Composite Materials Stiffness Determination and Defects Characterization Using Enhanced Leaky Lamb Wave Dispersion Data Acquisition
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Leaky Lamb Waves (LLW) NDE Composites Stiffness Co↗
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Composite Materials Stiffness Determination and Defects Characterization Using Enhanced Leaky Lamb Wave Dispersion Data Aquisition Method
The leaky Lamb waves (LLW) technique is approaching a maturity level that is making it attractive quantitative NDE tool for composites and bonded joints.
NDE Leaky Lamb Waves (LLW) composite materials Sti↗
Stochastic Characterization of Flutter using Historical Wind Tunnel Data
Methods for predicting the onset of flutter during an experiment are traditionally applied treating the data as deterministic values. Uncertainty and variation in the data is often glossed over by using best-fit curves to represent the information. This paper applies stochastic treatments to wind tunnel data obtained for the Piezoelectric Aeroelastic Response Tailoring Investigation model. These methods include modal amplitude tracking, modal frequency tracking and several applications of the flutter margin method. The flutter margin method was developed by Zimmerman and Weissenburger, and extended by Poirel, Dunn and Porter to incorporate uncertainty. Much of the current work follows the future work recommendations of Poirel, Dunn and Porter.
Heeg, Jennifer↗
RESOLVE for Lunar Polar Ice/Volatile Characterization Mission
Ever since data from the neutron spectrometer instrument on the Lunar Prospector mission indicated the possibility of significant concentrations of hydrogen at the lunar poles, speculation on the form and concentration of the hydrogen has been debated. The recent impact of the Lunar Crater Observation and Sensing Satellite (LCROSS) along with thermal, topographic, neutron spectrometry, and radar frequency data obtained from the Lunar Reconnaissance Orbiter (LRO) have provided more information suggesting significant amounts of water/ice and other volatiles may be available in the top 1 to 2 meters of regolith at the lunar poles. The next step in understanding what resources are available at the lunar poles is to perform a mission to obtain ground truth. data. To meet this need, the US National Aeronautics and Space Administration (NASA) along with the Canadian Space Agency (CSA) have been working on a prototype payload known as the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction experiment, or RESOLVE.
Sanders, G. B.↗
Measurement of Error Vector Magnitude (EVM) to Characterize the Impairment of the Tracking and Data Relay Satellite (TDRS) Channel
A digital signal is transmitted via a carrier wave, it demodulates at a receiver, and locates at an ideal constellation point. However, noise distortion, carrier leakage, and phase noise can force a signal to divert from its ideal position to a new position. Consequently, the performance of the signal is decreased. Bit Error Rate (BER) and Error Vector Magnitude (EVM) measurement techniques are used to enable the analysis and assessment of the extent to which the performance of a signal has been decreased. In this paper, we present the EVM measurement technique as a figure of merit to analyze and evaluate the performance of a User Services Subsystem Component Replacement (USSCR) modem. Also, we demonstrate the use of the EVM measurement technique in a Tracking and Data Relay Satellite (TDRS) system to measure and evaluate channel impairment between a satellite (transmitter) and the ground terminal (receiver) at the White Sands Complex.
Spacecraft RF Communications↗
MAARSL: automated mapping and characterization of recurring slope linea from HiRISE data
UNKNOWN
Stillman, David E.↗
Characterizing Walk Trips in communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources
Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over. The NHTS, in conjunction with the Census Bureau s American Community Survey, street density measures using Census Bureau TIGER, WalkScore , Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.
NHTS↗
Deep Modeling: Circuit Characterization Using Theory Based Models in a Data Driven Framework
Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity can degrade system performance. Furthermore, in all but the simplest systems, it is impossible to directly measure the intermediate outputs of all sub-circuits. The result is that circuit designers are unable to accurately evaluate the non-idealities of computational circuits in-situ and are therefore unable to fully utilize measurement results to improve future designs. In this paper we present a technique to use deep learning frameworks to model physical systems. Recently developed libraries like TensorFlow make it possible to use back propagation to learn parameters in the context of modeling circuit behavior. Offsets and scaling errors can be discovered even for sub-circuits that are deeply embedded in a computational system and not directly observable. The learned parameters can be used to refine simulation methods or to identify appropriate compensation strategies. We demonstrate the framework using a mixed-signal convolution operator as an example circuit.
