commercially available software tool that used computational thermodynamics. Co produced the largest change in gamma' solvus over the wide compositional range used in this study, and Mo produced the largest effect on the gamma lattice parameter and the gamma - gamma' lattice mismatch over its compositional range, although Re had a very potent influence on all microstructural parameters investigated. Changing the Cr, Co, Mo, and Re contents in the bulk alloy had a significant impact on their concentrations in the gamma matrix and, to a smaller extent, in the gamma' phase. The gamma phase chemistries exhibited strong temperature dependencies that were influenced by the gamma and gamma' volume fractions. A computational thermodynamic modeling tool significantly underpredicted gamma' solvus temperatures and grossly overpredicted the amount of TCP phase at 982 C. Furthermore, the predictions by the software tool for the gamma - gamma' lattice mismatch were typically of the wrong sign and magnitude, but predictions could be improved if TCP formation was suspended within the software program. However, the statistical regression models provided excellent estimations of the microstructural parameters based on bulk alloy composition, thereby demonstrating their usefulness.

MacKay, Rebecca A.↗
DOE OSTI2023

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

Abstract An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. Graphical abstract OFraMP applied to paclitaxel (ATB ID 35922).

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

Enhanced dynamic contingency analysis for power systems

The present disclosure describes systems and techniques that enhance effectiveness and efficiency of a contingency analysis tool that is used for studying the magnitude and likelihood of extreme contingencies and potential cascading events across a power system. The described systems and techniques include deploying the contingency analysis tool in a high-performance computing (HPC) environment and incorporating visual situational awareness approaches to allow power system engineers to quickly and efficiently evaluate multiple power system simulation models. Furthermore, the described systems and techniques include the power system contingency-analysis tool calculating and coordinating protection element settings, as well as assessing controls of the power system using small-signal nomograms, allowing power system engineers to more effectively comprehend, evaluate, and analyze causes and effects of cascading events against a topology of a power system.

Samaan, Nader A.↗
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗
DOE OSTI2021

Revealing functional insights into ER proteostasis through proteomics and interactomics

The endoplasmic reticulum (ER), responsible for processing approximately one-third of the human proteome including most secreted and membrane proteins, plays a pivotal role in protein homeostasis (proteostasis). Dysregulation of ER proteostasis has been implicated in a number of disease states. As such, continued efforts are directed at elucidating mechanisms of ER protein quality control which are mediated by transient and dynamic protein-protein interactions with molecular chaperones, co-chaperones, protein folding and trafficking factors that take place in and around the ER. Technological advances in mass spectrometry have played a pivotal role in characterizing and understanding these protein-protein interactions that dictate protein quality control mechanisms. Here, we highlight the recent progress from mass spectrometry-based investigation of ER protein quality control in revealing the topological arrangement of the proteostasis network, stress response mechanisms that adjust the ER proteostasis capacity, and disease specific changes in proteostasis network engagement. We close by providing a brief outlook on underexplored areas of ER proteostasis where mass spectrometry is a tool uniquely primed to further expand our understanding of the regulation and coordination of protein quality control processes in diverse diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1997

An Adaptive Flow Solver for Air-Borne Vehicles Undergoing Time-Dependent Motions/Deformations

This report describes a concurrent Euler flow solver for flows around complex 3-D bodies. The solver is based on a cell-centered finite volume methodology on 3-D unstructured tetrahedral grids. In this algorithm, spatial discretization for the inviscid convective term is accomplished using an upwind scheme. A localized reconstruction is done for flow variables which is second order accurate. Evolution in time is accomplished using an explicit three-stage Runge-Kutta method which has second order temporal accuracy. This is adapted for concurrent execution using another proven methodology based on concurrent graph abstraction. This solver operates on heterogeneous network architectures. These architectures may include a broad variety of UNIX workstations and PCs running Windows NT, symmetric multiprocessors and distributed-memory multi-computers. The unstructured grid is generated using commercial grid generation tools. The grid is automatically partitioned using a concurrent algorithm based on heat diffusion. This results in memory requirements that are inversely proportional to the number of processors. The solver uses automatic granularity control and resource management techniques both to balance load and communication requirements, and deal with differing memory constraints. These ideas are again based on heat diffusion. Results are subsequently combined for visualization and analysis using commercial CFD tools. Flow simulation results are demonstrated for a constant section wing at subsonic, transonic, and a supersonic case. These results are compared with experimental data and numerical results of other researchers. Performance results are under way for a variety of network topologies.

Singh, Jatinder↗
NASA NTRSDate not supplied

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗
DOE OSTI2022

Handing off the outcome of binary neutron star mergers for accurate and long-term postmerger simulations

In this work, we perform binary neutron star (BNS) merger simulations in full dynamical general relativity with IllinoisGRMHD, on a Cartesian grid with adaptive-mesh refinement. After the remnant black hole has become nearly stationary, the evolution of the surrounding accretion disk on Cartesian grids over long timescales (~1s) is suboptimal, as Cartesian coordinates over-resolve the angular coordinates at large distances, and the accreting plasma flows obliquely across coordinate lines dissipating angular momentum artificially from the disk. To address this, we present the HandOff, a set of computational tools that enables the transfer of general relativistic magnetohydrodynamic (GRMHD) and spacetime data from IllinoisGRMHD to harm3d, a GRMHD code that specializes in modeling black hole accretion disks in static spacetimes over long timescales, making use of general coordinate systems with spherical topology. We demonstrate that the handoff allows for a smooth and reliable transition of GRMHD fields and spacetime data, enabling us to efficiently and reliably evolve BNS dynamics well beyond merger. We also discuss future plans, which involve incorporating advanced equations of state and neutrino physics into BNS simulations using the HandOff approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Elucidating Abnormal Grain Growth in Thermomagnetic Processed Materials with Transfer Learning and Reinforcement Learning

