Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “stability graph”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Consensus-Based Formation Control of a Class of Multi-Agent Systems

This paper presents a consensus-based formation control scheme for autonomous multi-agent systems represented by double integrator dynamics. Assuming that the information graph topology consists of an undirected connected graph, a leader-based consensus-type control law is presented and shown to provide asymptotic formation stability when subjected to piecewise constant formation velocity commands. It is also shown that global asymptotic stability is preserved in the presence of (0, infinity)- sector monotonic non-decreasing actuator nonlinearities.

Joshi, Suresh↗

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling. Dynamic spatial-temporal dependencies in traffic data make traffic flow forecasting to be a challenging task. Most existing research cannot model dynamic spatial and temporal correlations to achieve well-forecasting performance. The multi-head self-attention mechanism is a valuable method to capture dynamic spatial-temporal correlations, and combining it with graph convolutional networks is a promising solution. Therefore, we propose a multi-head self-attention spatiotemporal graph convolutional network (MSASGCN) model. It can effectively capture local correlations and potential global correlations of spatial structures, can handle dynamic evolution of the road network, and, in the time dimension, can effectively capture dynamic temporal correlations. Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. Compared with advanced traffic flow forecasting methods, our model also has a performance improvement and a more stable prediction performance. We also discuss some problems and challenges in traffic forecasting.

Cao, Yang↗

Automated Detection of Instability-Inducing Channel Geometry Transitions in Saint-Venant Simulation of Large-Scale River Networks

A new sweep-search algorithm (SSA) is developed and tested to identify the channel geometry transitions responsible for numerical convergence failure in a Saint-Venant equation (SVE) simulation of a large-scale open-channel network. Numerical instabilities are known to occur at “sharp” transitions in discrete geometry, but the identification of problem locations has been a matter of modeler’s art and a roadblock to implementing large-scale SVE simulations. The new method implements techniques from graph theory applied to a steady-state 1D shallow-water equation solver to recursively examine the numerical stability of each flowpath through the channel network. The SSA is validated with a short river reach and tested by the simulation of ten complete river systems of the Texas–Gulf Coast region by using the extreme hydrological conditions recorded during hurricane Harvey. The SSA successfully identified the problematic channel sections in all tested river systems. Subsequent modification of the problem sections allowed stable solution by an unsteady SVE numerical solver. The new SSA approach permits automated and consistent identification of problem channel geometry in large open-channel network data sets, which is necessary to effectively apply the fully dynamic Saint-Venant equations to large-scale river networks or for city-wide stormwater networks.

54 ENVIRONMENTAL SCIENCES↗

A simple element for aeroelastic analysis of undamaged and damaged wings

The effects of material damage on the aeroelastic response of an anisotropic composite wing are investigated analytically. The wing is modeled as a Timoshenko beam of arbitrary cross section, applying a 24-DOF one-dimensional beam element and Cartesian coordinates. The formulations for the element stiffness matrix, the strain-displacement relations, the box-beam constitutive relations, the contributions of stringers and web, and the warping correction factor are outlined; the application of strip theory in deriving the aerodynamic model is briefly explained; and numerical results are presented in extensive graphs. It is shown that asymmetry and damage can induce bending-stretching coupling phenomena and thereby affect the stability of the aircraft either positively or negatively. The need to take such effects into account in the design of advanced composite wings is stressed.

Kapania, Rakesh K.↗

Attitude dynamic of spin-stabilized satellites with flexible appendages

Equations of motion and computer programs have been developed for analyzing the motion of a spin-stabilized spacecraft having long, flexible appendages. Stability charts were derived, or can be redrawn with the desired accuracy for any particular set of design parameters. Simulation graphs of variables of interest are readily obtainable on line using program FLEXAT. Finally, applications to actual satellites, such as UK-4 and IMP-1 have been considered.

