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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Absolute Branching Ratios of Prominent $γ$ Rays Following $α$ Decay of 233 U

The absolute $γ$-ray branching ratios (emission probabilities) for 19 prominent peaks in the $α$ decay of 233 U are reported with energies ranging from 97 to 366 keV. The branching ratios were obtained from $α-γ$ coincidence measurements, normalized to the $α$ singles. The high-purity 233 U material (> 99.98%) was separated from its decay products before preparation of a 4.74-mg/cm 2 uranyl nitrate foil with a 6-mm diameter. Furthermore, this is the first report on the absolute normalization of the branching ratios since 1984 and it is the only measure by $α-γ$ coincidences, where the $α-γ/α$ ratio removes several potential systematic biases. Overall, the results are consistent with the adopted literature, and they validate the quantities most relevant to the non-destructive assay of fissile 233 U material, which is relevant to the thorium fuel cycle and associated safeguards.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Evaluation of ceria as a surrogate material for UO 2 in experiments on fuel cracking driven by resistive heating

A variety of normal operation and accident scenarios can generate thermal stresses large enough to cause cracking in light-water reactor (LWR) fuel pellets. Cracking of fuel pellets can lead to reduced heat removal, larger centerline temperatures, and localized stress in cladding all of which impact fuel performance. Furthermore, pellet cracking also contributes to a temperature reduction in the pellet since the pellet fragments tend to move towards the heat sink (cladding), and the heat flow remains predominantly radial despite the presence of cracks. It is important to understand the temperature profile on the pellet before and after cracking to improve cracking models in fuel performance codes However, in-reactor observation and measurement of cracking is very challenging owing to the harsh environment and design of fuel rods. Recently, an experimental pellet cracking test stand was developed for separate effects testing of normal operations and accident temperature conditions, using thermal imaging to capture the pellet surface temperature for evaluation of thermal stresses and optical imaging to capture the evolution of cracking in real time. Cracking experiments were initially performed using ceria (CeO 2 ) as a surrogate fuel material, which is useful for developing and demonstrating the experimental approaches but is also valuable in its own right for cracking model development and validation. A combination of induction and resistance heating was used for volumetric heat generation in the pellet creating a thermal gradient. The material properties of CeO 2 and UO 2 are reviewed and compared for use in model development. Simulations of the experiment were performed to evaluate the behavior of the surrogate (CeO 2 ) fuel in BISON. The measured temperature profiles from BISON models match reasonably well with the observed experiments for the ceria pellets before cracking. The findings from this work will help improve confidence in fracture models used for fuel pellets under similar in-reactor conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification

An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Validation study of sodium pool fire modeling efforts in $\mathrm{MELCOR}$ and $\mathrm{SPHINCS}$ codes

Discharge of sodium coolant into containment from a sodium-cooled fast reactor vessel can occur in the event of a pipe leak or break. In this situation, some of the liquid sodium droplets discharged from the coolant system will react with oxygen in the air before reaching the containment. This phase of the event is normally termed the sodium spray fire phase. Unreacted sodium droplets pool on the containment floor where continued reaction with containment atmospheric oxygen occurs. This phase of the event is normally termed the sodium pool fire phase. Both phases of these sodium-oxygen reactions (or fires) are important to model because of the heat addition and aerosol generation that occur. Any fission products trapped in the sodium coolant may also be released during this progression of events, which if released from containment could pose a health risk to workers and the public. The paper describes progress of an international collaborative research in the area of the sodium fire modeling in the sodium-cooled fast reactors between the United States and Japan under the framework of the Civil Nuclear Energy Research and Development Working Group. In this collaboration between Sandia National Laboratories and Japan Atomic Energy Agency, the validation basis for and modeling capabilities of sodium spray and pool fires in MELCOR of Sandia National Laboratories and SPHINCS of Japan Atomic Energy Agency are being enhanced. Here this study documents MELCOR and SPHINCS sodium pool fire model validation exercises against the JAEA’s sodium pool fire experiments, F7-1 and F7-2. The proposed enhancement of the sodium pool fire models in MELCOR through addition of thermal hydraulic and sodium spreading models that enable a better representation of experimental results is also described.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Thermal mechanical assessment of a SiC-SiC-composite clad fuel pin concept in a light water reactor environment

