Search NASA⌕ Search

SEARCH · Search NASA

Results for “parameter es”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

35 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Extremum Seeking-Based Control System for Particle Accelerator Beam Loss Minimization

Particle accelerators throughout the world vary widely in terms of age and availability of advanced noninvasive diagnostics that provide varying levels of detail about the accelerated beams. Additionally, beam loss measurements and current monitors are ubiquitous in the accelerator community, they are noninvasive, and they are some of the most important metrics in terms of preventing damage or irradiation of beam pipes and equipment for high-energy machines. However, beam loss and current measurements are difficult to use for feedback tuning because of a lack of a known analytic relationship between scalar loss measurements throughout an accelerator and the hundreds of thousands of parameters that influence the beam and time variation of the beam source itself. In this work, we present a model-independent extremum seeking (ES) controller, which has been implemented for automated tuning and optimization of the Los Alamos Neutron Science Center (LANSCE) linear ion accelerator based only on scalar quantities, such as beam loss or flux measurements. We demonstrate the approach on various accelerator subsystems, including groups of radio frequency (RF) accelerating cavities, quadrupole magnets, bending magnets, and steering magnets. This tool is now available as a use graphical user interface (GUI) in the LANSCE control room, allowing beam physicists to choose arbitrary groups of parameters and beam loss or current monitors for adaptive tuning.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2021

Quantifying the Uncertainty of the Future Hydrological Impacts of Climate Change: Comparative Analysis of an Advanced Hierarchical Sensitivity in Humid and Semiarid Basins

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. Further, the results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Annual Storm Water Report for the Y-12 National Security Complex Oak Ridge, Tennessee

This is the seventh annual storm water report prepared in accordance with the modified National Pollutant Discharge Elimination System permit issued to the Y-12 National Security Complex (Y-12) on April 1, 2014. This modified permit removed the authorization to augment flow in East Fork Poplar Creek (EFPC) and thus removed the requirement to sample this effluent in conjunction with other major outfalls on EFPC. The general condition of the site continues to improve. The concentrations of Escherichia Coli (Es. coli) at the major outfalls and instream monitoring locations on EFPC are no longer elevated as they were in 2018. Follow-up samples indicated normal levels. Monitoring for this parameter will continue into 2020. The repair of Outfall 014 is nearing completion and will be sampled for storm water in 2020. This repair was expected to occur in 2019 but was delayed until 2020. There are several construction and demolition activities currently in progress at Y-12. These include the construction of the Uranium Processing Facility (UPF), the Mercury Treatment Facility (MTF) on EFPC and the impending demolition of the Biology Complex. These projects will present challenges for the protection of storm water. Oversight of these activities will be a priority in 2020. Y-12 will continue to implement appropriate Best Management Practices and reduce outside material storage areas where possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leptodermic corrections to the TOV equations and nuclear astrophysics within the effective surface approximation

The macroscopic model for a neutron star (NS) as a liquid drop at the equilibrium is used to extend the Tolman-Oppenheimer-Volkoff (TOV) equations taking into account the gradient terms responsible for the system surface. The parameters of the Schwarzschild metric in the spherical case are found with these surface corrections to the known leading (zero) order of the leptodermic approximation a/R << 1, where a is the NS effective-surface (ES) thickness, and R is the effective NS radius. The energy density $\mathscr{E}$ is considered in a general form including the functions of the particle number density and of its gradient terms. The macroscopic gravitational component $Φ$(ρ) of the energy density is taken into account in the simplest form as expansion in powers of $ρ$ – $\overline{ρ}$, where $\overline{ρ}$ is the saturation density, up to second order, in terms of its contributions to the separation particle energy and incompressibility. Density distributions ρ across the NS ES in the normal direction to the ES, which are derived in the simple analytical form at the same leading approximation, was used for the derivation of the modified TOV (MTOV) equations by accounting for their NS surface corrections. As a result, the MTOV equations are analytically solved at first order and the results are compared with the standard TOV approach of the zero order.

