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NASA NTRS2013

Reducing Organic Contamination in NASA JSC Astromaterial Curation Facility

Future robotic and human spaceflight missions to the Moon, Mars, asteroids and comets will require handling and storing astromaterial samples with minimal inorganic and organic contamination to preserve the scientific integrity of each sample. Much was learned from the rigorous attempts to minimize and monitor organic contamination during Apollo, but it was not adequate for current analytical requirements; thus [1]. OSIRIS-REx, Hayabusa-2, and future Mars sample return will require better protocols for reducing organic contamination. Future isolation con-tainment systems for astromaterials, possibly nitrogen enriched gloveboxes, must be able to reduce organic and inorganic cross-contamination. In 2012, a baseline study established the current state of organic cleanliness in gloveboxes used by NASA JSC astromaterials curation labs that could be used as a benchmark for future mission designs [2, 3]. After standard ultra-pure water (UPW) cleaning, the majority of organic contaminates found were hydrocarbons, plasticizers, silicones, and solvents. Hydro-carbons loads (> C7) ranged from 1.9 to 11.8 ng/cm2 for TD-GC-MS wafer exposure analyses and 5.0 to 19.5 ng/L for TD-GC-MS adsorbent tube exposure. Plasticizers included < 0.6 ng/cm2 of DBP, DEP, TXIB, and DIBP. Silicones included < 0.5 ng/cm2 of cyclo(Me2SiO)x (x = 6, 8, 9, 10) and siloxane. Solvents included < 1.0 ng/cm2 of 2-cyclohexen-1-one, 3,5,5-trimethyl- (Isopho-rone), N-formylpiperidine, and 2-(2-butoxyethoxy) ethanol. In addition, DBF, rubber/polymer additive was found at < 0.2 ng/cm2 and caprolactam, nylon-6 at < 0.6 ng/cm2. Reducing Organics: The Apollo program was the last sam-ple return mission to place high-level organic requirements and biological containment protocols on a curation facility. The high vacuum complex F-201 glovebox in the Lunar Receiving Labora-tory used ethyl alcohol (190 proof), 3:1 benzene/methanol (nano grade solution), and heat sterilization at 130degC for 48 hours to reduce organic contamination. In addition, both heat sterilization and peracetic acid sterilization were used in the atmospheric de-contamination (R) cabinets. Later, Lunar curation gloveboxes were degreased with a pressurized Freon 113 wash. Today, UPW has replaced Freon as the standard cleaning procedure, but does not have the degreasing solvency power of Freon. Future Cleaning Studies: Cleaning experiments are cur-rently being orchestrated to study how to degrease and reduce organics in a JSC curation glovebox lower than the established baseline. Several new chemicals in the industry have replaced traditional degreasing solvents such as Freon and others that are now federally restricted. However, these new suites of chemicals remain untested for lowering organics in curation gloveboxes. 3M's HFE-7100DL and DuPont's Vertrel XF are currently being tested as a replacement for Freon 113 as a degreaser at JSC cura-tion facilities. In addition, the use of UPW as a final rinse is be-ing tested, which presumably can maintain a lower total organic carbon load than the filtered purity of chemical solutions. References: [1] Allton J.H. et al. (2012) LPS XLIII, 2439; [2] Calaway M.

Calaway, M. J.↗

NASA NTRS2015

Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis

This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.

0000↗

NASA NTRS2017

The Effectiveness of Shrouding on Reducing Meshed Spur Gear Power Loss - Test Results

Gearbox efficiency is reduced at high rotational speeds due to windage drag and viscous effects on rotating, meshed gear components. A goal of NASA aeronautics rotorcraft research is aimed at propulsion technologies that improve efficiency while minimizing vehicle weight. Specifically, reducing power losses to rotorcraft gearboxes would allow gains in areas such as vehicle payload, range, mission type, and fuel consumption. To that end, a gear windage rig has been commissioned at NASA Glenn Research Center to measure windage drag on gears and to test methodologies to mitigate windage power losses. One method used in rotorcraft gearbox design attempts to reduce gear windage power loss by utilizing close clearance walls to enclose the gears in both the axial and radial directions. The close clearance shrouds result in reduced drag on the gear teeth, and reduced power loss. For meshed spur gears, the shrouding takes the form of metal side plates and circumferential metal sectors. Variably positioned axial and radial shrouds are incorporated in the NASA rig to study the effect of shroud clearance on gearbox power loss. A number of researchers have given experimental and analytical results for single spur gears, with and without shrouding. Shrouded meshed spur gear test results are sparse in the literature. Windage tests were run at NASA Glenn using meshed spur gears at four shroud configurations: unshrouded, shrouded (max. axial, max radial), and two intermediate shrouding conditions. Results are compared to available meshed spur gear power loss data analyses as well as single spur gear data/analyses. Recommendations are made for future work.

