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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gravitational form factors and mechanical properties of quarks in protons: A basis light-front quantization approach

We compute the gravitational form factors (GFFs) and study their applications for the description of the mechanical properties such as the pressure, shear force distributions, and the mechanical radius of the proton from its light-front wave functions (LFWFs) based on basis light-front quantization (BLFQ). The LFWFs of the proton are given by the lowest eigenvector of a light-front effective Hamiltonian that incorporates a three-dimensional confining potential and a one-gluon exchange interaction with fixed coupling between the constituent quarks solved in the valence Fock sector. We find acceptable agreement between our BLFQ computations and the lattice QCD for the GFFs. Our D -term form factor also agrees well with the extracted data from the deeply virtual Compton scattering experiments at Jefferson Lab, and the results of different phenomenological models. The distributions of pressures and shear forces are similar to those from different models. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2021

Particle charge distributions in the effluent of a flow-through atmospheric pressure low temperature plasma

Atmospheric pressure low-temperature plasmas are often utilized to perform particle synthesis, treatment, and removal. It is well-known that dust particles are highly negatively charged in these plasmas; however, little is known about dust particle charging behavior as particles leave the plasma volume and pass through the spatial afterglow region. In this work, monodisperse particles of various sizes and work functions were introduced into an atmospheric pressure radiofrequency capacitively coupled flow-through plasma. Dust particle electrical mobility distributions downstream of the flow-through plasma were measured utilizing a differential mobility analyzer in conjunction with a condensation particle counter at various gas flow velocities. Charge distributions were determined from the measured electrical mobility distributions. Experiments confirm that particles become less negatively charged, and even net-positively charged after leaving the plasma volume, with a distribution that follows a shifted Boltzmann charge distribution. Additionally, particle charge in the effluent of the flow-through plasma is negligibly dependent on work function but highly size and flow velocity dependent. Larger particles were shown to have a higher magnitude of charge under all studied conditions; however, particle polarity was switchable by varying gas flow velocity. The charging dynamics were simulated utilizing a constant number Monte Carlo model that accounts for electron temperature decay and the transition from ambipolar to free diffusion of electrons and ions in the spatial afterglow. Simulation results also suggest that, at the same flow velocity, larger particles obtain a greater magnitude of charge, negative or positive. Furthermore, the decrease in electron mobility and the difference between ion and electron convective loss rates create an ion-rich region in the plasma effluent that promotes ion–particle collisions and drives particle charge removal and even reversal of polarity. Larger particles more favorably collide with energetic species in these environments, which results in higher charge states.

atmospheric pressure low temperature plasma↗
DOE OSTI2022

Spatially enhanced electric field induced second harmonic (SEEFISH) generation for measurements of electric field distributions in high-pressure plasmas

Abstract The spatial resolution of the ps electric field induced second harmonic (EFISH) generation has been enhanced by using non-collinear pump laser beam arrangements. The pump laser beam (1064 nm, nominal pulse duration 150 ps, pulse energy 20–40 mJ) is separated into two coaxial or crossing beams, overlapping only near the focal point. The spatially enhanced EFISH (SEEFISH) signal is generated over a shorter beam overlap region compared to the collinear beam arrangement. Blocking of either of the two beams results in a complete suppression of the signal. The signal is spatially isolated from the ‘conventional’ EFISH signal and measured by a photomultiplier detector. Measurements of a known Laplacian field generated between two parallel cylinder electrodes in ambient air shows that SEEFISH improves the spatial resolution of the measurements by up to a factor of 2, such that the measurement results agree with the Laplacian field distribution. The spatial resolution is improved further by reducing the focal distance of the lens. The magnitude of the SEEFISH signal is significantly lower compared to that of the single-beam EFISH and decreases rapidly as the beam crossing angle is increased, due to the phase mismatch. This approach has a significant potential for measurements of electric field distributions in high-pressure plasmas, with an additional benefit of removing the stray second harmonic signal from the optical access windows.