Magner, A. G. [Institute for Nuclear Research, Kyi↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2025

Prediction of Redox Potentials for the Late Actinides Cm to Lr Using Electronic Structure Methods

Our previously developed computational method for calculating the aqueous redox potentials of the early actinides has been extended to the later elements in the actinide series: Cm, Bk, Cf, Es, Fm, Md, No, and Lr in multiple oxidation states. These calculations were performed using density functional theory with small-core pseudopotentials and their associated basis sets. Solvation effects were considered via a supermolecule-continuum approach, with 30 water molecules representing two solvation shells. Both the COSMO and SMD implicit solvation models were utilized. The structural parameters and hydration numbers for Cm(III), Bk(III), Bk(IV), and Cf(III) are in reasonable agreement with the available experimental data. For redox processes involving atomic cations in solution, the B3LYP/COSMO approach predicted redox potentials to within ±0.2 V of experiment for most redox couples, consistent with our prior work. Inclusion of spin-orbit corrections in specific redox pairs, especially those with the later actinides in high oxidation states, yields improved results relative to calculations including only scalar-relativistic corrections. The An +m /An(0) redox potentials were calculated using a Born-Haber cycle incorporating sublimation, ionization, and hydration energies. Due to a lack of experimental data, three sets of ionization energies were used for the Born-Haber cycle. The calculated An(III/0) potentials showed better agreement with experimental data when using the COSMO solvation model and the test set comprising the NIST recommended ionization energies. Furthermore, the Md(II/0) potential was better described with the SMD model, whereas No(II/0) was not well described by all methods. Finally, the computational approach was able to predict redox potentials that for most cases agreed with the current available experimental or estimated data.

Actinides↗
DOE OSTI2024

Ratio-preserving approach to cosmological concordance

Cosmological observables are particularly sensitive to key ratios of energy densities and rates, both today and at earlier epochs of the Universe. Well-known examples include the photon-to-baryon and the matter-to-radiation ratios. Equally important, though less publicized, are the ratios of pressure-supported to pressureless matter and the Thomson scattering rate to the Hubble rate around recombination, both of which observations tightly constrain. Preserving these key ratios in theories beyond the Λ Cold-Dark-Matter ( Λ CDM ) model ensures broad concordance with a large swath of datasets when addressing cosmological tensions. We demonstrate that a mirror dark sector, reflecting a partial Z 2 symmetry with the Standard Model, in conjunction with percentage level changes to the visible fine-structure constant and electron mass which represent a phenomenological change to the Thomson scattering rate, maintains essential cosmological ratios. Incorporating this ratio-preserving approach into a cosmological framework significantly improves agreement to observational data ( Δ χ 2 = - 35.72 ) and completely eliminates the Hubble tension with a cosmologically inferred H 0 = 73.80 ± 1.02 km / s / Mpc when including the S H 0 ES calibration in our analysis. While our approach is certainly nonminimal, it emphasizes the importance of keeping key ratios constant when exploring models beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Baryogenesis, primordial black holes and MHz–GHz gravitational waves

Gravitational waves (GWs) in the MHz–GHz frequency range are motivated by a host of early Universe phenomena such as oscillons, preheating, and cosmic strings. We point out that baryogenesis too serves as a motivation to probe GWs in this frequency range. The connection is through primordial black holes (PBHs): on the one hand, PBHs induce baryogenesis by Hawking evaporating into a species that has baryon number and CP violating decays; on the other, PBHs induce GWs through second order effects when the scalar fluctuations responsible for their formation re-enter the horizon. We describe the interplay of the parameters responsible for successful baryogenesis on the plane of the strain and frequency of the induced GWs, being careful to delineate regimes where PBH domination or washout effects occur. We provide semi-analytic scalings of the GW strain with the baryon number to entropy ratio and other parameters important for baryogenesis. Along the way, we sketch a solution to the dark matter-baryogenesis coincidence problem with two populations of PBHs, which leads to a double-peaked GW signal. Our results underscore the importance of probing the ultra high frequency GW frontier.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Specification of EBR-II Laser Profilometry Data

All laser profilometry data stored in FIPD were originally measured using the element laser profilometer system in HFEF/N. The irradiated fuel elements or pins were scanned by a laser beam to measure the outer diameter with position mapping of the spacer wire. The normal operation and data collection were performed automatically with HFEF/N Data Acquisition and Process Control System (DAPCS). With the digital control system, measured laser profilometry data were recorded in digital form on magnetic tapes, different from the analog contact profilometry data recorded by strip-chart record sheets. Two documents contained most of the important details about laser profilometry measurements. The first one is the operational manual of the laser profilometer (title: Element laser profilometer (ELP) operation and maintenance manual, HFEF/N OMM 4329, DOC. NO. W0171-0149-ES-01). This manual provides: (1) description of laser profilometer including the functions of each component (transceiver, retroreflector, clamping guide, shielding enclosure, electronic controller, etc.); (2) step-by-step guidance for calibrations, operations and measurements; and (3) maintenance procedures and other details of the element laser profilometer. Since first issued on 12/1/1986, several revisions/changes of the manual were developed to update the measurement accuracies and other factors for the laser profilometer system. The second document is a publicly accessible conference article titled “the element laser profilometer system in HFEF/N.” This article summarizes important functions and parameters of the laser profilometer. The range of measurements and the uncertainties reported in the article were consistent with the values reported in the operational manual.

