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DOE OSTI2021

Evaluating Manual Sampling Locations for Regulatory and Emergency Response

Drinking water systems commonly use manual or grab sampling to monitor water quality, identify or confirm issues, and verify that corrective or emergency response actions have been effective. In this paper, the effectiveness of regulatory sampling locations for emergency response is explored. An optimization formulation based on the literature was used to identify manual sampling locations to maximize overall nodal coverage of the system. Results showed that sampling locations could be effective in confirming incidents for which they were not designed. When evaluating sampling locations optimized for emergency response against regulatory scenarios, the average performance was reduced by 3%–4%, while using optimized regulatory sampling locations for emergency response reduced performance by 7%–10%. Secondary constraints were also included in the formulation to ensure geographical and water age diversity with minimal impact on the performance. This work highlighted that regulatory sampling locations provide value in responding to an emergency for these networks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Direct Air Capture of CO 2 and Delivery to Photobioreactors for Algal Biofuel Production (Final Report)

A mobile DAC system was designed and constructed to pair with photobioreactors growing algae for biofuel production. The DAC system was designed as a versatile research system, rather than a compact production unit. The system was constructed and mounted on a mobile skid to facilitate transportation to the algae production site. Within the DAC system, CO 2 was captured using amine-loaded monoliths that allow for high CO 2 uptake with low pressure drop. The CO 2 is collected using a Global Thermostat patented temperature/vacuum swing adsorption (TVSA) process. Amine sorbents and process conditions were optimized to produce 10 to >20 g CO 2 .h-1. The stability of the amine sorbents was also studied, with sorbent modifications made to improve stability to degradation by oxidation. An Algenol-developed Spirulina strain (Arthrospira platensis AB2293) was selected as the production cyanobacterial strain. AB2293 cultured was inoculum for outdoor production following PBR installation by Algenol. The PBR system was composed of three independent PBRs, with each PBR composed of four hanging bags internally recirculated by a liquid turnover pump. The PBRs were operated outdoors in Atlanta, GA, and integrated with the DAC system. Algae were grown with similar productivity using DAC-CO 2 as algae grown using pure CO 2 obtained commercially (Airgas). Throughout the experimental duration, no discoloration was observed, and cellular morphology was consistent between the two experimental treatments. An LCA including lifecycle greenhouse gas emissions, full life cycle inventory of the Algenol system and the DAC system and integrated DAC+PBR system was developed. Lifecycle greenhouse gas emissions were calculated for capture of carbon dioxide using input from Global Thermostat and the National Renewable Energy Laboratory. Three scenarios for energy provision were evaluated: a natural gas combined heat and power system sized to meet the electricity requirement, a natural gas combined heat and power system sized to meet the process heat requirements, and a system without on-site power that procures the electricity from the grid. In all three cases, as expected, the major contributor to the emissions is the energy consumption associated with the desorption step of the DAC process. The LCA quantified the reduced potential energy and greenhouse gas emissions of heat and mass integration of DAC and Algenol compared to unintegrated DAC and Algenol systems. A life cycle assessment of the role of sorbent productivity and lifetime was also developed. The development of more robust, oxidation resistant DAC sorbents may enable small reductions in energy requirements and in lifecycle greenhouse gas emissions and other environmental impacts. NREL performed techno-economic analysis (TEA) to identify the integration scenario most likely to achieve a 15% cost reduction target versus the baseline. Heat and mass integration of DAC and the PBR is critical to minimizing the MFSP. The baseline case utilizes no heat and mass integration, and the DAC system provides 100% of the CO 2 required by the photobioreactors (20 tonnes/hr), operating for 12 hours/day capturing 40 tonnes CO 2 /operating hour. The minimum fuel selling price (MFSP) of ethanol calculated from the baseline case was $10.68/gal ethanol. This corresponds with a targeted MFSP of $9.07/gal ethanol (or 15% reduction). This target was achieved by integration Option 2a with the greatest cost reduction of 17.8% (or $8.78/gal) and integration Option 2b with a cost reduction of 16.4% (or $8.93/gal). Reductions in MFSP are attributed to two primary process considerations: (a) CO 2 storage at night reduces the capital expenses associated with DAC (i.e., increasing on-stream time); and (b) distributed DAC scenarios (DAC-PBR integration Options 2a and 2b) make use of boiler and DAC CHP flue gas CO 2 (free). Direct air capture on-stream time was one of the largest contributors to MFSP reduction.

