SEARCH · Search NASA

Results for “data reduction techniques”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,477 records · Page 82

All sources NASA NTRS DOE OSTI

NASA NTRS2003

Electron Beam Freeform Fabrication: A Rapid Metal Deposition Process

Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley REsearch Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. The EBF process introduces metal wire feedstock into a molten pool that is created and sustained using a focused electron beam in a vacuum environment. Thus far, this technique has been demonstrated on aluminum and titanium alloys of interest for aerospace structural applications nickel and ferrous based alloys are also planned. Deposits resulting from 2219 aluminum demonstrations have exhibited a range of grain morphologies depending upon the deposition parameters. These materials ave exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF process is capable of bulk metal deposition at deposition rated in excess of 2500 cubic centimeters per hour (150 cubic inches per our) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

Taminger, Karen M. B.↗

NASA NTRS2011

Principal Component Noise Filtering for NAST-I Radiometric Calibration

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed- Interferometer (NAST-I) instrument is a high-resolution scanning interferometer that measures emitted thermal radiation between 3.3 and 18 microns. The NAST-I radiometric calibration is achieved using internal blackbody calibration references at ambient and hot temperatures. In this paper, we introduce a refined calibration technique that utilizes a principal component (PC) noise filter to compensate for instrument distortions and artifacts, therefore, further improve the absolute radiometric calibration accuracy. To test the procedure and estimate the PC filter noise performance, we form dependent and independent test samples using odd and even sets of blackbody spectra. To determine the optimal number of eigenvectors, the PC filter algorithm is applied to both dependent and independent blackbody spectra with a varying number of eigenvectors. The optimal number of PCs is selected so that the total root-mean-square (RMS) error is minimized. To estimate the filter noise performance, we examine four different scenarios: apply PC filtering to both dependent and independent datasets, apply PC filtering to dependent calibration data only, apply PC filtering to independent data only, and no PC filters. The independent blackbody radiances are predicted for each case and comparisons are made. The results show significant reduction in noise in the final calibrated radiances with the implementation of the PC filtering algorithm.

Tian, Jialin↗

NASA NTRS1995

Kuiper Airborne Observatory's Telescope Stabilization System: Disturbance Sensitivity Reduction Via Velocity Loop Feedback

In July of 1994 the Kuiper Airborne Observatory's (KAO) Telescope Stabilization System (TSS) was upgraded to meet performance goals necessary to view the Shoemaker-Levy 9 comet collision with Jupiter. The KAO is a modified C-141 Aircraft supporting a 36 inch Infrared telescope used to gather and analyze astronomical data. Before the upgrade, the TSS exhibited approximately a 10 arc-second resolution pointing accuracy. The majority of the inaccuracy was attributable to aircraft vibration and wind buffeting entering through the aircraft's telescope door opening; in other words, the TSS was overly sensitive to external disturbances. Because of power limitations and noise requirements, improving the pointing accuracy of the telescope required more sophistication than simply raising the bandwidth as some classical control strategies might suggest. Instead, relationships were developed between the disturbance sensitivity and closed loop transfer functions. These relationships suggested that employing velocity feedback along with an increase in current loop gain would dramatically improve the pointing resolution of the TSS by decreasing the control system's sensitivity to external disturbances. With the implementation of some classical control techniques and the above philosophy, the KAO's TSS's resolution was improved to approximately 2-3 arc-seconds.

