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At least 847 records · Page 47

Sensitivity Studies of Premixed Flame Response to Transverse, High Frequency Disturbances

This study analyzes the response of premixed flames to high frequency transverse acoustic disturbances. A significant body of experiment, modeling and simulation efforts has been performed to understand the response of the spatially integrated heat release of premixed flames to low-frequency disturbances. These studies quantified this sensitivity through the Flame Transfer Function (FTF), as the global heat release is the key quantity influencing thermoacoustic stability for acoustically compact flames. Recent efforts have expanded these models to consider high-frequency acoustic disturbances, and the sensitivity of premixed flames through the Rayleigh integral (RI). The full Rayleigh Integral, as opposed to simply the spatially integrated heat release, must be considered in these cases where the flame is not acoustically compact. Prior modeling studies considered several effects - stability of axisymmetric flames centered in a cylindrical combustion chamber and the effect of flame offset from the combustor axis and the effect of mean flame asymmetries in the flame centered in the combustor. These studies showed that the flame's stability was sensitive to all these parameters, as well as to the transverse mode in question. In this paper, we quantify these different parametric sensitivities of premixed flame stability in the presence of high-frequency transverse acoustic modes - specifically sensitivity to flame length and nozzle location within the acoustic mode shape for 2 different transverse modes. The sensitivity of the RI to these control parameters provides an improved understanding of which flame parameters are critical to improve the overall thermoacoustic stability of the system.

Acharya, Vishal S.↗

Evaluation and verification of epitaxial process sequence for silicon solar-cell production

To achieve the program goals, 28 minimodules were fabricated and tested, using 600 cells made from three-inch-diameter wafers processed by the sequence chosen for this purpose. Of these 600 cells, half were made from epitaxially grown layers on potentially low-cost substrates. The other half were made from commercial semiconductor-grade (SG), single-crystal silicon wafers that served as controls. Cell processing was normally performed on mixed lots containing significant numbers of each of these two types of wafers. After evaluation of the performance of all cells, they were separated by types for incorporation into modules that were to be tested for electrical performance and response to environmental stress. A simplified flow chart displaying this scheme, for quantities representing half of the planned total to be processed, is presented.

Redfield, D.↗

Soot formation in pyrolysis of acetylene, allene and 1,3-butadiene

The formation of soot behind reflected shock waves in argon-diluted mixtures of acetylene, allene, and 1,3-butadiene was investigated by monitoring the attenuation of a laser beam in both the visible (632.8 nm) and the infrared (3.39 microns) regions of the spectrum. The experiments utilized temperatures ranging from 1500-3100 K, reflected shock pressures of 0.3-7.0 bar, and total carbon atom concentrations of 2-20 x 10 to the 17th atoms/cu cm. A bell-shaped dependence of soot yield on temperature was observed during the pyrolysis of all three compounds, which was similar to that previously found for toluene. For acetylene, the decrese in total pressure was found to shift the soot bell to higher temperatures with a significant increase in the maximum soot yield. A computer simulation for acetylene pyrolysis suggested that the reactions between C2H3, C4H3, and C4H4 may be those which lead to the formation of aromatic structures. In addition, it was found that soot is formed much faster and in much larger quantities from allene than from 1,3-butadiene.

Frenklach, M.↗

Computational Aspects of Sensitivity Calculations in Linear Transient Structural Analysis

A study has been performed focusing on the calculation of sensitivities of displacements, velocities, accelerations, and stresses in linear, structural, transient response problems. One significant goal was to develop and evaluate sensitivity calculation techniques suitable for large-order finite element analyses. Accordingly, approximation vectors such as vibration mode shapes are used to reduce the dimensionality of the finite element model. Much of the research focused on the accuracy of both response quantities and sensitivities as a function of number of vectors used. Two types of sensitivity calculation techniques were developed and evaluated. The first type of technique is an overall finite difference method where the analysis is repeated for perturbed designs. The second type of technique is termed semianalytical because it involves direct, analytical differentiation of the equations of motion with finite difference approximation of the coefficient matrices. To be computationally practical in large-order problems, the overall finite difference methods must use the approximation vectors from the original design in the analyses of the perturbed models.

