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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 235 records · Page 13

High Power Light Gas Helicon Plasma Source For VASMIR

The VASIMR space propulsion development effort relies on a high power (greater than 10kW) helicon source to produce a dense flowing plasma (H, D and He) target for ion cyclotron resonance (ICR) acceleration of the ions. Subsequent expansion in an expanding magnetic field (magnetic nozzle) converts ion lunetic energy to directed momentum. This plasma source must have critical features to enable an effective propulsion device. First, it must ionize most of the input neutral flux of gas, thus producing a plasma stream with a high degree of ionization for application of ICR power. This avoids propellant waste and potential power losses due to charge exchange. Next, the plasma stream must flow into a region of high magnetic field (approximately 0.5 T) for efficient ICR acceleration. Third, the ratio of input power to plasma flux must be low, providing an energy per ion-electron pair approaching 100 eV. Lastly, the source must be robust and capable of very long life-times (years). In our helicon experiment (VX-10) we have measured a ratio of input gas to plasma flux near 100%. The plasma flows from the helicon region (B approximately 0.1 T) into a region with a peak magnetic field of 0.8 T. The energy input per ion-electron pair has been measured at 300 plus or minus 100 eV. Recent results at Oak Ridge National Laboratory (ORNL) show an enhanced efficiency mode of operation with a high power density, over 5 kW in a 5 cm diameter tube. Our helicon is presently 9 cm in diameter and operates up to 3.5 kW of input power. An upgrade to a power level of 10 kW is underway. Much of our recent work has been with a Boswell double-saddle antenna design. We are also converting the antenna design to a helical type. With these modifications, we anticipate an improvement in the ionization efficiency. This paper presents the results from scaling the helicon in the VX-10 device from 3.5 to 10 kW. We also compare the operation with a double-saddle to a helical antenna design. Finally, we discuss modeling of these configurations using ORNL's EMIR code.

Squire, J. P.↗

Tailored Bioblendstocks With Low Environmental Impact To Optimize MCCI Engines

The prohect goal is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel.

09 BIOMASS FUELS↗

BETO 2021 Peer Review - Improving Formate Upgrading by Cupriavidus Necator 2.3.2.111

Formate can be generated by electrocatalytic reduction of CO2 and has been proposed as a soluble intermediate for the storage of carbon and energy. Biological systems capable of assimilating formate could enable conversion of formate generated from low-cost renewable energy and waste CO2 to myriad fuels and chemicals. To that end, the goal of this project is to develop the natural formatotroph Cupriavidus necator as a robust microbial chassis for efficient conversion of formate to value-added products. Using a combination of laboratory evolution and rational engineering, we have identified mutations and genetic deletions that improve its growth rate and biomass yield on formate by 1.2X. Using RNA-seq transcriptomics, we are elucidating the mechanisms that underly these improvements and anticipate this will contribute to our understanding of formate conversion. We have also engineered C. necator to convert formate to the potential polymer precursor 2-hydroxymuconate semialdehyde (2HMS) by introducing an exogenous pathway and deleting competing pathways and demonstrated production and robust growth using a pH-stat bioreactor. Final techno-economic analysis and life-cycle assessment on biological production of 2HMS from formate will enable the DOE and other stake holders to evaluate the economic and environmental impact of this project and related technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Tailored Bioblendstocks with Low Environmental Impact to Optimize MCCI Engines (Final Technical Report)

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Overall, the project achieved the proposed objectives including producing the final tangible deliverable. A sample of algal bioblendstock was analyzed by National Renewable Energy Laboratory (NREL) staff and partners at Yale University. In addition, the work outlined in this report provides substantial new knowledge on the subjects of algae cultivation, algae conversion to biocrude, biocrude upgrading and combustion optimization.

