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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

In situ and ex situ formation models of Kepler 11 planets

We present formation simulations of the six Kepler 11 planets. Models assume either in situ or ex situ assembly, the latter with migration, and are evolved to the estimated age of the system, ≈8 Gyr. Models combine detailed calculations of both the gaseous envelope and the condensed core structures, including accretion of gas and solids, of the disk’s viscous and thermal evolution, including photo-evaporation and disk-planet interactions, and of the planet’s evaporative mass loss after disk dispersal. Planet–planet interactions are neglected. Both sets of simulations successfully reproduce measured radii, masses, and orbital distances of the planets, except for the radius of Kepler 11b, which loses its entire gaseous envelope shortly after formation. Gaseous (H+He) envelopes account for ≲18% of the planet masses, and between ≈35 and ≈60% of the planet radii. In situ models predict a very massive inner disk, whose solid surface density (σ{sub Z}) varies from over 10{sup 4} to ≈10{sup 3} g cm{sup −2} at stellocentric distances 0.1≲r≲0.5 au. Initial gas densities would be in excess of 10{sup 5} g cm{sup −2} if solids formed locally. Given the high disk temperatures (≳1000 K), planetary interiors can only be composed of metals and highly refractory materials. Sequestration of hydrogen by the core and subsequent outgassing is required to account for the observed radius of Kepler 11b. Ex situ models predict a relatively low-mass disk, whose initial σ{sub Z} varies from ≈10 to ≈5 g cm{sup −2} at 0.5≲r≲7 au and whose initial gas density ranges from ≈10{sup 3} to ≈100 g cm{sup −2}. All planetary interiors are expected to be rich in H{sub 2}O, as core assembly mostly occurs exterior to the ice condensation front. Kepler 11b is expected to have a steam atmosphere, and H{sub 2}O is likely mixed with H+He in the envelopes of the other planets. Results indicate that Kepler 11g may not be more massive than Kepler 11e.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Idea2Data: Toward a New Paradigm for Drug Discovery

Increasing the success rate and throughput of drug discovery will require efficiency improvements throughout the process that is currently used in the pharmaceutical community, including the crucial step of identifying hit compounds to act as drivers for subsequent optimization. Hit identification can be carried out through large compound collection screening and frequently involves the generation and testing of many hypotheses based on available knowledge. In practice, hypothesis generation can involve the selection of promising chemical structures from compound collections using predictive models built from previous screening/ assay results. Available physical collections, typically used during hit identification, are of the order of 10 6 compounds but represent only a small fraction of the small molecule drug-like chemical space. In an effort to survey a larger portion of chemical space and eliminate inefficiencies during hit identification, we introduce a new process, termed Idea2Data (I2D) that tightly integrates computational and experimental components of the drug discovery process. I2D provides the ability to connect a vast virtual collection of compounds readily synthesizable on automated synthesis systems with computational predictive models for the identification of promising structures. This new paradigm enables researchers to process billions of virtual molecules and select structures that can be prepared on automated systems and made available for biological testing, allowing for timely hypothesis testing and follow-up. Since its introduction, I2D has positively impacted several portfolio efforts through identification of new chemical scaffolds and functionalization of existing scaffolds. In this Innovations paper, we describe the I2D process and present an application for the discovery of new ULK inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Measuring the Weak Charge of the Proton via Elastic Electron-Proton Scattering

The Qweak experiment which ran in Hall C at Jefferson Lab in Newport News, VA, and completed data taking in May 2012, measured the weak charge of the proton Q p W via elastic electron-proton scattering. Longitudinally polarized electrons were scattered from an unpolarized liquid hydrogen target. The helicity of the electron beam was flipped at approximately 1 kHz between left and right spin states. The Standard Model predicts a small parity-violating asymmetry of scattering rates between right and left helicity states due to the weak interaction. An initial result using 4% of the data was published in October 2013 [1] with a measured parity-violating asymmetry of -279 ± 35(stat) ± 31 (syst) ppb. This asymmetry, along with other data from parity-violating electron scattering experiments, provided the world's first determination of the weak charge of the proton. The weak charge of the proton was found to be p W = 0.064 ± 0.012, in good agreement with the Standard Model prediction of p W (SM) = 0.0708 ± 0.0003[2].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Development and validation of a model for predicting direct heat transfer from the fuel to droplets in the post dryout regime

