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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Surrogate multi-fidelity data and model fusion for scientific discovery and uncertainty quantification in Earth System Models

This whitepaper addresses the Earth and Environmental Systems Sciences Division (EESSD)’s predictability challenges in modeling the integrated water cycle and data-model integration. Specifically, it focuses on reducing and characterizing the uncertainty in the representation of process models for unresolved physics, either due to model resolution or limited by the physical under standing or computational efficiency, and the use of observational data for in-situ process parameter optimization within ESM. The described methods may also be used to determine the nature of responses (e.g. strength and direction), and hence to identify critical processes that drive the overall ESM responses to perturbation in the forcing

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Usage of Observing System Simulation Experiments and Reinforcement Learning to Optimize Experimental Design and Operation

Various organizations regularly conduct field campaigns across the globe designed to probe and improve atmospheric process understanding. However, these campaigns are mostly designed ad-hoc, and rely on anecdotes and knowledge of what was successful in previous campaigns. Such ad-hoc experiment design results in sub-optimal instrument siting and operation strategies. Inadequate targeted data collection of extreme weather is a major limitation to Earth and Environmental Systems Science Division (EESSD)’s goals of data model integration (4.5.3), which limits the knowledge gained through the collected observations, holding back significant advances in predictability. While advances in instrument design are always chipping away at these limitations, we are not optimally utilizing the instrumentation we currently possess.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Using Machine Learning to Develop a Predictive Understanding of the Impacts of Extreme Water Cycle Perturbations on River Water Quality

This whitepaper addresses to two focal areas – (3) Insight gleaned from complex data using Artificial Intelligence (AI), and other advanced techniques (primary), and (2) Predictive modeling through the use of AI techniques and AI-derived model components (secondary). This topic is directly relevant to four DOE Earth and Environmental Systems Science Division Grand Challenges: integrated water cycle, biogeochemistry, drivers and responses in the Earth system, and data-model integration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Design rules for 316H nuclear components cladded with nickel or tungsten

The existing Class A metallic materials qualified in the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules for high temperature nuclear reactors are not ideally suited for long term molten salt corrosion resistance in high temperature molten salt reactors. Potentially, corrosion or corrosion driven environmentally assisted cracking could limit the design life of structural components in molten salt reactors. A solution to this limitation is the use of cladded components – overlay the Class A material with a thin layer of some non-qualified, corrosion-resistant material. However, this necessitates the development of design methods for cladded components that do not require long-term testing of clad materials in order to support the near-term deployment of molten salt reactors. This report develops such a methodology along with a complete set of rules presented in a format compatible with an ASME nuclear Code Case. These design rules are for 316H Class A components cladded with either nickel or tungsten. The report also discusses the development of a set of general criteria for selecting clad materials beyond the specific 316H/tungsten and 316H/nickel systems and general acceptance tests for checking the mechanical integrity of the clad/base metal interface. Finally, the report includes a set of fully-documented sample problems detailing the application of the rules to high temperature cladded components

36 MATERIALS SCIENCE↗
DOE OSTI2020

Structural Characterization of Potential Carbon Dioxide Reservoirs and Adjacent Strata within the Llandovery Silurian to Middle Devonian Strata of Ohio

The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO 2 ) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. This report details the work led by the Ohio Department of Natural Resources, Division of Geological Survey to evaluate the structure of nine formations in the Appalachian Basin of Ohio to assess seal integrity and whether carbon dioxide (CO 2 ) migration pathways could pose a potential risk. As part of Phase II MRCSP work, the Pennsylvania Geological Survey led the characterization of the Llandovery Silurian (“middle Silurian”) to Middle Devonian regional geologic characterization CO 2 utilization and storage. This preliminary assessment included generalized, regional-scale mapping, as well as the development of relatively coarse structure and isochore maps of stratigraphic intervals of interest for the Appalachian Basin. Because this stratigraphic interval offers several enhanced oil recovery targets and secondary targets for CO 2 storage, the Ohio Geological Survey undertook efforts in Phase III to characterize the Ohio’s portion of the Appalachian Basin more precisely and to resolve inconsistencies within Ohio’s formation tops. This study refined the subsurface correlations of the Silurian-through-Devonian stratigraphic section in Ohio. Higher-resolution isochore mapping of the CO 2 storage reservoirs and seals provides greater detail of potential high-porosity zones and potential structural influence on the interval.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

2020 Results for Avian Monitoring at the Technical Area 36 Minie Site, Technical Area 39 Point 6, and Technical Area 16 Burn Ground at Los Alamos National Laboratory

