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DOE OSTI2025

Design and full core fuel performance assessment of high burnup cores for 4-loop PWRs

Increasing the fuel discharge burnup of current light water reactors (LWRs) promises reductions in fuel cycle and/or operations costs. By assuming a constant core power density, the economic gain is enabled by better fuel utilization and/or an increased capacity factor. In this effort to investigate greater than 62 MWd/kgU maximum rod average burnup for 110+ kW/l core power density, two core designs have been developed for a standard 17x17, 193 fuel assemblies pressurized water reactor (PWR). The levelized unit cost methodology is employed to evaluate fuel cycle, operation and maintenance, and capital cost impacts and to examine the economic viability of both core design pathways. Core design and optimization are performed using the commercial STUDSVIK code package. Fuel performance analysis is realized in full core configuration via auditing FRAPCON4.1, FAST1.2, and the high-fidelity code BISON. To provide a realistic assessment, the core design process takes into consideration best practices in current PWR core design. It features acceptable performance in terms of various core design constraints on maximum allowable peaking and boron concentration. Gadolinia (Gd2O3) is used as a burnable poison with a maximum of 9 wt% concentration while feeding 89 or 77 fuel assemblies in a 3-batch refueling scheme. Full core fuel performance simulation, which allows for characterization of relevant fuel temperatures, plenum pressures, stresses, and strains, is performed with respect to two bounding burnup levels. Such performance is potentially licensable for the 18-month high burnup core (<68 MWd/kgU peak pin), while it is more challenging for the 24-month high burnup core design pathway (<75 MWd/kgU peak pin). Maximum rod plenum pressure is identified as the most limiting fuel performance parameter. Here, while the scope of the present study focuses on the steady-state plus overpower conditions, the acceptability of the new discharge burnup has to be further assessed by considering uncertainties and impacts under accident scenarios in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Visualization of Hierarchical Nanodomains in Polymer/Fullerene Bulk Heterojunction Solar Cells

Here, traditional electron microscopy techniques such as bright-field imaging provide poor contrast for organic films and identification of structures in amorphous material can be problematic, particularly in high-performance organic solar cells. By combining energy-filtered corrected transmission electron microscopy, together with electron energy loss and X-ray energy-dispersive hyperspectral imaging, we have imaged PTB7/ PC 61 BM blended polymer optical photovoltaic films, and were able to identify domains ranging in size from several hundred nanometers to several nanometers in extent. This work verifies that microstructural domains exist in bulk heterojunctions in PTB7/PC 61 BM polymeric solar cells at multiple length scales and expands our understanding of optimal device performance providing insight for the design of even higher performance cells.