Following dryout after a large loss of coolant accident, but before eventual final quenching of the fuel, the overheated fuel is cooled by a flow of superheated vapor with entrained saturated liquid droplets. The main mechanism for cooling the cladding is convective heat transfer to the superheated vapor, with this vapor in turn cooled by evaporation into it of the saturated droplets. An additional mechanism that is not normally considered explicitly is the cooling of the metal by direct droplet impingement of non-wetting droplets. It is difficult to measure and to analyze, and it is believed probably to contribute relatively little to the cooling, but it could be helpful additional cooling mechanism. In this paper is published validation of a simple analytical model of the heat removed from the wall during the few milliseconds that a non-wetting droplet is in 'contact' with the wall. It is found that the model's estimates of the heat removal are consistent with such limited experimental evidence as is available, paving the way for incorporation of the model into computations of post dryout heat transfer. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Direct comparisons of X-ray scattering and atomistic molecular dynamics simulations for precise acid copolymers and ionomers

Designing acid- and ion-containing polymers for optimal proton, ion, or water transport would benefit profoundly from predictive models or theories that relate polymer structures with ionomer morphologies. Recently, atomistic molecular dynamics (MD) simulations were performed to study the morphologies of precise poly(ethylene-co-acrylic acid) copolymer and ionomer melts. Here, we present the first direct comparisons between scattering profiles, I(q), calculated from these atomistic MD simulations and experimental X-ray data for 11 materials. This set of precise polymers has spacers of exactly 9, 15, or 21 carbons between acid groups and has been partially neutralized with Li, Na, Cs, or Zn. In these polymers, the simulations at 120 °C reveal ionic aggregates with a range of morphologies, from compact, isolated aggregates (type 1) to branched, stringy aggregates (type 2) to branched, stringy aggregates that percolate through the simulation box (type 3). Excellent agreement is found between the simulated and experimental scattering peak positions across all polymer types and aggregate morphologies. The shape of the amorphous halo in the simulated I(q) profile is in excellent agreement with experimental I(q). We found that the modified hard-sphere scattering model fits both the simulation and experimental I(q) data for type 1 aggregate morphologies, and the aggregate sizes and separations are in agreement. Given the stringy structure in types 2 and 3, we develop a scattering model based on cylindrical aggregates. Both the spherical and cylindrical scattering models fit I(q) data from the polymers with type 2 and 3 aggregates equally well, and the extracted aggregate radii and inter- and intra-aggregate spacings are in agreement between simulation and experiment. Furthermore, these dimensions are consistent with real-space analyses of the atomistic MD simulations. By combining simulations and experiments, the ionomer scattering peak can be associated with the average distance between branches of type 2 or 3 aggregates. Furthermore, this direct comparison of X-ray scattering data to the atomistic MD simulations is a substantive step toward providing a comprehensive, predictive model for ionomer morphology, gives substantial support for this atomistic MD model, and provides new credibility to the presence of stringy, branched, and percolated ionic aggregates in precise ionomer melts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Thermal Modeling Study for Geologic Borehole Conceptual Design - 17148

Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN/SP) is developing a strategy for safe, permanent disposal of disused sealed radioactive sources (DSRS) from industrial and medical applications within Brazil. The Institute is proposing modifications to the International Atomic Energy Agency (IAEA) Borehole Disposal of Sealed Radioactive Sources (BOSS) concept originally developed by the Nuclear Energy Corporation of South Africa. The current Brazilian modified design differs from the IAEA design in that the disposal zone is below 300 m versus 30 m of the boss concept, and will be used to dispose of a much larger number of DSRS. These modifications result in a considerable departure from the generic safety case established by IAEA. Therefore, a new safety case is required to assess radiological and thermal impacts among other considerations. Predictive modeling and simulations were performed to address impacts of the proposed borehole concept at the early design stage in order to provide timely improvements to the concept and a traceable rationale for decisions made throughout the program as required by the safety case. Preliminary objectives of the modeling effort were focused on evaluating the mechanical and thermal loads anticipated within the current Brazilian borehole disposal concept in order to assess potential material and design issues. This paper presents the thermal modeling predictions and performance results for the proposed BOSS design. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Measurement of the direct CP asymmetry in B¯->Xs+dy decays with a lepton tag