Renard, M. L.↗

Opportunity for academic research in a low-gravity environment - Crystal growth

The history of basic and applied research on crystal growth (CG), especially of semiconductor materials, is reviewed, stressing the dominance (at least in the U.S.) of industrial R&D projects over academic programs and the need for more extensive fundamental investigations. The NASA microgravity research program and the recommendations of the University Space Research Association are examined as they affect the availability of space facilities for academic CG research. Also included is a report on ground experiments on the effectiveness of magnetic fields in controlling vertical Bridgman CG and melt stability, using the apparatus employed in the Apollo-Soyuz experiments (Witt et al., 1978); the results are presented in graphs and briefly characterized. The role of NASA's microgravity CG program in stimulating academic work on CG, the importance of convection effects, CG work on materials other than semiconductors, and NSF support of CG research are discussed in a comment by R. F. Sekerka.

Matthiesen, D. H.↗

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper II: Local Geometry and Metric Structure

This paper develops the geometric sector of the replication-driven cosmogenesis framework introduced in Paper I. Starting from a pre-geometric spectral substrate and a minimal set of replication axioms, we show how coherent self-replicating units generate a spatial adjacency graph whose continuum limit acquires an effective Riemannian structure. The replication dynamics determines a characteristic correlation length that seeds the local metric, while overlap relations among coherent units produce an isotropic neighborhood geometry with an emergent dimensionality $d_{\rm eff}\simeq 3$ across a broad range of replication factors. As replication slows and causal order stabilizes, a limiting signal speed $c_\ast$ appears, providing the basis for the Lorentzian structure of spacetime without assuming a pre-existing light cone. We derive conditions under which the adjacency graph converges to a smooth three-dimensional manifold, describe the transition from Euclidean to Lorentzian propagation, and identify geometric invariants controlled by the replication parameters. This work establishes the geometric and causal layer of the replication cosmogenesis program, bridging the spectral axioms of Paper I to the cosmological dynamics explored in Paper III.

79 ASTRONOMY AND ASTROPHYSICS↗

The Qualification of Sealability and Creep Relaxation of Additively Manufactured Zytel Gaskets for PEM Fuel Cells

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target material for this study is Zytel by DuPont Chemical. The mechanical stability will be assessed via sealability and creep relaxation testing according to ASTM F37B and ASTM F38B respectively. Because the capabilities to conduct sealability testing at temperature were not available, each specimen was thermally soaked and allowed to return to room temperature prior to testing. As a result of sealability experiments, the 100°C-soaked specimens resulted in lower leak rates with a higher precision when compared to specimens soaked at -55°C and 22°C at across all compressive loads. It was observed from results from creep relaxation testing that there is thermal contraction and expansion occurring at 55°C and 100°C respectively, which can be observed by the resultant graphs. The recoverability of thermally cycled specimens are better than those that just experienced a high temperature hold. After the seven-day thermal cycle, the samples stabilized and maintained their structure.

Lazarin, Robert↗

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗

Spatial deadlocks in task-level planning

We will formulate the problem of resolving spatial (space occupancy and support-stability) interactions in terms of tools developed in Operating Systems for the problems of deadlocks and synchronization. We show how to construct state graphs and to detect resource contentions and deadlocks from these state graphs. We describe an algorithm, called CONTAC, to deal with deadlocks where 'processes' represent the ordered motions of parts. The algorithm is a monitor-like process using preventative preemptive protocol to resolve higher-degree deadlocks. We develop the representation for knowledge about current allocations, pending requests, and synchronization constraints, to generate a contention-free sequence of actions. In this paper we focus on modeling deadlocks which are manifestations of spatial interactions.

Doshi, Rajkumar S.↗

Interpretable Tree-Based and Graph Neural Network Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Materials discovery↗

Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

97 MATHEMATICS AND COMPUTING↗

Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibility

Mechanistic understanding of large molecule conversion and the discovery of suitable heterogeneous catalysts have been lagging due to the combinatorial inventory of intermediates and the inability of humans to enumerate all structures. Here, we introduce an automated framework to predict stable configurations on transition metal surfaces and demonstrate its validity for adsorbates with up to 6 carbon and oxygen atoms on 11 metals, enabling the exploration of ~10 8 potential configurations. It combines a graph enumeration platform, force field, multi-fidelity DFT calculations, and first-principles trained machine learning. Clusters in the data reveal groups of catalysts stabilizing different structures and expose selective catalysts for showcase transformations, such as the ethylene epoxidation on Ag and Cu and the lack of C-C scission chemistry on Au. Deviations from the commonly assumed atom valency rule of small adsorbates are also manifested. This library can be leveraged to identify catalysts for converting large molecules computationally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The hard start phenomena in hypergolic engines. Volume 2: Combustion characteristics of propellants and propellant combinations

The combustion characteristics of hypergolic propellants are described. A research project was conducted to determine if the reaction control system engine propellants on Apollo spacecraft undergo explosive reaction when subjected to conditions present in the engine at the time of ignition. Combustion characteristics pertinent to the hard-start phenomenon are considered. The thermal stability of frozen mixtures of hydrazine-based fuels with nitrogen tetroxide was analyzed. Results of the tests are presented in the form of tables and graphs.

Miron, Y.↗

Timing behavior of 96 radio pulsars

We present results from observations of 104 pulsars made between 1989 August and 1993 April, including timing solutions for 96 of them. Pulse profiles were recorded at four frequencies in the range 0.4-1.64 GHz, yielding topocentric pulse arrival times with uncertainties of order 10(exp -3) periods. Models fitted to the timing data yield accurate positions, periods, period derivatives, and dispersion measures for each pulsar. Nine of the measured period derivatives are new, and most of the parameters represent improvements upon previous measurements. In a few cases we correct some erroneous parameter values from the published literature. A glitch was observed in the PSR B1800-21 pulse arrival times, and we fit a simple exponential model to the post-glitch recovery. We present graphs of the observed pulse shapes and their evolution with frequency, a table of measured pulase widths, and quantitative estimates of the long-term timing stability of each pulsar.

Arzoumanian, Z.↗

Device Performance of Emerging Photovoltaic Materials (Version 3)

Abstract Following the 2nd release of the “Emerging PV reports,” the best achievements in the performance of emerging photovoltaic devices in diverse emerging photovoltaic research subjects are summarized, as reported in peer‐reviewed articles in academic journals since August 2021. Updated graphs, tables, and analyses are provided with several performance parameters, e.g., power conversion efficiency, open‐circuit voltage, short‐circuit current density, fill factor, light utilization efficiency, and stability test energy yield. These parameters are presented as a function of the photovoltaic bandgap energy and the average visible transmittance for each technology and application, and are put into perspective using, e.g., the detailed balance efficiency limit. The 3rd installment of the “Emerging PV reports” extends the scope toward triple junction solar cells.

14 SOLAR ENERGY↗

The importance of aerodynamics on dynamics

The effects of aerodynamic phenomena on helicopter structural dynamics are examined, reviewing the results of recent theoretical and experimental investigations. A schematic diagram of a dynamic analysis is presented and discussed, noting the numerous aerodynamic inputs, and numerical data are presented in graphs. Consideration is given to forcing functions, aerodynamic damping, aeroelastic coupling, negative damping, apparent coriolis coupling, periodic coefficients, inverse damping, additional degrees of freedom, flap-lag stability, and dynamic inflow. The need for theoretical models which account for the dynamic loop between blade lift and induced flow (permitting blade motion to dynamically alter the flowfield during transients) is indicated.

Peters, David A.↗

The Pack Method for Compressive Tests of Thin Specimens of Materials Used in Thin-Wall Structures

The strength of modern lightweight thin-wall structures is generally limited by the strength of the compression members. An adequate design of these members requires a knowledge of the compressive stress-strain graph of the thin-wall material. The "pack" method was developed at the National Bureau of Standards with the support of the National Advisory Committee for Aeronautics to make possible a determination of compressive stress-strain graphs for such material. In the pack test an odd number of specimens are assembled into a relatively stable pack, like a "pack of cards." Additional lateral stability is obtained from lateral supports between the external sheet faces of the pack and outside reactions. The tests seems adequate for many problems in structural research.

Aitchison, C S↗