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At least 307 records · Page 17

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NASA NTRS2013

Sustaining a Mature Risk Management Process: Ensuring the International Space Station for a Vibrant Future

The International Space Station (ISS) risk management methodology is an example of a mature and sustainable process. Risk management is a systematic approach used to proactively identify, analyze, plan, track, control, communicate, and document risks to help management make risk-informed decisions that increase the likelihood of achieving program objectives. The ISS has been operating in space for over 14 years and permanently crewed for over 12 years. It is the longest surviving habitable vehicle in low Earth orbit history. Without a mature and proven risk management plan, it would be increasingly difficult to achieve mission success throughout the life of the ISS Program. A successful risk management process must be able to adapt to a dynamic program. As ISS program-level decision processes have evolved, so too has the ISS risk management process continued to innovate, improve, and adapt. Constant adaptation of risk management tools and an ever-improving process is essential to the continued success of the ISS Program. Above all, sustained support from program management is vital to risk management continued effectiveness. Risk management is valued and stressed as an important process by the ISS Program.

Raftery, Michael↗

NASA NTRS2013

Summary of the 2008 NASA Fundamental Aeronautics Program Sonic Boom Prediction Workshop

The Supersonics Project of the NASA Fundamental Aeronautics Program organized an internal sonic boom workshop to evaluate near- and mid-field sonic boom prediction capability at the Fundamental Aeronautics Annual Meeting in Atlanta, Georgia on October 8, 2008. Workshop participants computed sonic boom signatures for three non-lifting bodies and two lifting configurations. A cone-cylinder, parabolic, and quartic bodies of revolution comprised the non-lifting cases. The lifting configurations were a simple 69-degree delta wing body and a complete low-boom transport configuration designed during the High Speed Research Project in the 1990s with wing, body, tail, nacelle, and boundary layer diverter components. The AIRPLANE, Cart3D, FUN3D, and USM3D ow solvers were employed with the ANET signature propagation tool, output-based adaptation, and a priori adaptation based on freestream Mach number and angle of attack. Results were presented orally at the workshop. This article documents the workshop, results, and provides context on previously available and recently developed methods.

Park, Michael A.↗

DOE OSTI2023

Physical Security Timeline Analysis in Support of Advanced Reactor Demonstration and Deployment

This report presents the regulatory requirements and directions on the physical security of advanced nuclear reactors in USA. Presently, a rule is being proposed that allows for a performance-based analysis. In determining the physical security requirements for an advanced reactor, new tools may be desired to conduct a performance-based analysis. These tools should incorporate dynamic analysis methods to provide as much realism as possible. In comparison, the security requirements for existing light water reactors (LWRs) are much more prescriptive and the analysis conducted to establish the required physical security strategies were more easily performed with static analysis. In order to achieve the cost goals that advanced reactors require for adoption; the nuclear security force required should not be excessive. Dynamic physical security analysis methods and tools have been developed by the US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program. This report details how the dynamic risk analysis tools developed in the LWRS program using the dynamic risk modelling tool, EMRALD, may be adapted for use in analyzing the physical security designs for advanced reactors accounting for variable performance-based requirements. This report provides an example analysis of a hypothetical SFR using publicly available information and generic assumptions to demonstrate the methods and potential presentation and analysis of the results. No actual plant information is used in this example analysis. Future work in this area will create additional models that can be adapted for any advanced reactor concept and use various security features to create a physical security system that provides adequate protection from radiological theft and sabotage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.

58 GEOSCIENCES↗

DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Flowfield computer graphics

The objectives of this research include supporting the Aerothermodynamics Branch's research by developing graphical visualization tools for both the branch's adaptive grid code and flow field ray tracing code. The completed research for the reporting period includes development of a graphical user interface (GUI) and its implementation into the NAS Flowfield Analysis Software Tool kit (FAST), for both the adaptive grid code (SAGE) and the flow field ray tracing code (CISS).