Physics↗
DOE OSTI2021

The research into the propagation law of the shock wave of a gas explosion inside a building

Based on the dissipation rate conservation equations of turbulent kinetic energy in the k‐ ε turbulence model, a complicated three‐dimensional finite element model of a kitchen filled with gas mixture is developed by using the open source field operation and manipulation (OpenFOAM). Two representative kitchens were used to investigate the propagation law of the shock wave of a gas explosion inside a building by considering the key characteristics of the blast shock wave. The influence of some crucial parameters, such as initial conditions and kitchen parameters, on the properties of the blast shock wave is investigated. The basic steps to predict the peak pressure of the blast shock wave are given in consideration of the initial condition and the kitchen whilst the injury effect of the blast shock wave on the humans and animals is evaluated. The research results indicate that the pressure time history and the peak pressure space distribution are greatly influenced by the kitchen design layout. The coupled interaction between the initial temperature and gas volume concentration, especially at the upper and lower explosion limits of the gas, significantly affects the peak pressure. The peak pressure varies significantly with the opening and the buffer; however, it has little relation with the width, length, and height of the kitchen. The proposed method can accurately and effectively predict the peak pressure of the blast shock wave inside buildings. In terms of the peak pressure space distribution of the explosion shock wave, the peak pressure is much higher than the threshold of the killing pressure, which is unsafe for the humans and animals in the building.

Lin, Shu-Chao↗
DOE OSTI2021

Determination of a most representative cycle from cylinder pressure ensembles via statistical method using distribution skewness

In internal combustion engine research, cylinder pressure measurements provide valuable information about the underlying thermodynamic and combustion processes, and are typically collected in ensembles of several 100 traces. Although in some particular fields of combustion research all traces are analyzed, in most cases only one trace is studied because analyzing all the traces is impractical due to the large number of collected samples. Instead, an ensemble-averaged pressure trace is commonly calculated and used for analysis. However, this pressure trace is highly smoothed and dynamic information is lost during the averaging process. With the average trace, pressure rise rates are lower and pressure oscillations such as the ones resulting from combustion knock are lost. In this work, a statistical method was developed to determine the “most representative cycle,” which is the cycle from the ensemble that has the pressure trace most representative of the engine operating condition. Eleven characteristic parameters are computed from each pressure trace and probabilistic distributions are obtained for each of the parameters using all the traces in the ensemble. Finally, the most representative cycle is selected by means of a cost function minimization. The benefits of this method are illustrated using experimental data from four very different engine platforms, under four different combustion modes and over a range of operating conditions.

42 ENGINEERING↗
DOE OSTI2023

Peak Reduction Using Mode Adjustment of Heat Pump Water Heaters in a Residential Neighborhood

Building electrification is putting pressure on distribution grid worldwide. Peak reduction is an important concern that can help reduce the growing stress and allow to defer investments in new capacity. Water heaters represent a convenient way of reducing peak because they are less dependent on weather, and their storage volume allows for asynchronous water heating and hot water use. Previous empirical studies investigated the ability of water heaters to reduce peak through the adjustment of the temperature setpoint. However, not all equipment vendors offer this option. This study aims at understanding the feasibility of peak reduction with an alternative configuration available in the market - by adjusting the device mode rather than temperature setpoint. The peak reduction methodology is tested in an occupied 46-townhome neighborhood located in Atlanta, GA. We find that peak shifting is possible with the adjustable mode approach, with the change in the peak load by 30-60%.

demand response↗
DOE OSTI2022

Finite Element Simulation of the Acoustic Pressure Inside a Beverage Container for Non-Thermal, Ultrasound-based Pasteurization

The purpose of this effort is to investigate whether large acoustic pressure waves can be transmitted inside beverage containers to enable pasteurization. Acoustic waves are known to induce large nonlinear compressive forces and shock waves in fluids, suggesting that compression waves may be capable of damaging bacteria inside beverage containers without appreciably increasingly the temperature or altering the freshness and flavor of the beverage contents. Although a combined process such as thermosonication (e.g., sonication with heating) is likely more efficient, it is instructive to compute the acoustic pressure field distribution inside the beverage container. The COMSOL simulations used two and three-dimensional models of beverage containers placed in a water bath to compute the acoustic pressure field. A limitation of these COMSOL models is that they cannot determine the bacterial lysis efficiency, rather the models provide an indirect metric of bacterial lysis based on the magnitude of the pressure field and its distribution.

42 ENGINEERING↗
DOE OSTI2023

Energy Savings With Acceptable Indoor Air Quality Through Improved Airflow Control in Residential Retrofits

The Partnership for Advanced Residential Retrofit (PARR) has been a U.S. Department of Energy (DOE) Building America team since 2009, with a primary focus on upgrading the performance of existing buildings to reduce energy loads. In this project, PARR’s work explored the integration of airflow-focused measures in residential retrofit homes with the goal to maximize energy savings while ensuring acceptable indoor air quality (IAQ) using a systems approach to controlling four contributing air streams: • Building air leakage (natural, uncontrolled infiltration), • Forced-air distribution system static pressure and airflow rate, • Distribution system duct leakage, and • Mechanical ventilation. This project addressed airflows in houses, their combined impact on energy use and IAQ, and the comparative effects of typical insulation and air sealing practices versus integrated system-level retrofits. Additionally, practical considerations for contractors taking either approach were addressed. Finally, the effects of supply ventilation and exhaust ventilation on IAQ were compared in occupied homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid

Predicting the functional properties of many molecular systems relies on understanding how atomistic interactions give rise to macroscale observables. However, current attempts to develop predictive models for the structural and thermodynamic properties of condensed-phase systems often rely on extensive parameter fitting to empirically selected functional forms whose effectiveness is limited to a narrow range of physical conditions. Here, we illustrate how these traditional fitting paradigms can be superseded using machine learning. Specifically, we use the results of molecular dynamics simulations to train machine learning protocols that are able to produce the radial distribution function, pressure, and internal energy of a Lennard-Jones fluid with increased accuracy in comparison to previous theoretical methods. The radial distribution function is determined using a variant of the segmented linear regression with the multivariate function decomposition approach developed by Craven et al. [J. Phys. Chem. Lett. 11, 4372 (2020)]. The pressure and internal energy are determined using expressions containing the learned radial distribution function and also a kernel ridge regression process that is trained directly on thermodynamic properties measured in simulation. The presented results suggest that the structural and thermodynamic properties of fluids may be determined more accurately through machine learning than through human-guided functional forms.

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

High-pressure deformation of metallic glass nanoparticles

Here, the atomistic structure of metallic glasses is closely related to properties such as strength and ductility. Here, Ni 1-x B x metallic glass nanoparticles of two different sizes are compressed under quasi-hydrostatic high-pressure conditions in order to understand structural changes under stress. The structural changes in the nanoparticles were tracked using in situ high-pressure X-ray diffraction (XRD). The ambient pressure pair distribution functions generated from XRD showed that the smaller sized nanoparticles had a more compact amorphous structure with lower coordination number. XRD showed that the amorphous structure was stable up to the maximum pressures achieved. The bulk modulus of the smaller and larger sized nanoparticles was found to be 208 GPa and 178 GPa, respectively. This size-dependent high-pressure behavior was related to compositional differences between the nanoparticles. These results show that Ni 1-x B x metallic glass nanoparticles are highly stable under pressure, which could enable their use as inclusions in metal or ceramic matrix composites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Calcined Polyethyleneimine Coated Optical Fibers for Distributed pH Monitoring at High Pressures and Temperatures

In the oil and gas, CO2 sequestration, H2 subsurface storage, and geothermal energy sectors, subsurface pH measurements are critical for monitoring the geochemical conditions and estimating potential corrosion rates of wellbore systems. Real-time pH measurements in these conditions are vital for detecting and predicting corrosion deterioration of wellbore components that may jeopardize the safety and continued operation of wellbore systems. Building off of earlier TiO2 based pH sensors and the known pH sensitivity of amine-based polymers, a coating based on the secondary amine polymer polyethyleneimine (PEI) was developed. The sensor coating was treated with a high temperature (500 °C) calcination procedure in air to convert it into a more stable oxidized coating capable of withstanding hot aqueous solutions without dissolving while retaining linear pH sensitivity from pH values between 2 and 11. The sensor performance was measured using optical transmission measurements in solutions of various pHs and using optical backscatter reflectometry for distributed pH sensing demonstration in wellbore-relevant pressures (up to 1000 psi) and temperatures (80 °C). A calibration curve with strong differentiation between acidic and alkaline pH was developed for both transmission-based and distributed pH measurements, using fixed wavelength transmission and integrated linear amplitude of backscattered light for distributed measurements.

Shumski, Alexander↗
DOE OSTI2024

Calcined Polyethyleneimine-Coated Optical Fibers for Distributed pH Monitoring at High Pressures and Temperatures

In the oil and gas, CO2 sequestration, H2 subsurface storage, and geothermal energy sectors, subsurface pH measurements are critical for monitoring the geochemical conditions and estimating potential corrosion rates of wellbore systems. Real-time pH measurements in these conditions are vital for detecting and predicting corrosion deterioration of wellbore components that may jeopardize the safety and continued operation of wellbore systems. Previous tests using metal oxide-based coatings (TiO2) provided strong responses at elevated temperatures and moderate pressure stability but provided poor differentiation between acidic and alkaline solutions. Building off the pH responsiveness of the TiO2 surface and known pH sensitivity of amine-based polymers, a coating based on the secondary amine polymer polyethyleneimine (PEI) was developed. As the polymer itself is highly water soluble and easily removed by aqueous solutions, the sensor coating was treated with a high temperature (500 °C) calcination procedure in air to convert it into a more stable oxidized coating capable of withstanding hot aqueous solutions without dissolving while retaining linear pH sensitivity from pH values between 2 and 11. The sensor performance was measured using optical transmission measurements in solutions of various pHs and using optical backscatter reflectometry for distributed pH sensing demonstration in wellbore-relevant pressures (up to 1,000 psi) and temperatures (80 °C).