We report the measurement of the direct CP asymmetry in the radiative B¯?Xs+d? decay using a data sample of (772±11)×106 BB¯ pairs collected at the ?(4S) resonance with the Belle detector at the KEKB asymmetric-energy e+e- collider. The CP asymmetry is measured as a function of the photon energy threshold. For E*?=2.1 GeV, where E*? is the photon energy in the center-of-mass frame, we obtain ACP(B¯?Xs+d?)=(2.2±3.9±0.9)%, consistent with the Standard Model prediction.

Pesantez, L↗
DOE OSTI2016

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Rapid estimation of sugar release from winter wheat straw during bioethanol production using FTIR-photoacoustic spectroscopy

Complexity and high cost are the main limitations for high-throughput screening methods for the estimation of the sugar release from plant materials during bioethanol production. In addition, it is important that we improve our understanding of the mechanisms by which different chemical components are affecting the degradability of plant material. In this study, Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) was combined with advanced chemometrics to develop calibration models predicting the amount of sugars released after pretreatment and enzymatic hydrolysis of wheat straw during bioethanol production, and the spectra were analysed to identify components associated with recalcitrance. A total of 1122 wheat straw samples from nine different locations in Denmark and one location in the United Kingdom, spanning a large variation in genetic material and environmental conditions during growth, were analysed. The FTIR-PAS spectra of non-pretreated wheat straw were correlated with the measured sugar release, determined by a high-throughput pretreatment and enzymatic hydrolysis (HTPH) assay. A partial least square regression (PLSR) calibration model predicting the glucose and xylose release was developed. The interpretation of the regression coefficients revealed a positive correlation between the released glucose and xylose with easily hydrolysable compounds, such as amorphous cellulose and hemicellulose. Additionally, we observed a negative correlation with crystalline cellulose and lignin, which inhibits cellulose and hemicellulose hydrolysis. FTIR-PAS was used as a reliable method for the rapid estimation of sugar release during bioethanol production. The spectra revealed that lignin inhibited the hydrolysis of polysaccharides into monomers, while the crystallinity of cellulose retarded its hydrolysis into glucose. Amorphous cellulose and xylans were found to contribute significantly to the released amounts of glucose and xylose, respectively.

09 BIOMASS FUELS↗
DOE OSTI2016

A side‐by‐side comparison of CPV module and system performance

Abstract A side‐by‐side comparison is made between concentrator photovoltaic module and system direct current aperture efficiency data with a focus on quantifying system performance losses. The individual losses measured/calculated, when combined, are in good agreement with the total loss seen between the module and the system. Results indicate that for the given test period, the largest individual loss of 3.7% relative is due to the baseline performance difference between the individual module and the average for the 200 modules in the system. A basic empirical model is derived based on module spectral performance data and the tabulated losses between the module and the system. The model predicts instantaneous system direct current aperture efficiency with a root mean square error of 2.3% relative. Copyright © 2016 John Wiley & Sons, Ltd.

Muller, Matthew↗
DOE OSTI2017

A Hubble Space Telescope Survey for Novae in M87. II. Snuffing out the Maximum Magnitude–Rate of Decline Relation for Novae as a Non-standard Candle, and a Prediction of the Existence of Ultrafast Novae

The extensive grid of numerical simulations of nova eruptions from the work of Yaron et al. first predicted that some classical novae might significantly deviate from the Maximum Magnitude–Rate of Decline (MMRD) relation, which purports to characterize novae as standard candles. Kasliwal et al. have announced the observational detection of a new class of faint, fast classical novae in the Andromeda galaxy. These objects deviate strongly from the MMRD relationship, as predicted by Yaron et al. Recently, Shara et al. reported the first detections of faint, fast novae in M87. These previously overlooked objects are as common in the giant elliptical galaxy M87 as they are in the giant spiral M31; they comprise about 40% of all classical nova eruptions and greatly increase the observational scatter in the MMRD relation. We use the extensive grid of the nova simulations of Yaron et al. to identify the underlying causes of the existence of faint, fast novae. These are systems that have accreted, and can thus eject, only very low-mass envelopes, of the order of 10{sup −7}–10{sup −8} M {sub ⊙}, on massive white dwarfs. Such binaries include, but are not limited to, the recurrent novae. These same models predict the existence of ultrafast novae that display decline times, t {sub 2,} to be as short as five hours. We outline a strategy for their future detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Gravity waves from non-minimal quadratic inflation

