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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Spectral Characterization of Modern Spacecraft Materials

One of the observational parameters of interest in ground-based optical measurements is ascertaining material properties using broadband filter photometry and spectroscopy for orbiting targets. Broadband photometry can provide reflectance measurements that can aid in color-color indices and assess if objects can be classified into families or taxonomies. However, these reflectance properties can vary due to aspect angle, phase angle, and general degradation of the target’s exterior material. Spectral characterization can aid in material characterization utilizing known absorption bands and spectra signatures, but these signatures are affected by the same conditions described for remote observations. When utilizing ground-based measurements, it is well understood that material characterization is subject to variability due to space weathering and/or other external events (i.e., collision or explosion). The focus of this study is on space weathering effects on spacecraft materials in low Earth orbit. To better assess how materials are affected by the harsh space environment, specifically modern materials, a collection of materials was analyzed in both its pristine condition and after electron bombardment. This sample collection is part of an upcoming mission with the Materials International Space Station Experiment Flight Facility (MISSE-FF) that will be launched in 2022. These laboratory analyses on the samples will provide a ground truth to compare with the in-situ collected data. The data will also be stored in the NASA Johnson Space Center’s Spacecraft Materials Spectral Database that is available to U. S. citizens and maintained by the Orbital Debris Program Office. The following paper provides an overview of the materials investigated, laboratory and database overview, and spectral results for both pristine and post-electron exposed conditions. The spectral signature data highlights which materials are stable, or remain relatively unchanged, and which materials vary significantly due to exposure and material configuration (variations due to rotation of the sample on a flat surface). Initial results on changes in spectral directional reflectance of the materials as a function of incident illumination direction are also presented. This data also will benefit the space situational awareness community with spectral characterization of novel materials that can support their respective optical measurements focused on material identification.

Heather M Cowardin↗
NASA NTRSDate not supplied

Description of Cloud Characterization and Icing Test for a 3D Heated Test Article at the NASA Icing Research Tunnel

This paper describes the cloud characterization and icing tests conducted with a 3D heated test article in Winter/Spring 2022 at the NASA Icing Research Tunnel. The intent is to present analyzed results from these recently conducted tests in a future technical paper. The test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and constructed to study the physics of supercooled water icing and ice crystal icing. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, a scale to measure ice mass, and other instruments will aid in characterizing the icing behavior. The aim of these tests is to generate ice accretions on the SIDRM test article under well-characterized conditions. To that end, a suite of instruments was utilized to characterize the ice crystal clouds at the test section in a separate test series. The icing measurements collected during the SIDRM model tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assess the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.

Ice crystal icing↗
NASA NTRSDate not supplied

Description of Cloud Characterization and Icing Tests for a 3D Heated Test Article at the NASA Icing Research Tunnel

This paper describes the cloud characterization and icing tests conducted with a 3D heated test article in Winter/Spring 2022 at the NASA Icing Research Tunnel. The intent is to present analyzed results from these recently conducted tests in a future technical paper. The test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and constructed to study the physics of supercooled water icing and ice crystal icing. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, a scale to measure ice mass, and other instruments will aid in characterizing the icing behavior. The aim of these tests is to generate ice accretions on the SIDRM test article under well-characterized conditions. To that end, a suite of instruments was utilized to characterize the ice crystal clouds at the test section in a separate test series. The icing measurements collected during the SIDRM model tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assess the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.

