Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dynamic timing 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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗
DOE OSTI2024

Unraveling the multi-step crystallization mechanism of polytetrafluoroethylene, modified polytetrafluoroethylene, and their nanocomposites with boron nitride nanobarbs: Experimental insights and theoretical analysis

The non-isothermal crystallization behavior and kinetics of polytetrafluoroethylene (PTFE) composites with boron nitride nanobarb (BNNB), a new generation nanostructure with unique surface morphology and mechanical “barbs” have been analyzed, understanding these properties is essential for their high-end applications as thermal interface materials (TIM) for microwave, 5G and microelectronic devices. The analysis of the crystallization parameters includes crystallization onset, peak and end temperatures, crystallization half-life and overall crystallinity of PTFE, modified PTFE and their BNNB composites. The results were further analyzed using theoretical models such as the combined Avrami-Ozawa model. It was found that BNNB supports crystallization in the modified PTFE but shows minimal effect on the crystallization of PTFE. Due to the limitation of the classical theoretical models used above in fully characterizing the multi-step crystallization process of PTFE, an in-depth analysis using the model-free advanced isoconversional computation was used to characterize the PTFE crystallization based on the evolution of activation energy with fractional crystallinity and for the first time with temperature. Three kinetic regions were identified in the crystallization mechanism. Here, this study investigated the molecular organization and microstructural evolution of PTFE, modified PTFE and their composites during non-isothermal crystallization using advanced X-ray scattering measurements. An insight into the changes undergone by the material's microstructural units including crystallite size and morphology, lamellar thickness and lamellar interfacial layer thickness, and crystallographic phase dynamics during non-isothermal cooling from the melt, was provided here in this work. The effect of copolymer modification of PTFE and the inclusion of pristine and functionalized BNNB (a thermally conductive and electrically insulating ceramic) are both new investigations that provide valuable knowledge for the development of materials with strong matrix-nanofiller interaction and guidance for optimizing sintering and cooling cycles, two key steps in PTFE processing that largely affect the material microstructural features. Overall, the result of the three-part investigation demonstrates that BNNB supports crystallization in the modified PTFE up to 20 wt% concentration and at low and high cooling rates typically used in the industrial processing of PTFE.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multi-Particle Three-Dimensional Covariance Imaging: “Coincidence” Insights into the Many-Body Fragmentation of Strong-Field Ionized D 2 O

We demonstrate the applicability of covariance analysis to three-dimensional velocity-map imaging experiments using a fast timestamping detector. Studying the photofragmentation of strong-field doubly ionized D$_2$O molecules, we show that combining high count rate measurements with covariance analysis yields the same level of information typically limited to the `gold standard' of true, low count rate coincidence experiments, when averaging over a large ensemble of photofragmentation events. This increases the effective data acquisition rate by approximately two orders of magnitude, enabling a new class of experimental studies. This is illustrated through an investigation into the dependence of three-body D$_2$O$^{2+}$ dissociation on the intensity of the ionizing laser, revealing mechanistic insights into the nuclear dynamics driven during the laser pulse. Here, the experimental methodology laid out, with its drastic reduction in acquisition time, is expected to be of great benefit to future photofragment imaging studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanoscale Miscibility in In Situ Polymerized Hybrid Electrolytes Speeds Up Ion Dynamics and Enables Stable Cycling of Li Metal Batteries