09 BIOMASS FUELS↗

DOE OSTI2024

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2012

The Resolved Stellar Population in 50 Regions of M83 from HST/WFC3 Early Release Science Observations

We present a multi-wavelength photometric study of approximately 15,000 resolved stars in the nearby spiral galaxy M83 (NGC 5236, D = 4.61 Mpc) based on Hubble Space Telescope Wide Field Camera 3 observations using four filters: F336W, F438W, F555W, and F814W. We select 50 regions (an average size of 260 pc by 280 pc) in the spiral arm and inter-arm areas of M83 and determine the age distribution of the luminous stellar populations in each region. This is accomplished by correcting for extinction toward each individual star by comparing its colors with predictions from stellar isochrones.We compare the resulting luminosity-weighted mean ages of the luminous stars in the 50 regions with those determined from several independent methods, including the number ratio of red-to-blue supergiants, morphological appearance of the regions, surface brightness fluctuations, and the ages of clusters in the regions. We find reasonably good agreement between these methods. We also find that young stars are much more likely to be found in concentrated aggregates along spiral arms, while older stars are more dispersed. These results are consistent with the scenario that star formation is associated with the spiral arms, and stars form primarily in star clusters and then disperse on short timescales to form the field population. The locations ofWolf-Rayet stars are found to correlate with the positions of many of the youngest regions, providing additional support for our ability to accurately estimate ages. We address the effects of spatial resolution on the measured colors, magnitudes, and age estimates. While individual stars can occasionally show measurable differences in the colors and magnitudes, the age estimates for entire regions are only slightly affected.

Hubble Space Telescope↗

NASA NTRSDate not supplied

Transcriptomic Changes in Seedlings from Seeds Exposed to Simulated Space Radiation

Outside the protection of Earth’s magnetic field, living organisms are constantly exposed to space radiation that consists of energetic protons and other heavier charged particles. With the goal of manned Mars exploration, the production of fresh crop during long duration space missions can be beneficial for meeting astronauts’ nutritional and psychological needs. In our study, we not only evaluated plant/fruit morphometrics and edible fresh mass, but also analyzed transcriptomic changes in seedlings from seeds of three plant species (Arabidopsis, mizuna, and tomato) exposed to simulated Galactic Cosmic Rays(GCR) and solar particle events(SPE). The radiation experiments were performed in the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). 10-day Arabidopsis seedlings were exposed acutely (~240 cGy/hr) to simulated GCR scenarios of combined ions including protons, helium, oxygen, titanium, and/or iron ions at 40 or 80 cGy. Seeds of Arabidopsis, mizuna, and tomato were exposed to 40 or 80 cGy simulated GCR (dry seeds) or SPE (imbibed seeds) at lower dose rates(20-26 cGy/hr). Seedlings from control and irradiated seeds were then collected in RNAlater at similar growth stages with true leaves emerged. Total RNA was isolated and analyzed via Illumina whole transcriptome sequencing technology. Plant species-specific bioinformatics revealed transcriptional biomarkers and signaling pathways induced by simulated space radiation that were found to be dose, dose-rate, and species dependent. DNA damage response, stress signaling, and metabolic pathways are among the most significant changes. These data highlight some critical insights on the mechanisms of how plants respond and adapt to the space radiation environment and provide a molecular basis for crop selection and refinement in deep space exploration.

