Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dynamic mechanical analysis”

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 181 records · Page 10

Normal stability of slow manifolds in nearly periodic Hamiltonian systems

Kruskal [J. Math. Phys. 3, 806 (1962)] showed that each nearly periodic dynamical system admits a formal U(1) symmetry, generated by the so-called roto-rate. We prove that such systems also admit nearly invariant manifolds of each order, near which rapid oscillations are suppressed. We study the nonlinear normal stability of these slow manifolds for nearly periodic Hamiltonian systems on barely symplectic manifolds—manifolds equipped with closed, non-degenerate 2-forms that may be degenerate to leading order. In particular, we establish a sufficient condition for long-term normal stability based on second derivatives of the well-known adiabatic invariant. We use these results to investigate the problem of embedding guiding center dynamics of a magnetized charged particle as a slow manifold in a nearly periodic system. Here, we prove that one previous embedding and two new embeddings enjoy long-term normal stability and thereby strengthen the theoretical justification for these models.

97 MATHEMATICS AND COMPUTING↗

Studying Interfacial Dark Reactions of Glyoxal and Hydrogen Peroxide Using Vacuum Ultraviolet Single Photon Ionization Mass Spectrometry

Aqueous secondary organic aerosol (aqSOA) formation from volatile and semivolatile organic compounds at the air–liquid interface is considered as an important source of fine particles in the atmosphere. However, due to the lack of in situ detecting techniques, the detailed interfacial reaction mechanism and dynamics still remain uncertain. In this study, synchrotron-based vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) was coupled with the System for Analysis at the Liquid Vacuum Interface (SALVI) to investigate glyoxal dark oxidation products at the aqueous surface. Mass spectral analysis and determination of appearance energies (AEs) suggest that the main products of glyoxal dark interfacial aging are carboxylic acid related oligomers. Furthermore, the VUV SPI-MS results were compared and validated against those of in situ liquid time-of-flight secondary ion mass spectrometry (ToF-SIMS). The reaction mechanisms of the dark glyoxal interfacial oxidation, obtained using two different approaches, indicate that differences in ionization and instrument operation principles could contribute to their abilities to detect different oligomers. Therefore, the mechanistic differences revealed between the VUV SPI-MS and ToF-SIMS indicate that more in situ and real-time techniques are needed to investigate the contribution of the air–liquid interfacial reactions leading to aqSOA formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanisms of Waterflood Inefficiency: Analysis of Geological, Petrophysical and Reservoir History, a Field Case Study of FWU (East Section)

The petroleum reservoir represents a complex heterogeneous system that requires thorough characterization prior to the implementation of any incremental recovery technique. One of the most commonly utilized and successful secondary recovery techniques is waterflooding. However, a lack of sufficient investigation into the inherent behavior and characteristics of the reservoir formation in situ can result in failure or suboptimal performance of waterflood operations. Therefore, a comprehensive understanding of the geological history, static and dynamic reservoir characteristics, and petrophysical data is essential for analyzing the mechanisms and causes of waterflood inefficiency and failure. In this study, waterflood inefficiency was observed in the Morrow B reservoir located in the Farnsworth Unit, situated in the northwestern shelf of the Anadarko Basin, Texas. To assess the potential mechanisms behind the inefficiency of waterflooding in the east half, geological, petrophysical, and reservoir engineering data, along with historical information, were integrated, reviewed, and analyzed. The integration and analysis of these datasets revealed that several factors contributed to the waterflood inefficiency. Firstly, the presence of abundant dispersed authigenic clays within the reservoir, worsened by low reservoir quality and high heterogeneity, led to unfavorable conditions for waterflood operations. The use of freshwater for flooding exacerbated the adverse effects of sensitive and migratory clays, further hampering the effectiveness of the waterflood. In addition to these factors, several reservoir engineering issues played a significant role in the inefficiency of waterflooding. These issues included inadequate perforation strategies due to the absence of detailed hydraulic flow units (HFUs) and rock typing, random placement of injectors, and uncontrolled injected fresh water. These external controlling parameters further contributed to the overall inefficiencies observed during waterflood operations in the east half of the reservoir. A detailed understanding of the mechanistic factors of inefficient waterflood operation will provide adequate insights into the development of the improved recovery technique for the field.

