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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

The NASA Real Time Mission Monitor - A Situational Awareness Tool for Conducting Tropical Cyclone Field Experiments

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, aircraft state information, airborne and surface instruments, and weather state data in to a single visualization package for real time field experiment management. RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses (investigated African easterly waves and Tropical Storm Debby and Helene) during August-September 2006 in Cape Verde, the Tropical Composition, Cloud and Climate Coupling experiment during July-August 2007 in Costa Rica, and the Hurricane Aerosonde mission into Hurricane Noel in 2-3 November 2007. The integration and delivery of this information is made possible through data acquisition systems, network communication links, and network server resources built and managed by collaborators at NASA Marshall Space Flight Center (MSFC) and Dryden Flight Research Center (DFRC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols. Each field experiment presents unique challenges and opportunities for advancing the functionality of RTMM. A description of RTMM, the missions it has supported, and its new features that are under development will be presented.

Goodman, Michael↗
DOE OSTI2021

A Range and Performance Optimized Version of the Computer-Aided Speckle Interferometry Algorithm for Real-Time Displacement-Strain Field Monitoring

Abstract This work presents an optimized implementation of the Computer-Aided Speckle Interferometry algorithm which enables full-field determination of displacements and strains on commodity Graphics Processing Units at high resolution and frame rates. By combining careful control of the average speckle size in a laser speckle pattern with a simple sampling rate conversion scheme, a compact representation of the optical speckle is achieved. This allows for optimal use of Graphics Processing Unit architecture with robust range extension. The optimal mapping of the Computer-Aided Speckle Interferometry algorithm to Graphics Processing Unit architecture is shown in detail, and a straightforward method for disambiguating large displacements is illustrated. Lastly, this paper demonstrates a two-step subimage-tapering modification to the original algorithm that enables robust range enhancement while maintaining resolution. Results from numerical simulations on synthetic speckle patterns are shown, and runtime performance metrics are provided, with performance ranging up to 60 frames per second in some cases. The method is suitable for interactive experimental mechanics research, process and testing or any application where real-time high-resolution displacement-strain monitoring is needed. A .NET Framework class library enabling the incorporation of the algorithm into 3rd -party applications is available for download.

42 ENGINEERING↗
DOE OSTI2022

Development and application of ReaxFF methodology for understanding the chemical dynamics of metal carbonates in aqueous solutions

A new ReaxFF reactive force field has been developed for metal carbonate systems including Na + , Ca 2+ , and Mg 2+ cations and the CO 3 2– anion. This force field is fully transferable with previous ReaxFF water and water/electrolyte descriptions. The Me–O–C (Me = metal) three-body valence angle parameters and Me–C non-reactive parameters of the force field have been optimized against quantum mechanical calculations including equations of state, heats of formation, heats of reaction, angle distortions and vibrational frequencies. The new metal carbonate force field has been validated using molecular dynamics simulations to study the solvation and reactivity of metal and carbonate ions in water at 300 K and 700 K. The coordination radius and self-diffusion coefficient show good consistency with existing experimental and simulation results. The angular distribution analysis explains the structural preference of carbonate ions to form carbonates and bicarbonates, where Na + predominantly forms carbonates due to weaker angular strain, while Ca 2+ and Mg 2+ prefer to form bicarbonate monodentate in nature. Residence time distribution analyses on different systems reveal the role of ions in accelerating and decelerating the dynamics of water and carbonate ions under different thermodynamic conditions. The formation and dissolution of bicarbonates and carbonates in solution were explored on the basis of the protonation capability in different systems. Here, the nucleation phenomenon of metal carbonates at ambient and supercritical conditions is explained from the perspective of cluster formation over time: Ca 2+ ions can form prenucleation clusters at ambient temperature but show saturation with increasing temperature, whereas Na + and Mg 2+ ions show a rapid increase in cluster size and amount upon increasing time and temperature.