Lawrence, David P.↗

DOE OSTI2025

Fast HARDI Uncertainty Quantification and Visualization with Spherical Sampling

In this paper, we study uncertainty quantification and visualization of orientation distribution functions (ODF), which corresponds to the diffusion profile of high angular resolution diffusion imaging (HARDI) data. The shape inclusion probability (SIP) function is the state‐of‐the‐art method for capturing the uncertainty of ODF ensembles. The current method of computing the SIP function with a volumetric basis exhibits high computational and memory costs, which can be a bottleneck to integrating uncertainty into HARDI visualization techniques and tools. We propose a novel spherical sampling framework for faster computation of the SIP function with lower memory usage and increased accuracy. In particular, we propose direct extraction of SIP isosurfaces, which represent confidence intervals indicating spatial uncertainty of HARDI glyphs, by performing spherical sampling of ODFs. Our spherical sampling approach requires much less sampling than the state‐of‐the‐art volume sampling method, thus providing significantly enhanced performance, scalability, and the ability to perform implicit ray tracing. Our experiments demonstrate that the SIP isosurfaces extracted with our spherical sampling approach can achieve up to 8164× speedup, 37282× memory reduction, and 50.2% less SIP isosurface error compared to the classical volume sampling approach. We demonstrate the efficacy of our methods through experiments on synthetic and human‐brain HARDI datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

In-situ Synthesis of PuCl 3 and Corresponding Raman and Density Functional Theory Vibrational Modes

The experimental and calculated Raman spectrum of PuCl 3 has been reported for the first time. PuCl 3 is a primary species found in plutonium metal refinement, specifically in pyrochemical salt processes including multicycle direct oxide reduction, metal chlorination, and electrorefining. As such, Raman signatures of PuCl 3 could serve as potential forensic indicators of material process history. A novel technique for synthesizing PuCl 3 from the in-situ chlorination of plutonium metal with HCl was developed to establish these signatures. Cerium metal surrogates were utilized to ensure optimization of the plutonium experiments and to minimize personnel exposure, and all experiments were carried out in a Raman reaction chamber designed for air-tight, high vacuum environments. In-situ Raman spectroscopy was employed in conjunction with Density Functional Theory (DFT) to investigate the vibrational modes of PuCl 3 . Associated mixed oxy and hydroxyl phases are also reported. The combined Raman and DFT results have eliminated inconsistencies in Raman mode assignments for the MX 3 family of metal chlorides having P6 3 /m symmetry, and IR modes derived from the DFT calculations are additionally presented. The data observed in this study is of potential interest to nuclear forensic analyses, nuclear sample aging, nuclear energy, plutonium processing, and stockpile stewardship.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

NASA NTRS1999

Jet Mixing Enhancement by Feedback Control

The objective of this work has been to produce methodologies for high speed jet noise reduction based on natural mechanisms and enhanced feedback control to affect frequencies and structures in a prescribed manner. In this effort the two-point hot wire measurements obtained in the Langley jet facility by Ukeiley were used in conjuction with linear stochastic estimation (LSE) to implement the LSE component of the complementary technique. This method combines the Proper Orthogonal Decomposition (POD) and LSE to provide an experimental low dimensional time dependent description of the flow field. From such a description it should be possible to identify short time high strain rate events in the jet which contribute to the noise. The main task completed for this effort is summarized: LSE experiments were performed at the downstream locations where the two point hot wire measurements have been obtained by Ukeiley. These experiments involved sampling simultaneously hot wire signals from a relatively course spatial grid in gamma and theta. From this simultaneous data, coupled with the two-point measurements of Ukeiley via the LSE components of the complementary technique, an experimental low dimensional description of the jet at 4, 5, 6, 7 and 8 diameters downstream was obtained for Mach numbers of 0.3 and 0.6. We first present an overview of the theory involved. We finish up with a statement of the work performed and finally provide charts from a 1999 APS talk which summarizes the results.