Ice crystal icing, heated test article, engine ici↗
NASA NTRSDate not supplied

Spectral Characterization of Modern Spacecraft Materials

One of the observational parameters of interest in ground-based optical measurements is ascertaining material properties using broadband filter photometry and spectroscopy for orbiting targets. Broadband photometry can provide reflectance measurements that can aid in producing color-color indices and assess if objects can be classified into families or taxonomies. However, these reflectance properties can vary due to aspect angle, phase angle, and general degradation of the target’s exterior material. Spectral characterization can aid in material characterization utilizing known absorption bands and spectral signatures, but these signatures are affected by the same conditions described for remote observations.When utilizing ground-based measurements, it is well understood that material characterization is subject to variability due to space weathering and/or other external events (i.e., collision or explosion). The focus of this study is on space weathering effects on spacecraft materials in low Earth orbit. To better assess how materials are affected by the harsh space environment, specifically modern materials, a collection of materials were analyzed in both their pristine condition and after electron bombardment. This sample collection is part of an upcoming mission with the Materials International Space Station Experiment Flight Facility (MISSE-FF) that will be launched in 2022. These laboratory analyses on the samples will provide a ground-truth to compare with the insitu collected data. The data will also be stored in the NASA Johnson Space Center’s Spacecraft Materials Spectral Database that is available to U.S. citizens and maintained by the Orbital Debris Program Office. The following paper provides an overview of the materials investigated, laboratory, and database overview, and spectral results for both pristine and post-electron exposed conditions. The spectral signature data highlights which materials are stable, or remain relatively unchanged, and which materials vary significantly due to exposure and material configuration (variations due to rotation of the sample on a flat surface).Initial results on changes in spectral directional reflectance of the materials as a function of incident illumination direction are also presented.This data also will benefit the space situational awareness community with spectral characterization of novel materials that can support their respective optical measurements focused on material identification.

Heather M. Cowardin↗
NASA NTRS2016

Characterizing Rocky and Gaseous Exoplanets with 2 m Class Space-based Coronagraphs

Several concepts now exist for small, space-based missions to directly characterize exoplanets in reflected light. While studies have been performed that investigate the potential detection yields of such missions, little work has been done to understand how instrumental and astrophysical parameters will affect the ability of these missions to obtain spectra that are useful for characterizing their planetary targets. Here, we develop an instrument noise model suitable for studying the spectral characterization potential of a coronagraph-equipped, space-based telescope. We adopt a baseline set of telescope and instrument parameters appropriate for near-future planned missions like WFIRST-AFTA, including a 2 m diameter primary aperture, an operational wavelength range of 0.4–1.0 μm, and an instrument spectral resolution of λ/Δλ =70, and apply our baseline model to a variety of spectral models of different planet types, including Earth twins, Jupiter twins, and warm and cool Jupiters and Neptunes. With our exoplanet spectral models, we explore wavelength-dependent planet–star flux ratios for main-sequence stars of various effective temperatures and discuss how coronagraph inner and outer working angle constraints will influence the potential to study different types of planets. For planets most favorable to spectroscopic characterization—cool Jupiters and Neptunes as well as nearby super-Earths—we study the integration times required to achieve moderate signal-to-noise ratio spectra. We also explore the sensitivity of the integration times required to either detect the bottom or presence of key absorption bands (for methane, water vapor, and molecular oxygen) to coronagraph raw contrast performance, exozodiacal light levels, and the distance to the planetary system. Decreasing detector quantum efficiency at longer visible wavelengths makes the detection of water vapor in the atmospheres of Earth-like planets extremely challenging, and also hinders detections of the 0.89 μm methane band. Additionally, most modeled observations have noise dominated by dark currents, indicating that improving CCD performance could substantially drive down requisite integration times. Finally, we briefly discuss the extension of our models to a more distant future Large UV-Optical-InfraRed (LUVOIR) mission.

Astrobiology↗
NASA NTRSDate not supplied

Experimental Characterization of Non-Associative Plasticity Flow Rule Coefficients and Post-Peak Stress Degradation for the LS-DYNA MAT213 Model

This project is focused on developing an experimental framework for characterizing non-associative plasticity flow rule coefficients through coupon-scale tests for the LS-DYNA MAT213 model. The main objective is to characterize these coefficients based on the multi-scale (i.e., both microscopic and macroscopic) full-field measurement of the evolution of strain and stress fields. This paper focuses on presenting the experimental work on characterizing the full-scale stress-strain curves of T700/LM-PAEK composites under tension, compression, and shear loads. The experimental data set was intended to build a deformation sub-model in the MAT213 model for the material. The strain data were collected using both microscopic and macroscopic digital image correlation techniques. The microscopic technique was particularly useful for fracture cases under small strains. A preliminary simulation result obtained from the MAT213 model is also presented in the paper. The experimental framework herein will be extended to characterize post-peak stress degradation in the composite material and to develop a damage sub-model for the material. This project will contribute to developing a simulation tool based on the MAT213 model for simulating the rate-dependent impact damage in composites under multi-axial loading.

