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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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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The solubility of NdPO 4 and DyPO 4 and stability of Nd and Dy chloride and hydroxyl complexes as a function of pH and salinity to 450 °C

The mobility of rare earth elements (REE) in geological systems is often controlled by the stability of monazite and xenotime, which are important hosts for the light and heavy REE. These REE phosphates constitute important resources and provide information on ore formation conditions and timing due to their uses as geothermometers and geochronometers. While the thermodynamic properties for these minerals are well-established up to high temperature and pressure, the properties for the aqueous REE complexes are not well constrained with limited information up to 300 °C. In this study, the solubility of synthetic NdPO 4 and DyPO 4 endmembers were measured in hydrothermal sub- to supercritical NaCl-bearing aqueous solutions from 350 at saturated water vapor pressure to 450 °C at 700 bar. The speciation of Nd and Dy was determined in acidic to alkaline solutions (pH 25 °C values from 2 to 10), and indicates that the hydroxyl species REE(OH) 2 + and REE(OH) 3 0 predominate at low salinity (0.01 mol/kg NaCl) with some contribution of REE chloride species REECl 2+ and REECl 2 + in acidic fluids. The REE phosphate solubility measured in these experiments is up to two orders of magnitude higher than predicted using existing thermodynamic properties from literature for aqueous species extrapolated from lower temperature data to supercritical conditions. To address this discrepancy, the thermodynamic properties of the REE aqueous species were optimized using GEMSFITS to derive the formation constants for the REE chloride (β Cl ) and hydroxyl (β OH ) complexes in the studied temperature range. This study highlights the importance of the hydroxyl species REE(OH) 2 + and REE(OH) 3 0 over a wide range of pH and temperature. As a result, the revised thermodynamic properties for Dy and Nd chloride and hydroxyl species more accurately predict the solubility of NdPO 4 and DyPO 4 and provide insight into the speciation and mobility of the light and heavy REE in hydrothermal supercritical fluids in the crust.

58 GEOSCIENCES↗
DOE OSTI2016

Impact disruption of gravity-dominated bodies: New simulation data and scaling

We present results from a suite of 169 hydrocode simulations of collisions between planetary bodies with radii from 100 to 1000 km. The simulation data are used to derive a simple scaling law for the threshold for catastrophic disruption, defined as a collision that leads to half the total colliding mass escaping the system post impact. For a target radius 100 ≤ R T ≤ 1000km and a mass M T and a projectile radius r p ≤ R T and mass mp we find that a head-on impact with velocity magnitude v is catastrophic if the kinetic energy of the system in the center of mass frame, K=0.5 M T m p v 2 /(M T +m p ) exceeds a threshold value K* that is a few times U= (3/5) GM$2\atop{T}$/RT+ (3/5) Gm$2\atop{p}$/r p + GM T m p /(R T +r p ), the gravitational binding energy of the system at the moment of impact; G is the gravitational constant. In all head-on collision runs we find K* = (5.5 ± 2.9) U. Oblique impacts are catastrophic when the fraction of kinetic energy contained in the volume of the projectile intersecting the target during impact exceeds ~2 K* for 30° impacts and ~3.5 K* for 45° impacts. We compare predictions made with this scaling to those made with existing scaling laws in the literature extrapolated from numerical studies on smaller targets. We find significant divergence between predictions where in general our results suggest a lower threshold for disruption except for highly oblique impacts with rp << RT. Lastly, this has implications for the efficiency of collisional grinding in the asteroid belt (Morbidelli et al., [2009] Icarus, 204, 558–573), Kuiper belt (Greenstreet et al., [2015] Icarus, 258, 267–288), and early Solar System accretion (Chambers [2013], Icarus, 224, 43–56).