09 BIOMASS FUELS↗

Compact, Engineered, 2-Micron Coherent Doppler Wind Lidar Prototype: A New NASA Instrument Incubator Program Project

A new project, selected in 2005 by NASA s Science Mission Directorate (SMD) under the Instrument Incubator Program (IIP), will be described. The 3-year effort is intended to design, fabricate, and demonstrate a packaged, rugged, compact, space-qualifiable coherent Doppler wind lidar (DWL) transceiver capable of future validation in an aircraft and/or Unmanned Aerial Vehicle (UAV). The packaged DWL will utilize the numerous advances in pulsed, solid-state, 2-micron laser technology at NASA s Langley Research Center (LaRC) in such areas as crystal composition, architecture, efficiency, cooling techniques, pulse energy, and beam quality. The extensive experience of Raytheon Space and Airborne Systems (RSAS) in coherent lidar systems, in spacebased sensors, and in packaging rugged lidar systems will be applied to this project. The packaged transceiver will be as close to an envisioned space-based DWL system as the resources and technology readiness allow. We will attempt to facilitate a future upgrade to a coherent lidar system capable of simultaneous wind and CO2 concentration profile measurements. Since aerosol and dust concentration is also available from the lidar signal, the potential for a triple measurement lidar system is attractive for both Earth and Mars remote sensing. A key follow on step after the IIP will be to add a telescope, scanner, and software for aircraft validation. This IIP should also put us in a position to begin a parallel formulation study in the 2006-2007 timeframe for a space-based DWL demonstration mission early next decade.

Kavaya, Michael J.↗

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗

Conversion, Stability, and Selectivity Improvements Through Catalyst Development for the Reductive Etherification Reaction

Economical pathways from lignocellulosic non-food biomass feedstocks to biofuels with appropriate fuel properties are necessary for displacing fossil-fuel derived diesel use in medium-/heavy duty vehicles. Oxygenated compounds have recently shown promise due to low sooting tendencies and autoignition properties and molecules with sufficiently high carbon numbers can meet the requisite standards for water solubility and flash point. Coupling waste biomass derived small molecules into bioblendstock targets through the reductive etherification reaction shows potential for increasing molecular weight without losing the advantages of oxygenates. However, the transition to industrial viability for this process is limited by strong catalyst deactivation in typical flow reactor systems. Strong acid resins such as Amberlyst-15 (A-15) show excellent activity in batch reactions but are limited to low temperatures and are poisoned by the side-product, water. In this talk, I will describe our recent work in catalyst synthesis and testing to select superior options with improved aqueous and thermal stability in reductive etherification flow reactions. Water-tolerant solid acid catalysts have potential to improve the conversion and selectivity to the ether target at temperatures above the degradation point of A-15. Analysis techniques such as physisorption, chemisorption, x-ray diffraction and transmission electron microscopy are being used to characterize the active sites. These techniques are also being used to evaluate degradation of the catalyst after extensive flow reactions in addition to comparative efficiency testing with standardized cyclohexene hydrogenation reactions. Finally, I will discuss a demonstration of the full pathway from bio-derived butyric acid to the performance-advantaged ether product and the additional obstacles from side-products and purification limitations in the preliminary upgrading reactions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The sweeper spectrometer for neutron invariant-mass spectroscopy at FRIB

Neutron invariant-mass spectroscopy (NIMS) is a key technique for studying unbound and weakly bound nuclei at the limits of stability. At the Facility for Rare Isotope Beams (FRIB), such measurements are performed using the Sweeper spectrometer, a large-gap, high-rigidity dipole system coupled to the MoNA-LISA neutron detector arrays. To meet the demands imposed by higher beam energies (>130 MeV/u) and the broad cocktail-beam selection available at FRIB, the spectrometer has recently been upgraded to improve particle-identification and detection performance. Upstream of the reaction target, a plastic scintillator with Silicon photomultiplier (SiPM) readout provides the global trigger and time reference, two parallel plate avalanche counters (PPACs) track the trajectories of incoming beam particles, and a silicon PIN detector measures the energy loss, ΔE, for charge (Z) identification. After the Sweeper magnet, the trajectories of the reaction products are tracked by two micro-pattern drift chambers (MPDCs), their charge (Z) is identified by a Frisch-grid ionization chamber (FG-IC), and their mass-to-charge ratio (A/Q) is deduced by time-of-flight measurement using a fast plastic scintillator read out by an array of photomultiplier tubes (PMTs). The detection system also incorporates the Modular Neutron Array (MoNA) for neutron detection and the CAESium-iodide scintillator ARray (CAESAR) for high-efficiency γ-ray measurements to enable full kinematic reconstruction. Performance was evaluated using a cocktail beam around 37 Al accelerated at E ≈ 130 MeV/u during the first FRIB campaign, demonstrating the readiness of the upgraded system for future studies of nuclei at and beyond the neutron drip line.