Anirudha Dixit↗

DOE OSTI2024

Optimizing Selection Pressures and Pest Management to Maximize Cultivation Yield (OSPREY) (Final Technical Report)

This project was proposed in response to AOI 1, Cultivation Intensification Processes for Algae, within the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement (FOA Number: DE-FOA-0002029). The work was designed to address a critical industry need to improve annualized productivity, stability, and quality of algal production strains for biofuels and bioproducts. The overall project goals were to generate process innovations rooted in established outdoor systems for strain selection, improvement, maintenance, and cultivation as well as pest detection and tracking. Planned advances included a 50% improvement in harvest yield based on AFDW (g m 2 d -1 ), 50% improvement in robustness based on stability metrics (e.g., high-productivity cultivation days, pond uptime), and 20% improvement in conversion yield. Individually, each of our planned process improvements (e.g., pest tracking) had the potential to increase productivity. However, to realize increases in yield at the system level, improvements to one unit’s process must be balanced against potential effects on other processes. For example, changes to strains, cultivation, and pest management developed in isolation may hurt other unit operations. Therefore, a critical success factor of the project was the integration of the pipeline components, achieved through iterative field-to- (short term) lab testing. In addition, through sustainability models, we evaluated how improvements would alter industry scenarios.

09 BIOMASS FUELS↗

DOE OSTI2024

Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming

The project Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Wyoming Carbon Underground Storage Project (WY-CUSP) consisted of CO2 storage site characterization and evaluation, focusing on Wyoming’s most promising CO2 storage reservoirs (the Pennsylvanian Weber/Tensleep Sandstone and Mississippian Madison Limestone) and premier CO2 storage site (Rock Springs Uplift). Results from the WY-CUSP project suggest the two reservoirs could store up to 17,000 million tons of CO2. The WY-CUSP team drilled a stratigraphic test well and acquired a 3-D seismic survey covering 25 square miles of the Rock Springs Uplift site. The team retrieved 916 feet of core from the 12,810-foot-deep well, along with a complete log suite, borehole images, fluid samples, and other data. Project partners (1) provided continuous visual documentation of the core, including grain size, mineralogy, facies distribution, and porosity; (2) performed continuous permeability and velocity scans of selected reservoir intervals; and (3) chemically analyzed the fluid samples. WY-CUSP scientists integrated seismic attributes with observations from log suites, a VSP survey, core, fluid samples, and laboratory analyses, including continuous permeability scans. From these integrations, researchers constructed 3-D spatial distribution volumes of reservoir and seal properties that represent geological heterogeneity at the targeted CO2 storage site. The WY-CUSP team used this data to perform new CO2 plume migration simulations. Baker Hughes, Inc., completed a series of small-scale, in-situ water injectivity measurements. A database was formed when observations, analyses, and experiments from the stratigraphic test well were integrated. Correlation of these data allowed petrophysical parameters to be extrapolated from the test well out into the storage domain (5x5 mile 3-D seismic survey volume). This resulted in an improved, realistic understanding of performance assessments for potential CO2 storage scenarios. The WY-CUSP team worked on (1) improving CO2 storage resource estimates, (2) establishing long-term integrity and permanence of confining layers, (3) designing a profitable strategy for pressure management, and (4) evaluating the utilization of stored CO2 at the Rock Spring Uplift. Finally, Baker Hughes developed a microseismic baseline for the test site using in-bore geophones to complete field operations.

3-D seismic↗

DOE OSTI2022

Electricity Costs and Carbon Implications for CO 2 -to-Fuels in Selected Locations in 2030

With the growing interest in converting carbon dioxide (CO 2 ) to fuels and products to reduce overall greenhouse gas emissions and extend carbon from biogenic and other sources, the development of carbon capture and utilization (CO2U) technologies and industry is crucial. The Markets, Resources, and Environmental and Energy Justice of CO 2 -to-Fuels Technologies (short title: MarkeRs & EEJ) project supports this goal by assessing the resource and market potential and infrastructure requirements for mid-term (-2030) and long-term (-2050) deployment of CO2U technologies. The overall project analyzes CO2U economic and resource requirements as well as sustainability and environmental and energy justice (EEJ) metrics. This report focuses on short-term (-2030) aspects of the project. It identifies three CO2U locations in the Midwestern United States and quantifies the costs for potential electricity resources and marginal emissions for each site in the near term (e.g., 2030). We focus on four electricity purchase options, including retail rate, physical power purchase agreement (PPA), financial PPA, and real-time pricing (RTP), for each of the three sites and consider potential policies such as production tax credits (PTCs). We also assess time-dependent hourly marginal electricity costs and the marginal emission rates using modeled scenarios from Cambium (Gagnon et al. 2021).The results of the analysis are expected to inform other projects within the U.S. Department of Energy's CO 2 -to-Fuels Consortium, especially the Economics and Sustainability of CO 2 Utilization Technologies with Techno-Economic Analysis and Life Cycle Analysis (TEA/LCA) project, led by Michael Wang of Argonne National Laboratory and Ling Tao of the National Renewable Energy Laboratory. The project results are also expected to inform the investment and technology communities and policymakers at the U.S. Department of Energy, state, and regional levels and guide investment by government and industry in research and development portfolios.

