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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Driven responses of periodically patterned superconducting films

Here, we simulate the motion of a commensurate vortex lattice in a periodic lattice of artificial circular pinning sites having different diameters, pinning strengths, and spacings using the time-dependent Ginzburg-Landau formalism. Above some critical DC current density J c , the vortices depin, and the resulting steady-state motion then induces an oscillatory electric field E (t) with a defect "hopping" frequency f 0 , which depends on the applied current density and the pinning landscape characteristics. The frequency generated can be locked to an applied AC current density over some range of frequencies, which depends on the amplitude of the DC as well as the AC current densities. Both synchronous and asynchronous collective hopping behaviors are studied as a function of the supercell size of the simulated system and the (asymptotic) synchronization threshold current densities determined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗
DOE OSTI2022

A resistive MHD model and simulation on plasma flow evolution in the presence of resonant magnetic perturbation in a tokamak

Nonaxisymmetric magnetic fields such as the intrinsic error field and the externally applied resonant magnetic perturbation (RMP) in a tokamak are known to influence the plasma momentum transport and flow evolution through plasma response, which itself strongly depends on the plasma flow as well. The nonlinear interaction between plasma response and flow has been previously modeled in the conventional error field theory with the “no-slip” condition, which has been recently extended to allow the “free-slip” condition. In this work, we further target this specific process and numerically simulate the nonlinear plasma response and flow evolution in the presence of a single-helicity RMP in a circular-shaped model tokamak configuration, based on the full resistive MHD model in the initial-value code NIMROD. Time evolution of the parallel (to k) flow or “slip frequency” profile and its asymptotic steady state obtained from the NIMROD simulations are compared with both conventional and extended nonlinear response theories. Here, k is the wave vector of the propagating island. Good agreement with the extended theory with free-slip condition has been achieved for the parallel flow profile evolution in response to RMP in all resistive regimes, whereas the difference from the conventional theory with the no-slip condition tends to diminish as the plasma resistivity approaches zero.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin

Tropical forests are acknowledged to be the largest global source of isoprene (C 5 H 8 ) and monoterpenes (C 10 H 16 ) emissions, with current synthesis studies suggesting few tropical species emit isoprenoids (20-38%) and do so with highly variable emission capacities, including within the same genera. This apparent lack of a clear phylogenetic thread has created difficulties both in linking isoprenoid function with evolution and for the development of accurate biosphere-atmosphere models. In this work, we present a systematic emission study of "hyperdominant" tree species in the Amazon Basin. Across 162 individuals, distributed among 25 botanical families and 113 species, isoprenoid emissions were widespread among both early and late successional species (isoprene: 61.9% of the species; monoterpenes: 15.0%; both isoprene and monoterpenes: 9.7%). The hyperdominant species (69) across the top five most abundant genera, which make up about 50% of all individuals in the Basin, had a similar abundance of isoprenoid emitters (isoprene: 63.8%; monoterpenes: 17.4%; both 11.6%). Among the abundant genera, only Pouteria had a low frequency of isoprene emitting species (15.8% of 19 species). In contrast, Protium, Licania, Inga, and Eschweilera were rich in isoprene emitting species (83.3% of 12 species, 61.1% of 18 species, 100% of 8 species, and 100% of 12 species, respectively). Light response curves of individuals in each of the five genera showed light-dependent, photosynthesis-linked emission rates of isoprene and monoterpenes. Importantly, in every genus, we observed species with light-dependent isoprene emissions together with monoterpenes including β-ocimene. These observations support the emerging view of the evolution of isoprene synthases from β-ocimene synthases. Our results have important implications for understanding isoprenoid function-evolution relationships and the development of more accurate Earth System Models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Viral community analysis in a marine oxygen minimum zone indicates increased potential for viral manipulation of microbial physiological state

Microbial communities in oxygen minimum zones (OMZs) are known to have significant impacts on global biogeochemical cycles, but viral influence on microbial processes in these regions are much less studied. Here we provide baseline ecological patterns using microscopy and viral metagenomics from the Eastern Tropical North Pacific (ETNP) OMZ region that enhance our understanding of viruses in these climate-critical systems. While extracellular viral abundance decreased below the oxycline, viral diversity and lytic infection frequency remained high within the OMZ, demonstrating that viral influences on microbial communities were still substantial without the detectable presence of oxygen. Viral community composition was strongly related to oxygen concentration, with viral populations in low-oxygen portions of the water column being distinct from their surface layer counterparts. However, this divergence was not accompanied by the expected differences in viral-encoded auxiliary metabolic genes (AMGs) relating to nitrogen and sulfur metabolisms that are known to be performed by microbial communities in these low-oxygen and anoxic regions. Instead, several abundant AMGs were identified in the oxycline and OMZ that may modulate host responses to low-oxygen stress. We hypothesize that this is due to selection for viral-encoded genes that influence host survivability rather than modulating host metabolic reactions within the ETNP OMZ. Together, this study shows that viruses are not only diverse throughout the water column in the ETNP, including the OMZ, but their infection of microorganisms has the potential to alter host physiological state within these biogeochemically important regions of the ocean.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Responses of summer mesoscale convective systems to irrigation over the North China Plain based on convection-permitting model simulations