Glauser, Mark↗

NASA NTRS2012

Orion Absolute Navigation System Progress and Challenge

The absolute navigation design of NASA's Orion vehicle is described. It has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to benchmark the current state of the design and some of the rationale and analysis behind it. There are specific challenges to address when preparing a timely and effective design for the Exploration Flight Test (EFT-1), while still looking ahead and providing software extensibility for future exploration missions. The primary onboard measurements in a Near-Earth or Mid-Earth environment consist of GPS pseudo-range and delta-range, but for future explorations missions the use of star-tracker and optical navigation sources need to be considered. Discussions are presented for state size and composition, processing techniques, and consider states. A presentation is given for the processing technique using the computationally stable and robust UDU formulation with an Agee-Turner Rank-One update. This allows for computational savings when dealing with many parameters which are modeled as slowly varying Gauss-Markov processes. Preliminary analysis shows up to a 50% reduction in computation versus a more traditional formulation. Several state elements are discussed and evaluated, including position, velocity, attitude, clock bias/drift, and GPS measurement biases in addition to bias, scale factor, misalignment, and non-orthogonalities of the accelerometers and gyroscopes. Another consideration is the initialization of the EKF in various scenarios. Scenarios such as single-event upset, ground command, and cold start are discussed as are strategies for whole and partial state updates as well as covariance considerations. Strategies are given for dealing with latent measurements and high-rate propagation using multi-rate architecture. The details of the rate groups and the data ow between the elements is discussed and evaluated.

Holt, Greg N.↗

NASA NTRSDate not supplied

The Plant Water Management Experiments: Hydroponics 3 & 4

As humans consider longer-duration missions in space, NASA has identified production of fresh vegetables aboard spacecraft as beneficial for crew nutrition, mental wellbeing, and enabling bioregenerative life support (i.e., air, water, and waste processing). Current low-g plant growth techniques have successfully grown a variety of leafy and flowering plants. However, unique microgravity fluidics challenges to maintain plant moisture levels persist which hamper overall system reliability. The Plant Water Management (PWM) experiments seek to demonstrate low-cost, low-mass, reusable plant growth systems that leverage recent advances in low-g capillary fluidics phenomena to provide routine, largely passive, water delivery to plants. This paper presents findings from a series of PWM-Hydroponics 3 & 4 experiments, which were collected during three ISS flight operations that occurred in March, May, and July of 2021. Open hydroponic capillary channel flows with synthetic evapo-transpiring plant models were used. Tests demonstrated flow stability for single and parallel channel flow configurations across a range of flow rates, plant types, and plant arrangements. Technology demonstrations of both passive aeration and bubble phase separation are reported. We provide details of the data reduction and archive. Insights from the successful flight demonstrations provide a foundation from which follow-on PWM-Hydroponics 5 & 6 experiments on ISS, potentially incorporate living plants, are being considered. Xx Summary of positives and negatives..

Marc B. Wasserman↗

DOE OSTI2019

Cp* Noninnocence Leads to a Remarkably Weak C–H Bond via Metallocene Protonation

Metallocenes, including their permethylated variants, are extremely important in organometallic chemistry. In particular, many are synthetically useful either as oxidants (e.g., Cp 2 Fe + ) or as reductants (e.g., Cp 2 Co, Cp* 2 Co, and Cp* 2 Cr). The latter have proven to be useful reagents in the reductive protonation of small-molecule substrates, including N 2 . As such, understanding the behavior of these metallocenes in the presence of acids is paramount. In the present study, we undertake the rigorous characterization of the protonation products of Cp* 2 Co using pulse electron paramagnetic resonance (EPR) techniques at low temperature. We provide unequivocal evidence for the formation of the ring-protonated isomers Cp*(exo/endo-η 4 -C 5 Me 5 H)Co + . Variable temperature Q-band (34 GHz) pulse EPR spectroscopy, in conjunction with density functional theory (DFT) predictions, are key to reliably assigning the Cp*(exo/endo-η 4 -C 5 Me 5 H)Co + species. We also demonstrate that exo-protonation selectivity can be favored by using a bulkier acid and suggest this species is thus likely a relevant intermediate during catalytic nitrogen fixation given the bulky anilinium acids employed. Of further interest, we provide physical data to experimentally assess the C–H bond dissociation free energy (BDFE C–H ) for Cp*(exo-η 4 -C 5 Me 5 H)Co + . These experimental data support our prior DFT predictions of an exceptionally weak C–H bond (<29 kcal mol –1 ), making this system among the most reactive (with respect to C–H bond strength) to be thoroughly characterized. Furthermore, these data also point to the propensity of Cp*(exo-η 4 -C 5 Me 5 H)Co to mediate hydride (H – ) transfer. Our findings are not limited to the present protonated metallocene system. Accordingly, we outline an approach to rationalizing the reactivity of arene-protonated metal species, using decamethylnickelocene as an additional example.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

