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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Towards Principled Experimental Study of Autonomous Mobile Robots

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.

Object-Oriented Simulation↗
DOE OSTI2013

Power to the People...Energy for Now and Later

Representing the Combustion Energy Frontier Research Center (CEFRC), this document is one of the entries in the Ten Hundred and One Word Challenge. As part of the challenge, the 46 Energy Frontier Research Centers were invited to represent their science in images, cartoons, photos, words and original paintings, but any descriptions or words could only use the 1000 most commonly used words in the English language, with the addition of one word important to each of the EFRCs and the mission of DOE: energy. The mission of CEFRC is to develop a validated, predictive, multi-scale combusion modeling capacity which can be used to optimize the design and operation of evolving fuels in advanced engines for transportation applications.

08 HYDROGEN↗
DOE OSTI2011

A Brief Review of Viscosity Models for Slag in Coal Gasification

Many researchers have defined the phenomenon of 'slagging' as the deposition of ash in the radiative section of a boiler, while 'fouling' refers to the deposition of ash in the convective-pass region. Among the important parameters affecting ash deposition that need to be studied are ash chemistry, its transport, deposit growth, and strength development; removability of the ash deposit; heat transfer mechanisms; and the mode of operation for boilers. The heat transfer at the walls of a combustor depends on many parameters including ash deposition. This depends on the processes or parameters controlling the impact efficiency and the sticking efficiency. For a slagging combustor or furnace, however, the temperatures are so high that much of the coal particles are melted and the molten layer, in turn, captures more particles as it flows. The main problems with ash deposition are reduced heat transfer in the boiler and corrosion of the tubes. Common ways of dealing with these issues are soot blowing and wall blowing on a routine basis; however, unexpected or uncontrolled depositions can also complicate the situation, and there are always locations inaccessible to the use of such techniques. Studies have indicated that slag viscosity must be within a certain range of temperatures for tapping and the membrane wall to be accessible, for example, between 1300 C and 1500 C, the viscosity is approximately 25 Pa {center_dot} s. As the operating temperature decreases, the slag cools and solid crystals begin to form. In such cases the slag should be regarded as a non-Newtonian suspension, consisting of liquid silicate and crystals. A better understanding of the rheological properties of the slag, such as yield stress and shear-thinning, are critical in determining the optimum operating conditions. To develop an accurate heat transfer model in any type of coal combustion or gasification process, the heat transfer and to some extent the rheological properties of ash and slag, especially in high-temperature environments need to be understood and properly modeled. The viscosity of slag and the thermal conductivity of ash deposits are among two of the most important constitutive parameters that need to be studied. The accurate formulation or representations of the (transport) properties of coal (and biomass for co-firing cases) present a special challenge of modeling efforts in computational fluid dynamics applications. In this report, we first provide a brief review of the various approaches taken by different researchers in formulating or obtaining a slag viscosity model. In general, these models are based on experiments. Since slag behaves as a non-linear fluid, we discuss the constitutive modeling of slag and the important parameters that must be studied.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2020

Effects of Resistive Windscreens and Foam Inserts on The Acoustic Response of an In-Flow Phased Microphone Array

The effects of varying windscreen resistance and cavity foam treatments on the acoustic response of an in-flow phased microphone array have been characterized by recent experiments at ARC, GRC, and LaRC using common array and calibration source designs. New correction models have been developed and validated with results from recent impedance tube, anechoic chamber, and wind tunnel tests.

Wind tunnel aeroacoustics research↗
DOE OSTI2015

Identification of Modeling Approaches To Support Common-Cause Failure Analysis

Experience with applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The impact of CCF vulnerability is to inhibit I&C modernization and, thereby, challenge the long-term sustainability of existing plants. For new plants and advanced reactor concepts, the issue of CCF vulnerability for highly integrated digital I&C systems imposes a design burden resulting in higher costs and increased complexity. The regulatory uncertainty regarding which mitigation strategies are acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. The conditions that constrain the transition to digital I&C technology by the U.S. nuclear industry require crosscutting research to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for usage in Nuclear Power Plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is conducting an investigation into mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive technical basis for establishing the qualification of digital technology for nuclear power applications. This report documents the investigation of modeling approaches for representing failure of I&C systems. Failure models are used when there is a need to analyze how the probability of success (or failure) of a system depends on the success (or failure) of individual elements. If these failure models are extensible to represent CCF, then they can be employed to support analysis of CCF vulnerabilities and mitigation strategies. Specifically, the research findings documented in this report identify modeling approaches that can be adapted to contribute to the basis for developing systematic methods, quantifiable measures, and objective criteria for evaluating CCF vulnerabilities and mitigation strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Research Update: Electrical monitoring of cysts using organic electrochemical transistors