power loss↗

NASA NTRS2017

Impact Delivery of Reduced Greenhouse Gases on Early Mars

Reducing greenhouse gases are once again the latest trend in finding solutions to the early Mars climate dilemma. In its current form - as proposed by Ramirez et al. [1], later refined by Wordsworth et al. [2], and confirmed by Ramirez [3] - collision induced absorptions between CO2-H2 or CO2-CH4 provide enough extra greenhouse power to raise global mean surface temperatures to the melting point of water provided the atmosphere is thick enough and the reduced gases are abundant enough. To raise surface temperatures significantly by this mechanism, surface pressures must be at least 500 mb and H2 and/or CH4 concentrations must be at or above the several percent level. Both Wordsworth et al. [2] and Ramirez [3] show that the melting point can be reached in atmospheres with 1-2 bars of CO2 and 2-10% H2; smaller concentrations of H2 will suffice if CH4 is also present. If thick weakly reducing atmospheres are the solution to the faint young Sun paradox, then plausible mechanisms must be found to generate and sustain the gases. Possible sources of reducing gases include volcanic outgassing, serpentinization, and impact delivery; sinks include photolyis, oxidation, and escape to space. The viability of the reduced greenhouse hypothesis depends, therefore, on the strength of these sources and sinks.

greenhose gases↗

NASA NTRS2017

The Effectiveness of Shrouding on Reducing Meshed Spur Gear Power Loss Test Results

Gearbox efficiency is reduced at high rotational speeds due to windage drag and viscous effects on rotating, meshed gear components. A goal of NASA aeronautics rotorcraft research is aimed at propulsion technologies that improve efficiency while minimizing vehicle weight. Specifically, reducing power losses to rotorcraft gearboxes would allow gains in areas such as vehicle payload, range, mission type, and fuel consumption. To that end, a gear windage rig has been commissioned at NASA Glenn Research Center to measure windage drag on gears and to test methodologies to mitigate windage power losses. One method used in rotorcraft gearbox design attempts to reduce gear windage power loss by utilizing close clearance walls to enclose the gears in both the axial and radial directions. The close clearance shrouds result in reduced drag on the gear teeth and reduced power loss. For meshed spur gears, the shrouding takes the form of metal side plates and circumferential metal sectors. Variably positioned axial and radial shrouds are incorporated in the NASA rig to study the effect of shroud clearance on gearbox power loss. A number of researchers have given experimental and analytical results for single spur gears, with and without shrouding. Shrouded meshed spur gear test results are sparse in the literature. Windage tests were run at NASA Glenn using meshed spur gears at four shroud configurations: unshrouded, shrouded (max. axial, max. radial), and two intermediate shrouding conditions. Results are compared to available meshed spur gear power loss data analyses as well as single spur gear data analyses.

windage↗

NASA NTRSDate not supplied

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

The spread of flames over the surface of solid combustible materials is affected by the environmental conditions. Variables such as flow velocity, oxygen concentration, ambient pressure, partial gravity or microgravity, may change the material flammability and influence the fire dynamics. This is an important fire safety issue for space exploration vehicles and space habitats which will very likely have different environments than those currently used on the International Space Station, such as reduced pressure and enriched oxygen concentration (SEA). However, testing experimentally the materials to be used and qualified for space exploration under these conditions is a difficult and expensive task. Here, numerical modeling is used to understand the dominant physico-chemical processes on the concurrent flame spread over thin fabrics under reduced ambient pressure (and in turn, buoyancy) and variable gravitational conditions. The numerical model uses the Fire Dynamics Simulator (FDS6) code with a single-step Arrhenius reaction rate for the solid phase decomposition. Different models are tested for the gas phase combustion kinetics. The model results are validated with experimental results obtained at similar reduced ambient pressure and flow conditions at 1 g. It is shown that as ambient pressure is reduced the flame spread rate over a thin fabric is also reduced, both experimentally and numerically. Numerical results are compared to an analytical approach previously developed to explain the experimental trends. Further interpretation of the model results provides information regarding the physics of the process and how they are affected by the lower pressure environments and gravity conditions. The results of this work provide guidance for potential on-earth testing for fire safety design in spacecraft and space habitats.