Greene, William H.↗

Energy Requirements of Hydrogen-Utilizing Microbes: Boundary Condition for Subsurface Life

For planetary bodies with surface conditions that are too harsh to permit continuous occupation by life, the deep subsurface offers a potentially stable and habitable niche. For organisms occupying this niche, the spectrum of possible metabolisms must be limited to those which do not include sunlight as an energy source or oxygen as a chemical reagent - generally, low-energy anaerobic oxidation-reduction processes. The quantity of energy released in such processes is critical, because currently understood mechanisms of biological energy conservation indicate that energy is only 'useful' to an organism when it is available at a certain minimum level - the 'biological energy quantum'. The mere existence of a BEQ implies that a significant fraction of the chemical energy present in the environment cannot be exploited by life; similarly, the absolute magnitude of the BEQ must be a key variable in determining the potential viability and distribution of subsurface microbial communities. Laboratory culture studies suggest that organisms require an energy of about -20 kJ/mol to grow. However, we find that hydrogen-utilizing microorganisms in an energy-limited natural ecosystem are active with energy yields as low as -10 kJ/mol. A lower BEQ would mean a significantly expanded range of energetically viable subsurface habitat for life.

Hoehler, Tori M.↗

Virtex-II Pro PowerPC SEE Characterization Test Methods and Results

The Xilinx Vix-11 Pro is a platform FPGA that embeds multiple microprocessors within the fabric of an SRAM-based reprogrammable FPGA. The variety and quantity of resources provided by this family of devices make them very attractive for spaceflight applications. However,these devices will be susceptible to single event effects (SEE), which must be mitigated. Observations from prior testing of the Xilinx Virtex-II Pro suggest that the PowerPC core has significant vulnerability to SEES. However, these initial tests were not designed to exclusively target the functionality of the PowerPC, therefore making it difficult to distinguish processor upsets from fabric upsets. The main focus of this paper involves detailed SEE testing of the embedded PowerPC core. Due to the complexity of the PowerPC, various custom test applications, both static and dynamic, will be designed to isolate each Unit of the processor. Collective analysis of the test results will provide insight into the exact upset mechanism of the PowerPC. With this information, mitigations schemes can be developed and tested that address the specific susceptibilities of these devices. The test bed will be the Xilinx SEE Consortium Virtex-II Pro test board, which allows for configuration scrubbing, design triplication, and ease of data collection. Testing will be performed at the Indiana University Cyclotron Facility using protons of varying energy levels and fluencies. This paper will present the detailed test approach along with the results.

Petrick, David↗

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗

Iterative and Self-Consistent Estimation of Degradation and Soiling Loss in PV Systems - A Case Study

In many parts of the world, soiling is a significant loss mechanism for PV energy production. Methods for accurately quantifying historical and current soiling losses are needed. Furthermore, state-of-the-art methods to estimate degradation rates based on production data do not handle soiling in a satisfactory manner. In order to accurately estimate either of these quantities, it is in many cases helpful to consider their combined effect on PV system performance. In this work we make use of the Combined Degradation and Soiling (CODS) algorithm, which iteratively decomposes time series of daily normalized energy yield into four components: a soiling ratio, a degradation trend, seasonal variations, and noise. We demonstrate the use of the model on field performance data from a utility-scale power plant in a high-soiling environment in the Middle East. We apply the algorithm to the temperature-corrected performance index of the DC power on inverter level, quantifying how soiling varies over time and through the plant. The irradiation-weighted average soiling loss in this plant is 2.3 %, with a median soiling rate of -0.086 %/day. Between the inverters in the site in study, estimated degradation rates range between -0.86 %/year and -0.15 %/year, with a mean rate of -0.48 %/year.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Space shuttle propulsion parameter estimation using optimal estimation techniques

The first twelve system state variables are presented with the necessary mathematical developments for incorporating them into the filter/smoother algorithm. Other state variables, i.e., aerodynamic coefficients can be easily incorporated into the estimation algorithm, representing uncertain parameters, but for initial checkout purposes are treated as known quantities. An approach for incorporating the NASA propulsion predictive model results into the optimal estimation algorithm was identified. This approach utilizes numerical derivatives and nominal predictions within the algorithm with global iterations of the algorithm. The iterative process is terminated when the quality of the estimates provided no longer significantly improves.

Source record↗

Software for a GPS-Reflection Remote-Sensing System

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Lowe, Stephen↗

Analysis of Risks to Oxygen Systems from Particulate and Fiber Contaminants and Derivation of Cleanliness Requirements

It has been well documented in the literature that contamination within oxygen systems can create significant fire hazards. Cleanliness limits for nonvolatile residues, ranging from 10 to 500 mg/sq m, have been established for various industries and types of oxygen systems to reduce the risk of ignition of flammable organic films. Particulate cleanliness limits used for oxygen systems vary considerably. Maximum allowed particle size, quantity limits, and allocations for fibers or metallic particles are all variables seen in aerospace cleanliness limits. Particles are known to have the potential to ignite within oxygen systems and must be limited to prevent fires. Particulate contamination may also pose risks to the performance of oxygen systems that are unrelated to ignition hazards. An extensive literature search was performed to better understand the relative importance of particle ignition mechanisms versus other deleterious effects of particles on oxygen systems and to identify rationale for derivation of particulate cleanliness limits for specific systems. The identified risks of different types and sizes of particles and fibers were analyzed. This paper summarizes the risks identified and rationale that may be used to derive particulate cleanliness limits for specific oxygen systems.