14 SOLAR ENERGY↗

DOE OSTI2015

Transition of Iodine Analysis to Accelerator Mass Spectrometry

The goal of the project, New Paradigms for Isotope Ratio Mass Spectrometry: Raising the Scientific Profile and Improved Performance for Accelerator Mass Spectrometry (AMS) and Thermal Ionization Mass Spectrometry (TIMS), is to ensure that the ongoing isotope ratio determination capability within the U.S. Department of Energy complex is the world’s best for application to nonproliferation. This report spells out the progress of Task 4, Transition of TIMS to AMS for Iodine Analysis, of the larger project. The subtasks under Task 4 and the accomplishments throughout the three year project life cycle are presented in this report. Progress was made in optimization of chemical extraction, determination of a detection limit for 127Iodine, production of standard materials for AMS analysis quality assurance, facilitation of knowledge exchange with respect to analyzing iodine on an AMS, cross comparison with a world-leading AMS laboratory, supercritical fluid extraction of iodine for AMS analysis and electrodeposition of seawater as a direct method of preparation for iodine analysis by AMS--all with the goal of minimizing the time required to stand up an AMS capability for iodine analysis of exposed air filters at INL. An effective extraction method has been developed and demonstrated for iodine analysis of exposed air filters. Innovative techniques to accomplish the cathode preparation for AMS analysis were developed and demonstrated and published. The known gap of a lack of available materials for reference standards in the analysis of iodine by AMS was filled by the preparation of homogenous materials that were calibrated against NIST materials. A minimum limit on the amount of abundant isotope in a sample was determined for AMS analysis. The knowledge exchange occurred with fantastic success. Scientists engaged the international AMS community at conferences, as well as in their laboratories for collaborative work. The supercritical fluid extraction work has positive data, but is not a replacement for leaching yet. The added seawater work has led to a good method and a possible publication. The focus of this project was to minimize the time to stand up the AMS capability, by having all the preparation and supporting functions worked out ahead of the instrument arrival. Due to all the preparatory work and its success, the instrument was delivered and turned over to the INL in February 2015. Since then, INL scientists have been successfully vetting the capabilities and accomplishing their own measurements that agree well with the leading laboratories of the world for iodine analysis by AMS. Initially, all AMS data was gathered on other laboratories instruments, but during the last six months data for this project has come from INL’s AMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Extracting and Generating PV Soiling Profiles for Analysis, Forecasting, and Cleaning Optimization

The identification and prediction of the daily soiling profiles of a photovoltaic site is essential to plan the optimal cleaning schedule. In this article, we analyze and propose various methods to extract and generate photovoltaic soiling profiles, in order to improve the analysis and the forecast of the losses. New soiling rate extraction methods are proposed to reflect the seasonal variability of the soiling rates and, for this reason, are found to identify the most convenient cleaning day with the highest accuracy for the investigated sites. Also, we present an approach that could be used to predict future soiling losses through the implementation of stochastic weather generation algorithms whose ability to identify in advance the best cleaning schedule is also successfully tested. The methods presented in this article can optimize the operation and maintenance schedule and could make it possible, in the future, to predict soiling losses through analysis based only on environmental parameters, such as rainfall and particulate matter, without the need of long-term soiling data.

14 SOLAR ENERGY↗

DOE OSTI2024

Influence of Linker Group on Bipolar Redox-Active Molecule Performance in Non-Aqueous Redox Flow Batteries

Redox flow batteries (RFBs) are an attractive choice for stationary energy storage of renewables such as solar and wind. Non-aqueous redox flow batteries (NARFBs) have garnered broad interest due to their high voltage operation compared to their aqueous counterparts. Further, the utilization of bipolar redox-active molecules (BRMs) is a practical way to alleviate crossover faced by asymmetric RFBs. In this work, ferrocene (Fc) and phthalimide (PI) are covalently linked with various tethering groups which vary in structure and length. The compiled results suggest that the length and steric shielding ability of the linker group can greatly influence the stability and overall performance of Fc-n-PI BRM-based NARFBs. Primary sources of capacity loss are found to be BRM degradation for straight chain spacers <6 carbons and membrane (Nafion) fouling. Fc-hexyl-PI provided the most stable battery cycling and coulombic efficiencies of >98 % over 100 cycles (~13 days). NARFB using Fc-hexyl-PI as an active material exhibited high working voltage (1.93 V) and maximum capacity (1.28 Ah L -1 ). Additionally, this work highlights rational strategies to improve cycling stability and optimize NARFB performance.

25 ENERGY STORAGE↗

DOE OSTI2020

Tunable Catalytic Performance of Palladium Nanoparticles for H 2 O 2 Direct Synthesis via Surface-Bound Ligands

