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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Gut anatomical properties and microbial functional assembly promote lignocellulose deconstruction and colony subsistence of a wood-feeding beetle

Beneficial microbial associations enhance the fitness of most living organisms, and wood-feeding insects offer some of the most striking examples of this. Odontotaenius disjunctus is a wood-feeding beetle that possesses a digestive tract with four main compartments, each of which contains well-differentiated microbial populations, suggesting that anatomical properties and separation of these compartments may enhance energy extraction from woody biomass. In this work, using integrated chemical analyses, we demonstrate that lignocellulose deconstruction and fermentation occur sequentially across compartments, and that selection for microbial groups and their metabolic pathways is facilitated by gut anatomical features. Metaproteogenomics showed that higher oxygen concentration in the midgut drives lignocellulose depolymerization, while a thicker gut wall in the anterior hindgut reduces oxygen diffusion and favours hydrogen accumulation, facilitating fermentation, homoacetogenesis and nitrogen fixation. We demonstrate that depolymerization continues in the posterior hindgut, and that the beetle excretes an energy- and nutrient-rich product on which its offspring subsist and develop. Our results show that the establishment of beneficial microbial partners within a host requires both the acquisition of the microorganisms and the formation of specific habitats within the host to promote key microbial metabolic functions. Together, gut anatomical properties and microbial functional assembly enable lignocellulose deconstruction and colony subsistence on an extremely nutrient-poor diet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Anomalously slow hot carrier cooling and insulator-to-metal transition in a photo-doped Mott insulator

Photo-doped Mott insulators can exhibit novel photocarrier transport and relaxation dynamics and non-equilibrium phases. However, time-resolved real-space imaging of these processes are still lacking. Here, we use scanning ultrafast electron microscopy (SUEM) to directly visualize the spatial-temporal evolution of photoexcited species in a spin-orbit assisted Mott insulator α-RuCl 3 . At low optical fluences, we observe extremely long hot photocarrier transport time over one nanosecond, almost an order of magnitude longer than any known values in conventional semiconductors. At higher optical fluences, we observe nonlinear features suggesting a photo-induced insulator-to-metal transition, which is unusual in a large-gap Mott insulator. Our results demonstrate the rich physics in a photo-doped Mott insulator that can be extracted from spatial-temporal imaging and showcase the capability of SUEM to sensitively probe photoexcitations in strongly correlated electron systems.

42 ENGINEERING↗
DOE OSTI2023

Front-End Engineering and Design: Project Tundra Carbon Capture System (Final Report)

As the next phase of Project Tundra, Minnkota Power Cooperative (MPC) completed a front-end engineering and design (FEED) study to install a post-combustion CO 2 capture system (CCS) at the MPC operated (Square Butte Electric Cooperative-owned) Milton R. Young Station (MRYS) Unit 2 (MRY2), a 477-MW power plant fueled by North Dakota lignite. The project team completed the FEED with Fluor’s Econamine FG Plus℠ (EFG+) technology and is taking the next steps leading up to start of construction. Team members included FEED technical lead Fluor Enterprises (Fluor); owner’s engineer and balance of plant (BOP) engineer Burns & McDonnell (BMcD); leading carbon capture consultants (David Greeson Consulting, Hunt International Energy Services); environmental consultants (AECOM, Agora Environmental), other BOP engineering consultants (Golder Associates, Nels); cost-share funding agency, the North Dakota Industrial Commission (NDIC); and the Energy & Environmental Research Center (EERC). Project Tundra’s goal is to implement carbon capture, utilization, and storage (CCUS) in North Dakota, while preserving the use of lignite. Future options could lead to revitalizing legacy oil fields and creating a new CO 2 enhanced oil recovery (EOR) industry. The topic of this report is the FEED study for the carbon dioxide capture portion of Project Tundra. Building on the findings of a pre-FEED study for MRY2, the key deliverables contained in this FEED study are: a) design, costing, and performance data needed to commence project financing activities; b) engineering and material balances required to file for all project permits; and c) a final project schedule. Based on the results of the previous pre-FEED study, MPC and its team evaluated two options to provide the large amount of steam needed to operate the CCS: 1) installation of new natural gas package boilers and a new pipeline to supply natural gas to the facility and 2) extraction of steam from the existing MRYS steam turbine generator. The FEED study was performed using the package boilers option, as it was deemed to have the lowest technical risk, overall cost, and cost uncertainty. A key feature of the design, however, was the mixing the natural gas boilers’ flue gas with the MRY2 flue gas. This increased the size of the CCS system. This design also enabled the tie-in of Unit 1 flue gas for times when Unit 2 is offline. The CCS was designed to capture a combined 12,978 short tons per day (STPD) of CO 2 from the flue gases produced by the existing MRY Unit 2 along with flue gas produced by the new boiler package within the CCS. The 12,978 STPD CO 2 capture is achieved by normally processing 100% of the total available MRY Unit 2 flue gas (considering full load operation) and 100% of the boiler package flue gas, then removing 90% of the CO 2 available from the processed flue gas streams.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Double-Side Cooled 1.2kV, 300A SiC MOSFET Phase-leg Modules for 200 kW, > 100 kW/L Traction Inverters