Accident Tolerant Fuels (ATFs) are designed to increase coping time following an accident scenario while preserving or improving current steady state reactor operational performance. A potential ATF concept is SiC-SiC composite claddings. Fuel performance simulations were conducted on a SiC-SiC based cladding concept utilizing a multilayered approach for improved performance. This cladding concept referred to as the Duplex concept is a duplex structure composed of a monolithic SiC layer placed on the outside of a SiC-SiC composite. A liquid metal is added to fuel-cladding gap for improved heat dissipation from the fuel. The monolithic SiC layer is used to improve the coolant corrosion characteristics and protect the SiC-SiC composite layer from exposure to the coolant. The fuel performance code BISON was used to conduct fuel performance simulations on the cladding concepts. Comparisons are made with a current prototypic fuel rod design (UO 2 fuel enclosed in Zircaloy-4 cladding). Representative steady-state cases were considered for normal power and two cycle power histories. Additionally, a PCI ramp case was simulated to analyze potential anticipated operational occurrences. Transient response during a Loss of Coolant Accident and a Reactivity Initiated Accident were also simulated. This computational study demonstrated that for normal operating conditions, the SiC concept cladding performed as well as the baseline for the standard power cases evaluated. The ramping evaluations indicate potential fracturing of the SiC-SiC composite of the composite cladding compared to the Zircaloy-4 cladding due to the temperature gradient and the subsequent differential thermal conductivity degradation and swelling across the composite thickness. In conclusion, the rod fails early at low enthalpy for RIA but survives a LOCA with minimal material loss due to high temperature steam corrosion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Results of the AGR-5/6/7 UCO TRISO fuel irradiation test in the Advanced Test Reactor

AGR-5/6/7 was the last in a series of irradiation experiments sponsored by the U.S. Department of Energy in support of the development and qualification of TRISO coated particle fuel for use in a high-temperature gas-cooled reactor. This experiment was conducted to verify the performance of the reference-design TRISO-coated low-enriched UCO fuel for modular high-temperature gas-cooled reactor normal operating conditions and to explore fuel performance at temperatures substantially beyond those typical of normal operation. A total of 194 UCO fuel compacts in five capsules were irradiated in the Advanced Test Reactor for 360.9 effective full-power days, achieving final burnup ranging from 5.66% to 15.26% fissions per initial heavy metal atom and fast neutron fluence ranging from 1.62 × 10 25 to 5.55 × 10 25 n/m 2 (E > 0.18 MeV). Calculated time-averaged fuel temperatures ranged from 467 °C to 1432 °C, with a peak fuel temperature of 1536 °C. During the first five irradiation cycles (∼180 effective full-power days), 85m Kr fission gas release-rate-to-birth-rate ratios were 10 −7 –10 −6 , indicating no particle failures. Near the end of the sixth cycle, a substantial number of in-pile particle failures occurred in Capsule 1. The fission gas release from this capsule impacted the readings from the other four capsules and led to unreliable fission gas release measurements for all capsules during the last four cycles. A preliminary post-irradiation examination of Capsule 1 fuel and internal components revealed the in-pile particle failures resulted from operational issues with the capsule, not subpar performance of the fuel particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2022

Frictional Contacts Between Individual Woody Biomass Particles under Wet and Dry Conditions

Friction between wood particles can be a critical property when designing processing equipment for creating cellulosic biofuels and similar natural products. Also, as wood processing is likely to occur year-round, understanding the friction between wet as well as dry wood particles can help design and model equipment, such as screw feeders. Here, a tribo-rheometry method was developed using a commercial rheometer that measured the torque required to rotate two contacting millimeter-scale wood chip particles. First, a range of normal forces were used to find the limits of the experimental method. Torque values were measured for seven pairs of wood chip particles at 1 N normal force under both dry and wet conditions, at both ambient conditions and in a humidity-controlled chamber. The torque required to rotate the wet particles was consistently higher than that of the dry particles, although differences were not quite statistically significant when measurements were performed at ambient conditions. Using humidity control resulted in torque values for wet particles of 1900 uNm and 900 uNm for dry particles. Finally, the friction coefficient was calculated as 0.23 for wet particles and 0.11 for dry particles when humidity was controlled. These frictions coefficients agreed with values for wood reported in the literature. Overall, controlling humidity is strongly recommended to quantify the range of friction for particles that uptake water, including granular systems from biomass to food to powders.

biomass↗
DOE OSTI2020

Effects of dilution and pressure on combustion characteristics within externally heated micro-tubes