There is a critical need for sustainable routes to produce hydrogen peroxide, H 2 O 2 . A promising approach involves direct synthesis from molecular hydrogen and oxygen at (sub)ambient temperatures using unmodified supported Pd catalysts, which are limited by low selectivities. Controlling the environment of Pd active sites via surface ligands is shown to enhance selectivity. Trends among a myriad of surface ligands (i.e., phosphines, thiols, weakly bound molecules) suggest that those containing H-bonding groups lead to the highest H 2 O 2 production, potentially by affecting reaction energetics via H-bonding with key intermediates. These insights lay the groundwork for ligand design to achieve the optimal catalyst performance for H 2 O 2 synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays”. In the the four-year effort, VT-CPT collaborated with the Departments of Mathmatics at VT and Sentek Instrument, LLC (Sentek) to develop a fiber-optic sensing system capable of real-time simultaneous distributed measurement of multiple subsurface, drilling, and production parameters. The ultra-sensitive fiber optic distributed acoustic sensing technology, picoDAS, developed by Sentek was integrated with a novel multi-material optical sensing fiber fabricated by CPT-VT to obtain distributed acoustic and magnetic field measurements with ultrahigh sensitivity and high spatial resolution. The sensing technology successfully developed and demonstrated under this research program is truly unique has application beyond subsurface imaging to include carbon storage and electrical grid monitoring, as well as healthcare and nuclear fusion. The project, sponsored by the Advanced Technology Program, began in 2019 and had the original goal of developing the next generation of harsh environment sensing systems. Exhaustive theoretical modeling was performed to optimize the multi-material optical fiber design. VT developed the processing techniques employed to successfully fabricate single mode fibers with metal cladding wires. Sensing fibers with nickel and Metglas cladding wires were fully characterized, inscribed with sensors, and fully integrated with the picoDAS system. Laboratory scale testing was performed to demonstrate performance upon exposure to lateral and transverse magnetic fields. Preliminary field trials were performed for prototype magnetic and acoustic sensing systems upon near surface deployment at VT. The distributed acoustic and magnetic field sensing system was advanced from a (Technology Readiness Level) TRL=2 to a TRL=5 via laboratory scale system validation in relevant environments. The truly one-of-its kind distributed magnetic and acoustic sensing system is expected to find immediate applications that require subsurface monitoring, to include carbon storage site monitoring, and has the potential to be a distributive technology in healthcare and electric grid markets. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future by ensuring affordable, abundant, and reliable energy that drives a robust economy and national security. Technical accomplishments during the program are summarized briefly here and described in detail in the remainder of the report.

02 PETROLEUM↗

DOE OSTI2017

Heat Treatment Optimization of Rutherford Cables for a 15 T Nb 3 Sn Dipole Demonstrator

FNAL has been developing a 15 T Nb 3 Sn dipole demonstrator for a future Very High Energy pp Collider based on an optimized 60-mm aperture 4-layer “cos-theta” coil. In order to increase magnet efficiency, we graded the coil by using two cables with same 15 mm width and different thicknesses made of two different Restacked Rod Process (RRP®) wires. Due to the non-uniform field distribution in dipole coils the maximum field in the inner coil will reach 15-16 T, whereas the maximum field in the outer coil is 12-13 T. In preparation for the 15 T dipole coil reaction, heat treatment studies were performed on strands extracted from these cables with the goal of achieving the best coil performance in the corresponding magnetic fields. Particularly, the effect of maximum temperature and time on the cable critical current was studied to take into account actual variations of these parameters during coil reaction. In parallel and in collaboration with OST, development was performed on optimizing Nb 3 Sn RRP® wire design and layout. Index Terms— Accelerator magnet, critical current density, Nb 3 Sn strand, Rutherford cable.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Society of abdominal radiology gastrointestinal bleeding disease-focused panel consensus recommendations for CTA technical parameters in the evaluation of acute overt gastrointestinal bleeding

