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At least 559 records · Page 31

DECOVALEX-2023 Task F Specification (Rev. 9)

This report is the revised (Revision 9) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DECOVALEX-2023: Task F Specification (Revision 10)

This report is the revised (Revision 10) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of a Complete Landsat Evapotranspiration and Energy Balance Archive to Support Agricultural Consumptive Water Use Reporting and Prediction in the Central Valley, CA

Mapping evapotranspiration (ET) from agricultural areas in Californias Central Valley is critical for understanding historical consumptive use of surface and groundwater. In addition, long histories of ET maps provide valuable training information for predictive studies of surface and groundwater demands. During times of drought, groundwater is commonly pumped to supplement reduced surface water supplies in the Central Valley. Due to the lack of extensive groundwater pumping records, mapping consumptive use using satellite imagery is an efficient and robust way for estimating agricultural consumptive use and assessing drought impacts. To this end, we have developed and implemented an algorithm for automated calibration of the METRIC remotely sensed surface energy balance model on NASAs Earth Exchange (NEX) to estimate ET at the field scale. Using automated calibration techniques on the NEX has allowed for the creation of spatially explicit historical ET estimates for the Landsat archive dating from 1984 to the near present. Further, our use of spatial NLDAS and CIMIS weather data, and spatial soil water balance simulations within the NEX METRIC workflow, has helped overcome challenges of time integration between satellite image dates. This historical and near present time archive of agricultural water consumption for the Central Valley will be an extremely useful dataset for water use and drought impact reporting, and predictive analyses of groundwater demands.

valleys↗

A Data-Driven Passive Islanding Detection Scheme

This paper proposes a simple yet effective statistical parameters based passive islanding scheme. The proposed scheme relies only the voltage data, measured at the point of common coupling (PCC), and is comprised of three stages. The Stage-1 quickly computes what is termed as mean based coarse islanding detection (MID), Stage-2 computes the decaying DC detector (DDCD), and 3) finally, MID is used in conjunction with DDCD as per the statistical digital relay logic (SRDL) is devised in Stage-3 to distinguish between islanding events from non islanding events. Various tests are investigated on the Banshee's industrial Microgrid (MG), modelled in the Real Time Digital Simulator (RTDS), on the basis of the IEEE-1547, UL 1741 standards. The validation of the proposed islanding detection methodology (PIDM) in RTDS platform ensures the viability of the proposed scheme in practical systems. The test results reveal that the PIDM can detect islanding within 2 cycles, and results in a very small non detection zone (NDZ). Moreover, the scheme can very well be used for single-phase MG too as it relies only on the single phase voltage information.

anti-islanding protection↗

Cloud Computing for Mission Design and Operations

The space mission design and operations community already recognizes the value of cloud computing and virtualization. However, natural and valid concerns, like security, privacy, up-time, and vendor lock-in, have prevented a more widespread and expedited adoption into official workflows. In the interest of alleviating these concerns, we propose a series of guidelines for internally deploying a resource-oriented hub of data and algorithms. These guidelines provide a roadmap for implementing an architecture inspired in the cloud computing model: associative, elastic, semantical, interconnected, and adaptive. The architecture can be summarized as exposing data and algorithms as resource-oriented Web services, coordinated via messaging, and running on virtual machines; it is simple, and based on widely adopted standards, protocols, and tools. The architecture may help reduce common sources of complexity intrinsic to data-driven, collaborative interactions and, most importantly, it may provide the means for teams and agencies to evaluate the cloud computing model in their specific context, with minimal infrastructure changes, and before committing to a specific cloud services provider.

cloud computing↗

How Noninnocent Spectator Species Improve the Oxygen Reduction Activity of Single-Atom Catalysts: Microkinetic Models from First-Principles Calculations

Graphene-based single-atom catalysts are promising alternatives to platinum-based catalysts for fuel cell applications. Different transition metals have been screened using electronic structure methods by estimating onset potentials from the most endergonic elementary reaction step. Here, we calculate onset potentials for the oxygen reduction reaction on metal atoms embedded in N-substituted graphene di-vacancies by virtue of first-principles-informed microkinetic analysis. We find that for more oxophilic metals (Cr, Fe, Mn, and Ru), purely thermodynamic models systematically underestimate onset potentials. Furthermore, the oxophilic metals (Cr, Fe, Mn, and Ru) are oxidized under reaction conditions, leading to an increase in activity compared to their reduced state. Importantly, coadsorbed O m H n species actively participate in the reaction, which requires a dynamic treatment of spectator species. These findings highlight the limitations of thermodynamic analyses for electrocatalytic processes, which commonly assume the same oxidation state for each metal, and show that deviations between computational and experimental onset potentials cannot be solely attributed to the shortcomings of the electronic structure methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗

Finding Bounded Rational Equilibria: Iterative Focusing - Part 1

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality characterizing all real-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. It has recently been shown that the same information theoretic mathematical structure, known as Probability Collectives (PC) underlies both issues. This relationship between statistical physics and game theory allows techniques and insights from the one field to be applied to the other. In particular, PC provides a formal model-independent definition of the degree of rationality of a player and of bounded rationality equilibria. This pair of papers extends previous work on PC by introducing new computational approaches to effectively find bounded rationality equilibria of common-interest (team) games.