Here this study investigates the impact of pressure and dilution on combustion behavior of of C 2H6/air/N2 mixtures within an externally heated micro-tube using both experimental and analytical techniques. Experiments are conducted for pressures up to 10 bar at multiple dilution levels and document three flame regimes, i.e. weak flames, FREI and normal flames. Characteristic temperatures for flame stabilization, as well as and ignition and extinction are obtained by applying a novel thin filament pyrometry method (TFP), which uses a thin silicon carbide (SiC) filament that enables temperature measurements for both reacting and non-reacting cases. Results show a decrease of characteristic temperatures with increasing pressure, which can be which can be partially compensated by a decrease of O2 content. Further, regime transitions occur at lower velocity as the pressure increases, whereas weak flame positions are insensitive to dilution at a given pressure. Predictions from the analytical model compare favorably with experimental results. The most prominent finding is that as dilution increases, the transition from weak flame to FREI becomes less abrupt and is completely lost for high dilution levels (i.e. low O2 content). Both experimental and analytical results indicate that the unstable FREI combustion regime does not exist at high dilution levels, i.e. weak flame and normal flame regimes are no longer clearly separated. As FREI are interpreted as a cyclic transition from an ignition zone to a propagating flame, results for highly diluted conditions are interpreted as a combustion regime where classical flame propagation ceases to exist.

42 ENGINEERING↗
DOE OSTI2026

Oil price states and drivers: An analysis of the second-month spot-futures price differential

Oil remains a dominant component of global energy use, and its price, characterized by frequent changes and an ever-present potential for large swings, continues to be a focus of industry participants, policymakers and analysts attention. Here, this study examines the behavior of future spot oil prices using a continuous-time hidden Markov model (HMM) and daily price data spanning years 2007 to 2024. We identify six states in the second-month WTI spot-futures price differential and assess the roles of eleven futures price, quantity, financial market, and geopolitical/volatility variables in each state. The model yields several insights into the workings of the oil market and the relative roles of these drivers. We find support for several theoretical and empirical findings in the oil market literature, including the role of inventory, volatility/risk, and market responses to contango/backwardation in futures markets. A novel finding is that “normal contango” conditions represent a significant portion of next-day states in our in-sample data. Under the most volatile normal contango state, many of the oil market drivers differ markedly in coefficient signs and magnitudes from those in other states. The resulting model also performed well out-of-sample and would, in addition to understanding the impact of market drivers, be useful for short-term forecasting. Overall, the findings highlight the highly non-linear, regime-dependent interactions of the oil price and its drivers, emphasizing the importance of detailed information to market stakeholders.

Oladosu, Gbadebo A. [Oak Ridge National Laboratory↗
DOE OSTI2026

Investigating the impact of a multi-module operation environment on the task performance time of human operators – An explanatory study

The worldwide demand for Small Modular Reactors (SMRs) has surged in recent years due to their enhanced safety and versatility in supporting diverse industrial sectors. A unique feature of SMR operation is that a single human operator is responsible for managing multiple modules. Therefore, securing a sufficient amount of human performance data pertaining to this new environment is essential for the safe operation of SMRs. In this explanatory study, a series of experiments were conducted using the NuScale simulator, a representative SMR design, with student operators. A total of 12 student operators were assigned two types of off-normal events and asked to cope with them using paper-based procedures. Subsequently, their task performance times were compared with those of student operators responsible for a single unit based on the Task Complexity (TACOM) measure. Results indicate that the performance of student operators under the experimental conditions of this study degraded by a factor of 2 to 3, depending on the characteristics of the off-normal events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

On the quantitative characterization of weld microstructures

Here, a new technique to quantify grain shape and grain boundary curvature in the fusion zone (FZ) and the heat-effected zone (HAZ) of refractory metals and alloys has been developed. The application of this technique to quantify the effect of welding speed on these microstructural characteristics in simulated molybdenum welds is highlighted in this study. A 50% increase in weld speed more than doubles the fraction of grain segments in the fusion zone with orientations between 00 to 300 to the normal to the welding direction, with a corresponding 50% decrease in the fraction of grain segments oriented along the welding direction. This increase in weld speed also results in a reduction in grain size from approximately 120 µm to 84 µm along the WD at the FZ centerline. Grain boundary curvature is negative near the weld centerline and the edge of the fusion zone, indicating that with increasing distance from the weld centerline, the grain segments progressively rotate towards a direction normal to the welding direction at both locations. Presence of regions with relatively straight grain segments indicated by curvatures close to zero were identified in between the weld centerline and the edge of the FZ at all weld speeds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

4D Observations of the initiation of abnormal grain growth in commercially pure Ni

