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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Preliminary structural assessment of VHTR graphite components according to ASME code - 18532

In this study, a preliminary structural assessment on a graphite component of a VHTR was done in accordance with the semi-probabilistic assessment procedures of the latest 2015 edition of the ASME Boiler and Pressure Vessel Code, Section III, Div. 5, Subpart HHA-Graphite Materials. Establishment of the Weibull distribution for the tensile strength is essential to set up the stress limits based on the probability of failure of the graphite materials. All parameters required in the ASME code were identified and evaluated for a nuclear graphite material, IG-110. The assessment of design level was done on one of fuel elements in a Korean VHTR design by two methodologies in the ASME code: (1) Simplified assessment and (2) Full assessment. The structural integrity of the fuel element was assured by both assessment methods. Also, the effect of the number of integration volume groups on the probability of failure in the full assessment was investigated and a recommendation for the conservative results was suggested. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of Plasmodium falciparum pfhrp2 and pfhrp3 gene deletions and performance of a rapid diagnostic test for identifying asymptomatic malaria infection in northern Ethiopia, 2015

Background: Rapid diagnostic tests (RDTs) are widely used for malaria diagnosis of both symptomatic and asymptomatic infections. Although RDTs are a reliable and practical diagnostic tool, the sensitivity of histidine-rich protein 2 (HRP2)-based RDTs can be reduced if pfhrp2 or pfhrp3 (pfhrp2/3) gene deletions exist in the Plasmodium falciparum parasite population. This study evaluated dried blood spot (DBS) samples collected from a national household survey to investigate the presence of pfhrp2/3 deletions and the performance of the RDT used in the cross-sectional survey in a low transmission setting. Methods: The 2015 Ethiopia Malaria Indicator Survey tested household members by RDT and collected DBS samples. DBS (n = 2648) from three regions in northern Ethiopia were tested by multiplex bead-based antigen detection assay after completion of the survey. The multiplex assay detected pan-Plasmodium lactate dehydrogenase (LDH), pAldolase, and HRP2 antigens in samples. Samples suspected for pfhrp2/3 gene deletions (pLDH and/or pAldolase positive but low or absent HRP2) were further investigated by molecular assays for gene deletions. Antigen results were also compared to each individual’s RDT results. Dose–response logistic regression models were fit to estimate RDT level of detection (LOD) antigen concentrations at which 50, 75, 90, and 95% of the RDTs returned a positive result during this survey. Results: Out of 2,648 samples assayed, 29 were positive for pLDH or pAldolase antigens but low or absent for HRP2 signal, and 15 of these samples (51.7%) were successfully genotyped for pfhrp2/3. Of these 15 P. falciparum infections, eight showed single deletions in pfhrp3, one showed a single pfhrp2 deletion, and six were pfhrp2/3 double-deletions. Six pfhrp2 deletions were observed in Tigray and one in Amhara. Twenty-five were positive for HRP2 by the survey RDT while the more sensitive bead assay detected 30 HRP2-positive samples. A lower concentration of HRP2 antigen generated a positive test result by RDT compared to pLDH (95% LOD: 16.9 ng/mL vs. 319.2 ng/mL, respectively). Conclusions: There is evidence of dual pfhrp2/3 gene deletions in the Tigray and Amhara regions of Ethiopia in 2015. As the prevalence of malaria was very low (< 2%), it is difficult to make strong conclusions on RDT performance, but these results challenge the utility of biomarkers in household surveys in very low transmission settings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-129: Atlas Development for Cardiac Automatic Contouring Using Multi-Atlas Segmentation

Purpose: To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity. Methods: Six thoracic cancer patients with both contrast and non-contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non-contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fused using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in-house multi-atlas segmentation. Using leave-one-out test, we generated auto-segmented contours for each ROI and each patient. The auto-segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: Inter-observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto-segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm. Conclusion: A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need for auto-segmented contours of indistinguishable small structures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Evaluation of advanced automatic PET segmentation methods using nonspherical thin-wall inserts