MAT213↗
NASA NTRSDate not supplied

Component Characterization of an eVTOL Reference Model for Crashworthiness Studies

Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a series of structural component and seat level tests to improve finite element model (FEM) characterization of a representative vertical take-off and landing (eVTOL) test article developed by NASA. A full-scale dynamic test was conducted on the representative eVTOL test article in November of 2022. The test article represented a high wing, six passenger eVTOL design concept and is referred to as the lift plus cruise (LPC) test article. The full-scale test identified limitations in the analytical models used to predict aircraft structural response, in particular the composite material models did not effectively capture brittle failure of the structure which were measured during dynamic loading. To better understand the mechanism behind the composite material failure mechanisms observed and to improve the FEM, intact sample specimens of the composite airframe structure were recovered from the test article post-test and used in material characterization testing. In addition, the seat configurations used in the LPC test article were further studied using isolated seat and anthropomorphic test device (ATD) drop tower testing. Dynamic compression tests and three-point bend tests, conducted at varied impact speeds, were performed on the recovered frame section specimens. Additional testing was conducted to characterize the material properties of the forming foam, which remained in the frames after fabrication. These tests were used to improve characterization of the damage and failure parameters of the composite material model used in the FE model of the LPC test article. Seat level tests were conducted on the seats used in the LPC test article using acceleration pulses inclusive of current general aviation and rotorcraft certification load levels as well as conditions representative of those measured at the seat base during the LPC test. The structural material models and seat environment models of the LPC test article FEM were calibrated using the generated component test data. The updates made to these models were then integrated into the LPC FEM and simulated in the full-scale test condition. Results demonstrated the effectiveness of component testing to improve predictive capability of composite aerospace structural models within the crash and dynamic loading environments. Demonstration of the LPC FEM response across an accumulation of coupon, component, seat environment, and full-scale test levels provides confidence in the predictive capability of this model for future use in the study of occupant safety within eVTOL relevant crash environments.

Craswhorthiness↗
NASA NTRSDate not supplied

Component Characterization of an eVTOL Reference Model for Crashworthiness Studies

Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a series of structural component and seat level tests to improve finite element model (FEM) characterization of a representative vertical take-off and landing (eVTOL) test article developed by NASA. A full-scale dynamic test was conducted on the representative eVTOL test article in November of 2022. The test article represented a high wing, six passenger eVTOL design concept and is referred to as the lift plus cruise (LPC) test article. The full-scale test identified limitations in the analytical models used to predict aircraft structural response, in particular the composite material models did not effectively capture brittle failure of the structure which were measured during dynamic loading. To better understand the mechanism behind the composite material failure mechanisms observed and to improve the FEM, intact sample specimens of the composite airframe structure were recovered from the test article post-test and used in material characterization testing. In addition, the seat configurations used in the LPC test article were further studied using isolated seat and anthropomorphic test device (ATD) drop tower testing. Dynamic compression tests and three-point bend tests, conducted at varied impact speeds, were performed on the recovered frame section specimens. Additional testing was conducted to characterize the material properties of the forming foam, which remained in the frames after fabrication. These tests were used to improve characterization of the damage and failure parameters of the composite material model used in the FE model of the LPC test article. Seat level tests were conducted on the seats used in the LPC test article using acceleration pulses inclusive of current general aviation and rotorcraft certification load levels as well as conditions representative of those measured at the seat base during the LPC test. The structural material models and seat environment models of the LPC test article FEM were calibrated using the generated component test data. The updates made to these models were then integrated into the LPC FEM and simulated in the full-scale test condition. Results demonstrated the effectiveness of component testing to improve predictive capability of composite aerospace structural models within the crash and dynamic loading environments. Demonstration of the LPC FEM response across an accumulation of coupon, component, seat environment, and full-scale test levels provides confidence in the predictive capability of this model for future use in the study of occupant safety within eVTOL relevant crash environments.

Craswhorthiness↗
NASA NTRSDate not supplied

Electroluminescence Imaging: A Quantitative Characterization Technique to Measure Dust Occlusion of Solar Cells