Extensive irrigation activities in the North China Plain (NCP) significantly influence regional weather and climate. However, previous studies focusing on the NCP were primarily based on coarse-resolution models, which are unable to explicitly resolve convection systems, causing large uncertainty in precipitation simulations. In this study, a convection-permitting model coupled with a dynamic irrigation scheme is utilized to investigate the impacts of irrigation on summertime mesoscale convective systems (MCSs) over the NCP. Sensitivity experiments with irrigation off and on are conducted for 5 summers and an MCS identification and tracking algorithm is applied to both satellite observations and model simulations. We find that incorporating irrigation in the model increases MCS precipitation, which agrees more with observations. The probability distributions of MCS lifetime, area, propagation speed, and intensity are all better simulated with irrigation. Irrigation increases the occurrence frequency of MCSs throughout the entire day. The nighttime increase is partly because of more frequent local initiation of MCS developed from isolated deep convection, while the daytime increase is mainly attributed to the changes in MCSs initiating elsewhere and then propagating to the NCP. On average, irrigation induces additional moisture that is more thermodynamically favorable for precipitation, but this effect is partially offset by the weakened ascending air motion primarily caused by irrigation surface cooling. Compared to weak MCS precipitation events, strong MCS precipitation events experience greater enhancement in precipitation intensity when including irrigation because the offset effect from the change in large-scale ascending air motion is insignificant. In addition, irrigation makes the variation of MCS precipitation intensity more correlated with the variation in ascending motion but less correlated with that in atmospheric moisture. Our results suggest the pronounced impacts of irrigation on MCSs over the NCP which should be included in numerical models to improve regional precipitation simulation and prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

What do far-infrared spectra of solitary water in “water-in-solvent” systems reveal about water’s solvation and dynamics?

Classical molecular dynamics simulations of water in ionic and dipolar solvents were used to interpret the far-infrared (FIR) rotation/libration spectra of “solitary water” in terms of water’s rotational dynamics and interactions with solvents. Seven solvents represented by nonpolarizable all-atom force fields and a series of idealized variable-charge solvents were used to span the range of solvent polarities (hydrogen bonding) studied experimentally. Simulated spectra capture the solvent dependence observed, as well as the relationship between the frequencies of water libration (νL) and OH stretching bands (νOH). In more strongly interacting solvents, simulated νL are ∼20% higher than those of experiment. In all solvents, the simulated spectra are composites of rotational motions about the two axes perpendicular to water’s dipole moment, and the different frequencies of these two motions are responsible for the breadth of the libration band and the bimodal shape observed in halide ionic liquids. Simulations overestimate the separation of these two components in most solvents. The character of water rotational motions changes markedly with solvent polarity, from quasi-free rotation in nonpolar and weakly polar solvents to highly constrained libration in strongly hydrogen bonding environments. The changeover to librational motions dominating the spectrum occurs between solvents such as benzene (νL ∼ 250 cm−1) and acetonitrile (νL ∼ 400 cm−1). For solvents in the latter category, the mean frequency of the experimental FIR band provides a direct measure of mean-squared torques and, therefore, force constants associated with interactions constraining water’s librational motion.