Purpose: The use of positron emission tomography (PET) within radiotherapy treatment planning requires the availability of reliable and accurate segmentation tools. PET automatic segmentation (PET-AS) methods have been recommended for the delineation of tumors, but there is still a lack of thorough validation and cross-comparison of such methods using clinically relevant data. In particular, studies validating PET segmentation tools mainly use phantoms with thick plastic walls inserts of simple spherical geometry and have not specifically investigated the effect of the target object geometry on the delineation accuracy. Our work therefore aimed at generating clinically realistic data using nonspherical thin-wall plastic inserts, for the evaluation and comparison of a set of eight promising PET-AS approaches. Methods: Sixteen nonspherical inserts were manufactured with a plastic wall of 0.18 mm and scanned within a custom plastic phantom. These included ellipsoids and toroids derived with different volumes, as well as tubes, pear- and drop-shaped inserts with different aspect ratios. A set of six spheres of volumes ranging from 0.5 to 102 ml was used for a baseline study. A selection of eight PET-AS methods, written in house, was applied to the images obtained. The methods represented promising segmentation approaches such as adaptive iterative thresholding, region-growing, clustering and gradient-based schemes. The delineation accuracy was measured in terms of overlap with the computed tomography reference contour, using the dice similarity coefficient (DSC), and error in dimensions. Results: The delineation accuracy was lower for nonspherical inserts than for spheres of the same volume in 88% cases. Slice-by-slice gradient-based methods, showed particularly lower DSC for tori (DSC < 0.5), caused by a failure to recover the object geometry. The region-growing method reached high levels of accuracy for most inserts (DSC > 0.76 except for tori) but showed the largest errors in the recovery of pears and drops dimensions (higher than 10% and 30% of the true length, respectively). Large errors were visible for one of the gradient-based contouring methods when delineating drop-shaped inserts. Low DSC due to systematic underestimation of the volumes was observed for our fuzzy clustering method when using nonspherical inserts. The adaptive iterative thresholding method produced the highest DSC score on our nonspherical dataset (DSC > 0.83, except for tori) and showed robustness to the insert geometry. Conclusions: This study investigated the accuracy of eight PET-AS methods for the delineation of objects with a range of nonspherical geometries. The authors’ results confirmed the robustness of some segmentation approaches, but also showed the weaknesses of some of the other methods implemented, which were not observed with spherical inserts. This work therefore highlights the importance of using a variety of thin-wall inserts with complex geometries for the validation of PET-AS methods and provided useful information for further development of the methods tested.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

TROPoe retrievals from SGP C1

The TROPoe (formerly called AERIoe) algorithm (Turner and L&ouml;hnert 2014, 2021; Turner and Blumberg 2019) retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The data can be used to characterize the evolution of the planetary boundary layer and boundary layer clouds. This data set was collected at the ARM SGP Central Facility (CF) during and after the MicroPulse DIAL Demonstration (MPDDEMO) field campaign. The TROPoe retrieval was run at 5-minute resolution, but retrievals can be performed at the maximum temporal resolution of the AERI instrument (order 30 s) -- if this higher temporal resolution is desired, please contact Dave Turner. This is a physical-iterative retrieval method. The retrieval of thermodynamic profiles from spectral infrared radiance observations is an ill-posed problem, and thus constraints need to be included in the retrieval algorithm to provide physically plausible results. Here, we use a climatology of radiosonde profiles collected at the ARM SGP site during the summer as our prior information in an optimal estimation framework. Surface meteorology and output from the rapid-refresh (RAP) numerical weather prediction model (above 4 km) were used as additional constraints by the retrieval. As the method uses an optimal estimation framework, a full error covariance matrix of each solution is included in the output file. The 1-sigma uncertainty of each retrieved variable, which is derived from the error covariance matrix, is included for each scientific field and is named "sigma_X", where "X" is the name of the scientific field (e.g., 'temperature'). The information content in the AERI observations, which is in the "dfs" field, on the thermodynamic profiles is primarily concentrated in the lowest 3 km or up to cloud base; the retrieved data should not be used above that level (or used with caution). There is an overall "qc_flag" field that is set when a retrieval should not be trusted. However, the logic that sets this flag did not work correctly, and it should not be used. Instead, consider all retrievals that have a value for "converged_flag" greater than 0 as valid. If you have any questions, contact Dave Turner. This is Release_2_12 of the TROPoe algorithm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗
DOE OSTI2023

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗
DOE OSTI2019

Influence of pseudopotentials on excitation energies from selected configuration interaction and diffusion Monte Carlo