Desautel, Richard↗

DOE OSTI2014

Assessing Development Impacts Associated with Low Emission Development Strategies: Lessons Learned from Pilot Efforts in Kenya and Montenegro

Low emission development strategies (LEDS) articulate economy-wide policies and implementation plans designed to enable a country to meet its long-term development objectives while reducing greenhouse gas emissions. A development impact assessment tool was developed to inform an analytically robust and transparent prioritization of LEDS actions based on their economic, social, and environmental impacts. The graphical tool helps policymakers communicate the development impacts of LEDS options and identify actions that help meet both emissions reduction and development goals. This paper summarizes the adaptation and piloting of the tool in Kenya and Montenegro. The paper highlights strengths of the tool and discusses key needs for improving it.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

SchemaOnRead: A Package for Schema-on-Read in R

Schema-on-read is an agile approach to data storage and retrieval that defers investments in data organization until production queries need to be run by working with data directly in native form. Schema-on-read functions have been implemented in a wide range of analytical systems, most notably Hadoop. SchemaOnRead is a CRAN package that uses R’s flexible data representations to provide transparent and convenient support for the schema-on-read paradigm in R. The schema-on- read tools within the package include a single function call that recursively reads folders with text, comma separated value, raster image, R data, HDF5, NetCDF, spreadsheet, Weka, Epi Info, Pajek network, R network, HTML, SPSS, Systat, and Stata files. The provided tools can be used as-is or easily adapted to implement customized schema-on-read tool chains in R. This paper’s contribution is that it introduces and describes SchemaOnRead, the first R package specifically focused on providing explicit schema-on-read support in R.

Data Science↗

DOE OSTI2016

SchemaOnRead: A Package for Schema-on-Read in R

Data Science↗

NASA NTRS2004

Cockpit System Situational Awareness Modeling Tool

This project explored the possibility of predicting pilot situational awareness (SA) using human performance modeling techniques for the purpose of evaluating developing cockpit systems. The Improved Performance Research Integration Tool (IMPRINT) was combined with the Adaptive Control of Thought-Rational (ACT-R) cognitive modeling architecture to produce a tool that can model both the discrete tasks of pilots and the cognitive processes associated with SA. The techniques for using this tool to predict SA were demonstrated using the newly developed Aviation Weather Information (AWIN) system. By providing an SA prediction tool to cockpit system designers, cockpit concepts can be assessed early in the design process while providing a cost-effective complement to the traditional pilot-in-the-loop experiments and data collection techniques.

Keller, John↗

DOE OSTI2014

Improving the Usability of Integrated Assessment for Adaptation Practice: Insights from the U.S. Southeast Energy Sector

Energy systems comprise a key sector of the U.S. economy, and one that has been identified as potentially vulnerable to the effects of climate variability and change. However, understanding of adaptation processes in energy companies and private entities more broadly is limited. It is unclear, for example, the extent to which energy companies are well-served by existing knowledge and tools emerging from the impacts, adaptation and vulnerability (IAV) and integrated assessment modeling (IAM) communities and/or what experiments, analyses, and model results have practical utility for informing adaptation in the energy sector. As part of a regional IAM development project, we investigated available evidence of adaptation processes in the energy sector, with a particular emphasis on the U.S. Southeast and Gulf Coast region. A mixed methods approach of literature review and semi-structured interviews with key informants from energy utilities was used to compare existing knowledge from the IAV community with that of regional stakeholders. That comparison revealed that much of the IAV literature on the energy sector is climate-centric and therefore disconnected from the more integrated decision-making processes and institutional perspectives of energy utilities. Increasing the relevance of research and assessment for the energy sector will necessitate a greater investment in integrated assessment and modeling efforts that respond to practical decision-making needs as well as greater collaboration between energy utilities and researchers in the design, execution, and communication of those efforts.