Fire Safety↗

NASA NTRSDate not supplied

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

microgravity↗

DOE OSTI2025

A Parametric, Data-Driven, Non-Intrusive Reduced-Order Model Framework for Crystal Plasticity Simulations of Voids

The influence of the internal structure at micrometer length scales on the deformation of polycrystalline materials can be effectively captured using crystal plasticity finite element methods (CPFEM). However, the complexity and nonlinearity of the deformation equations CPFEM solves demand significant computational power and resources to achieve accurate predictions, limiting its broader application. To address this challenge, we have identified a reduced-order representation of the complex data in order to establish a computationally efficient reduced-order models (ROM) and drastically reduce the computational expense of CPFEM. Specifically, in this work, we developed a parametric, data-driven, and non-intrusive ROM framework for CPFEM using proper orthogonal decomposition (POD) and sparse variational Gaussian process (SVGP) regression for single-crystal microstructures under tensile loading conditions. The developed protocol enables one to compress field into a latent/low-dimensional space described by principal component analysis (PCA) via the singular value decomposition (SVD) algorithm. As a result, the high-dimensional data are reduced to a significantly smaller amount of dimensions with POD bases and POD coefficients. Furthermore, we deployed an ensemble of SVGPs—extended from the classical Gaussian process (GP) regression for scalability and handling big data—in a massively parallel manner to train and predict latent POD coefficients using known POD bases from a set of previously obtained simulations results. Lastly, using the predicted POD coefficients, we reconstructed the full-field results and showed reasonable agreement compared with the true values obtained from running CPFEM. The developed framework is validated with a set of CPFEM simulations of a single embedded void in single-crystal aluminum alloy. While the framework is broadly applicable, this work specifically focuses on single-crystal microstructures, a single load case (e.g., tensile), and a specific void geometry (spherical).

Anisotropy↗

DOE OSTI2023

Reduced chemical kinetic model for CH 4 -air non-premixed flames including excited and charged species

Electric fields can impact small laminar flames by changing their shape and overall behavior by acting on charged species produced in combustion. However, no reduced chemical kinetic model has been developed considering both major species and minor species related to flame characterization and flame behavior in the presence of an electric field. Here, this study presents a reduced chemical kinetic model for methane-air combustion which includes minor excited species (CH*and OH*) and charged species (H 3 O + , HCO + , C 2 H 3 O + , CH 5 O + , O$_{2}^{–}$, OH – , e – , CO$_{3}^{–}$, CHO$_{2}^{–}$, O – , CHO$_{3}^{–}$). The results employing the reduced chemistry model have been validated for a two-dimensional flame geometry by comparison with (i) detailed chemistry simulation results for species location and peak values, and (ii) experimental CH* chemiluminescence location, considering the self-repulsion of charges yet without externally applied electric field to the flame. This reduced chemical kinetic model, with 45 species and 216 reactions, shows a computational demand one-third that of employing its equivalent detailed chemistry (83 species and 394 reactions). The reduction is modest but significant considering that high fidelity is needed to capture the behavior of the chemi-ion and chemiluminescent species. Future works will involve the use of this model for simulations predicting flame behavior with applied electric field (i.e., field strength ≠0 kV/cm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Reduced-Order Modeling Method for Phase-Change Thermal Energy Storage Heat Exchangers