Electroluminescence (EL) imaging is a qualitative characterization technique that is typically used to identify cracks, corrosion, and other defects in solar cells. It consists of imaging a cell under forward bias, where the solar cell emits photons due to radiative electron-hole pair recombination. Over the past few years, our team has expanded this into a quantitative technique with the help of image processing. We have primarily used this method to investigate lunar dust occlusion of solar cells and arrays. Lunar dust accumulation on solar cells is a major concern because it directly limits light accessible to the cell, decreasing power output. Many teams are working to develop dust mitigation technology to protect these arrays on the surface of the Moon, but thoroughly characterizing their efficacy is important to ensure their success prior to launch. Here, we present EL as a quantitative characterization technique to observe dust coverage on solar cells that, when coupled with IV performance measurements, can offer unique insights into how dust coverage impacts power output. Quantitative electroluminescence imaging works by running EL images through an image processing script that first grayscales the image then plots a histogram of the brightness of each pixel. On its own, it does not offer much insight into a solar cell’s performance. However, when comparing images to a baseline pristine, undamaged, or uncoated solar cell, it can quickly provide information about the impacts of surface contaminants or damage to the cell. Here, we present a case study where quantitative EL is used to measure the efficacy of dust mitigation technology for flexible solar arrays and discuss the lessons learned about dust mitigation, testing with lunar simulant, and this characterization technique.

photovoltaics↗
NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗
NASA NTRS2026

Development, Characterization, and Validation of Elevated-Temperature Constitutive Models: Deformation and Damage

This report provides a brief review of experimentally observed hereditary and nonhereditary material behavior along with background information on standard as well as advanced internal state variable constitutive modeling at elevated temperature. A description of exploratory, characterization, and validation testing is presented along with a detailed outline of what constitutes “sufficient” data content (i.e., quality and quantity) for developing or enhancing, characterizing, and validating a particular sophisticated nonlinear time- and history-dependent (hereditary) class of constitutive models known as GVIPS (generalized viscoplasticity with potential structure). The tests described are necessary to reveal a material’s behavior in the reversible (or viscoelastic) and irreversible (or viscoplastic) regimes, for the identification of both deformation and damage model parameters. Results presented are primarily for metallic materials. In all cases, both uniaxial and multiaxial tests are described, and the linkage between the specific tests and the parameters within the model that can be characterized from the results of these tests are also discussed. Discussion is also provided relative to the role information management must play relative to material data collection, analysis, maintenance, and dissemination. The need for such an information system is particularly important as both analyst and designer move toward utilizations of sophisticated, nonlinear time- and history dependent (hereditary) constitutive models. Lastly, the concept of state space and its utility in understanding and establishing constitutive models is addressed throughout. The intent behind this document is to help both the modeler and experimentalist understand each other’s specific points of view and provide guidance for both model development and characterization. Emphasis has been placed on providing the mechanician with information regarding how tests are performed and what issues to be aware of when interpreting results. It is hoped that experimentalists will take away a new perspective on the types of information that modelers and analysts are looking for from them.

Constitutive Modeling↗
DOE OSTI2019

Subtask 1.1 – Advanced Characterization of Unconventional Oil and Gas Reservoirs to Enhance CO2 Storage Resource Estimates

