Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Fast Timing”

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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sorption heat pump and control method

A method operates an absorption heat pump system, specifically the flow of hydronic cooling fluid through the condenser during system start-ups, or when the cooling fluid temperature is low. To minimize the time for an absorption heat pump to reach full cooling or heating capacity, it is desirable for the high side pressure to increase as fast as possible, and the low side pressure to decrease as fast as possible. Since the high side pressure is a function of the temperature of the refrigerant exiting the condenser, if the condenser cooling fluid temperature is low, the corresponding high side pressure will be low, which may not permit adequate working fluid flow rates from the high pressure side of the system to the low pressure side.

Garrabrant, Michael A.↗
DOE OSTI2023

Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)

Abstract. Some programming languages are easy to develop at the cost of slow execution, while others are fast at runtime but much more difficult to write. Julia is a programming language that aims to be the best of both worlds – a development and production language at the same time. To test Julia's utility in scientific high-performance computing (HPC), we built an unstructured-mesh shallow water model in Julia and compared it against an established Fortran-MPI ocean model, the Model for Prediction Across Scales–Ocean (MPAS-Ocean), as well as a Python shallow water code. Three versions of the Julia shallow water code were created: for single-core CPU, graphics processing unit (GPU), and Message Passing Interface (MPI) CPU clusters. Comparing identical simulations revealed that our first version of the Julia model was 13 times faster than Python using NumPy, where both used an unthreaded single-core CPU. Further Julia optimizations, including static typing and removing implicit memory allocations, provided an additional 10–20× speed-up of the single-core CPU Julia model. The GPU-accelerated Julia code was almost identical in terms of performance to the MPI parallelized code on 64 processes, an unexpected result for such different architectures. Parallelized Julia-MPI performance was identical to Fortran-MPI MPAS-Ocean for low processor counts and ranges from 2× faster to 2× slower for higher processor counts. Our experience is that Julia development is fast and convenient for prototyping but that Julia requires further investment and expertise to be competitive with compiled codes. We provide advice on Julia code optimization for HPC systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Enhancing CMC Temperature Performance in High Hydrogen Environments using Field Assisted Sintering Technology

This final report summarizes the developments in field assisted sintering technology (FAST) for rapid fabrication of ceramic matrix composite (CMC) materials with integrated environmental barrier coatings (EBCs), as well as their performance in a representative gas turbine combustor environment including stagnant flame zones, and high velocity product zones. CMCs are a possible high temperature tolerant material system for gas turbine engines, which are currently the dominant source of electric power production and the primary source of aircraft propulsion. However, CMCs are costly and time-consuming (on the order of weeks to months) to fabricate, and CMCs based on silicon carbide (SiC) ceramics are susceptible to water vapor degradation requiring the use of specialized EBCs. The manufacturing technique known as FAST can create consolidated parts in as little as a few hours using high pressure and temperature, and may be useful to integrate EBCs into CMCs directly during consolidation.

08 HYDROGEN↗
DOE OSTI2022

Electromagnetic Fireworks: Fast Radio Bursts from Rapid Reconnection in the Compressed Magnetar Wind

One scenario for the generation of fast radio bursts (FRBs) is magnetic reconnection in a current sheet of the magnetar wind. Compressed by a strong magnetic pulse induced by a magnetar flare, the current sheet fragments into a self-similar chain of magnetic islands. Time-dependent plasma currents at their interfaces produce coherent radiation during their hierarchical coalescence. We investigate this scenario using 2D radiative relativistic particle-in-cell simulations to compute the efficiency of the coherent emission and to obtain frequency scalings. Consistent with expectations, a fraction of the reconnected magnetic field energy, f ~ 0.002, is converted to packets of high-frequency fast magnetosonic waves, which can escape from the magnetar wind as radio emission. In agreement with analytical estimates, we find that magnetic pulses of 10 47 erg s –1 can trigger relatively narrowband GHz emission with luminosities of approximately 10 42 erg s –1 , sufficient to explain bright extragalactic FRBs. The mechanism provides a natural explanation for a downward frequency drift of burst signals, as well as the ~100 ns substructure recently detected in FRB 20200120E.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Real-Time Bayesian Inference at Extreme Scale: A Digital Twin for Tsunami Early Warning Applied to the Cascadia Subduction Zone