Los Alamos National Laboratory (LANL) biologists in the Environmental Protection and Compliance Division initiated a multi-year program in 2013 to monitor avifauna (birds) at two open detonation sites and one open burn site on LANL property. In this annual report we compare monitoring results from these efforts among years to monitor trends. The objectives of this study are to 1) determine whether LANL operations impact bird species richness, diversity, or abundance and 2) examine occupancy and nest success of secondary-cavity nesting birds using nestboxes. LANL biologists completed the eighth year of this effort in 2020

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Nimble Feedthrough Qualification - 125% High Explosive Overpressure Test Plan RevA

The primary purpose of this High Explosive (HE) Over-Pressure Test (OPT) is to qualify top cover diagnostic feedthroughs that will be used on LLNL Nimble Subcritical Experiment (SCE) Series designs per experimental design verification requirements specified in ASME Boiler and Pressure Vessel Code Case 2564, Impulsively-Loaded Pressure Vessels, Section VIII, Division 3; and to satisfy the over-test requirement of DOE-STD-1212. The diagnostic feedthroughs are part of the Vessel Confinement System (VCS), which is credited as a Safety Significant Design Feature per the U1a Facility Documented Safety Analysis (DSA). The OPT will be conducted at the LANL Area 1, R306 Firing Site (TA-15-R306) in a 3-foot diameter VCS depicted in Figure 1.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

EHS Health Assessment & Health Action Plan Report (CY 2020)

Sandia National Laboratories (SNL) Employee Health Services (EHS) program believes that good health is essential to getting the most out of life, which is why we offer a variety of worksite wellness programs that put employees in control of their own health. These programs are based on current research and strategies that are proven to minimize risk and decrease the impact of illness through early detection and treatment. Services includes Health Assessments, the Virgin Pulse (VP) online wellness platform, and Health Action Plans (HAP) which include one-on-one education, organizational health initiatives, a video library, an events calendar, onsite fitness facilities, and group fitness classes. Participation in these programs help employees and their spouses earn funding for their Health Reimbursement Accounts (HRAs). The EHS Health Action Plan (HAP) initiative targets the key health risks identified through the 8-15-80 model by engaging employees to change their own healthcare story. EHS identified the most prevalent of the health risks amongst our population through Health Risk Assessment (HRA) and used that data to build Health Action Plans (HAPs). The 2020 Health Action Plans addressed improving upon inadequate sleep, lack of energy, stress, weight, physical inactivity, cardiometabolic issues (hypertension, high cholesterol, diabetes), low back pain, allergies, asthma, digestive health, tobacco use, and living well to maintaining low risk for those individuals who do not have a chronic condition to manage. These plans connect employees with our onsite registered dietitians, fitness professionals, health coaches, physical therapists, and physicians as appropriate. In addition to addressing the physical aspects of health, the plans also emphasized pre/post-assessments to encourage building behavioral and emotional skills that promote health and facilitate lifestyle changes over a minimum of three months. Just one risk reduction or behavior change can make an impact on the health of the participant’s Division as well as Sandia’s overall risk levels and ultimately its healthcare costs. Sandia employees achieved an Overall Wellness Score of 69 based on the WellSource Health Assessment (the same as last year). A score of 70-100 is considered “Doing Well”, and a score of 40-69 is in the “Caution” category. Overall in CY 2019, Sandia saw a 34% participation rate in Health Action Plan (HAP) programs (up from 33% in CY 2019) with an 89% completion rate (4% lower than CY 2019). Overall, 5,039 (347 more than CY 2019) individuals participated in 8,329 HAPs, which is 1,005 more than the last calendar year (7,324).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Demonstration and Validation of Additively Manufactured Intensified Device for Enhanced Carbon Capture

In FY 2018 and 2019, ORNL personnel designed, prototyped, characterized, and tested the enhancement of amine-based carbon capture using additively manufactured intensified devices, i.e., devices combining multiple thermodynamic and kinetic processes into one unit operation. State of the art scrubbing technology often employs inter-stage cooling which requires multiple stages of single-purpose unit operations, leading to larger equipment size, higher capital cost, and sometimes less than optimal operating conditions for each piece of equipment. It was proposed that integrating multiple thermodynamic and kinetic operations into one unit could mitigate or negate these drawbacks. Heat and mass transfer studies demonstrated that an additively manufactured intensified device could significantly improve capture efficiency at bench scale. This project is a continuation of FEAA130 and aims at (1) demonstration and validation of enhanced CO 2 capture with 3D printed intensified devices (i.e., mass exchanger packing with internal cooling channels), for low-aqueous-solvent (LAS) based capture at the ORNL-constructed laboratory-scale (4.5-feet tall) column, namely Column A, with built-in cooling and (2) computational scoping on the conceptual design of a flexible and modular larger column, namely Column B, at ORNL for further demonstration of enhanced capture for aqueous solvent. To execute this multi-faceted project scope, an integrated project team from ORNL’s Manufacturing Science Division is tasked with applying capabilities in computational fluid dynamics (CFD), additive manufacturing, and absorber-scale demonstration/validation experiments.