While the potential use of copolymerized electrolytes in Li metal batteries is subject to intense investigation, the fundamental understanding of the nanoscale domain formation and its effect on Li + transport is still lacking. In this study, we investigated the correlation between the Li + transport mechanism and the miscibility of monomers in polymer blend electrolytes derived from the in situ copolymerization of methyl methacrylate (MMA) and vinylene carbonate (VC) in the presence of polyethylene glycol dimethyl ether (PEGDME) plasticizer and bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. The addition of a polar short chain plasticizer reduced the dynamic and structural heterogeneities of the electrolyte. Small-angle X-ray scattering (SAXS) measurements and coarse-grained molecular dynamics (MD) simulations were used to investigate the nanoscale structure of the electrolytes. The distribution of relaxation times corresponding to the three distinct diffusion mechanisms of the free and interfacial Li + ions at the copolymer/plasticizer and electrolyte/SEI boundaries was analyzed in a broad temperature range to elucidate the Li + transport mechanism. Furthermore, the chemical composition of the SEI and the contribution of a ceramic lithium lanthanum zirconium oxide (LLZO, Li 7 La 3 Zr 2 O 12 ) phase on the interfacial resistance, salt degradation, and SEI stability were studied by X-ray photoelectron spectroscopy (XPS) depth profile analysis and electrochemical testing.

Li metal↗
DOE OSTI2022

Projected U.S. drought extremes through the twenty-first century with vapor pressure deficit

Global warming is expected to enhance drought extremes in the United States throughout the twenty-first century. Projecting these changes can be complex in regions with large variability in atmospheric and soil moisture on small spatial scales. Vapor Pressure Deficit (VPD) is a valuable measure of evaporative demand as moisture moves from the surface into the atmosphere and a dynamic measure of drought. Here, VPD is used to identify short-term drought with the Standardized VPD Drought Index (SVDI); and used to characterize future extreme droughts using grid dependent stationary and non-stationary generalized extreme value (GEV) models, and a random sampling technique is developed to quantify multimodel uncertainties. The GEV analysis was performed with projections using the Weather Research and Forecasting model, downscaled from three Global Climate Models based on the Representative Concentration Pathway 8.5 for present, mid-century and late-century. Results show the VPD based index (SVDI) accurately identifies the timing and magnitude short-term droughts, and extreme VPD is increasing across the United States and by the end of the twenty-first century. The number of days VPD is above 9 kPa increases by 10 days along California’s coastline, 30–40 days in the northwest and Midwest, and 100 days in California’s Central Valley.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
DOE OSTI2023

Lagrangian statistics of a shock-driven turbulent dynamo in decaying turbulence

Small-scale fluctuating magnetic fields of order nG are observed in supernova shocks and galaxy clusters, where its amplification is likely caused by the Biermann battery mechanism. However, these fields cannot be amplified further without the turbulent dynamo, which generates magnetic energy through the stretch-twist-fold (STF) mechanism. Thus, we present here novel 3D magnetohydrodynamic (MHD) simulations of a laser-driven shock propagating into a stratified, multiphase medium, to investigate the post-shock turbulent magnetic field amplification via the turbulent dynamo. The configuration used here is currently being tested in the shock tunnel at the National Ignition Facility (NIF). In order to probe the statistical properties of the post-shock turbulent region, we use 384 × 512 × 384 tracers to track its evolution through the Lagrangian framework, thus providing a high-fidelity analysis of the shocked medium. Our simulations indicate that the growth of the magnetic field, which accompanies the near-Saffman kinetic energy decay (E kin ∝ t -1.15 ) without turbulence driving, exhibits slightly different characteristics as compared to periodic box simulations. Seemingly no distinct phases exist in its evolution because the shock passage and time to observe the magnetic field amplification during the turbulence decay are very short (~0.3 of a turbulent turnover time). Yet, the growth rate is still consistent with those expected for compressive (curl-free) turbulence driving in subsonic, compressible turbulence. Phenomenological understanding of the dynamics of the magnetic and velocity fields are also elucidated via Lagrangian frequency spectra, which are consistent with the expected inertial range scalings in the Eulerian–Lagrangian bridge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Implementation of a feature selection algorithm in FARM to identify important state variables and time-invariant matrices