The packaging of a double-side cooled 1.2 kV, 149 A SiC phase-leg modules has been reported in recent years for making 100 kW, 100 kW/L traction inverters. Each phase-leg module consists of two SiC MOSFETs, one per switch position. Six of the phase-leg modules are assembled into a segmented inverter configuration to meet the power and power density requirement. In this work, the layout of the phase-leg module was redesigned to include four of the SiC MOSFETs, two per switch position, with the aim of doubling the power to 200 kW and increasing the power density beyond 100 kW/L, but with only a 10.25% footprint increase. Key features of the packaging technology developed in the previous work were implemented in the current work, which include silver sintering for chip bonding and porous silver inter-posts for bonding device source pads to substrate. Parasitic extraction simulation showed that the four-chip module has a low parasitic inductance of 4.7 nH, like the two-chip module. Static characterization of the four-chip prototypes showed a low average on-resistance of 9 mΩ and a low average leakage current of 5 nA at Vds of 1.2 kV.

Zhang, Zichen↗
DOE OSTI2025

MARIE: A Python-Based Framework for Comprehensive Fuel Recycling Modeling

One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery of valuable materials from UNF assemblies has been considered as part of an overall strategy for minimization of the volume of reactor-based wastes to be managed, the deployment of commercial-scale reprocessing facilities presents an enormous economic challenge. The MARIE software package has been developed as a means of confronting this challenge. Representing components of a generic fuel reprocessing operation as individual physical processes, MARIE is designed as a modular framework intended to allow for analysis and cost-optimization for a hypothetical reprocessing facility while realistically accounting for the physical characteristics of the used fuel source term, such as decay heat, activity, and radiation dose (informing corresponding shielding requirements). Capabilities supported by MARIE include head-end operations such as fuel shearing, voloxidation, and dissolution; generic solvent extraction operations informed by available open-literature data; a suite of unit operations intended to represent electrochemical processing of used fuel assemblies (i.e., oxide reduction, electrorefining, and electrowinning); and finally, accounting for both costs and physical features of discharged waste streams, which can be used to inform follow-on analyses such as the feasibility of deep-borehole disposal of HLW. This paper presents an overview of the MARIE software capabilities, including how individual unit operations are implemented to enable a larger-scale optimization of a hypothetical reprocessing operation on aspects such as cost and recovery of valuable materials.