We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic–gravity wave equations, to infer earthquake-induced spatiotemporal seafloor motion in real time and forecast tsunami propagation toward coastlines for early warning with quantified uncertainties. Our target is the Cascadia subduction zone, with one billion parameters. Computing the posterior mean alone would require 50 years on a 512 GPU machine. Instead, exploiting the shift invariance of the parameter-to-observable map and devising novel parallel algorithms, we induce a fast offline–online decomposition. The offline component requires just one adjoint wave propagation per sensor; using MFEM, we scale this part of the computation to the full El Capitan system (43,520 GPUs) with 92% weak parallel efficiency. Moreover, given real-time data, the online component exactly solves the Bayesian inverse and forecasting problems in 0.2 seconds on a modest GPU system, a ten-billion-fold speedup.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. Furthermore, the computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2021

Phase-space sensitivity (weight functions) of 3 MeV proton diagnostics

Abstract The weight function W ( X ) is a diagnostic sensitivity to phase-space variables X that relates the measured signal C to the distribution function F ( X ) through the equation C = ∫ W ( X ) F ( X ) d X . In the present work, an algorithm to calculate W for a diagnostic that measures 3 MeV protons produced in d(d,p)t fusion reactions between a fast ion and a thermal deuteron is developed. The emitted protons escape the tokamak on curved orbits and are detected. These curved orbits constitute effective diagnostic ‘sightlines’. The presented algorithm accounts for the complications associated with these curved sightlines. An initial calculation of time-reversed proton orbits computes effective solid angles and sightlines for the relevant range of incident proton velocity vectors. These precomputed orbits are then used within the framework of FIDASIM (2020 Plasma Phys. Cont. Fusion 62 105008) to calculate the reactivity averaged over the thermal distribution of the ‘target’ deuterons and the probability that a fast ion of specified energy and pitch has a gyroangle that is consistent with the kinematic equations along each of the sightlines. Comparisons with analytic formulas and with independent calculations for the Mega Amp Spherical Tokamak 3 MeV proton diagnostic verify the algorithm.

Physics↗
DOE OSTI2022

Use of diamond sensors for a high-flux, high-rate X-ray pass-through diagnostic

X-ray free-electron lasers (XFELs) deliver pulses of coherent X-rays on the femtosecond time scale, with potentially high repetition rates. While XFELs provide high peak intensities, both the intensity and the centroid of the beam fluctuate strongly on a pulse-to-pulse basis, motivating high-rate beam diagnostics that operate over a large dynamic range. The fast drift velocity, low X-ray absorption and high radiation tolerance properties of chemical vapour deposition diamonds make these crystals a promising candidate material for developing a fast (multi-GHz) pass-through diagnostic for the next generation of XFELs. A new approach to the design of a diamond sensor signal path is presented, along with associated characterization studies performed in the XPP endstation of the LINAC Coherent Light Source (LCLS) at SLAC. Qualitative charge collection profiles (collected charge versus time) are presented and compared with those from a commercially available detector. Quantitative results on the charge collection efficiency and signal collection times are presented over a range of approximately four orders of magnitude in the generated electron–hole plasma density.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Pore architecture controls on mineral reactivity

Mineral dissolution rates measured in natural environments are much slower than those measured in laboratory settings. This project tested the hypothesis that the way fluid flows through rocks in natural systems creates areas where mineral dissolution is fast and areas where mineral dissolution is slow. This hypothesis was tested with a combination of laboratory experiments and numerical simulation. We demonstrated a separation of fluid flow pathways and rates of mineral dissolution in laboratory experiments for the first time using an experimental approach where we created synthetic rocks that have different ratios of connected and dead-end pathways for fluid flow. In laboratory experiments with higher proportions of dead-end pathways, the mineral dissolution rates were slower. We found that where fluid flows through connected pathways the continuous refreshing of fluid at the mineral surface creates conditions where dissolution is fast. In contrast, where fluid either flows slowly through poorly connected pathways or is stagnant in dead-end pathways, mineral dissolution is slow. The results from this project suggest that the overall slowing of rates of mineral dissolution is important when the proportion of dead-end pathways is greater than ~40%. This project informs our understanding of the way that fluids react with rocks in carbon dioxide sequestration and enhanced geothermal projects where fluids are purposefully injected into rocks for energy applications.