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

Extended flexibility of neutron Larmor diffraction for increased diffraction range in mosaicity measurements

Larmor diffraction (LD) is a neutron scattering technique that offers enhanced resolution by harnessing the Larmor precession of neutron spins in a magnetic field. By encoding subtle changes in neutron momentum transfer into significant alterations in the Larmor phase of neutron spins, LD can be employed to measure lattice expansion, lattice distortion, and mosaicity with exceptional resolution. As originally proposed by Rekveldt et al., LD necessitates the magnetic field boundaries to be tilted to be parallel to the crystal plane of interest. Here, this report explores the fundamental principles shared between LD and spin-echo small-angle neutron scattering (SESANS). Drawing inspiration from the flexibility of SESANS to adjust magnetic field boundaries to optimize the resolution in the measurement of the neutron momentum transfers q, we will demonstrate that the strict requirement of parallel alignment between the magnetic field boundaries and the crystal plane can be relaxed for the measurements of mosaicity. Such relaxation will expand the accessible diffraction angles for these situations that are highly constrained.

Larmor diffraction↗
DOE OSTI2023

Computed axial lithography optimization system

A system for determining a light intensity field for use in manufacturing a 3D object from a volume of material. The system receives a 3D specification of a 3D geometry for the 3D object that specifies voxels within the volume that contain material that is to be part of the 3D object. The system employs a cost function for effectiveness of a light intensity field in manufacturing the 3D object. The cost function may be an adjoint of an Attenuated Radon Transform that models an energy dose that each voxel would receive during manufacture of the 3D object using the light intensity field. The system applies an optimization technique that employs the cost function to generate a measure of the effectiveness of possible light intensity fields and outputs an indication of a light intensity field that will be effective in manufacturing the 3D object.

Shusteff, Maxim↗
DOE OSTI2022

Integrated reactor architecture of conductive network and catalytic nodes to accelerate polysulfide conversion for durable and high-loading Li-S batteries

The development of carbon-based heterogeneous framework host with synergistic catalytic and conductive effects for sulfur cathode is a promising strategy to realize high performance lithium sulfur batteries (LSBs). Here, an integrated reactor architecture with defective carbon nodes (IRA-DC) is designed for serving as high-loading (92.4 wt%) sulfur host. The hierarchical porous IRA-DC consists of untangled conductive carbon nanotube network and Co/N co-doped catalytic nodes with high dispersity. Therein the optimization of electric field distribution and homogenization of adsorption-catalysis sites offer the multi-electron conversion reaction of polysulfides with excellent kinetics and stability. The resultant IRA-DC/S cathode enables a high areal capacity of 8.86 mAh cm -2 under ultra-high sulfur loading (13.1 mg cm -2 ) and lean electrolyte (8 μL mg sulfur -1 ). It also displays a long-term cycling performance (1200 cycles at 1 C) and ultrahigh rate performance up to 20 C (with a capacity of 473.6 mAh g -1 ). In conclusion, this work provides an electrode building strategy by optimizing the environments of heterogeneous electrocatalysis and micro electric field to activate the polysulfide conversion efficiency and utilization of high-loading sulfur in monolithic sulfur-carbon cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Kinetics of low temperature plasma assisted NH 3 /H 2 oxidation in a nanosecond-pulsed discharge