58 GEOSCIENCES↗
DOE OSTI2019

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials

Reliable models of the thermodynamic properties of materials are critical for industrially relevant applications that require a good understanding of equilibrium phase diagrams, thermal and chemical transport, and microstructure evolution. The goal of thermodynamic models is to capture data from both experimental and computational studies and then make reliable predictions when extrapolating to new regions of parameter space. These predictions will be impacted by artifacts present in real data sets such as outliers, systematic errors, and unreliable or missing uncertainty bounds. Such issues increase the probability of the thermodynamic model producing erroneous predictions. We present a Bayesian framework for the selection, calibration, and quantification of uncertainty of thermodynamic property models. The modular framework addresses numerous concerns regarding thermodynamic models including thermodynamic consistency, robustness to outliers, and systematic errors by the use of hyperparameter weightings and robust Likelihood and Prior distribution choices. Furthermore, the framework’s inherent transparency (e.g. our choice of probability functions and associated parameters) enables insights into the complex process of thermodynamic assessment. We introduce these concepts through examples where the true property model is known. Additionally, we demonstrate the utility of the framework through the creation of a property model from a large set of experimental specific heat and enthalpy measurements of Hafnium metal from 0 to 4900K.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of sample size on the maximum value distribution of fatigue driving forces in metals and alloys

An analytical framework is presented to predict the effects of sample size on the maximum value distribution (MVD) of the driving forces for fatigue crack formation in metals and alloys. The distribution of the maximum driving force for fatigue crack formation over the domain follows the generalized extreme value theory in the limit as the domain size increases to infinity. Here, a simulation-based analysis of microstructure influences on fatigue resistance for polycrystalline metals and alloys is very costly, and reaching those limits is intractable. This work models the MVD of Fatigue Indicator Parameters (FIPs), which serve as surrogate measures for the driving force for fatigue crack formation, at finite sample sizes prior to their convergence to a limiting extreme value distribution. Large-scale crystal plasticity finite element (CPFE) simulations of FCC Al 7075-T6 with microstructure realizations of various sizes are incorporated to calibrate and evaluate the developed framework, and a total of ∼6.5 million grains of Al 7075-T6 are examined. The calibrated analytical solution agrees well with the brute force Monte Carlo simulation results extracted from the CPFE simulations. Furthermore, the developed formulation can predict the MVD of FIPs for different sample sizes using a size-dependent parameter, and it is capable of accurately extrapolating the MVD of FIPs for much larger microstructure sample sizes than the size used for its calibration.

Crystal plasticity↗
DOE OSTI2015

Mineral dissolution and precipitation during CO 2 injection at the Frio-I Brine Pilot: Geochemical modeling and uncertainty analysis

During the Frio-I Brine Pilot CO 2 injection experiment in 2004, distinct geochemical changes in response to the injection of 1600 tons of CO 2 were recorded in samples collected from the monitoring well. Previous geochemical modeling studies have considered dissolution of calcite and iron oxyhydroxides, or release of adsorbed iron, as the most likely sources of the increased ion concentrations. We explore in this modeling study possible alternative sources of the increasing calcium and iron, based on the data from the detailed petrographic characterization of the Upper Frio Formation “C”. Particularly, we evaluate whether dissolution of pyrite and oligoclase (anorthite component) can account for the observed geochemical changes. Due to kinetic limitations, dissolution of pyrite and anorthite cannot account for the increased iron and calcium concentrations on the time scale of the field test (10 days). However, dissolution of these minerals is contributing to carbonate and clay mineral precipitation on the longer time scales (1000 years). The one-dimensional reactive transport model predicts carbonate minerals, dolomite and ankerite, as well as clay minerals kaolinite, nontronite and montmorillonite, will precipitate in the Frio Formation “C” sandstone as the system progresses towards chemical equilibrium during a 1000-year period. Cumulative uncertainties associated with using different thermodynamic databases, activity correction models (Pitzer vs. B-dot), and extrapolating to reservoir temperature, are manifested in the difference in the predicted mineral phases. Furthermore, these models are consistent with regards to the total volume of mineral precipitation and porosity values which are predicted to within 0.002%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Residence time distribution in a structured packing unit for monitoring aerosol emissions