Purpose: To formulate consensus recommendations for CT angiography technical parameters used to evaluate overt gastrointestinal (GI) bleeding. Methods: An electronic questionnaire consisting of 17 questions was sent to a panel of 16 radiologists with expertise on the imaging of GI bleeding from the Society of Abdominal Radiology GI Bleeding disease-focused panel to obtain consensus agreement on issues related to CTA technical parameters for imaging overt GI bleeding. A multi-round Delphi method of voting was performed to obtain consensus which was defined as ≥ 80% agreement. Results: Consensus agreement was reached in 15/17 (89%) of the questions including the technique for the administration of IV contrast, the number of phases, scan timing, and image reconstruction. Conclusions: A panel of experts on the imaging of GI bleeding from the Society of Abdominal Radiology was able to reach consensus on the majority of technical parameters used for CTA of overt GI bleeding. These recommendations should improve the quality of patient care by adopting these minimal technical requirements for optimal exam performance and lead to less variation in the performance of these exams which will facilitate collecting and comparing published data from different centers. These recommendations will need revisions as additional scientific data become available.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Recent Experiments At Ndcx-II: Irradiation Of Materials Using Short, Intense Ion Beams

We present an overview of the performance of the Neutralized Drift Compression Experiment-II (NDCX-II) accelerator at Berkeley Lab, and summarize recent studies of material properties created with nanosecond and millimeter-scale ion beam pulses. The scientific topics being explored include the dynamics of ion induced damage in materials, materials synthesis far from equilibrium, warm dense matter and intense beam-plasma physics. We summarize the improved accelerator performance, diagnostics and results of beam-induced irradiation of thin samples of, e.g., tin and silicon. Bunches with over 3x10^10 ions, 1- mm radius, and 2-30 ns FWHM duration have been created. To achieve these short pulse durations and mm-scale focal spot radii, the 1.2 MeV He+ ion beam is neutralized in a drift compression section which removes the space charge defocusing effect during final compression and focusing. Quantitative comparison of detailed particle-in-cell simulations with the experiment play an important role in optimizing accelerator performance; these keep pace with the accelerator repetition rate of ~1/minute.

Seidl, PA↗

DOE OSTI2023

Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (DEMO-FTES) [Abstract]

Approximately half of global energy consumption is used for heating and cooling. Because fossil fuels are used to meet most of this demand, heating and cooling of buildings produces a large portion of global greenhouse gas (GHG) emissions. The proposed project seeks to demonstrate the feasibility of a seasonal thermal energy storage concept called fracture thermal energy storage (FTES), which has the potential to dramatically lower energy requirements for heating and cooling and improve the resilience of building energy systems. FTES is a technique for building a highly efficient heat exchanger by creating a carefully designed set of fractures in the ground below a building. This heat exchanger allows thermal energy to be stored over seasonal timeframes—for example, hot thermal energy that is easily captured in the summer or energy from waste heat sources—to meet heating needs during colder months. FTES offers a solution with a relatively small footprint and lower cost compared to currently operating aquifer thermal energy storage (ATES) systems and could be used in the many areas without aquifers suitable for ATES. If commercialized, FTES systems could exceed the 2.5 TWh of energy storage per year from the more than 2,800 ATES systems in operation worldwide, which range from 0.1 MW to 30 MW. The savings in CO2 emissions per year are also expected to match or exceed individual ATES projects, with the largest, a 30 MW system used to provide heating and cooling to the University of Technology in Eindhoven in the Netherlands, estimated to save 13,000 tons of CO2 emissions per year. FTES utilizes mature drilling and fracturing technology and therefore has the potential to be rapidly commercialized once demonstrated. The ability to construct and establish flow through an FTES heat exchanger has been demonstrated by a previous project and the potential for efficient, large-capacity energy storage has been shown using numerical models. However, no experimental validation of these numerical estimates of thermal energy storage has been made. The first crucial need to advance FTES technology is to identify the sensitivity of key metrics such as thermal energy storage and production rates, capacities, and efficiencies to design parameters such as the number of fractures, depth/temperature of fractures, size of fractures, and circulation rates. The second crucial need is experimental testing of achievable thermal performance with optimized system design parameters. The proposed scope of work seeks to systematically address these two critical needs through a highly complementary international collaboration spanning theory, laboratory, and mesoscale field evaluation. The proposed work plan calls for using dimensional analysis and existing state-of-the-art numerical simulators to design carefully scaled laboratory and 10-meter-scale field tests of the thermal efficiency of FTES. The existing advanced laboratory and intermediate-scale field testbeds that will be used for this project will allow for detailed monitoring of the system performance during the test and of how the performance changes across time and length scales. These results will determine the feasibility of full- scale FTES systems. If the thermal performance is consistent with model predictions, the results will provide a strong economic justification for rapid commercialization of FTES technology in a wide range of geographical areas.