Ammonia (NH 3 ) has been widely recognized as one of the carbon-neutral fuels. However, ammonia combustion suffers low reactivity and high N 2 O/NO x emissions. Here, to overcome these issues, this work reports plasma assisted NH 3 /H 2 oxidation and unveils the kinetics of fuel oxidation and N 2 O/NO x formation by combining time-resolved laser diagnostics with plasma modeling. Firstly, we found that the NH 3 consumption is promoted with a H 2 blending ratio of 0.3, due to enhancements of H and OH formation by plasma assisted H 2 dissociation. Secondly, at a high reduced electric field, when the H 2 blending ratio increases, the NH 3 oxidation is promoted due to both the HO 2 formation and strong NO kinetic enhancement via NO-HO 2 and NO 2 -H pathways. In the meantime, it is shown that the NO mole fraction also increases with H 2 blending ratio, because the NO formation is enhanced via N( 2 D)-O 2 pathways, and the DeNO x chemistry is weakened with less NH 2 production. By contrast, at a lower reduced electric field, when the H 2 blending ratio increases, the decreased N( 2 D) formation does not produce enough NO to replenish the NO formation drop caused by lower NH 3 concentration. Thirdly, the reduced electric field non-monotonically affects fuel consumption and N 2 O/NO x formation by manipulating electron energy deposition pathways. The NH 3 consumption is maximized with an optimal reduced electric field where N 2 * excitation and O 2 dissociation are most efficient. When the reduced electric field deviates from its optimum, the NH 3 consumption decreases due to the discharge energy deposition to either vibrational excitation or dissociation of N 2 . The N 2 O/NO x emissions governed by the NH 3 oxidation follow the above NH 3 consumption trend.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1980

An application of extremal field guidance in statistical low thrust guidance analysis

The subject of this paper is the application of extremal field guidance to the covariance analysis of low thrust retargeting guidance. The general procedure for low thrust navigation analysis is briefly reviewed. The basic equations of trajectory optimization and extremal field guidance are presented with emphasis on the low thrust problem. The adopted formulation includes thruster on-off times as control variables and accounts for the effects of model parameter variations. A method of solution of the guidance equations is outlined; and the application of the solution in a covariance analysis, including a procedure for the treatment of model parameter variations as either biases or first order Gauss-Markov stochastic processes, is discussed.

Jacobson, R. A.↗
NASA NTRSDate not supplied

Generating a 4D Global CH(4) Product by Assimilating TROPOMI column CH(4) in NASA’s GEOS GCM

Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.

Nikolay V. Balashov↗
DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Conceptual Design of DUNE Near Detector Superconducting Magnet System

The Deep Underground Neutrino Experiment (DUNE) has formed a near detector design group (NDDG) tasked with delivering a CDR by the end of 2019. The DUNE Near Detectors will be housed in an underground hall on the Fermilab site. The two main detector systems are a liquid argon detector and a high-pressure gas time projection chamber (HPgTPC). The HPgTPC requires a magnet that generates a 0.5 T solenoidal magnetic field in a large volume of 6 m diameter, and 5 m length. Herein, we present a superconducting magnet system design. We investigated: an open air core magnet with three coils, and a five coils system having two active fringe field shielding coils. Coils positions were optimized to obtain the specified field homogeneity in the magnet good field region, while minimizing the Lorentz forces and the superconductor volume. We discuss the magnetic, mechanical, and thermal conceptual designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Comparative Analysis of TRGBs (CATs) from Unsupervised, Multi-halo-field Measurements: Contrast is Key

The tip of the red giant branch (TRGB) is an apparent discontinuity of the luminosity function (LF) due to the end of the red giant evolutionary phase and is used to measure distances in the local universe. In practice, tip localization via edge detection response (EDR) relies on several methods applied on a case-by-case basis. It is hard to evaluate how individual choices affect a distance estimation using only a single host field while also avoiding confirmation bias. To devise a standardized approach, we compare unsupervised, algorithmic analyses of the TRGB in multiple halo fields per galaxy. We first optimize methods for the lowest field-to-field dispersion, including spatial filtering, smoothing, and weighting of LF, color band selection, and tip selection based on the number of likely RGB stars and the ratio of stars below versus above the tip (R). We find R, which we call the tip contrast, to be the most important indicator of the quality of EDR measurements; higher R selection can decrease field-to-field dispersion. Further, since R is found to correlate with the age or metallicity of the stellar population based on theoretical modeling, it might result in a displacement of the detected tip magnitude. We find a tip-contrast relation with a slope of -0.023 ± 0.0046 mag/ratio, an ~5σ result that can be used to correct these variations in the detections. When using TRGB to establish a distance ladder, consistent TRGB standardization using tip-contrast relation across rungs is vital to make robust cosmological measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