Solvent absorption in a structured packed column has been demonstrated as a viable option for post-combustion carbon capture. Amine emissions in the form of aerosol particles pose a major challenge that severely impacts the separation efficiency of the packed column. The aerosol particles quickly achieve the motion of the gas flow. In this context, residence time distribution (RTD) of the gaseous phase will provide insights for managing aerosol particles, thereby controlling amine loss in the packed column. Computational fluid dynamics (CFD) modeling of such columns is a multiscale problem because of a wide range of disparity in length scales. Accordingly, three-dimensional CFD simulations in the representative elementary unit of a structured packing are conducted using OpenFOAM. The RTD is analyzed in terms of residence time distribution function, mean residence time, and variance. Effects of the diffusivity and flow rates on RTD are extensively studied, and the dispersion coefficient is calculated using a one-dimensional axial dispersion model. Furthermore, RTDs computed in a smaller domain are extrapolated to a larger domain using a convolution integral. The computed and corresponding CFD models derived from the convolution integral match well at different flow rates and domain sizes. A comparison of RTD among different packing designs also is presented at a fixed number of repeating units and different flow rates.

structured packings, residence time distribution↗
DOE OSTI2019

Reactive jet and cyclonic attrition analysis of ilmenite in chemical looping combustion systems

In chemical looping combustion (CLC), the chosen oxygen carrier’s (OC) reactivity maintenance and attrition propensity play key roles in determining its lifetime in such systems. Jet and cyclonic attrition are two main mechanisms of attrition in CLC systems, which typically use fluidized beds and cyclones. In contrast to standardized tests, that assess attrition characteristics under ambient and non-reacting conditions, a realistic evaluation must include the behavior under relevant high temperatures and cyclic oxidation-reduction. In this study, separate jet and cyclonic attrition test units were constructed to investigate the effects of temperature, fuel gas concentration and velocity on the performance of ilmenite, a natural ore-based OC in CLC. Testing showed that thermal and chemical effects were crucial to accurately determine the performance of ilmenite. For experiments conducted between 820°C and 970°C, the intermediate temperature of 895°C provided the best balance between high reactivity and material durability. Additionally, fuel gas concentration affected particle morphology evolution. Iron migration to the surface of the ilmenite particle was enhanced at higher fuel gas concentrations and resulted in reduced attrition rate, presumably due to sintering of the more highly reduced enriched iron phase on the particle surface. The laboratory jet and cyclonic attrition evaluation test units tested in this study can be used to investigate multiple parameters relevant for OC performance, including the degree of reduction, oxygen carrying capacity, attrition resistance, agglomeration, and optimum material operability conditions, as well as to extrapolate test data to determine OC replacement costs in a commercial CLC system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Microscopic ejecta measurements from hypervelocity impacts on aluminum and powdered regolith targets

Meteoroids and space debris pose a two-fold threat to spacecraft due to the risk of both mechanical damage from the impact and electrical damage from the impact-generated plasma, which produces electromagnetic emissions. Analysis of impact products, however, has the potential to provide useful information about planetary rings and small solar system bodies, such as asteroids and comets. Understanding the plasma dynamics and radiation mechanism is essential to addressing the impact threat and extracting science data from impacts. Charge attachment to condensed-phase debris may lead to a dusty plasma under certain conditions, so interpreting hypervelocity impacts requires knowledge of both the nature of the plasma and of the ejecta. We address the latter with measurements of the microscopic ejecta distribution produced by light gas gun impacts on solid aluminum and powdered regolith simulant targets. We examine both the size and shape of the ejecta using thin-film witness plates and find that the size distributions of microscopic ejecta follow power laws. Observations from the powdered regolith simulant match well with disruption experiments of solid basalt, while measurements from the aluminum impacts diverge from extrapolations based on studies of macroscopic debris. Analysis of the ejecta shape shows a transition from smooth to irregularly shaped ejecta at the material grain size, and the shape of debris may provide insight on the phase of the ejected material. Finally, based on our results, we predict a significant number of secondary impacts on plasma sensors due to ejecta, even at considerable distance from the target, supporting the hypothesis that charged dust affects plasma measurements in the ejecta curtain.