25 ENERGY STORAGE↗

DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Operations research modeling in support of the Hanford direct feed low activity waste program - 15538

Operations Research (OR) modeling is a supplemental system planning tool for the Hanford Tank Farm Contractor. OR models are designed to quantify the impact of equipment failures and other constraints on mission duration; to determine overall system performance; and to identify any potential bottleneck areas and identify any potential improvement areas. OR models are being developed to provide critical insights into the expected operational performance of current and planned facilities and to help identify any operational risks which impact performance of plant and equipment. This information is used to aid decision making on facility design and operations. A new OR model is being developed in support of the Direct Feed Low Activity Waste (DFLAW) Program and will be a valuable tool in the development of overall operational and management strategies as well as providing input to facility design. The OR model will identify predicted system availability, process bottlenecks, and key equipment influencing system performance. The OR model will also test proposed solutions to improve system availability by resolving process bottlenecks and provide this information to the design agent for incorporation into the DFLAW process design. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Laser-Induced Graphene Composites for Printed, Stretchable, and Wearable Electronics

Not provided.

Materials Science↗

DOE OSTI2014

Sci—Thur PM: Planning and Delivery — 06: Real-Time Interactive Treatment Planning

Purpose: To describe and evaluate a novel system for generalized Real-Time Interactive Planning (RTIP) applied to head and neck (H and N) VMAT. Methods: The clinician interactively manipulates dose distributions using DVHs, isodoses, or rate of dose fall-off, which may be subjected to user-defined constraints. Dose is calculated using a fast Achievable Dose Estimate (ADE) algorithm, which simulates the limits of what can be achieved during treatment. After each manipulation contributing fluence elements are modified and the dose distribution updates in effectively real-time. For H and N VMAT planning, structure sets for 11 patients were imported into RTIP. Each dose distribution was interactively modified to minimize OAR dose while constraining target DVHs. The resulting RTIP DVHs were transferred to the Eclipse™ VMAT optimizer, and conventional VMAT optimization was performed. Results: Dose calculation and update times for the ADE algorithm ranged from 2.4 to 22.6 milliseconds, thus facilitating effectively real-time manipulation of dose distributions. For each of the 11 H and N VMAT cases, the RTIP process took ∼2–10 minutes. All RTIP plans exhibited acceptable PTV coverage, mean dose, and max dose. 10 of 11 RTIP plans achieved substantially improved sparing of one or more OARs without compromising dose to targets or other OARs. Importantly, 10 of the 11 RTIP plans required only one or two post-RTIP optimizations. Conclusions: RTIP is a novel system for manipulating and updating achievable dose distributions in real-time. H and N VMAT plans generated using RTIP demonstrate improved OAR sparing and planning efficiency. Disclosures: One author has a commercial interest in the presented materials.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Screening of Coulombic Interactions To Achieve a Higher Power Factor in Conjugated Polymers