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM aids the HERON software module in the evaluation of the optimal dispatch for the different IES components. Set-point trajectories are required to meet limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To evaluate the feasibility of HERON generated set-points and to do so in an acceptable time, FARM employs reduced order models to represent the dynamic behavior of the systems to be dispatched. These surrogate models take the form of a linear dynamic system with sets of Linear Parameter Varying (LPV) matrices that are mapped to the system operating space. These matrices are derived from the trajectories of system state variables and system output variables during transients. The accuracy of LPV matrices depends on the selection of state variables. In previous reports, state variables were selected by adopting a complicated workflow requiring multiple software licenses and an advanced level of user expertise. In this report, a new workflow that automates the state variable selection process is presented. It significantly reduces the frequency of user interventions and does not require multiple software licenses. Each module in the new workflow is described in detail, and the input / output examples in each step of the workflow are provided. It was demonstrated that this workflow can greatly reduce the complexity of the state variable selection process, and that the updated FARM-Gamma and FARM-Delta validators can benefit from this workflow when solving the power dispatch problem of a representative IES test case. Finally, some code improvements that can further enhance the efficiency are suggested.

42 ENGINEERING↗
DOE OSTI2024

Real-space atomic dynamics in metallic liquids investigated by inelastic neutron scattering

Understanding the dynamics of liquids at the atomic level remains a major challenge. Even though viscosity is one of the most fundamental properties of liquids, its atomistic origin is not fully elucidated. Through inelastic neutron scattering experiment on levitated metallic liquid droplets, the time-dependent pair correlation function, the Van Hove function, was determined for Z⁢r 50 ⁢C⁢u 50 and Z⁢r 80 ⁢P⁢t 20 liquids at various temperatures. The time for change in local atomic connectivity, τ LC , which is the timescale of atomic bond cutting and forming, is estimated based on the exponential decay of the nearest neighbor peak of the Van Hove function. At high temperatures above the crossover temperature T A , τ LC is equal to the Maxwell relaxation time, τ M =η/G ∞ , where η is the macroscopic shear viscosity and G ∞ is the high-frequency shear modulus. Below T A the ratio of τ M /τ LC increases with decreasing temperature, indicating increased atomic cooperativity as predicted by molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

In Situ Analysis of Laser Powder Bed Fusion Using Simultaneous High-Speed Infrared and X-ray Imaging

Laser powder bed fusion is a metal additive manufacturing technique that has received significant scientific and industrial attention over the past decades. However, the quality and reproducibility of parts manufactured by this technique is still a problem. Overcoming this issue requires an understanding of multiple complex physical phenomena which occur simultaneously during the process. Here, we illustrate a powerful new technique which synchronizes high-speed x-ray imaging with high-speed infrared imaging to study laser powder bed fusion processes in real time. Using this technique, we demonstrate the simultaneous observation of multiple phenomena including three-dimensional melt pool visualization, vapor plume dynamics, spatter formation, thermal history, and point cooling rates. The paired observation of these dynamic phenomena is critical to understanding the fundamentals of laser powder bed fusion, and the overall impact of process parameters on print quality.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Achieving Multimodal and Multicolor Luminescence in LaAlO 3 :Pr 3+ , Gd 3+ via Trap Engineering and Energy Transfer

Achieving multimodal luminescence within a single phosphor is vital for multifunctional applications but remains challenging due to complex color tuning and trap engineering. In this study, we report Pr 3+ and Gd 3+ co‐doped LaAlO 3 (LAO:PG) phosphors, designed through careful modulation of multilevel traps and Pr 3+ → Gd 3+ energy transfer dynamics. These materials exhibit diverse luminescence modes, including down‐conversion luminescence (DCL), up‐conversion luminescence (UCL), persistent luminescence (PersL), optically stimulated luminescence (OSL), and thermally stimulated luminescence (TSL) across a wide spectral range. Unlike previously studied Pr 3+ ‐doped LAO, the co‐doped LAO:PG shows DCL in both UV‐visible and NIR regions and displays ultraviolet‐C UCL under visible excitation. Notably, we observe, for the first time, PersL lasting several minutes in these phosphors—an improvement over the non‐PersL behavior of Pr 3+ ‐only doped LAO. Additionally, the LAO:PG phosphors exhibit strong OSL response. TSL analysis reveals five distinct trap levels linked to these properties. Density functional theory calculations further correlate intrinsic defects to these traps, supporting a proposed mechanism for the observed multimodal luminescence. These findings highlight LAO:PG as a promising platform for developing advanced phosphors with integrated luminescence modes, paving the way for future applications in data storage, phototherapy, and anti‐counterfeiting technologies.