Thermal energy storage can facilitate the effective utilization of renewable energy. To speed up the design process of thermal energy storage devices, it is critical to develop fast and accurate modeling methods for phase change material embedded heat exchangers (PCM HXs). This study developed and compared two approximation-assisted reduced-order PCM HX models for the simulation of thermal storage components and systems, which were verified against a validated finite-volume model. They are a pure black-box model, and a grey-box model based on the Number of Transfer Units (or effectiveness-NTU) approach. We used the reduced-order models to predict the performance of standalone PCM HX for 1000 cases with different fluid inlet conditions and HX designs. We also integrated the models with a vapor compression system to predict the compressor energy consumption and total charging time under various conditions. The results show that overall, the black-box model gave more accurate results than the grey-box model. On average, the mean absolute deviation in the PCM HX fluid outlet temperature was 0.05 K and 0.1 K for the black-box model and grey-box model, respectively. The grey-box model gave larger temperature deviation toward the end of the phase change process, due to the simplified two-node PCM representation. On the system level, the mean absolute deviation in compressor energy consumption was 0.2% and 0.3% for the black-box model and grey-box model, respectively. Their mean absolute deviation in total charging time was 1.1% and 2.6%, respectively. In terms of computation efficiency, the system simulation speedup ratio gained by using the reduced-order models was 11 to 57. System simulation time was decreased from an average of 1465 s to an average of 59 s. This shows that the proposed reduced-order modeling methods can be used to predict system performance of PCM HXs with less than 3% accuracy penalty, and 25 times less computational time than finite-volume models, enabling faster design and evaluation of PCM thermal storage devices.

25 ENERGY STORAGE↗

DOE OSTI2020

Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference

This work introduces a method for learning low-dimensional models from data of high-dimensional black-box dynamical systems. The novelty is that the learned models are exactly the reduced models that are traditionally constructed with classical projection-based model reduction techniques. Thus, the proposed approach learns models that are guaranteed to have the well-studied properties of reduced models known from model reduction, without requiring full knowledge of the governing equations and without requiring the operators of the high-dimensional systems. The key ingredient is a new data sampling scheme to obtain re-projected trajectories of high-dimensional systems that correspond to Markovian dynamics in low-dimensional subspaces. The exact recovery of reduced models from these re-projected trajectories is guaranteed pre-asymptotically under certain conditions for finite amounts of data and for a large class of systems with polynomial nonlinear terms. Numerical results demonstrate that the low-dimensional models learned with the proposed approach match reduced models from traditional model reduction up to numerical errors in practice. In conclusion, the numerical results further indicate that low-dimensional models fitted to re-projected trajectories are predictive even in situations where models fitted to trajectories without re-projection are inaccurate and unstable.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models

While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms with a much smaller dimension. The goal of this work is to introduce the points selection algorithm developed by Shin and Xiu as a hyper-reduction method. The selection algorithm was originally proposed as a stochastic collocation method for uncertainty quantification. Since the algorithm aims at maximizing a quantity $\mathcal{S}$ that measures both the column orthogonality and the determinant, we refer to the algorithm as S-OPT. Numerical examples are provided to demonstrate the performance of S-OPT and to compare its performance with a gappy proper orthogonal decomposition (POD) algorithm. Here, we found that using the S-OPT algorithm is shown to predict the full order solutions with higher accuracy than gappy POD especially when the number of sampling points is small, although we note that S-OPT shows slow asymptotic convergence with respect to the number of samples for some applications, e.g., Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Reduced basis approximations of parameterized dynamical partial differential equations via neural networks

Projection-based reduced order models are effective at approximating parameter-dependent differential equations that are parametrically separable. When parametric separability is not satisfied, which occurs in both linear and nonlinear problems, projection-based methods fail to adequately reduce the computational complexity. Devising alternative reduced order models is crucial for obtaining efficient and accurate approximations to expensive high-fidelity models. In this work, we develop a timestepping procedure for dynamical parameter-dependent problems, in which a neural-network is trained to propagate the coefficients of a reduced basis expansion. This results in an online stage with a computational cost independent of the size of the underlying problem. Here, we demonstrate our method on several parabolic partial differential equations, including a problem that is not parametrically separable.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Characterization of a new thermophilic sulfate-reducing bacterium Thermodesulfovibrio yellowstonii, gen. nov. and sp. nov.: its phylogenetic relationship to Thermodesulfobacterium commune and their origins deep within the bacterial domain

A thermophilic sulfate-reducing vibrio isolated from thermal vent water in Yellowstone Lake, Wyoming, USA is described. The gram-negative, curved rod-shaped cells averaged 0.3 micrometer wide and 1.5 micrometers long. They were motile by means of a single polar flagellum. Growth was observed between 40 degrees and 70 degrees C with optimal growth at 65 degrees C. Cultures remained viable for one year at 27 degrees C although spore-formation was not observed. Sulfate, thiosulfate and sulfite were used as electron acceptors. Sulfur, fumarate and nitrate were not reduced. In the presence of sulfate, growth was observed only with lactate, pyruvate, hydrogen plus acetate, or formate plus acetate. Pyruvate was the only compound observed to support fermentative growth. Pyruvate and lactate were oxidized to acetate. Desulfofuscidin and c-type cytochromes were present. The G + C content was 29.5 mol%. The divergence in the 16 S ribosomal RNA sequences between the new isolate and Thermodesulfobacterium commune suggests that these two thermophilic sulfate-reducing bacteria represent different genera. These two bacteria depict a lineage that branches deeply within the Bacteria domain and which is clearly distinct from previously defined phylogenetic lines of sulfate-reducing bacteria. Strain YP87 is described as the type strain of the new genus and species Thermodesulfovibrio yellowstonii.