Thermoelectric properties of conducting polymers typically suffer from molecular chain disordering, as charge transport is predominantly controlled by morphology. This is especially more problematic when counterions are introduced to tune the carrier concentration for optimal thermoelectric performance, which disturbs the morphology further. Here, in this work, we introduce a new avenue for enhancing thermoelectric properties without needing to regulate the morphology, namely, by controlling the coulombic interaction between polarons and counterions. We perform in situ de-doping thermoelectric experiments over 3 orders of magnitude change in electrical conductivity of three distinct thermoelectric polymers, namely, poly(3-hexylthiophene-2,5-diyl) (P3HT), poly[2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT-C 12 ), and poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (OD-PDPP2T-TT) conjugated polymers, followed by grazing-incidence wide-angle X-ray scattering (GIWAXS) to study their respective morphologies. We demonstrate a 9-fold enhancement in the thermoelectric power factor in OD-PDPP2T-TT compared to PBTTT-C 12 and link it to the coulombic screening of charge carriers, including in the optimally doped regime. We support this hypothesis using Boltzmann transport equations and show that, in both P3HT and PBTTT-C 12 , as the polymer is doped, impurity scattering remains the dominant scattering mechanism, while in OD-PDPP2T-TT, the scattering mechanism changes from impurity to acoustic phonon limited, resulting in more effective screening of ionized counterions. Our results provide an additional knob to enhance the fundamental understanding of thermoelectric physics of conducting polymers and provide a pathway to achieve higher performance in the field of organic thermoelectrics.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Data-driven analysis to understand GPU hardware resource usage of optimizations

With heterogeneous systems, the number of GPUs per chip increases to provide computational capabilities for solving science at a nanoscopic scale. However, low utilization for single GPUs defies the need to invest more money in expensive accelerators. Although related work develops optimizations to improve application performance, none studies how these optimizations impact hardware resource usage or average GPU utilization. Here, this paper takes a data-driven analysis approach in addressing this gap by (1) characterizing how hardware resource usage affects device utilization, execution time, or both, (2) presenting a multiobjective metric to identify important application-device interactions that can be optimized to improve device utilization and application performance jointly, (3) studying hardware resource usage behaviors of several optimizations for a benchmark application, and finally (4) identifying optimization opportunities for several scientific proxy applications based on their hardware resource usage behaviors. Furthermore, we demonstrate the applicability of our methodology by applying the identified optimizations to a proxy application, which improves the execution time, device utilization, and power consumption by up to 29.6%, 5.3% and 26.5% respectively.

Computer science↗

DOE OSTI2016

Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods

Purpose: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate. Methods: The performance of logistic regression, elastic-net, support-vector machine, random forest, neural network, and multivariate adaptive regression splines (MARS) to predict urinary symptoms was analyzed using data from 754 participants accrued by TROG03.04-RADAR. Predictive features included dose-surface data, comorbidities, and medication-intake. Four symptoms were analyzed: dysuria, haematuria, incontinence, and frequency, each with three definitions (grade ≥ 1, grade ≥ 2 and longitudinal) with event rate between 2.3% and 76.1%. Repeated cross-validations producing matched models were implemented. A synthetic minority oversampling technique was utilized in endpoints with rare events. Parameter optimization was performed on the training data. Area under the receiver operating characteristic curve (AUROC) was used to compare performance using sample size to detect differences of ≥0.05 at the 95% confidence level. Results: Logistic regression, elastic-net, random forest, MARS, and support-vector machine were the highest-performing statistical-learning strategies in 3, 3, 3, 2, and 1 endpoints, respectively. Logistic regression, MARS, elastic-net, random forest, neural network, and support-vector machine were the best, or were not significantly worse than the best, in 7, 7, 5, 5, 3, and 1 endpoints. The best-performing statistical model was for dysuria grade ≥ 1 with AUROC ± standard deviation of 0.649 ± 0.074 using MARS. For longitudinal frequency and dysuria grade ≥ 1, all strategies produced AUROC>0.6 while all haematuria endpoints and longitudinal incontinence models produced AUROC<0.6. Conclusions: Logistic regression and MARS were most likely to be the best-performing strategy for the prediction of urinary symptoms with elastic-net and random forest producing competitive results. The predictive power of the models was modest and endpoint-dependent. New features, including spatial dose maps, may be necessary to achieve better models.

60 APPLIED LIFE SCIENCES↗