Orion Absolute Navigation System Progress and Challenges

The Orion spacecraft is being designed as NASA's next-generation exploration vehicle for crewed missions beyond Low-Earth Orbit. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to benchmark the current state of the design and some of the rationale and analysis behind it. There are specific challenges to address when preparing a timely and effective design for the Exploration Flight Test (EFT-1), while still looking ahead and providing software extensibility for future exploration missions. The primary measurements in a Near-Earth or Mid-Earth environment consist of GPS pseudorange and deltarange, but for future explorations missions the use of star-tracker and optical navigation sources need to be considered. Discussions are presented for state size and composition, processing techniques, and consider states. A presentation is given for the processing technique using the computationally stable and robust UDU formulation with an Agee-Turner Rank-One update. This allows for computational savings when dealing with many parameters which are modeled as slowly varying Gauss-Markov processes. Preliminary analysis shows up to a 50% reduction in computation versus a more traditional formulation. Several state elements are discussed and evaluated, including position, velocity, attitude, clock bias/drift, and GPS measurement biases in addition to bias, scale factor, misalignment, and non-orthogonalities of the accelerometers and gyroscopes. Another consideration is the initialization of the EKF in various scenarios. Scenarios such as single-event upset, ground command, pad alignment, cold start are discussed as are strategies for whole and partial state updates as well as covariance considerations. Strategies are given for dealing with latent measurements and high-rate propagation using multi-rate architecture. The details of the rate groups and the data ow between the elements is discussed and evaluated.

Holt, Greg N.↗

DOE OSTI2023

Bayes goes fast: Uncertainty quantification for a covariant energy density functional emulated by the reduced basis method

A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the calibration is enabled by the emulation of the high-fidelity model through the implementation of a reduced basis method (RBM)—a set of dimensionality reduction techniques that can speed up demanding calculations involving partial differential equations by several orders of magnitude. The RBM emulator we build—using only 100 evaluations of the high-fidelity model—is able to accurately reproduce the model calculations in tens of milliseconds on a personal computer, an increase in speed of nearly a factor of 3,300 when compared to the original solver. Besides the analysis of the posterior distribution of parameters, we present model calculations for masses and radii with properly estimated uncertainties. We also analyze the model correlation between the slope of the symmetry energy L and the neutron skin of 48 Ca and 208 Pb. The straightforward implementation and outstanding performance of the RBM makes it an ideal tool for assisting the nuclear theory community in providing reliable estimates with properly quantified uncertainties of physical observables. Such uncertainty quantification tools will become essential given the expected abundance of data from the recently inaugurated and future experimental and observational facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2012

The Economics of NASA Mission Cost Reserves

Increases in NASA mission costs are well-noted but not well-understood, and there is little evidence that they are decreasing in frequency or amount over time. The need to control spending has led to analysis of the causes and magnitude of historical mission overruns, and many program control efforts are being implemented to attempt to prevent or mitigate the problem (NPR 7120). However, cost overruns have not abated, and while some direct causes of increased spending may be obvious (requirements creep, launch delays, directed changes, etc.), the underlying impetus to spend past the original budget may be more subtle. Gaining better insight into the causes of cost overruns will help NASA and its contracting organizations to avoid .them. This paper hypothesizes that one cause of NASA mission cost overruns is that the availability of reserves gives project team members an incentive to make decisions and behave in ways that increase costs. We theorize that the presence of reserves is a contributing factor to cost overruns because it causes organizations to use their funds less efficiently or to control spending less effectively. We draw a comparison to the insurance industry concept of moral hazard, the phenomenon that the presence of insurance causes insureds to have more frequent and higher insurance losses, and we attempt to apply actuarial techniques to quantifY the increase in the expected cost of a mission due to the availability of reserves. We create a theoretical model of reserve spending motivation by defining a variable ReserveSpending as a function of total reserves. This function has a positive slope; for every dollar of reserves available, there is a positive probability of spending it. Finally, the function should be concave down; the probability of spending each incremental dollar of reserves decreases progressively. We test the model against available NASA CADRe data by examining missions with reserve dollars initially available and testing whether they are more likely to spend those dollars, and whether larger levels of reserves lead to higher cost overruns. Finally, we address the question of how to prevent reserves from increasing mission spending without increasing cost risk to projects budgeted without any reserves. Is there a "sweet spot"? How can we derive the maximum benefit associated with risk reduction from reserves while minimizing the effects of reserve spending motivation?