42 ENGINEERING↗
DOE OSTI2020

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models

Bayesian experimental design (BED) aims at designing an experiment to maximize the information gathering from the collected data. The optimal design is usually achieved by maximizing the mutual information (MI) between the data and the model parameters. When the analytical expression of the MI is unavailable, e.g.,having implicit models with intractable data distributions, a neural network-based lower bound of the MI was recently proposed and a gradient ascent method was used to maximize the lower bound [1]. However, the approach in [1] requires a pathwise sampling path to compute the gradient of the MI lower bound with respect to the design variables, and such a pathwise sampling path is usually inaccessible for implicit models. In this work, we propose a hybrid gradient approach that leverages recent advances in variational MI estimator and evolution strategies (ES)combined with black-box stochastic gradient ascent (SGA) to maximize the MI lower bound. This allows the design process to be achieved through a unified scalable procedure for implicit models without sampling path gradients. Several experiments demonstrate that our approach significantly improves the scalability of BED for implicit models in high-dimensional design space.

Zhang, Jiaxin↗
DOE OSTI2020

A Computational Assessment of Actinide Dioxide Cations AnO 2 2+ for An = U to Lr: The Limited Stability Range of the Hexavalent Actinyl Moiety, [O=An=O] 2+

The isolated gas-phase actinide dioxide dications, AnO 2 2+ , were evaluated by DFT and coupled cluster CCSD(T) calculations for 12 actinides, An = U–Lr. CASSCF calculations were used to define the orbitals for the CCSD(T) calculations. The characteristic linear [O$=$An$=$O] 2+ hexavalent actinyl(VI) was found to be the lowest energy structure for An = U, Np, and Pu, which also form stable actinyl(VI) species in solution and possibly for Am when spin–orbit effects are included. For Am, there is a divalent [An II (O 2 )] 2+ structure where the dioxygen is an end-on physisorbed η 1 - 3 O 2 2 kcal/mol above the actinyl when spin–orbit effects are included which lower the energy of the actinyl structure. For An = Cm, Bk, and Lr, the lowest energy structure is trivalent [An III (O 2 – )] 2+ where the dioxygen is a side-on superoxide, η 2 -O 2 – . For Cm, the actinyl is close in energy to the ground state when spin–orbit effects are included. For An = Cf, Es, Fm, Md, and No, the lowest energy structure is divalent [An II (O 2 )] 2+ where the dioxygen is an end-on physisorbed η 1 - 3 O 2 . The relative energies suggest that curyl(VI) and berkelyl(VI), like well-known americyl(VI), might be stabilized by coordinating ligands in condensed phases. The results further indicate that for californyl and beyond, the actinyl(VI) moieties will probably be elusive even using strong donor ligands. The prevalence of low oxidation states (OSs) An(II) and An(III) for transplutonium actinides reflects stabilization of the 5f orbitals and validates established trends, including the remarkably high stability of divalent No. Finally, bond distances and other parameters suggest maximum bond covalency around plutonyl(VI), with a particularly substantial decrease in bond strength between americyl(VI) and curyl(VI).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Developing of Quaternary Pumped Storage Hydropower for Dynamic Studies

Quaternary pumped storage hydropower (Q-PSH) technology, as one of the new advanced-PSH technology, has been developed by taking advantage of Conventional-PSH (C-PSH) and Adjustable Speed-PSH (AS-PSH). By combining adjustable-speed pump unit and conventional hydropower turbine unit in the quaternary configuration, Q-PSH has the more competitive capability of providing fast power support in the future high renewable penetrated power system. Acting as energy storage (ES), Q-PSH provides promising power supply to deal with the uncertainty and variability from renewable energy generation. This paper focuses on the dynamic modeling of Q-PSH technology employing full-converter machine and the impact of Q-PSH on the frequency response in a system. The detailed model of Q-PSH is developed and implemented in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform, which captures the dynamic of multiple operation modes, especially hydraulic short-circuit (HSC) operation mode. Several cases are set up to reveal the advantages of Q-PSH technology when power electronic based renewable energy generation is deployed in the system. Sensitivity studies of the controller in pump governor show the impact of parameters in pump response performance. The comparison case illustrates the impact of frequency response provided by the Q-PSH in the system.

dynamic modeling↗
DOE OSTI2024

Effect of Anoxic Iron Corrosion on WIPP Brine Geochemistry FY23 Final Report (U)