Shumski, Alexander↗
DOE OSTI2021

Experimental Study of Transport Behavior of Swellable Microgel Particles in Superpermeable Channels for Conformance Control

Summary Gel treatment is an effective way to attack excessive water production during oil development. The transport behavior of gel materials in reservoirs is of crucial importance to the effectiveness of gel treatments. The aim of this paper is investigating the transport behavior of swellable micrometer-sized preformed particle gels (PPGs, or microgels) through superpermeable (super-K) channels. Sandpacks with permeabilities ranging from 27 to 221 darcies were used to mimic the super-K channels. Multiple pressure sensors were applied along the sandpack models to monitor the propagation behavior of the microgels. The tested microgel particles could transport through the super-K channels, and a higher driving pressure gradient was required when the particle/pore size ratio was larger. The pressure gradient distribution along the super-K channels was relatively uniform when the particle/pore ratio was low (less than 1.3). However, the inlet section would show increasingly higher pressure gradients as the particle/pore ratio was increased, indicating increased difficulty in propagation. The propagation of the gel particles was significantly slower compared with the carrying fluid. The delayed propagation behavior was more pronounced when the particle/pore ratio was higher. The injection pressure was much less sensitive to the injection flow rate compared with a Newtonian fluid. The gel dispersion exhibited an apparent shear thinning (pseudoplastic) behavior when transporting through the porous channels. Breakage of the gel particles was observed especially at high superficial velocities. The particle breakage was partially responsible for the apparent shear thinning behavior. The breakage phenomenon was in favor of deep placement of the gel particles. The channel permeabilities were significantly reduced by the microgels, bringing sufficient resistance to subsequent waterflooding (more than 99.5%). At given matching size conditions, softer gels were more likely to establish in-depth placement and uniform water blocking capacity in the channels. The microgel particles exhibited salinity-responsive behavior to the post-brine flush. The gel particles could shrink and reswell according to the salinity of the injected water. Possibilities were discussed to use this salinity-responsive behavior. Also, the microgels exhibited a particular disproportionate permeability reduction (DPR) effect. After gel injection, the channel permeability to water flow was reduced by more than 20 to 92 times of the permeability to oil flow. This work provides important support to understand the transport behavior of gel particles in super-K channels. The achievements are helpful for gel product selection and gel treatment design.

Engineering↗
DOE OSTI2020

CHARACTERISTICS OF CYCLE-TO-CYCLE COMBUSTION VARIABILITY AT PARTIAL-BURN LIMITED AND MISFIRE LIMITED SPARK TIMING UNDER HIGHLY DILUTED CONDITIONS

Diluted combustion with exhaust gas recirculation (EGR) has been widely employed to improve the fuel economy of spark ignition engines. The combustion kinetics, however, are affected and the flame propagation speed is decreased. In order to compensate for this adverse effect, the spark timing needs to be recalibrated to achieve maximum brake torque (MBT). At high levels of EGR dilution, the spark timing is constrained by two ignition limits: 1) the partial-bum limit where the spark timing is retarded from MBT and 2) the misfire limit where the spark timing is too advanced. This work uses a probabilistic framework to capture the differences between both ignition limits. In particular, it introduces the concept of a nominal indicated mean effective pressure (IMEP) distribution based on the stochastic properties of the cycle-to-cycle variability (CCV) at nominal stable conditions. By defining a nominal band where fully burned cycles occur with high probability, we introduce a cycle classification method that can be used to 1) determine the level of randomness of misfire and partial-burn events, and 2) measure CCV. The new CCV metric based on the density of the nominal band is compared with the traditional coefficient of variation of IMEP (CoVIMEP). It is shown that the nominal band concept, together with the CoVIMEP, can help to discern between partial-burn limited and misfire limited conditions. Furthermore, the Kullback-Leibler divergence is used to demonstrate that the IMEP distribution is significantly different between nominal and partial-burn/misfire limited conditions. Experiments are carried at various EGR levels and spark timings while recoding in-cylinder pressure at steady state. Although the emphasis of this work is to characterize the differences of both ignition limits from a probabilistic point of view, similarities between partial-burn cycles at either limiting conditions are also discussed.