Chemistry↗
DOE OSTI2021

Possibility of an integrated transmission electron microscope: enabling complex in-situ experiments

Abstract Multimodal in-situ experiments are the wave of the future, as this approach will permit multispectral data collection and analysis during real-time nanoscale observation. In contrast, the evolution of technique development in the electron microscopy field has generally trended toward specialization and subsequent bifurcation into more and more niche instruments, creating a challenge for reintegration and backward compatibility for in-situ experiments on state-of-the-art microscopes. We do not believe this to be a requirement in the field; therefore, we propose an adaptive instrument that is designed to allow nearly simultaneous collection of data from aberration-corrected transmission electron microscopy (TEM), probe-corrected scanning transmission electron microscopy, ultrafast TEM, and dynamic TEM with a flexible in-situ testing chamber, where the entire instrument can be modified as future technologies are developed. The value would be to obtain a holistic understanding of the underlying physics and chemistry of the process-structure–property relationships in materials exposed to controlled extreme environments. Such a tool would permit the ability to explore, in-situ, the active reaction mechanisms in a controlled manner emulating those of real-world applications with nanometer and nanosecond resolution. If such a powerful tool is developed, it has the potential to revolutionize our materials understanding of nanoscale mechanisms and transients. Graphical Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2020

On the proper derivation of the Floquet-based quantum classical Liouville equation and surface hopping describing a molecule or material subject to an external field

We investigate different approaches to derive the proper Floquet-based quantum–classical Liouville equation (F-QCLE) for laser-driven electron-nuclear dynamics. The first approach projects the operator form of the standard QCLE onto the diabatic Floquet basis and then transforms to the adiabatic representation. The second approach directly projects the QCLE onto the Floquet adiabatic basis. Both approaches yield a form that is similar to the usual QCLE with two modifications: (1) The electronic degrees of freedom are expanded to infinite dimension and (2) the nuclear motion follows Floquet quasi-energy surfaces. However, the second approach includes an additional cross derivative force due to the dual dependence on time and nuclear motion of the Floquet adiabatic states. Our analysis and numerical tests indicate that this cross derivative force is a fictitious artifact, suggesting that one cannot safely exchange the order of Floquet state projection with adiabatic transformation. Our results are in accord with similar findings by Izmaylov et al., [J. Chem. Phys. 140, 084104 (2014)] who found that transforming to the adiabatic representation must always be the last operation applied, although now we have extended this result to a time-dependent Hamiltonian. Finally, this paper and the proper derivation of the F-QCLE should lay the basis for further improvements of Floquet surface hopping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Study of Stark broadening of krypton helium-$\beta$ lines and estimation of electron density and temperature in NIF compressed capsules

Here the National Ignition Facility (NIF) diagnostic instrument manipulator (DIM) - based high resolution (dHIRES) x-ray spectrometer was used to measure the time evolution of the electron density (n e ) and temperature (T e ) in the hot spot of four NIF compressed capsules with 25 ps time resolution during the 'stagnation' phase. The electron density was inferred by comparing the measured Stark broadening of the krypton (Kr) Heβ spectral complex with theoretical calculations that include ion dynamic effects, and the electron temperature was inferred by comparing the measured ratio of the intensity of a dielectronically excited Li-like Kr line to the intensity of the Kr Heβ resonance line with calculations using the spectroscopic collisional radiative atomic model (SCRAM) and CRETIN collisional-radiative models. The inferred, time averaged n e values mainly agree with n e values from neutron diagnostics within uncertainties, but the neutron time-of-flight values of T ion are consistently higher than dHIRES T e values by 200–700 eV. The dHIRES measurements and measurement techniques, method of uncertainty analysis, and discussion of comparisons with measurements from neutron diagnostics are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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↗