09 BIOMASS FUELS↗

NASA NTRSDate not supplied

Onboard Hyperspectral Image Classification via Transfer Learning for Communication-Limited Spacecraft

Employing deep-learning and artificial-intelligence (AI) techniques onboard spacecraft can dramatically improve priority data selection to ensure more effective use of the available downlink. However, deployment of effective deep-learning models requires significant training on the ground, which may not be feasible, due to limited data available in an unexplored environment. Therefore, this research explores building robust classification models for onboard data processing where training data is highly limited using transfer-learning techniques. In this paper, we focus on the use case of hyperspectral imaging for remote sensing, a domain where the high dimensionality of the data from the sensor can rapidly saturate the downlink bandwidth. With this bottleneck, there is an impending need to autonomously and robustly classify data onboard to optimize downlink of high-impact measurements, thus maximizing the scientific utility per bit transmitted to the ground. This paper examines the use of deep neural networks onboard for hyperspectral image classification in a communication-limited scenario to analyze how the models perform with limited training data. The use of transfer learning can ameliorate the issue of poor generalization by transferring features learned from training on a large source dataset for one classification task to the target classification task with limited training data. For two deep-learning models from literature, we compare the accuracy of the models trained using transfer learning to models trained from scratch using a random weight initialization with varying amounts of training data. We demonstrate the feasibility and performance of running inference of the deep-learning models on representative flight-like hardware.

Advanced Avionics, Machine Learning, Data Processi↗

NASA NTRS1996

Test Outline for Flutter Analysis of Rectangular Panels in Rarefied Flow Conditions

Jet plume impingement forces acting on large flexible space structures may precipitate dynamically unstable behavior during space flights. Typical operating conditions in space involve rarefied gas flow regimes which are intrinsically distinct from continuum gas flow and are normally modeled using the kinetic theory of gas flow. Docking and undocking operations of the Space Shuttle with the Russian Mir space laboratory represent a scenario in which the stability boundaries of solar panels may be of interest. Extensive literature review of research work on the dynamic stability of rectangular panels in rarefied gas flow conditions indicated the lack of published reports dealing with this phenomenon. A recently completed preliminary study for NASA JSC dealing with the mathematical analysis of the stability of two-degree-of-freedom elastically supported rigid panels under the effect of rarefied gas flow was reviewed. A test plan outline is prepared for the purpose of conducting a series of experiments on four rectangular rigid test articles in a vacuum chamber under the effect of continuous and pulsating Nitrogen jet plumes. The purpose of the test plan is to gather enough data related to a number of key parameters to allow the validation of the two-degree-of-freedom mathematical model. The hardware required careful design to select a very lightweight material while satisfying rigidity and frequency requirements within the constraints of the test environment. The data to be obtained from the vacuum chamber tests can be compared with the predicted behavior of the theoretical two-degree-of-freedom model. Using the data obtained in this study, further research can identify the limitations of the mathematical model. In addition modifications to the mathematical model can be made, if warranted, to accurately predict the behavior of rigid panels under rarefied gas flow regimes.

Akl, Fred A.↗

NASA NTRS2019

Interface Conductance Under a Real Electronics Box

Electronics Boxes with high heat dissipations use a thermal interface material to increase heat transfer to the radiator in a vacuum/space environment. There are lots of materials to choose from, but for Spacecraft applications, there are more than high heat transfer metrics which must be met. Contamination (both particle generation and outgassing), ease of cutting, and removal are just as important metrics in material selection. However, vendor data of material thermal conductance is usually based on a 1" X 1" piece of material under high uniform pressures. Large Electronics boxes almost never have optimal pressures, as they are bolted along the perimeter and leave gaps in the center regions. In order to characterize the relative thermal conductance for large Electronics boxes, an 8" X 8" plate was fabricated to simulate an electronics box bottom and bolted around the perimeter to a cold plate. Various thermal interface materials were inserted between the box and cold plate, and overall thermal conductance's were calculated. A table was generated which compares the full gamut of thermal interface materials for large boxes, from a dry joint to a wet joint. Materials were placed in order of high to low conductance's, so an engineer can compare the benefit of each material in a real-world scenario.