Bolme, David S↗
Impact of light output on the timing resolution of organic glass scintillator bars in a dual-ended readout configuration
The effectiveness of detector system modeling and validation depends on the quality of characterization performed on the system. For nuclear nonproliferation applications, which require detectors to address complex and variable field conditions, access to accurate system models is essential. This study presents the timing characterization of organic glass scintillator bars used in an imaging system developed at the University of Michigan. 137 Cs and 60 Co gamma-ray sources were used to determine the coincidence time resolution as a function of measured light output for two Compton scatter events between two organic glass scintillator bars. Timing resolution for two events, each with light output ranging from 100 to 1100 keVee were characterized. The resulting data were fit to a parametric function that was validated to agree with experimental results within ±25 ps. Simulations were performed to establish appropriate calibration points for each organic scintillator, thereby ensuring accurate calibration of light output values during analysis. This work successfully characterized the light output dependence of the coincidence timing resolution of a pair of organic glass detectors for use in an imaging system. Depending on the amount of scintillation light output from the events, the full width at half maximum of the measured coincidence time resolution ranged from 653.2 ± 16.1 ps for low light yields, 100 keVee, to 121.0 ± 8.4 ps for higher yields at 1100 keVee. The insights obtained from the timing resolution behavior will allow for accurate simulation capabilities in future security and verification efforts using scatter-based imaging systems.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Study and review of permanent magnets for electric vehicle propulsion motors
A study of permanent magnets (PM) was performed in support of the DOE/NASA electric and hybrid vehicle program. PM requirements for electric propulsion motors are analyzed, design principles and relevant properties of magnets are discussed. Available PM types are reviewed. For the needed high-grade magnets, design data, commercial varieties and sources are tabulated, based on a survey of vendors. Economic factors such as raw material availability, production capability and cost are analyzed, especially for cobalt and the rare earths. Extruded Mn-Al-C magnets from Japan were experimentally characterized. Dynamic magnetic data for the range -50 deg to +150 deg C and some mechanical properties are reported. The state of development of the important PM material families is reviewed. Feasible improvements or new developments of magnets for electric vehicle motors are identified.
Strnat, K. J.↗
Hydrothermal synthesis of lanthanide rhenium oxides: Structures and magnetism of Ln 2 Re 2 O 7 (OH) (Ln = Pr, Nd) and Ln 4 Re 2 O 11 (Ln = Eu, Tb)
The reactions of Ln 2 O 3 (Ln =LaLu) with ReO 2 were examined in high temperature hydrothermal water (650 °C). In all cases the rhenium oxide was added in a three-fold excess. No external mineralizer was needed and the rhenate itself acted as a sufficient mineralizer to form high quality single crystals of several crystalline products. These form in good yield with compositions varying as a function of the size of the rare earth ion. The largest sesquioxide, La 2 O 3 , forms the well-known La 4 Re 6 O 19 phase, but when Ln = Nd or Pr, a new product, Ln 2 Re 2 O 7 (OH), is isolated. Reactions with Ln = SmTb form Ln 4 Re 2 O 11 , and those with DyLu form Ln 2 ReO 5 . The new Ln 2 Re 2 O 7 (OH) series was characterized as a new structure type by single crystal X-ray diffraction. This structure features a tetrameric Re 4 O 16 cluster embedded in a lanthanide oxide framework. Additional detailed structural data is also provided for Tb 4 Re 2 O 11 and Eu 4 Re 2 O 11 , which were not previously reported for the Ln 4 Re 2 O 11 family. In Ln 2 Re 2 O 7 (OH), no direct ReRe bond (ReRe = 2.60 Å) is observed while Ln 4 Re 2 O 11 appears to possess a rhenium-rhenium double bond with a ReRe distance of 2.42 Å. Single crystal Raman data supports both of these characterizations. Magnetic data is reported for Ln 2 Re 2 O 7 (OH) and Tb 4 Re 2 O 11 , and their behavior appears to be dominated by the f-element magnetic moments. At low temperatures Tb 4 Re 2 O 11 displays possible canted antiferromagnetic coupling.
