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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scalable modular dynamic molten salt reactor system model with decay heat

Nodal dynamic models allow rapid reduced-order simulations of complex systems. This paper presents a publicly available system dynamic model of a molten salt reactor system with a topology of the Molten Salt Reactor Experiment (MSRE), in MATLAB/Simulink, building upon a model previously published and validated with MSRE data. It adds scaling of nominal power, dynamic representation of decay heat generation, a generic decay heat removal system, improved documentation, modularity, and test cases. One hour of system transient runs in less than 10 min on a laptop. This model is intended for first order engineering calculations, developing insights into system transient behavior, equipment sizing, parameter sensitivity studies. The model contains an easy to use toolkit which can be customized and expanded to describe any molten salt reactor system. Finally, scenarios involving off-normal transients are presented. Relation between shutdown reactivity insertions, decay heat removal, core recriticality, and safe shutdown conditions are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Static and dynamic modeling of steam integration for a NuScale small modular reactor and pulp and paper mill coupling for carbon-neutral manufacturing

Small modular reactors (SMRs) are reactor designs producing less than 300 MWe and are generally planned for deployment as multimodule nuclear power plants. The possibility of factory-manufactured, flexibly sized plants expands the opportunities for nuclear power to different communities and industries, including manufacturing plants that currently utilize fossil fuels to produce both steam and electricity. This paper examines the feasibility of coupling a NuScale SMR with a midsize pulp and paper mill in the Southeastern United States. A steady-state mill model was developed in Aspen HYSYS, based on real data from the operation of the mill, and modified it to include the SMR while maintaining steam quality requirements and making as few changes as possible to existing equipment. Dynamic plant models were also developed Dymola to demonstrate possible plant conditions, using three configurations. Preliminary results suggest that, while SMR coupling is physically feasible, its economic feasibility is limited by the differences in steam and electricity demands. Because of limitations in the amount of steam the mill can take from the SMR, sizing the SMR for the plant’s steam demand may result in an electricity deficit, or vice versa. Furthermore, dynamic analyses show that the addition of a thermal storage system could reduce such deficits, but this entails its own challenges. Each plant must determine the best configuration and control scheme for itself, based on its electricity and heat needs, including the peak duration and intensity for both. Ultimately, an implementation of SMRs with manufacturing processes would benefit from partnering with a local utility to purchase excess electricity generated by the SMR. This will help manufacturing facilities meet their environmental and cost-savings goals, in addition to meeting the need for cost-effective baseload power across the United States.

03 NATURAL GAS↗
DOE OSTI2019

Modular Architecture of the STING C-Terminal Tail Allows Interferon and NF-κB Signaling Adaptation

Stimulator of interferon genes (STING) is a key regulator of type I interferon and pro-inflammatory responses during infection, cellular stress, and cancer. Here, we reveal a mechanism for how STING balances activation of IRF3- and NF-κB-dependent transcription and discover that acquisition of discrete signaling modules in the vertebrate STING C-terminal tail (CTT) shapes downstream immunity. As a defining example, we identify a motif appended to the CTT of zebrafish STING that inverts the typical vertebrate signaling response and results in dramatic NF-κB activation and weak IRF3-interferon signaling. We determine a co-crystal structure that explains how this CTT sequence recruits TRAF6 as a new binding partner and demonstrate that the minimal motif is sufficient to reprogram human STING and immune activation in macrophage cells. Together, our results define the STING CTT as a linear signaling hub that can acquire modular motifs to readily adapt downstream immunity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modular adjuvant-free pan-HLA-DR-immunotargeting subunit vaccine against SARS-CoV-2 elicits broad sarbecovirus-neutralizing antibody responses

Subunit vaccines typically require co-administration with an adjuvant to elicit protective immunity, adding development hurdles that can impede rapid pandemic responses. To circumvent the need for adjuvant in a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) subunit vaccine, we engineer a thermostable immunotargeting vaccine (ITV) that leverages the pan-HLA-DR monoclonal antibody 44H10 to deliver the viral spike protein receptor-binding domain (RBD) to antigen-presenting cells. X-ray crystallography shows that 44H10 binds to a conserved epitope on HLA-DR, providing the basis for its broad HLA-DR reactivity. Adjuvant-free ITV immunization in rabbits and ferrets induces robust anti-RBD antibody responses that neutralize SARS-CoV-2 variants of concern and protect recipients from SARS-CoV-2 challenge. We demonstrate that the modular nature of the ITV scaffold with respect to helper T cell epitopes and diverse RBD antigens facilitates broad sarbecovirus neutralization. Our findings support anti-HLA-DR immunotargeting as an effective means to induce strong antibody responses to subunit antigens without requiring an adjuvant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

iSeq 2.0: A Modular and Interchangeable Toolkit for Interaction Screening in Yeast