Abnormal grain growth (AGG), where a small fraction of grains grow faster than others, is critical to predict because it can significantly impact material properties. However, the mechanism behind AGG remains unclear. In this study, laboratory-based x-ray diffraction contrast tomography (LabDCT) is employed to non-destructively track the 3D microstructural evolution of high-purity nickel during the onset of AGG at 800 °C. The initial microstructure state is used to test hypothesized microstructure predictors of the initiation of AGG. The change in grain size was not related to the initial grain size or normalized integral mean curvature. Additionally, the grain boundary energy distributions of abnormal grains were indistinguishable from those of control groups exhibiting normal grain growth. However, the grains that later became abnormal exhibit large areas of asymmetric tilt boundaries that were previously found to be fast. This 3D microstructure dataset is useful to investigate new hypotheses for the initiation of AGG.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experimental comparison of pyranometer, reflectometer, and spectrophotometer methods for the measurement of roofing product albedo

Albedo (solar reflectance) can be measured outdoors with a pyranometer or indoors with a hemispherical reflectometer or a spectrophotometer. The current study evaluates these methods and their applicability to roofing materials by measuring and comparing the ASTM E1918 (pyranometer), non-ASTM E1918A (alternative pyranometer), ASTM C1549 (reflectometer), and E903 (spectrophotometer) albedos of 10 roofing products, including three single-ply membranes, one asphalt shingle, three roofing aggregates, and three high-profile tiles. It uses full-size (4 m × 4 m) assemblies in the E1918 and E1918A trials; corrects the E1918 albedos to remove shadow and background errors; and evaluates C1549 and E903 albedos with two different irradiance spectra, one global horizontal and the other beam normal. E1918A albedos matched E1918 corrected (E1918_cor) albedos to within 0.036. Furthermore, agreement between C1549 air mass 1 global horizontal (C1549_G1) albedo and E1918_cor albedo was within 0.015 for membrane and shingle coupons, and within 0.031 for aggregates, though the uncertainty in the latter agreement was up to 0.043. After minor corrections, C1549_G1 albedos of flat or slightly convex tile chips were 0.032–0.052 higher than the E1918_cor albedos of their corresponding high-profile tile assemblies because high-profile surfaces have concavities. Switching to the beam-normal albedo C1549_1.5E increased the C1549 albedos of the 10 tested products by 0.004–0.054, with the largest increases (C1549_1.5E – C1549_G1) accruing to spectrally selective cool colors. Using C1549_1.5E albedo to characterize a chip of a cool-colored tile compounded the error induced by representing a high-profile surface by a flat or slightly convex specimen.

14 SOLAR ENERGY↗
DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗
DOE OSTI2022

Use of Physics to Improve Solar Forecast: Part II, Machine Learning and Model Interpretability

Machine learning (ML) models have been applied to forecast solar energy; however, they often lack clarity of interpretability and underlying physics. This work addresses such challenges by developing a hierarchy of ML models that gradually introduce predictors to improve the forecast accuracy based on a physics-based framework. Three ML models (ARIMA, LSTM, and XGBoost) are examined and compared with four physics-informed persistence models reported in Part I and the simple persistence model to assess the improvement of different models. The 7-year measurements at the U.S. Department of Energy's Atmospheric Radiation Measurement's Southern Great Plains Central Facility site are used for forecasts and evaluations. The results reveal that the step-by-step introduction of predictors leads to different improvements for models at different hierarchical levels. Comparison of the ML models with persistence models shows that LSTM and XGBoost outperform all the persistence models, with LSTM having the overall best performance; however, ARIMA underperforms the four physics-informed persistence models. This study demonstrates the importance and utility of incorporating physics into ML models in improving forecast accuracy by introducing a hierarchy of physics-based predictors, distinguishing predictor contributions, and enhancing the ML interpretability. The combined use of Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) significantly improves the forecast accuracy compared to using individual irradiances alone because the pair contains more information on cloud-radiation interactions.

interpretability↗
DOE OSTI2025

Effects of non-monochromaticity in laboratory XPS: Representative example of pyrimidine

The Mg and Al K α radiation used in standard laboratory sources for X-Ray Photoelectron Spectroscopy, XPS, is not naturally monochromatic because the spin orbit splitting of the Mg and Al 2p shells is not normally resolved. However, since the 2p spin-orbit splitting of the K α1 and K α2 X-Rays in these light atoms is small, it is normally ignored. In the present work, the consequences of the departure from monochromaticity is explicitly shown to be extremely small for the representative case of the C(1 s) ionizations in the XPS of the pyrimidine molecule. Furthermore, this conclusion is general and does not depend on the particular molecule studied since the K α1 and K α2 BE splittings reflect the spin-orbit splittings in the X-Ray source.

Binding Energies (BEs)↗
DOE OSTI2023

Deep learning integrates histopathology and proteogenomics at a pan-cancer level

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

60 APPLIED LIFE SCIENCES↗