The Energy & Environmental Research Center (EERC) developed methods and approaches for advanced characterization of unconventional oil and gas reservoirs to enhance CO2 storage resource estimates using samples collected from organic-rich shales of the Bakken Formation. The project was funded under U.S. Department of Energy (DOE) Cooperative Agreement No. DE-FE0024233, with nonfederal cost share provided by Hitachi High Technologies America. The project participants included the EERC, Hitachi High Technologies America, the team at the National Energy Technology Laboratory’s (NETL’s) computed tomography (CT) scanning laboratory in Morgantown, West Virginia, and several NETL staff who have worked on CO2 storage resource estimation. Investigations on the use of subsurface geologic formations for CO2 storage have been ongoing for many years. In the last decade, improvements in directional drilling technology and hydraulic fracturing of organic-rich shale and other tight rock formations have opened new opportunities for CO2 storage, with the potential cobenefit of enhancing gas and oil recovery. Gas-bearing, organic-rich shales have been of particular interest as a carbon storage target because their ability to store large volumes of CO2 is implied by their ability to store methane; however, estimating the CO2 storage resource of organic-rich shales and other unconventional reservoirs is challenging because of the lack of detailed geologic and petrophysical data that are needed to develop improved volumetric equations. According to NETL’s method for estimating regional-scale CO2 storage resources, the key factors that control CO2 storage in geologic formations include void space within induced fractures, natural fractures and matrix pores, as well as the occurrence and distribution of organic matter (OM) and clay minerals. A key goal of this effort was to use field emission scanning electron microscopy (FESEM) analysis of fine-grain unconventional reservoir rocks coupled with advanced image analysis and machine learning techniques to quantify the occurrence and distribution of porosity, OM, and clay minerals. By better understanding the potential migration pathways of CO2 within tight rocks and quantifying the occurrence of sorptive components (OM and clays) along potential flow pathways, methods to estimate the CO2 storage resource of such rocks can be refined. The Bakken petroleum system (Bakken) was used as the source of rock samples for this effort because it includes organic-rich shales with contrasting degrees of thermal maturity as well as tight, nonshale clastic rocks with varying clay mineral content. To better understand the key components of interest in tight rock samples, the EERC worked closely with Hitachi to optimize the FESEM settings necessary to resolve the sample mineralogy, porosity and OM content at micro- to nanoscale resolution. The EERC also worked closely with Hitachi to apply and improve its advanced mineral identification and characterization system (AMICS) software so that it is better suited for mineral identification at the high resolution necessary to resolve features of interest in fine-grained rocks such as organic-rich shales. The EERC also applied advanced image analysis software packages, including Ilastik, to classify and quantify the key components of interest within the samples using FESEM imagery. These advanced techniques allowed for quantification and differentiation of the void space within fractures, pores and OM, as well as a technique to determine and quantify the key mineral and OM components surrounding pore spaces. Being able to better quantify the void space and the potential accessibility of CO2 to sorptive minerals or OM within tight rocks allows for improved estimation of the CO2 storage resource potential of organic-rich shales and other unconventional formations. The information derived from the image analysis techniques was used to refine NETL’s method for estimating regional-scale CO2 storage resources in collaboration with staff from NETL. An additional goal of this work was to better understand rates of CO2 permeation, flow pathways, and sorption in organic-rich shales and nonshale reservoir rocks and to evaluate potential changes in CO2 flow over time. The EERC conducted long-duration (several weeks) CO2 flow-through testing at reservoir conditions using Bakken shale and nonshale samples to assess CO2 permeation rates and retention/sorption within core plugs to represent bulk matrix behavior. Conventional isothermal adsorption testing over a range of pressure conditions was also performed on pulverized Bakken samples to better assess potential maximum sorptive capacity of the samples. The results of this testing illustrated the higher sorptive capacity of the Bakken shales when compared to the sorptive capacity of the nonshale reservoir rock, which contains very little OM when compared to the Bakken shales. The results also illustrate the differences in permeation behavior as a function of fracture flow versus matrix flow. In an attempt to visualize CO2 permeation and flow behavior in Bakken shale samples over time, the EERC collaborated with NETL’s CT Lab in Morgantown, West Virginia. A variety of tests were performed at the NETL lab on unfractured and fractured samples of the Bakken shale. The unfractured Bakken shale samples did not result in CO2 migration within the samples over the testing duration; thus imagery of CO2 migration pathways within the matrix of Bakken samples was not obtained. The results of the flow-through testing within fractured samples illustrate changes in CO2 permeation rates over time, with a trend of decreasing CO2 flow over time. The results of this effort suggest that FESEM analysis coupled with advanced image analysis and machine learning techniques are effective in characterizing and quantifying the mineralogy, porosity, fractures, and OM content of 2-D imagery at the high resolution needed to identify features of interest in tight rocks. In addition, the image analysis techniques allow for identification and quantification of different porosity types as well as the key mineral components and/or OM that CO2 would contact in the reservoir as it migrates through pores and fracture networks. This is key information needed to better estimate the CO2 storage resource potential of organic-rich shales and other tight reservoirs. Additional work is needed to determine the sorptive capacity of the individual sample components (OM and clay minerals) at reservoir conditions so that this approach and the refined CO2 storage resource equation can be applied to other shale and unconventional reservoirs. In addition, subsequent work should be performed to better understand the number of images needed to use stereological approaches to estimate the volume of sample components using 2-D imagery, to explore machine learning techniques to differentiate between induced vs. natural fractures, and to estimate the connectivity of pores and fracture networks using 2-D imagery. Being able to derive this information at the microscale would facilitate scaling up of the sample characterization data used for reservoir modeling and simulation to estimate the CO2 storage resource potential of tight formations.

