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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Incorporate MPACT into TIAMAT and Demonstrate Pellet-Clad Interactions (PCI) Calculations

CASL (the Consortium for Advanced Simulation of LWRs) is investing in the development of the multi-dimensional Bison fuel performance code for both transient and nominal performance analysis. The MPACT whole-core neutronics capability has been integrated with the Cobra-TF sub-channel solver to provide a neutron-transport based core-simulator with substantially improved fidelity over traditional diffusion-based core simulators. The Tiamat code is being developed to provide an integrated tool for predicting pellet-clad interaction and improving the high-fidelity core simulator.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Simulation-Based Assessment of Energy Consumption of Alternative Powertrains in Agricultural Tractors

The objectives of this research were to develop simulation models for agricultural tractors with different powertrain technologies and evaluate the energy consumption in typical agricultural operations. Simulation models were developed for conventional, parallel hybrid electric, series hybrid electric, fuel cell hybrid, and battery electric powertrains. Autonomie vehicle simulation software (version 2022) was used for the simulations and the tractor models were simulated in two tilling cycles and in a road transport cycle with a trailer. The alternative powertrains were configured to have at least the same tractive performance as the conventional, diesel engine-powered tractor model. The simulation results showed that the potential of the parallel and series hybrid powertrains to improve energy efficiency depends heavily on the tractor size and the operating cycle conditions. The fuel cell hybrid and battery electric powertrains have a higher potential to reduce energy consumption and emissions but still have inherent technical challenges for practical operation. The battery-powered electric tractor would require improvements in the storage energy density to have a comparable operational performance in comparison to other powertrains. The fuel cell hybrid tractor already provided an adequate operating performance but the availability of hydrogen and refueling infrastructure could be challenging to resolve in the farming context.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Simulated Fuel Economy and Emissions Performance during City and Interstate Driving for a Heavy-Duty Hybrid Truck

We compare simulated fuel economy and emissions for both conventional and hybrid class 8 heavy-duty diesel trucks operating over multiple urban and highway driving cycles. Both light and heavy freight loads were considered, and all simulations included full aftertreatment for NOx and particulate emissions controls. The aftertreatment components included a diesel oxidation catalyst (DOC), urea-selective catalytic NOx reduction (SCR), and a catalyzed diesel particulate filter (DPF). Our simulated hybrid powertrain was configured with a pre-transmission parallel drive, with a single electric motor between the clutch and gearbox. A conventional HD truck with equivalent diesel engine and aftertreatment was also simulated for comparison. Our results indicate that hybridization can significantly increase HD fuel economy and improve emissions control in city driving. However, there is less potential hybridization benefit for HD highway driving. A major factor behind the reduced hybridization benefit for highway driving is that there are fewer opportunities to utilize regenerative breaking. Our aftertreatment simulations indicate that opportunities for passive DPF regeneration are much greater for both hybrid and conventional trucks during highway driving due to higher sustained exhaust temperatures. When passive DPF regeneration is extensively utilized, the fuel penalty for particulate control is virtually eliminated, except for the 0.4%-0.9% fuel penalty associated with the slightly higher exhaust backpressure.

Daw, C. Stuart↗
DOE OSTI2012

NEAMS Software Licensing, Release, and Distribution: Implications for FY2013 Work Package Planning

The vision of the NEAMS program is to bring truly predictive modeling and simulation (M&S) capabilities to the nuclear engineering community in order to enable a new approach to the analysis of nuclear systems. NEAMS anticipates issuing in FY 2018 a full release of its computational 'Fermi Toolkit' aimed at advanced reactor and fuel cycles. The NEAMS toolkit involves extensive software development activities, some of which have already been underway for several years, however, the Advanced Modeling and Simulation Office (AMSO), which sponsors the NEAMS program, has not yet issued any official guidance regarding software licensing, release, and distribution policies. This motivated an FY12 task in the Capability Transfer work package to develop and recommend an appropriate set of policies. The current preliminary report is intended to provide awareness of issues with implications for work package planning for FY13. We anticipate a small amount of effort associated with putting into place formal licenses and contributor agreements for NEAMS software which doesn't already have them. We do not anticipate any additional effort or costs associated with software release procedures or schedules beyond those dictated by the quality expectations for the software. The largest potential costs we anticipate would be associated with the setup and maintenance of shared code repositories for development and early access to NEAMS software products. We also anticipate an opportunity, with modest associated costs, to work with the Radiation Safety Information Computational Center (RSICC) to clarify export control assessment policies for software under development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Systems Level Fuel Cycle Modeling in TMAP8 - A Demonstration

The tritium migration analysis program (TMAP) has been used for tritium inventory tracking and analysis for several years, and the Multiphysics Object Oriented Simulation Environment (MOOSE)-based TMAP8 has several improvements over TMAP4 and TMAP7, such as support for multiple dimensions and non-cartesian coordinate systems, as well as interoperability with sub-apps at higher and lower length scales. We demonstrate that TMAP8 has the additional capacity to solve systems-level problems using zero-dimensional ordinary differential equations by reproducing a literature model which describes a systems-level fuel-cycle of tritium inventory in a hypothetical fusion power plant. The capacity to run several coupled multi-scale physics calculations as part of a single package will be necessary for accurate blanket and fuel-cycle design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