Lowrey, Nikki M.↗

Invariant Imbedded T-Matrix Method for Axial Symmetric Hydrometeors with Extreme Aspect Ratios

The single-scattering properties (SSPs) of hydrometeors are the fundamental quantities for physics-based precipitation retrievals. Thus, efficient computation of their electromagnetic scattering is of great value. Whereas the semi-analytical T-Matrix methods are likely the most efficient for nonspherical hydrometeors with axial symmetry, they are not suitable for arbitrarily shaped hydrometeors absent of any significant symmetry, for which volume integral methods such as those based on Discrete Dipole Approximation (DDA) are required. Currently the two leading T-matrix methods are the Extended Boundary Condition Method (EBCM) and the Invariant Imbedding T-matrix Method incorporating Lorentz-Mie Separation of Variables (IITM+SOV). EBCM is known to outperform IITM+SOV for hydrometeors with modest aspect ratios. However, in cases when aspect ratios become extreme, such as needle-like particles with large height to diameter values, EBCM fails to converge. Such hydrometeors with extreme aspect ratios are known to be present in solid precipitation and their SSPs are required to model the radiative responses accurately. In these cases, IITM+SOV is shown to converge. An efficient, parallelized C++ implementation for both EBCM and IITM+SOV has been developed to conduct a performance comparison between EBCM, IITM+SOV, and DDSCAT (a popular implementation of DDA). We present the comparison results and discuss details. Our intent is to release the combined ECBM IITM+SOV software to the community under an open source license.

Pelissier, Craig↗

TPSAS-NF1676L-30451-DND

The fundamental laws of the physics of fluid flow in the continuum regime are embedded in a somewhat "simple" set of partial differential equations describing the transport of mass, momentum, energy, and/orentropy. These basic equations can be manipulated to construct other important physical quantities such as vorticity that help further elucidate flow physics. Additionally, these equations can be nondimensionalized to identify important nondimensional groups governing compressible, reacting fluid flows, most prominently Reynolds, Mach, Froude, Prandtl, Lewis, Schmidt, Damkohler, and Zeldovich numbers. In this lecture, we present these governing equations and discuss the significance of the different terms and nondimensional groups. Furthermore, since these equations cannot be solved directly on current supercomputers for turbulent flows at Reynolds numbers of engineering interest, a scale reduction by averaging or filtering is introduced, which leads to a "closure" problem. The closure is then provided by introducing some common models. The current introduction is by no means complete, but it and the references herein may serve as a good starting point for learning about the most common approaches to turbulent reacting flows.

Tomasz (Tom) G Drozda↗

Strictly Enforcing Invertibility and Conservation in CNN-Based Super Resolution for Scientific Datasets

Abstract Recently, deep convolutional neural networks (CNNs) have revolutionized image “super resolution” (SR), dramatically outperforming past methods for enhancing image resolution. They could be a boon for the many scientific fields that involve imaging or any regularly gridded datasets: satellite remote sensing, radar meteorology, medical imaging, numerical modeling, and so on. Unfortunately, while SR-CNNs produce visually compelling results, they do not necessarily conserve physical quantities between their low-resolution inputs and high-resolution outputs when applied to scientific datasets. Here, a method for “downsampling enforcement” in SR-CNNs is proposed. A differentiable operator is derived that, when applied as the final transfer function of a CNN, ensures the high-resolution outputs exactly reproduce the low-resolution inputs under 2D-average downsampling while improving performance of the SR schemes. The method is demonstrated across seven modern CNN-based SR schemes on several benchmark image datasets, and applications to weather radar, satellite imager, and climate model data are shown. The approach improves training time and performance while ensuring physical consistency between the super-resolved and low-resolution data. Significance Statement Recent advancements in using deep learning to increase the resolution of images have substantial potential across the many scientific fields that use images and image-like data. Most image super-resolution research has focused on the visual quality of outputs, however, and is not necessarily well suited for use with scientific data where known physics constraints may need to be enforced. Here, we introduce a method to modify existing deep neural network architectures so that they strictly conserve physical quantities in the input field when “super resolving” scientific data and find that the method can improve performance across a wide range of datasets and neural networks. Integration of known physics and adherence to established physical constraints into deep neural networks will be a critical step before their potential can be fully realized in the physical sciences.