Due to their diverse nature, the faithful description of excited states within electronic structure theory methods remains one of the grand challenges of modern theoretical chemistry. Quantum Monte Carlo (QMC) methods have been applied very successfully to ground state properties but still remain generally less effective than other non-stochastic methods for electronically excited states. Nonetheless, we have recently reported accurate excitation energies for small organic molecules at the fixed-node diffusion Monte Carlo (FN-DMC) within a Jastrow-free QMC protocol relying on a deterministic and systematic construction of nodal surfaces using the selected configuration interaction (sCI) algorithm known as CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively). Albeit highly accurate, these all-electron calculations are computationally expensive due to the presence of core electrons. One very popular approach to remove these chemically-inert electrons from the QMC simulation is to introduce pseudopotentials (also known as effective core potentials). Taking the water molecule as an example, we investigate the influence of Burkatzki-Filippi-Dolg (BFD) pseudopotentials and their associated basis sets on vertical excitation energies obtained with sCI and FN-DMC methods. Although these pseudopotentials are known to be relatively safe for ground state properties, we evidence that special care may be required if one strives for highly accurate vertical transition energies. Indeed, comparing all-electron and valence-only calculations, we show that using pseudopotentials with the associated basis sets can induce differences of the order of 0.05 eV on the excitation energies. Fortunately, a reasonable estimate of this shift can be estimated at the sCI level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. Finally, we anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Noble gas encapsulation into carbon nanotubes: Predictions from analytical model and DFT studies

The energetics for the interaction of the noble gas atoms with the carbon nanotubes (CNTs) are investigated using an analytical model and density functional theory calculations. Encapsulation of the noble gas atoms, He, Ne, Ar, Kr, and Xe into CNTs of various chiralities is studied in detail using an analytical model, developed earlier by Hill and co-workers. The constrained motion of the noble gas atoms along the axes of the CNTs as well as the off-axis motion are discussed. Analyses of the forces, interaction energies, acceptance and suction energies for the encapsulation enable us to predict the optimal CNTs that can encapsulate each of the noble gas atoms. We find that CNTs of radii 2.98 − 4.20 Å (chiral indices, (5,4), (6,4), (9,1), (6,6), and (9,3)) can efficiently encapsulate the He, Ne, Ar, Kr, and Xe atoms, respectively. Endohedral adsorption of all the noble gas atoms is preferred over exohedral adsorption on various CNTs. The results obtained using the analytical model are subsequently compared with the calculations performed with the dispersion-including density functional theory at the M06 − 2X level using a triple-zeta basis set and good qualitative agreement is found. The analytical model is however found to be computationally cheap as the equations can be numerically programmed and the results obtained in comparatively very less time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS

In the face of atypical weather events, power infrastructure failures, and limited resources for resilience investment, energy decision-makers need data-driven metrics to allocate resilience investments and maximize the reduction of power outage impacts. For state-level planning, for instance, ranking the resilience of each county is key to ensuring effective distribution of resources. In such cases, resilience for each spatial unit is multifaceted and is captured by a set of indicators (i.e., metrics) that can be combined into an overall score that reduces the complexity of power outage dynamics to a single decision metric. However, weighting of these indicators is often addressed by simplifying assumptions (i.e., equal weights) or semi-subjective methods that rely on user-defined weights that can introduce biases (e.g., weighted average score). Within the disaster risk reduction and resilience engineering community, a recurring challenge in multicriteria decision-making is the objective weighting of indicators for composite indices. To address this issue, we have leveraged a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with an entropy-based weighting approach to calculated the integrated scores. This method objectively determines the importance of each metric, better discerns between spatial units (i.e., counties), and offers a more reliable ranking of counties according to their relative resilience attributes. By improving methods for integrating resilience indicators, our approach helps planners and decision-makers prioritize resources more effectively for more efficient resilience investments.

Bhusal, Narayan [Oak Ridge National Laboratory (OR↗
DOE OSTI2015

Searches for a sterile-neutrino admixture in detecting tritium decays in a proportional counter: New possibilities

An experiment aimed at searches for an admixture of a sterile neutrino whosemass is 1 to 8 keV via detecting electrons from tritium decay in a proportional counter is proposed. The admixture in question can be discovered by a specific distortion of the energy spectrum of these electrons. For the above masses, the distortion extends over the whole spectrum; therefore, use can bemade of detectors that have a relatively low energy resolution (about 10 to 15%). A classic proportional counter is a simple and natural choice of detector for the decays of a gaseous tritium. The approach that we propose is novel in two respects. On one hand, the proportional counter used is made as a discrete unit in the form of a fully fused quartz tube. This permits a readout of current signals directly from the anode filament and ensures a high stability in the case of long-term measurements. At the same time, the application of state-of-the-art digital data-acquisition methods will make it possible to perform measurements under conditions of high counting rates—up to 10{sup 6} Hz. As a result, the energy spectrum of electrons from tritium decays that is formed by 10{sup 12} counts could be accumulated within about a month. This data sample would make it possible to set an upper limit in the range of 10{sup −3}–10{sup −5} on a sterile-neutrino admixture at a confidence level of three standard deviations (3σ) for m{sub s} in the range of 1–8 keV, this being one to two orders of magnitude more stringent than present-day limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Biosafety Level 3 Recon Training