Wolpert, David H.↗

Finding Bounded Rational Equilibria: Alternative Lagrangians and Uncountable Move Spaces - Part 2

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality characterizing all real-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. It has recently been shown that the same information theoretic mathematical structure, known as Probability Collectives (PC) underlies both issues. This relationship between statistical physics and game theory allows techniques and insights &om the one field to be applied to the other. In particular, PC provides a formal model-independent definition of the degree of rationality of a player and of bounded rationality equilibria. This pair of papers extends previous work on PC by introducing new computational approaches to effectively find bounded rationality equilibria of common-interest (team) games.

Wolpert, David H.↗

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗

The DESI DR1 Peculiar Velocity Survey: Growth Rate Measurements from the Galaxy Power Spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios where the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as $fσ_8$, is extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models and parameter-fitting framework have been tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques are then applied to analyze the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey, and the fit result of the growth rate is $fσ_8=0.440^{+0.080}_{-0.096}$ at effective redshift $z_{\rm eff}=0.07$. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation and power spectrum, yields a consensus value of $fσ_8(z_{\rm eff}=0.07) = 0.450 ^{+0.055}_{-0.055}$, and correspondingly we obtain $γ=0.580^{+0.110}_{-0.110}$, $Ω_\mathrm{m}=0.301^{+0.011}_{-0.011}$ and $σ_8=0.834^{+0.032}_{-0.032}$. The measured $fσ_8$ and $γ$ are consistent with the prediction of the $Λ$ Cold Dark Matter Model and General Relativity.

Qin, F. [Marseille, CPPM] (ORCID:0000000179507864)↗

Using Satellite Soil Moisture and Rainfall in the Landslide Hazard Assessment for Situational Awareness System

The Landslide Hazard Assessment for Situational Awareness system(LHASA)gives a global view of landslide hazard in nearly real time. Currently, it is being upgraded from version 1 to version 2, which entails improvements along several dimensions. These include the incorporation of new predictors, machine learning, and new event-based landslide inventories. As a result, LHASA version 2 substantially improves on the prior performanceand introduces a probabilistic element to the global landslide nowcast. Data from the soil moisture active-passive (SMAP) satellite has been assimilated into a globally consistent data product with a latency less than 3 days, known as SMAP Level 4. In LHASA, thesedata representthe antecedent conditions prior to landslide-triggering rainfall. In some cases, soil moisture may have accumulated over aperiod of many months. The model behind SMAP Level 4 also estimates the amount of snow on the ground, which is an important factor in some landslide events. LHASA also incorporates this information as an antecedent condition that modulates the response torainfall. Slope, lithology, and active faults were also used as predictor variables. These factors can have a strong influence on where landslides initiate.LHASA relies on precipitation estimates from the Global Precipitation Measurement mission to identify the locations where landslides are most probable. The low latency and consistent global coverage of these data make them ideal for real-time applications at continental to global scales. LHASA relies primarily on rainfall from the last 24 hours to spothazardous sites, which is rescaled by the local 99thpercentile rainfall.However, the multi-day latency of SMAP requires the use of a 2-day antecedent rainfall variable to represent the accumulation of rain between the antecedent soil moisture and current rainfall. LHASA merges these predictors with XGBoost, a commonly used machine-learning tool, relying on historical landslide inventories to develop the relationship between landslide occurrence and various risk factors. The resulting model relies heavily on current daily rainfall, but other factors also play an important role. LHASA outputsthe probability oflandslide occurrence ona grid of roughly one kilometer over all continents from 60 North to 60 South latitude. Evaluation over the period 2019-2020 showsthat LHASA version 2 doubles the accuracy of the global landslide nowcast without increasing the global false alarm rate. LHASA also identifies the areas where the human exposure to landslide hazard is most intense. Landslide hazard is divided into 4 levels: minimal, low, moderate, and high. Next, the number of persons and the length of major roads (primary and secondary roads)within each of these areas is calculated for every second-level administrative district (county). These results can be viewedthrough a web portal hosted at the Goddard Space Flight Center. In addition, users can download daily hazard and exposure data.LHASAversion 2uses machine learning and satellite data to identify areas of probable landslide hazard within hours of heavy rainfall. Itsglobal maps are significantly more accurate, and it now includes rapid estimates of exposed populations and infrastructure. In addition, a forecast mode will be implemented soon.

Thomas Stanley↗

The DESI DR1 peculiar velocity survey: Growth rate measurements from the galaxy power spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios in which the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as fσ 8 , was extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models, and parameter-fitting framework were tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques were then applied to analyse the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey. The fit result of the growth rate is fσ8 = 0.440$^{+0.080}_{−0.096}$ at effective redshift zeff = 0.07. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation, and the power spectrum, a consensus value is yielded of fσ 8 (z eff = 0.07) = 0.450$^{+0.055}_{−0.055}$, and correspondingly we obtain γ = 0.580$^{+0.110}_{−0.110}$, Ω m = 0.301$^{+0.011}_{−0.011}$, and σ 8 = 0.834$^{+0.032}_{−0.032}$. The measured fσ8 and γ are consistent with the prediction of the Λ cold dark matter model and general relativity.