Chemistry↗
DOE OSTI2024

Distributed Magnetic Field and Temperature Monitoring for Superconducting Radio Frequency Cavities

The overall objective of the proposed Phase I program was to design, construct and demonstrate a fiber optic sensing system capable of providing temperature and magnetic field measurements with an enhanced spatial resolution that can be implemented over a large surface area (cryomodules) to survey superconducting radio frequency cavities and magnets. A magnetic field sensor capable of detecting fluxes on the order of 1 μT is required to detect the distribution of trapped flux on the cavity surface. A unique distributed magnetic field sensor was successfully designed and constructed to demonstrate the detection of magnetic fluxes less than 500 nT. The sensor leveraged the ultra-high sensitivity of Sentek’s picoDAS to measure the magnetostriction induced vibrations in a commercially available Metglas 2605 SC ribbon that was in physical contact with sensing fiber. Static magnetic fields were detected by applying an alternating current a copper wire proximate to the Metglas 2605SC ribbon to create an AC bias magnetic field. In an alternative approach, an AC bias magnetic field was applied to a special magnetic field sensing fiber with Metglas 2605SC cladding successfully detect a magnetic field flux of a 3 μT. Exhaustive testing was performed to characterize the dependency of sensor response on the direction of the applied magnetic field. Although the special sensing fiber based magnetic field sensor did not exhibit an observable dependence on the direction of the magnetic field, the Metglas 2605SC ribbon sensor exhibited a clear directional dependence. A wide variety of polymer materials were evaluated to enhance the temperature response of an FBG based sensor at cryogenic temperatures. The processing and performance challenges provided the motivation to develop a new simple cryogenic temperature sensor that uses a commercially available fiber optic splice protector. The EVA hot melt tube that becomes adhered to the optical fiber and the polyolefin outer tube that shrinks upon heating in the fusion splicer heater provide the high thermal expansion coefficient necessary to impart a significant strain on the FBG when exposed to cryogenic temperatures. The temperature sensitivity (Δ𝜆𝐵𝑟𝑎𝑔𝑔~ 62 𝑝𝑝𝑚/℃) of the FBG-based sensor was on par with the best reported to date. The simple design, use of readily available cost-effective materials, and well-established processing techniques lends this approach to the creation of hundreds to thousands of temperature sensors on one single optical fiber length. The inherently small form factor also allows for co-location with the distributed magnetic field sensor. In preparation for field testing of the prototype sensing system at the Jefferson Labs in potential Phase II program, several different cable designs were evaluated to package the sensors. The preliminary successful demonstration of fully functional sensing cables provides the foundation for subsequent development efforts to advance the Technology Readiness Level of the technology. The technical feasibility of the proposed approach was successfully demonstrated in this Phase I effort.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Commercial building loads providing ancillary services In PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

MacDonald, Jason↗
DOE OSTI2026

Millimeter-wave dielectric tunability driven by topological polar structure switching in PbTiO 3 /SrTiO 3 superlattices

Dielectric tunability induced by an external electric field in materials underpins radio frequency signal modulation devices such as phase shifters, which are critical components in wireless communication and sensing systems. However, the tunability and integrability of current devices have yet to be enhanced for emerging applications, particularly at millimeter-wave frequencies. Here, we demonstrate that topological polar structures formed in PbTiO 3 /SrTiO 3 superlattices exhibit large tunable in-plane dielectric properties, as determined by their multiscale structural configurations and polarization switching behaviors. Under a moderate field of 30 kV cm −1 , the dipole wave structure maintains a tunability exceeding 15% at 70 GHz and above 8% over the measured range up to 110 GHz, contrasting with the weakly tunable flux closure structure. Based on in situ structural characterizations and molecular dynamics simulations, we delineate the polarization switching processes and elucidate the mechanisms underlying the observed tunable millimeter-wave dielectric responses. Our results provide new insights into the high-frequency dielectric properties of topological polar phases, potentially broadening the versatility of these materials in next-generation integrated electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗
DOE OSTI2020

Reducing the Susceptibility of Lumped-Element KIDs to Two-Level System Effects

Arrays of lumped-element kinetic inductance detectors (LEKIDs) optically coupled through an antenna-coupled transmission line are a promising candidate for future cosmic microwave background experiments. However, the dielectric materials used for the microstrip architecture are known to degrade the performance of superconducting resonators. In this paper, we investigate the feasibility of microstrip coupling to a LEKID, focusing on a systematic study of the effect of depositing amorphous silicon nitride on a LEKID. The discrete and spatially separated inductive and capacitive regions of the LEKID allow us to vary the degree of dielectric coverage and determine the limitations of the microstrip coupling architecture. We show that by careful removal of dielectric from regions of high electric field in the capacitor, there is minimal degradation in dielectric loss tangent of a partially covered lumped-element resonator. We present the effects on the resonant frequency and noise power spectral density and, using the dark responsivity, provide an estimate for the resulting detector sensitivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