36 MATERIALS SCIENCE↗
An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Arnold, Steven M.↗
An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Arnold, Steven M.↗
Development of a strain/temperature gauge and attachment system for use on carbon composites at elevated temperature
The difficulties encountered when instrumenting solid rocket motors for acquiring strain data are reviewed, emphasizing the strong temperature dependence due to apparent strain effects. The development of a strain/temperature gage to overcome some of these problems is discussed. This gage is designed to produce low apparent strain when attached to a carbon-carbon substrate. Characterization and performance data for gages attached with ceramic cement to carbon-carbon tensile coupons are presented, and the effect of a flame-sprayed installation process is discussed.
Lanius, S. J.↗
An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling
Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Arnold, Steven M.↗
Subtask 1.3 – Integrated Carbon Capture and Storage for North Dakota Ethanol Production
The Energy & Environmental Research Center (EERC), in partnership with Red Trail Energy, LLC (RTE), a North Dakota ethanol producer; the North Dakota Industrial Commission (NDIC) Renewable Energy Program (REP); and the U.S. Department of Energy (DOE), conducted a feasibility and implementation study for a commercial carbon capture and storage (CCS) effort. This subtask provided technical support and developed recommended practices of how small-scale industrial CO2 emitters (<1,000,000 tonnes of CO2 emitted annually) may economically deploy CCS. The 64-million-gallon dry mill RTE ethanol facility, emitting an average 180,000 tonnes of CO2 annually, was the subject of the case study. The positive outcome of this research, which shows technical and economic potential for ethanol–CCS in North Dakota, has resulted in RTE acquiring an approved Permit to Drill on December 2, 2019, for a stratigraphic test well in early 2020, a necessary step toward a North Dakota CO2 Storage Facility Permit (SFP) for the RTE CCS effort. Outcomes include 1) validating the Broom Creek Formation as a regional target for CCS, 2) determining the full carbon life cycle of an industrial fuel production facility with CCS, 3) developing a field implementation plan (FIP) for small-scale CCS, and 4) determining the validity and pathway for using CCS to meet low-carbon fuel (LCF) standards. The technical team included the EERC, RTE, Trimeric Corporation, Schlumberger Carbon Services, and Computer Modelling Group (CMG). Findings from activities conducted November 2016 – May 2020 are summarized as follows. Several key steps have been accomplished toward validating the Broom Creek Formation as a CO2 injection and storage target at the RTE CCS site, including verification of the presence and structure of sandstone layers that may comprise the potential CO2 storage reservoir and the several thousand feet of overlying confining zone. Work included site characterization using existing data, interpretation of seismic data within the study area, and geologic modeling simulation of CO2 injection. Interpreted results estimate 3000 feet of confining zone between the Broom Creek Formation (storage target) and the lowermost underground source of drinking water (e.g., the Fox Hills Formation). The thickness of the Broom Creek injection target varies 230–420 ft within the survey area. Results were used to inform the location of a stratigraphic test well and associated characterization test program. No impediments were identified within the targeted CO2 storage complex that would prevent the project from moving forward. A stratigraphic test well is the next step to validate these results and to acquire remaining data necessary to develop a North Dakota CO2 SFP application. The EERC generated full carbon life cycle estimates for CCS integration with the RTE ethanol facility. Results indicated that an average 40% reduction in CO2 emissions is possible through CCS implementation. Approximately half of the carbon in the overall life cycle for a dry mill ethanol plant is generated through the fermentation process and emitted to the atmosphere; this is the CO2 stream targeted for CCS. The remaining carbon is attributed to corn feedstock farming (diesel, fertilizer), energy for fuel processing (natural gas, electricity), and transportation (diesel) of the fuel product. Life cycle carbon estimates are also affected by the anticipated energy consumption of a potential capture facility, which depend on the type of CO2 product generated. For example, a 30%–40% net CO2 emission reduction is estimated if a liquefied CO2 facility were incorporated compared to a 40%–50% net CO2 reduction if a supercritical “injection-grade” CO2 product is generated; i.e., more energy is required to further refine the CO2 