Organotypic three-dimensional (3D) cell culture models have the potential to act as surrogate tissues in vitro, both for basic research and for drug discovery/toxicology. 3D cultures maintain not only 3D architecture but also cell-cell and cell extracellular matrix interactions, particularly when grown in cysts or spheroids. Characterization of cell cultures grown in 3D formats, however, provides a significant challenge for cell biologists due to the incompatibility of these structures with commonly found optical or electronic monitoring systems. Electronic impedance spectroscopy is a cell culture monitoring technique with great potential; however, it has not been possible to integrate 3D cultures with commercially available systems to date. Cyst-like 3D cultures are particularly challenging due to their small size and difficulty in manipulation. Herein, we demonstrate isolation of cyst-like 3D cultures by capillarity and subsequent integration with the organic electrochemical transistor for monitoring the integrity of these structures. We show not only that this versatile device can be adapted to the cyst format for measuring resistance and, therefore, the quality of the cysts, but also can be used for quantitative monitoring of the effect of toxic compounds on cells in a 3D format. The ability to quantitatively predict effects of drugs on 3D cultures in vitro has large future potential for the fields of drug discovery and toxicology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

A Review of Dynamic Generator Reduction Methods For Transient Stability Studies

Due to the complex interconnected nature of power system, aggregate or reduced system is commonly used by operators and engineers for various power system studies. Transient stability studies need dynamically reduced models to include the dynamic effects of the generating units. Dynamic generator reduction is therefore an important component of power system dynamic reduction. The many different methods for generator reduction in power systems taken from the earliest available literature are discussed. This paper aims to provide an easy reference to researchers interested in exploring dynamic reduction of power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Atmospheric testbed workshop, August 5-6, 2013

A primary goal of the Climate and Environmental Sciences Division (CESD) is to improve the predictive ability of regional and global climate models (GCMs). One set of tools used for evaluating and improving model predictions and projections are testbeds that combine data derived from observations and model simulations. In these testbeds, outputs of model simulations can be compared to observations of the climate system in order to identify errors and/or biases in the model simulations and determine the specific model processes that need improvements. Testbeds can also be used to provide scientific insights into dominant processes and process interactions as well as increase our understanding of the role of various physical processes involved in a particular case study or meteorological event. CESD currently funds multiple activities, which are developing testbeds to evaluate and improve atmospheric model parameterizations across a range of models, scales, and processes. For each of these testbeds, the Atmospheric Radiation Measurement (ARM) Climate Research Facility represents a primary source of observational data for evaluating the models. The Atmospheric System Research (ASR), Earth System Modeling (ESM), Regional and Global Climate Modeling (RGCM), and ARM program managers co-sponsored a workshop on atmospheric testbed activities across CESD. The workshop was held August 5-6, 2013, at the U. S. Department of Energy (DOE) Germantown facility. The principal objectives of the workshop were to survey the CESD testbed portfolios; identify the distinctive capabilities of each testbed as well as commonalities between the testbeds; identify areas for coordination and collaboration among testbeds; improve linkages between testbed activities and the ARM facility; identify gaps in testbed activities; and identify ways to improve coordination and communication among the testbeds and between the testbeds and the broader scientific community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

The SIMRAND methodology - Simulation of Research and Development Projects

In research and development projects, a commonly occurring management decision is concerned with the optimum allocation of resources to achieve the project goals. Because of resource constraints, management has to make a decision regarding the set of proposed systems or tasks which should be undertaken. SIMRAND (Simulation of Research and Development Projects) is a methodology which was developed for aiding management in this decision. Attention is given to a problem description, aspects of model formulation, the reduction phase of the model solution, the simulation phase, and the evaluation phase. The implementation of the considered approach is illustrated with the aid of an example which involves a simplified network of the type used to determine the price of silicon solar cells.

Miles, R. F., Jr.↗
NASA NTRS2023

A Guide to Forced Oscillation Data Processing and Analysis

The NASA Langley Research Center Flight Dynamics Branch has a long history of experimental testing of aircraft and spacecraft flight dynamics. One of the frequently used wind tunnel test methods is forced oscillation testing. This method involves a model mounted on a specialized dynamic test rig in a tunnel and oscillated about a body axis, typically at a fixed sinusoidal frequency and amplitude. This report provides the derivation of two commonly used data reduction methods and introduces one new method to extract the linear dynamic derivatives from forced oscillation wind tunnel data.