42 ENGINEERING↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Tensile and compressive plastic deformation behavior of medium-entropy Cr-Co-Ni single crystals from cryogenic to elevated temperatures

The equiatomic Cr-Co-Ni medium-entropy alloy has the face-centered cubic (FCC) structure. Bulk single crystals of this alloy were grown and tested in tension and compression between 14 K and 1373 K with the loading axis parallel to [23]. At room temperature, the critical resolved shear stress (CRSS) for {111}<10> slip is 65 ± 5 MPa and does not exhibit a tension-compression asymmetry. It does, however, increase significantly as the test temperature decreases. A dulling of this temperature dependence occurs below 50 K, which may be due to the inertia effect. When the measured values above 50 K are extrapolated to lower temperatures, a value of 225 MPa is estimated for the CRSS at 0 K. This is larger than that (168 MPa) previously determined for the equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloy using a similar procedure. The stacking fault energy of the present Cr-Co-Ni is estimated to be about 14 mJm-2, which is sufficiently low to account for deformation twinning both at 77 K and room temperature. Twinning at 77 K occurs on conjugate (1) planes at an onset shear stress of 482 MPa after primary slip and propagates in the form of Lüders deformation. At room temperature, twinning occurs uniformly throughout the gauge section on primary (111) planes at an onset shear stress of 381 MPa after primary and subsequent conjugate slip. Thin layers with the hexagonal close-packed stacking are observed in association with twinning both at 77 K and room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructure-sensitive modeling of high temperature creep in grade-91 alloy

Predicting the effects of microstructure on high-temperature creep responses of steel components is critical to minimize the risks of failure and maximize economic viability in the energy sector. In this research, a recently developed advanced mechanistic constitutive model is employed to study the effect of microstructure on the creep responses and to rationalize experimentally reported variability in the performances of grade-91 alloy. Hundreds of experimental creep tests from the literature are used to assess the predictability of the model. The model proposed is shown to accurately predict the steady-state creep rates and also the less commonly considered, yet important, primary-to-secondary transients for a wide range of creep conditions. Further, the model is capable of extrapolating the creep response of grade 91 alloy even outside of the calibration regime. Using this model, the roles of initial microstructure described in terms of grain size, dislocation density, and precipitate content, on the creep responses are investigated. The effect of initial microstructure on the steady-state creep rates and creep-strain is found to vary with stress and temperature. Grain size plays a significant role in the low-stress creep, where the diffusional creep is dominant. On the other hand, the effects of dislocation densities and precipitate content are significant in the dislocation-plasticity-dominated high-stress and temperature regimes. Furthermore, by comparing model predictions against a large experimental creep database, it is found that variability in the creep responses can be rationalized on the basis of differences in the initial microstructure. Overall, this work provides a robust pathway for microstructure-aware engineering design, verification, and validation of metallic components for energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stochastic room temperature creep of 316 L stainless steel

The creep behavior of 316 L stainless steel at room temperature was evaluated as a function of time and applied stress using a new high-throughput approach. Several common creep models were evaluated against the observations, leading to deeper analysis of a stress-dependent modified logarithmic creep model. Within this model, multiple sources of uncertainty were compared. Aleatoric stochastic variation between samples under nominally identical conditions was identified as the primary contributor to uncertainty in creep response. Under any particular set of conditions, the sample-to-sample variability in creep strain was as high as a factor of two, highlighting the engineering importance of characterizing large statistical datasets. The model's extrapolation capabilities were assessed by comparing predictions derived from calibration on partial, shorter-duration subsets of the data. In conclusion, these findings underscore the importance of accounting for stochastic effects in predictive modeling of aging phenomena.

High-throughput↗
DOE OSTI2021

A probabilistic creep model incorporating test condition, initial damage, and material property uncertainty