de Bremond, Ariane↗

DOE OSTI2024

Achieving Cooperative Community Equitable Solar Sources (ACCESS) (Final Technical Report)

Since 2011, solar has grown from a niche technology to a widely accessible source of power for homes and businesses across the United States and has become a fundamental part of the modern grid. There are still challenges, however, in learning how to integrate and use PV most effectively and how to make PV universally available. Most low- and moderate-income (LMI) customers cannot currently afford PV; capital costs and financing costs are too high to drive significant penetration. Providing access to LMI individuals and communities is a critical and immediate priority, and the focus of this project. The overall objective of the Achieving Cooperative Community Equitable Solar Sources (ACCESS) project is to explore and amplify the use of innovative, cost-effective energy access programs to serve co-ops’ LMI members1. ACCESS will research at least three financing mechanisms and at least six LMI program designs including LMI engagement strategies to maximize participation for these hard-to-reach audiences. ACCESS evaluated the financial mechanisms and program designs from field tests sited at diverse co-ops that provide recognizable models for the broader co-op community to identify optimal solutions for small utilities. The research with these cooperatives allowed testing of concepts and development of models and tools for other utilities to adapt to their own program designs and expansions. ACCESS published results and developed an “ACCESS Solar Access Toolkit” consisting of program designs, LMI engagement strategies, how-to guidance, and other tools to facilitate replication at small utilities across the country. Through the dissemination practices of the ACCESS project team, all NRECA member co-ops (~900) were made aware of the “ACCESS Solar Access Toolkit” and all other ACCESS resources. NRECA and its partners developed innovations to expand co-ops’ solar energy offerings to provide all of a co-op’s members—especially those who struggle to pay their bills—with cost-effective options that meet their needs. ACCESS specifically explored utility financing mechanisms and program designs that, independently or used in combination, increase solar access for rural electric cooperatives’ LMI members/ratepayers and that reduce LMI member/ratepayers’ electricity costs by at least 10%. LMI engagement strategies focused on maximizing the number of members who receive benefits and on the cost savings to LMI participants.

14 SOLAR ENERGY↗

DOE OSTI2019

Double-Shell Tank Primary Bottom Inspection Development - 19067

Double-Shell Tank (DST) integrity at Hanford is maintained with a variety of activities such as ultrasonic and visual inspections, chemistry controls, corrosion monitoring and structural analyses methods [1]. A pressing need for the Double-Shell Tank Integrity Program is the ability to inspect the bottom of the tanks. Though the DSTs' annulus spaces (the space between the internal and external tank walls) have been inspected visually since 1992 and with Ultrasonic Testing (UT) since 1996, WRPS has been unable to conduct inspections of the tank bottoms due to limitations of available technology, omitting about 40 percent of the tank surface below the maximum fill level from routine inspection. Visual inspections of the tank annulus have been conducted up to five times in some DSTs and the annulus space for all of the DSTs has been inspected twice with UT. The annulus region includes the walls of the primary tank and secondary liner along with accessible portions of the secondary liner bottom. Due to the lack of under-tank inspection technology, degradation of the primary tank bottom in Tank AY-102 was undetected until the tank leaked into its annulus space, confirmed in 2012 [2]. Since that time, WRPS has been working with the nondestructive examination community and the Pacific Northwest National Laboratory to evaluate potential technologies to conduct these challenging remote inspections. Recent work has included the development, testing, and deployment of several remote visual inspection technologies to observe the condition of the primary tank bottom of the DSTs by leveraging air distribution slots in the refractory pad on which it rests. Robotic solutions to conduct this inspection were developed with a detailed understanding of the physical configuration and operational logistics. Understanding and subsequent communication of these details to vendors within the robotics and nondestructive examination community was a critical component to the successful production of these new tools. In total, two remote visual inspection tools were produced by two vendors. The first tool was designed to leverage existing ultrasonic testing magnetic wall crawler technology in use within the double-shell tank annuli at Hanford. This resulted in a cost savings, immediate familiarization with the equipment, and a more streamlined shop to field experience. The second tool was developed from the ground up, and represents a more tailored and purpose-built solution to the problem. While costlier and more complex, it is also more versatile and capable of future growth or adaptation. Initial design of both tools began in early FY17 with fabrication and testing completed in early FY18. The tools were designed to be deployed alongside existing inspection operations and expand coverage. Development of visual inspection tools to evaluate the primary tank bottom region of the double-shell tanks was planned as the first stage of inspection. Continued development of volumetric sensors and incorporation of these inspection tools into Hanford's ongoing Double-Shell Tank Integrity Program are the next steps, continuously seeking to expand understanding of asset integrity and remaining useful life. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗

NASA NTRS2016

Designing and Building a Crew-Centric Mobile Scheduling and Planning Tool for Exploring Crew Autonomy Concepts Onboard the International Space Station

During 2015, as part of our ongoing research on crew autonomy, our team adapted and extended the plan viewing tool, Playbook, into a mobile tool for exploring crew autonomy onboard the International Space Station (ISS). This work enables crewmembers to intuitively re-plan and schedule on their own with limited input from mission control. Designed for ease of use, re-planning is composed of simple drag and drop interactions and learning the tool requires little to no training. Playbook was successfully uplinked onto ISS as a technology demonstration and completed its onboard ground and crew checkouts in August and September 2015, respectively. We will discuss and describe how Playbook was able to integrate with actual ISS operational plans and operational procedures without disrupting real mission operations. This work will also outline the design and technical constraints required to build a collaborative tool that allows multiple users to simultaneously self-schedule and synchronize during communication dropouts in the restricted networking and computing environment onboard ISS. Finally, we will explore the aspects of crew autonomy that this technology enables as well as discuss our next steps and possible extensions.

ISS↗

DOE OSTI2024

Dyn$\mathrm{AMO}$: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws

Here we introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost and solution accuracy in numerical methods for partial differential equations. However, traditional adaptive mesh refinement approaches for time-dependent problems typically rely only on instantaneous error indicators to guide adaptivity. As a result, standard strategies often require frequent remeshing to maintain accuracy. In the DynAMO approach, multi-agent reinforcement learning is used to discover new local refinement policies that can anticipate and respond to future solution states by producing meshes that deliver more accurate solutions for longer time intervals. By applying DynAMO to discontinuous Galerkin methods for the linear advection and compressible Euler equations in two dimensions, we demonstrate that this new mesh refinement paradigm can outperform conventional threshold-based strategies while also generalizing to different mesh sizes, remeshing and simulation times, and initial conditions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2012

Adaption of G-TAG Software for Validating Touch and Go Asteroid Sample Return Design Methodology

A software tool is used to demonstrate the feasibility of Touch and Go (TAG) sampling for Asteroid Sample Return missions. TAG is a concept whereby a spacecraft is in contact with the surface of a small body, such as a comet or asteroid, for a few seconds or less before ascending to a safe location away from the small body. Previous work at JPL developed the G-TAG simulation tool, which provides a software environment for fast, multi-body simulations of the TAG event. G-TAG is described in Multibody Simulation Software Testbed for Small-Body Exploration and Sampling, (NPO-47196) NASA Tech Briefs, Vol. 35, No. 11 (November 2011), p.54. This current innovation adapts this tool to a mission that intends to return a sample from the surface of an asteroid. In order to demonstrate the feasibility of the TAG concept, the new software tool was used to generate extensive simulations that demonstrate the designed spacecraft meets key requirements. These requirements state that contact force and duration must be sufficient to ensure that enough material from the surface is collected in the brushwheel sampler (BWS), and that the spacecraft must survive the contact and must be able to recover and ascend to a safe position, and maintain velocity and orientation after the contact.

Blackmore, Lars James C.↗

DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