Skutnik, Steve [ORNL] (ORCID:000000016441135X)↗
DOE OSTI2023

Model selection and signal extraction using Gaussian Process regression

We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2012

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗
DOE OSTI2019

Factors that impact the outcomes in testicular germ cell tumors in low–middle-income countries

Germ cell tumors (GCTs) are one of the most common tumors in adolescents and young adults. There is paucity of data on GCT from low–middle-income countries (LMIC). The present study was conducted to assess the demographic features, clinical manifestations, pathology, and outcomes of GCT patients treated at our center. Patients with testicular GCT above the age of 18 years, treated at our center from 2001 to 2015 were included in the study. Data were extracted retrospectively from the case records. Event-free survival (EFS) and overall survival (OS) were calculated using the Kaplan–Meier method and the variables were compared using the log-rank test. The study included 421 patients among whom 128 (30%) had a histological diagnosis of seminoma and 293 (70%) had non-seminomatous germ cell tumor (NSGCT). Metastatic disease at presentation was observed in 83/128 (65%) with seminoma and 254/293 (87%) with NSGCT. According to the International Germ Cell Cancer Collaborative Group (IGCCCG) risk stratification for metastatic disease, good- and intermediate-risk seminoma were observed in 55/83 (66%) and 28/83 (34%) patients, respectively, and good-, intermediate-, and poor-risk NSGCT were observed in 82/254 (32%), 76/254 (30%), and 96/254 (38%) patients, respectively. The median follow-up was 32.3 months (range 0.03–200 months). The 3-year OS for the entire cohort was 80.3%. The 3-year OS for seminoma was 91.4%, and for NSGCT was 75.3%. Factors significantly associated with inferior EFS and OS on multivariate analysis included poor performance status, scrotal orchidectomy, carboplatin-based regimen, NSGCT histology, and treatment default. Patients with testicular GCT in India present in an advanced stage and higher IGCCCG risk compared to Western data. Factors unique to LMIC like treatment default, bulky disease, dose compromise, and scrotal orchidectomy have a negative impact on the outcome.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗
DOE OSTI2022

Spin-exchange Hamiltonian and topological degeneracies in elemental gadolinium

In this report we present a comprehensive study of the magnetic exchange Hamiltonian of elemental gadolinium. We use neutron scattering to measure the magnon spectrum over the entire Brillouin zone and fit the excitations to a spin wave model to extract the first 26 nearest-neighbor magnetic exchange interactions with rigorously defined uncertainty. We find these exchange interactions to follow RKKY behavior, oscillating from ferromagnetic to antiferromagnetic as a function of distance. Finally, we discuss the topological features and degeneracies in Gd, and HCP ferromagnets in general. We show theoretically how, with asymmetric exchange, topological properties could be tuned with a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Coherent elastic neutrino-nucleus scattering with directional detectors

We study the sensitivity of detectors with directional sensitivity to coherent elastic neutrino-nucleus scattering (CE$\textit{ν}$NS), and how these detectors complement measurements of the nuclear recoil energy. In this work we consider stopped pion and reactor neutrino sources, and use gaseous helium and fluorine as examples of detector material. We generate Standard Model predictions, and compare to scenarios that include new, light vector or scalar mediators. We show that directional detectors can provide valuable additional information in discerning new physics, and we identify prominent spectral features in both the angular and the recoil energy spectrum for light mediators, even for nuclear recoil energy thresholds as high as ~50 keV. Combined with energy and timing information, directional information can play an important role in extracting new physics from CE$\textit{ν}$NS experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Identification of Dynamic Force Coefficients for an Additively Manufactured Hermetic Squeeze Film Bearing Support Damper Utilizing a Pass-Through Channel