58 GEOSCIENCES↗
DOE OSTI2026

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗
DOE OSTI2025

Electrically Conductive Amine Functionalized Reduced Graphite Oxide Foam for CO 2 Removal from the Air

Rapid regeneration of CO 2 adsorbents is critical to improving the productivity of direct air capture (DAC) systems. In this study, we codesigned a material to have appropriate electrical conductivity and CO 2 adsorption properties to enable efficient CO 2 capture from air. Specifically, we present a poly(ethylenimine) (PEI)-impregnated thermally annealed graphite oxide (TAGO900) foam adsorbent tailored for vacuum-assisted electrically driven thermal swing adsorption (V-ETSA). This structured adsorbent leverages the high electrical conductivity of the reduced graphite oxide framework to enable fast and direct heating of the adsorbent material by electrical resistance heating (Joule heating). An optimal sample, 40 wt % PEI (molecular weight 25k) impregnated TAGO900, shows the best balance between adsorption capacity (1.54 mmol g –1 ) and adsorption rates (0.016 mmol g –1 min –1 ) using fixed bed breakthrough experiments at 25 °C and 70% RH using 50 sccm 400 ppm of CO 2 /N 2 flow. Compared to conventional temperature vacuum swing adsorption (TVSA), the V-ETSA approach achieves substantially faster CO 2 desorption, achieving average desorption rates (including cooling time) of 0.09 mmol g –1 min –1 ─approximately 2.5 times faster than TVSA under similar operating conditions. The maximum desorption rate reaches 0.23 mmol/g/min during the desorption stage. These results underscore the importance of the direct heating strategy, such as Joule heating, for fast and highly productive vacuum swing adsorption in DAC systems.

amines↗
DOE OSTI2021

Proof-of-concept of a neutron time-of-flight ellipsoidal detector

The time-resolved measurement of neutrons emitted from nuclear implosions at inertial confinement fusion facilities is used to characterize the fusing plasma. Several significant quantities are routinely measured by neutron time-of-flight (nToF) detectors in these experiments. Current nToF detectors use scintillators as well as solid-state Cherenkov radiators. The latter has an inherently faster time response and can provide a co-registered γ-ray measurement as well as improved precision in the bulk hot-spot velocity. This work discusses a nToF ellipsoidal detector that also utilizes a solid-state Cherenkov radiator. The detector has the potential to achieve a fast instrument response function allowing for characterization of the γ-ray burn history as well as the ability to field the detector closer to the fusion source. Proof-of-concept testing of the nToF ellipsoidal detector has been conducted at the National Ignition Facility using commercial optics. A time-resolved neutron signal has been measured from the diagnostic. Preliminary simulations corroborate the results.

Jeet, J. (ORCID:0000000291091563)↗
DOE OSTI2021

Mechanisms and kinetics of citrate-promoted dissolution of a uranyl phosphate mineral

The formation of uranyl phosphate precipitates is a remediation strategy to limit the mobility of uranium in contaminated soils. However, exposure to organic ligands, like the plant exudate citrate, can remobilize the uranium. The purpose of this study is to provide a more thorough comprehension of citrate-promoted dissolution of a uranyl phosphate mineral, chernikovite [(H 3 O)(UO 2 )(PO 4 )·3H 2 O], by determining the extent of uranium release from chernikovite at a wide range of citrate concentrations. Here we have quantified the kinetics of dissolution and proposed potential mechanisms of chernikovite dissolution to gain a better understanding of the fate of uranyl phosphate precipitates in the environment. Batch dissolution and continuously stirred tank reactor (CSTR) experiments indicate that increasing citrate concentrations from 0.1 mM to 50 mM increases the concentration of dissolved uranium. However, at citrate concentrations of 10 mM and greater, the effectiveness of the ligand to enhance the dissolution decreases. Density functional theory modeling and Raman spectroscopy indicate a strong interaction between citrate and the uranyl ions at the surface of the uranyl phosphate. The interaction between citrate and uranyl suggests the formation of an alteration layer of uranyl-citrate surface complexes, which could impede uranium release at citrate concentrations of 10 mM or higher. Together, these results indicate that the citrate-promoted dissolution of chernikovite is a fast reaction that is hindered by a combination of surface saturation and a secondary-phase precipitation reaction at higher concentrations of citrate and reaction times greater than or equal to 72 min based on the hydraulic residence time of CSTR experiments. These findings improve our understanding of the stability of uranyl phosphate for use in sequestration of uranium groundwater plumes at contaminated sites.