New developments in ALCYONE 2.0 fuel performance code

ALCYONE is a multi-dimensional (1D, 2D or 3D) fuel performance code dedicated to pressurized water reactors (PWR). This code is co-developed in the PLEIADES platform by CEA, EDF and AREVA and simulates fuel pellets and cladding evolutions during base irradiation, power ramps and accidental situations. Sophisticated chemical and physical models are used. The thermal and mechanical behavior is solved with the finite element method based code CAST3M. ALCYONE 2.0 is the next release of the code and it includes several new features: improvements in incidental and accidental situations modeling, new models available for 2D and 3D schemes and an evolution of neutron model to simulate gadolinium fuel. ALCYONE 2.0 uses a new version of PLEIADES platform which allows the parallelized computation of rod axial slices in order to decrease computation times. To better simulate accidental situations, an axial transfer model for gases and a modeling of heaters for Loss Of Coolant Accident (LOCA) experiments have been added to the code. The axial transfer model can simulate an axial internal pressure gradient in the fuel rod. For power ramps simulations in the 1D scheme, a new model for dish filling is available. This version will be validated on more than 400 rods covering a wide range of irradiation conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

PCI analysis of a commercial PWR using BISON fuel performance code

Through the early 2000’s, nuclear fuel cladding failure resulting from pellet-cladding interaction in commercial pressurized water reactor fuel was managed successfully by incorporating power ramp restrictions. Within the past decade, however, cladding failures have again begun to appear, often correlated to missing pellet surface defects, and further aggravated by modern reactor operating strategies demanding higher fuel duty operations. In response, renewed efforts in fuel behavior modeling and simulation are being pursued to improve our understanding of the conditions that can lead to missing pellet surface related cladding failure. This paper describes a methodology used to model pellet-cladding interaction related failures observed in commercial pressurized water reactors using the BISON fuel performance code developed at Idaho National Laboratory. In order to accomplish this goal, a three-step process is followed: 1) A failure-stress threshold is developed by using BISON code to model ramp test with known pellet-clad interaction related failures, 2) BISON analysis is applied to a commercial pressurized water reactor cycle startup with one rod confirmed to contain a missing pellet surface defect, and 3) an missing pellet surface sensitivity study of a cycle startup of the same commercial pressurized water reactor which contained a failed fuel rod of un-identified type. The analysis results described in this paper serve to illustrate the BISON code capabilities for modeling pressurized water reactor fuel subjected to higher duty power events.

Nuclear Science & Technology↗
DOE OSTI2024

Determination of the Diffusion Coefficients of Binary CH4 and C2H6 in a Supercritical CO2 Environment (500–2000 K and 100–1000 atm) by Molecular Dynamics Simulations

The self-diffusion coefficients of carbonaceous fuels in a supercritical CO2 environment provide transport information that can help us understand the Allam Cycle mechanism at a high pressure of 300 atm. The diffusion coefficients of pure CO2 and binary CO2/CH4 and CO2/C2H6 at high temperatures (500 K~2000 K) and high pressures (100 atm~1000 atm) are determined by molecular dynamics simulations in this study. Increasing the temperature leads to an increase in the diffusion coefficient, and increasing the pressure leads to a decrease in the diffusion coefficients for both methane and ethane. The diffusion coefficient of methane at 300 atm is approximately 0.012 cm2/s at 1000 K and 0.032 cm2/s at 1500 K. The diffusion coefficient of ethane at 300 atm is approximately 0.016 cm2/s at 1000 K and 0.045 cm2/s at 1500 K. The understanding of diffusion coefficients potentially leads to the reduction in fuel consumption and minimization of greenhouse gas emissions in the Allam Cycle.

Energy & Fuels↗
DOE OSTI2024

Harvest Initiated Volatile Organic Compound Emissions from In-Field Tall Wheatgrass

While crop and grassland usage continues to increase, the full diversity of plant-specific volatile organic compounds (VOCs) emitted from these ecosystems, including their implications for atmospheric chemistry and carbon cycling, remains poorly understood. It is particularly important to investigate VOCs in the context of potential biofuels: aside from the implications of largescale land use, harvest may shift both the flux and speciation of emitted VOCs. To this point, we evaluate the diversity of VOCs emitted both pre and postharvest from “Alkar” tall wheatgrass (Thinopyrum ponticum), a candidate biofuel that exhibits greater tolerance to frost and saline land compared to other grass varieties. Mature plants grown under field conditions (n = 6) were sampled for VOCs both pre- and postharvest (October 2022). Via hierarchical clustering of emitted VOCs from each plant, we observe distinct “volatilomes” (diversity of VOCs) specific to the pre- and postharvest conditions despite plant-to-plant variability. In total, 50 VOCs were found to be unique to the postharvest tall wheatgrass volatilome, and these unique VOCs constituted a significant portion (26%) of total postharvest signal. While green leaf volatiles (GLVs) dominate the speciation of postharvest emissions (e.g., 54% of unique postharvest VOC signal was due to 1-penten-3-ol), we demonstrate novel postharvest VOCs from tall wheatgrass that are under characterized in the context of carbon cycling and atmospheric chemistry (e.g., 3-octanone). Continuing evaluations will quantitatively investigate tall wheatgrass VOC fluxes, better informing the feasibility and environmental impact of tall wheatgrass as a biofuel.