03 NATURAL GAS↗
DOE OSTI2018

Development of Non Destructive Assay Approach for Characterization of Spent Fuel Debris at Fukushima - 18543

Fukushima is considering options for decommissioning the damaged reactor. One of the technical challenges is the accurate characterization of fissile isotopes in the spent fuel debris. This is due to the fissile content, high gamma and neutron emission and uncertainties regarding the fuel burnup and unknown, heterogeneous mixture of materials that may be present. These requirements lead to significant challenges for potential measurement approaches with regard to the requirements for shielding and remote operation that result from plant and operational constraints. Mirion Technologies (MTKK) has been working to perform feasibility and concept design studies for a non-destructive assay (NDA) system that could be used to characterize the fissile content of retrieved samples of fuel debris. The main advantage of using an NDA technique is that the entire volume of the sample is interrogated so the method is not reliant upon assumptions of representativeness of samples retrieved and sent for laboratory analysis. The proposed technique comprises a combination of gamma spectroscopy and combined passive / active neutron interrogation with advanced data analysis algorithms in order to determine the maximum available data on the spent fuel properties and obtain a full radionuclide characterization of each sample. This includes quantification of individual fissile nuclides with validated uncertainties. In this paper we describe the NDA techniques and systems that are proposed, their benefits and limitations, and how they may be implemented into a full-scale system for fuel element debris characterization. We describe the studies that were performed based on experience of real systems and research supplemented with extensive computer modelling work to represent the expected fuel element debris properties. The work benefits from Mirion's extensive global physics and engineering expertise in designing, supplying and operating a wide range of NDA systems for diverse applications and in different challenging physical and operational environments. We describe how the advanced and innovative physics techniques that have resulted from Mirion's collective experience in these areas, can be deployed in an NDA system. The final approach that has been developed provides a means for determining the masses of the individual fissile isotopes with robust uncertainties and capable of implementation into an NDA system that meets the expected requirements for an operational plant. We focus on the techniques that have been developed and describe how they are of wider relevance and interest for projects that include challenges for characterisation of fuel residues. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Characterization of Tc-99 Speciation and Chemical Composition of 241-AN-102 Tank Waste Supernatant - 19201

Technetium (Tc) in its isotopic form {sup 99}Tc is generated in high yields from the fission of {sup 235}U and {sup 239}Pu. A significant inventory of {sup 99}Tc remains at the U.S. Department of Energy's Hanford Site, and it is one of the most difficult contaminants to address. In the strongly alkaline solutions that are typical of Hanford tank waste, Tc exists as both pertechnetate (TcO{sub 4}{sup -} in oxidation state VII) and in reduced forms (oxidation state <VII) collectively known as non-pertechnetate species. Pertechnetate is a well-characterized anionic Tc species that can be removed from low-activity waste by anion exchange or other methods. There is no definitive information on the origin or a comprehensive description of the non-pertechnetate species in Hanford tanks. Designing strategies for effective management of Tc, including separation and immobilization, requires an understanding of the molecular structure of the non-pertechnetate species and their identification in actual tank waste samples. Developing this advanced understanding would facilitate development of new technologies for treating dissimilar Tc species. Toward this objective, a spectroscopic library of the Tc(I) [fac-Tc(CO){sub 3}]{sup +} and Tc(IV, VI, VII) compounds was generated using a range of techniques and applied to the characterization of actual 241-AN-102 tank waste supernatant. A sample of the 241-AN-102 tank waste (collected in 2013) was processed to remove {sup 137}Cs by spherical resorcinol-formaldehyde (sRF) ion exchange resin after the sodium concentration was adjusted to 5.6 M. The Cs-loaded sRF column was eluted with 0.45 M HNO{sub 3}. As-received AN-102, Cs-depleted AN-102 effluent, and sRF eluate fractions were comprehensively characterized for chemical composition and speciation of Tc using {sup 99}Tc nuclear magnetic resonance (NMR) spectroscopy and X-ray absorption spectroscopy. The results of these analyses demonstrated for the first time that non-pertechnetate Tc present in the 241-AN-102 tank waste is composed of several low-valent Tc species, including the Tc(I) [fac-Tc(CO){sub 3}L{sub 3}]{sup +}, Tc(IV), and possibly Tc(VI) compounds. This is the second experimental observation of the [fac-Tc(CO){sub 3}L{sub 3}]{sup +} species in the Hanford tank waste that highlights their importance for waste processing. In addition, the chemical composition of the 241-AN-102 tank waste was characterized with the focus on small chelators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Revolutionizing Waste Management: AI-Powered Real-Time Characterization for Efficient Handling of Non-Recyclable Municipal Solid Waste