Here, we developed a flexible toolkit for combinatorial screening in Saccharomyces cerevisiae , which generates large libraries of cells, each uniquely barcoded to mark a combination of DNA elements. This interaction sequencing platform (iSeq 2.0) includes genomic landing pads that assemble combinations through sequential integration of plasmids or yeast mating, 15 barcoded plasmid libraries containing split selectable markers (URA3 AI , KanMX AI , HphMX AI , and NatMX AI ), and an array of ~24,000 “double-barcoder” strains that can make existing yeast libraries iSeq compatible. Various DNA elements are compatible with iSeq: DNA introduced on integrating plasmids, engineered genomic modifications, or entire genetic backgrounds. DNA element libraries are modular and interchangeable, and any two libraries can be combined, making iSeq capable of performing many new combinatorial screens by short-read sequencing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modular machine learning-based elastoplasticity: Generalization in the context of limited data

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

42 ENGINEERING↗
DOE OSTI2017

Rapid multiphase-field model development using a modular free energy based approach with automatic differentiation in MOOSE/MARMOT

In this paper, we present a novel rapid phase-field model development capability using a modular free energy based approach in the finite element based MOOSE framework. The phase-field equations are implemented in a general form as separate code form the model specific data such as the thermodynamic free energy density and mobility functions. This isolates researchers from complicated code and allows them to focus on implementing new material models. In addition, using a native symbolic differentiation algorithm, all required derivatives of the free energy density are automatically determined, removing sources for potential human error, and guaranteeing optimally preconditioned equation systems through fully populated Jacobian matrices. Free energy terms contributing to a phase-field model are abstracted into self contained objects that can be combined at will at simulation run time. Combining multiple chemical and mechanical free energy contributions allows the construction of coupled phase-field, mechanics, and multiphase models. Through just-in-time compilation, we greatly reduce the computational time required to evaluate the differentiated expressions. Lastly, we demonstrate the new capability on a variety of example simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Nexus: a modular workflow management system for quantum simulation codes

The management of simulation workflows is a significant task for the individual computational researcher. Automation of the required tasks involved in simulation work can decrease the overall time to solution and reduce sources of human error. A new simulation workflow management system, Nexus, is presented to address these issues. Nexus is capable of automated job management on workstations and resources at several major supercomputing centers. Its modular design allows many quantum simulation codes to be supported within the same framework. Current support includes quantum Monte Carlo calculations with QMCPACK, density functional theory calculations with Quantum Espresso or VASP, and quantum chemical calculations with GAMESS. Users can compose workflows through a transparent, text-based interface, resembling the input file of a typical simulation code. A usage example is provided to illustrate the process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

eqtools: Modular, extensible, open-source, cross-machine Python tools for working with magnetic equilibria

As plasma physics research for fusion energy transitions to an increasing emphasis on cross-machine collaboration and numerical simulation, it becomes increasingly important that portable tools be developed to enable data from diverse sources to be analyzed in a consistent manner. This paper presents eqtools, a modular, extensible, open-source toolkit implemented in the Python programming language for handling magnetic equilibria and associated data from tokamaks. eqtools provides a single interface for working with magnetic equilibrium data, both for handling derived quantities and mapping between coordinate systems, extensible to function with data from different experiments, data formats, and magnetic reconstruction codes, replacing the diverse, non-portable solutions currently in use. Moreover, while the open-source Python programming language offers a number of advantages as a scripting language for research purposes, the lack of basic tokamak-specific functionality has impeded the adoption of the language for regular use. Implementing equilibrium-mapping tools in Python removes a substantial barrier to new development in and porting legacy code into Python. In this paper, we introduce the design of the eqtools package and detail the workflow for usage and expansion to additional devices. Additionally, the implementation of a novel three-dimensional spline solution (in two spatial dimensions and in time) is also detailed. Finally, verification and benchmarking for accuracy and speed against existing tools are detailed. Wider deployment of these tools will enable efficient sharing of data and software between institutions and machines as well as self-consistent analysis of the shared data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

The Modular Borehole Monitoring Program. A research program to optimize well-based monitoring for geologic carbon sequestration