The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Topological Analysis of Temporal Hypergraphs

In this work we study the topological properties of temporal hypergraphs. Hypergraphs provide a higher dimensional generalization of a graph that is capable of capturing multi-way connections. As such, they have become an integral part of network science. A common use of hypergraphs is to model events as hyperedges in which the event can involve many elements as nodes. This provides a more complete picture of the event in comparison to the standard dyadic connection limitation of a graph. However, a common attribution to events is temporal information as an interval for when the event occurred. Consequently, a temporal hypergraph is born which accurately captures both the temporal information of events as well as their multi-way connections. Common tools for studying these temporal hypergraphs typically use summary statistics of snapshots from a sliding window procedure to capture changes in the underlying dynamics. However, these do not provide insight into how the changing structure of the hypergraph evolves and which components of the temporal hypergraph persist and are influential to the underlying system. To alleviate this need we leverage zigzag persistence from the field of Topological Data Analysis (TDA) to study the change in topological structure of time-evolving hypergraphs. We apply our pipeline to both a cyber security and social network dataset and show how the topological structure of their temporal hypergraphs change and can be used to understand the underlying dynamics.

hypergraphs, topological data analysis, zigzag per↗
DOE OSTI2023

Symmetry-specific characterization of bond orientation order in DNA-assembled nanoparticle lattices

Bond-orientational order in DNA-assembled nanoparticles lattices is explored with the help of recently introduced Symmetry-specific Bond Order Parameters (SymBOPs). Here, this approach provides a more sensitive analysis of local order than traditional scalar BOPs, facilitating the identification of coherent domains at the single bond level. The present study expands the method initially developed for assemblies of anisotropic particles to the isotropic ones or cases where particle orientation information is unavailable. The SymBOP analysis was applied to experiments on DNA-frame-based assembly of nanoparticle lattices. It proved highly sensitive in identifying coherent crystalline domains with different orientations, as well as detecting topological defects, such as dislocations. Furthermore, the analysis distinguishes individual sublattices within a single crystalline domain, such as pair of interpenetrating FCC lattices within a cubic diamond. The results underscore the versatility and robustness of SymBOPs in characterizing ordering phenomena, making them valuable tools for investigating structural properties in various systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Abstract We introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command-line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelization on high-performance cluster systems, which enables high-throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.

Kainer, David (ORCID:0000000172714676)↗
NASA NTRS1983

Coherent structures - Reality and myth

Large-scale coherent structures (CS) in turbulent shear flows are characterized, reviewing recent theoretical and experimental investigations. The use of computers as a research tool and the flow-visualization experimental technique are introduced, CS are defined, the history of their discovery is traced, and their main characteristics are listed. Topics discussed and illustrated include the initial condition of the free shear layer, triple and double decomposition, topological features of CS, detection and eduction of CS, phase alignment via cross correlation, induced versus natural structures, the bursting phenomenon, turbulent spot, streaks, bursting frequency, the axisymmetric mixing layer, vortex pairing in an axisymmetric jet, CS and jet noise, broadband noise amplification via pure-tone excitation, CS interaction in a plane-jet near field, the Taylor hypothesis applied to CS, negative production, and the validity of the Reynolds-number similarity hypothesis. It is found that the coherent Reynolds stress, vorticity, and production are not much greater than the time-averaged values for fully developed flows with significant incoherent turbulence, suggesting that the importance of CS may have been exaggerated in some recent studies.

Hussain, A. K. M. F.↗
DOE OSTI2023

The MIGDAL experiment: Measuring a rare atomic process to aid the search for dark matter

We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking experimental confirmation. Our goal is to detect the predicted atomic electron emission which is thought to accompany nuclear scattering with low, but calculable, probability, by deploying an Optical Time Projection Chamber filled with a low-pressure gas based on CF 4 . Initially, pure CF 4 will be used, and then in mixtures containing other elements employed by leading dark matter search technologies — including noble species, plus Si and Ge. High resolution track images generated by a Gas Electron Multiplier stack, together with timing information from scintillation and ionisation readout, will be used for 3D reconstruction of the characteristic event topology expected for this process — an arrangement of two tracks sharing a common vertex, with one belonging to a Migdal electron and the other to a nuclear recoil. Different energy-loss rate distributions along both tracks will be used as a powerful discrimination tool against background events. In this article we present the design of the experiment, informed by extensive particle and track simulations and detailed estimations of signal and background rates. In pure CF 4 we expect to observe 8.9 (29.3) Migdal events per calendar day of exposure to an intense D–D (D–T) neutron generator beam at the NILE facility located at the Rutherford Appleton Laboratory (UK). With our nominal assumptions, 5σ median discovery significance can be achieved in under one day with either generator.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