Flight Dynamics↗
NASA NTRS2001

Lower Stratospheric Temperature Differences Between Meteorological Analyses in two cold Arctic Winters and their Impact on Polar Processing Studies

A quantitative intercomparison of six meteorological analyses is presented for the cold 1999-2000 and 1995-1996 Arctic winters. The impacts of using different analyzed temperatures in calculations of polar stratospheric cloud (PSC) formation potential, and of different winds in idealized trajectory-based temperature histories, are substantial. The area with temperatures below a PSC formation threshold commonly varies by approximately 25% among the analyses, with differences of over 50% at some times/locations. Freie University at Berlin analyses are often colder than others at T is less than or approximately 205 K. Biases between analyses vary from year to year; in January 2000. U.K. Met Office analyses were coldest and National Centers for Environmental Prediction (NCEP) analyses warmest. while NCEP analyses were usually coldest in 1995-1996 and Met Office or NCEP[National Center for Atmospheric Research Reanalysis (REAN) warmest. European Centre for Medium Range Weather Forecasting (ECMWF) temperatures agreed better with other analyses in 1999-2000, after improvements in the assimilation model. than in 1995-1996. Case-studies of temperature histories show substantial differences using Met Office, NCEP, REAN and NASA Data Assimilation Office (DAO) analyses. In January 2000 (when a large cold region was centered in the polar vortex), qualitatively similar results were obtained for all analyses. However, in February 2000 (a much warmer period) and in January and February 1996 (comparably cold to January 2000 but with large cold regions near the polar vortex edge), distributions of "potential PSC lifetimes" and total time spent below a PSC formation threshold varied significantly among the analyses. Largest peaks in "PSC lifetime" distributions in January 2000 were at 4-6 and 11-14 days. while in the 1996 periods, they were at 1-3 days. Thus different meteorological conditions in comparably cold winters had a large impact on expectations for PSC formation and on the discrepancies between different meteorological analyses. Met Office. NCEP, REAN, ECMWF and DAO analyses are commonly used for trajectory calculations and in chemical transport models; the choice of which analysis to use can strongly influence the results of such studies.

Manney, Gloria L.↗
DOE OSTI2024

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

OCHRE: The Object-oriented, Controllable, High-resolution Residential Energy Model for Dynamic Integration Studies

Electrification and the growth of distributed energy resources (DERs), including flexible loads, are changing the energy landscape of electric distribution systems and creating new challenges and opportunities for electric utilities. Changes in demand profiles require improvements in distribution system load models, which have not historically accounted for device controllability or impacts on customer comfort. Although building modeling research has focused on these features, there is a need to incorporate them into distribution load models that include DERs and can be used to study grid-interactive buildings. In this paper, we present the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) model. OCHRE is a controllable thermal-electric residential energy model that captures building thermal dynamics, integrates grid-dependent electrical behavior, contains models for common DERs and end-use loads, and simulates at a time resolution down to 1 minute. It includes models for space heaters, air conditioners, water heaters, electric vehicles, photovoltaics, and batteries that are externally controllable and integrated in a co-simulation framework. Using a proposed zero energy ready community in Colorado, we co-simulate a distribution grid and 498 all-electric homes with a diverse set of efficiency levels and equipment properties. We show that controllable devices can reduce peak demand within a neighborhood by up to 73% during a critical peak period without sacrificing occupant comfort. We also demonstrate the importance of modeling load diversity at a high time resolution when quantifying power and voltage fluctuations across a distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Evaluation of RANS vs. LES simulation of fluid flow through 3 × 3 rod bundle with a simple spacer grid as a precursor to coupled fluid–structure interaction simulations

The research literature on Computational Fluid Dynamics (CFD) of coolant flow through rod bundles with spacer-grids and mixing vanes is replete, ranging from high fidelity Large Eddy Simulation (LES)/Direct Numerical Simulation (DNS) simulations to Reynolds-Averaged Navier–Stokes (RANS) modeled studies. The mixing of flow between subchannels and the pressure drop through the bundle are fundamental quantities useful for comparing and evaluating CFD methods. Less commonly observed and compared are the forces exerted onto the structure by the fluid. The present study seeks to evaluate the use of RANS simulations for predicting the structural response to fluid flow. Wall resolved RANS simulations are benchmarked against LES simulations of fluid flow at a Reynolds number of 15,000 through a 3 × 3 fuel rod bundle with a simple spacer grid. Velocity line-plots are compared showing good agreement between RANS and LES results, ascertaining that the former is capable of capturing the essential time-averaged velocity profile. Additionally, the distribution of forces on the spacer grid and fuel rods are collected as a function of time and space. The RANS methods are evaluated using the frequency and magnitude of the fluctuating forces on various portions of the structure as compared to LES. In conclusion, the power spectral density evaluation of the models reveal underprediction of force amplitude on the rod walls by RANS and also discrepancy in the prediction of high frequency spectra, especially in the immediate vicinity of spacer-grid structure, which may be attributed to the lack of random turbulence fluctuation or insufficient modeling of small-scale eddies in RANS simulation.