Non-NASA Center↗

DOE OSTI2024

Use of Lignin-Based Admixture as Water Reducer (WRA) for Tailoring the Rheological Properties of Mortars for 3D-Printing

Efforts towards decarbonizing construction materials and industrial processes related to cement and concrete can be aided via multifaceted approaches that target alternative admixtures as well as precision control of fabrication. Chemical admixtures for water reduction have played a crucial role in the development of advanced mortar and concrete mixtures. Newer biomass processing techniques developed for aviation fuel production from corn stover biomass produce a highly reactive lignin byproduct that is suitable for chemical modifications to mimic the properties of commonly used polycarboxylate ethers (PCEs) with a smaller carbon footprint. These lignin-based plasticizers developed at NREL can be used in place of petrochemical-derived superplasticizers to tailor the rheological properties of cement-based systems for applications such as additive manufacturing while reducing the carbon intensity of the concrete mix. Lignosulfonates derived from paper pulping were historically used as water reducers only to be displaced with the rise of PCEs. The present study examines the use of a NREL produced lignin-based water reducing admixture (WRA), in cement pastes and mortar mixtures for 3D-printing at small- (mm) scale. The experimental program consisted of different formulations of oxidized lignin-based WRAs added in variable dosages to cement pastes with a fixed water-to-cement ratio. The objective is to achieve an appropriate workability, extrudability and buildability of mortar mixtures to produce 3D-printed specimens. The rheological characterization was performed to compare the initial yield stress and viscosity of the different mixtures with lignin-based admixture with respect to conventional PCE superplasticizers. The rheological characterization shows that the proposed material act as an effective water-reducer in cement systems, affecting the yield stress, plastic viscosity, and structuration rate of the mixtures evaluated. On the other hand, the effect on early hydration process of the cement pastes containing lignin-based admixtures is comparable to conventional superplasticizers.

3D-printing↗

DOE OSTI2023

Assessing whole-sounder removal versus traditional control for reducing invasive wild pig ( Sus scrofa ) populations

Trapping is commonly used as the primary management tool in attempts to reduce invasive wild pigs (Sus scrofa), but traditional trapping techniques are often ineffective. However, recently developed traps permit the capture of entire social groups (sounders) of wild pigs, and the strategy of whole-sounder removal may achieve more effective control. Our objective was to experimentally compare traditional control (TC; primarily traditional trapping, but including hunting with dogs, and opportunistic shooting) and whole-sounder removal (WSR) strategies by assessing density reduction and removal rate after 1 and 2 years of treatment. After 1 year of trapping, average wild pig density on WSR units declined 53% and remained stable after the second year, whereas on TC units, pig density did not differ after trapping, although it declined 33% and remained stable after the second year of trapping. The median removal rate (percentage of uniquely marked pigs present at the beginning of each year that were removed) was 42.5% for WSR units and 0.0% for TC units during 2018 and were 29.6% from WSR units and 5.3% from TC units during 2019. WSR removal was more effective at reducing wild pig density than TC, but factors such as previous exposure of this population to traditional traps and the lack of barriers to recolonization from surrounding areas may have reduced WSR efficacy. WSR can effectively reduce wild pig density to a greater extent than TC, but managers should recognize the additional time and expense necessary for implementation.

Sus scrofa↗

DOE OSTI2023

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [ 18 F]flutemetamol and [ 18 F]florbetaben. Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [ 18 F]flutemetamol (N = 175) or [ 18 F]florbetaben (N = 75). PET scans were acquired in list-mode (90–110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [ 18 F]flutemetamol and [ 18 F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. This proof-of-concept study showed that for both [ 18 F]flutemetamol and [ 18 F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

62 RADIOLOGY AND NUCLEAR MEDICINE↗