We discuss non-minimal quadratic inflation in supersymmetric (SUSY) and non-SUSY models which entails a linear coupling of the inflaton to gravity. Imposing a lower bound on the parameter c{sub R}, involved in the coupling between the inflaton and the Ricci scalar curvature, inflation can be attained even for subplanckian values of the inflaton while the corresponding effective theory respects the perturbative unitarity up to the Planck scale. Working in the non-SUSY context we also consider radiative corrections to the inflationary potential due to a possible coupling of the inflaton to bosons or fermions. We find ranges of the parameters, depending mildly on the renormalization scale, with adjustable values of the spectral index n{sub s}, tensor-to-scalar ratio r≃(2−4)⋅10{sup −3}, and an inflaton mass close to 3⋅10{sup 13} GeV. In the SUSY framework we employ two gauge singlet chiral superfields, a logarithmic Kähler potential including all the allowed terms up to fourth order in powers of the various fields, and determine uniquely the superpotential by applying a continuous R and a global U(1) symmetry. When the Kähler manifold exhibits a no-scale-type symmetry, the model predicts n{sub s}≃0.963 and r≃0.004. Beyond no-scale SUGRA, n{sub s} and r depend crucially on the coefficient involved in the fourth order term, which mixes the inflaton with the accompanying non-inflaton field in the Kähler potential, and the prefactor encountered in it. Increasing slightly the latter above (−3), an efficient enhancement of the resulting r can be achieved putting it in the observable range. The inflaton mass in the last case is confined in the range (5−9)⋅10{sup 13} GeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Differential cross-section measurements of Higgs boson production in the H → τ + τ - decay channel in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

Differential measurements of Higgs boson production in the τ-lepton-pair decay channel are presented in the gluon fusion, vector-boson fusion (VBF), VH and $t\overline{t}H$ associated production modes, with particular focus on the VBF production mode. The data used to perform the measurements correspond to 140 fb -1 of proton-proton collisions collected by the ATLAS experiment at the LHC. Two methods are used to perform the measurements: the Simplified Template Cross-Section (STXS) approach and an Unfolded Fiducial Differential measurement considering only the VBF phase space. For the STXS measurement, events are categorized by their production mode and kinematic properties such as the Higgs boson’s transverse momentum (${p}_{\textrm{T}}^{\textrm{H}}$ ), the number of jets produced in association with the Higgs boson, or the invariant mass of the two leading jets (mjj). For the VBF production mode, the ratio of the measured cross-section to the Standard Model prediction for m jj > 1.5 TeV and ${p}_{\textrm{T}}^{\textrm{H}}$ > 200 GeV (${p}_{\textrm{T}}^{\textrm{H}}$ < 200 GeV) is ${1.29}_{-0.34}^{+0.39}$ (${0.12}_{-0.33}^{+0.34}$ ). This is the first VBF measurement for the higher-${p}_{\textrm{T}}^{\textrm{H}}$ criteria, and the most precise for the lower-${p}_{\textrm{T}}^{\textrm{H}}$ criteria. The fiducial cross-section measurements, which only consider the kinematic properties of the event, are performed as functions of variables characterizing the VBF topology, such as the signed ΔΦ jj between the two leading jets. The measurements have a precision of 30%–50% and agree well with the Standard Model predictions. These results are interpreted in the SMEFT framework, and place the strongest constraints to date on the CP-odd Wilson coefficient ${c}_{H\overset{\sim }{W}}$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk

Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were also included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between RP covariates and its potential to improve RP prediction accuracy. Our Bayesian approach to incorporate prior knowledge can enhance efficiency in searching of such associations from data. The authors acknowledge partial support by: 1) CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and 2) The Terry Fox Foundation Strategic Training Initiative for Excellence in Radiation Research for the 21st Century (EIRR21)

60 APPLIED LIFE SCIENCES↗