09 BIOMASS FUELS↗
DOE OSTI2013

Impact of advanced fuel cycles on uncertainty associated with geologic repositories

This paper provides a qualitative evaluation of the impact of advanced fuel cycles, particularly partition and transmutation of actinides, on the uncertainty associated with geologic disposal. Based on the discussion, advanced fuel cycles, will not materially alter (1) the repository performance (2) the spread in dose results around the mean (3) the modeling effort to include significant features, events, and processes in the performance assessment, or (4) the characterization of uncertainty associated with a geologic disposal system in the regulatory environment of the United States. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

Non-Ideal Behavior in Solvent Extraction

This report presents a summary of the work performed to meet FCR&D level 3 milestone M31SW050801, 'Complete the year-end report summarizing FY11 experimental and modeling activities.' This work was carried out under the auspices of the Non-Ideality in Solvent Extraction Systems FCR&D work package. The report summarizes our initial considerations of potential influences that non-ideal chemistry may impose on computational prediction of outcomes in solvent extraction systems. The report is packaged into three separate test cases where a robustness of the prediction by SXFIT program is under scrutiny. The computational exercises presented here emphasize the importance of accurate representation of both an aqueous and organic mixtures when modeling liquid-liquid distribution systems. Case No.1 demonstrates that non-ideal behavior of HDEHP in aliphatic diluents, such as n-dodecane, interferes with the computation. Cases No.2 and No.3 focus on the chemical complexity of aqueous electrolyte mixtures. Both exercises stress the need for an improved thermodynamic model of an aqueous environment present in the europium distribution experiments. Our efforts for year 2 of this project will focus on the improvements of aqueous and non-aqueous solution models using fundamental physical properties of mixtures acquired experimentally in our laboratories.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2012

Efficient Computation of Info-Gap Robustness for Finite Element Models

A recent research effort at LANL proposed info-gap decision theory as a framework by which to measure the predictive maturity of numerical models. Info-gap theory explores the trade-offs between accuracy, that is, the extent to which predictions reproduce the physical measurements, and robustness, that is, the extent to which predictions are insensitive to modeling assumptions. Both accuracy and robustness are necessary to demonstrate predictive maturity. However, conducting an info-gap analysis can present a formidable challenge, from the standpoint of the required computational resources. This is because a robustness function requires the resolution of multiple optimization problems. This report offers an alternative, adjoint methodology to assess the info-gap robustness of Ax = b-like numerical models solved for a solution x. Two situations that can arise in structural analysis and design are briefly described and contextualized within the info-gap decision theory framework. The treatments of the info-gap problems, using the adjoint methodology are outlined in detail, and the latter problem is solved for four separate finite element models. As compared to statistical sampling, the proposed methodology offers highly accurate approximations of info-gap robustness functions for the finite element models considered in the report, at a small fraction of the computational cost. It is noted that this report considers only linear systems; a natural follow-on study would extend the methodologies described herein to include nonlinear systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Benchmarking Data for the Proposed Signature of Used Fuel Casks

A set of benchmarking measurements to test facets of the proposed extended storage signature was conducted on May 17, 2016. The measurements were designed to test the overall concept of how the proposed signature can be used to identify a used fuel cask based only on the distribution of neutron sources within the cask. To simulate the distribution, 4 Cf-252 sources were chosen and arranged on a 3x3 grid in 3 different patterns and raw neutron totals counts were taken at 6 locations around the grid. This is a very simplified test of the typical geometry studied previously in simulation with simulated used nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Development of a RIA Experimental Benchmark for BISON

This milestone report documents FY-17 efforts for the Reactivity Initiated Accident (RIA) Challenge Problem to demonstrate PWR RIA Fuel Performance capability. The challenge problem implementation plan identified a series of experimental comparisons to validate RIA capability in BISON. The specific cases chosen for FY-17 are CABRI REP Na-2, 3, 5, and 10. Work was also performed on the Nuclear Safety Research Reactor (NSRR) FK-1, 2, 3, 4, 5, 6, 7, 8, and 9 cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Introduction of plutonium systems to the nuclear criticality slide rule

AWE (UK), IRSN (France), LLNL (USA) and ORNL (USA) began a long term collaboration effort in 2015 to update the nuclear criticality Slide Rule for the emergency response to a nuclear criticality accident. This document, published almost 20 years ago, gives order of magnitude estimates of key parameters, such as number of fissions and doses (neutron/gamma), useful for emergency response teams and public authorities. This paper presents, firstly, the motivation and the long term objectives for this update, then it introduces the initial critical configuration, and finally it presents the preliminary results obtained with modern 3D radiation transport codes and nuclear data for new configurations including plutonium systems. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