A 280-day study was completed to evaluate the effect of zero-valent iron (Fe 0 ) on the Waste Isolation Pilot Plant (WIPP) brine geochemistry under anticipated reducing conditions. Hydrogen (H 2 ) gas is expected to be present in the repository after closure due to the anoxic corrosion of a vast quantity of iron contained in the waste forms disposed at WIPP; therefore, a background argon atmosphere containing H 2 was chosen for this study. WIPP groundwater brine pH and E h will impact the mobility and fate of plutonium within the repository. Modeling and laboratory results for Castile WIPP brine indicate that equilibrium fa values relative to the standard hydrogen electrode (SHE) are 40 mV more reducing (i.e., more negative) than those for Salado WIPP brine (-480 mV vs. -440 mV, respectively) because of the higher pH of the Castile brine (pH 9 .3 for Castile vs. pH 8.8 for Salado). The E h and pH data were corrected for the effects of high ionic strength. The experimental results for both brines are consistent with thermodynamic predictions using OLI Systems' Mixed Solvent Electrolyte chemical equilibrium model. The measured and corrected pH and E h data from this study are provided in Table ES-I and Table ES-2, respectively. The experimental study, with four test conditions in triplicate, was performed in a dual glovebox with a nominally 3 vol.% H 2 in argon atmosphere (target H 2 range: 3 ± I vol.%). Simulants containing MgO only ( experimental control) and MgO+Fe 0 (WIPP base case) were prepared for both the Salado and Castile brines. MgO was included in all simulants to account for the use of bulk magnesium oxide in the WIPP repository. Fe 0 was included in some simulants to incorporate the effects of the anoxic corrosion of iron and in-situ hydrogen generation in the study. The brine compositions were developed by Sandia National Laboratory (SNL; Xiong, 2008) and have been used in previous WIPP evaluations. The test method (agitation, etc.) is partially based on ASTM D3987-12. Twelve rounds of periodic measurements of pH and E h were performed over the course of the study. Chemical analysis results for liquids and solids (ICP-MS, ICP-ES, IC Anion, TIC, SEM-EDX) are consistent with the pH, E h , and thermodynamic modeling results. This study included the following conditions that deviate from anticipated post-closure conditions following brine intrusion, but were selected to facilitate bench-scale testing to validate modeling of pH and E h for the post-closure WIP P repository: an anoxic glove box atmosphere containing ≤ 4 vol. % H 2 vs. substantially higher H 2 gas concentrations assumed in the WIPP Performance Assessment (PA); a significantly higher liquid-to-solid test ratio compared to the much lower phase ratio anticipated in the WIP P repository; agitation of the simulant bottles to maximize mass transfer; and finally the use of Fe 0 reagents having a much greater surface area than expected in the WIP P repository. Non-representative conditions were chosen for various reasons such as: to provide bounding conservative results, to provide a margin of safety for testing, or to facilitate simulant sub-sampling and analysis. In a parallel effort, aqueous electrolyte thermodynamic models were developed for the synthetic Salado and Castile brines to inform the experimental design, facilitate laboratory data interpretation, and allow extension of evaluations beyond the parameters tested. Thermodynamic modeling simulations including the MgO and Fe 0 additives that are directly relevant to the experimental measurements (e.g., pH calibration curve, ORP corrections) are included in this report. The measured fa of the simulants was close to the OLI model predictions for both brines and was largely controlled by the background H 2 partial pressure in the vapor phase as well as H 2 generated in situ in the aqueous phase by the Fe 0 corrosion. The H 2 gas-phase concentration tested and thermodynamically evaluated was much lower than is assumed in the WIPP PA; however, H 2 (g) concentrations significantly below this level are still predicted to result in very reducing conditions. In conclusion: • The experimental results are consistent with thermodynamic model predictions for fa, pH, and the effects of high ionic strength. • Evidence to date suggests that the H2 concentration in the glovebox atmosphere ultimately determined the final E h values of the simulants and resulted in highly reducing conditions. As a result, little difference was observed between the control simulants containing only MgO and the WIPP base-case simulants that contained MgO and Fe 0 . • This test methodology is recommended for future studies evaluating WIPP repository conditions. The methodology includes: (1) background H 2 in argon with agitation ( or could alternatively include in-situ-generated H 2 in sealed bottles); (2) carefully measured and corrected ORP data ( with much effort focused on allowing the probes to fully stabilize); and (3) ionic-strength-corrected pH data. Other best practices, such as simulant sparging/handling, ORP probe replacement, etc., should also be considered. • The coupling of experimental studies and thermodynamic modeling is also highly recommended because these methods inform and direct one another leading to greater confidence in and understanding of the results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

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 ↗
DOE OSTI2022

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