Understanding the impacts caused by injection of large volumes of CO 2 in the deep subsurface necessitates a comprehensive monitoring strategy. While surface-based and other remote geophysical methods can provide information on the general morphology of a CO 2 plume, verification of the geochemical conditions and validation of the remote sensing data requires measurements from boreholes that penetrate the storage formation. Unfortunately, the high cost of drilling deep wellbores and deploying instrumentation systems constrains the number of dedicated monitoring borings as well as limits the technologies that can be incorporated in a borehole completion. The objective of the Modular Borehole Monitoring (MBM) Program was to develop a robust suite of well-based tools optimized for subsurface monitoring of CO 2 that could meet the needs of a comprehensive well-based monitoring program. It should have enough flexibility to be easily reconfigured for various reservoir geometries and geologies. The MBM Program sought to provide storage operators with a turn-key fully engineered design that incorporated key technologies, function over the decades long time-span necessary for post-closure reservoir monitoring, and meet industry acceptable risk profiles for deep-well installations. While still within the conceptual design phase of the MBM program, the SECARB Anthropogenic Test in Citronelle, Alabama, USA was identified as a deployment site for our engineered monitoring systems. The initial step in designing the Citronelle MBM system was to down-select from the various monitoring tools available to include technologies that we considered essential to any program. Monitoring methods selected included U-tube geochemical sampling, discrete quartz pressure and temperature gauges, an integrated fibre-optic bundle consisting of distributed temperature and heat-pulse sensing, and a sparse string of conventional 3C-geophones. While not originally planned within the initial MBM work scope, the fibre-optic cable was able to also be used for the emergent technology of distributed acoustic sensing. The MBM monitoring string was installed in March, 2012. To date, the Citronelle MBM instruments continue to operate reliably. Results and lessons learned from the Citronelle MBM deployment are addressed along with examples of data being collected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Modular evaluation method for subsurface activities (MEMSA). A novel approach for integrating social acceptance in a permit decision-making process for subsurface activities

We investigate how the decision support system ‘Modular Evaluation Method Subsurface Activities’ (MEMSA) can help facilitate an informed decision-making process for permit applications of subsurface activities. To this end, we analyze the extent the MEMSA approach allows for a dialogue between stakeholders in a transparent manner. We use the exploration permit for the underground gas storage facility at the Pieterburen salt dome (Netherlands) as a case study. The results suggest that the MEMSA approach is flexible enough to adjust to changing conditions. Furthermore, MEMSA provides a novel way for identifying structural problems and possible solutions in permit decision-making processes for subsurface activities, on the basis of the sensitivity analysis of intermediate rankings. We suggest that the planned size of an activity should already be specified in the exploration phase, because this would allow for a more efficient use of the subsurface as a whole. We conclude that the host community should be involved to a greater extent and in an early phase of the permit decision-making process, for example, already during the initial analysis of the project area of a subsurface activity. We suggest that strategic national policy goals are to be re-evaluated on a regular basis, in the form of a strategic vision for the subsurface, to account for timing discrepancies between the realization of activities and policy deadlines, because this discrepancy can have a large impact on the necessity and therefore acceptance of a subsurface activity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Implications of Small Modular Reactors for Climate Change Mitigation

Achieving climate policy targets will require large-scale deployment of low-carbon energy technologies, including nuclear power. The small modular reactor (SMR) is viewed as a possible solution to the problems of energy security as well as climate change. In this paper, we use an integrated assessment model (IAM) to investigate the evolution of a global energy portfolio with SMRs under a stringent climate policy. Technology selection in the model is based on costs; we use results from previous expert elicitation studies of SMR costs. We find that the costs of achieving a 2oC target are lower with SMRs than without. The costs are higher when large reactors do not compete for market share compared to a world in which they can compete freely. When both SMRs and large reactors compete for market share, reduction in mitigation cost is achieved only under advanced assumptions about SMR technology costs and future cost improvements. While the availability of SMRs could lower mitigation costs by a moderate amount, actual realization of these benefits would depend on the rapid up-scaling of SMRs in the near term. Such rapid deployment could be limited by several social, institutional and behavioral obstacles.