Morgan, Anthony (ORCID:0000000211519153)↗

A thermodynamic analysis of hypervelocity impacts on metals

Hypervelocity impacts on solid surfaces generate and propagate shock waves and create extreme density, pressure, and temperature conditions. Understanding hypervelocity impacts requires a multi-physics approach at the intersection of fluid dynamics, solid mechanics, and quantum theory, which has the capability of spanning multiple different dominating physics regimes. These strong shock conditions found in hypervelocity impacts are studied in the context of high-speed collisions between spacecraft and meteoroids and debris. We study the problem of hypervelocity impacts on metals with the lens of understanding the processes that lead to the creation of an impact generated plasma. In order to characterize the impacting particle as well as its threat to spacecraft from the subsequent radiating plasma an analysis was performed that highlights how the kinetic energy of the impactor is deposited into a target, how the shock wave and shocked material in the target evolve, and how these effects can lead towards the creation of an impact plasma through heating. The analysis suggests that at low velocities the majority of the energy from a hypervelocity impact is stored in reversible elastic energy and does not contribute to strong heating. At higher impact velocities, nucleus and electron thermal components dominate, increasing the energy available for ionization. Overall, this work provides the complete set of state variable initial conditions for any study of hypervelocity impact plasma expansion and its effects.

42 ENGINEERING↗

Photoinduced anisotropic lattice dynamic response and domain formation in thermoelectric SnSe

Identifying and understanding the mechanisms behind strong phonon–phonon scattering in condensed matter systems is critical to maximizing the efficiency of thermoelectric devices. To date, the leading method to address this has been to meticulously survey the full phonon dispersion of the material in order to isolate modes with anomalously large linewidth and temperature-dependence. Here we combine quantitative MeV ultrafast electron diffraction (UED) analysis with Monte Carlo based dynamic diffraction simulation and first-principles calculations to directly unveil the soft, anharmonic lattice distortions of model thermoelectric material SnSe. A small single-crystal sample is photoexcited with ultrafast optical pulses and the soft, anharmonic lattice distortions are isolated using MeV-UED as those associated with long relaxation time and large displacements. We reveal that these modes have interlayer shear strain character, induced mainly by c -axis atomic displacements, resulting in domain formation in the transient state. These findings provide an innovative approach to identify mechanisms for ultralow and anisotropic thermal conductivity and a promising route to optimizing thermoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Isothermal solidification for high-entropy alloy synthesis

Kinetically trapping the high-temperature states through rapid cooling solidification is widely used for the synthesis of high-entropy alloys (HEAs), especially those with intrinsically immiscible elemental combinations. However, strategies need to be developed to overcome the fundamental limitations of rapid cooling solidification in controlling the crystallinity, structure and morphology of HEAs. Here, in this study, we introduce an isothermal solidification strategy for the synthesis of HEAs by rapidly altering the metal alloy composition through liquid–liquid interface reactions at low temperatures, for example, from 25 °C to 80 °C. We use gallium (Ga)-based metal as the sacrificial reagent and mixing medium. By directing the reactions to the interfaces between the Ga-based liquid metal and an aqueous metal ion solution, the foreign metal ions can be reduced at the interfaces and incorporated into the liquid metal quickly. HEAs with various crystallinity (single crystal, mesocrystal, polycrystal and amorphous), morphology (zero, two and three dimensions) and compositions can be achieved through the isothermal solidification. Ga can be completely consumed, resulting in Ga-free HEAs. If desired, Ga can be one of the metal elements in the final products. In situ liquid phase transmission electron microscopy (TEM) studies and theoretical analysis show the isothermal solidification mechanisms. Our direct observations show the enhanced mixing of liquid metal elements and the solidification process with fluctuating nucleation dynamics. The isothermal solidification marks a powerful strategy for HEA synthesis through an unexplored pathway of kinetically trapping the high-entropy states.

Zhang, Qiubo [Lawrence Berkeley National Laborator↗

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↗

Habitat‐adapted microbial communities mediate Sphagnum peatmoss resilience to warming

Summary Sphagnum peatmosses are fundamental members of peatland ecosystems, where they contribute to the uptake and long‐term storage of atmospheric carbon. Warming threatens Sphagnum mosses and is known to alter the composition of their associated microbiome. Here, we use a microbiome transfer approach to test if microbiome thermal origin influences host plant thermotolerance. We leveraged an experimental whole‐ecosystem warming study to collect field‐grown Sphagnum , mechanically separate the associated microbiome and then transfer onto germ‐free laboratory Sphagnum for temperature experiments. Host and microbiome dynamics were assessed with growth analysis, Chl a fluorescence imaging, metagenomics, metatranscriptomics and 16S rDNA profiling. Microbiomes originating from warming field conditions imparted enhanced thermotolerance and growth recovery at elevated temperatures. Metagenome and metatranscriptome analyses revealed that warming altered microbial community structure in a manner that induced the plant heat shock response, especially the HSP70 family and jasmonic acid production. The heat shock response was induced even without warming treatment in the laboratory, suggesting that the warm‐microbiome isolated from the field provided the host plant with thermal preconditioning. Our results demonstrate that microbes, which respond rapidly to temperature alterations, can play key roles in host plant growth response to rapidly changing environments.