79 ASTRONOMY AND ASTROPHYSICS↗

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Abstract Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondary measurements. Traditional black-box optimizers such as Bayesian optimization are slow and inefficient when dealing with such objectives as they must acquire the full series of measurements, but return only the emittance, with each query. We propose a new information-theoretic algorithm, Multipoint-BAX , for black-box optimization on multipoint queries, which queries and models individual beam-size measurements using techniques from Bayesian Algorithm Execution (BAX). Our method avoids the slow multipoint query on the accelerator by acquiring points through a virtual objective , i.e. calculating the emittance objective from a fast learned model rather than directly from the accelerator. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II). In simulation, our method is 20× faster and more robust to noise compared to existing methods. In live tests, it matched the hand-tuned emittance at FACET-II and achieved a 24% lower emittance than hand-tuning at LCLS. Our method represents a conceptual shift for optimizing multipoint queries, and we anticipate that it can be readily adapted to similar problems in particle accelerators and other scientific instruments.

43 PARTICLE ACCELERATORS↗

A wind tunnel technique for determining stability derivatives from cable mounted aeroelastic models

System identification techniques in common use for extracting stability derivatives from flight test data have been adapted for application to data obtained from aeroelastically-scaled flutter models flown in a wind tunnel on a cable mount system. The concept has been applied with reasonable success to data from rigid models of a Space Shuttle Orbiter and a fighter tested in the NASA Langley transonic dynamics tunnel. Further application of this technique should permit extraction of derivatives that include scaled flexibility effects, thereby obtaining additional information from the testing of expensive flutter models.

Bennett, R. M.↗

The Effects of Elevated Temperatures on the Response of Resins Under Dynamic and Static Loadings

The overall objective of the research is to experimentally study the combined effects of temperature and strain rate on the response of two resins that are commonly used for the matrix material in composites. The resins are loaded at various temperatures in shear and in tension over a wide range of strain rates. These two types of loadings provide an opportunity to examine also the effect that temperature might have on the effects of the hydrostatic stress component on the material response. The experimental data provide the information needed for NASA scientists for the development of a nonlinear, strain rate, and temperature dependent deformation and strength models for composites that can subsequently be used in design. This year effort was directed into the development and testing of the epoxy resin at elevated temperatures. Two types of epoxy resins were tested in shear at high strain rates of about 10(exp-4)/s and elevated temperatures of 50 and 8OC. The results show that the temperature significantly affects the response of epoxy.

Gilat, Amos↗

A Deeper Dive Into the Meaning and Implications of Interoperability for LunaNet Communications and Navigation Services

As part of planning efforts for cislunar exploration and science missions, space agencies have been collaborating with each other to enable communications, networking, Position, Navigation, and Timing (PNT) systems to exchange information and provide services to spacecraft and space systems in transit, in orbit, and on the surface, thus helping each other to achieve their common goals. To achieve commonality and lower cost for mutual benefit, the strategy of interoperability is being adopted to help all the pieces fit together and function smoothly. Interoperability gives cislunar users the ability to operate in a collaborative environment similar to the terrestrial Internet, allowing them to share information, navigate safely despite increasing radio frequency congestion, and follow common processes and procedures for effective joint operations. Unlike prior government-dominated efforts, this ecosystem is expected to include commercial for-profit businesses, non-profit organizations, and academic institutions. Ultimately, the goal is to enable a cislunar ecosystem of service providers and users to contribute and/or utilize infrastructure and capabilities to accomplish mission objectives spanning the full range of human endeavours while supporting a variety of business models. This paper reports on the results of an effort to assist in efforts to frame the development of the international LunaNet architecture by providing a canonical definition of interoperability broad enough to meet these needs, examine architectural and operational implications of the definition, and explore interoperability strategies and tactics for deploying and evolving these services. It describes key systems-of-systems (SoS) (Network-of-Networks) interoperability concepts in the context of sustainment of the ecosystem over time as systems evolve in technologies, standards and Standards Development Organizations, component and subsystem upgrades, and user applications

LunaNet↗

Modeling and Simulation Supporting Material Control and Accounting for Advanced Reactors: Task 2: Safeguards Modeling and Simulation Assessment

Commercial interest in advanced reactors for power production in the United States is increasing. A variety of advanced reactor designs are being developed, and many of them use non-traditional fuel forms. Therefore, the material control and accounting (MC&A) methods that will be required for these advanced reactor systems also need to be developed to ensure that the necessary safeguards are implemented. To provide information that can be leveraged to explore different MC&A approaches, three representative advanced reactor types were evaluated from a technical safeguards perspective. These reactor designs were selected to encompass common materials and configurations that could affect safeguards considerations. The three designs evaluated were a molten salt reactor (MSR), a gas-cooled reactor (GCR), and a heat pipe-cooled microreactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