FIV↗
DOE OSTI2013

SciDAC-Center for Plasma Edge Simulation Report

The Common Component Architecture (CCA) effort is the embodiment of a long-range program of research and development into the formulation, roles, and use of component technologies in high-performance scientific computing. CCA components can interoperate with other components in a variety of frameworks, including SCIRun2 from the University of Utah. The SCIRun2 framework is also developing the ability to connect components from a variety of different models through a mechanism called meta-components. The meta component model operates by providing a plugin architecture for component models. Abstract components are manipulated and managed by the SCIRun2 framework, while concrete component models perform the actual work and communicate with each other directly. We will leverage the SCIRun2 framework and the Kepler system to orchestrate components in the Fusion Simulation Project (FSP) and to provide a CCA-based interface with Kepler. The groundwork for this functionality is being performed with the Scientific Data Management center. The SDM center is developing CCA-compliant interfaces for expressing and executing workflows and create workflow components based on SCIRun and Ptolemy (Kepler) execution engines, including development of uniform interfaces for selecting, starting, and monitoring scientific workflows. Accomplishments include Introduction to CCA and Simulation Software Systems, Introduction into SCIRun2 and Bridging within SCIRun2, CCALoop: A scalable design for a distributed component framework, and Combining Workflow methodologies with Component Architectures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Historic American engineering record. Nevada national security site, Bren Tower Complex. Written historical and descriptive data and field records

The BREN (Bare Reactor Experiment, Nevada) Tower Complex is significant for its role in the history of nuclear testing, radiation dosimetry studies, and early field testing of the Strategic Missile Defense System designs. At the time it was built in 1962, the 1,527 ft (465 m) BREN Tower was the tallest structure west of the Mississippi River and exceeded the height of the Empire State Building by 55 ft (17 m). It remains the tallest ever erected specifically for scientific purposes and was designed and built to facilitate the experimental dosimetry studies necessary for the development of accurate radiation dose rates for the survivors of Hiroshima and Nagasaki. The tower was a key component of the Atomic Bomb Casualty Commission’s (ABCC) mission to predict the health effects of radiation exposure. Moved to its current location in 1966, the crucial dosimetry studies continued with Operation HENRE (High Energy Neutron Reactions Experiment). These experiments and the data they generated became the basis for a dosimetry system called the Tentative 1965 Dose or more commonly the T65D model. Used to estimate radiation doses received by individuals, the T65D model was applied until the mid-1980s when it was replaced by a new dosimetry system known as DS86 based on the Monte Carlo method of dose rate calculation. However, the BREN Tower data are still used for verification of the validity of the DS86 model. In addition to its importance in radiation heath effects research, the BREN Tower Complex is also significant for its role in the Brilliant Pebbles research project, a major component of the Strategic Defense Initiative popularly known as the “Star Wars” Initiative. Instigated under the Reagan Administration, the program’s purpose was to develop a system to shield the United States and allies from a ballistic missile attack. The centerpiece of the Strategic Defense System was space-based, kinetic-kill vehicles. In 1991, BREN Tower was used for the tether tests of the Brilliant Pebbles prototype vehicle at the earth’s surface prior to the more costly space testing program. The success of these tests established the Brilliant Pebbles program as an essential component of America’s space-based missile defense system even after the dismantling of the Soviet Union. Data from the Brilliant Pebbles research program continues to inspire current missile defense system research (Independent Working Group 2009).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Integrated pre-feasibility study for CO 2 geological storage in the Cascadia Basin, offshore Washington State, British Columbia