Particle identification methods↗

Collaborative Research Towards a tonne-scale bolometer-based neutrinoless double beta decay experiment (Final Report)

Cryogenic bolometers are an excellent technology for neutrinoless double beta decay searches owing to their very high energy resolution and potential for high radiopurity. The current most advanced large-scale experiment using these detectors is the Cryogenic Underground Observatory for Rare Events (CUORE). The largest source of background in CUORE is degraded alpha particles, emitted from shallow depths of the detector holders, which can deposit a thermal energy signature similar to neutrinoless double beta decay. To mitigate this background, the CUPID concept (CUORE Upgrade with Particle IDentification) proposes to use scintillating cryogenic detectors. Detecting both the scintillation light and the thermal signal allows discrimination between alpha particle events and beta/gamma events. We report on the design and execution of R&D tests to optimize the design of the single detector module, in particular the scintillation light collection efficiency at cryogenic temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Benign termination of runaway electron beams on ASDEX Upgrade and TCV

Abstract This paper discusses the development of a benign termination scenario for runaway electron (RE) beams on ASDEX Upgrade and TCV. A systematic study revealed that a low electron density (n e ) companion plasma was required to achieve a large MHD instability, which expelled the confined REs over a large wetted area and allowed for the conversion of magnetic energy to radiation. Control of the companion plasma n e was achieved via neutral pressure regulation and was agnostic to material injection method. The neutral pressure required for recombination was found to be dependent on impurity species, quantity and RE current. On TCV,n e increased at neutral pressures above 1 Pa, indicating that higher collisionality between the REs and neutrals may lead to an upper pressure limit. The conversion of magnetic energy to radiated energy was measured on both machines and a decrease in efficiency was observed at high neutral pressure on TCV. The benign termination technique was able to prevent any significant increase in maximum heat flux on AUG from 200 to 600 kA of RE current, highlighting the ability of this approach to handle fully formed RE beams.

Physics↗

Deep Eutectic Solvents for Pretreatment of Lignocellulose Biomass: Physical Properties, Solubility Mechanisms, and Their Interactions

As the most accessible and abundant renewable resource on earth, lignocellulosic biomass mainly consists of cellulose, hemicelluloses, and lignin with a small amount of protein, pectin, minerals, and extractives (e.g., tannins, lipids, and resins). Lignocellulosic biomass has gained extensive attention in industry and research owing to its renewability, availability, and low cost. However, achieving efficient fractionation of lignocellulose components and all-component utilization in a green and cost-effective manner remains a challenge dueto biomass recalcitrance. Deep eutectic solvents (DESs) have received considerable attention because they are biocompatible, inexpensive, biodegradable, have low toxicity, and are easy to prepare and recycle; these characteristics strongly depend on individual components involved in DESs preparation. This review systematically summarizes recent progress in the fractionation of carbohydrates (cellulose and hemicelluloses) and lignin from biomass using DESs, with particular emphasis on the effects of DES types and pretreatment parameters on fractionation efficiency. The subsequent conversion and upgrading of the DES-fractionated products (i.e., carbohydrates and lignin) are comprehensively analyzed. Finally, the challenges and future prospects of lignocellulose biomass fractionation using DESs are proposed in view of the existing limitations. This review provides an in-depth understanding of lignocellulose biomass fractionation during DESs processing, offering insights to improve current pretreatment methods and/or to explore new pretreatment methods aimed at mitigating the global energy crisis.

Mqoni, Ntebogeng [North-West University (Mafikeng ↗

Harnessing Virtual Power Plants Reliably: Enabling tools for increased observability, controllability, operation, and aggregation of distributed energy resources

Harnessing virtual power plants enhances the integration of distributed energy resources into utility grids for a sustainable energy future. Virtual power plants (VPPs) aggregate DERs to enhance resource adequacy and reduce emissions. U.S. utilities are exploring various technologies to manage DERs effectively. FERC Order 2222 allows DERs to participate in both wholesale and retail markets. Enhancing observability and controllability of behind-the-meter (BTM) DERs is essential for reliable grid operations. A hierarchical control architecture can improve coordination among residential energy resources. Field tests showed nearly 20% energy savings and 30% peak power reduction during grid events. Effective management of DERs requires enhanced situational awareness to prevent grid congestion. Integrating DER management systems (DERMS) with existing planning tools can improve operational security. Near-real-time grid models can validate optimal resource set points against resource uncertainty. Traditional uninterruptible power supplies (UPS) can be upgraded to support grid services and become part of VPPs. Upgrading UPS systems can reduce costs by 75% and unlock significant battery capacity. New battery management systems and grid-aware controllers are essential for optimizing UPS performance. Continued research and development are necessary to address challenges in integrating DERs into utility grids. Encouraging customer participation in pilot programs is vital for the evolution of VPPs. Here, the shift towards price-responsive DERs and VPPs is expected to enhance energy distribution efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ADRIANO2 Calorimeter Performance from 2022 Test Beams