Abstract The following paper presents breakthrough experimental results for a new hermetic squeeze film damper (HSFD) concept that is integrally designed within an externally pressurized tilting-pad radial gas bearing support. The flexibly damped gas bearing module was designed for a 7.2″ (183 mm) diameter shaft and fabricated using direct metal laser melting (DMLM); also known as additive manufacturing. The bearing and HSFD were sized based on ongoing studies for oil-free supercritical carbon dioxide (sCO2) power turbines in the 8.5 MW–10 MW power range. The development of the new damper concept was motivated by past dynamic testing on HSFD, which generated frequency-dependent stiffness and damping force coefficients. In efforts to eliminate the frequency dependency, a new HSFD architecture was conceived that adds accumulator volumes and a pass-through channel to previously conceived HSFD flow network designs. The other motivation for the work is the need to develop a cost-effective and reliable oil-free bearing technology that is scalable to large power turbomachinery applications. There were several objectives for the following work. The first objective was to successfully design and fabricate a single piece bearing-damper using additive manufacturing, while dimensionally controlling critical design features. The paper discusses the manufacturing steps and shows cut-ups that reveal adequate clearance control capability with internal damper clearances. The second objective was to perform experimental testing with the new HSFD design in efforts to extract stiffness and damping coefficients for excitation frequencies within 20–160 Hz and peak vibration amplitudes between 0.25 mils (6.35 microns) to 1 mil (25.4 microns). The test results for a single HSFD bearing module indicated that the design modifications to the HSFD architecture were successful in eliminating nearly all the frequency dependencies for the stiffness force coefficient. The dynamic tests yielded a stiffness coefficient that varied between 112 klb/in. (19.6 MN/m) and 96 klb/in. (16.8 MN/m). The damping force coefficient however, exhibited relatively more variation with frequency with values residing between 175 lb-s/in. (31 kN-s/m) to 214 lb-s/in. (37 kN-s/m). Finally, the paper advances a three-dimensional fluid-structure interaction (FSI) model using transient finite element analysis (FEA) coupled to a computational fluid dynamics (CFD) model. The FSI analysis performed between 20 Hz and 80 Hz was used to predict the stiffness and damping of the HSFD using a quarter-section model of the damper. The FSI analysis was able to support test results by showing only a 6–7.4% change in the magnitude of force coefficients. Stiffness predictions agree reasonably well with experiments whereas damping is underpredicted.

Engineering↗
NASA NTRS1973

Plagioclase mineralogy of olivine alkaline basalt

A geological and mineralogical study of the Potrillo volcanics is reported. The investigation consisted first of field mapping to establish and identify the different rock types and volcanic features in order to determine the geological history. Next, samples were collected and analyzed petrographically to determine suitable rocks from the various stratigraphic units for study of plagioclase. Samples selected for further study were crushed and the plagioclase extracted for the determination of composition and structural state. These results were then related to the petrology and crystallization of the basalt.

Hoffer, J. M.↗
NASA NTRS1988

Particulate emissions from a mid-latitude prescribed chaparral fire

Particulate emission from a 400-acre prescribed chaparral fire in the San Dimas Experimental Forest was investigated by collecting smoke aerosol on Teflon and glass-fiber filters from a helicopter, and using SEM and EDAX to study the features of the particles. Aerosol particles ranged in size from about 0.1 to 100 microns, with carbon, oxygen, magnesium, aluminum, silicon, calcium, and iron as the primary elements. The results of ion chromatographic analysis of aerosol-particle extracts (in water-methanol) revealed the presence of significant levels of NO2(-), NO3(-), SO4(2-), Cl(-), PO4(3-), C2O4(2-), Na(+), NH4(+), and K(+). The soluble ionic portion of the aerosol was estimated to be about 2 percent by weight.