42 ENGINEERING↗
DOE OSTI2021

2021-2026 Weapons Research Services Strategic Plan

The Weapons Research Services (WRS) Division provides Los Alamos National Laboratory with services, resources, and staff that are critical to fulfilling its national security mission. WRS serves the entire LANL Weapons Program and is housed within the Weapons Physics Directorate (ALDX), which is at the core of the design, certification, and assessment of the nation’s nuclear weapons. More specifically, WRS is a research and development organization that provides unique tools designed to meet the specific needs of the Lab’s weapons mission rather than administrative or Information & Technology (IT) tools used broadly by the Lab. WRS partners with other LANL organizations, including Global Security to conduct mission research and I&T organizations to meet basic IT infrastructure needs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

E-Student Welcome [Slides]

This orientation covers introductions, overview of W/Q divisions, safety and security, and end-of-summer documentation and presentations for the E Student program.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Weapons Production Directorate Overview

Detonator Production and Prototype Fabrication divisions serve a variety of organizations throughout the Laboratory and the nation by providing key non-nuclear components through excellence in on-site engineering, design, manufacturing, machining, and more.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Demonstration of Advanced Experimental and Theoretical Characterization of Hydrogen Dynamics and Associated Behavior in Advanced Reactors

Advanced materials development, manufacturing, and modeling capabilities for innovative reactor designs support nuclear security and mission-focused science through enhanced technology for safer and more efficient and secure production of nuclear energy. The research in this project has established: 1) a state-of-the-art neutron-based hydrogen mapping and cross-section measurement capability as well as detailed crystallographic characterization of hydrogen atoms at LANSCE, and 2) a multi-physics framework for simulating behavior of moderator materials and other material performance in advanced nuclear reactors. Through the course of this project, we successfully developed and demonstrated measurement techniques for hydrogen distribution and atomistic-scale behavior of hydrogen atoms using pulsed neutron techniques. In parallel, advanced multi-physics simulation tools to predict the behavior of hydrogen atoms, e.g. in a moderator for a nuclear reactor, through materials performance, neutron transport, and thermal mechanical behavior were enhanced. Multi-discipline areas across the laboratory were involved in the project as the integration of improved experimental capabilities with enhanced modeling and simulation through MST, NEN, SIGMA, and XCP division subject matter experts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Integrated Project Review (IPR) Program

Environmental Protection and Compliance Division (EPC-DO) owns institutional responsibility for compliance with Federal, State, and local environmental requirements. EPC SMEs want to know about all activities and projects being conducted at the Lab. Our regulatory framework requires LANL customers to use the Integrated Review Tool which includes PRID, EXID, and Siting. SD400 Environmental Management System, Rev 5 states all new/modified work, activities, operations and projects at the Lab must be reviewed for applicable environmental requirements through the IRT.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vessel Fabrication Overview

LANL utilizes spherical vessels for numerous basic science, materials, and system performance experiments. These pressure vessels are designed and fabricated to meet the intent of ASME B&PV Section VIII, Division 3 and Code Case 2564. LANL has successfully contracted vessel construction in the past, utilizing HSLA-100 steel. As current vessel inventories approach design life, we are once again embarking upon a series of fabrication contracts to produce replacement components and vessel assemblies to support continued experiment cadence at LANL. LANL’s intent is to ramp up a continuous vessel supply chain for the DOE Complex.

42 ENGINEERING↗
DOE OSTI2021

Evaluation of the Polymer Characterization Capabilities of Matrix-Assisted Laser Desorption/Ionization (Literature Review)

Matrix-assisted laser desorption/ionization (MALDI) is becoming a key method in expanding the characterization capabilities of synthetic polymers. While there are still some analytical limitations, technological and methodological improvements have greatly improved this technique for analyzing large molecules. This paper serves as an investigation into MALDI-Time of Flight (TOF) capabilities and potential applications as the Material Science Division at Los Alamos National Laboratory seeks to expand its analytical capabilities. Three MALDI-TOF instrument offerings from Bruker, an industry-leader in MALDI-TOF polymer analysis that will evaluated in further detail.

36 MATERIALS SCIENCE↗