The Cascadia CarbonSAFE project conducted a pre-feasibility study to evaluate technical and nontechnical aspects of storing 50 million metric tons (MMT) of carbon dioxide in a safe, ocean basalt reservoir offshore Washington State and British Columbia. Sub-seafloor basalts are very common on Earth and enable geological mineralization as a long-term storage mechanism, permanently sequestering the carbon in solid rock form. This project evaluated the offshore storage complex, developed potential industrial source/transport scenarios, built an inventory of existing geophysical/geological data and environmental monitoring capabilities, conducted laboratory studies and reservoir modeling to determine storage capacity, and analyzed economic factors, regulatory requirements, and project management risks. Our team included researchers at Columbia University in New York, Pacific Northwest National Laboratory (PNNL) in Washington, University of Victoria in British Columbia, University of California at Santa Cruz, and GHG Underground in Maine, as well as collaborators at University of Iceland in Reykjavik and University of Washington in Saint Louis. In the study region, large emitters (>100,000 MT/year) generate a total of approximately 40 MMT annually from stationary sources, such as power plants, refineries, ammonia production, and mineral processing plants. Five potential industry source/transport scenarios were identified (three in U.SA S. and two in Canada) to potentially provide 50 MMT of carbon dioxide to the offshore reservoir. One scenario included net carbon-negative sources that would reduce atmospheric levels. The inventory of existing data illustrated that basalt properties in the region are potentially beneficial for long-term storage. Permeability is on the order of 0.1 to 1 Darcies within the uppermost 600 m of ocean crust and density-derived porosity reaches 10–20% in thin layers that provide act as flow channels and provide access to porous and permeable basalt. Fine-grained sediments overlying basalt provide a low-permeability barrier separating the storage reservoir from the overlying ocean. Subsurface monitoring of the storage complex benefits from a unique opportunity close proximity of to the nearby NEPTUNE cabled seafloor observatory, which actively transmits data to shore and could be used to monitor reservoir properties. Injection pressure changes, reservoir chemistry, seismicity, well head corrosion, and potential leakage monitoring would be feasible in real time. Using existing data and published models, the STOMP-CO 2 modeling code developed at PNNL was used to simulate carbon dioxide injection, storage, and mineralization in the reservoir. Preliminary simulations indicate that a 50 MMT carbon dioxide plume injected over a 20-year period remains well within the reservoir area, both laterally and vertically, for at least a 50-year period of post-injection monitoring. Laboratory studies on core samples from Cascadia measured dissolution rates in CO 2 –basalt–seawater mixtures and indicated large variability in rates with the potential for complete mineralization. Compared to published data, the dissolution rate measured in these samples is faster, decreasing the time until full conversion to carbonate minerals would occur. Adding geochemical reactivity in the STOMP-CO 2 model indicates that carbon dioxide would be fully converted to carbonate minerals in 135 years or less after injection ceases. The project assessed the viability and costs for the five scenarios using either dedicated offshore pipelines or shipping vessels. Carbon dioxide capture costs were not considered. Shipping incurred lower upfront CAPEX costs, and because most viable sources were located near the shore and waterways, shipping is preferred; no dedicated carbon dioxide pipelines exist in the region. The project also considered potential risks from mixed-use impacts on surrounding lands and ocean areas, such as active use by commercial and recreational fisherman, and other community considerations in planning for public engagement in the future. Other project risks were identified, including project management, permitting and compliance, and financing, as well as technical issues such as long-term instrumentation, plume migration, and model development. Geological concerns like reservoir permeability, seal, and induced seismicity held relatively low risk. The regulatory framework for offshore storage in the U.S. and Canada may be covered by general legal/regulatory programs, but is not yet fully defined. Existing programs appear to restrict the transportation of carbon dioxide across national boundaries (e.g., Canada to U.S.) and its sub-seabed disposal in some circumstances. Our assessment suggests that developing specific and separate pilot projects will help to advance the technical feasibility and regulatory requirements in each country, and lessons learned from such activities may be transferable elsewhere around the globe.

42 ENGINEERING↗
DOE OSTI2025

High y + Shear-Stress Turbulence Implementation for High Flux Isotope Reactor Narrow Channel Flows

The research objective of this work was to improve the engineering predictions of the turbulence characteristics of flows in curved narrow channels. Such channel flows are commonly encountered in nuclear research and test reactors, with one of them being the high-flux isotope reactor (HFIR). Research reactors bear high heat fluxes, and the proper computing of turbulence is paramount for safe and reliable reactor operation. The study builds on the results of a previous direct numerical simulation of turbulence to inform a well-known Reynolds-averaged Navier–Stokes shear-stress turbulence model and improves its accuracy in simulating parallel channel flows. A new formulation of the loss term in the dissipation conservation equation is suggested. Combined with high wall distance computational grids, the new implementation provides a fast-running flow solution, suitable for engineering purposes. Model generalization for parallel channel flows, in a broader range of frictional Reynolds numbers, is suggested by introducing a new form of the model constants.

CFD↗