Iyer, Gokul C.↗
DOE OSTI2024

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Experimental and numerical studies of helium-cooled modular divertors with multiple jets

As part of the US-Japan PHENIX program, the helium-cooled modular divertor with multiple jets (HEMJ) and a simpler “flat” variant were experimentally studied in a closed helium loop with a redesigned test chamber at coolant inlet temperatures as great as 425 °C, incident heat fluxes as great as 2.2 MW/m 2 and prototypical inlet pressures of ~10 MPa. The data were used to develop correlations for the average Nusselt number and loss coefficient for a range of mass flow rates; these correlations were used in turn to predict the thermal-hydraulic performance of a single divertor module at prototypical conditions. The experimental results suggest that a flat jet array with six holes surrounding one central hole, all of the same diameter, can provide similar average heat transfer coefficients as the HEMJ divertor, albeit with higher pumping power requirements. Because of its smaller cooled surface area, however, this design has lower maximum allowable heat fluxes compared with the HEMJ divertor. Nevertheless, the flat variant could potentially simplify manufacturing and reduce the costs required to fabricate O(10 6 ) “finger” modules.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Estimation of the Thermal-Fluids and Thermal-Structural Performance of Helium-Cooled Modular Finger-Type Divertors

Over the past decade, our group has investigated the thermal-fluid performance of the helium-cooled modular divertor with multiple jets (HEMJ) and a simplified “flat” design of the HEMJ for long-pulse magnetic fusion energy (MFE) reactors. Experimental studies were performed in a helium (He) loop at the prototypical pressure of 10 MPa, nearly prototypical He temperatures and incident heat fluxes using test sections made from stainless steel and tungsten alloys. Correlations for average Nusselt numbers and pressure loss coefficients were developed from the data and are used to validate computational fluid dynamics (CFD) models. Here, this work presents updated thermal-fluids performance curves based on these correlations that estimate the maximum heat flux that can be accommodated by the plasma-facing surface and coolant pumping power requirements at prototypical operating conditions. Thermal-structural performance curves developed from ITER structural design criteria are introduced, which include protection against ductile and non-ductile failure, ratcheting fatigue, and creep fatigue. The performance design curves for these finger-type divertors demonstrate that the “flat” design, with a significantly less complicated geometry than the HEMJ, has thermal-fluid and thermal-structural performance comparable to the original HEMJ concept, and may be superior in terms of non-ductile failure criteria.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

State-of-the-art and review of condensation heat transfer for small modular reactor passive safety: Experimental studies

Here this study focused on state-of-the-art and review of condensation heat transfer for small modular reactors (SMR). Nuclear reactors adopt passive containment cooling systems (PCCS) for accident mitigation, containment integrity, and primarily to maintain the last barrier for radioactive particle release to the environment during and beyond design-basis accidents. However, improving the effectiveness of the PCCS is more critical for the SMR than for commercial reactors to ensure higher safety margins and compactness. In the PCCS of SMR, due to its smaller size containment, the filmwise condensation (FWC) is dominant. Therefore, this study emphasized the FWC. Earlier condensation studies for the PCCS did not make SMR the primary focus, so a critical review for formulating the state-of-the-art was necessary. Part-1 of this study covered the review of physics phenomena, previous experimental studies with a brief overview of associated test facilities and empirical correlations. This study identified a research gap with the condensation test data scaling relations by using the information and findings of the previous PCCS studies and applied them to the SMR system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steady-state fuel performance analyses for the preliminary fuel concept of general atomics fast modular reactor

Here this manuscript presents the fuel performance analysis results of the General Atomics Fast Modular Reactor (FMR) based on an axi-symmetric (2D-RZ) geometry. Three fuel performance model sets that fit the FMR fuel specifications best, i.e., a BISON baseline model set, a BISON diffusion enhancement model set, and a BISON-FASTGRASS model set, were identified and evaluated against a series of relevant experimental cases featuring high burnup and low irradiation temperature conditions. The three BISON-based model sets were then utilized to conduct a comprehensive fuel performance analysis of the FMR fuel under normal operation including the shutdown/restarting periods for refueling. The evaluation of the fuel performance parameters, represented by temperature, internal pressure, stress, and strain, shows that the FMR fuel maintains its thermal and mechanical integrity during normal operation. Technology gaps and limitations are also discussed to guide future efforts for extending the performance analysis to transient scenarios as well as improving the fuel performance evaluation through experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

First Results from the Modular Total Absorption Spectrometer at the HRIBF

A Modular Total Absorption Spectrometer constructed at the Holifield Radioactive Ion Beam Facility has been applied to decay studies of over 20 {sup 238}U fission products. The measurements were focused on nuclei identified as important for decay heat analysis during a nuclear fuel cycle. Preliminary results on the average electromagnetic (EM) energy release in the β decay of {sup 89}Kr and {sup 139}Xe isotopes yielded values of 2446 keV and 1126 keV, respectively. It represents an increase of over 35% and 20%, respectively, when compared to the average EM energies deduced using the ENSDF database.

43 PARTICLE ACCELERATORS↗