The Biosafety Level 3 Recon training is a 3D virtual tool developed for the Counter WMD Analysis Cell (CWAC) and the Asymmetric Warfare Group (AWG) by the Application Modeling and Development Team within the NEN-3 International Threat Reduction Group. The training simulates a situation where friendly forces have secured from hostile forces a suspected bioweapons development laboratory. The trainee is a squad member tasked to investigate the facility, locate laboratories within the facility, and identify hazards to entrants and the surrounding area. Before beginning the 3D simulation, the trainee must select the appropriate MOPP level for entering the facility. The items in the simulation, including inside and outside the bioweapon facility, are items that are commonly used by scientists in Biosafety Level (BSL) laboratories. Each item has clickable red tags that, when activated, give the trainee a brief description of the item and a controllable turn-around view. The descriptions also contain information about potential hazards the item can present. Trainees must find all tagged items in order to complete the simulation, but can also reference descriptions and turn-around view of the items in a glossary menu. Training is intended to familiarize individuals whom have little or no biology or chemistry background with technical equipment used in BSL laboratories. The revised edition of this simulation (Biosafety Level 3 Virtual Lab) changes the trainee into a investigator instead of a military combatant. Many doors now require a virtual badge swipe to open. Airlock doors may come in sets such that the open door must be closed before the next door in the set can be opened. A user interface was added so that the instructor can edit the information about the items (the brief descriptions mentioned above) using the simulation software instead of the previous method of manually entering the material in xml settings files. Facility labels, such as "No Parking" and "Men's room", were changed from Korean, into English. No other changes were made.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Rays for Roots - Integrating Backscatter X-Ray Phenotyping, Modeling and Genetics to Increase Carbon Sequestration and Switchgrass Resource Use (Final Report)

To increase carbon (C) deposition in the soil and enhance crop resource use efficiency, characterizing root form and function is essential. Several root and soil traits have been linked to increased root-to-soil C transfer. Technology that could provide high-resolution characterization of many of these traits in field conditions would revolutionize our ability to study and understand how to increase C sequestration. In this effort, we developed an initial early prototype backscatter X-ray system for non-destructive imaging of root traits. We collected initial backscatter X-ray data in field and lab settings and carried out early analysis of these data. Along with this prototype, we also developed a suite of root phenotyping approaches including advanced minirhizotron image analysis, soil core imaging, and mesocosm imaging. Minirhizotron (MR) tubes are clear tubes inserted into the soil in the field and used to image roots and the surrounding soil. Our team has developed deep learning-based methods that can segment roots from soil that can learn from imprecise image-level labels. The ability to learn or fine-tune our deep learning algorithms from image-level labels allows easier and faster application of these approaches to new locations and new plant species. We have successfully implemented and applied our MR analysis approaches to thousands of switchgrass MR images collected across geographical regions. An advantage of MR imaging is the ability to collect root and soil images over time. Our soil core analysis included collecting hundreds of soil core samples from harvested switchgrass fields and imaging these cores with both X-ray CT and backscatter X-ray imaging. Initial segmentation approaches for the X-ray CT images of these cores have been developed and applied. An advantage of soil core analysis is that it preserves the three-dimensional structures of the roots and soil in the core collected. Our group also developed photogrammetry-based mesocosm root imaging and phenotyping approaches. In this approach, a plant was grown in a large mesocosm with a three-dimensional grid of thin supporting lines inserted throughout the mesocosm. After the plant (and, correspondingly, the root architecture is grown and established) the soil media was removed and the supporting lines approximately preserved the three-dimensional root architecture. Then, we applied photogrammetry techniques to create a three-dimensional digital representation of the root architecture for which we developed analysis algorithms including skeletonization. We carried out our phenotyping development with powerful switchgrass resources and physiological and agroecosystem modeling to deliver novel technology. This project contributes to multiple ARPA-E missions including reduction of foreign imports of energy, reduction of energy-related emissions including greenhouse gases, and ensuring that the United States maintains a technological lead in developing and deploying advanced energy technology. Furthermore, the developed tools could transform public and private plant breeding and could be broadly applicable to other crops and, potentially, other application areas. Our team of engineers, plant and soil scientists, and modelers i) developed an early prototype backscatter X-ray platform that can operate in field conditions; ii) developed a suite of root phenotyping and characterization approaches as described above; iii) developed and carried out plant biology and physiology roots studies and; iv) developed and implemented mechanistic physiological modeling.