Cofer, Wesley R., III↗
NASA NTRS2000

Magnetic Flux Compression Concept for Aerospace Propulsion and Power

The objective of this research is to investigate system level performance and design issues associated with magnetic flux compression devices for aerospace power generation and propulsion. The proposed concept incorporates the principles of magnetic flux compression for direct conversion of nuclear/chemical detonation energy into electrical power. Specifically a magnetic field is compressed between an expanding detonation driven diamagnetic plasma and a stator structure formed from a high temperature superconductor (HTSC). The expanding plasma cloud is entirely confined by the compressed magnetic field at the expense of internal kinetic energy. Electrical power is inductively extracted, and the detonation products are collimated and expelled through a magnetic nozzle. The long-term development of this highly integrated generator/propulsion system opens up revolutionary NASA Mission scenarios for future interplanetary and interstellar spacecraft. The unique features of this concept with respect to future space travel opportunities are as follows: ability to implement high energy density chemical detonations or ICF microfusion bursts as the impulsive diamagnetic plasma source; high power density system characteristics constrain the size, weight, and cost of the vehicle architecture; provides inductive storage pulse power with a very short pulse rise time; multimegajoule energy bursts/terawatt power bursts; compact pulse power driver for low-impedance dense plasma devices; utilization of low cost HTSC material and casting technology to increase magnetic flux conservation and inductive energy storage; improvement in chemical/nuclear-to-electric energy conversion efficiency and the ability to generate significant levels of thrust with very high specific impulse; potential for developing a small, lightweight, low cost, self-excited integrated propulsion and power system suitable for space stations, planetary bases, and interplanetary and interstellar space travel; potential for attaining specific impulses approaching 10 (exp 6) seconds, which would enable missions to the outer planets within ten years and missions at interstellar distances within fifty years.

Litchford, Ron J.↗
NASA NTRS2004

Topographic Evidence for Eruptive Style Changes and Magma Evolution of Small Plains-style Volcanoes on Earth and Mars

Topographic profiles and surface characteristics of small (5 - 25 km diameter) plains-style shield volcanoes on the eastern Snake River Plain (ESRP) provide a method to evaluate eruptive processes and magmatic evolution on Martian volcanic plains. The ESRP is an ideal place to observe Mars-like volcanic features where hundreds of small monogenetic basaltic shields dominate the volcanic-sedimentary depositional sequence, and numerous planetary analogues are evident: coalescent mafic shields, hydromagmatic explosive eruptions, the interaction of lava flows with surficial water and glacial ice, and abundant eolian sand and loess. Single flows cannot be correlated over great distances, and are spatially restricted. These relations are useful for planetary exploration when inferring volcanic evolutionary patterns in lava plains represented by numerous eruptive vents. High spatial resolution imagery and digital topographic data for Mars from MOC, MOLA, and THEMIS is allowing for improvements in the level of detail of stratigraphic mapping of fields of small (< 25 km in diameter) volcanoes as well as studies of the morphological characteristics of individual volcanoes. In order to compare Mars and Earth volcanic features, elevation data from U.S.G.S. 10-meter digital elevation models (DEMs) and high-precision GPS field measurements are used in this study to generate approx. 20m spacing topographic profiles from which slope and surface morphology can be extracted. Average ESRP flank and crater slopes are calculated using 100 - 200 m spacing for optimum comparison to MOLA data, and to reduce the effects of surface irregularities.

Hughes, S. S.↗
NASA NTRS1997

Wavelet Methods Developed to Detect and Control Compressor Stall

A "wavelet" is, by definition, an amplitude-varying, short waveform with a finite bandwidth (e.g., that shown in the first two graphs). Naturally, wavelets are more effective than the sinusoids of Fourier analysis for matching and reconstructing signal features. In wavelet transformation and inversion, all transient or periodic data features (as in compressor-inlet pressures) can be detected and reconstructed by stretching or contracting a single wavelet to generate the matching building blocks. Consequently, wavelet analysis provides many flexible and effective ways to reduce noise and extract signals which surpass classical techniques - making it very attractive for data analysis, modeling, and active control of stall and surge in high-speed turbojet compressors. Therefore, fast and practical wavelet methods are being developed in-house at the NASA Lewis Research Center to assist in these tasks. This includes establishing user-friendly links between some fundamental wavelet analysis ideas and the classical theories (or practices) of system identification, data analysis, and processing.

Le, Dzu K.↗