Uncertainty is prevalent in the creep resistance of alloys, where at elevated temperature and low pressure, rupture can range across logarithmic decades. In this study, a probabilistic continuum-damage-mechanics (CDM)-based model is derived to capture the uncertainty of creep resistance. To meet this objective, creep data for alloy 304 Stainless Steel is gathered. A constitutive model, “Sinh”, is calibrated deterministically to determine the statistical variability of the material properties. Three sources of uncertainty are injected into the model: test condition (stress and temperature), initial damage, and material properties. Probabilistic simulations are carried out by (a) calibrating probability distribution functions (pdfs) for each source of uncertainty (b) randomly sampling the pdfs using Monte Carlo methods and (c) executing simulations to replicate the uncertain creep behavior. A sensitivity analysis is performed to evaluate the relative effect of each source of uncertainty. In full probabilistic simulations, the cumulative uncertainty of creep behavior is evaluated. The probabilistic model accurately predicts the creep deformation and rupture of the available experiments. The probabilistic model is validated for interpolation but lacks extrapolation ability. Several future works are proposed to further improve the model.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗
DOE OSTI2020

A geospatial model for the analysis of time-dependent land subsidence induced by reservoir depletion

Land subsidence due to fluid depletion is an outcome of physical processes operating across a wide range of time and length scales. Although geomechanical models are crucial to simulate reservoir compaction and predict its long-term fate, their use across large regions often bears prohibitive computational costs. To overcome this obstacle, this paper proposes a simplified modelling framework consisting of (i) a near-field numerical solver simulating the coupling between fluid flow and rock deformation with reference to a simplified one-dimensional geometry and (ii) a far-field geospatial algorithm mapping ground settlements across a region through the superposition of poroelastic computations at multiple wells. The model computes the delay between depletion history and reservoir compaction in proximity of a producing well by assuming basal depletion of a fluid-saturated deformable disk, while the Geertsma solution of nucleus of strain is used to extrapolate the impact of such time-varying reservoir compaction around the well. This approach has been used to back-analyze the spatio-temporal progression of subsidence at the Groningen gas field. The results are compared against measurements collected over 50 year of production at 25 benchmark locations scattered over an area of 900 km 2 . It is shown that coupled simulations based on average values of rock compressibility and permeability lead to nonlinear trends of subsidence evolution in good agreement with field measurements, while uncoupled analyses overpredict settlements by more than 70%. Lastly, synthetic forecasts based on different rates of depletion were provided. The results suggest that slower depletion rates lead to lower subsidence at a given time, and that residual subsidence may continue to develop for several decades after interruption of production activities.

58 GEOSCIENCES↗
DOE OSTI2013

Hypofractionated Radiation Therapy (66 Gy in 22 Fractions at 3 Gy per Fraction) for Favorable-Risk Prostate Cancer: Long-term Outcomes

Purpose: To report long-term outcomes of low- and intermediate-risk prostate cancer patients treated with high-dose hypofractionated radiation therapy (HypoRT). Methods and Materials: Patients with low- and intermediate-risk prostate cancer were treated using 3-dimensional conformal radiation therapy to a dose of 66 Gy in 22 daily fractions of 3 Gy without hormonal therapy. A uniform 7-mm margin was created around the prostate for the planning target volume, and treatment was prescribed to the isocenter. Treatment was delivered using daily ultrasound image-guided radiation therapy. Common Terminology Criteria for Adverse Events, version 3.0, was used to prospectively score toxicity. Biochemical failure was defined as the nadir prostate-specific antigen level plus 2 ng/mL. Results: A total of 129 patients were treated between November 2002 and December 2005. With a median follow-up of 90 months, the 5- and 8-year actuarial biochemical control rates were 97% and 92%, respectively. The 5- and 8-year actuarial overall survival rates were 92% and 88%, respectively. Only 1 patient died from prostate cancer at 92 months after treatment, giving an 8-year actuarial cancer-specific survival of 98%. Radiation therapy was well tolerated, with 57% of patients not experiencing any acute gastrointestinal (GI) or genitourinary (GU) toxicity. For late toxicity, the worst grade ≥2 rate for GI and GU toxicity was 27% and 33%, respectively. There was no grade >3 toxicity. At last follow-up, the rate of grade ≥2 for both GI and GU toxicity was only 1.5%. Conclusions: Hypofractionation with 66 Gy in 22 fractions prescribed to the isocenter using 3-dimensional conformal radiation therapy produces excellent biochemical control rates, with moderate toxicity. However, this regimen cannot be extrapolated to the intensity modulated radiation therapy technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Absorbed Doses and Risk Estimates of {sup 211}At-MX35 F(ab'){sub 2} in Intraperitoneal Therapy of Ovarian Cancer Patients