42 ENGINEERING↗
DOE OSTI2024

Strategy to Develop a Control Scheme for Core Thermal Performance Optimization

This report outlines a three-year research plan for optimizing reactor core thermal performance through use of a Digital Twin (DT) model and a set of neutron detectors to correspondingly adapt the reactor control strategy. It identifies reactor features and achievable neutron measurements that factor into this optimization task. It considers spatial effects that are important and how they can be managed by a real-time algorithm that controls reactivity actuators. The report presents a set of tasks, along with corresponding methods, for accomplishing this objective. The final task in this set is to validate the combined optimization procedure in the Purdue University’s PUR-1 reactor, for which we have an agreement of understanding. Additionally, we describe an alternative approach for overcoming some of the limitations inherent in the above approach, which includes the computational costs of high-fidelity simulations and achievable integration of neutron measurements into the DT. The proposed algorithms lower the technology readiness level (TRL) of the overall approach as some additional analysis and the development of a new neutron detector concept are necessary. In particular, a sensor measuring the gradient of the neutron flux is required, and the prototype is expected to be validated in the PUR-1 reactor. The potential benefits and the opportunity to significantly push forward the state-of-the-art make this approach worthy of further exploration in the upcoming years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Calibration of Traceable Solid Mock 131 I Phantoms Used in an International SPECT Image Quantification Comparison

The International Atomic Energy Agency (IAEA) has organized an international comparison to assess Single Photon Emission Computed Tomography (SPECT) image quantification capabilities in 12 countries. Iodine-131 was chosen as the radionuclide for the comparison because of its wide use around the world, but for logistical reasons solid 133 Ba sources were used as a long-lived surrogate for 131 I. For this study, we designed a set of solid cylindrical sources so that each site could have a set of phantoms (having nominal volumes of 2 mL, 4 mL, 6 mL, and 23 mL) with traceable activity calibrations so that the results could be properly compared. We also developed a technique using two different detection methods for individually calibrating the sources for 133 Ba activity based on a National standard. This methodology allows for the activity calibration of each 133 Ba source with a standard uncertainty on the activity of 1.4 % for the high-level 2-, 4-, and 6-mL sources and 1.7 % for the lower-level 23 mL cylinders. This level of uncertainty allows for these sources to be used for the intended comparison exercise, as well as in other SPECT image quantification studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

The Current State of Radiation Dosimetry in Radionuclide Therapy

Radionuclide therapy combines the specificity of cancer cell targeting with the well-known cytotoxic effects of ionizing radiation. It has the potential to simultaneously eradicate both the primary tumor site as well as the metastatic extent of the disease throughout the body. Despite these advantages, a major limitation of radionuclide therapy is that conventional internal dosimetry methods have failed to accurately predict treatment outcomes in patients. It has been proposed that this shortcoming is due to the fact that therapeutic dosimetry is typically performed using methods developed for diagnostic imaging that do not consider patient specific anatomy, pharmacokinetics and dose heterogeneity. Even worse, dosimetry methods are often completely neglected during treatment planning and dose prescription is based on Body Surface Area/Weight (BSA/BW) and platelet counts. The most widely used internal dosimetry software is OLINDA/EXM (Organ Level Internal Dose Assessment for Exponential Modeling). OLINDA/EXM calculates absorbed doses using the formulism developed by the Medical Internal Radiation Dose (MIRD) committee of the Society of Nuclear Medicine. In its current implementation, OLINDA/EXM requires the use of S factors, which are derived in phantoms that do not accurately represent the actual patient. In addition, OLINDA/EXM assumes that the activity distribution in each organ and tumor is uniform, when it has been well established that activity distributions are often highly heterogeneous. Furthermore, the tumor is not modeled in the phantom, which introduces additional uncertainties in the calculation. Due to these limitations, there is a clear need for improved dosimetry methods for therapeutic nuclear medicine that utilize patient-specific imaging information. A variety of efforts are currently underway to develop such methods. There are two commercial software packages on the market for voxel level internal dosimetry: STRATOS (Philips Technologies, Aachen, Germany) and VoxelDose (DosiSoft, Cachan, France), but both packages are not widely used in clinical practice. In addition, several academic platforms have been developed. Similar to these offerings, RAPID is a robust, fast and multimodal platform. However, RAPID has been designed with tremendous flexibility to perform accurate dosimetry for any radiopharmaceutical in the pre-clinical and clinical setting in order to aid in drug development and to assist in radionuclide therapy treatment planning. This presentation will overview existing dosimetry platforms while focusing on the Monte Carlo-based platform developed at the University of Wisconsin known as RAPID (Radiopharmaceutical Assessment Platform for Internal Dosimetry). RAPID is a robust and universal platform that can provide accurate 3D internal dosimetry for any radiopharmaceutical during both the pre-clinical and clinical stages of drug development as well as clinical treatment planning in TRT. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