MEP: Mobility Energy Productivity Metric

In response to the need to assess fundamental improvements in mobility as technology provides new modes, methods, and opportunities in urban areas to connect people with goods, services, and employment, a mobility-energy productivity score (MEPS) has been developed. The MEPS fundamentally measures the potential of a multi-modal system to connect a person to a variety of services and activities that define a high-quality of life. The MEPS is measured relative to the convenience and energy needed to provide connectivity. Fundamentally derived from accessibility theory, the MEPS advances practice by using readily available travel time data (either from web-based APIs or outputs from an urban transportation model) combined with established parameters that reflect the energy intensity of various travel modes, and relative frequency of activity engagement. The construction of the MEPS allows for aggregation and disaggregation to the appropriate spatial, modal, and trip purpose resolution, as analysis needs dictate. The MEPS could be used to compare alternative futures related to technology, infrastructure investment, or policy, providing a much needed tool for planners, researchers, and analysts. In other words, the metric measures how efficiently connected a place is.

Hou, Yi↗
DOE OSTI2022

Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems

The large thermal gradients and high subsurface temperatures of the western region of the U.S. hold great potential for the implementation of enhanced geothermal systems (EGS). The development of these potential EGS resources requires stimulation of the reservoir to enhance permeability and it has been widely reported that a substantial amount of water will be required should conventional hydraulic stimulation be used. This presents a huge challenge and a high risk to the geothermal development because the water stress1 in these areas is already high or extremely high. The use of foam, a gas/liquid mixture predominantly composed of gas, in fracturing is considered and explored in this project as a potential approach to address water concerns with hydraulic stimulation in the development of EGS. This project, led by Oak Ridge National Laboratory (ORNL) in collaboration with Temple University, was awarded in an open lab call in 2018, and was part of the DOE GTO waterless stimulation initiative. The goal of the project was to demonstrate the feasibility of foam fracturing for EGS development through two primary tasks: Task 1: Laboratory study of the effectiveness of foam fracturing for representative geological materials, including cyclic pressurization using foam (led by ORNL) and Task 2: High temperature foam material selection and characterization (led by Temple University). In FY19, ORNL finished the critical review on serval issues associated with foam fracturing and the implementation of the proposed tasks in a lab study (Wang, et al., 2019), and completed the foam fracturing testing using cement as a model material (Wang, et al, 2020a). The work at ORNL was geared up to develop a brand-new foam testing system in FY20. The purchase of main components for the new system was finished in the first half of the FY20. The assembly of the foam testing system and foam fracturing testing were completed in the second half of the FY20 (Wang, et al., 2021a). Task 1 required the development of a test system which can be used to perform hydraulic fracturing of geological specimens with both water and foamed liquids at pressure up to 6,000 psi (41.4 MPa). The system possesses several capabilities that conventional injection systems lack for hydraulic fracturing. In addition to its ability to generate foam with controlled quality, it is capable of cycling pressure levels between specified values up to frequencies of 50 Hz. The latter capability was developed to evaluate the hypothesis that cyclic loading of samples would produce enhanced fracturing. The system consists of two sections: one for foam generation and another for foam injection. The foam is generated through separate control and pressurization of liquid and gas phases with controlled flow rates. The injection section is equipped with a low-flow Coriolis flow that monitors the density of foam to ensure the injection is in the range of target foam quality2. Experimental results of foam fracturing are reported for cylindrical granite specimens using water and aqueous N2 foam as the fracturing fluids. All experiments were performed for unconfined conditions. The effects of injection mode (i.e., monotonic vs cyclic pressurization) on breakdown pressure and failure response sample were investigated using water alone as a fracturing fluid and foams with a range of compositions. It was found that in the case of monotonic injection, the breakdown pressure of granite specimens tended to be slightly higher when fracturing with foam. Additionally, with a foam quality of 90%, the water use can be reduced by 50 to 84%, depending on hole size. On the other hand, it was observed that the breakdown pressure can be brought down to 70% of the monotonic breakdown pressure by using low cycle fatigue. Finally, discussions are presented regarding injectivity and water use reduction.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗
DOE OSTI2022

Dynamic Response of an Electron Gas: Towards the Exact Exchange-Correlation Kernel

Precise calculations of dynamics in the homogeneous electron gas (jellium model) are of fundamental importance for design and characterization of new materials. In this work, we introduce a diagrammatic Monte Carlo technique based on algorithmic Matsubara integration that allows us to compute frequency and momentum resolved finite temperature response directly in the real frequency domain using series of connected Feynman diagrams. The data for charge response at moderate electron density are used to extract the frequency dependence of the exchange-correlation kernel at finite momenta and temperature. These results are as important for development of the time-dependent density functional theory for materials dynamics as ground state energies are for the density functional theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