54 ENVIRONMENTAL SCIENCES↗

Measurements of ion velocity distributions in a large scale laser-produced plasma

Laser-produced plasma velocity distributions are an important, but difficult quantity to measure. In this work, we present a noninvasive technique for measuring individual charge state velocity distributions of laser-produced plasmas using a high temporal and spectral resolution monochromator. The novel application of this technique is its ability to detect particles up to seven meters from their inception (significantly larger than most laboratory plasma astrophysics experiments, which take place at or below the millimeter scale). The design and assembly of this diagnostic is discussed in terms of maximizing the signal to noise ratio, maximizing the spatial and temporal resolution, and other potential use cases. The analysis and results of this diagnostic are demonstrated by directly measuring the time-of-flight velocity of all ion charge states in a laser produced carbon plasma.

47 OTHER INSTRUMENTATION↗

Region-Specific Merchant Hydrogen Market Assessment and Techno-Economic Assessment of Electrolytic Hydrogen Generation: Cooperative Research and Development Final Report, CRADA Number CRD-18-00751

Utilities need to recover value from baseload and some renewable assets even when the electricity is curtailed. The declining cost of renewables (particularly solar), the persistently low-cost of natural gas, and the declining electricity demand, have all worked to lower the price of electricity. Furthermore, the baseload assets have a high turndown cost, which is not reflected in the low market electricity prices. One option for utilizing the curtailed electricity is hydrogen generation. One important aspect of this project will be to provide a “go/no-go” recommendation on the economic feasibility of pursuing hydrogen generation vs. other markets that could offtake curtailed electricity or nuclear steam. This project will specifically assess the opportunities for hydrogen production and use in the service territories of Southern Company Services (SCS), Exelon SBC, and Xcel Energy. Each utility partner represents a different mix of generation fleets: Exelon has significant nuclear assets, Xcel is primarily renewables (wind) with some nuclear, and SCS represents both a renewables fleet and a heavily baseload fleet, which includes significant nuclear. The Contractors will conduct the study of hydrogen market opportunities by first considering the approximate electricity demand and price profiles for the year, and power generation capacity that can be used to produce hydrogen. Therefore, a profile for hydrogen generation will also be developed to better understand the quantity and timing of hydrogen production. Once the hydrogen production schedule is estimated, hydrogen storage requirements can be determined. This effort will provide sufficient information to make a go/no-go decision on moving ahead with a detailed regional case study for hydrogen production in any of the three utility areas.

08 HYDROGEN↗

Geodetic and geophysical results from Lageos

Seven years of laser tracking of the Lageos spacecraft have been used to derive geodetic quantities describing the earth and its rotational motion. The dynamical motions of the solid-earth on its axis have been derived continuously since launch and changes in the length-of-day show very high correlation with variations in the atmospheric zonal winds between 1000 and 50 mbars. A significant improvement in the determination of the product of the earth's mass and the gravitational constant has been made. The high accuracy of the orbit determination of Lageos over the 7 years since launch has permitted the identification of a small deceleration in the nodal precession of the orbit. This deceleration is being caused by a small reduction in the flattening of the earth arising from the rebound of the earth after the last ice age. Measurements of the distances between the tracking stations over several years are showing changes consistent with tectonic plate motion and with general ideas of vertical movements.

Smith, D. E.↗

Kuwait oil fires - Compositions of source smoke

While the Kuwait oil-fire smoke plumes manifested a pronounced impact on solar radiation in the Gulf region (such as visibility and surface temperatures), smoke plume concentrations of combustion-generated pollutants suggest that the overall chemical impact on the atmosphere of the smoke from these fires was probably much less than anticipated. Combustion in the Kuwaiti oil fires was surprisingly efficient, releasing on average more than 93 percent of the combusted hydrocarbon fuels as CO2. Correspondingly, combustion-produced quantities of carbon monoxide (CO) and carbonaceous particles were low, each about 2 percent by weight. The fraction of CH4 produced by the fires was also relatively low (about 0.2 percent), but source emissions of nonmethane hydrocarbons were high (about 2 percent). Processes other than combustion (e.g., volatilization) probably contributed significantly to the measured in-plume hydrocarbon concentrations. Sulfur emissions (particulate and gaseous) measured at the source fires were lower (about 0.5 percent) than predicted based on average sulfur contents in the crude. N2O emissions from the Kuwaiti oil fires were very low and often could not be distinguished from background concentrations.

Cofer, Wesley R., III↗