Maldonado, Bryan↗
DOE OSTI2020

Smart Proxy Modeling Application of Artificial Intelligence & Machine Learning in Computational Fluid Dynamics

Smart proxy technology leverages the art of artificial intelligence and machine learning in order to build accurate and very fast proxy models for highly complex numerical simulation models. In this project, smart proxy technology is used to replicate the results of a highly complex single phase CFD simulation with reasonable degree of accuracy while reducing the computational cost associated with such CFD simulations. The CFD model under study simulates the combustion of natural gas under various conditions such as varying natural gas composition and flow rate, inlet air flow rate and temperature, and outlet pressure in a High-Pressure Combustion Facility (B6 Combustor) with more than 4 million simulation cells. Only eight CFD simulation runs were used to create a smart proxy model that replicates the detail distribution of Pressure, Temperature, Nitrogen, Oxygen and Carbon-dioxide concentration in the CFD simulation model in seconds with less than 10% error.

03 NATURAL GAS↗
DOE OSTI2026

Velocity-space Origins of the Pressure–Strain Interaction in Multipopulation Distributions and Its Application to Magnetic Reconnection

A forefront research question is how energy evolves in weakly collisional plasmas for which departures from local thermodynamic equilibrium (LTE) are significant. The standard approach is studying the terms in the non-LTE energy evolution equation derived by taking the second moment of the Boltzmann equation, but the resultant fluid metrics do not retain information about which particles at which velocities drive energy evolution. A widely studied channel for internal energy density evolution is the pressure–strain interaction. Here, we employ the kinetic pressure–strain, a phase-space diagnostic whose velocity-space integral recovers the pressure–strain interaction to disambiguate the contributions to the pressure–strain interaction from disparate particle populations in composite phase-space densities. We develop phase-space analogs of the pressure–strain interaction decompositions to provide the phase-space origins of normal versus sheared flow. We introduce the “kinetic strain-rate” tensor, the phase-space analog of the strain-rate tensor, which we argue is needed to interpret the phase-space origins of the pressure–strain interaction. To demonstrate the utility of these quantities, we investigate them for composite electron distributions near the electron diffusion region in two-dimensional particle-in-cell simulations of antiparallel symmetric magnetic reconnection. We find that the phase-space-based diagnostics isolate the roles of distinct populations. These results contribute to a growing body of work providing new methods for quantifying phase-space energy evolution for a broad array of processes, from magnetic reconnection to collisionless shocks and turbulence, opening new pathways for answering longstanding problems of particle energization in weakly collisional plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Prediction for Pressure Differential Across HEPA Filter Media Based on Media Characteristics and Particle Size Distribution

A new method for predicting the pressure drop across High Efficiency Particulate Air (HEPA) filter media is proposed based upon mass deposited onto the filter and known physical characteristics of the filter media. Detailed are the methods used in conjunction with current filter loading models to predict the pressure drop, as well as tests conducted to validate the methods. The benefit of a prediction model for practical use lies in the manufacturing and service life of nuclear grade HEPA filters. HEPA filters for use in nuclear facilities have a prescribed expiration date and a maximum allowable operating pressure drop. Therefore, the ability to predict the pressure drop across a filter and relate it to an expected length of service time can enable a reduction in wasted filters. This will allow for more informed decisions to be made based upon the dictated life cycle of the filters. Also, understanding and predicting how the pressure drop of HEPA filter media behaves as a function of physical characteristics and loaded mass can assist in future design and manufacturing of filter media. Currently, most existing pressure drop models are either computationally based or analytical methods relying on data gathered during tests. Neither are practical for prediction; the computational methods are difficult to implement, and the current analytical methods are more useful as tools for analysis. The current analytical model developed by Bergman et al. is based upon the pressure drop from each media fiber and modeling the deposited particles as newly formed fibers. Using Bergman's model and the media properties, air properties, and known aerosol particle size distribution, a pressure drop curve as a function of loaded mass can be created. This curve implies initial loading in the depth of the filter media with a transition to pure surface loading on the filter face, and a sensitivity to an evolving particle size distribution as mass continues to load onto the filter. To implement the predictive model, knowledge of the mean filter fiber diameter and porosity of the filter media is required. Traditionally, the mean fiber diameter is calculated as an effective diameter from prior media testing, however, in this study a Scanning Electron Microscope (SEM) technique is used to acquire this variable. Validation of the predictive model is provided by flat sheet media tests under a controlled environment with a measured particle size distribution of the challenge aerosol and shows reasonable preliminary agreement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