Thermal Interface Conductance↗

NASA NTRS2018

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O<1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M~ 1x10(exp 7) M☉/yr) and the high mass-loss rate AGB star IK Tau (M~5x10(exp 6) M☉/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ~150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v=5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2.We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v1, previously derived for both objects (36 km/s versus v(∞)~17.7 km/s for IK Tau and 23 km/s versus v(∞)~5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond _400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ~3.7 x 10(exp 7) M☉ and ~2 x 10(ex0 8) M☉ for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

Stars: AGB and post-AGB, Stars: mass loss, Stars: ↗

NASA NTRS2018

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O < 1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M’ ∼ 1 × 10(exp −7) M/yr) and the high mass-loss rate AGB star IK Tau (M’ ∼ 5 × 10(exp −6) M/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ∼150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v = 5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2. We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v∞, previously derived for both objects (36 km/s versus v(∞) ∼ 17.7 km/s for IK Tau and 23 km/s versus v(∞) ∼ 5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond ∼400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ∼3.7 × 10(exp −7) Mand ∼2 × 10(exp −8) M for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

L. Decin↗

NASA NTRS1986

Nonlinear system controller design based on domain of attaction: An application to CELSS analysis and control

Nonlinear system controller design based on the domain of attraction is presented. This is particularly suited to investigating Closed Ecological Life Support Systems (CELSS) models. In particular, the dynamic consequences of changes in the waste storage capacity and system mass, and how information is used for control in CELSS models are examined. The models' high dimensionality and nonlinear state equations make them difficult to analyze by any other technique. The domain of attraction is the region in initial conditions that tend toward an attractor and it is delineated by randomly selecting initial conditions from the region of state space being investigated. Error analysis is done by repeating the domain simulations with independent samples. A refinement of this region is the domain of performance which is the region of initial conditions meeting a performance criteria. In nonlinear systems, local stability does not insure stability over a larger region. The domain of attraction marks out this stability region; hence, it can be considered a measure of a nonlinear system's ability to recovery from state perturbations. Considering random perturbations, the minimum radius of the domain is a measure of the magnitude of perturbations for which recovery is guaranteed. Design of both linear and nonlinear controllers are shown. Three CELSS models, with 9 to 30 state variable, are presented. Measures of the domain of attraction are used to show the global behavior of these models under a variety of design and controller scenarios.

Babcock, P. S., IV↗

DOE OSTI2021

Pilot-Scale Testing of an Integrated Circuit for the Extraction of Rare Earth Minerals and Elements from Coal and Coal Byproducts Using Advanced Separation Technologies