Whitley, Sally↗

DOE OSTI2022

Probing elemental speciation in hydrochar produced from hydrothermal liquefaction of anaerobic digestates using quantitative X-ray diffraction

Valorization of hydrochar, a solid byproduct from hydrothermal liquefaction (HTL) of anaerobically-digested agriculture wastes (digestates), requires fundamental knowledge of elemental speciation. This study investigated the effects of reaction temperatures (320–360 °C), digestate pH (3.5–8), and digestate cellulose-to-lignin ratios (0.2–1.8) on the speciation (chemical form) and composition of organics and inorganics in hydrochars produced during hydrothermal treatment. Quantitative X-ray diffraction (XRD) method was the primary technique used to characterize hydrochars. The comprehensive XRD pattern processing including the Rietveld refinement protocols demonstrated that the organic phase was comprised of mostly crystalline monocyclic, heterocyclic, and polycyclic aromatics with diverse aliphatic and aromatic substituents, while the inorganic mineral phase consisted of calcium-phosphates, magnesium-phosphates, calcium-carbonates, and magnesium-carbonates. Further, XRD results were validated by the elemental yields of products and the distribution of chemical functionalities measured using solid-state nuclear magnetic resonance (NMR) spectroscopy. The characterization data were used to evaluate proposed mechanistic pathways using compositional analysis of biocrude and aqueous-phase coproducts. Mechanistic pathways developed in the study suggested that benzoic acids, phenols, benzaldehydes, phenolic aldehydes, α-dicarbonyls, and α-hydroxycarbonyls were responsible for the precipitation of organics through various reactions depending on operating conditions. Meanwhile, the formation of inorganic compounds appeared to be consistently represented by reactions including dehydration, hydrolysis, endergonic reduction, and structure rearrangement of native minerals in the digestates. This study provides basic knowledge needed to create and assess potential elemental speciation pathways. In addition, the results of the study facilitate the specification of process conditions to optimize targeted utilization routes of hydrochar for more economically-feasible and sustainable HTL processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Document-Based Nuclear Archaeology

Deeper reductions in the nuclear arsenals will require better understanding of historic fissile material management and production. The concept of “nuclear archaeology” has been considered since the 1990s to provide the tools and methods to develop independent production estimates, primarily based on nuclear forensic techniques. Here, we propose to add a framework for reconstructing the history of a nuclear program that complements traditional nuclear archaeology techniques by examining the role of operating records to support such an effort. As a test case, we use the JEEP II reactor, a 2 MW civilian research reactor at Norway’s Institute for Energy Technology (IFE), in operation for more than fifty years, however, recently shut down permanently. We have collected, analyzed, and started to preserve the reactor’s operating records, which exist on both analog and digital media, and to simulate parts of its history using OpenMC/ONIX neutronics calculations. Here, a particular focus of this project has been on digital data curation and preservation to confirm and maintain the integrity, authenticity, and provenance of these records. In developing guidelines for best practices that conform to existing standards for long-term digital preservation and curation, we hope this project can help lay the basis for future nuclear archaeology efforts to support nuclear arms control and disarmament.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2023

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Characterization of Highly Active Cells in Preparation for Post Operational Clean Out at Sellafield - 18139