59 BASIC BIOLOGICAL SCIENCES↗

Development of the TREAT M2 experiment as a transient benchmark

A transient benchmark based on the Transient Reactor Test Facility (TREAT) M2 Calibration experiment (M2-CAL) is under development. TREAT, at Idaho National Laboratory, is a graphite moderated air-cooled research reactor which has been used extensively for fuel material testing under extreme and accident conditions. Accurate benchmark models are a beneficial component in the operations, experimental planning, and development of TREAT. In this work, we present a transient benchmark model for the M2-CAL experiment core loading. The benchmark model incorporates the coupling between the Monte Carlo Code SERPENT and the computational fluid dynamics code OpenFOAM to capture the temperature feedback mechanism. The M2-CAL transient 2580 was simulated in this work. A pre-transient analysis was performed to determine the optimum core composition and conditions before the beginning of the transient. The analysis was validated against historic TREAT kinetic measurements and the worth of the transient rod T-2. The axial power distribution in the flux wire for the M2-CAL experiment was determined and contrasted with the experiment. The model was then used to simulate the M2-CAL transient 2580 experiment based on the reported pre-transient and transient conditions. Several transient observables were calculated and compared to the experiment. The model shows good agreement with the experimental power traces, period, and average increase of power at the power ramp (time > 7.8 s). Inverse point kinetics analysis was performed during the period of the power ramp for the model and the experiment based on that, the temperature feedback component was isolated and contrasted with the experimental feedback. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.

60 APPLIED LIFE SCIENCES↗

Probing multiscale dissolution dynamics in natural rocks through microfluidics and compositional analysis

Mineral dissolution significantly impacts many geological systems. Carbon released by diagenesis, carbon sequestration, and acid injection are examples where geochemical reactions, fluid flow, and solute transport are strongly coupled. The complexity in these systems involves interplay between various mechanisms that operate at timescales ranging from microseconds to years. Current experimental techniques characterize dissolution processes using static images that are acquired with long measurement times and/or low spatial resolution. These limitations prevent direct observation of how dissolution reactions progress within an intact rock with spatially heterogeneous mineralogy and morphology. We utilize microfluidic cells embedded with thin rock samples to visualize dissolution with significant temporal resolution (100 ms) in a large observation window (3 × 3 mm). Here we injected acidic fluid into eight shale samples ranging from 8 to 86 wt % carbonate. The pre- and postreaction microstructures are characterized at the scale of pores (0.1 to 1 µm) and fractures (1 to 1,000 µm). We observe that nonreactive particle exposure, fracture morphology, and loss of rock strength are strongly dependent on both the relative volume of reactive grains and their distribution. Time-resolved images of the rock unveil the spatiotemporal dynamics of dissolution, including two-phase flow effects in real time and illustrate the changes in the fracture interface across the range of compositions. Moreover, the dynamical data provide an approach for characterizing reactivity parameters of natural heterogeneous samples when porous media effects are not negligible. The platform and workflow provide real-time characterization of geochemical reactions and inform various subsurface engineering processes.

58 GEOSCIENCES↗

The nonexistence of a paddlewheel effect in superionic conductors

Since the 1980s, the paddlewheel effect has been suggested as a mechanism to boost lithium-ion diffusion in inorganic materials via the rotation of rotor-like anion groups. However, it remains unclear whether the paddlewheel effect, defined as large-angle anion group rotations assisting Li hopping, indeed exists; furthermore, the physical mechanism by which the anion-group dynamics affect lithium-ion diffusion has not yet been established. In this work, we differentiate various types of rotational motions of anion groups and develop quaternion-based algorithms to detect, quantify, and relate them to lithium-ion motion in ab initio molecular dynamics simulations. Our analysis demonstrates that, in fact, the paddlewheel effect, where an anion group makes a large angle rotation to assist a lithium-ion hop, does not exist and thus is not responsible for the fast lithium-ion diffusion in superionic conductors, as historically claimed. Instead, we find that materials with topologically isolated anion groups can enhance lithium-ion diffusivity via a more classic nondynamic soft-cradle mechanism, where the anion groups tilt to provide optimal coordination to a lithium ion throughout the hopping process to lower the migration barrier. This anion-group disorder is static in nature, rather than dynamic and can explain most of the experimental observations. Our work substantiates the nonexistence of the long-debated paddlewheel effect and clarifies any correlation that may exist between anion-group rotations and fast ionic diffusion in inorganic materials.