The primary objective of this project was to develop and demonstrate an integrated pilot-scale circuitry for recovering high-value rare earth elements (REEs) from coal and coal byproducts. The target performance was to produce a mixed REE product with content of at least two percent by weight on a dry mass basis in a cost-effective and environmentally benign manner. During the first nine months of the project period (Phase 2 Budget Period 2), pilot plant construction was completed including all field site startup activities such as permitting, engineering design, procurement/bidding, unit fabrication, site construction, equipment installation, module assembly, safety training, and circuit shakedown. During the remaining 21 months of project period (Phase 2 Budget Period 3), detailed field-testing activities were performed including feedstock sample collection and preparation, exploratory testing, circuit modification, detailed parametric study, and performance optimization. A detailed techno-economic analysis was performed based on the pilot plant testing findings which provided various scenarios for REE production. The project successfully accomplished the proposed target performance by producing mixed rare earth oxide (REO) with greater than 90% purity by weight in a continuous pilot scale operation from two distinctly different coarse refuse materials (i.e., West Kentucky No. 13 and Fire Clay coal seams), and at least three secondary sources (i.e., heap leach process and naturally formed acid mine drainage system). Project partners included the University of Kentucky, Virginia Tech, West Virginia University, Alliance Coal, Blackhawk Mining, Mineral Refining Company, and Mineral Separation Technologies. The pilot scale test facility was constructed at a former mining complex owned by Alliance Natural Resource Partners (Alliance Coal). The site was rehabilitated to accommodate the equipment installation, construction and fabrication, electrical power requirement, water line management and containment. The process units constructed and installed included X-ray sorting unit, crushing and grinding unit, physical separation unit, acid leaching unit, solvent extraction unit, and wastewater management unit. A rare earth mineral concentration unit was constructed as a standalone unit for flexible operation. A detailed environmental assessment and control plan was carried out to identify and quantify any potential impacts of the pilot-scale processing circuitry on the human and eco-system health and well-being. Corresponding mitigation strategies and control measures were provided. A conceptual flowsheet was developed to effectively remove thorium and uranium from high purity rare earth oxide mix or any potential radionuclide enriched stream. The two distinct feedstock materials were secured from the Blackhawk Mining Complex in eastern Kentucky where the Fire Clay (Hazard No. 4) seam is processed. The West Kentucky No. 13 (Baker) coarse refuse material was collected from an active process stream at an Alliance coal preparation plant located in western Kentucky. Characterization analysis indicated that both of feed materials generated from the two sources contained >300 ppm of TREEs on a dry whole mass basis which met the requirements for a qualified feed stock. The two feedstocks were further upgraded using a dual x-ray sorter to prepare the feed material for hydrometallurgical circuit. Thermal treatment on feed material prior to leaching was found to: 1) improve the leaching recovery of REEs, 2) increase the leaching kinetics, and 3) allow the leaching reaction to occur at lower acidity. Roasting at 600°C was selected as the pre-treatment condition for both West Kentucky No. 13 and Fire Clay coarse refuse material. Over 40% of leaching recovery was achieved by roasting West Kentucky No. 13 material having a top particle size of 3 mm in the pilot scale operation using 1.2M sulfuric acid leaching at 75OC. Initial pilot scale testing involved continuous operation of the pilot plant for 94 hours. The leaching unit was operated at solid-to-liquid ratio of 1 to 10 (w/v) using 0.5M sulfuric acid solution at a temperature of 75°C. The continuous solvent extraction circuit utilized rougher and cleaner units with DEHPA and TBP as the extractants. An innovative stripping circuit was developed to accumulate the REE concentration in the stripping solution to a level above 600 ppm. A bleed stream from the recycled strip solution was treated using oxalic acid precipitation which produced a high grade rare earth oxalate. The oxalate product was roasted to remove the oxalate which produced a rare earth oxide product having a purity greater 90%. Due to high concentrations of contaminant ions in the pregnant leach solution (PLS), a modified flowsheet was developed that involved pre-concentration of the REEs using multiple stages of precipitation and redissolution. The advantage of this process was improved removal of contamination before the downstream purification process and a significant cost reduction relative to the circuit that utilized the solvent extraction process. The modified circuitry included processes involving leaching, multistage precipitation, redissolution, and oxalate precipitation followed by