stream, affecting the full carbon life cycle estimates. A CCS FIP was developed and initiated at the RTE CCS site, resulting in the development of several guidance documents: a CO2 Capture Process Design Package, a North Dakota CO2 geologic Storage Permits Template, and a Public Outreach Package for CCS in North Dakota. General FIP components include CO2 capture system, pipeline and well designs; monitoring, verification, and accounting (MVA) plans; geologic characterization and testing programs; and permitting and outreach plans. Vendor bids were also acquired for the CO2 liquefaction facility. Near-surface characterization (groundwater and soil gas sampling) and geologic characterization (seismic survey) were initiated to inform development of a UIC Class VI-compliant MVA plan compliant with a North Dakota CO2 SFP. Designs (well and geologic testing) were completed for a stratigraphic test well compliant with a North Dakota CO2 SFP. In addition, the outreach plan was executed, including community open houses, meetings with city/county/state officials, and development of public materials. Although other entities continued to mature incentive programs in 2019–2020, California and the Internal Revenue Service (IRS) currently provide the most advanced economic opportunities for CCS integrated with fuel production. The California Low-Carbon Fuel Standard (LCFS) adopted a CCS Protocol in January 2019, allowing submittal of a design-based pathway (DBP) application for an approved temporary (not certified) carbon intensity value for a fully engineered facility. An ethanol–CCS DBP application to the California LCFS Program (officially approved February 28, 2020) was developed to show that the RTE CCS effort meets LCFS requirements. The approved DBP provides confidence to advance the project and supports potential investments. Other entities continue to mature incentive programs. The IRS issued guidance in February 2020 that addresses the definition of beginning of construction and revenue procedure on partnerships for the Enhancement of Carbon Dioxide Sequestration Credit (a.k.a. Section 45Q) CCS tax credit program; the IRS anticipates issuing further guidance on issues such as secure geologic storage, utilization qualifications, and recapture of claimed credits. Maturing incentive programs coupled with workable permitting regulations provide confidence to advance CCS projects in North Dakota and support financial investment to proceed with designing, constructing, and implementing CCS projects at small-scale fuel production facilities. The largest hurdles for CCS implementation at small-scale industrial systems are often business/economic-related (i.e., not technical). Market uncertainty already exists for agriculture-based alternative fuels such as corn ethanol, for which production has increased by ~33%, and prices have correspondingly lowered since 2015. Passing the Section 45Q tax credit program improves economic feasibility for CCS but may require external investors for a small business to achieve maximum benefits. Public–private partnerships with NDIC and DOE have resulted in foundational technical and regulatory knowledge, growing stakeholder confidence, and a pathway to implementation that enables similar industrial CCS projects in the region to advance. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by NDIC and RTE. The authors would also like to thank CMG, ESRI, IHS, Neuralog, and Schlumberger for allowing the use of their software packages in support of this work.
42 ENGINEERING↗
GeoLab's First Field Trials, 2010 Desert RATS: Evaluating Tools for Early Sample Characterization
As part of an accelerated prototyping project to support science operations tests for future exploration missions, we designed and built a geological laboratory, GeoLab, that was integrated into NASA's first generation Habitat Demonstration Unit-1/Pressurized Excursion Module (HDU1-PEM). GeoLab includes a pressurized glovebox for transferring and handling samples collected on geological traverses, and a suite of instruments for collecting preliminary data to help characterize those samples. The GeoLab and the HDU1-PEM were tested for the first time as part of the 2010 Desert Research and Technology Studies (DRATS), NASA's analog field exercise for testing mission technologies. The HDU1- PEM and GeoLab participated in two weeks of joint operations in northern Arizona with two crewed rovers and the DRATS science team.
Evans, Cindy A.↗
Atmo-ecometabolomics: A novel atmospheric particle chemical characterization methodology for ecological research
Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biologicalactivity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles.We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmoecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry.
Rivas-Ubach, Albert (ORCID:0000000312937127)↗