36 MATERIALS SCIENCE↗

Nonlinear Interface Reduction for Time-Domain Analysis of Hurty/Craig-Bampton Superelements with Frictional Contact

Virtual prototyping in engineering design relies today on modern numerical models of contacting structures with accurate resolution of interface mechanics, which strongly affect the system-level stiffness and energy dissipation due to frictional losses. High-fidelity modeling within the localized interfaces is required to resolve local quantities of interest that may drive design decisions. The high-resolution finite element meshes necessary to resolve inter-component stresses tend to be computationally expensive, particularly when the analyst is interested in response time histories. The Hurty/Craig-Bampton (HCB) transformation is a widely used method in structural dynamics for reducing the interior portion of a finite element model while having the ability to retain all nonlinear contact degrees of freedom (DOF) in physical coordinates. These models may still require many DOF to adequately resolve the kinematics of the interface, leading to inadequate reduction and computational savings. This study proposes a novel interface reduction method to overcome these challenges by means of system-level characteristic constraint (SCC) modes and properly orthogonal interface modal derivatives (POIMDs) for transient dynamic analyses. Both SCC modes and POIMDs are computed using the reduced HCB mass and stiffness matrices, which can be directly computed from many commercial finite element analysis software. Comparison of time history responses to an impulse-type load in a mechanical beam assembly indicate that the interface-reduced model correlates well with the HCB truth model. Localized features like slip and contact area are well-represented in the time domain when the beam assembly is loaded with a broadband excitation. The proposed method also yields reduced-order models with greater critical timestep lengths for explicit integration schemes.

42 ENGINEERING↗

Prediction of the energetic particle redistribution by an improved critical gradient model and analysis of the transport threshold

Based on the theory of critical gradient model (CGM) and following the simulation method proposed by Waltz et al., a combination of TGLFEP and EPtran code is employed to predict the energetic particle (EP) transport induced by Alfvén eigenmodes (AEs). To be consistent with the experiment, recent improvements to the simulation method include consideration of threshold evolution and orbit loss due to finite orbit width. The revised CGM is applied to simulate two DIII-D experimental discharges (#142111 and #153071). It well reproduces the experimental profiles with multiple unstable AEs and large-scale EP transport. Discharge #142111 had previously been simulated using a nonlinear MHD-kinetic code MEGA with a transport mechanism based on stochasticity induced by overlapping AE. By comparing the simulated EP profiles, we find that the AE transport threshold is approximated by both the MEGA nonlinear stability threshold and the proposed CGM threshold (error <5% for single n and <17% for multiple n simulation). Both of them are larger than the linear stability threshold of the most unstable AE mode by a quantity of the order of the flux needed to sustain EP transport by the background turbulence. Additionally, we have also applied the improved CGM to simulate the α particle redistribution for a China Fusion Engineering Test Reactor steady state scenario. Because of the clear separation between the AE unstable region and the loss cone, only a moderate α particle loss of ~9.6% is predicted.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fast and flexible control of beam longitudinal phase space for high-repetition-rate x-ray free-electron lasers

The wide-ranging requirements for the photon properties from multiple beamlines in superconducting based free-electron lasers (FELs) demand more challenging beam manipulation techniques. Shot-by-shot control of electron beam bunch length and peak current at high repetition rate up to megahertz is highly desired. In this paper, we present a comprehensive study of a method based on a 2-m-long normal conducting radio-frequency cavity to achieve fast and flexible control of beam compression and realize the full potential of the facility, including theoretical analysis, beam dynamics simulations, and conceptual cavity design for the Linac Coherent Light Source II and its high-energy upgrade. We illustrate the physical mechanism of the chirping cavity on the control of the final beam compression and propose methods to lower the requirements for the cavity parameters. The application of this method will allow tailored photon properties of individual beamlines to optimize their performance and drastically improve the multiplexing capabilities of a high-repetition rate FEL facility.

42 ENGINEERING↗

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

54 ENVIRONMENTAL SCIENCES↗

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

58 GEOSCIENCES↗