roasting of the oxalate product. The circuit produced a mixed REO that was 92.96% pure from the initial test. A detailed parametric test plan was carried out which involved varying key parameters including solids feed rate, acid flowrate, acid concentration, multistage precipitation pH, redissolution pH, oxalate precipitation dosage and pH. The response variables included REE recovery, contaminant recovery, REO product grade and overall chemical consumption. Test results indicated that the acid-to-solid ratio is the key parameter to leaching efficiency as performance deteriorated with an increase in solids concentration. The optimal pH determined for REE precipitation and redissolution was 6.5 and 2.5, respectively. Additional tests were conducted to further improve the flowsheet. Recirculating a portion of the PLS to the feed of the leach tanks improved the leaching performance by lowering the pH of the leaching system and reducing the contamination recovery by shortening the residence time. Moreover, the removal of Al prior to REE precipitation significantly reduced the oxalic acid consumption in the oxalate precipitation circuit. The modified circuit produced over 90% grade REO by weight from both West Kentucky No. 13 and Fire Clay coarse refuse material in pilot scale continuous test programs. A case analysis model was developed to project the REE and major contaminants concentration in each PLS stream based on the leaching condition, pH cut point, and oxalic acid dosage. A correlation was established using empirical and semi-empirical models. Using the models, chemical consumption required for each stage was predicted based on the projected performance of the hydrometallurgy circuit. After identifying the optimum conditions, validation tests were carried out for the treatment of both West Kentucky No. 13 and Fire Clay coarse refuse materials in the pilot plant. The actual circuit performance and chemical consumptions were very close to the model predictions. Other than the two coarse refuse sources, several secondary feedstocks were also tested in the pilot plant facility. A “heap leach” system was constructed using the coarse refuse material generated from cleaning the West Kentucky No. 13 seam coal. Using the two stage SX rougher and cleaner circuit, a concentrate with a grade >90% REO was produced while recovering >97% of the REEs from the heap leach PLS. Naturally generated acid mine drainage (AMD) from West Kentucky No.13 mine was processed using the multistage precipitation circuit in the pilot plant in a test conducted for a period of 32 hours. The final grade of the mix RE oxide produced from the AMD was 90.84% with an overall circuit recovery of 64%. The primary source of REE was the selective precipitation steps involving iron and aluminum rejection. The hydrophobic-hydrophilic separation (HHS) process was proven to effectively recover coal from fine waste materials. For REM recovery, the HHS process was able to produce concentrates at grades of approximately 1.8% REE on an ash basis; however, recovery values were typically low, <10%, under the optimal conditions determined in the laboratory-scale testing. Staged testing of the pilot-scale HHS process for coal recovery and semi-continuous laboratory testing for REM testing showed that a total concentration ratio of more than 15x was observed for the REM recovery process. A circuit simulation package was developed for REE extraction and purification using a spreadsheet-based platform (Microsoft Excel). The REESim circuit simulation package is configured to track the mass and volume flows of components passing through a series of unit operations specified and configured by the user. The mass rates can then be utilized by the user to determine important performance indicators such as product mass yields, concentrate purity levels, element-by-element recoveries, and so forth. The techno-economic analysis showed that the roasting and leaching operations were the most expensive capital items, each contributing approximately 30% to the total capital cost. One notable contributor to the high production costs was the low REE recovery observed in the pilot scale trials. The product basket price was shown to have a strong influence on the economic viability of the scenarios, with the scandium price being the most significant influencer. Operating cost was shown to be extremely sensitive to REE recovery, REE feed grade, and leaching acid consumption. An analysis of ten different scenarios for a 500 t/h commercial operation revealed that three were economically favorable, producing internal rates of return varying from 27.7% to 33.1% and payback periods of 4 to 5 years. The project successfully developed and demonstrated a process to recover REEs from coal and coal byproducts in a pilot-plant operation which consistently produced over 90% grade REO mix from varies types of feedstocks. Commercialization analysis showed that the technology readiness level successfully achieved TRL 6 at the end of the project and demonstrated the need and the potential for scaling the process to further advance the technologies toward the goal of providing a domestic supply of REEs at a commercial scale.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2006