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration. The ADRIANO2 Calorimeter Prototype consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. Čerenkov light from the lead glass are exploited to for high resolution timing measurements, while high granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle detection for REDTOP as it is crucial for a calorimeter to detect the decay products of eta/eta-prime mesons. Measurements were collected on ADRIANO2 between February to December 2022 to evaluate the detector performance at Fermilab’s Test Beam Facility. The key metrics extracted from my analysis are the detector’s efficiency for various tile configuration and light-yield which will then be used as parameters for an upgraded REDTOP monte-carlo simulation campaign. An in-depth analysis of ADRIANO2 performance are detailed in this presentation.

43 PARTICLE ACCELERATORS↗

Kentucky: Using LEAD Tool Data to Fund Energy Efficiency Programs

The Kentucky Office of Energy Policy (OEP) applied the U.S. Department of Energy’s (DOE’s) web-based Low-Income Energy Affordability Data (LEAD) Tool to identify areas of their state with energy affordability needs. Kentucky OEP staff used the LEAD Tool to identify counties in Kentucky with the highest energy burden, which is the percentage of household income spent on energy. With this knowledge, Kentucky OEP staff allocated funds to relevant nonprofit organizations that provide home repairs, weatherization upgrades, and other solutions in areas where these services have the highest potential energy saving benefits and can reduce energy burden.

Low-Income Energy Affordability Data Tool, LEAD To↗

Test results of the Chrysler upgraded automotive gas turbine engine: Initial design

The upgraded engine as built to the original design was deficient in power and had excessive specific fuel consumption. A high instrumented version of the engine was tested to identify the sources of the engine problems. Analysis of the data shows the major problems to be low compressor and power turbine efficiency and excessive interstage duct losses. In addition, high HC and CO emission were measured at idle, and high NOx emissions at high energy speeds.

Horvath, D.↗

Identification of opportunities for integrating chemical processes for carbon (dioxide) utilization to nuclear power plants

The energy and industrial sectors are responsible for more than 75% of global carbon dioxide emissions, which are primary contributors to climate change. Decarbonization strategies to reduce overall carbon dioxide emissions are urgently needed. Among the numerous decarbonization strategies that are being defined and implemented, a particular strategy of interest for the present work is “the Re-X or zero waste” strategy, which involves recycling, reuse, repurposing, and remanufacturing of industrial emissions, by-products, and waste in general. A circular value chain or Circular Economy is embedded within this strategy. In a circular carbon economy, efficient reuse of emitted carbon dioxide is considered. However, the stability of carbon dioxide implies the requirement of significant amounts of energy for its transformation into value-added chemicals or products, which must be supplied by low carbon emitting energy sources. Nuclear power plants are low carbon energy sources that, additionally to electricity, could also supply heat and radiation for chemical transformations. This work identifies the opportunities and challenges for the development of integrated energy systems to upgrade and transform carbon dioxide, involving chemical and nuclear energy. The analysis encompasses possible use of the different forms of energy that can be obtain from nuclear reactors (i.e., radiation, electricity, and heat), by reviewing the published literature on potential routes for its conversion. Overall, our review indicates that an universal technology of the one-fits-all solution-type is an utopic dream. Instead, a suite of (contaminants tolerant) technologies for processing various concentrations CO 2 and producing a variety of products is currently needed.

08 HYDROGEN↗

TexAT detector upgrade for 14 O($α$, $p$) 17 F cross section measurement

A direct cross-section measurement of the 14 O($α$, $p$) 17 F reaction is important to understand the light curves of x-ray bursts. The measurement will be performed using the Texas Active Target TPC version 2 (TexAT_v2). The TexAT_v2 aims at measuring lower energy protons from the reaction than the original TexAT. Newly developed silicon and CsI(Tl) detector arrays are added at the left, right and bottom of a modified field cage to increase its detection efficiency. Furthermore, this paper describes the overall specifications and two commissioning experiments performed at Texas A&M University.

14O(α, p)17F↗

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