58 GEOSCIENCES↗
DOE OSTI2021

Contributions of biofilm-induced flow heterogeneities to solute retention and anomalous transport features in porous media

We report that microbial biofilms are ubiquitous within porous media and the dynamics of their growth influence surface and subsurface flow patterns which impacts the physical properties of porous media and large-scale transport of solutes. Here, a two-dimensional pore-scale numerical model was used to evaluate the impact of biofilm-induced flow heterogeneities on conservative transport. Our study integrates experimental biofilm images of Paenibacillus 300A strain in a microfluidic device packed with cylindrical grains in a hexagonal distribution, with mathematical modeling. Biofilm is represented as a synthetic porous structure with locally varying physical properties that honors the impact of biofilm on the porous medium. We find that biofilm plays a major role in shaping the observed conservative transport dynamics by enhancing anomalous characteristics. More specifically, when biofilm is present, the pore structure in our geometry becomes more spatially correlated. We observe intermittent behavior in the Lagrangian velocities that switches between fast transport periods and long trapping events. Our results suggest that intermittency enhances solute spreading in breakthrough curves which exhibit extreme anomalous slope at intermediate times and very marked late solute arrival due to solute retention. The efficiency of solute retention by the biofilm is controlled by a transport regime which can extend the tailing in the concentration breakthrough curves. These results indicate that solute retention by the biofilm exerts a strong control on conservative solute transport at pore-scale, a role that to date has not received enough attention.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coil optimization for quasi-helically symmetric stellarator configurations

Filament-based coil optimizations are performed for several quasi-helical stellarator configurations, beginning with the one from Landreman & Paul ( Phys. Rev. Lett. , vol. 128, 2022, 035001), demonstrating that precise quasi-helical symmetry can be achieved with realistic coils. Several constraints are placed on the shape and spacing of the coils, such as low curvature and sufficient plasma–coil distance for neutron shielding. The coils resulting from this optimization have a maximum curvature 0.8 times that of the coils of the Helically Symmetric eXperiment (HSX) and a mean squared curvature 0.4 times that of the HSX coils when scaled to the same plasma minor radius. When scaled up to reactor size and magnetic field strength, no fast particle losses were found in the free-boundary configuration when simulating 5000 alpha particles launched at $3.5\,\mathrm {MeV}$ on the flux surface with a normalized toroidal flux of $s=0.5$ . An analysis of the tolerance of the coils to manufacturing errors is performed using a Gaussian process model, and the coils are found to maintain low particle losses for smooth, large-scale errors up to amplitudes of approximately $0.15\,\mathrm {m}$ . Another coil optimization is performed for the Landreman–Paul configuration with the additional constraint that the coils are purely planar. Visual inspection of the Poincaré plot of the resulting magnetic field-lines reveal that the planar modular coils alone do a poor job of reproducing the target equilibrium. Additional non-planar coil optimizations are performed for the quasi-helical configuration with $5\,\%$ volume-averaged plasma beta from Landreman et al. ( Phys. Plasma , vol. 29, issue 8, 2022, 082501), and a similar configuration also optimized to satisfy the Mercier criterion. The finite beta configurations had larger fast-particle losses, with the free-boundary Mercier-optimized configuration performing the worst, losing approximately $5.5\,\%$ of alpha particles launched at $s=0.5$ .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A parametrically programmable delay line for microwave photons

Delay lines that store quantum information are crucial for advancing quantum repeaters and hardware efficient quantum computers. Traditionally, they are realized as extended systems that support wave propagation but provide limited control over the propagating fields. Here, we introduce a parametrically addressed delay line for microwave photons that provides a high level of control over the stored pulses. By parametrically driving a three-wave mixing circuit element that is weakly hybridized with an ensemble of resonators, we engineer a spectral response that simulates that of a physical delay line, while providing fast control over the delay line’s properties. We demonstrate this novel degree of control by choosing which photon echo to emit, translating pulses in time, and even swapping two pulses, all with pulse energies on the order of a single photon. We also measure the noise added from our parametric interactions and find it is much less than one photon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