NASA Tech Briefs, September 2006

Topics covered include: Improving Thermomechanical Properties of SiC/SiC Composites; Aerogel/Particle Composites for Thermoelectric Devices; Patches for Repairing Ceramics and Ceramic- Matrix Composites; Lower-Conductivity Ceramic Materials for Thermal-Barrier Coatings; An Alternative for Emergency Preemption of Traffic Lights; Vehicle Transponder for Preemption of Traffic Lights; Automated Announcements of Approaching Emergency Vehicles; Intersection Monitor for Traffic-Light-Preemption System; Full-Duplex Digital Communication on a Single Laser Beam; Stabilizing Microwave Frequency of a Photonic Oscillator; Microwave Oscillators Based on Nonlinear WGM Resonators; Pointing Reference Scheme for Free-Space Optical Communications Systems; High-Level Performance Modeling of SAR Systems; Spectral Analysis Tool 6.2 for Windows; Multi-Platform Avionics Simulator; Silicon-Based Optical Modulator with Ferroelectric Layer; Multiplexing Transducers Based on Tunnel-Diode Oscillators; Scheduling with Automated Resolution of Conflicts; Symbolic Constraint Maintenance Grid; Discerning Trends in Performance Across Multiple Events; Magnetic Field Solver; Computing for Aiming a Spaceborne Bistatic- Radar Transmitter; 4-Vinyl-1,3-Dioxolane-2-One as an Additive for Li-Ion Cells; Probabilistic Prediction of Lifetimes of Ceramic Parts; STRANAL-PMC Version 2.0; Micromechanics and Piezo Enhancements of HyperSizer; Single-Phase Rare-Earth Oxide/Aluminum Oxide Glasses; Tilt/Tip/Piston Manipulator with Base-Mounted Actuators; Measurement of Model Noise in a Hard-Wall Wind Tunnel; Loci-STREAM Version 0.9; The Synergistic Engineering Environment; Reconfigurable Software for Controlling Formation Flying; More About the Tetrahedral Unstructured Software System; Computing Flows Using Chimera and Unstructured Grids; Avoiding Obstructions in Aiming a High-Gain Antenna; Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft; Tracking Positions and Attitudes of Mars Rovers; Stochastic Evolutionary Algorithms for Planning Robot Paths; Compressible Flow Toolbox; Rapid Aeroelastic Analysis of Blade Flutter in Turbomachines; General Flow-Solver Code for Turbomachinery Applications; Code for Multiblock CFD and Heat-Transfer Computations; Rotating-Pump Design Code; Covering a Crucible with Metal Containing Channels; Repairing Fractured Bones by Use of Bioabsorbable Composites; Kalman Filter for Calibrating a Telescope Focal Plane; Electronic Absolute Cartesian Autocollimator; Fiber-Optic Gratings for Lidar Measurements of Water Vapor; Simulating Responses of Gravitational-Wave Instrumentation; SOFTC: A Software Correlator for VLBI; Progress in Computational Simulation of Earthquakes; Database of Properties of Meteors; Computing Spacecraft Solar-Cell Damage by Charged Particles; Thermal Model of a Current-Carrying Wire in a Vacuum; Program for Analyzing Flows in a Complex Network; Program Predicts Performance of Optical Parametric Oscillators; Processing TES Level-1B Data; Automated Camera Calibration; Tracking the Martian CO2 Polar Ice Caps in Infrared Images; Processing TES Level-2 Data; SmaggIce Version 1.8; Solving the Swath Segment Selection Problem; The Spatial Standard Observer; Less-Complex Method of Classifying MPSK; Improvement in Recursive Hierarchical Segmentation of Data; Using Heaps in Recursive Hierarchical Segmentation of Data; Tool for Statistical Analysis and Display of Landing Sites; Automated Assignment of Proposals to Reviewers; Array-Pattern-Match Compiler for Opportunistic Data Analysis; Pre-Processor for Compression of Multispectral Image Data; Compressing Image Data While Limiting the Effects of Data Losses; Flight Operations Analysis Tool; Improvement in Visual Target Tracking for a Mobile Robot; Software for Simulating Air Traffic; Automated Vectorization of Decision-Based Algorithms; Grayscale Optical Correlator Workbench; "One-Stop Shopping" for Ocean Remote-Sensing and Model Data; State Analysis Database Tool; Generating CAHV and CAHVOmages with Shadows in ROAMS; Improving UDP/IP Transmission Without Increasing Congestion; FORTRAN Versions of Reformulated HFGMC Codes; Program for Editing Spacecraft Command Sequences; Flight-Tested Prototype of BEAM Software; Mission Scenario Development Workbench; Marsviewer; Tool for Analysis and Reduction of Scientific Data; ASPEN Version 3.0; Secure Display of Space-Exploration Images; Digital Front End for Wide-Band VLBI Science Receiver; Multifunctional Tanks for Spacecraft; Lightweight, Segmented, Mostly Silicon Telescope Mirror; Assistant for Analyzing Tropical-Rain-Mapping Radar Data; and Anion-Intercalating Cathodes for High-Energy- Density Cells.

Source record↗

DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

47 OTHER INSTRUMENTATION↗