The Highly Active Liquor Evaporation and Storage (HALES) Plant at Sellafield receives highly active (HA) raffinate liquors from the Magnox and Thermal Oxide (THoRP) Reprocessing Plants. These liquors are concentrated through evaporation into Highly Active Liquor (HAL), conditioned and stored in HALES before immobilisation in glass in the Waste Vitrification Plant (WVP). Reprocessing operations at Sellafield are nearing completion and hence these liquor feeds will soon cease. Therefore, HALES is starting its planning and preparation phases for Post Operational Clean Out (POCO) and decommissioning. POCO is a transitional phase between operations and decommissioning and encompasses activities undertaken to remove residual inventory and activity from the facility. Key drivers for POCO include risk and hazard reduction and facilitating subsequent decommissioning activities (including potential surveillance and maintenance or care and maintenance regimes). Characterization is a critical enabler for development and implementation of effective POCO. In addition to the key drivers above characterization within HALES will be used to: - Define the start and end points of POCO (radiological condition, inventory sources and location, configuration, etc.); - Develop and technically underpin the wash out strategy (volumes, rates, reagent types, etc.; - Monitor the effectiveness of POCO activities (reduction in inventory/activity, points of diminishing return, confirmation of end points for POCO). There are a number of significant challenges that present to characterization of the HALES facilities. Perhaps the most significant of these is the radiological status of the facility. HALES is an HA facility meaning that the high dose rates limit not only the technology selection for characterization (i.e. those with a very high radiation tolerance) but also place constraints on the access and deployment for the selected technology. Additionally, parts of the facility are circa 60 years old which brings its own challenges such as poor quality construction drawings and limited operational knowledge. Finally, limited sampling capability and minimal data regarding historic operations has resulted in uncertainties that will need to be addressed in order to undertake POCO as efficiently and effectively as possible. The solution to this challenge requires a novel and innovative approach and an example of this is the technique which is described in this paper. This is a radiometric characterization technique which utilizes remotely deployed dosimetry to determine the activity distribution within the vessels of interest to POCO. The results to date have been extremely promising, and the ability to produce concise visual representation of these results has already begun to facilitate better informed discussions around the POCO of the facility. It is expected that in the future this technique will be applicable to other areas of Sellafield which face similar characterization challenges. This paper presents a summary of the development and implementation of the solution along with the results obtained so far. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Multicriteria-Based Selection of Microalgae Biorefineries: Biomass Composition Defines the Most Suitable Product Portfolios

The supply of microalgae-derived biofuels and bioproducts will be vital in a global-scale bioeconomy. As the diversity of microalgae strains and their compositional plasticity may yield a wide array of products of market interest, the design of effective biorefineries is a central aspect in the path to making microalgae-based products available in the market. In this way, the conversion of microalgae biomass should be planned to employ mature technologies, while maximizing economic and environmental benefits obtained from a diverse product portfolio. This study applied sequential, hybrid Multicriteria Decision Analyses (MCDA) to aid the decision-making process of outlining the most suitable biorefining pathways for specific compositional profiles. For this, the methodology simultaneously considered multiple technical, economic, and environmental criteria, such as market aspects for the main algae-derived products, potential reduction in greenhouse gas (GHG) emissions provided by the biobased alternatives, and technology readiness level of conversion routes, among others. The framework was tested using productivity and compositional data for 13 high-productivity summer strains cultivated under varying nutrient availability. The analysis pointed to compositional profile being a key driver in defining the core biorefining strategy of algae biomass, with lipid-to-carbohydrate ratios higher than roughly 1 warranting the preferential processing of lipids into hydrocarbon fuels with the remainder of the algae biomass compounds being sent to higher-value applications, such as carboxylic acids and renewable thermoplastic substitutes. An in-depth process simulation, techno-economic assessment (TEA), and life-cycle analysis (LCA) effort was carried out as a closing step to corroborate the results stemming from the proposed framework. This study validates the use of MCDAs as a screening method prior to implementing more time-consuming analysis techniques and makes a compelling case for this approach as a product selection tool on a wide range of algae species, thus helping establish species-agnostic (but composition-driven) biorefineries.

biofuels↗