The Use of Handheld X-Ray Fluorescence (XRF) Technology in Unraveling the Eruptive History of the San Francisco Volcanic Field, Arizona

While traditional geologic mapping includes the examination of structural relationships between rock units in the field, more advanced technology now enables us to simultaneously collect and combine analytical datasets with field observations. Information about tectonomagmatic processes can be gleaned from these combined data products. Historically, construction of multi-layered field maps that include sample data has been accomplished serially (first map and collect samples, analyze samples, combine data, and finally, readjust maps and conclusions about geologic history based on combined data sets). New instruments that can be used in the field, such as a handheld xray fluorescence (XRF) unit, are now available. Targeted use of such instruments enables geologists to collect preliminary geochemical data while in the field so that they can optimize scientific data return from each field traverse. Our study tests the application of this technology and projects the benefits gained by real-time geochemical data in the field. The integrated data set produces a richer geologic map and facilitates a stronger contextual picture for field geologists when collecting field observations and samples for future laboratory work. Real-time geochemical data on samples also provide valuable insight regarding sampling decisions by the field geologist

Young, Kelsey E.↗
DOE OSTI2025

Iterative quantum optimization of spin glass problems with rapidly oscillating transverse fields

In this work, we introduce a new iterative quantum algorithm, called Iterative Symphonic Tunneling for Satisfiability problems (IST-SAT), which solves quantum spin glass optimization problems using high-frequency oscillating transverse fields. IST-SAT operates as a sequence of iterations, in which bitstrings returned from one iteration are used to set spin-dependent phases in oscillating transverse fields in the next iteration. Over several iterations, the novel mechanism of the algorithm steers the system toward the problem ground state. We benchmark IST-SAT on sets of hard MAX-3-XORSAT problem instances with exact state vector simulation, and report polynomial speedups over Trotterized adiabatic quantum computation and the best known semi-greedy classical algorithm. When IST-SAT is seeded with a sufficiently good initial approximation, the algorithm converges to exact solution(s) in a polynomial number of iterations. Our numerical results identify a critical Hamming radius, or quality of initial approximation, where the time-to-solution crosses from exponential to polynomial scaling in problem size. This work proposes IST-SAT a new quantum algorithm, which improves upon solutions obtained from initial classical or quantum optimization algorithms. The steering mechanism we introduce through IST-SAT presents a new path toward achieving quantum advantage in optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2014

First Use of Synoptic Vector Magnetograms for Global Nonlinear, Force-Free Coronal Magnetic Field Models

Context. The magnetic field permeating the solar atmosphere is generally thought to provide the energy for much of the activity seen in the solar corona, such as flares, coronal mass ejections (CMEs), etc. To overcome the unavailability of coronal magnetic field measurements, photospheric magnetic field vector data can be used to reconstruct the coronal field. Currently, there are several modelling techniques being used to calculate three-dimensional field lines into the solar atmosphere. Aims. For the first time, synoptic maps of a photospheric-vector magnetic field synthesized from the vector spectromagnetograph (VSM) on Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used to model the coronal magnetic field and estimate free magnetic energy in the global scale. The free energy (i.e., the energy in excess of the potential field energy) is one of the main indicators used in space weather forecasts to predict the eruptivity of active regions. Methods. We solve the nonlinear force-free field equations using an optimization principle in spherical geometry. The resulting threedimensional magnetic fields are used to estimate the magnetic free energy content E(sub free) = E(sub nlfff) − E(sub pot), which is the difference of the magnetic energies between the nonpotential field and the potential field in the global solar corona. For comparison, we overlay the extrapolated magnetic field lines with the extreme ultraviolet (EUV) observations by the atmospheric imaging assembly (AIA) on board the Solar Dynamics Observatory (SDO). Results. For a single Carrington rotation 2121, we find that the global nonlinear force-free field (NLFFF) magnetic energy density is 10.3% higher than the potential one. Most of this free energy is located in active regions.

Sun: corona↗