According to EPA, -300 MM tons of municipal solid waste (MSW) was available in the US as of 2018. Of that total material, nearly 50% was landfilled resulting in a significant loss for the potential to convert its energy value into cost effective and sustainable biofuels. Redirecting this material away from the landfill and into conversion ready feedstock for energy generation can directly address DOE's selling price < $2.50/GGE while securing the US national energy independence [1]. However, the paramount challenges in any rational fuel conversion strategy are understanding the chemical makeup, quality and associated calorific value of the MSW. Understanding these parameters is critical in achieving any acceptable fuel conversion and requires rapid characterization followed by accurate separation technologies. Therefore, we are proposing to address the rapid characterization by building a non-invasive, rapid, and highly accurate Artificial Intelligence (AI)-enabled spectrometric/optical approach augmented with multi-sensory information for advanced characterization of domestic heterogeneous MSW. North Carolina State University (NCSU) and the National Renewable Energy Laboratory (NREL), in partnership with strong support from the Town of Cary and IBM, Inc., will closely work together to implement this ground-breaking technology for the effective characterization of MSW for sustainable and affordable production of conversion-ready feedstocks, while solving the environment issue of planetary proportions.

artificial intelligence↗
DOE OSTI2025

Automating Sensor Characterization with Bayesian Optimization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Cuevas-Zepeda, Julian [Chicago U., KICP; Chicago U↗
DOE OSTI2022

Two–Photon Polymerized Shape Memory Microfibers: A New Mechanical Characterization Method in Liquid

Two-photon polymerization (TPP) is widely used to create 3D micro- and nanoscale scaffolds for biological and mechanobiological studies, which often require the mechanical characterization of the TPP fabricated structures. To satisfy physiological requirements, most of the mechanical characterizations need to be conducted in liquid. However, previous characterizations of TPP fabricated structures are all conducted in air due to the limitation of conventional micro- and nanoscale mechanical testing methods. In this study, a new experimental method is reported for testing the mechanical properties of TPP-printed microfibers in liquid. The experiments show that the mechanical behaviors of the microfibers tested in liquid are significantly different from those tested in air. By controlling the TPP writing parameters, the mechanical properties of the microfibers can be tailored over a wide range to meet a variety of mechanobiology applications. In addition, it is found that, in water, the plasticly deformed microfibers can return to their predeformed shape after tensile strain is released. The shape recovery time is dependent on the size of microfibers. The experimental method represents a significant advancement in mechanical testing of TPP fabricated structures and may help release the full potential of TPP fabricated 3D tissue scaffolds for mechanobiological studies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

LX-17 Thermal Decomposition-Characterization of Solid Residues from Cook-Off in a Small-Scale Vessel Under Confinement

Concerns surround whether insensitive (or any) energetic materials are more dangerous to handle when exposed to abnormal thermal environments. This study characterizes the residual material remaining after LX-17 (92.5 % 1,3,5-triamino 2,4,6-trinitro benzene (TATB) and 7.5 % Kel-F) is exposed to various thermal environments in a sealed small-scale vessel cook-off test reactor (heated at 0.1 to 100 °C/min until the reactor opened at 3000 psi (20.7 MPa)). Previous work has shown no additional sensitivity of these residues as evaluated by small-scale safety analysis, but characterization on the molecular scale indicates the TATB is transformed to more reactive compounds as well as the residue could be precursors to toxic gases. The solids and chars were characterized by various analytical methods. Heat-flow measurements indicated exothermic release is due to a mixture of residual TATB and related decomposition products (which may be more energetic). The N/C and O/N ratios indicated a material much more degraded than TATB. Primarily, the solids were a network of amorphous C inter-dispersed with N and O. Types of bonding include C–C, C–N, N–H, N–C, N=C, N≡C, C–O=, and –OH. Solvent extracts of the solids showed TATB decomposition intermediates benzo-furazans and benzo-furoxans, substituted TATB (mono-nitroso, hydroxyl, and chlorinated) along with several unidentified smaller molecules. These results indicate thermal treatment produces an amorphous carbon residue with heteroatoms incorporated through differing functionality, varying depending upon the thermal severity of exposure. These structures also could further decompose producing toxic light gases (such as cyanide).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