Purpose: Ovarian cancer is often diagnosed at an advanced stage with dissemination in the peritoneal cavity. Most patients achieve clinical remission after surgery and chemotherapy, but approximately 70% eventually experience recurrence, usually in the peritoneal cavity. To prevent recurrence, intraperitoneal (i.p.) targeted α therapy has been proposed as an adjuvant treatment for minimal residual disease after successful primary treatment. In the present study, we calculated absorbed and relative biological effect (RBE)-weighted (equivalent) doses in relevant normal tissues and estimated the effective dose associated with i.p. administration of {sup 211}At-MX35 F(ab'){sub 2}. Methods and Materials: Patients in clinical remission after salvage chemotherapy for peritoneal recurrence of ovarian cancer underwent i.p. infusion of {sup 211}At-MX35 F(ab'){sub 2}. Potassium perchlorate was given to block unwanted accumulation of {sup 211}At in thyroid and other NIS-containing tissues. Mean absorbed doses to normal tissues were calculated from clinical data, including blood and i.p. fluid samples, urine, γ-camera images, and single-photon emission computed tomography/computed tomography images. Extrapolation of preclinical biodistribution data combined with clinical blood activity data allowed us to estimate absorbed doses in additional tissues. The equivalent dose was calculated using an RBE of 5 and the effective dose using the recommended weight factor of 20. All doses were normalized to the initial activity concentration of the infused therapy solution. Results: The urinary bladder, thyroid, and kidneys (1.9, 1.8, and 1.7 mGy per MBq/L) received the 3 highest estimated absorbed doses. When the tissue-weighting factors were applied, the largest contributors to the effective dose were the lungs, stomach, and urinary bladder. Using 100 MBq/L, organ equivalent doses were less than 10% of the estimated tolerance dose. Conclusion: Intraperitoneal {sup 211}At-MX35 F(ab'){sub 2} treatment is potentially a well-tolerated therapy for locally confined microscopic ovarian cancer. Absorbed doses to normal organs are low, but because the effective dose potentially corresponds to a risk of treatment-induced carcinogenesis, optimization may still be valuable.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Surgical Resection of Brain Metastases and the Risk of Leptomeningeal Recurrence in Patients Treated With Stereotactic Radiosurgery

Purpose: Recent prospective data have shown that patients with solitary or oligometastatic disease to the brain may be treated with upfront stereotactic radiosurgery (SRS) with deferral of whole-brain radiation therapy (WBRT). This has been extrapolated to the treatment of patients with resected lesions. The aim of this study was to assess the risk of leptomeningeal disease (LMD) in patients treated with SRS to the postsurgical resection cavity for brain metastases compared with patients treated with SRS to intact metastases. Methods and Materials: Four hundred sixty-five patients treated with SRS without upfront WBRT at a single institution were identified; 330 of these with at least 3 months' follow-up were included in this analysis. One hundred twelve patients had undergone surgical resection of at least 1 lesion before SRS compared with 218 treated for intact metastases. Time to LMD and overall survival (OS) time were estimated from date of radiosurgery, and LMD was analyzed by the use of cumulative incidence method with death as a competing risk. Univariate and multivariate analyses were performed with competing risk regression to determine whether various clinical factors predicted for LMD. Results: With a median follow-up time of 9.0 months, 39 patients (12%) experienced LMD at a median of 6.0 months after SRS. At 1 year, the cumulative incidence of LMD, with death as a competing risk, was 5.2% for the patients without surgical resection versus 16.9% for those treated with surgery (Gray test, P<.01). On multivariate analysis, prior surgical resection (P<.01) and breast cancer primary (P=.03) were significant predictors of LMD development. The median OS times for patients undergoing surgery compared with SRS alone were 12.9 and 10.6 months, respectively (log-rank P=.06). Conclusions: In patients undergoing SRS with deferral of upfront WBRT for intracranial metastatic disease, prior surgical resection and breast cancer primary are associated with an increased risk for the development of LMD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